Research on Intelligent Vehicle Trajectory Tracking Control Based on Improved Adaptive MPC

Intelligent vehicle trajectory tracking exhibits problems such as low adaptability, low tracking accuracy, and poor robustness in complex driving environments with uncertain road conditions. Therefore, an improved method of adaptive model predictive control (AMPC) for trajectory tracking was designed in this study to increase the corresponding tracking accuracy and driving stability of intelligent vehicles under uncertain and complex working conditions. First, based on the unscented Kalman filter, longitudinal speed, yaw speed, and lateral acceleration were considered as the observed variables of the measurement equation to estimate the lateral force of the front and rear tires accurately in real time. Subsequently, an adaptive correction estimation strategy for tire cornering stiffness was designed, an AMPC method was established, and a dynamic prediction time-domain adaptive model was constructed for optimization according to vehicle speed and road adhesion conditions. The improved AMPC method for trajectory tracking was then realized. Finally, the control effectiveness and trajectory tracking accuracy of the proposed AMPC technique were verified via co-simulation using CarSim and MATLAB/Simulink. From the results, a low lateral position error and heading angle error in trajectory tracking were obtained under different vehicle driving conditions and road adhesion conditions, producing high trajectory-tracking control accuracy. Thus, this work provides an important reference for improving the adaptability, robustness, and optimization of intelligent vehicle tracking control systems.

ConvNeXt-MHC: improving MHC-peptide affinity prediction by structure-derived degenerate coding and the ConvNeXt model

Peptide binding to major histocompatibility complex (MHC) proteins plays a critical role in T-cell recognition and the specificity of the immune response. Experimental validation such peptides is extremely resource-intensive. As a result, accurate computational prediction of binding peptides is highly important, particularly in the context of cancer immunotherapy applications, such as the identification of neoantigens. In recent years, there is a significant need to continually improve the existing prediction methods to meet the demands of this field. We developed ConvNeXt-MHC, a method for predicting MHC-I-peptide binding affinity. It introduces a degenerate encoding approach to enhance well-established panspecific methods and integrates transfer learning and semi-supervised learning methods into the cutting-edge deep learning framework ConvNeXt. Comprehensive benchmark results demonstrate that ConvNeXt-MHC outperforms state-of-the-art methods in terms of accuracy. We expect that ConvNeXt-MHC will help us foster new discoveries in the field of immunoinformatics in the distant future. We constructed a user-friendly website at http://www.combio-lezhang.online/predict/, where users can access our data and application.

Inhibitory effects and mechanisms of cinnamaldehyde against Fusarium oxysporum, a serious pathogen in potatoes

BACKGROUND

Potatoes, a major economic crop, are significantly impacted by Fusarium dry rot, a prevalent postharvest disease. Despite the broad-spectrum antimicrobial properties of cinnamaldehyde, a naturally-derived plant substance, its efficacy against the causal pathogen of potato dry rot (Fusarium oxysporum) and the underlying mechanisms have not been extensively studied.

RESULTS

Our study demonstrates that cinnamaldehyde effectively inhibits the growth of Fusarium oxysporum, the pathogen responsible for potato dry rot, and increases its sensitivity to environmental stress factors such as extreme temperatures and high salt stress. Treatment with cinnamaldehyde results in altered fungal mycelium morphology, compromised cell wall stability, and disrupted cell membrane integrity, thereby reducing spore viability. Specifically, it interferes with the cell membrane and cell wall structures of the fungus, potentially disrupting fungal growth by modulating signaling pathways involved in cell wall maintenance, chitin metabolism, and GPI-anchored protein function. Notably, we show that cinnamaldehyde induces a form of regulated cell death in F. oxysporum, which is characterized not as typical apoptosis, as evidenced by Annexin V negative staining. However, the specific cell death type and underlying mechanism still needed to be further explored.

CONCLUSION

Cinnamaldehyde, an environmentally friendly plant-based active compound, exhibits strong inhibitory effects on F. oxysporum, indicating its potential use in the prevention and control strategies for potato dry rot. This research contributes to the understanding of novel antifungal mechanisms and offers promising insights into eco-friendly alternatives for managing this economically significant postharvest disease. © 2024 Society of Chemical Industry.

Organic Molecular Intercalation Enabled Anionic Redox Chemistry with Fast Kinetics for High Performance Magnesium Storage

Rechargeable magnesium-ion batteries possess desirable characteristics in large-scale energy storage applications. However, severe polarization, sluggish kinetics and structural instability caused by high charge density Mg2+ hinder the development of high-performance cathode materials. Herein, the anionic redox chemistry in VS4 is successfully activated by inducing cations reduction and introducing anionic vacancies via polyacrylonitrile (PAN) intercalation. Increased interlayer spacing and structural vacancies can promote the electrolyte ions migration and accelerate the reaction kinetics. Thanks to this "three birds with one stone" strategy, PAN intercalated VS4 exhibits an outstanding electrochemical performance: high discharge specific capacity of 187.2 mAh g-1 at 200 mA g-1 after stabilization and a long lifespan of 5000 cycles at 2 A g-1 are achieved, outperforming other reported VS4-based materials to date for magnesium storage under the APC electrolyte. Theoretical calculations confirm that the intercalated PAN can indeed induce cations reduction and generate anionic vacancies by promoting electron transfer, which can accelerate the electrochemical reaction kinetics and activate the anionic redox chemistry, thus improving the magnesium storage performance. This approach of organic molecular intercalation represents a promising guideline for electrode material design on the development of advanced multivalent-ion batteries.

Effects of tirofiban on large vessel occlusion stroke are modified by etiology and renal function

OBJECTIVE

Renal function can modify the outcomes of large vessel occlusion (LVO) stroke across stroke etiologies in disparate degrees. The presence of renal function deficit can also impair the pharmacokinetics of tirofiban. Hence, this study aimed to investigate the roles of renal function in determining efficacy and safety of intravenous tirofiban before endovascular treatment (EVT) for acute ischemic stroke patients with large vessel occlusion (LVO).

METHODS

This study was a post hoc exploratory analysis of the RESCUE-BT trial. The primary outcome was the proportion of patients achieving functional independence (modified Rankin scale 0-2) at 90 days, and the primary safety outcome was the rate of symptomatic intracranial hemorrhage (sICH).

RESULTS

Among 908 individuals with available serum creatinine, decreased estimated glomerular filtration rate (eGFR) status was noted more commonly in patients with cardioembolic stroke (CE), while large artery atherosclerosis (LAA) was predominant in patients with normal renal function. In LAA with normal renal function, tirofiban was associated with higher rates of functional independence at 90 days (41.67% vs 59.80%, p = 0.003). However, for LVO patients with renal dysfunction, tirofiban did not improve functional outcomes for any of the etiologies (LAA, p = 0.876; CE, p = 0.662; others, p = 0.894) and significantly increased the risk of sICH among non-LAA patients (p = 0.020). Mediation analysis showed tirofiban reduced thrombectomy passes (12.27%) and drug/placebo to recanalization time (14.25%) mediated its effects on functional independence.

CONCLUSION

This present study demonstrated the importance of evaluating renal function before administering intravenous tirofiban among patients with LVO who are planned to undergo EVT.

Binary Mg-1 at%Gd alloy anode for high-performance rechargeable magnesium batteries

Rechargeable magnesium batteries (RMBs) become a highly promising candidate for the large-scale energy storage system by right of the high volumetric capacity, intrinsic safety and abundant resources of Mg anode. However, the uneven Mg stripping and large overpotential will cause a severe pitting perforation and the followed failure of Mg anode. Herein, we proposed a high-performance binary Mg-1 at% Gd alloy anode prepared by the melting and hot extrusion. The introduction of 1 at% Gd element can effectively reduce the Mg2+ diffusion energy barrier (0.34 eV) on alloy surface and induces the formation of a robust and low-resistance electrolyte/anode interphase, thus enabling a uniform and fast Mg plating/stripping. As a result, the Mg-1 at.% Gd anode displays a largely enhanced life of 220 h and a low overpotential of 213 mV at a high current density of 5.0 mA cm-2 with 2.5 mAh cm-2 . Moreover, the assembled Mg-1 at.% Gd//Mo6 S8 full cell delivers a high rate performance (73.5 mAh g-1 at 5 C) and ultralong cycling stability of 8000 cycles at 5 C. This work brings new insights to design the new-type and practical Mg alloy anodes for commercial RMBs.

The Effect P Additive on the CeZrAl Support Properties and the Activity of the Pd Catalysts in Propane Oxidation

The properties of a catalyst support are closely related to the catalyst activity, yet the focus is often placed on the active species, with little attention given to the support properties. In this work, we specifically investigated the changes in support properties after the addition of P, as well as their impact on catalyst activity when used for catalyst preparation. We prepared the CeO2-ZrO2-P2O5-Al2O3 (CeZrPAl) composite oxides using the sol-gel, impregnation, and mechanical mixing methods, and characterized the support properties using techniques such as XRD, XPS, SEM-EDS, N2 adsorption-desorption, and Raman spectra. The results showed that the support prepared using the sol-gel method can exhibit a more stable phase structure, larger surface area, higher adsorption capacity for oxygen species, and greater oxygen storage capacity. The addition of an appropriate amount of P is necessary. On the one hand, the crystallization and growth of CePO4 can lead to a decrease in the Ce content in the cubic phase ceria-zirconia solid solution, resulting in a phase separation of the ceria-zirconia solid solution. On the other hand, CePO4 can lock some of the Ce3+/Ce4+ redox pairs, leading to a reduction in the adsorption of oxygen species and a decrease in the oxygen storage capacity of the CeZrPAl composite oxides. The research results indicated that the optimal P addition is 6 wt.% in the support. Therefore, we prepared a Pd/CeZrPAl catalyst using CeZrAl with 6 wt.% P2O5 as the support and conducted the catalytic oxidation of C3H8. Compared with the support without P added, the catalyst activity of the support loaded with P was significantly improved. The fresh and aged (1000 °C/5 h) catalysts decreased by 20 °C and 5 °C in T50 (C3H8 conversion temperature of 50%), and by 81 °C and 15 °C in T90 (C3H8 conversion temperature of 90%), respectively.

Catalyzing Desolvation at Cathode-Electrolyte Interface Enabling High-Performance Magnesium-Ion Batteries

Magnesium ion batteries (MIBs) are expected to be the promising candidates in the post-lithium-ion era with high safety, low cost and almost dendrite-free nature. However, the sluggish diffusion kinetics and strong solvation capability of the strongly polarized Mg2+ are seriously limiting the specific capacity and lifespan of MIBs. In this work, catalytic desolvation is introduced into MIBs for the first time by modifying vanadium pentoxide (V2 O5 ) with molybdenum disulfide quantum dots (MQDs), and it is demonstrated via density function theory (DFT) calculations that MQDs can effectively lower the desolvation energy barrier of Mg2+ , and therefore catalyze the dissociation of Mg2+ -1,2-Dimethoxyethane (Mg2+ -DME) bonds and release free electrolyte cations, finally contributing to a fast diffusion kinetics within the cathode. Meanwhile, the local interlayer expansion can also increase the layer spacing of V2 O5 and speed up the magnesiation/demagnesiation kinetics. Benefiting from the structural configuration, MIBs exhibit superb reversible capacity (≈300 mAh g-1 at 50 mA g-1 ) and unparalleled cycling stability (15 000 cycles at 2 A g-1 with a capacity of ≈70 mAh g-1 ). This approach based on catalytic reactions to regulate the desolvation behavior of the whole interface provides a new idea and reference for the development of high-performance MIBs.

A Review of the Application of Spatial Transcriptomics in Neuroscience

Since spatial transcriptomics can locate and distinguish the gene expression of functional genes in special regions and tissue, it is important for us to investigate the brain development, the development mechanism of brain diseases, and the relationship between brain structure and function in Neuroscience (or Brain science). While previous studies have introduced the crucial spatial transcriptomic techniques and data analysis methods, there are few studies to comprehensively overview the key methods, data resources, and technological applications of spatial transcriptomics in Neuroscience. For these reasons, we first investigate several common spatial transcriptomic data analysis approaches and data resources. Second, we introduce the applications of the spatial transcriptomic data analysis approaches in Neuroscience. Third, we summarize the integrating spatial transcriptomics with other technologies in Neuroscience. Finally, we discuss the challenges and future research directions of spatial transcriptomics in Neuroscience.

Insights into genetic diversity and phenotypic variations in domestic geese through comprehensive population and pan-genome analysis

BACKGROUND

Domestic goose breeds are descended from either the Swan goose (Anser cygnoides) or the Greylag goose (Anser anser), exhibiting variations in body size, reproductive performance, egg production, feather color, and other phenotypic traits. Constructing a pan-genome facilitates a thorough identification of genetic variations, thereby deepening our comprehension of the molecular mechanisms underlying genetic diversity and phenotypic variability.

RESULTS

To comprehensively facilitate population genomic and pan-genomic analyses in geese, we embarked on the task of 659 geese whole genome resequencing data and compiling a database of 155 RNA-seq samples. By constructing the pan-genome for geese, we generated non-reference contigs totaling 612 Mb, unveiling a collection of 2,813 novel genes and pinpointing 15,567 core genes, 1,324 softcore genes, 2,734 shell genes, and 878 cloud genes in goose genomes. Furthermore, we detected an 81.97 Mb genomic region showing signs of genome selection, encompassing the TGFBR2 gene correlated with variations in body weight among geese. Genome-wide association studies utilizing single nucleotide polymorphisms (SNPs) and presence-absence variation revealed significant genomic associations with various goose meat quality, reproductive, and body composition traits. For instance, a gene encoding the SVEP1 protein was linked to carcass oblique length, and a distinct gene-CDS haplotype of the SVEP1 gene exhibited an association with carcass oblique length. Notably, the pan-genome analysis revealed enrichment of variable genes in the "hair follicle maturation" Gene Ontology term, potentially linked to the selection of feather-related traits in geese. A gene presence-absence variation analysis suggested a reduced frequency of genes associated with "regulation of heart contraction" in domesticated geese compared to their wild counterparts. Our study provided novel insights into gene expression features and functions by integrating gene expression patterns across multiple organs and tissues in geese and analyzing population variation.

CONCLUSION

This accomplishment originates from the discernment of a multitude of selection signals and candidate genes associated with a wide array of traits, thereby markedly enhancing our understanding of the processes underlying domestication and breeding in geese. Moreover, assembling the pan-genome for geese has yielded a comprehensive apprehension of the goose genome, establishing it as an indispensable asset poised to offer innovative viewpoints and make substantial contributions to future geese breeding initiatives.

Graph Sampling-Based Multi-Stream Enhancement Network for Visible-Infrared Person Re-Identification

With the increasing demand for person re-identification (Re-ID) tasks, the need for all-day retrieval has become an inevitable trend. Nevertheless, single-modal Re-ID is no longer sufficient to meet this requirement, making Multi-Modal Data crucial in Re-ID. Consequently, a Visible-Infrared Person Re-Identification (VI Re-ID) task is proposed, which aims to match pairs of person images from the visible and infrared modalities. The significant modality discrepancy between the modalities poses a major challenge. Existing VI Re-ID methods focus on cross-modal feature learning and modal transformation to alleviate the discrepancy but overlook the impact of person contour information. Contours exhibit modality invariance, which is vital for learning effective identity representations and cross-modal matching. In addition, due to the low intra-modal diversity in the visible modality, it is difficult to distinguish the boundaries between some hard samples. To address these issues, we propose the Graph Sampling-based Multi-stream Enhancement Network (GSMEN). Firstly, the Contour Expansion Module (CEM) incorporates the contour information of a person into the original samples, further reducing the modality discrepancy and leading to improved matching stability between image pairs of different modalities. Additionally, to better distinguish cross-modal hard sample pairs during the training process, an innovative Cross-modality Graph Sampler (CGS) is designed for sample selection before training. The CGS calculates the feature distance between samples from different modalities and groups similar samples into the same batch during the training process, effectively exploring the boundary relationships between hard classes in the cross-modal setting. Some experiments conducted on the SYSU-MM01 and RegDB datasets demonstrate the superiority of our proposed method. Specifically, in the VIS→IR task, the experimental results on the RegDB dataset achieve 93.69% for Rank-1 and 92.56% for mAP.

MiR-601-induced BMSCs senescence accelerates steroid-induced osteonecrosis of the femoral head progression by targeting SIRT1

BACKGROUND

The imbalance between osteogenic and adipogenic differentiation of bone marrow mesenchymal stem cells (BMSCs) is not only the primary pathological feature but also a major contributor to the pathogenesis of steroid-induced osteonecrosis of the femoral head (SONFH). Cellular senescence is one of the main causes of imbalanced BMSCs differentiation. The purpose of this study was to reveal whether cellular senescence could participate in the progression of SONFH and the related mechanisms.

METHODS

The rat SONFH model was constructed, and rat BMSCs were extracted. Aging-related indicators were detected by SA-β-Gal staining, qRT-PCR and Western Blot experiments. Using H2O2 to construct a senescent cell model, and overexpressing and knocking down miR-601 and SIRT1 in hBMSCs, the effect on BMSCs differentiation was explored by qRT-PCR, Western Blot experiment, oil red O staining (ORO), alizarin red staining (ARS), and luciferase reporter gene experiment. A rat SONFH model was established to test the effects of miR-601 and metformin in vivo.

RESULTS

The current study showed that glucocorticoids (GCs)-induced BMSCs senescence, which caused imbalanced osteogenesis and adipogenesis of BMSCs, was responsible for the SONFH progression. Further, elevated miR-601 caused by GCs was demonstrated to contribute to BMSCs senescence through targeting SIRT1. In addition, the anti-aging drug metformin was shown to be able to alleviate GCs-induced BMSCs senescence and SONFH progression.

CONCLUSIONS

Considering the role of BMSCs aging in the progression of SONFH, this provides a new idea for the prevention and treatment of SONFH.

miR-486-5p Attenuates Steroid-Induced Adipogenesis and Osteonecrosis of the Femoral Head Via TBX2/P21 Axis

Enhanced adipogenic differentiation of mesenchymal stem cells (MSCs) is considered as a major risk factor for steroid-induced osteonecrosis of the femoral head (SOFNH). The role of microRNAs during this process has sparked interest. miR-486-5p expression was down-regulated significantly in femoral head bone tissues of both SONFH patients and rat models. The purpose of this study was to reveal the role of miR-486-5p on MSCs adipogenesis and SONFH progression. The present study showed that miR-486-5p could significantly inhibit adipogenesis of 3T3-L1 cells by suppressing mitotic clonal expansion (MCE). And upregulated expression of P21, which was caused by miR-486-5p mediated TBX2 decrease, was responsible for inhibited MCE. Further, miR-486-5p was demonstrated to effectively inhibit steroid-induced fat formation in the femoral head and prevented SONFH progression in a rat model. Considering the potent effects of miR-486-5p on attenuating adipogenesis, it seems to be a promising target for the treatment of SONFH.

Shear Behaviour and Calculation Methods of Bearing-Shear Connectors for Prefabricated Steel-Concrete Composite Beams

The bearing-shear connector (B-SC) is a newly developed connector that exhibits excellent shear behaviour and is easy to process. However, research on the application of B-SCs as substitutes for grouped studs in prefabricated steel-concrete composite beams is rare, and systematically studying their shear behaviour is necessary. Thus, a refined numerical model was developed to study the shear behaviour of the B-SCs. The numerical model, validated by push-out tests, was conducted to analyse the stress of the B-SCs and concrete slab during loading and to explore the failure mechanism of B-SCs. Then, a parametric study was performed to identify the key factors influencing the shear behaviour of the B-SCs. The concrete strength, and the thickness and the tensile strength of the shear plate were found to significantly influence the shear behaviour of B-SCs. According to the experiments and numerical analysis, calculation formulae for the ultimate shear resistance and slip modulus were proposed.

Efficient Aggressive Behavior Recognition of Pigs Based on Temporal Shift Module

Aggressive behavior among pigs is a significant social issue that has severe repercussions on both the profitability and welfare of pig farms. Due to the complexity of aggression, recognizing it requires the consideration of both spatial and temporal features. To address this problem, we proposed an efficient method that utilizes the temporal shift module (TSM) for automatic recognition of pig aggression. In general, TSM is inserted into four 2D convolutional neural network models, including ResNet50, ResNeXt50, DenseNet201, and ConvNext-t, enabling the models to process both spatial and temporal features without increasing the model parameters and computational complexity. The proposed method was evaluated on the dataset established in this study, and the results indicate that the ResNeXt50-T (TSM inserted into ResNeXt50) model achieved the best balance between recognition accuracy and model parameters. On the test set, the ResNeXt50-T model achieved accuracy, recall, precision, F1 score, speed, and model parameters of 95.69%, 95.25%, 96.07%, 95.65%, 29 ms, and 22.98 M, respectively. These results show that the proposed method can effectively improve the accuracy of recognizing pig aggressive behavior and provide a reference for behavior recognition in actual scenarios of smart livestock farming.

OsNF-YA3 regulates plant growth and osmotic stress tolerance by interacting with SLR1 and SAPK9 in rice

The antagonism between gibberellin (GA) and abscisic acid (ABA) signaling pathways is vital to balance plant growth and stress response. Nevertheless, the mechanism by which plants determine the balance remains to be elucidated. Here, we report that rice NUCLEAR FACTOR-Y A3 (OsNF-YA3) modulates GA- and ABA-mediated balance between plant growth and osmotic stress tolerance. OsNF-YA3 loss-of-function mutants exhibit stunted growth, compromised GA biosynthetic gene expression, and decreased GA levels, while its overexpression lines have promoted growth and enhanced GA content. Chromatin immunoprecipitation-quantitative polymerase chain reaction analysis and transient transcriptional regulation assays demonstrate that OsNF-YA3 activates GA biosynthetic gene OsGA20ox1 expression. Furthermore, the DELLA protein SLENDER RICE1 (SLR1) physically interacts with OsNF-YA3 and thus inhibits its transcriptional activity. On the other side, OsNF-YA3 negatively regulates plant osmotic stress tolerance by repressing ABA response. OsNF-YA3 reduces ABA levels by transcriptionally regulating ABA catabolic genes OsABA8ox1 and OsABA8ox3 by binding to their promoters. Furthermore, OSMOTIC STRESS/ABA-ACTIVATED PROTEIN KINASE 9 (SAPK9), the positive component in ABA signaling, interacts with OsNF-YA3 and mediates OsNF-YA3 phosphorylation, resulting in its degradation in plants. Collectively, our findings establish OsNF-YA3 as an important transcription factor that positively modulates GA-regulated plant growth and negatively controls ABA-mediated water-deficit and salt tolerance. These findings shed light on the molecular mechanism underlying the balance between the growth and stress response of the plant.

Metabolomic analysis of bone-derived exosomes in osteonecrosis of the femoral head based on UPLC-MS/MS

INTRODUCTION

Osteonecrosis of the femoral head (ONFH) is a disorder that causes a collapse of the femoral head, requiring subsequent total hip replacement. However, the pathogenesis of ONFH remains largely unclear. Herein, exosome metabolomics analyses were conducted to explore the pathophysiology of ONFH.

OBJECTIVES

This study aimed to conduct metabolic profiling of bone-derived exosomes of ONFH.

METHODS

30 ONFH patients and 30 femoral neck fracture (FNF) patients were included in this study. Exosomes were harvested from the femoral head by using ultracentrifugation. Ultraperformance liquid chromatography/tandem mass spectrometry (UPLC-MS/MS) was performed in combination with multivariate statistical analysis to reveal and provided new insight into identify the global metabolic profile of ONFH.

RESULTS

The results of transmission electron microscope (TEM), nanoparticle tracking analysis (NTA), and Western blots indicated that the microvesicles isolated from the femoral head were exosomes. Several compounds were identified, including lipids and lipid-like molecules, amino acids, peptides, organooxygen compounds. 44 differential metabolites were screened between ONFH and FNF patients. The up-and down-regulation of Riboflavin metabolism, Pantothenate and CoA biosynthesis, Glycerophospholipid metabolism, and Sphingolipid metabolism were associated with ONFH pathophysiology.

CONCLUSION

Our results suggest that metabolomics has huge prospects for elucidating pathophysiology of ONFH.

Application of Multivariate Methods to Evaluate Differential Material Attributes of HPMC from Different Sources

The aim of the present study is to achieve differential material attributes (DMAs) of hydroxypropyl methylcellulose (HPMC) with different viscosity grades (K4M, K15M, and K100M) from different manufacturers (Anhui Shanhe and Dow Chemical). Two kinds of multivariate methods, principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA), were adopted. The physicochemical properties of HPMC were systematically investigated via various techniques (e.g., SEM, particle size detection, and SeDeM characterization). Data from 33 characterization variables were applied to the multivariate methods. The PCA and OPLS-DA results indicated the differences between the HPMC from two manufacturers by the common variables that include the tablet hardness (HD), tensile strength (TS), bulk density, interparticle porosity, Carr index, cohesion index, Hausner ratio, flowability, and the width of the particle size distribution (span). Interestingly, these variables showed a certain correlation with each other, supporting the characterization results. Except for these different variables of the HPMC obtained by multivariate analysis results, distinguishable shapes and surface morphologies also appeared between different sources. To sum up, the powder properties (particle size, surface topography, dimension, flowability, and compressibility) and the tablet properties (HD and TS) were recognized as the DMAs of HPMC samples. This work provided the multivariate methods for the physicochemical characterization of HPMC, with potential in the quality control and formulation development.

Oestrus Analysis of Sows Based on Bionic Boars and Machine Vision Technology

This study proposes a method and device for the intelligent mobile monitoring of oestrus on a sow farm, applied in the field of sow production. A bionic boar model that imitates the sounds, smells, and touch of real boars was built to detect the oestrus of sows after weaning. Machine vision technology was used to identify the interactive behaviour between empty sows and bionic boars and to establish deep belief network (DBN), sparse autoencoder (SAE), and support vector machine (SVM) models, and the resulting recognition accuracy rates were 96.12%, 98.25%, and 90.00%, respectively. The interaction times and frequencies between the sow and the bionic boar and the static behaviours of both ears during heat were further analysed. The results show that there is a strong correlation between the duration of contact between the oestrus sow and the bionic boar and the static behaviours of both ears. The average contact duration between the sows in oestrus and the bionic boars was 29.7 s/3 min, and the average duration in which the ears of the oestrus sows remained static was 41.3 s/3 min. The interactions between the sow and the bionic boar were used as the basis for judging the sow's oestrus states. In contrast with the methods of other studies, the proposed innovative design for recyclable bionic boars can be used to check emotions, and machine vision technology can be used to quickly identify oestrus behaviours. This approach can more accurately obtain the oestrus duration of a sow and provide a scientific reference for a sow's conception time.

Incomplete Information Management Using an Improved Belief Entropy in Dempster-Shafer Evidence Theory

Quantifying uncertainty is a hot topic for uncertain information processing in the framework of evidence theory, but there is limited research on belief entropy in the open world assumption. In this paper, an uncertainty measurement method that is based on Deng entropy, named Open Deng entropy (ODE), is proposed. In the open world assumption, the frame of discernment (FOD) may be incomplete, and ODE can reasonably and effectively quantify uncertain incomplete information. On the basis of Deng entropy, the ODE adopts the mass value of the empty set, the cardinality of FOD, and the natural constant e to construct a new uncertainty factor for modeling the uncertainty in the FOD. Numerical example shows that, in the closed world assumption, ODE can be degenerated to Deng entropy. An ODE-based information fusion method for sensor data fusion is proposed in uncertain environments. By applying it to the sensor data fusion experiment, the rationality and effectiveness of ODE and its application in uncertain information fusion are verified.

Heterologous Expression of CLIBASIA_03915/CLIBASIA_04250 by Tobacco Mosaic Virus Resulted in Phloem Necrosis in the Senescent Leaves of Nicotiana benthamiana

Huanglongbing (HLB), also known as citrus greening, is the most notorious citrus disease worldwide. Candidatus Liberibacter asiaticus (CaLas) is a phloem-restricted bacterium associated with HLB. Because there is no mutant library available, the pathogenesis of CaLas is obscure. In this study, we employed tobacco mosaic virus (TMV) to express two mature secretion proteins CLIBASIA_03915 (m03915) and CLIBASIA_04250 (m04250) in Nicotiana benthamiana (N. benthamiana). Phloem necrosis was observed in the senescent leaves of N. benthamiana that expressed the two low molecular weight proteins, while no phloem necrosis was observed in the plants that expressed the control, green fluorescent protein (GFP). Additionally, no phloem necrosis was observed in the senescent leaves of N. benthamiana that expressed the null mutation of m03915 and frameshifting m04250. The subcellular localizations of m03915 and m04250 were determined by fusion with GFP using confocal microscopy. The subcellular localization of m03915 was found to be as free GFP without a nuclear localization sequence (NLS). However, m04250 did have an NLS. Yeast two-hybrid (Y2H) was carried out to probe the citrus proteins interacting with m03915 and m04250. Six citrus proteins were found to interact with m03915. The identified proteins were involved in the metabolism of compounds, transcription, response to abiotic stress, ubiquitin-mediated protein degradation, etc. The prey of m04250 was involved in the processing of specific pre-mRNAs. Identification of new virulence factors of CaLas will give insight into the pathogenesis of CaLas, and therefore, it will eventually help develop the HLB-resistant citrus.