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Goldsmith GR, Aiken ML, Camarillo-Abad HM, Diki K, Gardner DL, Stipčić M, Espeleta JF. Overcoming the Barriers to Teaching Teamwork to Undergraduates in STEM. CBE Life Sci Educ 2024; 23:es2. [PMID: 38442149 DOI: 10.1187/cbe.23-07-0128] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/07/2024]
Abstract
There is widespread recognition that undergraduate students in the life sciences must learn how to work in teams. However, instructors who wish to incorporate teamwork into their classrooms rarely have formal training in how to teach teamwork. This is further complicated by the application of synonymous and often ambiguous terminology regarding teamwork that is found in literature spread among many different disciplines. There are significant barriers for instructors wishing to identify and implement best practices. We synthesize key concepts in teamwork by considering the knowledge, skills, and attitudes (KSAs) necessary for success, the pedagogies and curricula for teaching those KSAs, and the instruments available for evaluating and assessing success. There are only a limited number of studies on teamwork in higher education that present an intervention with a control group and a formal evaluation or assessment. Moreover, these studies are almost exclusively outside STEM disciplines, raising questions about their extensibility. We conclude by considering how to build an evidence base for instruction that will empower students with the KSAs necessary for participating in a lifetime of equitable and inclusive teamwork.
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Affiliation(s)
| | - Miranda L Aiken
- Grand Challenges Initiative, Chapman University, Orange, CA 92866
| | | | - Kamal Diki
- Grand Challenges Initiative, Chapman University, Orange, CA 92866
| | - Daniel L Gardner
- Grand Challenges Initiative, Chapman University, Orange, CA 92866
| | - Mario Stipčić
- Grand Challenges Initiative, Chapman University, Orange, CA 92866
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2
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Huang L, Peng Z, Chen F, Dai S, He Z, Liu K. Cross-modality interaction for few-shot multispectral object detection with semantic knowledge. Neural Netw 2024; 173:106156. [PMID: 38340468 DOI: 10.1016/j.neunet.2024.106156] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Revised: 12/19/2023] [Accepted: 01/31/2024] [Indexed: 02/12/2024]
Abstract
Multispectral object detection (MOD), which incorporates additional information from thermal images into object detection (OD) to robustly cope with complex illumination conditions, has garnered significant attention. However, existing MOD methods always demand a considerable amount of annotated data for training. Inspired by the concept of few-shot learning, we propose a novel task called few-shot multispectral object detection (FSMOD) that aims to accomplish MOD using only a few annotated data from each category. Specifically, we first design a cross-modality interaction (CMI) module, which leverages different attention mechanisms to interact with the information from visible and thermal modalities during backbone feature extraction. With the guidance of interaction process, the detector is able to extract modality-specific backbone features with better discrimination. To improve the few-shot learning ability of the detector, we also design a semantic prototype metric (SPM) loss that integrates semantic knowledge, i.e., word embeddings, into the optimization process of embedding space. Semantic knowledge provides stable category representation when visual information is insufficient. Extensive experiments on the customized FSMOD dataset demonstrate that the proposed method achieves state-of-the-art performance.
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Affiliation(s)
- Lian Huang
- School of Electrical and Electronic Engineering, Chongqing University of Technology, Chongqing, 400054, China.
| | - Zongju Peng
- School of Electrical and Electronic Engineering, Chongqing University of Technology, Chongqing, 400054, China.
| | - Fen Chen
- School of Electrical and Electronic Engineering, Chongqing University of Technology, Chongqing, 400054, China.
| | - Shaosheng Dai
- School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China.
| | - Ziqiang He
- School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China.
| | - Kesheng Liu
- School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China.
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3
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Holmes CA, Cooney SM, Dempsey P, Newell FN. Developmental changes in the visual, haptic, and bimodal perception of geometric angles. J Exp Child Psychol 2024; 241:105870. [PMID: 38354447 DOI: 10.1016/j.jecp.2024.105870] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 01/11/2024] [Accepted: 01/12/2024] [Indexed: 02/16/2024]
Abstract
Geometrical knowledge is typically taught to children through a combination of vision and repetitive drawing (i.e. haptics), yet our understanding of how different spatial senses contribute to geometric perception during childhood is poor. Studies of line orientation suggest a dominant role of vision affecting the calibration of haptics during development; however, the associated multisensory interactions underpinning angle perception are unknown. Here we examined visual, haptic, and bimodal perception of angles across three age groups of children: 6 to 8 years, 8 to 10 years, and 10 to 12 years, with age categories also representing their class (grade) in primary school. All participants first learned an angular shape, presented dynamically, in one of three sensory tracing conditions: visual only, haptic only, or bimodal exploration. At test, which was visual only, participants selected a target angle from four possible alternatives with distractor angle sizes varying relative to the target angle size. We found a clear improvement in accuracy of angle perception with development for all learning modalities. Angle perception in the youngest group was equally poor (but above chance) for all modalities; however, for the two older child groups, visual learning was better than haptics. Haptic perception did not improve to the level of vision with age (even in a comparison adult group), and we found no specific benefit for bimodal learning over visual learning in any age group, including adults. Our results support a developmental increment in both spatial accuracy and precision in all modalities, which was greater in vision than in haptics, and are consistent with previous accounts of cross-sensory calibration in the perception of geometric forms.
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Affiliation(s)
- Corinne A Holmes
- School of Psychology and Institute of Neuroscience, Trinity College Dublin, College Green, Dublin 2, Ireland
| | - Sarah M Cooney
- School of Psychology and Institute of Neuroscience, Trinity College Dublin, College Green, Dublin 2, Ireland; School of Psychology, University College Dublin, Belfield, Dublin 4, Ireland
| | - Paula Dempsey
- School of Psychology and Institute of Neuroscience, Trinity College Dublin, College Green, Dublin 2, Ireland
| | - Fiona N Newell
- School of Psychology and Institute of Neuroscience, Trinity College Dublin, College Green, Dublin 2, Ireland; Department of Psychology, New York University Abu Dhabi, United Arab Emirates.
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4
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Jiang S, Chen Q, Xiang Y, Pan Y, Wu X, Lin Y. Confounder balancing in adversarial domain adaptation for pre-trained large models fine-tuning. Neural Netw 2024; 173:106173. [PMID: 38387200 DOI: 10.1016/j.neunet.2024.106173] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 01/07/2024] [Accepted: 02/08/2024] [Indexed: 02/24/2024]
Abstract
The excellent generalization, contextual learning, and emergence abilities in the pre-trained large models (PLMs) handle specific tasks without direct training data, making them the better foundation models in the adversarial domain adaptation (ADA) methods to transfer knowledge learned from the source domain to target domains. However, existing ADA methods fail to account for the confounder properly, which is the root cause of the source data distribution that differs from the target domains. This study proposes a confounder balancing method in adversarial domain adaptation for PLMs fine-tuning (CadaFT), which includes a PLM as the foundation model for a feature extractor, a domain classifier and a confounder classifier, and they are jointly trained with an adversarial loss. This loss is designed to improve the domain-invariant representation learning by diluting the discrimination in the domain classifier. At the same time, the adversarial loss also balances the confounder distribution among source and unmeasured domains in training. Compared to newest ADA methods, CadaFT can correctly identify confounders in domain-invariant features, thereby eliminating the confounder biases in the extracted features from PLMs. The confounder classifier in CadaFT is designed as a plug-and-play and can be applied in the confounder measurable, unmeasurable, or partially measurable environments. Empirical results on natural language processing and computer vision downstream tasks show that CadaFT outperforms the newest GPT-4, LLaMA2, ViT and ADA methods.
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Affiliation(s)
- Shuoran Jiang
- Haibin Institute of Technology, ShenZhen, Harbin Institute of Technology campus, Taoyuan Street, Nanshan District, Shenzhen, 518055, GuangDong, China
| | - Qingcai Chen
- Haibin Institute of Technology, ShenZhen, Harbin Institute of Technology campus, Taoyuan Street, Nanshan District, Shenzhen, 518055, GuangDong, China; Peng Cheng Laboratory, No. 2, Xingke 1st Street, Nanshan District, Shenzhen, 518055, Guangdong, China.
| | - Yang Xiang
- Peng Cheng Laboratory, No. 2, Xingke 1st Street, Nanshan District, Shenzhen, 518055, Guangdong, China.
| | - Youcheng Pan
- Peng Cheng Laboratory, No. 2, Xingke 1st Street, Nanshan District, Shenzhen, 518055, Guangdong, China
| | - Xiangping Wu
- Haibin Institute of Technology, ShenZhen, Harbin Institute of Technology campus, Taoyuan Street, Nanshan District, Shenzhen, 518055, GuangDong, China
| | - Yukang Lin
- Haibin Institute of Technology, ShenZhen, Harbin Institute of Technology campus, Taoyuan Street, Nanshan District, Shenzhen, 518055, GuangDong, China
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5
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Wang H, Wu C, Zheng K. Defense against adversarial attacks based on color space transformation. Neural Netw 2024; 173:106176. [PMID: 38402810 DOI: 10.1016/j.neunet.2024.106176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Revised: 12/26/2023] [Accepted: 02/10/2024] [Indexed: 02/27/2024]
Abstract
Deep Learning algorithms have achieved state-of-the-art performance in various important tasks. However, recent studies have found that an elaborate perturbation may cause a network to misclassify, which is known as an adversarial attack. Based on current research, it is suggested that adversarial examples cannot be eliminated completely. Consequently, it is always possible to determine an attack that is effective against a defense model. We render existing adversarial examples invalid by altering the classification boundaries. Meanwhile, for valid adversarial examples generated against the defense model, the adversarial perturbations are increased so that they can be distinguished by the human eye. This paper proposes a method for implementing the abovementioned concepts through color space transformation. Experiments on CIFAR-10, CIFAR-100, and Mini-ImageNet demonstrate the effectiveness and versatility of our defense method. To the best of our knowledge, this is the first defense model based on the amplification of adversarial perturbations.
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Affiliation(s)
- Haoyu Wang
- School of Cyberspace Security, Beijing University of Posts and Telecommunications, China
| | - Chunhua Wu
- School of Cyberspace Security, Beijing University of Posts and Telecommunications, China.
| | - Kangfeng Zheng
- School of Cyberspace Security, Beijing University of Posts and Telecommunications, China
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6
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Xue G, Zhong M, Qian T, Li J. PSA-GNN: An augmented GNN framework with priori subgraph knowledge. Neural Netw 2024; 173:106155. [PMID: 38335793 DOI: 10.1016/j.neunet.2024.106155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Revised: 12/13/2023] [Accepted: 01/29/2024] [Indexed: 02/12/2024]
Abstract
Graph neural networks have become the primary graph representation learning paradigm, in which nodes update their embeddings by aggregating messages from their neighbors iteratively. However, current message passing based GNNs exploit the higher-order subgraph information other than 1st-order neighbors insufficiently. In contrast, the long-standing graph research has investigated various subgraphs such as motif, clique, core, and truss that contain important structural information to downstream tasks like node classification, which deserve to be preserved by GNNs. In this work, we propose to use the pre-mined subgraphs as priori knowledge to extend the receptive field of GNNs and enhance their expressive power to go beyond the 1st-order Weisfeiler-Lehman isomorphism test. For that, we introduce a general framework called PSA-GNN (Priori Subgraph Augmented Graph Neural Network), which augments each GNN layer by a pair of parallel convolution layers based on a bipartite graph between nodes and priori subgraphs. PSA-GNN intrinsically builds a hybrid receptive field by incorporating priori subgraphs as neighbors, while the embeddings and weights of subgraphs are trainable. Moreover, PSA-GNN can purify the noisy subgraphs both heuristically before training and deterministically during training based on a novel metric called homogeneity. Experimental results show that PSA-GNN achieves an improved performance compared with state-of-the-art message passing based GNN models.
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Affiliation(s)
- Guotong Xue
- School of Computer Science, Wuhan University, Wuhan, China
| | - Ming Zhong
- School of Computer Science, Wuhan University, Wuhan, China.
| | - Tieyun Qian
- School of Computer Science, Wuhan University, Wuhan, China
| | - Jianxin Li
- School of Information Technology, Deakin University, Burwood, Australia
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7
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Sun G, Ji B, Liang L, Chen M. CeCR: Cross-entropy contrastive replay for online class-incremental continual learning. Neural Netw 2024; 173:106163. [PMID: 38430638 DOI: 10.1016/j.neunet.2024.106163] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 12/07/2023] [Accepted: 02/02/2024] [Indexed: 03/05/2024]
Abstract
Aiming at the realization of learning continually from an online data stream, replay-based methods have shown superior potential. The main challenge of replay-based methods is the selection of representative samples which are stored in the buffer and replayed. In this paper, we propose the Cross-entropy Contrastive Replay (CeCR) method in the online class-incremental setting. First, we present the Class-focused Memory Retrieval method that proceeds the class-level sampling without replacement. Second, we put forward the class-mean approximation memory update method that selectively replaces the mistakenly classified training samples with samples of current input batch. In addition, the Cross-entropy Contrastive Loss is proposed to implement the model training with obtaining more solid knowledge to achieve effective learning. Experiments show that the CeCR method has comparable or improved performance in two benchmark datasets in comparison with the state-of-the-art methods.
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Affiliation(s)
- Guanglu Sun
- School of Computer Science and Technology, Harbin University of Science and Technology, Harbin 150080, China.
| | - Baolun Ji
- School of Computer Science and Technology, Harbin University of Science and Technology, Harbin 150080, China.
| | - Lili Liang
- School of Computer Science and Technology, Harbin University of Science and Technology, Harbin 150080, China.
| | - Minghui Chen
- School of Computer Science and Technology, Harbin University of Science and Technology, Harbin 150080, China.
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8
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Fast AA, Riggs AE. Preschoolers negatively evaluate conventional norm violations in pretend play. J Exp Child Psychol 2024; 241:105861. [PMID: 38354448 DOI: 10.1016/j.jecp.2024.105861] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Revised: 01/02/2024] [Accepted: 01/03/2024] [Indexed: 02/16/2024]
Abstract
A growing body of research demonstrates that children's pretend play is largely influenced by their understanding of reality. The current work took a novel approach to testing children's understanding of pretense by investigating whether children apply and uphold their knowledge of conventional norms in pretend play. In this study, 3- to 5-year-old children (N = 200) were introduced to a series of pretend play scenarios (e.g., pretending to eat breakfast) in which a puppet pretended to follow a norm (e.g., pretended to eat cereal for breakfast) or violate a norm (e.g., pretended to eat a hamburger for breakfast). These pretend play scenarios were presented as either fantastical or realistic in nature. Consistent with our hypotheses, children evaluated pretend norm violation more negatively than pretend norm adherence and reported liking norm violators less than norm followers. Contrary to our hypothesis, the manipulation of play context (fantastical vs. realistic) did not affect children's evaluations. That is, children were just as negative about pretend norm violations (relative to pretend norm adherence) in fantastical pretend play scenarios as they were in realistic pretend play scenarios. Furthermore, individual differences in children's fantasy orientation did not predict their evaluations. This study is the first to establish that children maintain their real-world understanding of conventional norms in pretend play, providing further evidence that children's pretense is largely realistic in nature.
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Affiliation(s)
- Anne A Fast
- Department of Psychology, Western Washington University, Bellingham, WA 98225, USA.
| | - Anne E Riggs
- Department of Psychology, Western Washington University, Bellingham, WA 98225, USA.
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9
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Tian J, Han D, Karimi HR, Zhang Y, Shi P. A universal multi-source domain adaptation method with unsupervised clustering for mechanical fault diagnosis under incomplete data. Neural Netw 2024; 173:106167. [PMID: 38359643 DOI: 10.1016/j.neunet.2024.106167] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 11/17/2023] [Accepted: 02/06/2024] [Indexed: 02/17/2024]
Abstract
Recently, due to the difficulty of collecting condition data covering all mechanical fault types in industrial scenarios, the fault diagnosis problem under incomplete data is receiving increasing attention where no target prior information can be available. The existing open-set or universal domain adaptation (DA) diagnosis methods typically treat private fault samples in the target as a generalized "unknown" fault class, neglecting their inherent structure. This oversight can lead to confusion in latent feature space representations and difficulties in separating unknown samples. Therefore, a universal DA method with unsupervised clustering is developed to explore the intrinsic structure of the target samples for mechanical fault diagnosis, where multi-source information on different working conditions is considered to transfer complementary knowledge. First, a composite clustering metric combining single-domain and cross-domain evaluation is constructed to recognize shared and unknown health classes on source-target domains. Second, to alleviate the intra-class shift while enlarging the inter-class gap, a class-wise DA algorithm is suggested which operates on the basis of maximum mean discrepancy. Finally, an entropy regularization criterion is utilized to facilitate clustering of different health classes. The efficacy of the presented approach in the fault diagnosis issues when monitoring data is inadequate has been verified through extensive experiments on three rotating machinery datasets.
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Affiliation(s)
- Jinghui Tian
- School of Vehicles and Energy, Yanshan University, Qinhuangdao, Hebei 066004, PR China
| | - Dongying Han
- School of Vehicles and Energy, Yanshan University, Qinhuangdao, Hebei 066004, PR China.
| | - Hamid Reza Karimi
- Department of Mechanical Engineering, Politecnico di Milano, 20156 Milan, Italy
| | - Yu Zhang
- School of Vehicles and Energy, Yanshan University, Qinhuangdao, Hebei 066004, PR China
| | - Peiming Shi
- School of Electrical Engineering, Yanshan University, Qinhuangdao, Hebei 066004, PR China
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10
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Romanova A, Rubinelli S, Diviani N. Improving health and scientific literacy in disadvantaged groups: A scoping review of interventions. Patient Educ Couns 2024; 122:108168. [PMID: 38301598 DOI: 10.1016/j.pec.2024.108168] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Revised: 12/05/2023] [Accepted: 01/21/2024] [Indexed: 02/03/2024]
Abstract
OBJECTIVE To explore approaches for developing and implementing interventions aimed at improving health literacy and health-related scientific literacy in disadvantaged groups. METHODS A scoping review of literature published in 2012-2022 was conducted, followed by quality appraisal of eligible studies. RESULTS Interventions were conducted mainly in community settings, where the most popular venues were adult education facilities. The primary target groups were those with limited income or education, ethnic minorities, or immigrants. Programs were often held in-person using interactive and culturally appropriate methods. They were predominantly focused on functional and interactive health literacy dimensions rather than on critical and scientific ones. Evaluations measured knowledge, health literacy, behavioral and psychological outcomes using various quantitative and qualitative instruments. CONCLUSIONS The findings offer a comprehensive overview of the ways to design and evaluate health and scientific literacy interventions tailored to disadvantaged groups. PRACTICE IMPLICATIONS Future interventions should prioritize participatory designs, culturally appropriate materials, and shift focus to critical and scientific health literacy, as well as to program scalability in less controlled conditions.
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Affiliation(s)
- Anna Romanova
- Faculty of Health Sciences and Medicine, University of Lucerne, Alpenquai 4, 6005 Luzern, Switzerland; Swiss Paraplegic Research, Person-Centered Healthcare & Health Communication Group, Guido A, Zäch-Strasse 4, 6207 Nottwil, Switzerland
| | - Sara Rubinelli
- Faculty of Health Sciences and Medicine, University of Lucerne, Alpenquai 4, 6005 Luzern, Switzerland; Swiss Paraplegic Research, Person-Centered Healthcare & Health Communication Group, Guido A, Zäch-Strasse 4, 6207 Nottwil, Switzerland
| | - Nicola Diviani
- Faculty of Health Sciences and Medicine, University of Lucerne, Alpenquai 4, 6005 Luzern, Switzerland; Swiss Paraplegic Research, Person-Centered Healthcare & Health Communication Group, Guido A, Zäch-Strasse 4, 6207 Nottwil, Switzerland.
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11
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Zhang R, Wen X, Cao H, Cui P, Chai H, Hu R, Yu R. High-risk event prone driver identification considering driving behavior temporal covariate shift. Accid Anal Prev 2024; 199:107526. [PMID: 38432064 DOI: 10.1016/j.aap.2024.107526] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Revised: 02/15/2024] [Accepted: 02/25/2024] [Indexed: 03/05/2024]
Abstract
Drivers who perform frequent high-risk events (e.g., hard braking maneuvers) pose a significant threat to traffic safety. Existing studies commonly estimated high-risk event occurrence probabilities based upon the assumption that data collected from different time periods are independent and identically distributed (referred to as i.i.d. assumption). Such approach ignored the issue of driving behavior temporal covariate shift, where the distributions of driving behavior factors vary over time. To fill the gap, this study targets at obtaining time-invariant driving behavior features and establishing their relationships with high-risk event occurrence probability. Specifically, a generalized modeling framework consisting of distribution characterization (DC) and distribution matching (DM) modules was proposed. The DC module split the whole dataset into several segments with the largest distribution gaps, while the DM module identified time-invariant driving behavior features through learning common knowledge among different segments. Then, gated recurrent unit (GRU) was employed to conduct time-invariant driving behavior feature mining for high-risk event occurrence probability estimation. Moreover, modified loss functions were introduced for imbalanced data learning caused by the rarity of high-risk events. The empirical analyses were conducted utilizing online ride-hailing services data. Experiment results showed that the proposed generalized modeling framework provided a 7.2% higher average precision compared to the traditional i.i.d. assumption based approach. The modified loss functions further improved the model performance by 3.8%. Finally, benefits for the driver management program improvement have been explored by a case study, demonstrating a 33.34% enhancement in the identification precision of high-risk event prone drivers.
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Affiliation(s)
- Ruici Zhang
- College of Transportation Engineering, Tongji University, Shanghai, 201804, China; The Key Laboratory of Road and Traffic Engineering, Ministry of Education, 4800 Cao'an Road, 201804, Shanghai, China.
| | - Xiang Wen
- Didi Chuxing, Zuanshi Mansion, Zhongguancun Software Park Compound 19, Dongbeiwang Road, 100000, Beijing, China.
| | - Huanqiang Cao
- Didi Chuxing, Zuanshi Mansion, Zhongguancun Software Park Compound 19, Dongbeiwang Road, 100000, Beijing, China.
| | - Pengfei Cui
- Didi Chuxing, Zuanshi Mansion, Zhongguancun Software Park Compound 19, Dongbeiwang Road, 100000, Beijing, China.
| | - Hua Chai
- Didi Chuxing, Zuanshi Mansion, Zhongguancun Software Park Compound 19, Dongbeiwang Road, 100000, Beijing, China.
| | - Runbo Hu
- Didi Chuxing, Zuanshi Mansion, Zhongguancun Software Park Compound 19, Dongbeiwang Road, 100000, Beijing, China.
| | - Rongjie Yu
- College of Transportation Engineering, Tongji University, Shanghai, 201804, China; The Key Laboratory of Road and Traffic Engineering, Ministry of Education, 4800 Cao'an Road, 201804, Shanghai, China.
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12
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Li H, Chen X, Ditzler G, Roveda J, Li A. Knowledge distillation under ideal joint classifier assumption. Neural Netw 2024; 173:106160. [PMID: 38330746 PMCID: PMC10961204 DOI: 10.1016/j.neunet.2024.106160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Revised: 12/05/2023] [Accepted: 02/01/2024] [Indexed: 02/10/2024]
Abstract
Knowledge distillation constitutes a potent methodology for condensing substantial neural networks into more compact and efficient counterparts. Within this context, softmax regression representation learning serves as a widely embraced approach, leveraging a pre-established teacher network to guide the learning process of a diminutive student network. Notably, despite the extensive inquiry into the efficacy of softmax regression representation learning, the intricate underpinnings governing the knowledge transfer mechanism remain inadequately elucidated. This study introduces the 'Ideal Joint Classifier Knowledge Distillation' (IJCKD) framework, an overarching paradigm that not only furnishes a lucid and exhaustive comprehension of prevailing knowledge distillation techniques but also establishes a theoretical underpinning for prospective investigations. Employing mathematical methodologies derived from domain adaptation theory, this investigation conducts a comprehensive examination of the error boundary of the student network contingent upon the teacher network. Consequently, our framework facilitates efficient knowledge transference between teacher and student networks, thereby accommodating a diverse spectrum of applications.
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Affiliation(s)
- Huayu Li
- Department of Electrical & Computer Engineering at the University of Arizona, Tucson, 85721, AZ, USA
| | - Xiwen Chen
- School of Computing at Clemson University, Clemson, 29634, SC, USA
| | | | - Janet Roveda
- Department of Electrical & Computer Engineering at the University of Arizona, Tucson, 85721, AZ, USA; Department of Biomedical Engineering, The University of Arizona, Tucson, 85721, AZ, USA; BIO5 Institute, The University of Arizona, Tucson, 85721, AZ, USA
| | - Ao Li
- Department of Electrical & Computer Engineering at the University of Arizona, Tucson, 85721, AZ, USA; BIO5 Institute, The University of Arizona, Tucson, 85721, AZ, USA.
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13
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Zhou Y, Zhu C, Zhu W, Li H. SCMEA: A stacked co-enhanced model for entity alignment based on multi-aspect information fusion and bidirectional contrastive learning. Neural Netw 2024; 173:106178. [PMID: 38367354 DOI: 10.1016/j.neunet.2024.106178] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Revised: 10/31/2023] [Accepted: 02/13/2024] [Indexed: 02/19/2024]
Abstract
Entity alignment refers to discovering the entity pairs with the same realistic meaning in different knowledge graphs. This technology is of great significance for completing and fusing knowledge graphs. Recently, methods based on knowledge representation learning have achieved remarkable achievements in entity alignment. However, most existing approaches do not mine hidden information in the knowledge graph as much as possible. This paper suggests SCMEA, a novel cross-lingual entity alignment framework based on multi-aspect information fusion and bidirectional contrastive learning. SCMEA initially adopts diverse representation learning models to embed multi-aspect information of entities and integrates them into a unified embedding space with an adaptive weighted mechanism to overcome the missing information and the problem of different-aspect information are not uniform. Then, we propose a stacked relation-entity co-enhanced model to further improve the representations of entities, wherein relation representation is modeled using an Entity Collector with Global Entity Attention. Finally, a combined loss function based on improved bidirectional contrastive learning is introduced to optimize model parameters and entity representation, effectively mitigating the hubness problem and accelerating model convergence. We conduct extensive experiments to evaluate the alignment performance of SCMEA. The overall experimental results, ablation studies, and analysis performed on five cross-lingual datasets demonstrate that our model achieves varying degrees of performance improvement and verifies the effectiveness and robustness of the model.
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Affiliation(s)
- Yunfeng Zhou
- Faculty of Information Technology, Beijing University of Technology, Beijing, 100020, China.
| | - Cui Zhu
- Faculty of Information Technology, Beijing University of Technology, Beijing, 100020, China.
| | - Wenjun Zhu
- Faculty of Information Technology, Beijing University of Technology, Beijing, 100020, China.
| | - Hongyang Li
- Faculty of Information Technology, Beijing University of Technology, Beijing, 100020, China.
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14
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Li Q, Wang Y, Dong J, Zhang C, Peng K. Multi-node knowledge graph assisted distributed fault detection for large-scale industrial processes based on graph attention network and bidirectional LSTMs. Neural Netw 2024; 173:106210. [PMID: 38417353 DOI: 10.1016/j.neunet.2024.106210] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Revised: 01/29/2024] [Accepted: 02/23/2024] [Indexed: 03/01/2024]
Abstract
Modern industrial processes are characterized by extensive, multiple operation units, and strong coupled correlation of subsystems. Fault detection of large-scale processes is still a challenging problem, especially for tandem plant-wide processes in multiple fields such as water treatment process. In this paper, a novel distributed graph attention network-bidirectional long short-term memory (D-GATBLSTM) fault detection model is proposed for large-scale industrial processes. Firstly, a multi-node knowledge graph (MNKG) is constructed using a joint data and knowledge driven strategy. Secondly, for large-scale industrial process, a global feature extractor of graph attention networks (GATs) is constructed, on the basis of which, sub-blocks are decomposed based on MNKG. Then, local feature extractors of bidirectional long short-term memory (Bi-LSTM) for each sub-block are constructed, in which correlations among multiple sub-blocks are considered. Finally, a multi-subblock fusion collaborative prediction model is constructed and the comprehensive fault detection results are given by the grid search method. The effectiveness of our D-GATBLSTM is exemplified in a secure water treatment process case, where it outperforms baseline models compared, with 27% improvement in precision, 15% increase in recall, and overall F-score enhancement of 0.22.
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Affiliation(s)
- Qing Li
- Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, University of Science and Technology Beijing, Beijing, 100083, PR China; School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, 100083, PR China
| | - Yangfan Wang
- School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, 100083, PR China
| | - Jie Dong
- Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, University of Science and Technology Beijing, Beijing, 100083, PR China; School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, 100083, PR China; National Engineering Research Center for Advanced Rolling and Intelligent Manufacturing, University of Science and Technology Beijing, Beijing, 100083, PR China
| | - Chi Zhang
- School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, 100083, PR China
| | - Kaixiang Peng
- Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, University of Science and Technology Beijing, Beijing, 100083, PR China; School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, 100083, PR China; National Engineering Research Center for Advanced Rolling and Intelligent Manufacturing, University of Science and Technology Beijing, Beijing, 100083, PR China.
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15
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Zhang Z, Lu Y, Wang T, Wei X, Wei Z. DDK: Dynamic structure pruning based on differentiable search and recursive knowledge distillation for BERT. Neural Netw 2024; 173:106164. [PMID: 38367353 DOI: 10.1016/j.neunet.2024.106164] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Revised: 02/01/2024] [Accepted: 02/03/2024] [Indexed: 02/19/2024]
Abstract
Large-scale pre-trained models, such as BERT, have demonstrated outstanding performance in Natural Language Processing (NLP). Nevertheless, the high number of parameters in these models has increased the demand for hardware storage and computational resources while posing a challenge for their practical deployment. In this article, we propose a combined method of model pruning and knowledge distillation to compress and accelerate large-scale pre-trained language models. Specifically, we introduce a dynamic structure pruning method based on differentiable search and recursive knowledge distillation to automatically prune the BERT model, named DDK. We define the search space for network pruning as all feed-forward layer channels and self-attention heads at each layer of the network, and utilize differentiable methods to determine their optimal number. Additionally, we design a recursive knowledge distillation method that employs adaptive weighting to extract the most important features from multiple intermediate layers of the teacher model and fuse them to supervise the student network learning. Our experimental results on the GLUE benchmark dataset and ablation analysis demonstrate that our proposed method outperforms other advanced methods in terms of average performance.
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Affiliation(s)
- Zhou Zhang
- School of Computer Science and Information Engineering, Hefei University of Technology, Hefei 230009, China.
| | - Yang Lu
- School of Computer Science and Information Engineering, Hefei University of Technology, Hefei 230009, China; Anhui Mine IOT and Security Monitoring Technology Key Laboratory, Hefei 230088, China.
| | - Tengfei Wang
- School of Computer Science and Information Engineering, Hefei University of Technology, Hefei 230009, China.
| | - Xing Wei
- School of Computer Science and Information Engineering, Hefei University of Technology, Hefei 230009, China; Intelligent Manufacturing Institute of Hefei University of Technology, Hefei 230009, China.
| | - Zhen Wei
- School of Computer Science and Information Engineering, Hefei University of Technology, Hefei 230009, China; Intelligent Manufacturing Institute of Hefei University of Technology, Hefei 230009, China.
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16
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Yu X, Yi H, Tang Q, Huang K, Hu W, Zhang S, Wang X. Graph-based social relation inference with multi-level conditional attention. Neural Netw 2024; 173:106216. [PMID: 38442650 DOI: 10.1016/j.neunet.2024.106216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Revised: 01/15/2024] [Accepted: 02/26/2024] [Indexed: 03/07/2024]
Abstract
Social relation inference intrinsically requires high-level semantic understanding. In order to accurately infer relations of persons in images, one needs not only to understand scenes and objects in images, but also to adaptively attend to important clues. Unlike prior works of classifying social relations using attention on detected objects, we propose a MUlti-level Conditional Attention (MUCA) mechanism for social relation inference, which attends to scenes, objects and human interactions based on each person pair. Then, we develop a transformer-style network to achieve the MUCA mechanism. The novel network named as Graph-based Relation Inference Transformer (i.e., GRIT) consists of two modules, i.e., a Conditional Query Module (CQM) and a Relation Attention Module (RAM). Specifically, we design a graph-based CQM to generate informative relation queries for all person pairs, which fuses local features and global context for each person pair. Moreover, we fully take advantage of transformer-style networks in RAM for multi-level attentions in classifying social relations. To our best knowledge, GRIT is the first for inferring social relations with multi-level conditional attention. GRIT is end-to-end trainable and significantly outperforms existing methods on two benchmark datasets, e.g., with performance improvement of 7.8% on PIPA and 9.6% on PISC.
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Affiliation(s)
- Xiaotian Yu
- Department of AI Technology Center, Shenzhen Intellifusion Ltd., China.
| | - Hanling Yi
- Department of AI Technology Center, Shenzhen Intellifusion Ltd., China
| | - Qie Tang
- Department of AI Technology Center, Shenzhen Intellifusion Ltd., China
| | - Kun Huang
- Department of AI Technology Center, Shenzhen Intellifusion Ltd., China
| | - Wenze Hu
- Department of AI Technology Center, Shenzhen Intellifusion Ltd., China
| | - Shiliang Zhang
- Department of Computer Science, Peking University, China
| | - Xiaoyu Wang
- Department of AI Technology Center, Shenzhen Intellifusion Ltd., China; The Chinese University of Hong Kong (Shenzhen), China
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17
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Abley K, Goswami R, Locke JCW. Bet-hedging and variability in plant development: seed germination and beyond. Philos Trans R Soc Lond B Biol Sci 2024; 379:20230048. [PMID: 38432313 PMCID: PMC10909506 DOI: 10.1098/rstb.2023.0048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Accepted: 11/28/2023] [Indexed: 03/05/2024] Open
Abstract
When future conditions are unpredictable, bet-hedging strategies can be advantageous. This can involve isogenic individuals producing different phenotypes, under the same environmental conditions. Ecological studies provide evidence that variability in seed germination time has been selected for as a bet-hedging strategy. We demonstrate how variability in germination time found in Arabidopsis could function as a bet-hedging strategy in the face of unpredictable lethal stresses. Despite a body of knowledge on how the degree of seed dormancy versus germination is controlled, relatively little is known about how differences between isogenic seeds in a batch are generated. We review proposed mechanisms for generating variability in germination time and the current limitations and new possibilities for testing the model predictions. We then look beyond germination to the role of variability in seedling and adult plant growth and review new technologies for quantification of noisy gene expression dynamics. We discuss evidence for phenotypic variability in plant traits beyond germination being under genetic control and propose that variability in stress response gene expression could function as a bet-hedging strategy. We discuss open questions about how noisy gene expression could lead to between-plant heterogeneity in gene expression and phenotypes. This article is part of a discussion meeting issue 'Causes and consequences of stochastic processes in development and disease'.
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Affiliation(s)
- Katie Abley
- The Sainsbury Laboratory, University of Cambridge, Cambridge, Cambridgeshire CB2 1LR, UK
| | - Rituparna Goswami
- The Sainsbury Laboratory, University of Cambridge, Cambridge, Cambridgeshire CB2 1LR, UK
| | - James C. W. Locke
- The Sainsbury Laboratory, University of Cambridge, Cambridge, Cambridgeshire CB2 1LR, UK
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18
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Zeng X, Liu Y, Zhang J, Guo Y. Medical object detector jointly driven by knowledge and data. Neural Netw 2024; 172:106084. [PMID: 38183830 DOI: 10.1016/j.neunet.2023.12.038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2023] [Revised: 11/15/2023] [Accepted: 12/22/2023] [Indexed: 01/08/2024]
Abstract
Most of the existing object detection algorithms are trained on medical datasets and then used for prediction. When the features of an object are not obvious in an image, these models are prone to mislocalize and misclassify it. In this paper, we propose a medical Object Detection algorithm jointly driven by Knowledge and Data (ODKD). It enables medical semantic knowledge provided by specialized physicians to be effective and helpful when traditional models have difficulty in correctly detecting objects relying on features alone. Our model consists of a base object detector together with a fusion module: the base object detector is trained based on medical datasets to obtain data-driven results; then we use a graph to represent external semantic knowledge and map the data-driven results to the nodes embedding of this graph structure. In the fusion module, a graph convolution network is used to fuse the data-driven results with the external semantic knowledge to output category adjustment coefficients. Finally, the adjustment coefficients are used to adjust the data-driven results to obtain results jointly driven by knowledge and data. Experiments show that professional medical semantic knowledge can effectively correct the erroneous results of the base detector, and the effect of our model outperforms Faster Rcnn, YOLOv5, YOLOv7, etc. on three medical datasets, Camus, Synapse, and AMOS.
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Affiliation(s)
- Xianhua Zeng
- School of Computer Science and Technology/School of Artificial Intelligence, Chongqing University of Posts and Telecommunications, Chongqing 400065, China.
| | - Yuhang Liu
- School of Computer Science and Technology/School of Artificial Intelligence, Chongqing University of Posts and Telecommunications, Chongqing 400065, China.
| | - Jian Zhang
- School of Computer Science and Technology/School of Artificial Intelligence, Chongqing University of Posts and Telecommunications, Chongqing 400065, China.
| | - Yongli Guo
- School of Computer Science and Technology/School of Artificial Intelligence, Chongqing University of Posts and Telecommunications, Chongqing 400065, China.
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19
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Kunovich RM. Work and the public understanding of science. Public Underst Sci 2024; 33:353-369. [PMID: 37865816 PMCID: PMC10958755 DOI: 10.1177/09636625231203478] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/23/2023]
Abstract
This study examines whether engaging in science work and work that is substantively complex (e.g. requiring independent thought and judgment) is related to interest in science, science knowledge, and confidence in the scientific community in the United States. It also examines whether the conditions of work mediate the relationship between education and these science-related outcomes. Occupation-level data from O*NET are merged with survey data from the General Social Survey. Results indicate that science work is related to interest in science and science knowledge and that work complexity is related to confidence in the scientific community. Results offer only limited evidence of mediation-science work mediates the relationship between educational attainment and science knowledge but not the relationships involving interest or confidence. In sum, results indicate that the conditions of work are associated with science attitudes, and that researchers should examine these connections in future research.
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20
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Bai L, Li N, Li G, Zhang Z, Zhu L. Embedding-Based Entity Alignment of Cross-Lingual Temporal Knowledge Graphs. Neural Netw 2024; 172:106143. [PMID: 38309139 DOI: 10.1016/j.neunet.2024.106143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Revised: 09/06/2023] [Accepted: 01/21/2024] [Indexed: 02/05/2024]
Abstract
Entity alignment aims to construct a complete knowledge graph (KG) by matching the same entities in multi-source KGs. Existing researches on entity alignment mainly focuses on static multi-relational data in knowledge graphs. However, the relationships or attributes between entities often possess temporal characteristics as well. Neglecting these temporal characteristics can frequently lead to alignment errors. Compared to studying entity alignment in temporal knowledge graphs, there are relatively few efforts on entity alignment in cross-lingual temporal knowledge graphs. Therefore, in this paper, we put forward an entity alignment method for cross-lingual temporal knowledge graphs, namely CTEA. Based on GCN and TransE, CTEA combines entity embeddings, relation embeddings and attribute embeddings to design a joint embedding model, which is more conducive to generating transferable entity embedding. In the meantime, the distance calculation between elements and the similarity calculation of entity pairs are combined to enhance the reliability of cross-lingual entity alignment. Experiments shows that the proposed CTEA model improves Hits@m and MRR by about 0.8∼2.4 percentage points compared with the latest methods.
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Affiliation(s)
- Luyi Bai
- School of Computer and Communication Engineering, Northeastern University (Qinhuangdao), Qinhuangdao 066004, China.
| | - Nan Li
- School of Computer and Communication Engineering, Northeastern University (Qinhuangdao), Qinhuangdao 066004, China
| | - Guishun Li
- School of Computer and Communication Engineering, Northeastern University (Qinhuangdao), Qinhuangdao 066004, China
| | - Ziyi Zhang
- School of Computer and Communication Engineering, Northeastern University (Qinhuangdao), Qinhuangdao 066004, China
| | - Lin Zhu
- School of Computer and Communication Engineering, Northeastern University (Qinhuangdao), Qinhuangdao 066004, China
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21
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Saragih ID, Tonapa SI, Osingada CP, Porta CM, Lee BO. Effects of telehealth-assisted interventions among people living with HIV/AIDS: A systematic review and meta-analysis of randomized controlled studies. J Telemed Telecare 2024; 30:438-450. [PMID: 34967240 DOI: 10.1177/1357633x211070726] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
INTRODUCTION Taking antiretroviral therapy (ART) is a daily necessity for people living with HIV but these individuals experience multiple barriers and challenges to medication adherence. Interventions to support medication adherence have yielded effects in the expected direction, but the extent to which telehealth or virtually delivered interventions to promote adherence are effective among people living with HIV/AIDS remains unknown. We aimed to address this knowledge gap and inform future research and practice that promotes the well-being of people living with HIV/AIDs through telehealth interventions addressing medication use. METHODS A systematic review and meta-analysis of randomized controlled trials (RCTs) was conducted using the following databases: Academic Search Complete, Cochrane library, Cumulative Index to Nursing and Allied Health Literature (CINAHL), EMBASE, MEDLINE, PubMed, OVID (UpToDate), and the Web of Science. Relevant full-text articles published through September 2021 were retrieved. The revised Cochrane risk of bias tool for randomized trials was used to assess the methodological quality of the included studies. A meta-analysis was performed using a random-effects model to calculate the pooled effects of telehealth-assisted interventions for people living with HIV/AIDS. Stata 16.0 was used for statistical analysis. RESULTS A total of 12 studies (N = 3557 participants) that used telehealth-assisted interventions for people living with HIV/AIDS were included. Telehealth interventions were found to increase the adherence to treatment (standardized mean difference [SMD]: 0.21; 95% confidence interval (CI): 0.03 to 0.40), to reduce depressive symptoms (SMD: -2,74; 95% CI: -3.39 to -2.09), and to improve perceived quality of life (SMD: 0.74; 95% CI: 0.37 to 1.10). DISCUSSION The meta-effects of telehealth-assisted interventions include significantly enhanced adherence to treatment, improved quality of life, and reduced depressive symptoms among people living with HIV/AIDS. These findings suggesting that delivering health management interventions remotely through telehealth-assisted modalities was both feasible and effective in yielding health benefits for people living with HIV/AIDS. Integrating telehealth-assisted interventions as a modality in HIV/AIDS care might support continuity of care and sustained well-being. Future research should evaluate telehealth intervention outcomes and examine mediating, moderating, or other tailorable variables affecting intervention effectiveness.
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Affiliation(s)
| | - Santo Imanuel Tonapa
- College of Nursing, Kaohsiung Medical University, Kaohsiung, Taiwan
- School of Nursing, Sam Ratulangi University, Manado, Indonesia
| | | | - Carolyn M Porta
- School of Nursing, University of Minnesota, Minneapolis, USA
| | - Bih-O Lee
- College of Nursing, Kaohsiung Medical University, Kaohsiung, Taiwan
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22
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Caskie GIL, Canell AE, Bashian HM. Identifying Specific Gaps in Knowledge of Aging and Examining Its Relation to Biases Toward Older Adults. J Appl Gerontol 2024; 43:437-445. [PMID: 38087808 DOI: 10.1177/07334648231210503] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/20/2024] Open
Abstract
Accurate aging knowledge is key to reducing ageist attitudes that impact older adult well-being. We first investigated how aging knowledge and negative and positive age-bias indirectly expressed via aging knowledge responses were related to an explicitly negative ageism measure. We then identified specific gaps in the aging knowledge of emerging adults and middle-aged adults. More negative ageism correlated with less aging knowledge overall and in psychological and social, but not biological, domains. Negative ageism correlated with negative age-bias, but not positive age-bias, expressed via aging knowledge responses. Knowledge of aging was poorest regarding social and psychological aspects of aging and best regarding biological aging. Middle-aged adults had slightly, but significantly, more accurate aging knowledge and less negative age-bias than emerging adults; positive age-bias did not differ by age-group. These results suggest that effectiveness of anti-ageism educational interventions may be enhanced if focused on improving knowledge of social and psychological aging.
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23
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Young DG, Molokach B, Oittinen EM. Lay epistemology and the Populist's playbook: The roles of epistemological identity and expressive epistemology. Curr Opin Psychol 2024; 56:101776. [PMID: 38103282 DOI: 10.1016/j.copsyc.2023.101776] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Revised: 11/23/2023] [Accepted: 11/24/2023] [Indexed: 12/19/2023]
Abstract
Salient social identities have long appeared to shape what we believe and know. But do social identities also shape how we know? This essay argues that performances of "lay epistemology" by populist leaders may shape group norms in ways that encourage supporters to orient to their worlds more through intuition and emotion and less through evidence and data (or at least to report that they do, thus constituting a form of "expressive epistemology"). We summarize research on the positive link between populist attitudes, valuing intuition and emotion over evidence and data, and belief in misinformation and conspiracy theories, and then explore how these relationships may be mutually reinforcing - and strategically beneficial to populist leaders.
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24
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Udry J, Barber SJ. The illusory truth effect: A review of how repetition increases belief in misinformation. Curr Opin Psychol 2024; 56:101736. [PMID: 38113667 DOI: 10.1016/j.copsyc.2023.101736] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Revised: 11/01/2023] [Accepted: 11/10/2023] [Indexed: 12/21/2023]
Abstract
Repetition increases belief in information, a phenomenon known as the illusory truth effect. In laboratory experiments, the illusory truth effect has often been examined using general trivia statements as stimuli, but repetition also increases belief in misinformation, such as fake news headlines and conspiracy beliefs. Repetition even increases belief in claims that are implausible or that contradict prior knowledge. Repetition also has broader impacts beyond belief, such as increasing sharing intentions of news headlines and decreasing how unethical an act is perceived to be. Although the illusory truth effect is robust, some interventions reduce its magnitude, including instruction to focus on accuracy and awareness of the illusory truth effect. These strategies may be effective for reducing belief in misinformation.
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Affiliation(s)
- Jessica Udry
- Department of Psychology, Georgia State University, USA
| | - Sarah J Barber
- Department of Psychology, Georgia State University, USA; Gerontology Institute, Georgia State University, Atlanta, GA, USA.
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25
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Deng L, Yang B, Kang Z, Xiang Y. Invariant feature based label correction for DNN when Learning with Noisy Labels. Neural Netw 2024; 172:106137. [PMID: 38309136 DOI: 10.1016/j.neunet.2024.106137] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 11/14/2023] [Accepted: 01/17/2024] [Indexed: 02/05/2024]
Abstract
Learning with Noisy Labels (LNL) methods have been widely studied in recent years, which aims to improve the performance of Deep Neural Networks (DNNs) when the training dataset contains incorrectly annotated labels. Popular existing LNL methods rely on semantic features extracted by the DNN to detect and mitigate label noise. However, these extracted features are often spurious and contain unstable correlations with the label across different environments (domains), which can occasionally lead to incorrect prediction and compromise the efficacy of LNL methods. To mitigate this insufficiency, we propose Invariant Feature based Label Correction (IFLC), which reduces spurious features and accurately utilizes the learned invariant features that contain stable correlation to correct label noise. To the best of our knowledge, this is the first attempt to mitigate the issue of spurious features for LNL methods. IFLC consists of two critical processes: The Label Disturbing (LD) process and the Representation Decorrelation (RD) process. The LD process aims to encourage DNN to attain stable performance across different environments, thus reducing the captured spurious features. The RD process strengthens independence between each dimension of the representation vector, thus enabling accurate utilization of the learned invariant features for label correction. We then utilize robust linear regression for the feature representation to conduct label correction. We evaluated the effectiveness of our proposed method and compared it with state-of-the-art (sota) LNL methods on four benchmark datasets, CIFAR-10, CIFAR-100, Animal-10N, and Clothing1M. The experimental results show that our proposed method achieved comparable or even better performance than the existing sota methods. The source codes are available at https://github.com/yangbo1973/IFLC.
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Affiliation(s)
- Lihui Deng
- School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, China.
| | - Bo Yang
- School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, China.
| | - Zhongfeng Kang
- School of Information Science and Engineering, Lanzhou University, Lanzhou, Gansu 730000, China.
| | - Yanping Xiang
- School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, China.
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26
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Wu Y, Li X. Outcomes of heart failure: gaps in knowledge and needs for action. Lancet Glob Health 2024; 12:e539-e540. [PMID: 38485417 DOI: 10.1016/s2214-109x(24)00060-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Accepted: 02/02/2024] [Indexed: 03/19/2024]
Affiliation(s)
- Yi Wu
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - Xi Li
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China; Fuwai Hospital Chinese Academy of Medical Sciences, Shenzhen, Shenzhen, China; Central China Sub-Center of the National Center for Cardiovascular Diseases, Zhengzhou, China.
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Chatterjee A, Baker T, Rudorf M, Walt G, Stotz C, Martin A, Kinnard EN, McAlearney AS, Bosak J, Medley B, Pinkhover A, Taylor JL, Samet JH, Lunze K. Mobile treatment for opioid use disorder: Implementation of community-based, same-day medication access interventions. J Subst Use Addict Treat 2024; 159:209272. [PMID: 38128649 PMCID: PMC10947870 DOI: 10.1016/j.josat.2023.209272] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/10/2023] [Revised: 09/20/2023] [Accepted: 12/13/2023] [Indexed: 12/23/2023]
Abstract
BACKGROUND Medications for Opioid Use Disorder (MOUD) are lifesaving, but <20 % of individuals in the US who could benefit receive them. As part of the NIH-supported HEALing Communities Study (HCS), coalitions in several communities in Massachusetts and Ohio implemented mobile MOUD programs to overcome barriers to MOUD receipt. We defined mobile MOUD programs as units that provide same-day access to MOUD at remote sites. We aimed to (1) document the design and organizational structure of mobile programs providing same-day or next-day MOUD, and (2) explore the barriers and facilitators to implementation as well as the successes and challenges of ongoing operation. METHODS Program staff from five programs in two states (n = 11) participated in semi-structured interviews. Two authors conducted thematic analysis of the transcripts based on the domains of the social-ecological model and the semi-structured interview guide. RESULTS Mobile MOUD units sought to improve immediate access to MOUD ("Our answer is pretty much always, 'Yes, we'll get you started right here, right now,'"), advance equity ("making sure that we have staff who speak other languages, who are on the unit and have some resources that are in different languages,"), and decrease opioid overdose deaths. Salient program characteristics included diverse staff, including staff with lived experience of substance use ("She just had that personal knowledge of where we should be going"). Mobile units offered harm reduction services, broad medical services (in particular, wound care), and connection to transportation programs and incorporated consistency in service provision and telemedicine access. Implementation facilitators included trusting relationships with partner organizations (particularly pharmacies and correctional facilities), nuanced understanding of local politics, advertising, protocol flexibility, and on-unit prescriber hours. Barriers included unclear licensing requirements, staffing shortages and competing priorities for staff, funding challenges due to inconsistency in grant funding and low reimbursement ("It's not really possible that billing in and of itself is going to be able to sustain it"), and community stigma toward addiction services generally. CONCLUSIONS Despite organizational, community, and policy barriers, participants described mobile MOUD units as an innovative way to expand access to life-saving medications, promote equity in MOUD treatment, and overcome stigma.
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Affiliation(s)
- Avik Chatterjee
- Boston University School of Medicine, Boston, MA, United States of America; Boston Medical Center, Boston, MA, United States of America.
| | - Trevor Baker
- Boston Medical Center, Boston, MA, United States of America
| | - Maria Rudorf
- Boston Medical Center, Boston, MA, United States of America
| | - Galya Walt
- Boston Medical Center, Boston, MA, United States of America
| | - Caroline Stotz
- Boston Medical Center, Boston, MA, United States of America
| | - Anna Martin
- Boston Medical Center, Boston, MA, United States of America
| | | | - Ann Scheck McAlearney
- The Ohio State University College of Medicine, Columbus, OH, United States of America
| | - Julie Bosak
- Boston Medical Center, Boston, MA, United States of America
| | - Bethany Medley
- Columbia University School of Social Work, New York, NY, United States of America
| | - Allyson Pinkhover
- Brockton Neighborhood Health Center, Brockton, MA, United States of America; Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States of America
| | - Jessica L Taylor
- Boston University School of Medicine, Boston, MA, United States of America; Boston Medical Center, Boston, MA, United States of America
| | - Jeffrey H Samet
- Boston University School of Medicine, Boston, MA, United States of America; Boston Medical Center, Boston, MA, United States of America
| | - Karsten Lunze
- Boston University School of Medicine, Boston, MA, United States of America; Boston Medical Center, Boston, MA, United States of America
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Peachey KL, Franklin RC, Lower T. A Summary of Fatal Injury Surveillance Methods in Australian Agriculture and Their Impact on Safety Policies and Practices. J Agromedicine 2024; 29:297-303. [PMID: 37937811 DOI: 10.1080/1059924x.2023.2281516] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Accepted: 10/17/2023] [Indexed: 11/09/2023]
Abstract
Agriculture is one of the most important and also hazardous industries in Australia. Having a sound knowledge and understanding of the circumstance of injury events is critical to developing evidence-based intervention programs. This paper aims to provide a brief historical snapshot of the development of data systems underpinning the assessment of fatal farm injury in Australia and how it has impacted on safety policy and practice. The first Australian studies used coronial information to explore agricultural fatalities, these studies reviewed paper-based records (in-situ) and collected the information for analysis and reporting. This task was laborious and costly. When the National Coronial Information System (NCIS) was established in 2000, this allowed access to coronial records online. Information provided about the deceased includes demographics, contextual details on the nature of the fatality and autopsy, toxicology, and police reports, as-well-as the coroner's finding. Information from the NCIS, along with media reports, have been used to develop the farm fatality database. This information has been used to inform the safety goals and targets for farm commodity groups, identify key risks, provide long-term benchmark indicators and underpin the development of prevention materials and training resources. Without accurate, timely, concise and relevant data about injury occurring on farms, there is no evidence to drive policy and practice or to evaluate programs of work. As such, the continued utilization and extension of the NCIS data will prove crucial to further reducing the burden of preventable fatal injuries on Australian farms.
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Affiliation(s)
- Kerri-Lynn Peachey
- AgHealth Australia, School of Rural Health, The University of Sydney, Dubbo, Moree, NSW, Australia
| | - Richard C Franklin
- WSO Collaborating Center for Injury Prevention and Safety Promotion, College of Public Health, Medical and Veterinary Sciences, James Cook University, Townsville, QLD, Australia
| | - Tony Lower
- AgHealth Australia, School of Rural Health, The University of Sydney, Dubbo, Moree, NSW, Australia
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Carazo-Díaz C, Prieto-Valiente L. [The p-value of the test is not a 'mathematical index', it is simply a relative frequency]. Rev Neurol 2024; 78:209-211. [PMID: 38502169 DOI: 10.33588/rn.7807.2023164] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/20/2024]
Abstract
Leading scientific journals in fields such as medicine, biology and sociology repeatedly publish articles and editorials claiming that a large percentage of doctors do not understand the basics of statistical analysis, which increases the risk of errors in interpreting data, makes them more vulnerable to misinformation and reduces the effectiveness of research. This problem extends throughout their careers and is largely due to the poor training they receive in statistics - a problem that is common in developed countries. As stated by H. Halle and S. Krauss, '90% of German university lecturers who regularly use the p-value in tests do not understand what that value actually measures'. It is important to note that the basic reasoning of statistical analysis is similar to what we do in our daily lives and that understanding the basic concepts of statistical analysis does not require any knowledge of mathematics. Contrary to what many researchers believe, the p-value of the test is not a 'mathematical index' that allows us to clearly conclude whether, for example, a drug is more effective than a placebo. The p-value of the test is simply a percentage.
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Affiliation(s)
- C Carazo-Díaz
- Universidad Católica San Antonio de Murcia, Guadalupe de Maciascoque, España
| | - L Prieto-Valiente
- Universidad Católica San Antonio de Murcia, Guadalupe de Maciascoque, España
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Imbernon U, Casanovas-Rubio MDM, Monteiro C, Armengou J. Towards transparent decision-making processes within museums: Case study of Museu Nacional d'Art de Catalunya (MNAC). Eval Program Plann 2024; 103:102405. [PMID: 38309207 DOI: 10.1016/j.evalprogplan.2024.102405] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Revised: 02/06/2023] [Accepted: 01/15/2024] [Indexed: 02/05/2024]
Abstract
Understanding that good decision-making is paramount for the success of an organization and recognizing that strategic decision-making inside museums is a topic that has been over-passed by researchers, this paper intends to contribute to the relevance of the subject through the implementation of an innovative tool. Decision-making in museums is normally focused on the intuition, subjectivity, and experience of the curator, who brings all his knowledge to the exhibition programming. However, museums' management and environment are constantly changing, thus the application of this tool would aim to make decisions in a more democratic, transparent, inclusive, and accurate manner. Besides, it will be easier to understand how distinct subjects can work together, demonstrating successful results to improve the decision-making process when programming and measuring temporary exhibition seasons in museums. This paper describes the design and implementation of the Multi-Attribute Utility Theory (MAUT) for the Museu Nacional d'Art de Catalunya (MNAC). It also analyzes and evaluates the decision-making process when scheduling exhibitions for a season.
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Affiliation(s)
- Ursula Imbernon
- Boston University Summer Term Office, Boston University, Boston, USA.
| | | | - Carolina Monteiro
- Department of Art History, University of Leiden, Leiden, the Netherlands.
| | - Jaume Armengou
- IESE Business School, University of Navarra, Barcelona, Spain.
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31
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Aydin O. Rise of single-case experimental designs: A historical overview of the necessity of single-case methodology. Neuropsychol Rehabil 2024; 34:301-334. [PMID: 36811612 DOI: 10.1080/09602011.2023.2181191] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Accepted: 02/13/2023] [Indexed: 02/24/2023]
Abstract
ABSTRACTWindelband ([1894]1980) advocated that two approaches are used for accumulating scientific knowledge. The first is the idiographic approach that derives knowledge from a single unit, and the second is the nomothetic approach that accumulates knowledge of a group. Given these two approaches, the former matches case studies while the latter is more appropriate with experimental group studies. Scientists have criticized both methodologies for their various limitations. Later, the single-case methodology emerged as an alternative that potentially allays these limitations. In this context, this narrative review aims to describe the historical roots of single-case experimental designs (SCEDs) that have emerged to eliminate the tension of nomothetic and idiographic approaches over time. First, the review focuses on the emergence of SCEDs. Second, the strengths and challenges of SCEDs are reviewed, including those to address the limitations of group experimental and case studies. Third, the use and analyses of SCEDs are outlined, considering their current status. Fourth, this narrative review continues to delineate the dissemination of SCEDs in the modern scientific world. As a result, SCEDs can be evaluated as a method that has the potential to overcome the issues encountered in case description and group experimental research. Thus, that helps accumulate nomothetic and idiographic knowledge in determining evidence-based practices.
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Affiliation(s)
- Orhan Aydin
- Faculty of Education, Erzincan Binali Yildirim University, Erzincan, Türkiye
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Gao T, Xu CZ, Zhang L, Kong H. GSB: Group superposition binarization for vision transformer with limited training samples. Neural Netw 2024; 172:106133. [PMID: 38266471 DOI: 10.1016/j.neunet.2024.106133] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Revised: 12/02/2023] [Accepted: 01/15/2024] [Indexed: 01/26/2024]
Abstract
Vision Transformer (ViT) has performed remarkably in various computer vision tasks. Nonetheless, affected by the massive amount of parameters, ViT usually suffers from serious overfitting problems with a relatively limited number of training samples. In addition, ViT generally demands heavy computing resources, which limit its deployment on resource-constrained devices. As a type of model-compression method, model binarization is potentially a good choice to solve the above problems. Compared with the full-precision one, the model with the binarization method replaces complex tensor multiplication with simple bit-wise binary operations and represents full-precision model parameters and activations with only 1-bit ones, which potentially solves the problem of model size and computational complexity, respectively. In this paper, we investigate a binarized ViT model. Empirically, we observe that the existing binarization technology designed for Convolutional Neural Networks (CNN) cannot migrate well to a ViT's binarization task. We also find that the decline of the accuracy of the binary ViT model is mainly due to the information loss of the Attention module and the Value vector. Therefore, we propose a novel model binarization technique, called Group Superposition Binarization (GSB), to deal with these issues. Furthermore, in order to further improve the performance of the binarization model, we have investigated the gradient calculation procedure in the binarization process and derived more proper gradient calculation equations for GSB to reduce the influence of gradient mismatch. Then, the knowledge distillation technique is introduced to alleviate the performance degradation caused by model binarization. Analytically, model binarization can limit the parameter's search space during parameter updates while training a model. Therefore, the binarization process can actually play an implicit regularization role and help solve the problem of overfitting in the case of insufficient training data. Experiments on three datasets with limited numbers of training samples demonstrate that the proposed GSB model achieves state-of-the-art performance among the binary quantization schemes and exceeds its full-precision counterpart on some indicators. Code and models are available at: https://github.com/IMRL/GSB-Vision-Transformer.
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Affiliation(s)
- Tian Gao
- School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu, China.
| | - Cheng-Zhong Xu
- State Key Laboratory of Internet of Things for Smart City (SKL-IOTSC), University of Macau, 999078, Macao Special Administrative Region of China; Department of Computer and Information Science (CIS), University of Macau, 999078, Macao Special Administrative Region of China.
| | - Le Zhang
- School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.
| | - Hui Kong
- State Key Laboratory of Internet of Things for Smart City (SKL-IOTSC), University of Macau, 999078, Macao Special Administrative Region of China; Department of Computer and Information Science (CIS), University of Macau, 999078, Macao Special Administrative Region of China; Department of Electromechanical Engineering (EME), University of Macau, 999078, Macao Special Administrative Region of China.
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Wilson JT, Bauer PJ. Generative and active engagement in learning neuroscience: A comparison of self-derivation and rephrase. Cognition 2024; 245:105709. [PMID: 38232474 DOI: 10.1016/j.cognition.2023.105709] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Revised: 11/25/2023] [Accepted: 12/19/2023] [Indexed: 01/19/2024]
Abstract
It is crucial to identify cognitive mechanisms that support knowledge growth. One such mechanism that is known to improve learning outcomes is generative processing: the construction of novel information beyond what is directly taught. In this study of college students, we investigate the learning outcomes associated with the generative process of self-derivation through integration, the integration of multiple related facts to generate novel information. We compare the effects of self-derivation versus an active rephrase control condition on retrieval, application, and organization of neuroscience classroom content. In the self-derivation condition, learners were prompted to generate inferences based on integration of two explicitly-taught facts. In the rephrase condition, learners were explicitly provided these inferences and asked to rephrase them. We found few overall differences between learning manipulation conditions. However, we found that, regardless of the learning manipulation condition to which learners were exposed, learners generated their own information on some trials. This generation predicted success on retrieval and application of learned information. Further, self-derivation, when successful, led to particularly high rates of retrieval when compared with active rephrase. These findings inform theory on generative processing, and demonstrate that self-derivation is a mechanism of knowledge growth that may be useful for retrieval.
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Kurupınar M, Serbest O, Yılmaz D, Soley G. Children's expectations about the stability of others' knowledge and preference states. J Exp Child Psychol 2024; 240:105834. [PMID: 38183878 DOI: 10.1016/j.jecp.2023.105834] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2023] [Revised: 11/06/2023] [Accepted: 12/04/2023] [Indexed: 01/08/2024]
Abstract
It is a crucial ability to predict others' psychological states across time and contexts. Focusing on cultural inventions such as songs and stories, we contrasted children's attributions of stability with others' knowledge and preference states across time and space and whether these attributions change as a function of children's familiarity with the known/liked items. Children (91 4-year-olds and 97 6-year-olds) were introduced to characters who knew or liked a song, a story, a game and a dance that were either novel or familiar. Children were asked whether the characters would still know/like these when they move to another city or when they grow up to be an adult. Both age groups expected these attributes to be more durable in the moving scenario compared with the growing-up scenario, but this trend became more robust with age. Whereas overall children did not judge knowledge as more durable than preferences, children found knowledge to be more enduring with age. The 6-year-olds' stability attributions also increased when known/liked items were familiar. These results suggest that, across the preschool years, children become more nuanced in their predictions about the future forms of knowledge and preference states.
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Affiliation(s)
- Mahmut Kurupınar
- Department of Psychology, Boğaziçi University, Bebek, 34342 Istanbul, Turkey
| | - Oya Serbest
- Department of Psychology, Boğaziçi University, Bebek, 34342 Istanbul, Turkey; Department of Psychology, University of California, Santa Barbara, Santa Barbara, CA 93106, USA
| | - Duygu Yılmaz
- Department of Psychology, Boğaziçi University, Bebek, 34342 Istanbul, Turkey; Department of Psychology, New York University
| | - Gaye Soley
- Department of Psychology, Boğaziçi University, Bebek, 34342 Istanbul, Turkey; Department of Cognition, Development and Educational Psychology, University of Barcelona.
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Li J, Wang J, Wu L, Wang X, Luo X, Xu Y. AMHGCN: Adaptive multi-level hypergraph convolution network for human motion prediction. Neural Netw 2024; 172:106153. [PMID: 38306784 DOI: 10.1016/j.neunet.2024.106153] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Revised: 11/20/2023] [Accepted: 01/28/2024] [Indexed: 02/04/2024]
Abstract
Human motion prediction is the key technology for many real-life applications, e.g., self-driving and human-robot interaction. The recent approaches adopt the unrestricted full-connection graph representation to capture the relationships inside the human skeleton. However, there are two issues to be solved: (i) these unrestricted full-connection graph representation methods neglect the inherent dependencies across the joints of the human body; (ii) these methods represent human motions using the features extracted from a single level and thus can neither fully exploit the various connection relationships among the human body nor guarantee the human motion prediction results to be reasonable. To tackle the above issues, we propose an adaptive multi-level hypergraph convolution network (AMHGCN), which uses the adaptive multi-level hypergraph representation to capture various dependencies among the human body. Our method has four different levels of hypergraph representations, including (i) the joint-level hypergraph representation to capture inherent kinetic dependencies in the human body, (ii) the part-level hypergraph representation to exploit the kinetic characteristics at a higher level (in comparison to the joint-level) by viewing some part of the human body as an entirety, (iii) the component-level hypergraph representation to model the semantic information, and (iv) the global-level hypergraph representation to extract long-distance dependencies in the human body. In addition, to take full advantage of the knowledge carried in the training data, we propose a reverse loss (i.e., adopting the future human poses to predict the historical poses reversely) to realize data augmentation. Extensive experiments show that our proposed AMHGCN can achieve state-of-the-art performance on three benchmarks, i.e., Human3.6M, CMU-Mocap, and 3DPW.
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Affiliation(s)
- Jinkai Li
- School of Computer Science and Technology, Harbin Institute of Technology, Shenzhen, Shenzhen 518055, China
| | - Jinghua Wang
- School of Computer Science and Technology, Harbin Institute of Technology, Shenzhen, Shenzhen 518055, China
| | - Lian Wu
- School of Mathematics and Big Data, GuiZhou Education University, Guiyang 550018, China
| | - Xin Wang
- School of Computer Science and Technology, Harbin Institute of Technology, Shenzhen, Shenzhen 518055, China
| | - Xiaoling Luo
- College of Computer Science and Software Engineering, Shenzhen University, Shenzhen 518060, China
| | - Yong Xu
- School of Computer Science and Technology, Harbin Institute of Technology, Shenzhen, Shenzhen 518055, China; Peng Cheng Laboratory, Shenzhen 518055, China.
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Jia M, Ju R, Zhu J. Understanding Mental Health Organizations' Instagram Through Visuals: A Content Analysis. Health Commun 2024; 39:767-777. [PMID: 36856059 DOI: 10.1080/10410236.2023.2185350] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
This study analyzed the content, visual features, and audience engagement data of Instagram posts from two mental health organizations over one year (N = 725). For content features, mental health literacy and communicative strategies were examined. Posts that promoted knowledge of mental disorders and treatments, used information and community strategy were more likely to receive higher audience engagement. Visual features of demographic segments, visual composition, and visual framing topics were analyzed. Images that covered an unspecific population, used illustrated images, and focused on anti-stigma topical frames obtained more engagement. Theoretical contributions and practical applications regarding visual message design and management on social media to promote mental health are also offered.
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Affiliation(s)
- Moyi Jia
- Communication and Media Studies Department, State University of New York at Cortland
| | - Ran Ju
- Department of Public Relations, Mount Royal University
| | - Jian Zhu
- Department of Psychology, Eastern Illinois University
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Liu R, Chen Y, Li A, Ding Y, Yu H, Guan C. Aggregating intrinsic information to enhance BCI performance through federated learning. Neural Netw 2024; 172:106100. [PMID: 38232427 DOI: 10.1016/j.neunet.2024.106100] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Revised: 11/20/2023] [Accepted: 01/03/2024] [Indexed: 01/19/2024]
Abstract
Insufficient data is a long-standing challenge for Brain-Computer Interface (BCI) to build a high-performance deep learning model. Though numerous research groups and institutes collect a multitude of EEG datasets for the same BCI task, sharing EEG data from multiple sites is still challenging due to the heterogeneity of devices. The significance of this challenge cannot be overstated, given the critical role of data diversity in fostering model robustness. However, existing works rarely discuss this issue, predominantly centering their attention on model training within a single dataset, often in the context of inter-subject or inter-session settings. In this work, we propose a hierarchical personalized Federated Learning EEG decoding (FLEEG) framework to surmount this challenge. This innovative framework heralds a new learning paradigm for BCI, enabling datasets with disparate data formats to collaborate in the model training process. Each client is assigned a specific dataset and trains a hierarchical personalized model to manage diverse data formats and facilitate information exchange. Meanwhile, the server coordinates the training procedure to harness knowledge gleaned from all datasets, thus elevating overall performance. The framework has been evaluated in Motor Imagery (MI) classification with nine EEG datasets collected by different devices but implementing the same MI task. Results demonstrate that the proposed framework can boost classification performance up to 8.4% by enabling knowledge sharing between multiple datasets, especially for smaller datasets. Visualization results also indicate that the proposed framework can empower the local models to put a stable focus on task-related areas, yielding better performance. To the best of our knowledge, this is the first end-to-end solution to address this important challenge.
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Affiliation(s)
- Rui Liu
- School of Computer Science and Engineering, Nanyang Technological University, 50 Nanyang Ave, 639798, Singapore.
| | - Yuanyuan Chen
- School of Computer Science and Engineering, Nanyang Technological University, 50 Nanyang Ave, 639798, Singapore.
| | - Anran Li
- School of Computer Science and Engineering, Nanyang Technological University, 50 Nanyang Ave, 639798, Singapore.
| | - Yi Ding
- School of Computer Science and Engineering, Nanyang Technological University, 50 Nanyang Ave, 639798, Singapore.
| | - Han Yu
- School of Computer Science and Engineering, Nanyang Technological University, 50 Nanyang Ave, 639798, Singapore.
| | - Cuntai Guan
- School of Computer Science and Engineering, Nanyang Technological University, 50 Nanyang Ave, 639798, Singapore.
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Liabo K, Asare L, Ruthen P, Burton J, Staunton P, Day J. Emotion in public involvement: A conceptual review. Health Expect 2024; 27:e14020. [PMID: 38504467 PMCID: PMC10951420 DOI: 10.1111/hex.14020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Revised: 02/29/2024] [Accepted: 03/10/2024] [Indexed: 03/21/2024] Open
Abstract
BACKGROUND Experiential knowledge can aid in designing research by highlighting what an idea looks like from a patient and carer perspective. Experiential knowledge can be emotional, and this can create challenges at formal research meetings. OBJECTIVE The aim of this study was to consider the role of emotions in public involvement. METHODS This is a conceptual review informed by relevant literature and reflection within the author team. A structured Scopus search was conducted in November 2021 and December 2022, identifying 18 articles that presented findings from patient and public involvement (PPI) research related to 'emotion'. We complemented the search with theory-generating articles related to the role of emotion and emotional labour in human life. FINDINGS Study findings from the structured search were tabulated to identify recurring themes; these were as follows: emotional connections to the research topic can cause stressful as well as cathartic experiences of PPI, 'emotional work' is part of PPI when people are contributing with their experiential knowledge and the emotional aspect of 'lived experience' needs to be recognised in how PPI is planned and facilitated. These points were considered in relation to theoretical works and experiences within the author team. DISCUSSION 'Emotion work' is often required of public collaborators when they contribute to research. They are asked to contribute to research alongside researchers, with knowledge that often contains emotions or feelings. This can be both upsetting and cathartic, and the environment of the research study can make the experience worse or better. CONCLUSIONS The emotional component of experiential knowledge can be challenging to those invited to share this knowledge. It is imperative that researchers, research institutions and health and care professionals adjust research meeting spaces to show an awareness of the emotional labour that is involved in PPI. PATIENT OR PUBLIC CONTRIBUTION This review was initiated after a meeting between carers and family members of residents in care homes and researchers. The review is co-written by a group of three researchers and three carers and family members. Regular online meetings were held during the draft stages to incorporate people's views and ideas. Data extracted from the review were presented to the group of public collaborators in a variety of formats (e.g., posters, slideshows, text and verbally) to facilitate shared sense-making and synthesis of the literature.
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Affiliation(s)
- Kristin Liabo
- Department of Community and Health Sciences, Faculty of Health and Life Sciences, University of Exeter Medical SchoolUniversity of ExeterExeterUK
| | - Lauren Asare
- Department of Community and Health Sciences, Faculty of Health and Life Sciences, University of Exeter Medical SchoolUniversity of ExeterExeterUK
| | - Philip Ruthen
- Exeter Lived Experience Group (LEG), Department of Psychology, Faculty of Health and Life SciencesUniversity of ExeterExeterUK
| | - Julia Burton
- National Institute for Health Research Applied Research Collaboration South West Peninsula Public Engagement Group (PenPEG)University of ExeterExeterUK
| | - Pamela Staunton
- National Institute for Health Research Applied Research Collaboration South West Peninsula Public Engagement Group (PenPEG)University of ExeterExeterUK
| | - Joanne Day
- Department of Community and Health Sciences, Faculty of Health and Life Sciences, University of Exeter Medical SchoolUniversity of ExeterExeterUK
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Wang L, Bari MW, Shaheen S, Zhong K. Impostor leader and knowledge hiding: Attachment avoidance as underlying mechanism. Acta Psychol (Amst) 2024; 244:104188. [PMID: 38368783 DOI: 10.1016/j.actpsy.2024.104188] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Revised: 02/10/2024] [Accepted: 02/12/2024] [Indexed: 02/20/2024] Open
Abstract
Impostorism and knowledge-hiding behaviors negatively impact employees and organizational performance. This study examines the association between impostor leaders and knowledge hiding (evasive hiding, playing dumb, and rationalized hiding). Attachment avoidance is discussed as a mediator between impostor leaders and knowledge-hiding. For quantitative analyses, this study collected the data from 429 individuals with two time lags by sharing the survey instrument link on different organizations' randomly selected official media pages. After obtaining approval from the administrators of these pages, leaders and subordinates from these organizations were asked to participate in the study. The partial least squares structural equation modeling method is employed with Smartpls-4 software for data analyses. The findings indicate that impostor leaders promote knowledge hiding in subordinates. However, impostor leaders highly promote rationalized hiding behavior in subordinates. Attachment avoidance mediates the relationship between the impostor leader and knowledge-hiding behaviors. However, the highest mediation relationship exists between an impostor leader and playing dumb behavior in subordinates. This study strengthens the generalizability of the social exchange theory. The implications mentioned in this study are beneficial in understanding and dealing with the Impostorism and knowledge-hiding phenomena.
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Affiliation(s)
- Laibin Wang
- School of Business, Chizhou University, Chizhou, China; Center for International Education, Philippines Christian University, Manila, Philippines.
| | | | - Sadia Shaheen
- Lyallpur Business School, Government College University Faisalabad, Pakistan.
| | - Kaiyang Zhong
- College of Information Science & Electronic Engineering, Zhejiang University, Hangzhou, China.
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Caronia L, Ranzani F. Epistemic Trust as an Interactional Accomplishment in Pediatric Well-Child Visits: Parents' Resistance to Solicited Advice as Performing Epistemic Vigilance. Health Commun 2024; 39:838-851. [PMID: 36967666 DOI: 10.1080/10410236.2023.2189504] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Epistemic trust - i.e. the belief in knowledge claims we do not understand or cannot validate - is pivotal in healthcare interactions where trust in the source of knowledge is the foundation for adherence to therapy as well as general compliance with the physician's suggestions. However, in the contemporary knowledge society professionals can no longer count on unconditional epistemic trust: boundaries of the legitimacy and extension criteria of expertise have become increasingly fuzzier and professionals must take into account laypersons' expertise. Drawing on a conversation analysis-informed study of 23 videorecorded pediatrician-led well-child visits, the article deals with the communicative constitution of healthcare-relevant phenomena such as: epistemic and deontic struggles between parents and pediatricians, the local accomplishment of (responsible) epistemic trust, and the possible outcomes of blurred boundaries between the layperson's and the professional's "expertise." In particular, we illustrate how epistemic trust is communicatively built in sequences where parents request the pediatrician's advice and resist it. The analysis shows how parents perform epistemic vigilance by suspending the immediate acceptance of the pediatrician's advice in favor of inserting expansions that make it relevant for the pediatrician to account for her advice. Once the pediatrician has addressed parents' concerns, parents perform (delayed) acceptance, which we assume indexes what we call responsible epistemic trust. While acknowledging the advantages of what seems to be a cultural change in parent-healthcare provider encounters, in the conclusion we advance that possible risks are implied in contemporary fuzziness of the legitimacy and extension criteria of expertise in doctor-patient interaction.
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Efteli E, Çömez S. Effects of Web-Assisted Education on Nursing Students' Pressure Injury Knowledge Levels. Adv Skin Wound Care 2024; 37:1-5. [PMID: 38506585 DOI: 10.1097/asw.0000000000000116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/21/2024]
Abstract
OBJECTIVE To investigate the effect of web-assisted education on the pressure injury knowledge levels of nursing students. METHODS The study was conducted with 106 first-year students in the Nursing Department. Those who received both web-assisted education and conventional education were assigned to the experimental group, and those who received only conventional education were assigned to the control group. The authors used arithmetic mean, percentages, Student t test, and χ2 test to analyze the data. RESULTS The rate of the correct responses given to the questions by the students was 97.55% in the experimental group and 85.15% in the control group. The comparison of the mean number of correct answers revealed a statistically significant difference between the two groups. CONCLUSIONS The authors conclude that the web-supported education given to nursing students in addition to the conventional education positively contributed to their learning level.
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Affiliation(s)
- Elçin Efteli
- In the Faculty of Health Sciences, Mehmet Akif Ersoy University, Burdur, Turkey, Elçin Efteli, PhD, RN, and Saadet Çömez, PhD, RN, are Assistant Professors
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Ng R, Indran N. Youth is Prized in Medicine, Old Age is Valued in Law: Analysis of Media Narratives Over 200 Years. J Med Internet Res 2024; 26:e45855. [PMID: 38530338 DOI: 10.2196/45855] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Revised: 03/13/2023] [Accepted: 08/31/2023] [Indexed: 03/27/2024] Open
Abstract
BACKGROUND This is the first study to explore how age has influenced depictions of doctors and lawyers in the media over the course of 210 years, from 1810 to 2019. The media represents a significant platform for examining age stereotypes and possesses tremendous power to shape public opinion. Insights could be used to improve depictions of older professionals in the media. OBJECTIVE This study aims to understand how age shapes the portrayals of doctors and lawyers. Specifically, it compares the difference in sentiments toward younger and older doctors as well as younger and older lawyers in the media over 210 years. METHODS Leveraging a 600-million-word corpus of American media publications spanning 210 years, we compiled top descriptors (N=478,452) of nouns related to youth × occupation (eg, younger doctor or physician) and old age × occupation (eg, older lawyer or attorney). These descriptors were selected using well-established criteria including co-occurrence frequency and context relevance, and were rated on a Likert scale from 1 (very negative) to 5 (very positive). Sentiment scores were generated for "doctor/physician," "young(er) doctor/physician," "old(er) doctor/physician," "lawyer/attorney," "young(er) lawyer/attorney," and "old(er) lawyer/attorney." The scores were calculated per decade for 21 decades from 1810 to 2019. Topic modeling was conducted on the descriptors of each occupation in both the 1800s and 1900s using latent Dirichlet allocation. RESULTS As hypothesized, the media placed a premium on youth in the medical profession, with portrayals of younger doctors becoming 10% more positive over 210 years, and those of older doctors becoming 1.4% more negative. Meanwhile, a premium was placed on old age in law. Positive portrayals of older lawyers increased by 22.6% over time, while those of younger lawyers experienced a 4.3% decrease. In the 1800s, narratives on younger doctors revolved around their participation in rural health care. In the 1900s, the focus shifted to their mastery of new medical technologies. There was no marked change in narratives surrounding older doctors from the 1800s to the 1900s, though less attention was paid to their skills in the 1900s. Narratives on younger lawyers in the 1800s referenced their limited experience. In the 1900s, there was more focus on courtroom affairs. In both the 1800s and 1900s, narratives on older lawyers emphasized their prestige, especially in the 1900s. CONCLUSIONS Depending on the occupation, one's age may either be seen as an asset or a liability. Efforts must be expended to ensure that older professionals are recognized for their wealth of knowledge and skills. Failing to capitalize on the merits of an older workforce could ultimately be a grave disservice not only to older adults but to society in general.
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Affiliation(s)
- Reuben Ng
- Lee Kuan Yew School of Public Policy, National University of Singapore, Singapore, Singapore
- Lloyd's Register Foundation Institute for the Public Understanding of Risk, National University of Singapore, Singapore, Singapore
| | - Nicole Indran
- Lee Kuan Yew School of Public Policy, National University of Singapore, Singapore, Singapore
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López-García A, Gómez-Hernández M, Gándara E. Variation in traditional knowledge of culturally important macromycete species among three indigenous communities of Oaxaca, Mexico. J Ethnobiol Ethnomed 2024; 20:38. [PMID: 38519986 PMCID: PMC10958891 DOI: 10.1186/s13002-024-00679-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/03/2024] [Accepted: 03/18/2024] [Indexed: 03/25/2024]
Abstract
BACKGROUND For centuries, wild mushrooms have been a forest resource of significant cultural value in several ethnic groups worldwide. In Mexico, extensive traditional knowledge on the use of fungal resources has been developed and deeply rooted. Mexico is the second country in the world in which the most species of wild mushroom are consumed, and it is considered a pioneer in ethnomycology. Nonetheless, there are still many indigenous groups in this country that have not been studied from an ethnomycological approach. The present study aimed to record the traditional knowledge on wild mushrooms in three indigenous groups of the state of Oaxaca, Mexico, and assess the variation in this knowledge within and across the studied groups. METHODS The data were recorded from April to October 2022 within three communities belonging to the indigenous groups Chatino, Chontal, and Chinanteco. Through 84 interviews, information related to their knowledge of wild mushrooms was obtained. The cultural significance index of wild edible mushrooms was calculated for each community. Regression analyses, analysis of variance and covariance, t test, and non-metric multidimensional scaling analysis were performed to assess the distribution of traditional knowledge in the communities. RESULTS A total of 32 culturally important mushroom species were recorded for the three indigenous groups (30 edible, 2 medicinal); 23 used by Chatinos, 16 by Chontales, and 6 by Chinantecos. Only Chatinos and Chinantecos use wild mushrooms in medicine. The cultural significance of wild edible mushrooms differed among groups. Traditional knowledge about wild mushrooms declines when the level of schooling increases and age decreases, especially in the Chatino group. This knowledge distributes more homogeneously in the Chontal and Chinanteco groups. Their age determines the difference in knowledge between men and women. CONCLUSION Documenting how traditional knowledge differs among ethnic groups is relevant for preserving cultural and biological diversity. Factors such as level of schooling and age can affect traditional knowledge of wild mushrooms, but the effects of these factors vary within and across communities. Conducting studies encompassing a broader range of variables is of interest for a better understanding of the human-mushroom relationship.
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Affiliation(s)
- Alexanders López-García
- Centro Interdisciplinario de Investigación para el Desarrollo Integral Regional, Unidad Oaxaca, Instituto Politécnico Nacional, Hornos No. 1003, CP 71230, Santa Cruz Xoxocotlán, Oaxaca, Mexico
| | - Marko Gómez-Hernández
- CONAHCYT. Centro Interdisciplinario de Investigación para el Desarrollo Integral Regional, Unidad Oaxaca, Instituto Politécnico Nacional, Hornos No. 1003, CP 71230, Santa Cruz Xoxocotlán, Oaxaca, Mexico.
| | - Etelvina Gándara
- Facultad de Ciencias Biológicas, Benemérita Universidad Autónoma de Puebla, Av. San Claudio S/N Col. Ciudad Universitaria, CP 72592, Puebla, Mexico.
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Maloney LT, Dal Martello MF, Fei V, Ma V. A comparison of human and GPT-4 use of probabilistic phrases in a coordination game. Sci Rep 2024; 14:6835. [PMID: 38514688 PMCID: PMC10958015 DOI: 10.1038/s41598-024-56740-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Accepted: 03/11/2024] [Indexed: 03/23/2024] Open
Abstract
English speakers use probabilistic phrases such as likely to communicate information about the probability or likelihood of events. Communication is successful to the extent that the listener grasps what the speaker means to convey and, if communication is successful, individuals can potentially coordinate their actions based on shared knowledge about uncertainty. We first assessed human ability to estimate the probability and the ambiguity (imprecision) of twenty-three probabilistic phrases in a coordination game in two different contexts, investment advice and medical advice. We then had GPT-4 (OpenAI), a Large Language Model, complete the same tasks as the human participants. We found that GPT-4's estimates of probability both in the Investment and Medical Contexts were as close or closer to that of the human participants as the human participants' estimates were to one another. However, further analyses of residuals disclosed small but significant differences between human and GPT-4 performance. Human probability estimates were compressed relative to those of GPT-4. Estimates of probability for both the human participants and GPT-4 were little affected by context. We propose that evaluation methods based on coordination games provide a systematic way to assess what GPT-4 and similar programs can and cannot do.
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Affiliation(s)
- Laurence T Maloney
- Department of Psychology, New York University, 6 Washington Place, Room 574, New York, NY, 10012, USA.
- Center for Neural Science, New York University, 6 Washington Place, New York, NY, 10012, USA.
| | - Maria F Dal Martello
- Department of Psychology, New York University, 6 Washington Place, Room 574, New York, NY, 10012, USA
- Dipartmento di Psicologia Generale, Università di Padova, Via Venezia 8, Padua, Italy
| | - Vivian Fei
- Department of Psychology, New York University, 6 Washington Place, Room 574, New York, NY, 10012, USA
| | - Valerie Ma
- Department of Psychology, New York University, 6 Washington Place, Room 574, New York, NY, 10012, USA
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Schallenburger M, Schwartz J, Batzler YN, Meier S, Küppers R, Tenge T, Doll A, Kremeike K, Wetzchewald D, Neukirchen M. Handling the desire to die- evaluation of an elective course for medical students. BMC Med Educ 2024; 24:279. [PMID: 38494509 PMCID: PMC10946106 DOI: 10.1186/s12909-024-05269-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Accepted: 03/06/2024] [Indexed: 03/19/2024]
Abstract
BACKGROUND The desire to die can occur in palliative care patients with a prevalence of up to 22%. Not every desire to die is accompanied by a pressure to act, but usually by a burden that can arise from various factors. To address this burden appropriately, health care workers should be trained. Based on an evaluated course on handling the desire to die, an elective course for medical students was developed and evaluated. In order to identify the impact of the elective course's content, a comparison of attitudes towards assisted dying with two other participant groups was conducted. Therefore, three questions from the evaluation of the elective course were used. METHOD Online evaluation of the elective and questions addressing attitude were assessed using a five-point Likert scale. The specific outcome-based assessment was determined using the Comparative Self-Assessment Gain. The main participant group (group 1) were students who took the elective. The additional survey on attitudes towards assisted dying included undergraduate medical students who had taken compulsory palliative care courses (group 2) and physicians who had taken an introductory course in intensive care or emergency medicine (group 3). RESULTS Group 1 (n = 13, response rate rr = 86.7%) was very satisfied with the blended learning format (100%) and the course itself (100%). They were able to deepen their knowledge (81.0%) and train skills (71.2%) through the course. In the additional surveys, there were 37 students in group 2 (rr = 66.1%) and 258 physicians in group 3 (rr = 73.6%). Willingness to assist with or accompany the various options for assisted dying varied according to the type of assistance. Among the participants, it can be summarised that the highest willingness was shown by the students of group 2 followed by the physicians of group 3 and the students of group 1. CONCLUSIONS A course on handling the desire to die of palliative patients can deepen knowledge and train communication skills and thus support self-confidence. Dealing with the background of the desire to die, knowledge about assisted dying, but also one's own attitudes and responsibilities can influence the attitude towards assisted dying.
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Affiliation(s)
- M Schallenburger
- Interdisciplinary Centre for Palliative Medicine, Heinrich-Heine-University Duesseldorf, University Hospital Duesseldorf, Duesseldorf, Germany
- Centre of Integrated Oncology Aachen Bonn Cologne Duesseldorf (CIO ABCD), Cologne, Germany
| | - J Schwartz
- Interdisciplinary Centre for Palliative Medicine, Heinrich-Heine-University Duesseldorf, University Hospital Duesseldorf, Duesseldorf, Germany
- Centre of Integrated Oncology Aachen Bonn Cologne Duesseldorf (CIO ABCD), Cologne, Germany
| | - Yann-Nicolas Batzler
- Interdisciplinary Centre for Palliative Medicine, Heinrich-Heine-University Duesseldorf, University Hospital Duesseldorf, Duesseldorf, Germany.
- Centre of Integrated Oncology Aachen Bonn Cologne Duesseldorf (CIO ABCD), Cologne, Germany.
| | - St Meier
- Department of Anaesthesiology, Heinrich-Heine-University Duesseldorf, University Hospital Duesseldorf, Duesseldorf, Germany
| | - R Küppers
- Department of Anaesthesiology, Heinrich-Heine-University Duesseldorf, University Hospital Duesseldorf, Duesseldorf, Germany
| | - Th Tenge
- Department of Anaesthesiology, Heinrich-Heine-University Duesseldorf, University Hospital Duesseldorf, Duesseldorf, Germany
| | - A Doll
- Centre of Integrated Oncology Aachen Bonn Cologne Duesseldorf (CIO ABCD), Cologne, Germany
- Centre for Palliative Medicine, University Cologne, University Hospital Cologne, Cologne, Germany
| | - K Kremeike
- Centre of Integrated Oncology Aachen Bonn Cologne Duesseldorf (CIO ABCD), Cologne, Germany
- Centre for Palliative Medicine, University Cologne, University Hospital Cologne, Cologne, Germany
| | - D Wetzchewald
- Institute for Emergency Medicine, University Witten/Herdecke, Arnsberg, Germany
| | - M Neukirchen
- Interdisciplinary Centre for Palliative Medicine, Heinrich-Heine-University Duesseldorf, University Hospital Duesseldorf, Duesseldorf, Germany
- Centre of Integrated Oncology Aachen Bonn Cologne Duesseldorf (CIO ABCD), Cologne, Germany
- Department of Anaesthesiology, Heinrich-Heine-University Duesseldorf, University Hospital Duesseldorf, Duesseldorf, Germany
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Yazdizadeh B, Ahmadi A, Najafi F, Mohammad K, Fariden M, Khalili D, Mahdavi M, Rahimpour E, Jouyban A, Kelishadi R, Monazzam MR, Eftekhari MB, Falahat K, Nikooee S, Majdzadeh R. Establishing research impact assessment in Iran: The first report from a non-high-income country. J Glob Health 2024; 14:04050. [PMID: 38483444 PMCID: PMC10939117 DOI: 10.7189/jogh.14.04050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/17/2024] Open
Abstract
Background This study presents the first report on research impact assessment (RIA) in non-high-income countries, undertaken as a pilot initiative in 2021. Within it, we aimed to explore the feasibility of employing the 'payback' model for evaluating the impact of health research and enhancing the accountability of universities. We focussed on three key impact domains: 'production of decision support documents and knowledge-based products,' 'implementation of research results,' and 'health and economic impact.' Methods We adopted a case study approach to assess the impact of 5334 health research projects conducted by researchers from 18 universities from 2018 to 2020. Researchers were required to submit evidence related to at least one of the specified impact domains; six scientific committees verified and scored claimed impacts at the national level. Results Only 25% of the assessed projects achieved impact in at least one domain, with the production of decision support documents and knowledge products being the most reported impact. Notably, economic impact was verified in only three projects, indicating room for improvement in this area. Technology research exhibited the highest acceptance rate of claimed impact, suggesting a positive correlation between technology-focused projects and impactful outcomes. Conclusions This study demonstrates the feasibility of employing a case study approach and the 'payback' model to evaluate the impact of health research, even within the constraints of a moderately equipped research infrastructure. These findings underscore the potential of integrating RIA into the governance of health research in Iran and other non-high-income countries, as well as the importance of using RIA to assess the accountability of health research systems, guide the allocation of research funding, and advocate for the advancement of health research. The study sets a precedent for future assessments in similar contexts and contributes to the ongoing global dialogue on the societal impact of health research.
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Affiliation(s)
- Bahareh Yazdizadeh
- Knowledge Utilization Research Center, Tehran University of Medical Sciences, Tehran, Iran
- Equal contribution
| | - Ayat Ahmadi
- Knowledge Utilization Research Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Farid Najafi
- Research Center for Environmental Determinants of Health, Health Institute, Kermanshah University of Medical Sciences, Kermanshah, Iran
| | - Kazem Mohammad
- Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
| | - Mohammad Fariden
- Environmental Health Research Center, Department of Occupational Health and Safety at Work Engineering, Lorestan University of Medical Sciences, Khorramabad, Iran
| | - Davood Khalili
- Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Mahdi Mahdavi
- National Institute for Health Research, Tehran University of Medical Sciences, Tehran, Iran
| | - Elaheh Rahimpour
- Pharmaceutical Analysis Research Center and Faculty of Pharmacy, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Abolghasem Jouyban
- Pharmaceutical Analysis Research Center and Faculty of Pharmacy, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Roya Kelishadi
- Child Growth and Development Research Center, Research Institute for Primordial Prevention of Non-Communicable Disease, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Mohammad Reza Monazzam
- Department of Occupational Health Engineering, School of Public Health, Tehran University of Medical Sciences
| | | | - Katayoun Falahat
- Deputy for Research and Technology, Ministry of Health and Medical Education, Tehran, Iran
| | - Sima Nikooee
- Knowledge Utilization Research Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Reza Majdzadeh
- School of Health and Social Care, University of Essex, Colchester, UK
- Equal contribution
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Huang Y, Lau CW. Can digital transformation promote the green innovation quality of enterprises? Empirical evidence from China. PLoS One 2024; 19:e0296058. [PMID: 38466672 PMCID: PMC10927151 DOI: 10.1371/journal.pone.0296058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2023] [Accepted: 12/05/2023] [Indexed: 03/13/2024] Open
Abstract
Digital transformation constitutes a crucial component of the digital economy and represents a microcosmic manifestation, playing a vital role in advancing enterprise sustainable development from the perspective of green innovation quality. Using the panel data of Chinese listed companies from 2011 to 2020, the study examines the impact of digital transformation on the quality of green innovation. The study finds that digital transformation significantly increases the green innovation quality of enterprises. Moreover, the positive effect of digital transformation on green innovation quality is strengthened by the executive with digital knowledge experience and in regions with high-level intellectual property protection. The study findings contribute to digitalization research and the literature on green innovation, and provide suggestions for managers and policymakers seeking to improve the quality of environmental sustainability through digital transformation in developing economies.
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Affiliation(s)
- Yang Huang
- School of Business, Macau University of Science and Technology, Macau, China
| | - Chau-wa Lau
- School of Management, Jinan University, Guangzhou, China
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Stribling D, Xia Y, Amer MK, Graim KS, Mulligan CJ, Renne R. The model student: GPT-4 performance on graduate biomedical science exams. Sci Rep 2024; 14:5670. [PMID: 38453979 PMCID: PMC10920673 DOI: 10.1038/s41598-024-55568-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Accepted: 02/25/2024] [Indexed: 03/09/2024] Open
Abstract
The GPT-4 large language model (LLM) and ChatGPT chatbot have emerged as accessible and capable tools for generating English-language text in a variety of formats. GPT-4 has previously performed well when applied to questions from multiple standardized examinations. However, further evaluation of trustworthiness and accuracy of GPT-4 responses across various knowledge domains is essential before its use as a reference resource. Here, we assess GPT-4 performance on nine graduate-level examinations in the biomedical sciences (seven blinded), finding that GPT-4 scores exceed the student average in seven of nine cases and exceed all student scores for four exams. GPT-4 performed very well on fill-in-the-blank, short-answer, and essay questions, and correctly answered several questions on figures sourced from published manuscripts. Conversely, GPT-4 performed poorly on questions with figures containing simulated data and those requiring a hand-drawn answer. Two GPT-4 answer-sets were flagged as plagiarism based on answer similarity and some model responses included detailed hallucinations. In addition to assessing GPT-4 performance, we discuss patterns and limitations in GPT-4 capabilities with the goal of informing design of future academic examinations in the chatbot era.
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Affiliation(s)
- Daniel Stribling
- Department of Molecular Genetics and Microbiology, University of Florida, Gainesville, FL, 32610, USA.
- UF Genetics Institute, University of Florida, Gainesville, FL, 32610, USA.
- UF Health Cancer Center, University of Florida, Gainesville, FL, 32610, USA.
| | - Yuxing Xia
- Department of Neuroscience, Center for Translational Research in Neurodegenerative Disease, College of Medicine, University of Florida, Gainesville, FL, 32610, USA
- Department of Neurology, UCLA, Los Angeles, CA, 90095, USA
| | - Maha K Amer
- Department of Molecular Genetics and Microbiology, University of Florida, Gainesville, FL, 32610, USA
| | - Kiley S Graim
- Department of Computer and Information Science and Engineering, Herbert Wertheim College of Engineering, University of Florida, Gainesville, FL, 32610, USA
| | - Connie J Mulligan
- UF Genetics Institute, University of Florida, Gainesville, FL, 32610, USA
- Department of Anthropology, University of Florida, Gainesville, FL, 32610, USA
| | - Rolf Renne
- Department of Molecular Genetics and Microbiology, University of Florida, Gainesville, FL, 32610, USA.
- UF Genetics Institute, University of Florida, Gainesville, FL, 32610, USA.
- UF Health Cancer Center, University of Florida, Gainesville, FL, 32610, USA.
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Severinsen C, Neely E, Hutson R. Resisting stigma: the role of online communities in young mothers' successful breastfeeding. Int Breastfeed J 2024; 19:17. [PMID: 38448916 PMCID: PMC10918889 DOI: 10.1186/s13006-024-00626-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Accepted: 03/01/2024] [Indexed: 03/08/2024] Open
Abstract
BACKGROUND Breastfeeding initiation and continuation rates are shaped by complex and interrelated determinants across individual, interpersonal, community, organisational, and policy spheres. Young mothers, however, face a double burden of stigma, being perceived as immature and incompetent in their mothering and breastfeeding abilities. In this study, we aimed to understand the experiences of young mothers who exclusively breastfed for six months and beyond and explore their experiences of stigma and active resistance through social media. METHODS In 2020, in-depth telephone interviews about breastfeeding experiences were conducted with 44 young mothers under age 25 in Aotearoa New Zealand who breastfed for six months or longer. Participants were recruited via social media. Interviews were audio-recorded, transcribed and analysed thematically. RESULTS Analysis yielded four themes on young mothers' negotiation of breastfeeding and support. The first three themes revealed young mothers' encounters with socio-cultural contexts. They faced negative judgments about maturity and competence, adverse guidance to supplement or cease breastfeeding, and an undermining of their breastfeeding efforts. The fourth theme showed how young mothers sought alternative support in online environments to avoid negative interactions. Online spaces provided anonymity, convenience, experiential knowledge and social connections with shared values. This facilitated identity strengthening, empowerment and stigma resistance. CONCLUSION Our research highlights the importance of online communities as a tool for young mothers to navigate and resist the societal stigmas surrounding breastfeeding. Online spaces can provide a unique structure that can help counteract the adverse effects of social and historical determinants on breastfeeding rates by fostering a sense of inclusion and support. These findings have implications for the development of breastfeeding promotion strategies for young mothers and highlight the potential of peer support in counteracting the negative impacts of stigma. The research also sheds light on the experiences of young mothers within the health professional relationship and the effects of stigma and cultural health capital on their engagement and withdrawal from services. Further research should examine how sociocultural barriers to breastfeeding stigmatise and marginalise young mothers and continue to reflect on their socio-political and economic positioning and how it can exacerbate inequities.
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Affiliation(s)
- Christina Severinsen
- School of Health Sciences, Massey University, Palmerston North, Aotearoa, New Zealand.
| | - Eva Neely
- School of Health, Victoria University of Wellington, Wellington, Aotearoa, New Zealand
| | - Rochelle Hutson
- School of Health Sciences, Massey University, Palmerston North, Aotearoa, New Zealand
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Amano K, Koshimoto S, Arakawa S, Oyamada S, Ishiki H, Morita T, Takeuchi T, Satomi E, Mori N. Factors associated with multimodal care practices for cancer cachexia among registered dietitians. Support Care Cancer 2024; 32:213. [PMID: 38446230 DOI: 10.1007/s00520-024-08417-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Accepted: 02/29/2024] [Indexed: 03/07/2024]
Abstract
PURPOSE This study aimed to determine factors associated with multimodal care practices for cancer cachexia among registered dietitians (RDs) working in cancer care. METHODS A secondary analysis was performed using RDs' data. Data on knowledge, skills, and confidence in multimodal care were obtained. Nine items regarding multimodal care practices were evaluated. Subjects were divided into two groups based on their answers associated with the nine items. Comparisons were obtained using the Mann-Whitney U test or chi-squared test. Multiple regression analysis was performed to identify the critical factors involved in practicing multimodal care by determining the variables with significant differences between the two groups. RESULTS Two hundred thirty-two RDs were included in this study. Significant differences were observed in their primary area of practice (p = 0.023), the number of clinical guidelines used (p < 0.001), the number of items used in cancer cachexia assessment (p = 0.002), the number of symptoms used in cancer cachexia assessment (p = 0.039), training for cancer cachexia (p < 0.001), knowledge of cancer cachexia (p < 0.001), and confidence in cancer cachexia management (p < 0.001). The number of symptoms used in cancer cachexia assessment (B = 0.42, p = 0.019), knowledge of cancer cachexia (B = 6.60, p < 0.001), and confidence in cancer cachexia management (B = 4.31, p = 0.010) were identified as critical factors according to the multiple regression analysis. CONCLUSION The RDs' knowledge and confidence in cancer cachexia management were associated with their multimodal care practices.
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Affiliation(s)
- Koji Amano
- Palliative and Supportive Care Center, Osaka University Hospital, 2-15 Yamadaoka, Suita, Osaka, 565-0871, Japan.
- Department of Psycho-Oncology and Palliative Medicine, Osaka International Cancer Institute, 3-1-69 Otemae, Chuo-Ku, Osaka, 541-8567, Japan.
- Department of Palliative and Supportive Medicine, Graduate School of Medicine, Aichi Medical University, 1-1 Yazakokarimata, Nagakute City, Aichi, 480-1195, Japan.
- Department of Palliative Medicine, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045, Japan.
| | - Saori Koshimoto
- School of Health Care Sciences, Faculty of Medicine, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-Ku, Tokyo, 113-8519, Japan
- Faculty of Human Nutrition, Department of Human Nutrition, Tokyo Kasei Gakuin University, 22 Sanban-Cho, Chiyoda-Ku, Tokyo, 102-8341, Japan
| | - Sayaka Arakawa
- Department of Palliative Medicine, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045, Japan
| | - Shunsuke Oyamada
- Department of Biostatistics, JORTC Data Center, 2-54-6-302 Nishi-Nippori, Arakawa-Ku, Tokyo, 116-0013, Japan
| | - Hiroto Ishiki
- Department of Palliative Medicine, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045, Japan
| | - Tatsuya Morita
- Palliative and Supportive Care Division, Seirei Mikatahara General Hospital, 3453 Mikatahara-Cho, Kita-Ku, Hamamatsu City, Shizuoka, 433-8558, Japan
| | - Takashi Takeuchi
- Liaison Psychiatry and Psycho-Oncology Unit, Department of Psychiatry and Behavioral Sciences, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-Ku, Tokyo, 113-8510, Japan
| | - Eriko Satomi
- Department of Palliative Medicine, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045, Japan
| | - Naoharu Mori
- Department of Palliative and Supportive Medicine, Graduate School of Medicine, Aichi Medical University, 1-1 Yazakokarimata, Nagakute City, Aichi, 480-1195, Japan
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