Dataset of mathematics learning and assessment of higher education students using the MathE platform

Higher education institutions are promoting the adoption of innovative methodologies and instructional approaches to engage and promote personalized learning paths to their students. Several strategies based on gamification, artificial intelligence, and data mining are adopted to create an interactive educational setting centred around students. Within this personalized learning environment, there is a notable boost in student engagement and enhanced educational outcomes. The MathE platform, an online educational system introduced in 2019, is specifically crafted to support students tackling difficulties in comprehending higher-education-level mathematics or those aspiring to deepen their understanding of diverse mathematical topics - all at their own pace. The MathE platform provides multiple-choice questions, categorized under topics and subtopics, aligning with the content taught in higher education courses. Accessible to students worldwide, the platform enables them to train their mathematical skills through these resources. When the students log in to the training area of the platform, they choose a topic to study and specify whether they prefer basic or advanced questions. The platform then selects a set of seven multiple-choice questions from the available ones under the chosen topic and generates a test for the student. After completing and submitting the test, the answers are recorded and stored on the platform. This paper describes the data stored in the MathE platform, focusing on the 9546 answers to 833 questions, provided by 372 students from 8 countries who use the platform to practice their skills using the questions (and other resources) available on the platform. The information in this paper will help research about active learning tools to support the improvement of future education, especially at higher educational level. Furthermore, these data are valuable for understanding student learning patterns, assessing platform efficacy, gaining a global perspective on mathematics education, and contributing to the advancement of active learning tools for higher education.

Application of machine learning in dementia diagnosis: A systematic literature review

According to the World Health Organization forecast, over 55 million people worldwide have dementia, and about 10 million new cases are detected yearly. Early diagnosis is essential for patients to plan for the future and deal with the disease. Machine Learning algorithms allow us to solve the problems associated with early disease detection. This work attempts to identify the current relevance of the application of machine learning in dementia prediction in the scientific world and suggests open fields for future research. The literature review was conducted by combining bibliometric and content analysis of articles originating in a period of 20 years in the Scopus database. Twenty-seven thousand five hundred twenty papers were identified firstly, of which a limited number focused on machine learning in dementia diagnosis. After the exclusion process, 202 were selected, and 25 were chosen for analysis. The recent increasing interest in the past five years in the theme of machine learning in dementia shows that it is a relevant field for research with still open questions. The methods used to identify dementia or what features are used to identify or predict this disease are explored in this study. The literature review revealed that most studies used magnetic resonance imaging (MRI) and its types as the main feature, accompanied by demographic data such as age, gender, and the mini-mental state examination score (MMSE). Data are usually acquired from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Classification of Alzheimer's disease is more prevalent than prediction of Mild Cognitive Impairment (MCI) or their combination. The authors preferred machine learning algorithms such as SVM, Ensemble methods, and CNN because of their excellent performance and results in previous studies. However, most use not one machine-learning technique but a combination of techniques. Despite achieving good results in the studies considered, there are new concepts for future investigation declared by the authors and suggestions for improvements by employing promising methods with potentially significant results.

Do Childcare Teachers Evaluate Children's Weight Status More Accurately Than Parents? A Brief Report

PURPOSE

Parents' underestimation of young children's weight can reduce their engagement and readiness to implement changes in children's diet and physical activity. Childcare teachers can support parents' identification of children at risk for being overweight only if they can accurately do this themselves.

DESIGN

Quantitative, cross-sectional study.

SETTING

Fifteen kindergartens near Lisbon, Portugal.

SUBJECTS

319 parents, 32 teachers (47.5% and 100% response rate, respectively), and 319 children.

MEASURES

Caregivers classified the children's weight, considering their height and age as underweight, healthy weight, or overweight; children's body mass index (BMI) status for age and sex was assessed.

ANALYSIS

Differences in caregivers' accuracy of children's weight perception were assessed. Multilevel multivariate logistic regression models were used to analyze the predictors of the accuracy of teachers' and parents' weight perception as a binary outcome.

RESULTS

The proportion of children with overweight correctly assessed differed significantly (P = 0.004) between teachers (31.1%) and parents (17.5%). The child's BMI percentile was the only significant positive predictor for both caregivers' weight perception accuracy (P < 0.001 and P = 0.004, for parents and teachers, respectively), holding the child's age and sex constant.

CONCLUSION

Although childcare teachers were better raters than parents when evaluating children's weight status, the percentage of children with overweight that childcare teachers misclassified was still relatively high.

Data Acquisition Filtering Focused on Optimizing Transmission in a LoRaWAN Network Applied to the WSN Forest Monitoring System

Developing innovative systems and operations to monitor forests and send alerts in dangerous situations, such as fires, has become, over the years, a necessary task to protect forests. In this work, a Wireless Sensor Network (WSN) is employed for forest data acquisition to identify abrupt anomalies when a fire ignition starts. Even though a low-power LoRaWAN network is used, each module still needs to save power as much as possible to avoid periodic maintenance since a current consumption peak happens while sending messages. Moreover, considering the LoRaWAN characteristics, each module should use the bandwidth only when essential. Therefore, four algorithms were tested and calibrated along real and monitored events of a wildfire. The first algorithm is based on the Exponential Smoothing method, Moving Averages techniques are used to define the other two algorithms, and the fourth uses the Least Mean Square. When properly combined, the algorithms can perform a pre-filtering data acquisition before each module uses the LoRaWAN network and, consequently, save energy if there is no necessity to send data. After the validations, using Wildfire Simulation Events (WSE), the developed filter achieves an accuracy rate of 0.73 with 0.5 possible false alerts. These rates do not represent a final warning to firefighters, and a possible improvement can be achieved through cloud-based server algorithms. By comparing the current consumption before and after the proposed implementation, the modules can save almost 53% of their batteries when is no demand to send data. At the same time, the modules can maintain the server informed with a minimum interval of 15 min and recognize abrupt changes in 60 s when fire ignition appears.

A robot localization proposal for the RobotAtFactory 4.0: A novel robotics competition within the Industry 4.0 concept

Robotic competitions are an excellent way to promote innovative solutions for the current industries’ challenges and entrepreneurial spirit, acquire technical and transversal skills through active teaching, and promote this area to the public. In other words, since robotics is a multidisciplinary field, its competitions address several knowledge topics, especially in the STEM (Science, Technology, Engineering, and Mathematics) category, that are shared among the students and researchers, driving further technology and science. A new competition encompassed in the Portuguese Robotics Open was created according to the Industry 4.0 concept in the production chain. In this competition, RobotAtFactory 4.0, a shop floor, is used to mimic a fully automated industrial logistics warehouse and the challenges it brings. Autonomous Mobile Robots (AMRs) must be used to operate without supervision and perform the tasks that the warehouse requests. There are different types of boxes which dictate their partial and definitive destinations. In this reasoning, AMRs should identify each and transport them to their destinations. This paper describes an approach to the indoor localization system for the competition based on the Extended Kalman Filter (EKF) and ArUco markers. Different innovation methods for the obtained observations were tested and compared in the EKF. A real robot was designed and assembled to act as a test bed for the localization system’s validation. Thus, the approach was validated in the real scenario using a factory floor with the official specifications provided by the competition organization.

Portuguese Football Federation consensus statement 2020: nutrition and performance in football

Nutrition is an undeniable part of promoting health and performance among football (soccer) players. Nevertheless, nutritional strategies adopted in elite football can vary significantly depending on culture, habit and practical constraints and might not always be supported by scientific evidence. Therefore, a group of 28 Portuguese experts on sports nutrition, sports science and sports medicine sought to discuss current practices in the elite football landscape and review the existing evidence on nutritional strategies to be applied when supporting football players. Starting from understanding football's physical and physiological demands, five different moments were identified: preparing to play, match-day, recovery after matches, between matches and during injury or rehabilitation periods. When applicable, specificities of nutritional support to young athletes and female players were also addressed. The result is a set of practical recommendations that gathered consensus among involved experts, highlighting carbohydrates periodisation, hydration and conscious use of dietary supplements.

Mathematics learning and assessment using MathE platform: A case study

Universities are encouraging the implementation of innovative methodologies and teaching strategies to develop an interactive and appealing educational environment where students are the focus of the learning process. In such a personalised learning environment, an increase of the students' engagement and the improvement of the outcomes arise. MathE has been developed to help achieve this goal. Based on collaborative procedures, internet resources - both pre-existing and freely available as well as resources specifically conceived by the project team - and communities of practices, MathE intends to be a tool to nurture and stimulate the learning of Mathematics in higher education. This study introduces and describes the MathE platform, which is divided into three sections: Student's Assessment, Library and Community of Practice. An in-depth description of the Student's Assessment section is presented and an analysis of the results obtained from students, when using this feature of the platform, is also provided. After this, and based on the answers to an online survey, the impact of the MathE platform among students and teachers of eight countries is shown. Although the number of collected results is still scarce, it allows the recognition of a trend regarding the use of the material of the Student's Assessment section for autonomous study. The results indicate the platform is well organized, with a satisfactory amount and diversity of questions and good interconnection between the various parts. Nevertheless, both teachers and students indicate that more questions should be introduced. The overall opinion about the MathE platform is very favourable.

Cardiac arrest after a cerebral gas embolism. Case report

Cerebral arterial gas embolism is a serious and often iatrogenic fatal event associated with invasive procedures. It is a possible cause of a cardiac arrest and the diagnosis is challenging. We report a case of a cardiac arrest after a cerebral arterial gas embolism, in a 63-year-old male subjected to a Computed Tomography-guided Transthoracic Needle Aspiration Biopsy, which was successfully managed with hyperbaric oxygen therapy.

Effectiveness of a combined surf and psychological preventive intervention with children and adolescents in residential childcare: A randomized controlled trial

Children and adolescents living in residential childcare have a higher prevalence of mental health problems as a result of a history of adverse childhood experiences. Therefore, this population should be a priority target for mental health preventive interventions. The current study analyses the effectiveness of the Wave by Wave surf therapy program, that combines surfing with a psychological group intervention, through a randomized controlled trial. Seventy-three youth (7-17 years) living in residential care participated in the study. Main mental health outcomes (adjustment problems, depression, anxiety, and wellbeing) and secondary outcomes (self-efficacy, self-regulation, sleep quality, physical activity, pro-social behavior, and social connectivity) were assessed at pre- and post-intervention. The results indicated a significant impact of the intervention on mental health outcomes reported by the key residential worker, with medium to large effect sizes. Specifically, after the intervention, there was a significant reduction in the total emotional and behavioural problems, and a significant increase of youth pro-social behaviour and quality of life that was not observed for the waiting list group. There were no significant effects on other measures reported by the children (e.g., depression and anxiety, self-esteem, emotion regulation, social connectedness, sleep quality, physical activity) and on executive functions measures. The Wave by Wave program seems to be an effective intervention to reduce behavior problems and to promote pro-social behavior in a high-risk sample. The absence of significant effects on other dimensions may indicate the need of some complementary support to address specific difficulties of this population.

Push-Pull N,N-Diphenylhydrazones Bearing Bithiophene or Thienothiophene Spacers as Nonlinear Optical Second Harmonic Generators and as Photosensitizers for Nanocrystalline TiO2 Dye-Sensitized Solar Cells

A series of push-pull heterocyclic N,N-diphenylhydrazones were prepared to study the effect of structural modifications (different π-spacers and electron-withdrawing groups) on the optical (linear and nonlinear) and electronic properties of the molecules. The photovoltaic response of dye-sensitized solar cells assembled using nanocrystalline titania photosensitized with the synthesized dyes was also studied. These heterocyclic push-pull conjugated dyes involve N,N-diphenylhydrazones as electron donors linked to bithiophene or thieno[3,2-b]thiophene spacers and were functionalized with carboxylic acid, cyanoacetic acid, or dicyanovinyl acceptor groups. A combination of Suzuki-Miyaura cross-coupling, Vilsmeier formylation, and condensation reactions was used to synthesize the intermediates and final products. Density functional theory (DFT) and time dependent-DFT calculations were used to obtain information on conformation, electronic structure, and electron distribution, both for the free dyes and those adsorbed on TiO₂. The results of this multidisciplinary study indicate that dyes 5b and 6b have the strongest second-order nonlinear optical response with hyperpolarizability values in the range of β = 2330 × 10^-30 to 2750 × 10^-30 esu, whereas photovoltaic power conversion efficiencies reach values in the range of 0.7-3.0% for dyes 5a-b and 7c and were enhanced by coadsorbing deoxycholic acid (0.8-5.1%).

Deformation of Red Blood Cells, Air Bubbles, and Droplets in Microfluidic Devices: Flow Visualizations and Measurements

Techniques, such as micropipette aspiration and optical tweezers, are widely used to measure cell mechanical properties, but are generally labor-intensive and time-consuming, typically involving a difficult process of manipulation. In the past two decades, a large number of microfluidic devices have been developed due to the advantages they offer over other techniques, including transparency for direct optical access, lower cost, reduced space and labor, precise control, and easy manipulation of a small volume of blood samples. This review presents recent advances in the development of microfluidic devices to evaluate the mechanical response of individual red blood cells (RBCs) and microbubbles flowing in constriction microchannels. Visualizations and measurements of the deformation of RBCs flowing through hyperbolic, smooth, and sudden-contraction microchannels were evaluated and compared. In particular, we show the potential of using hyperbolic-shaped microchannels to precisely control and assess small changes in RBC deformability in both physiological and pathological situations. Moreover, deformations of air microbubbles and droplets flowing through a microfluidic constriction were also compared with RBCs deformability.

International child abuse prevention: insights from ACT Raising Safe Kids

BACKGROUND

Evidence-based practices are often viewed as lofty goals endorsed by wealthy academics in developed nations, but impossible to implement in other contexts. This article will provide evidence suggesting that, to the contrary, we can indeed scale up western-developed parenting interventions that can be both effective and warmly received by parents in diverse cultural and economic contexts.

METHODS/RESULTS

This paper gives a brief overview of the ACT Raising Safe Kids Program and summarizes the results of evaluation studies done with parents around the world. It discusses specific strategies facilitators use to modify the program as necessary to fit cultural contexts while also maintaining fidelity, implementing the manualized curriculum under varied, and complex circumstances.

CONCLUSIONS

It is hoped that the lessons learned from our work will inspire practitioners to adapt ACT or other programs to diverse contexts, evaluate those programs, and thereby improve the mental health and life trajectories of children and families around the world.

A Novel Method for Studying the Pharmacokinetics of [(14) C]Umeclidinium After Application to the Axilla or Palm of Healthy Male Subjects

Umeclidinium (UMEC), a long-acting muscarinic antagonist approved for chronic obstructive pulmonary disease (COPD), was investigated for primary hyperhidrosis as topical therapy. This study evaluated the pharmacokinetics, safety, and tolerability of a single dose of [(14) C]UMEC applied to either unoccluded axilla (UA), occluded axilla (OA), or occluded palm (OP) of healthy males. After 8 h the formulation was removed. [(14) C]UMEC plasma concentrations (Cp) were quantified by accelerator mass spectrometry. Occlusion increased systemic exposure by 3.8-fold. Due to UMEC absorption-limited pharmacokinetics, Cp data from the OA were combined with intravenous data from a phase I study. The data were described by a two-compartment population model with sequential zero and first-order absorption and linear elimination. Simulated systemic exposure following q.d. doses to axilla was similar to the exposure from the inhaled therapy, suggesting that systemic safety following dermal administration can be bridged to the inhaled program, and offering the potential for a reduced number of studies and/or subjects.

Automatic tracking of labeled red blood cells in microchannels

The current study proposes an automatic method for the segmentation and tracking of red blood cells flowing through a 100- μm glass capillary. The original images were obtained by means of a confocal system and then processed in MATLAB using the Image Processing Toolbox. The measurements obtained with the proposed automatic method were compared with the results determined by a manual tracking method. The comparison was performed by using both linear regressions and Bland-Altman analysis. The results have shown a good agreement between the two methods. Therefore, the proposed automatic method is a powerful way to provide rapid and accurate measurements for in vitro blood experiments in microchannels.

Estimation of postmortem interval by hypoxanthine and potassium evaluation in vitreous humor with a sequential injection system

The estimation of the time since death known as postmortem interval (PMI) is a main issue in the field of forensic science and legal medicine. In this work it is proposed a sequential injection system for the determination of hypoxanthine and potassium in the same sample of vitreous humor since the concentrations of both parameters change with PMI and the vitreous humor has been regarded as the ideal extracellular fluid for these kinds of determinations. By measuring both parameters the accuracy of estimation of PMI can be increased, and the effects of factors which influence the values in postmortem chemistry minimized. Hypoxanthine determination is based on its oxidation to uric acid (290 nm), catalyzed by immobilized xanthine oxidase, and the quantification of potassium levels in vitreous humor was performed using a tubular potassium ion-selective electrode. With a unique analytical cycle both analytes were evaluated being potassium levels determined during the degradation of hypoxanthine in the enzymatic reactor. Working concentration ranges between 6.04-40.00 micromol L(-1) and 7.00 x 10(-5) to 1.00 x 10(-1)mmol L(-1) were obtained, for hypoxanthine and potassium, respectively. The method proved to be reproducible with R.S.D. <5% for hypoxanthine and <3% for potassium. Sampling rate was approximately 30 per hour for the sequential determination of both parameters being 15 and 60 determinations per hour if hypoxanthine or potassium, where evaluated independently. Statistical evaluation at the 95% confidence level showed good agreement between the results obtained, for the vitreous humor samples, with both the SIA system and the comparison batch procedures. Moreover the methodology has low environmental impact in agreement with the demands of green analytical chemistry as only 2.7 mL of chemical waste is produced during both determinations.

Determination of the glucocorticoid fluticasone propionate in plasma by automated solid-phase extraction and liquid chromatography-tandem mass spectrometry

A sensitive, robust and high throughput mass spectrometry based method is described for the determination of the glucocorticoid fluticasone propionate in plasma. The method employs solid-phase extraction in 96 well microtitre plate format which has been automated by means of a custom built Zymark robotic system. The extracts are analysed by liquid chromatography-tandem mass spectrometry using thermally and pneumatically assisted electrospray ionisation and selected reaction monitoring. The method is both accurate and precise with both intra- and inter-assay precision (C.V.) of less than <6%. The method provides a lower limit of quantification of 20 pg/ml from 0.5 ml of human plasma, sufficient to monitor systemic concentrations of inhaled fluticasone propionate at therapeutic doses.