bluuebunny/crossref_metadata_2025 huggingface dataset:
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

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

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

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

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

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

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

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

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

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

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

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

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.
The up-regulated expression level of deubiquitinating enzyme USP46 induces the apoptosis of A549 cells by TRAF6
Authors: Zhao Xuan , Li Yanan , Gu Dandan , Wang Xiaoru , Han Guangxin , Yao Yasen , Ren Limei , Yao Qingguo , Li Xiaobing , Qi Yonghao
Published: November 2024

This study investigates the function of Ubiquitin-specific protease 46 (USP46), a deubiquitinase, in the context of lung cancer, particularly its role in regulating cell proliferation via the ubiquitination of TRAF6. In A549 lung cancer cells, analysis revealed a significant downregulation of USP46 expression, while TRAF6 levels were notably elevated. These findings were corroborated by Western blotting, which confirmed the altered expression patterns. To further assess the implications of these changes, several experimental assays, including the Cell Counting Kit-8, transwell migration assays, and flow cytometry, were conducted to evaluate cell viability and apoptosis rates. Co-immunoprecipitation experiments demonstrated a direct interaction between USP46 and TRAF6, implicating USP46 in the modulation of TRAF6 ubiquitination, a process that is fundamental to tumor physiology. The results indicated that decreased USP46 expression led to an increase in the levels of the anti-apoptotic protein Bcl-2, while there was a corresponding decrease in key pro-apoptotic proteins such as caspase-3, caspase-9, and Bax. Additionally, the study found elevated levels of phosphorylated AKT and mTOR, which suggest the activation of survival signaling pathways in the cancer cells. These findings collectively suggest that the up-regulated USP46 promotes apoptosis in lung cancer cells through the regulation of TRAF6. Therefore, targeting the USP46/TRAF6 signaling pathway presents a promising therapeutic strategy for lung cancer treatment, potentially offering new avenues for intervention in cancer progression and cell survival mechanisms.
Relationship between Anxiety and Fatigue in Dementia Family Caregivers: Hope as a Mediator
Authors: Jiang Jiin-Ling , Chang Shing-Ling , Wang Ke-chieh , Ma Yu-Chin
Published: November 2024

Aim This study investigated the mediating role of hope in the relationship between anxiety and fatigue in family caregivers of individuals with dementia. Methods A cross-sectional design was employed, with data collected from 84 family members caring for a patient with dementia in Tzu Chi Hospital in eastern Taiwan. Instruments were the Herth Hope Index, a fatigue scale, and an anxiety scale. Results The findings revealed a significant negative correlation between fatigue and hope (r = − 0.431, p < .01), a significant positive correlation between fatigue and anxiety (r = 0.584, p < .01), and a significant negative correlation between hope and anxiety (r = − 0.364, p < .01). Furthermore, the results indicated that anxiety indirectly predicted fatigue through hope. Hope was a mediating variable between anxiety and fatigue, accounting for 15.6% of the mediating effect. Conclusions Prioritizing the physical and mental health of family caregivers of individuals with dementia by fostering hope can help alleviate their caregiving fatigue and enhance their overall well-being.
Adversarial Red Teaming for NIDS:Model-Agnostic Physical-Space Attacks
Authors: Rizvi Syed Wali Abbas , Farrukh Yasir Ali , Khan Irfan
Published: November 2024

Adversarial examples have been widely studied across domains such as image recognition and speech processing, but their implications for Network Intrusion Detection Systems (NIDS) remain underexplored. This paper introduces the NIDS Robustness Toolbox (NRT), a model-agnostic tool designed to generate adversarial samples for machine learning-based NIDS by directly manipulating network traffic in the physical space. Unlike traditional approaches, our method requires no information about the processing pipeline or underlying model architecture, making it adaptable and highly practical for real-world red teaming. The NRT facilitates the creation of adversarial traffic that disguises malicious intent within realistic network behavior, targeting both flow-based and payloadbased NIDS models. Experimental evaluations demonstrate that these adversarial samples lead to significant declines in detection performance, assessed across multiple metrics including precision, recall, F1-score, evasion, and misclassification rates.These findings reveal substantial vulnerabilities in current NIDS configurations, underscoring the critical need for more resilient, adaptable defenses to withstand sophisticated adversarial threats in real-world deployments.
Predictors of postictal delirium at 30 minutes after electroconvulsive therapy in Indian patients
Authors: Dagar Sonali , Daria Vinod , Daria Usha , Singh Kuldeep , Gupta Shreya
Published: November 2024

Acute confusional state or delirium occurs in 12% of patients after receiving electroconvulsive therapy (ECT). This adverse effect can lead to falls and injuries in the recovery room. The duration of disorientation also predicts retrograde amnesia in patients. Knowing the predictors of postictal delirium after ECT will help optimize treatment and improve the safety of therapy in this part of the world, where ECT is still widely used for the treatment of psychiatric disorders and acute agitation and is increasingly becoming a daily care procedure. The aim of this study was to identify predictors of post-ECT delirium. We hypothesized that patient variables, type of general anesthesia and ECT treatment variables might influence the likelihood of delirium. Methodology: A prospective randomized study was conducted after registration with the Central Trial Registry of India via the Richmond Agitation-Sedation Scale and the Confusion Assessment Method for the Intensive Care Unit at 30 min after the first ECT treatment of 90 consecutive patients. Patients were randomized into three groups and received different anesthetic agents. We used the half-age dosing method for ECT, and patient variables were extracted via chart review. Variables, including the type of general anesthesia, ECT treatment parameters, age and biochemical parameters of the patient, were analyzed. Results: Postictal delirium was present in 10 patients (11.11%) at 30 minutes after ECT administration. Significant differences in baseline hemoglobin levels and systolic blood pressure were detected between delirious and nondelirious patients at 30 minutes post-ECT administration (p < 0.05). No significant differences were observed in age, number of concomitant medications, anticholinergic cognitive burden, baseline biochemical characteristics, type of anesthesia, total charge, stimulus duration, or seizure length for electroconvulsive therapy between these two groups. Conclusion: Potential predictors of delirium, such as baseline hemoglobin levels, can lead to improved risk stratification and personalized treatment approaches. The choice of anesthetic does not predict delirium after ECT. Long seizure duration is not a risk factor for prolonged disorientation after the administration of electroconvulsive therapy. Adequate seizure duration can be administered to patients with the choice of appropriate anesthetic agents for effective ECT without risk for post-ECT delirium.
Protective effect of probiotics on the intestinal mucosal barrier and expression of Zonulin, ZO-1, and MUC1 in the intestinal tissue of yaks
Authors: Chang Zhenyu , Liu Ruidong , Dong Hailong , Fouad Dalia , Nawaz Shah , Zhong Lang , Wu Qingxia
Published: November 2024

Background
Diarrhea is the most common disease among yak calves in Tibetan breeding farms, primarily caused by E.coli. The study aimed to investigate the preventive effect and mechanisms of probiotics on E. coli-induced intestinal mucosal barrier damage in yak calves.
Methods
Twenty-four healthy yaks were randomly divided into four groups: control group, model group (E.coli O78), treatment group A (E.coli O78 + probiotics), and treatment group B (E.coli O78 + flufenicol). Serum levels of Zonulin protein were detected by ELISA, intestinal pathological changes were observed by HE staining, and mRNA levels of Zonulin, ZO-1, and MUC1 in intestinal tissues were quantitatively measured by PCR.
Results
The results showed that compared to the control group, the model group exhibited a significant increase in the serum Zonulin level of calves (P < 0.01). Following probiotic treatment, serum Zonulin levels in group A treatment decreased significantly compared to the model group (P < 0.01), while serum Zonulin levels in group B treatment also showed a significant decrease (P < 0.05). In contrast to the control group, the intestinal mucosa of the model group had extensive infiltration of inflammatory cells, along with degeneration, necrosis, and exfoliation of intestinal epithelial cells. Treatment Group A exhibited an intact intestinal structure with very well-developed intestinal villi and glands, indicating that probiotics had a protective effect on the intestinal mucosal structure and reduced intestinal mucosal damage, improvement of intestinal health in calf yaks. The results of the quantitative fluorescence assay revealed that probiotics significantly reduce the expression of Zonulin mRNA in the intestinal mucosa (P < 0.05), and increase the expression of ZO-1 and MUC1 mRNA (P < 0.05), indicating that probiotics can inhibit or increase the expression of proteins related to intestinal permeability pathways and play a role in the prevention and treatment of E.coli O78 induced diarrhea in yak calves.
Conclusion
The findings of this study suggest that probiotics can influence proteins which involved in intestinal permeability and have an obvious effect on the treatment and prevention of diarrhea caused by E. coli O78. Probiotics can be used as an alternative drug for the treatment and prevention of such types of diseases.
Multilingual AI System for Detecting Offensive Content Across Text, Audio, and Visual Media
Authors: Koreddi Venkatesh , Manisha Nalluri , Kaif Shaik Mohammad , Teja Yeligeti Sai
Published: November 2024

This project aims to develop an AI system with advanced capabilities to detect offensive language across diverse platforms—covering text, audio (both live and recorded speech), and images (such as memes)—in multiple languages. By lever-aging technologies like Natural Language Processing (NLP), Speech Recognition (SR), and Optical Character Recognition (OCR) for identifying text within images, the system can already flag potentially harmful or inappropriate content. Integration with Google Translator ensures automatic detection and translation of input languages, enabling global applicability and enhanced reliability. For text analysis, the system utilizes BERT (Bidirectional Encoder Representations from Transformers), a large, pre-trained model known for its strong contextual and semantic comprehension of human language. As the digital landscape rapidly evolves, precise identification of offensive content is becoming ever more essential. Through this project, we are building robust, fair, and impactful technology to foster safer online environments for all users, addressing this significant challenge head-on.
1D Modelling and Diagnostics of Low-Pressure Capacitively Coupled Radio-Frequency Argon Plasma
Authors: Atlas Sharona , Lavan Shani Har , Kaplan Amir , Lehrer Avi , Rozenberg Illya , Zhao Hao , Baraban Joshua H.
Published: November 2024

We utilized a combination of experimental alongside data-driven and theoretical modelling techniques to study non-thermal plasma properties and observables including optical emission spectral intensities, electron temperature, species concentrations, degree of ionization, and reaction rates. As a case study we measured the plasma properties of Argon gas in the low-pressure regime using optical emission spectroscopy (OES) while varying plasma input power and gas flow rate. We used data-driven and drift-diffusion modeling techniques to obtain complementary information, including electron temperature, reduced electric field, and species densities. The calculated density number of excited argon has a linear correlation to measured emission intensity, and we found that the dominant effect on Ar I intensity is the applied power with the gas flow (or pressure) the secondary factor (77% and 20%, respectively). The electron temperature increases with power but decreases with flow (or pressure). Combining the measured and modelling results help to understand the cold plasma dynamics and chemistry towards more complex plasma chemistry applications.
CH02 peptide-stimulated periodontal ligament stem cells enhance periodontal regeneration
Authors: Wang Huijuan , He Huiying , Cheng Xin , Feng Qi , Yang Xuesong , Chen Xiaojia , Huang Yue
Published: November 2024

Objectives
Periodontal ligament stem cells (PDLSCs) are considered ideal seed cells for periodontal tissue engineering and regeneration, and optimizing their efficacy is a pressing challenge. Although basic fibroblast growth factor (bFGF) has been extensively studied for promoting periodontal regeneration, its instability limits its application. This study introduces a smaller, less degradable peptide, CH02, to address this issue. Therefore, this study aims to explore the promoting effect of the CH02 peptide on the osteogenic differentiation of PDLSCs, providing new support for periodontal regeneration.
Methods
Extracted PDLSCs from human premolars; used bFGF as a positive control to analyze the effects of CH02 on the proliferation, toxicity, migration, osteogenic differentiation, and calcification ability of PDLSCs; RT-qPCR analysis of osteogenesis-related gene expression; constructed a rat model of periodontal bone defect, delivered PDLSCs encapsulated in Matrigel to the defect site, and intervened with CH02 and bFGF for 2W and 4W respectively, then analyzed bone regeneration through Micro-CT, HE staining, Masson staining, and immunohistochemistry.
Results
The extracted PDLSCs meet the international standards for mesenchymal stem cells. CH02 at 25 µg/mL promotes the proliferation, migration, and osteogenic differentiation of PDLSCs, with effects comparable to those of 25 ng/mL bFGF. CH02 enhances the expression of osteogenic-related genes RUNX2, OCN, and COL-1 in PDLSCs. In vivo, CH02 promotes the repair of periodontal bone defects in rats by PDLSCs.
Conclusions
PDLSCs have the potential for osteogenic differentiation; CH02 is more efficient than bFGF in promoting osteogenic differentiation of PDLSCs and the repair of periodontal bone defects in rats.
Separation and Recovery of Niobium coating from 440C Tool Steel by High-temperature Oxidation
Authors: Gupta Akanksha , Mishra Brajendra
Published: November 2024

Niobium is a transition metal with various oxidation states. It oxidizes readily to form NbO, NbO2, and Nb2O5 (Niobium pentoxide) in the presence of oxygen at elevated temperatures. Niobium pentoxide is the most common and stable oxide phase of Niobium which has high dielectric constant and high refractive index and finds applications in Niobium metal production (main application), production of optical glasses, as a precursor for production of lithium niobate (ceramic), dielectric capacitors, and other smaller applications. The Nb2O5 market stands at 240 million USD in 2021 with a CAGR of 5.8%. Nb2O5 has a pilling-Bedworth ratio (ratio of volume of niobium pentoxide formed to the volume of niobium metal) of 2.69 which is very high resulting in high compressive stress over niobium substrate causing the formed niobium pentoxide to detach and spall off. Taking advantage of this property of Niobium, the high-temperature oxidation technique for Niobium coating removal from 440C tool steel substrate as Nb2O5 is suggested in this study. The oxidation parameters evaluated are temperature and time, and the oxidation kinetics of Niobium coating is studied and presented. The steel substrates resistance to oxidation is studied post-oxidation to examine its mechanical and chemical properties. This is conducted in order to evaluate its performance for extension of its service life for intended additive manufacturing application. This is conducted by investigating elemental maps, phases formed, and hardness tensile profiles of the composite and oxidation product post oxidation.
Study on flutter stability of TiBw mesh reinforced titanium matrix composites thin-walled parts in ultrasonic vibration machining
Authors: Dong Guojun , Guo Zhiqing , Cao Yongzhi , Lai Ruida , Wu Mengwei
Published: November 2024

In order to study the influence of ultrasonic vibration on the machining chatter stability of reticulated titanium matrix composite thin-walled parts, firstly, the influence law of machining parameters on ultrasonic cutting separation ratio was obtained through kinematics analysis. Then, based on the cutting separation ratio, an improved semi-discrete method is established to predict the chatter stability of ultrasonic vibration milling, and it is found that the stability lobe diagram corresponding to ultrasonic vibration milling is higher than that of traditional milling as a whole. Then, the cutting force coefficient identification and modal experiment of ultrasonic vibration machining of titanium matrix composites are carried out, and the cutting force coefficient and modal parameters of ultrasonic vibration machining are analyzed. Finally, based on the drawn stability lobe diagram, different machining parameters are selected to carry out the stability model verification experiment, and the vibration signal measured by a laser vibrometer is used to identify the machining stability state. The experimental results verify the model's accuracy and show that ultrasonic vibration can suppress the machining chatter.
Geophysical Study of Crustal Deformation Using Gravity Data: Muzaffarabad and Adjoining Regions in Azad Jammu and Kashmir
Authors: Zulqranan Arooj , Šprlák Michal , Khan Muhammad Rustam
Published: November 2024

The present research utilizes the Gravity method to investigate Muzaffarabad and its adjacent areas in Azad Jammu and Kashmir. Qualitative interpretation involved creating various maps such as Bouguer Anomaly, Free Air Anomaly, Elevation, Residual Bouguer Anomaly, and Regional Bouguer Anomaly maps. Quantitative interpretation included computing a geological model along the selected profile A-A'. The study revealed subsurface structural features and the thickness of the sedimentary-metasedimentary wedge, identifying two major faults: The Muzaffarabad Fault (MF) and Bagh Basement Fault (BBF). The NW-SE contour trend in the north indicates the MF, while the western part shows the Jhelum strike-slip fault trend. The BBF extends from Mahoter to Shahdara and reaches the Moho depth. The geological model demarcates the MF within the Miocene Murree Formation, dipping at 49° and connecting with a detachment fault. These faults are tectonically active, indicating a risk of earthquakes that could range from moderate to high magnitudes. Numerous active landslides and fault-related folding and faulting highlight the region's seismic activity. Areas above the hanging walls of MF and BBF are unsuitable for heavy civil engineering structures, whereas footwall areas are comparatively feasible.
Challenges and Supports: Exploring Health Service Accessibility for Key Populations in Mozambique
Authors: Junior Simeão Hanhane , Vuvo Ana Matusse , Manuel Pedro , McOwen Jordan , Banze Áuria Ribeiro , Baltazar Cynthia Semá
Published: November 2024

Background
Key populations (KP) can have poor access to public health services. Mozambique ranks among the top ten countries with the highest HIV prevalence worldwide, with an estimated 12.5% of People Living with HIV (PLHIV). Despite national strategic efforts and guidelines to address HIV transmission among KP, pervasive stigma and discrimination in healthcare settings remain significant barriers to effective service delivery. This study aims to explore the experiences of KP in accessing healthcare and social services in Mozambique.
Methods
This qualitative study conducted in 2022 across six urban provinces, key informant interviews (KII) and focus group discussions (FGD) to explore the experiences of KPs in accessing HIV-related health and social services. Participants included Female Sex Workers (FSW), Men who have Sex with Men (MSM), People Who Inject Drugs (PWID), transgender individuals, health providers, and members of community-based organizations (CBOs). Data were collected, transcribed, and analyzed using NVivo software based on Grounded Theory.
Results
A total of 440 interviews were conducted, including 151 KIIs and 293 FGD participants. Despite the availability of targeted healthcare services and community-based support, findings indicated pervasive stigma and discrimination within healthcare settings, particularly affecting transgender individuals and PWID. Many participants reported experiencing discriminatory attitudes from healthcare providers, leading to refusal of care and inadequate treatment, which deterred KP from seeking necessary medical assistance.
Discussion
While the country has made progress in providing services tailored to KP, stigma and discrimination within healthcare settings remain critical barriers. This issue disproportionately affects transgender individuals and PWID, who often face refusal of care and poor treatment. Although CBOs have been instrumental in offering support, systemic changes are needed to create a more inclusive healthcare environment.
Conclusion
These findings underscore the importance of considering systemic changes to address stigma and discrimination in healthcare settings in Mozambique. Comprehensive training for healthcare providers, robust anti-discrimination policies, and strengthened collaboration between healthcare facilities and CBOs are essential to improve healthcare access and outcomes for KP. Promoting inclusive healthcare practices can help reduce health disparities and advance national HIV response efforts in Mozambique.
On the use of covariates for trachoma prevalence estimation using geostatistical methods: benefits and limitations
Authors: Sasanami Misaki , Almou Ibrahim , Diori Adam Nouhou , Bakhtiari Ana , Beidou Nassirou , Bisanzio Donal , Boyd Sarah , Burgert-Brucker Clara R , Amza Abdou , Gass Katherine , Kadri Boubacar , Kebede Fikreab , Masika Michael P , Olobio Nicholas P. , Seife Fikre , Souley Abdoul Salam Youssoufou , Tefera Amsayaw , Kello Amir B , Solomon Anthony W , Harding-Esch Emma M , Giorgi Emanuele
Published: November 2024

Background:
Model-based geostatistics (MBG) is increasingly used for estimating the prevalence of neglected tropical diseases, including trachoma, in low- and middle-income countries. We sought to investigate the impact of spatially referenced covariates to improve spatial predictions for trachomatous inflammation—follicular (TF) prevalence generated by MBG. To this end, we assessed the ability of spatial covariates to explain the spatial variation of TF prevalence and to reduce uncertainty in the assessment of TF elimination for pre-defined evaluation units (EUs).
Methods:
We used data from EUs in Ethiopia, Malawi, Niger, and Nigeria. For each EU, we compared two models: a model that used only age, a variable required for the standardisation of prevalence as used in the routine, standard prevalence estimation; and a model that included spatial covariates in addition to age. For each fitted model, we reported estimates of the parameters that quantify the strength of residual spatial correlation and 95% prediction intervals as the measure of uncertainty.
Results:
The strength of association between covariates and TF prevalence varied within and across countries. For some EUs, spatially referenced covariates explained most of the spatial variation and thus allowed us to generate predictive inferences for TF prevalence with a substantially reduced uncertainty, compared with models without the spatial covariates. For example, the prediction interval for TF prevalence in the areas with the lowest TF prevalence in Nigeria narrowed substantially, from a width of 2.9 to 0.7. This reduction occurred as the inclusion of spatial covariates significantly decreased the variance of the spatial Gaussian process in the geostatistical model. In other cases, spatial covariates only led to minor gains, with slightly smaller prediction intervals for the EU-level TF prevalence or even a wider prediction interval.
Conclusions:
Although spatially referenced covariates could help reduce prediction uncertainty in some cases, the gain could be very minor, or uncertainty could even increase. When considering the routine, standardised use of MBG methods to support national trachoma programmes worldwide, we recommend that spatial covariate use be avoided.
Image Shadow Removal Algorithm Based on MaskGuideAttention and Mask-Aware Enhancement Module
Authors: Wang Donghui , Wang Jinhua , He Ning , Zhang Jingzun , Zhang Sen , Liu Shuai
Published: November 2024

The complex and variable nature of shadows in natural environments—including diverse shapes, intensities, and intricate scene compositions—presents significant challenges for accurate shadow removal. To address these challenges, this study introduces a novel shadow removal algorithm, MGME-ShadowNet, designed to enhance image quality by restoring details within shadowed regions, thereby improving the performance of subsequent image processing tasks. MGME-ShadowNet integrates a MaskGuideAttention mechanism and a Mask-Aware Enhancement Module (MAEM) within a diffusion model framework, allowing it to effectively handle both soft and hard shadows, especially in complex scenes. The MaskGuideAttention mechanism adaptively adjusts the contributions of self-attention and spatial attention through learnable parameters, and it allocates attention to shadowed and non-shadowed regions based on shadow masks. Meanwhile, the MAEM module further refines the initial shadow masks generated by the shadow detection network. By combining dilated convolutions and pyramid pooling, MAEM improves the accuracy of the shadow masks, ensuring a clear distinction between shadowed and non-shadowed regions. Experimental evaluations on the SRD dataset demonstrate that MGME-ShadowNet outperforms current state-of-the-art methods, achieving a 2.09 dB increase in peak signal-to-noise ratio (PSNR) in shadowed regions and a 0.56-point reduction in root mean square error (RMSE) for shadow quality, surpassing the performance of ShadowDiffusion. These results confirm MGME-ShadowNet's effectiveness in managing complex shadow scenarios.The code for is available at
https://github.com/Donghui-Wang/MGMEShadowNet.
Midwives’ rural health experiences of ‘being-with’ women and newborns in labour and delivery settings, Ghana: Implications for policy and planning
Authors: Ani-Amponsah Mary , Richter Solina , Appiah Evans , Ampofo Evelyn Asamoah , Annan Emma , Mensah Gwendolyn , Badzi Caroline Dinam , Armah Deborah , Amankwah Bridget , Amegavluie Ruby Elikem Afi , Pwavra Joyce
Published: November 2024

Introduction: The global shortage of midwives and skilled birth attendants is a major risk factor for quality health service delivery in resource limited settings. This gap in skilled health workforce impacts quality labour and delivery services and the survival of pregnant women and their newborns, as well as midwives’ emotional and physical wellbeing. In resource-constrained contexts where midwives practice as fontline health workers, respectful maternal and newborn care delivery is compromised as midwives encounter continual distress with health system gaps. In Ghana, midwives in rural practice work as frontline health staff but their lifesaving efforts in maternal and newborn health have least been researched. We therefore aimed to explore, gain insight, and offer in-depth descriptions of the meanings embedded in midwives’ contextual experiences of being-with women and newborns in birth settings of southern rural Ghana.
Methods: Thirteen (13) midwives were purposively and conveniently sampled, and data were collected through face-to-face in-depth interviews. Data were content analysed and three major themes emerged.
Results: The study findings revealed that midwives in rural practice face complex distress circumstances that require resilience and capacity to embrace peculiarities, typically in emergency situations within resource-constrained settings where families are engaged as lifesaving companions to save maternal and newborn lives.
Conclusions: Reviewing policies on rural health care delivery focused on primary health care, planning on rural midwifery postings and creating support network for midwives are critical for saving maternal and newborn lives and improving retention of rural midwives at post. Future research is required to examine midwives’ resilience in rural practice and intention to stay for delivering quality maternal and newborn community health care service.