bluuebunny/crossref_metadata_2025_split huggingface dataset:
Sanitary Conditions and Associated Factors Among Food and Drinking Establishment in Bule Hora Town, West Guji Zone, Southern Ethiopia
Authors: Asefa Lechisa , Gemechu Tibeso , Daba Chala , Kumela Gudeta , Karbana Gedeno , Dhengesu Degefa , Olkeba Beekam Kebede , Roba Habtamu , Lemma Hailu 
Published: November 2024

Abstract

Introduction:Maintaining food safety is mandatory because food is a good medium for the growth of microorganisms. In developing countries, rapid urbanization is accompanied by numerous food and drinking establishments. However, the sanitation status of these establishments and associated factors are not well-known or studied.
Objective: -The main objective of this study is to assess sanitary condition and associated factors among food and drinking establishment in Bule Hora town, west Guji zone, southern Ethiopia
Methods and material: A cross-sectional study design was employed to evaluate the sanitation status of the establishments. Semi-structured questionnaires and observational checklists were utilized as data collection instruments. Multivariate logistic regression analysis was carried out to identify factors associated with sanitary conditions. Variables with a p-value less than 0.050 were deemed to be statistically significantly related to sanitary conditions. A Hosmer-Lemeshow test was applied to assess the model's fit.
Results: Of the 246 food and beverage establishments, 36.2% were found to have adequate sanitary facilities. Having a license (AOR=3.18, 95%CI, 1.056-7.62), privately owning the building (AOR=5.56, 95%CI, 1.44-9.78), regular inspection by a regulatory body (AOR=3.32, 95%CI, 1.95-11.64), and a trained manager on the sanitation of food and beverage establishments (AOR=1.56, 95%CI, 1.032-3.41) were found to have significant associations with the sanitary facilities of food and beverage establishments.
Result: - of 246 foods and drinking establishment 36.2% have adequate sanitary facility. Having license (AOR=3.18, CI, 1.056-7.62), owner of Building (AOR=5.56, CI, 1.44-9.78), regular inspection by regulatory body (AOR=3.32 CI, 1.95-11.64) and trained for manager on sanitation of food and drinking establishment (AOR=1.56, CI, 1.032-3.41) have significant association with sanitary facility of food and drinking establishment.
Conclusion: Inadequate sanitary facilities were present within food and beverage establishments within Bule Hora town. Adequate sanitation was positively correlated with having a license, private ownership of the building, inspection by a regulatory body, and the training status of the manager. To improve sanitary conditions, it is recommended that regular inspections and training be provided.
Optimizing global rainfed crop production can promote food system climate resilience without additional land or water
Authors: Wang Zhen , Li Cai , Hadjikakou Michalis , Deng Zhongci , Shi Zhihua , Bryan Brett 
Published: November 2024

Abstract

The global food system faces escalating risks to the production of major rainfed agricultural crops such as wheat, maize, rice, and soy due to increasing climate variability and long-term climate change. Here, we used modern portfolio theory to explore Pareto-optimal spatial arrangements of global rainfed cropping that explicitly account for trade-offs between total crop production (i.e., expected returns) and variability (i.e., risk). We analysed production/risk trade-offs under recent historical climate and yields for 2010, as well as under business-as-usual (RCP 6.0) and ambitious mitigation (RCP 2.6) climate futures for 2050. We found that optimizing the spatial distribution of rainfed crops could increase global production by 10.1% at the risk level of 2010, or, alternatively, reduce risk by 33.1% at the production level of 2010, all without additional land or water. Optimal global rainfed cropping patterns could also meet future food demand with enhanced resilience under increased climate variability but only when accompanied by yield gap closure and more open and globalised trade. Future climate adaptation policy for agriculture should consider the potential benefits of improving the coordination of global crop production, promoting global trade cooperation, and the sustainable intensification of agricultural production.
From Screen to Table: How Religious Food Documentaries Inspire Non-Religious Consumers’ Purchase Intentions
Authors: Yang Jian , Yang Ni Cai , Zhang Hua Dong , Yao Rui 
Published: November 2024

Abstract

Religious food plays a key role in conveying religious culture, transcending religious values due to its everyday and universal nature. With the growth of digital media, film and television, particularly documentaries, have become valuable tools for promoting religious food culture. While religious food is often viewed as a niche for the faithful, non-religious consumers now dominate the halal food market. This study explores how religious food documentaries influence non-religious individuals' purchase intentions, focusing on narrative transportation theory and awe in religious experiences through the lens of the theory of planned behaviour (TPB). A survey of 381 non-Muslim viewers of halal food documentaries revealed that documentary narratives and religious experiences significantly impact purchase intentions. Telepresence and social presence in the narratives affect perceived behavioural control, attitudes, and subjective norms, while awe directly influences subjective norms. All three intermediate variables positively contribute to purchase intentions. The findings offer insights and recommendations for religious food marketers and scriptwriters.
From Family to Workplace: The Relationship and Mechanisms between Filial Piety Belief and Employee Organizational Loyalty
Authors: Li Wei , Lan Ruiming , Li Yichang 
Published: November 2024

Abstract

This study explores the relationship and mechanisms between filial piety beliefs and organizational loyalty among corporate employees, with a focus on the mediating roles of family motivation and job involvement, using the Work-Home Resources Model (W-HR Model). A questionnaire survey was conducted with 435 employees of private enterprises in the southeastern coastal region of China, utilizing the Filial Piety Scale, Organizational Loyalty Scale, Family Motivation Scale, and Job Involvement Scale. The results indicate that filial piety beliefs have a direct positive predictive effect on employees’ organizational loyalty. Additionally, they generate significant indirect effects through three pathways: the first pathway is mediated by the sole impact of family motivation, the second pathway is mediated by job involvement, and the third pathway is mediated through the chain mediation of family motivation and job involvement.These findings reveal that contemporary filial piety beliefs are closely linked to organizational loyalty, with family motivation and job involvement playing important roles in this process. The study presents a novel perspective on the mechanisms by which filial piety beliefs influence organizational loyalty among employees and offers important references for enhancing employee loyalty and optimizing corporate management practices.
Optimized Ozone Concentration Prediction in Seoul Districts Using ANN and K-means Clustering for Accuracy Enhancement
Authors: Park Junbum 
Published: November 2024

Abstract

Ozone is a dangerous greenhouse gas and air pollutant in urban areas, with significant negative impacts on climate change and human health. Predicting ozone concentrations is a critical factor in environmental issues such as air pollution management, risk assessment, public health, and global warming. Since an early prediction model of ozone is essential for building a warning system, research is needed on indicators that explain whether ozone pollution status will rise or fall. This study proposed a prediction model trained using artificial neural network (ANN)-based classification with training data divided into specific time periods through k-means clustering to predict ozone concentrations. This model lowers the cost of training owing to around 30% of the reduced training data in a specific time period, and is also applicable for a variety of features. Air quality data was collected from 2019 and 2020 in the 25 districts of Seoul, South Korea and used for training and testing on whether the ozone concentration changes after one hour during 07:00 to 18:00. The proposed model yielded 3% higher F1 score and 3-4% higher accuracy in comparison with other models. As a result, the model proposed in this study showed improved performance while reducing the training data in a specific environment.
The Mediating Role of Self-Forgiveness in the Relationship Between Social Exclusion and Psychological Symptoms in University Students
Authors: Kaşıkcı Furkan , Korkmaz Burak Can 
Published: November 2024

Abstract

Social exclusion is a risk factor for the psychological well-being of university students. Because they pass through emerging adulthood characterized by pressure and uncertainty, interpersonal resources are more significant for them. However, social exclusion limits these resources. It also causes negative emotional states, such as guilt and sadness. At this point, self-forgiveness may play a significant role as an emotion-focused coping strategy. Thus, the present study aimed to investigate the mediating role of self-forgiveness on the relationship between social exclusion and psychological symptoms in university students. This study included 725 university students aged 18-24 years, with a mean age of 21.01 years. Of these university students, 481 (66.3%) were female, and 244 (33.7%) were male. The participants completed the Social Exclusion Scale, Self-Forgiveness Scale, and Depression Anxiety Stress Scale-21. The findings revealed that social exclusion was significantly associated with psychological symptoms. Furthermore, self-forgiveness mediated the relationship between social exclusion and psychological symptoms. Therefore, psychological symptoms can be prevented by focusing on the self-forgiveness of university students experiencing social exclusion.
Examining the Artificial Intelligence Frameworks and Guidelines as Evaluation Tools between 1998-2024
Authors: Bulut Mehmet Akın , Baghırlı Sevda Nur Akan 
Published: November 2024

Abstract

This study utilised a bibliometric analysis technique using PRISMA model on academic studies containing frameworks, guidelines, rubrics, and regulations related to artificial intelligence use in education, found in the Web of Science database. The research aimed to understand the relationships, trends, and patterns among these publications by examining the scientific literature. A total of 301 academic publications were analysed based on the years of publication, types of publications, journals where the publications were published, countries of origin, institutions, number of publications by authors, and most frequently occurring words in the publications. According to the analysis, the year with the highest number of academic publications was 2023, the country with the highest scientific content production in this field was China, the journal with the most content published was "Engineering Applications of Artificial Intelligence," the most common type of content was articles, the author with the highest number of scholarly work was Li Y., and the most frequently repeated word was "framework." This descriptive analysis study is anticipated to contribute to the field.
Threshold of PAGln Changes: Exponential Growth Between Age and Gut Microbiota in Stroke Patients
Authors: Liu Yang , Chu Min , Wang Delong , Li Qian , Zhao Jing 
Published: November 2024

Abstract

Importance PAGln, a gut microbiota-derived metabolite, is linked to increased platelet reactivity and thrombosis risk. However, its relationship with age, particularly the nonlinear patterns in ischemic stroke patients, remains unclear.
Objectives To explore the nonlinear relationship between age and plasma PAGln levels in ischemic stroke patients, focusing on identifying exponential growth trends and critical age thresholds.
Design, Setting, and Participants This single-center, prospective cohort study was conducted at the Department of Neurology, Minhang Hospital, Fudan University, from January 2022 to December 2023. A total of 121 patients with ischemic stroke were consecutively enrolled. Demographic information, lifestyle factors, stroke characteristics, and comorbidities were systematically collected. Plasma PAGln levels were measured using rapid resolution liquid chromatography–quadrupole time-of-flight mass spectrometry. Generalized additive models and smoothing curve fitting were applied to assess nonlinear relationships between age and PAGln levels, with threshold effect analysis used to identify age breakpoints. Multivariable regression models were applied to adjust for confounders, and subgroup analyses tested the robustness of findings.
Main Outcomes and Measures Plasma PAGln levels and their association with age in ischemic stroke patients, evaluated through nonlinear models and regression analysis.
Results Significant differences in PAGln levels were found across age quartiles (P=0.004), rising from 186.87 ± 95.49 µmol/L in the youngest quartile (33–54 years) to 433.11 ± 474.03 µmol/L in the oldest quartile (69–87 years). A nonlinear association between age and PAGln levels was identified (P=0.0006). Smoothing curve fitting revealed an exponential increase in PAGln levels with age. A threshold effect analysis pinpointed a breakpoint at 71 years. Below this age, no significant association between age and PAGln was observed (P=0.5394), while above 71, a significant exponential increase in PAGln levels was detected (P<0.0001). Subgroup analyses confirmed consistent results across various patient characteristics, with no significant interactions.
Conclusions and Relevance A nonlinear exponential relationship exists between age and plasma PAGln levels in ischemic stroke patients, with a marked increase after 71 years. Elevated PAGln levels in elderly patients suggest significant metabolic dysregulation, potentially raising thrombosis risk. Monitoring PAGln levels in stroke patients over 71 years could provide valuable insights for personalized interventions to reduce thrombotic complications.
VDR decrease enhances the efficacy of 1,25-dihydroxyvitamin D3 inhibiting gefitinib resistance by regulating EGFR/FASN loop in NSCLC cells
Authors: Yang Junqing , Fang Mingyu , Hou Mengjun , Duan Yalei , Wang Jiali , Hu Kaiyong , Liu Shuo , Liu Xiaoying , Peng Xiaohan , Ding Xuansheng , Jia Zhirong 
Published: November 2024

Abstract

Our previous studies have demonstrated that 1,25-dihydroxyvitamin D3 (1,25(OH)2D3) inhibits epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) resistance in non-small cell lung cancer (NSCLC); however, the role of vitamin D receptor (VDR) in regulating NSCLC EGFR-TKIs resistance is unknown. To this end, we detected the VDR expression in EGFR-TKI sensitive and resistant NSCLC cells, and found that VDR expression was increased significantly in EGFR-TKI resistant NSCLC cells. By knocking-down VDR both in cell lines and in xenograft models, we discovered that VDR loss inhibited cell proliferation and tumor progression, and VDR loss or overexpression respectively made cells less or more resistant to gefitinib, and decreased or increased the expression of EGFR and FASN (Fatty acid synthase). Moreover, by silencing EGFR and FASN respectively, we found that there exists positive feedback loop among VDR, EGFR and FASN in NSCLC cells. Furthermore, 1,25(OH)2D3 increased the expression of VDR and decreased the expression of EGFR and FASN. VDR loss increases the efficacy of 1,25(OH)2D3 inhibiting gefitinib resistance, and the combination of VDR knockdown and 1,25(OH)2D3 further suppressed the expression of EGFR and FASN. Collectively, VDR knockdown increases the efficacy of 1,25(OH)2D3 inhibiting gefitinib resistance by decreasing expression of EGFR and FASN. Our study provides a new strategy through targeting VDR to enhance the efficacy of 1,25(OH)2D3 inhibiting gefitinib resistance.
A rapid and simplified detection of Agroathelia rolfsii (syn. Sclerotium rolfsii) by LAMP assay in fields
Authors: Harata Ken , Momma Yusuke , Tokumaru Susumu 
Published: November 2024

Abstract

Agroathelia rolfsii (syn. Sclerotium rolfsii) causes southern blight and root rot in various agricultural crops. In soybean, this pathogen attacks host roots and stems near the ground, and then forms abundant sclerotia which have an ability to overwinter and survive in soil for a long time. In the Kyoto Prefecture, Japan, damping-off disease in black soybean seedlings is caused by A. rolfsii and is a threat to sustainable production. To circumvent expansion of inoculum resource, A. rolfsii-infected soybean seedlings must be identified as soon as possible. In this study, we developed a loop-mediated isothermal amplification (LAMP) assay for A. rolfsii. A positive reaction of the LAMP assay was detected in A. rolfsii, but not Calonectria ilicicola and Phytophthora sojae. The LAMP assay is completed within 1 h. The detection sensitivity of the LAMP assay was 1000 times higher than that of conventional PCR. Moreover, the LAMP assay could detect A. rolfsii-infected soybean seedlings in fields, achieving practical diagnosis technique. Taken together, our technique allows for rapid and simplified diagnosis and contributes to disease management.
Repurposing herbal extracts as antimicrobial agents against bacterial pathogens isolated from UTI
Authors: Dhiman Simran , Devi Sushila , Sharma Karuna 
Published: November 2024

Abstract

Aim of the study: To evaluate the antimicrobial and antibiofilm activities of extracts from clove, turmeric, and ginger against Uropathogens. Material and methods: Clove, turmeric and ginger extracts were prepared by cold percolation method. Antimicrobial and antibiofilm assays were conducted against isolated Uropathogens. Exopolysaccharide (EPS) production and serum bactericidal assay were measured. Results: The extracts demonstrated significant antimicrobial activity against uropathogens. They effectively inhibited biofilm formation and reduced EPS production. Showed a significant decrease in the Bactericidal action of serum against isolated Uropathogens. Conclusion: This study underscores the potential of clove, turmeric, and ginger extracts as potent antimicrobial and antibiofilm agents against uropathogen. These extracts offer a promising approach to combat antibiotic-resistant bacteria by inhibiting exopolysaccharide synthesis. Further research is warranted to elucidate their mechanisms of action, optimize extraction processes, and evaluate their clinical efficacy for the development of novel therapeutic strategies
Investigating the prevalence of medication near-misses and reporting intention among nurses in tertiary hospitals from China
Authors: Fang Jinxia , Zhang Zeyi , Zhang Qi , Jia Wanshun , Chen Xue , Li Yuanyuan 
Published: November 2024

Abstract

Background
To investigate the prevalence of nurses' medication near-misses and reporting intention in tertiary hospitals of Shandong Province, China. To explore the potential influencing factors for the reporting intention from the perspective of both nurses and managers.
Design:
A cross-sectional design.
Methods
Between March 2021 and December 2021, 2625 nurses in seven tertiary hospitals from Shandong Province, China were enrolled in the study. Information about medication near-misses, reporting intention and barriers was collected using self-reported questionnaire, subscales of the Adverse Event Reporting Intention Questionnaire, and Medication Near-Miss Reporting Barriers Scale. We explored the association between potential determinants from the perspective of nurses and managers using generalized linear model.
Results
About 25.3% of nurses experienced medication near-misses, with a mean reporting intention score of 5.44 (standardized deviation = 1.13). The main approach for reporting medication near-misses was verbal language (80.6%). Nurses with higher professional title (χ2 = 13.770, P = 0.003), lower educational level (χ2 = 6.722, P = 0.035), fewer weekly work hours (χ2 = 3.947, P = 0.047), no previous medication near-misses experience (χ2 = 46.517, P < 0.001), and not having siblings (χ2 = 4.150, P = 0.042) showed a higher level of reporting intention. The manager's negative response (χ2 = 7.059, P = 0.008) and complex reporting system (χ2 = 17.120, P < 0.001) were associated with lower levels of reporting intention, primarily influenced by departmental categories (χ2 = 22.306, P = 0.002).
Conclusion
A quarter of nurses experienced medication near-misses, but most of them had intention to report the near-misses. Therefore, clinical managers should provide timely support to nurses who are likely to avoid reporting medication near-misses and establish mature reporting systems for near-misses.
Machine Learning Analysis of Mental Health Disparities among African Americans in Southeastern Virginia: Predictive Modeling, Risk Factors, and Policy Implications
Authors: Moudden Ismail El , Bittner Michael , Karpov Matvey , Osunmakinde Isaac , Acheamponmaa Akosua , Nevels Breshell , Mbaye Mamadou , Fields Tonya , Jordan Karthiga , Bahoura Messaoud 
Published: November 2024

Abstract

This study examined mental health disparities among African Americans, emphasizing gender differences and using AI and machine learning for outcome prediction. Data from African American adults (18-85) in Southeastern Virginia (2016-2020) were analyzed using descriptive statistics, chi-square, Kruskal-Wallis, and Wilcoxon tests. Machine learning models, including gradient boosting, random forest, neural networks, logistic regression, and Naive Bayes, were validated through 100 repeated 5-fold cross-validations. Nomograms were developed to visualize risk factors, identifying mood affective disorders as most prevalent, followed by schizophrenia, delusional disorders, and substance use disorders. Gender, age, comorbidities, and insurance type were key predictors, with females primarily affected by mood and neurotic disorders. Gradient boosting demonstrated high accuracy. The study highlights demographic and clinical predictors' significance despite limitations like its retrospective design and regional focus. It offers insights into mental health disparities among African Americans in Southeastern Virginia and calls for further research to inform effective health policies.
Lane Detection Based on ECBAM_ASPP Model
Authors: Gu Xiang , Huang Qiwei , Du Chaonan 
Published: November 2024

Abstract

As autonomous driving becomes more important, so does lane detection. This means that the accuracy and speed of lane detection need to be further improved. The paper proposes the Efficient Convolution Block Attention Module (ECBAM) and the ECBAM\_ASPP model to process the problems. The ECBAM can maintain the efficient performance of the attention mechanism without dimensionality reduction. Based on the ECBAM and the Atrous Spatial Pyramid Pool (ASPP), we propose the ECBAM\_ASPP model. By embedding the ECBAM attention mechanism into the feature extraction network, precisely motivate network to focus on useful features and suppress useless features. The input is sampled at different sampling rates to obtain features extracted at different scales, thus obtaining more abundant lane feature information. Training and evaluating the ECBAM\_ASPP model on TuSimple based on the idea of row selection classification. Experimental results indicate the model improves lane detection speed and accuracy.