CNN-ViT Supported Weakly-Supervised Video Segment Level Anomaly Detection

Video anomaly event detection (VAED) is one of the key technologies in computer vision for smart surveillance systems. With the advent of deep learning, contemporary advances in VAED have achieved substantial success. Recently, weakly supervised VAED (WVAED) has become a popular VAED technical route of research. WVAED methods do not depend on a supplementary self-supervised substitute task, yet they can assess anomaly scores straightway. However, the performance of WVAED methods depends on pretrained feature extractors. In this paper, we first address taking advantage of two pretrained feature extractors for CNN (e.g., C3D and I3D) and ViT (e.g., CLIP), for effectively extracting discerning representations. We then consider long-range and short-range temporal dependencies and put forward video snippets of interest by leveraging our proposed temporal self-attention network (TSAN). We design a multiple instance learning (MIL)-based generalized architecture named CNN-ViT-TSAN, by using CNN- and/or ViT-extracted features and TSAN to specify a series of models for the WVAED problem. Experimental results on publicly available popular crowd datasets demonstrated the effectiveness of our CNN-ViT-TSAN.publishedVersio

Relationship between trade enhancement, firm characteristics and CSR: key mediating role of green investment

Organisations are increasingly implementing socially responsible strategies in response to increased rivalry in trade and commercial activities. Organisations are expected to increase their profitability through corporate social responsibility (CSR). Hence, this study investigates the relationship between trade enhancement, firm characteristics, and CSR. Further, this study also explored the critical mediating role of green investment (GI). The data were collected from 456 respondents from manufacturing organisations in China through a questionnaire and analysed by partial least square structural equation modelling (PLS-SEM). PLS-SEM results revealed that trade enhancement has a significant positive effect on CSR and GI. GI also has a significant effect on CSR. In comparison, firm characteristics do not have a substantial impact on CSR and GI. However, GI significantly mediates the relationship between trade enhancement, firm characteristics, and CSR. This study provides insights to managers and stakeholders regarding GI and CSR in the Chinese manufacturing industry. Lastly, this study proposes theoretical and practical implications andoffers valuable information for practitioners and policymakers

Current and Prospective Applications of 3D Printing in Cosmetics: A Literature Review

3D printing (3DP) is a manufacturing technology that produces 3D objects from a design file using layer-by-layer deposition of material. It has already found applications in the healthcare and pharmaceutical industries, while its use in the field of topical delivery has been extensively studied in the last two decades. The aim of this study is to provide a comprehensive overview of the 3DP-based developments in topical delivery, with special emphasis on its current and potential use in the cosmetic field. This review covers the principles and main types of 3DP technology, production and characteristics of two key 3DP skin delivery platforms (patches and microneedles—MNs), as well as topical active materials used, focusing on those for cosmetic application

Resting-State Brain Organization Revealed by Functional Covariance Networks

BACKGROUND: Brain network studies using techniques of intrinsic connectivity network based on fMRI time series (TS-ICN) and structural covariance network (SCN) have mapped out functional and structural organization of human brain at respective time scales. However, there lacks a meso-time-scale network to bridge the ICN and SCN and get insights of brain functional organization. METHODOLOGY AND PRINCIPAL FINDINGS: We proposed a functional covariance network (FCN) method by measuring the covariance of amplitude of low-frequency fluctuations (ALFF) in BOLD signals across subjects, and compared the patterns of ALFF-FCNs with the TS-ICNs and SCNs by mapping the brain networks of default network, task-positive network and sensory networks. We demonstrated large overlap among FCNs, ICNs and SCNs and modular nature in FCNs and ICNs by using conjunctional analysis. Most interestingly, FCN analysis showed a network dichotomy consisting of anti-correlated high-level cognitive system and low-level perceptive system, which is a novel finding different from the ICN dichotomy consisting of the default-mode network and the task-positive network. CONCLUSION: The current study proposed an ALFF-FCN approach to measure the interregional correlation of brain activity responding to short periods of state, and revealed novel organization patterns of resting-state brain activity from an intermediate time scale

Influences of Excluded Volume of Molecules on Signaling Processes on Biomembrane

We investigate the influences of the excluded volume of molecules on biochemical reaction processes on 2-dimensional surfaces using a model of signal transduction processes on biomembranes. We perform simulations of the 2-dimensional cell-based model, which describes the reactions and diffusion of the receptors, signaling proteins, target proteins, and crowders on the cell membrane. The signaling proteins are activated by receptors, and these activated signaling proteins activate target proteins that bind autonomously from the cytoplasm to the membrane, and unbind from the membrane if activated. If the target proteins bind frequently, the volume fraction of molecules on the membrane becomes so large that the excluded volume of the molecules for the reaction and diffusion dynamics cannot be negligible. We find that such excluded volume effects of the molecules induce non-trivial variations of the signal flow, defined as the activation frequency of target proteins, as follows. With an increase in the binding rate of target proteins, the signal flow varies by i) monotonically increasing; ii) increasing then decreasing in a bell-shaped curve; or iii) increasing, decreasing, then increasing in an S-shaped curve. We further demonstrate that the excluded volume of molecules influences the hierarchical molecular distributions throughout the reaction processes. In particular, when the system exhibits a large signal flow, the signaling proteins tend to surround the receptors to form receptor-signaling protein clusters, and the target proteins tend to become distributed around such clusters. To explain these phenomena, we analyze the stochastic model of the local motions of molecules around the receptor.Comment: 31 pages, 10 figure

Proteomic identification of galectin-11 and 14 ligands from Haemonchus contortus

Haemonchus contortus is the most pathogenic nematode of small ruminants. Infection in sheep and goats results in anaemia that decreases animal productivity and can ultimately cause death. The involvement of ruminant-specific galectin-11 (LGALS-11) and galectin-14 (LGALS-14) has been postulated to play important roles in protective immune responses against parasitic infection; however, their ligands are unknown. In the current study, LGALS-11 and LGALS-14 ligands in H. contortus were identified from larval (L4) and adult parasitic stages extracts using immobilised LGALS-11 and LGALS-14 affinity column chromatography and mass spectrometry. Both LGALS-11 and LGALS-14 bound more putative protein targets in the adult stage of H. contortus (43 proteins) when compared to the larval stage (two proteins). Of the 43 proteins identified in the adult stage, 34 and 35 proteins were bound by LGALS-11 and LGALS-14, respectively, with 26 proteins binding to both galectins. Interestingly, hematophagous stage-specific sperm-coating protein and zinc metalloprotease (M13), which are known vaccine candidates, were identified as putative ligands of both LGALS-11 and LGALS- 14. The identification of glycoproteins of H. contortus by LGALS-11 and LGALS-14 provide new insights into host-parasite interactions and the potential for developing new interventions

Axitinib targets cardiac fibrosis in pressure overload-induced heart failure through VEGFA-KDR pathway

BackgroundThere are no specific clinical medications that target cardiac fibrosis in heart failure (HF). Recent studies have shown that tyrosine kinase inhibitors (TKIs) may benefit fibrosis in various organs. However, there is limited research on their application in cardiac fibrosis. Axitinib, an FDA-approved tyrosine kinase inhibitor, was used to evaluate its effects on cardiac fibrosis and function in pressure overload-induced heart failure.MethodsTo build a pharmacological network, the pharmacological targets of axitinib were first retrieved from databases and coupled with key heart failure gene molecules for analysis and prediction. To validate the results outlined above, 8-week-old male C57BL/6 J mice were orally administrated of axitinib (30 mg/kg) daily for 8 weeks after Transverse Aortic Constriction (TAC) surgery. Mouse cardiomyocytes and cardiac fibroblasts were used as cell lines to test the function and mechanism of axitinib.ResultsWe found that the pharmacological targets of axitinib could form a pharmacological network with key genes involved in heart failure. The VEGFA-KDR pathway was found to be closely related to the differential gene expression of human heart-derived primary cardiomyocyte cell lines treated with axitinib, based on analysis of the publicly available dataset. The outcomes of animal experiments demonstrated that axitinib therapy greatly reduced cardiac fibrosis and improved TAC-induced cardiac dysfunction. Further research has shown that the expression of transforming growth factor-β(TGF-β) and other fibrosis genes was significantly reduced in vivo and in vitro.ConclusionOur study provides evidence for the repurposing of axitinib to combat cardiac fibrosis, and offers new insights into the treatment of patients with HF

Comparative effectiveness of mind-body exercise versus cognitive behavioral therapy for college students with problematic smartphone use: a randomized controlled trial

Purpose: The purpose of the present study was to compare the effectiveness of mind-body exercise (ME) and cognitive behavioral therapy (CBT) on addiction level and psychological well-being among college students with problematic smartphone use (PSU). Methods: A 12-week randomized controlled study was carried out at a university in central China. A total of 95 PSU college students who met the inclusion criteria were randomly assigned to a ME group (ME, n = 31), CBT group (CBT, n = 30), or control group (CG, n = 34). Both ME intervention and CBT, twice per week for 90 min per session, lasting for 12 weeks were administered by a certified therapist respectively. Participants in the CG group were asked to maintain their original lifestyle. Results: A significant reduction in addiction level (p < 0.001 for ME vs. CBT; p < 0.001 for ME vs. CG), loneliness (p < 0.001 for ME vs. CG), anxiety (p < 0.001 for ME vs. CG; p < 0.001 for CBT vs. CG) was found. Only significant stress reduction was observed in ME and CBT between baseline and Week 12 (ps < 0.001). Conclusions: ME and CBT (mainstream psychotherapy) may effectively overcome PSU of college students, and reduced the level of smartphone addiction, loneliness, anxiety, and stress. Furthermore, as a culture-specific, low-cost, and readily accessible training program with multiple components (gentle movement, anatomic alignment, mental focus, deep breathing, and meditative state of mind that is similar to mindfulness emphasizing noncompetitive, present-moment, and nonjudgmental introspective component), ME seems to be superior to CBT in terms of PSU

Association between active school travel and depressive symptoms among 51,702 adolescents in 26 low-and middle-income countries

Little is known about the role of active school travel (AST) on mental health among adolescents. Thus, this study aimed to explore the AST-depression association among adolescents aged 12-15 years from 26 low-and middle-income countries (LMICs). Data from the Global School-based Student Health Survey were analyzed in 51,702 adolescents [mean (SD) age 13.8 (1.0) years; 49.3% boys). Both depressive symptoms and AST were assessed by a single question self-reported measure, respectively. Participants who reported having 5 days or above were considered as AST. Multivariable logistic regression analysis (accounting for sampling weights) was performed while controlling for gender, age, physical activity, sedentary behavior, and food insecurity, and a countrywide meta-analysis was undertaken. The prevalence of depressive symptoms and AST were 30.1% and 37.0%, respectively. Compared with those not having AST, adolescents with AST were less likely to have self-reported depressive symptoms (OR = 0.88, 95%CI: 0.85-0.93) regardless of gender. Countrywide meta-analysis demonstrated that having AST versus not having AST was associated with 12% lower odds for depressive symptoms (OR = 0.88; 95%CI: 0.82-0.94) but with a moderate between-country heterogeneity (I 2 = 59.0%). Based on large samples of adolescents from LMICs, it would be expected that AST may play a critical role in preventing adolescent depression worldwide. However, it is necessary to consider more country-specific This work is licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited