bluuebunny/crossref_metadata_2025 huggingface dataset:
Educator Perspectives on Stressors and Health: A qualitative study of U.S. K-12 educators in February 2022
Authors: Cavallari Jennifer M. , Trudel Sierra M. , Charamut Natalie R. , Suleiman Adekemi O. , Sanetti Lisa M. H. , Miskovsky Megan N. , Brennan Matthew E. , Dugan Alicia G.
Published: April 2024

Background
The teaching profession, already characterized by high stress and burnout, experienced exacerbated challenges during the height of the COVID-19 pandemic. While educators faced changing job demands over the course of the pandemic with switches in remote and in-person teaching along with COVID-19 transmission prevention strategies, the demands and resulting impact in the years that follow are still being explored. We sought to understand the stressors and health impacts of U.S. educators in the 2021–2022 school year, 2 years following the acute phase of the pandemic.
Methods
Thirty-four certified educators based in Connecticut, USA participated in 4 virtual focus groups in February 2022. A semi-structured focus group script, designed by the research team and guided by the job demands-resources model, was administered to understand stress impacts and stressors. Data were transcribed and analyzed using the constant comparative method to identify themes and sub-themes. Themes were summarized by frequency as well as by individuals.
Results
The majority of respondents reported educator well-being impacts of stress fell into three categories: physical health impacts and behaviors (76%; e.g. poor sleep, physical exhaustion, lack of exercise, unhealthy eating), psychological health impacts (62%; e.g. emotional exhaustion, anxiety, negative self-evaluation); and social well-being impacts and behaviors (68%; e.g. connections with family or friends, connections with others, relationships with coworkers). Sources of reported stressors included the school or district (94%), personal (65%), situational (35%), and to a lesser extent parents (24%), other work factors (15%), community (12%), students (12%), and state or national level (9%) factors. At the school/district level, stressors were related to protocols/expectations (91%, e.g. excessive or increased demands, insufficient or decreased resources) or administrators (38%). Personal level stressors included personal life (41%); other personal factors (20%); and income (17%); situational factors included the pandemic (26%) and safety concerns (9%).
Conclusion
Focus groups allowed us to assess the health and working conditions of Connecticut’s public education workforce 2 years following the acute phase of the pandemic. Lasting effects are relevant in the post-pandemic era and continue to pose challenges as teacher shortages increase. Targeted interventions are needed to reduce school and district-related demands and to address stress-related educator well-being.
Acceptability of an e-mental health self-help intervention aiming to improve psychological distress among persons experiencing unstable housing in France
Authors: Tortelli Andrea , Figueiredo Natasha , Martinez Julian Vadell , Roversi Aurélia , Bryant Richard , McDaid David , Lorant Vincent , Nicaise Pablo , Mediavilla Roberto , McGreevy Kerry R. , Haro Josep Maria , Sijbrandij Marit , Witteween Anke , Underhill James , Surkan Pamela J. , Melchior Maria
Published: April 2024

Background
People experiencing socioeconomic disadvantage are at high risk of having mental health needs. E-mental health tools could help address the mental health needs of this hard-to-reach population. The aim of our study was to explore the acceptability and appropriateness of a mobile-supported website adaptation of WHO’s stress management guide “Doing What Matters in Times of Stress” (DWM) among individuals experiencing unstable housing conditions, as well as among relevant health and social care sector professionals working with this population in Paris.
Methods
48 individuals (22 persons experiencing unstable housing conditions and 26 key informants including health care and social workers) participated in a two-phase qualitative study. Participants completed free listing individual interviews (FLI) aiming to investigate access to communication technologies as well as barriers and facilitators of use e-mental health tools, and focus groups (FG) examining barriers and facilitators of use of the DWM online intervention (DWM-OI). All FLIs and FGs were transcribed and content analysis was implemented.
Results
DWM-OI was considered a useful tool to help individuals deal with stress, both by individuals experiencing unstable housing conditions and by health care and social professionals. Identified barriers to use included: low literacy, lack of face-to-face interaction, and intermittent accessibility to a smartphone or to the Internet. Some participants experiencing unstable housing conditions requested assistance to use DWM-OI as they would not be entirely at ease with this technology.
Conclusion
Our data suggest that the DWM e-mental health intervention (DWM-OI) is probably well-accepted by persons experiencing unstable housing conditions and by healthcare and social workers in contact with this group. However, certain barriers need to be addressed to make this type of e-mental health tool widely accessible to individuals who experience socioeconomic disadvantage.
Risk factors analysis of Flexible Ureteroscopic Lithotripsy with UTI and construction of clinical prediction model
Authors: Xiong Feng , Zhang Pan , Fan Xiangyi , Qiao Hongliang , Cao Zhongjun , Chen Xiaobo
Published: April 2024

Purpose
The flexible ureteroscope offers advantages such as safety, minimally invasive procedures, quick recovery, and a high rate of stone removal. It has become a standard method for treating ureteral stones as well as small and medium-sized kidney stones. UTI is one of the most common postoperative complications that can lead to sepsis, systemic inflammatory response syndrome, urological sepsis, and even septic shock. Our aim is to analyze the risk factors for UTI following ureteroscopic lithotripsy and to develop corresponding clinical prediction models.
Methods
A retrospective analysis was conducted on patients who underwent FURS surgery for urinary tract stones at our hospital from January 2021 to January 2023. Univariate and multivariate logistic regression analyses were used to identify independent risk factors for postoperative infection and to develop the corresponding Nomogram prediction model.
Results
In total, 560 patients underwent flexible ureteroscopic lithotripsy (FURL) in our hospital, including 111 patients who developed postoperative UTI, resulting in an incidence rate of 19.8%. Analysis of the multivariate logistic regression data showed that renal dysfunction[OR = 2.103(95%CI:1.134–3.907),P = 0.018],positive preoperative urine culture [OR = 6.070(95%CI:1.800-20.474),P = 0.004], positive urinary nitrate [OR = 3.206 (95%CI: 1.599–6.429),P = 0.001],IL-6 > 5.3pg/ml[OR = 6.876(95%CI:3.734–12.661),P < 0.001],uric acid > 430 umol /L [OR = 2.024(95%CI:1.088–3.765),P = 0.026], ureteral stricture[OR = 3.174(95%CI:1.660–6.070), P < 0.001] were independent risk factors for UTI in patients after flexible ureteroscopy. The area under the ROC curve of the constructed nomogram prediction model is 0.89 (95% CI: 0.876–0.937). The concordance index reached 0.841.
Conclusion
Renal dysfunction, positive preoperative urine culture, positive urine nitrite, IL-6 > 5.3 pg/ml, uric acid > 430 umol/L, and ureteral stenosis were identified as risk factors for UTI after flexible ureteroscopic lithotripsy. The nomogram prediction model has high clinical value in the prediction of UTI.
Cold-water coral mortality under ocean warming is associated with pathogenic bacteria
Authors: Chemel Mathilde , Peru Erwan , Binsarhan Mohammad Mutlaq , Logares Ramiro , Lartaud Franck , Galand Pierre E.
Published: April 2024

Cold-water corals form vast reefs that are highly valuable habitats for diverse deep-sea communities. The deep ocean is, however, warming and it’s therefore essential to assess the resilience of cold-water corals to future conditions. Here we investigate the effects of elevated temperatures on the cold-water coral Lophelia pertusa (now named Desmophyllum pertusum) from the north east Atlantic Ocean at the holobiont level, the coral host and its microbiome. We show that at temperature increases of + 3 and + 5°C, L. pertusa exhibits significant mortality concomitant with changes in its microbiome composition. In addition, a metagenomic approach revealed the presence of genes markers for bacterial virulence factors suggesting that coral death was due to infection by pathogenic bacteria. Interestingly, different coral colonies had different survival rates, as well as colony-specific microbiome signatures, indicating strong colony variability in response to warming waters. Our results suggest that L. pertusa can only survive a temperature increase of < 3°C over the long term. Regional variations in deep-sea temperature increase should therefore be considered in future estimates of the global distribution of cold-water corals.
DDANet: Deep DenseAttention Learning-Based for Intrusion Detection in Industrial Control Systems
Authors: Sharma Ankita , Sahu Rakesh , Bajaj Rohit
Published: April 2024

Industrial control systems (ICSs) are integrated with communication networks and the Internet of Things (IoT), they become more susceptible to cyberattacks, which can have catastrophic effects. However, the lack of sufficient high-quality attack examples has made it very difficult to withstand cyber threats like large-scale, sophisticated, and heterogeneous ICS. Conventional intrusion detection systems (IDSs), designed primarily to assist IT systems, rely heavily on pre-established models and are mostly trained on particular types of cyberattacks. Furthermore, most intrusion detection systems suffer from low accuracy and high false-positive rates when used because they fail to take into account the imbalanced nature of datasets and feature redundancy. In this article,the Deep DenseAttention Learning Model (DDAnet), a novel and inventive deep learning scheme described in this article, is intended to identify and detect cyber attacks that target industrial control systems. The intrusion activity is regarded as a densenet-based network intrusion detection model with an attention model along with a random forest as a classifier. The DDAnet learning scheme has been extensively tested on a real industrial control system dataset. The results of these experiments reveal the great effectiveness of the scheme in identifying different types of data injection attacks on industrial control systems. Furthermore, the scheme has been found to have superior performance compared to state-of-the-art schemes and existing methodologies. The proposed strategy is a versatile method that can be easily deployed in the current ICS infrastructure with minimal effort.
Temporal clustering of streamflow extremes and relevance to flood insurance claims: a stochastic investigation for the contiguous USA
Authors: Papoulakos Konstantinos , Iliopoulou Theano , Dimitriadis Panayiotis , Tsaknias Dimosthenis , Koutsoyiannis Demetris
Published: April 2024

Recent research highlights the importance of Hurst-Kolmogorov dynamics (else known as long-range dependence), characterized by strong correlation and high uncertainty in large scales, in flood risk assessment, particularly in the dynamics of flood occurrence and duration. While several catastrophe modeling professionals nowadays incorporate scenarios that account for previous historical extreme events, traditional flood risk estimation assumes temporal independence of such events, overlooking the role of long-range dependence that has been observed in hydrometeorological processes. This study delves into the validity implications of these assumptions, investigating both the empirical properties of streamflow extremes from the US-CAMELS dataset and the ones of flood insurance claims from the recently published FEMA National Flood Insurance Program database. Analyzing the US-CAMELS dataset, we explore the impact of streamflow’s clustering dynamics on return periods, event duration, and severity of the over-threshold events and corroborate empirical findings with stochastic simulations reproducing the observed dynamics. The association between the observed flood event properties, considered as proxies of collective risk, and the FEMA aggregate flood insurance claims is then investigated. New insights are derived with respect to the strength of their linkage and its spatial variability, which are essential to accurate flood insurance and reinsurance practices.
Energetic constraints of metal-reducing bacteria as biocatalysts for microbial electrosynthesis
Authors: Miller Shaylynn , Ford Kathryne C. , Cross Megan C. Gruenberg , TerAvest Michaela A.
Published: April 2024

Background
As outlined by the Intergovernmental Panel on Climate Change, we need to approach global net zero CO2 emissions by approximately 2050 to prevent warming beyond 1.5°C and the associated environmental tipping points. Future MES systems could decrease net CO2 emissions by capturing it from industrial sources. Microbial electrosynthesis (MES) is a process where electroactive microorganisms convert the carbon from CO2 and reduction power from a cathode into reduced organic compounds. However, no MES system has attained an efficiency compatible with a financially feasible scale-up. To improve MES efficiency, we need to consider the energetic constraints of extracellular electron uptake (EEU) from an electrode to cytoplasmic electron carriers like NAD+. In many microbes, EEU to the cytoplasm must pass through the respiratory quinone pool (Q-pool). However, electron transfer from the Q-pool to cytoplasmic NAD+ is thermodynamically unfavorable. Here, we model the thermodynamic barrier for Q-pool dependent EEU using the well-characterized bidirectional electron transfer pathway of Shewanella oneidensis, which has NADH dehydrogenases that are energetically coupled to proton-motive force (PMF), sodium-motive force (SMF), or uncoupled. We also tested our hypothesis that Q-pool dependent EEU to NAD+ is ion-motive force (IMF)-limited in S. oneidensis expressing butanediol dehydrogenase (Bdh), a heterologous NADH-dependent enzyme. We assessed membrane potential changes in S. oneidensis + Bdh on a cathode at the single-cell level pre to post injection with acetoin, the substrate of Bdh.
Results
We modeled the Gibbs free energy change for electron transfer from respiratory quinones to NADH under conditions reflecting changes in membrane potential, pH, reactant to product ratio, and energetically coupled IMF. Of the 40 conditions modeled for each method of energetic coupling (PMF, SMF, and uncoupled), none were thermodynamically favorable without PMF or SMF. We also found that membrane potential decreased upon initiation of EEU to NAD+ for S. oneidensis on a cathode.
Conclusions
Our results suggest that Q-pool-dependent EEU is both IMF-dependent and is IMF-limited in a proof-of-concept system. Because microbes that rely on Q-pool-dependent EEU are among the most genetically tractable and metabolically flexible options for MES systems, it is important that we account for this thermodynamic bottleneck in future MES platform designs.
Deep peroneal nerve block may be a new treatment way for plantar fasciitis
Authors: Lin Ping , Ying Yujuan , Zhong Chaoping , Zhu Yuanfang , Gao Yang
Published: April 2024

Background
Toe dorsiflexion is considered to be an important cause of plantar fasciitis, and the deep peroneal nerve (DPN) is the only nerve innervating the ankle joint and toe dorsiflexion. We hypothesized that blocking the DPN at the lower part of the tibia can reduce dorsiflexion of the toes at rest and in motion, thereby reducing plantar fascia tension, and will not affect the patient's normal activities.
Methods
Under ultrasound guidance, a DPN block was performed 2 cm above the ankle joint. Blocking twice a week for two consecutive weeks. The VAS pain scores at rest and movement were evaluated before and after treatment. The toe dorsiflexion angle change was observed in a static state, and the plantar fascia thickness changes before and after the block were observed by ultrasound to reflect the plantar fascia tension.
Results
We analyzed the location of DNP block on the specimen, and implemented DNP block in 18 patients with unilateral plantar fasciitis. DPN block reduces the heel pain in patients with plantar fasciitis both at rest and movement, the visual analog score (VAS) at rest at baseline with a MD (95% CI) of 3.77 (2.96 to 4.59) and at 2 weeks of treatment of 1.16 (0.62 to 1.71), the VAS at movement of baseline with a MD (95% CI) of (5.22 4.75 to 5.69) and at 2 weeks of treatment of 3.16 (2.43 to 3.89). After the block the angle of toe dorsiflexion at baseline with a MD (95% CI) of 20.50° (18.7 to 22.26) was decreased to 13.08° (10.88 to 15.27), and the thickness of plantar fascia at baseline with a MD (95% CI) of 4.56 mm (4.18 to 4.95) was increased to 5.53 mm (4.95 to 5.04), showing signs of decreased fascial tension.
Conclusion
From the perspective of balancing the biological force of the plantar fascia, using DPN block can improve the biomechanical position and tension of the plantar fascia to a certain extent to promote the recovery of the damaged fascia block. As far as we know, this treatment concept may be a new treatment way for plantar fasciitis.
Knowledge Graph Link Prediction via Hyperbolic Attenuated Attention Networks
Authors: Zhang Xuanyu , Wu Jianbin , Peng Hao , Wang Junkai
Published: April 2024

Graph Attention Networks serve as prevalent models for knowledge graph link prediction, enabling the completion of link prediction tasks on general knowledge graphs. However, most current models embed nodes in Euclidean space, leading to distortion in node embedding features. Additionally, existing methods overlook the issue of assigning weights to n-hop neighbors during node embedding aggregation and fail to investigate the prediction of different relation patterns in hyperbolic space. In this paper, we propose a Hyperbolic Graph Attenuated Attenuation Network (HGAAT) model for link prediction, utilizing hyperbolic graph attention networks to handle relations and entity representations in knowledge graphs. By introducing a attenuated attention mechanism, HGAAT effectively integrates information from n-top neighboring nodes, thereby generating more accurate entity and relation embeddings in complex relational graphs. Extensive experiments demonstrate the effectiveness and superiority of the HGAAT model in knowledge graph link prediction tasks.
Physician characteristics and implicit bias in disparate rates of primary cesarean delivery in Black vs. non-Black patients
Authors: Roloff Kristina A , Okekpe Chioma C , Stowe Robert J , Valenzuela Guillermo J
Published: April 2024

Background
Black patients experience a higher chance of cesarean delivery (5–19% increased incidence over white patients) and reductions in low-risk cesarean deliveries in white patients have surpassed reductions among Black patients. The reasons driving this health care disparity are largely unknown. Here, we assess physician demographic characteristics and a measure of implicit bias in relation to primary cesarean delivery in Black vs. non-Black patients as possible contributing reasons for disparate rates of cesarean delivery by patient race.
Methods
This is a retrospective study of patients delivered at term at a single safety-net hospital. Demographics of the attending physician responsible for the delivery, including physician gender, race, years in practice, type of training, and physicians' results of an Implicit Association Test were compared to determine associations between provider factors on mode of delivery (cesarean or vaginal) by maternal race (Black vs. non-Black). Multinomial regression analysis was used to model primary cesarean delivery rates in Black compared to non-Black patients.
Results
In 4,847 singleton, term deliveries without a prior cesarean delivery, we found a significant difference in mode of delivery (cesarean or vaginal delivery) by race in the sample, with higher cesarean delivery rates in Black patients (21.3%) compared to non-Black patients (12.9%) (P < 0.001). Ten of 22 physicians (47.6%) responded to a request to share implicit association test results. Multinomial regression demonstrated higher rate of cesarean delivery in Black vs. non-Black patients that persisted for all physician attributes: gender (aOR 0.53, 0.20–1.38 95% CI), race and ethnicity (aOR 1.01, 0.94–1.09 95% CI), years in practice (aOR 0.71, 0.25-2.00 95% CI), training type (aOR1.05 0.84–1.32 95% CI), and measure of implicit bias (aOR 0.99, 0.82–1.19 95% CI).
Conclusion
We did not find that higher primary cesarean delivery in Black vs. non-Black patients were related to physician characteristics or implicit association test results.
The relationship between fetal tissue chromosomal karyotype and clinical characteristics in patients with spontaneous abortion: a retrospective study
Authors: Liu Lin , Yang Yanting , Huo Huyan , Hu Ning , Wang Fang
Published: April 2024

Background
Abnormal fetal tissue chromosome karyotypes are one of the important pathogenic factors for spontaneous abortion (SA). To analyze the characteristics of fetal tissue chromosomal karyotype in 778 women with a history of SA and its relationship with clinical features.
Methods
A retrospective study collected maternal age, body mass index (BMI), gestational weeks at miscarriage, the number of previous pregnancy losses and fetal tissue karyotypes CNV-seq data of 778 SA couples from Lanzhou University Second Hospital from October 2019 to December 2023, and described the characteristics of fetal tissue chromosomal karyotype and its relationship with clinical features.
Results
In our study, 432 patients (55.53% of total) had abnormal fetal tissue chromosomal karyotypes, with the highest incidence being trisomy syndrome (46.99%,203/432). Advanced maternal age(>35 years), early pregnancy(<12 weeks), and a history of less than four previous pregnancy losses were all identified as risk factors for fetal tissue chromosomal abnormalities.
Conclusion
The results of this study indicate that fetal tissue chromosomal abnormalities are the primary factor leading to SA. Additionally, advanced maternal age(>35years), early pregnancy(<12 weeks=, and the fewer number of previous pregnancy losses(≤ 4 times) are associated with a higher risk of fetal tissue chromosomal abnormalities following miscarriage.
Assessing the Performance of Plugin-Integrated ChatGPT-4 in the German Medical Board Examination: An Experimental Study on the Advancements and Limitations of Modern AI Modelling Approaches
Authors: Madrid Julian , Diehl Philipp , Selig Mischa , Rolauffs Bernd , Hans Felix Patricius , Busch Hans-Jörg , Scheef Tobias , Benning Leo
Published: April 2024

Background
The Generative Pre-trained Transformer (GPT-4) is a large language model (LLM) trained and fine-tuned on an extensive dataset. After the public release of its predecessor in November 2022, the use of LLMs has seen a significant spike in interest, and a multitude of potential use cases have been proposed. In parallel, however, important limitations have been outlined. Particularly, current LLM encounters limitations, especially in symbolic representation and accessing contemporary data. The recent version of GPT-4, alongside newly released plugin features, has been introduced to mitigate some of these limitations. Before this background, this work aims to investigate the performance of GPT-3.5, GPT-4, GPT-4 with plugins, and GPT-4 with plugins using pre-translated English text on the German medical board examination. Recognizing the critical importance of quantifying uncertainty for LLM applications in medicine, we furthermore assess this ability and develop a new metric termed 'confidence accuracy' to evaluate it.
Methods
We employed GPT-3.5, GPT-4, GPT-4 with plugins, and GPT-4 with plugins and translation to answer questions from the German medical board examination. Additionally, we conducted a thorough analysis to assess how the models justify their answers, the accuracy of their responses, and the error structure of their answers. Bootstrapping and confidence intervals were utilized to evaluate the statistical significance of our findings.
Results
This study demonstrated that available GPT models, as LLM examples, exceeded the minimum competency threshold established by the German medical board for medical students to obtain board certification to practice medicine. Moreover, the models could assess the uncertainty in their responses, albeit exhibiting overconfidence. Additionally, this work unraveled certain justification and reasoning structures that emerge when GPT generates answers.
Conclusion
The high performance of GPTs in answering medical questions positions it well for applications in academia and, potentially, clinical practice. Its capability to quantify uncertainty in answers suggests it could be a valuable AI agent within the clinical decision-making loop. Nevertheless, significant challenges must be addressed before AI agents can be robustly and safely implemented in the medical domain.
Comparative Cell Viability of Dentin-Bonding Adhesive Systems on Human Dental Pulp Stem Cells: Time-Dependent Analysis
Authors: Kazak Magrur , Gungor Ayca Sarialioglu , Ozman Zeynep , Donmez Nazmiye
Published: April 2024

Background
Restorative materials are in prolonged contact with living tissues such as oral mucosa, dentin, pulp, periodontal, and periapical tissues. Therefore, the potentially harmful effects of these materials and their components on oral tissues should be evaluated before clinical use. This study aimed to compare the cell viability of different dentin-bonding adhesive systems (DBASs) on human dental pulp stem cells (hDPSCs).
Methods
Three DBASs that combining MDP monomer with new hydrophilic amide monomers [Clearfil Universal Bond Quick(CUBQ), Kuraray Noritake], self-reinforcing 3D monomer [Bond Force II(BFII), Tokuyama)], and dual-cure property [Futurabond DC(FBDC), VOCO] were used. Three (n = 3) samples were prepared for each group. Samples were incubated in Dulbecco's modified Eagle's medium (DMEM) for 24 hours (h), 72 h, and 7 days (d) to obtain extracts. For the control group, cells were cultured without DBA samples. Cell viability of DBASs extracts was measured using a cell proliferation detection kit (WST-1, Roche). Statistical analysis was performed using two-way ANOVA and post-hoc (Duncan) tests (p < 0.05).
Results
At 24 and 72 h statistically significant differences were determined between control and BFII, control and FBDC groups (p < 0.05), while no differences between control and CUBQ groups (p > 0.05). On the 7th d, statistically significant differences were found between the control and experimental groups (p < 0.05), while no differences between experimental groups (p > 0.05). A statistically significant difference was detected for the BFII group over the three-time interval (p < 0.05). The lowest cell viability was observed for the FBDC group at 24 h, and the difference was statistically significant when compared with 72 h and 7th d (p < 0.05).
Conclusion
All DBASs showed different cell viability values at different contact times. In addition to the contents of DBASs, their pH should also be taken into account in terms of biocompatibility.
Research Hotspots and Evolution Trends of “Reused Brick”: A Bibliometric Analysis based on VOSviewer
and Citespace 1977-2022
Authors: Yu Boyuan , Luo Jianing , Li Yangzhi , Fingrut Adam
Published: April 2024

Recycling and reuse alleviate the already scarce natural resources to some extent and promote a rational distribution of resources. This study summarizes various aspects of the current recycling phase of reused bricks. It discusses the drawbacks of various utilization methods in the building and construction sector and the non-degradable recycling potential. This study aims to visualize the current state of research and knowledge structure of the literature related to reused bricks based on the scientific bibliometric survey of Citespace and VOSview. Intuitively, topics within the field were clustered and analyzed. It was found that most of the waste originates from urban development processes, such as construction waste (CDW); material recycling research in building and construction materials manufacturing and construction is mainly based on the mechanical kinetic energy of the material to degrade it and use it as an aggregate for new bricks and as a new aggregate for brick making or mixing concrete. In this study, a systematic review of the material degradation and reuse processes involved in the reuse brick topic is presented, and related studies are clustered summarized, and discussed, with the expectation of providing a theoretical basis and technical support for future research in the field of reuse brick and its subfields.
Research on textile Defect detection Algorithm for Deep Learning
Authors: Si Yachao , Gao Jiajie , Zhao Xingxuan
Published: April 2024

Textile defect detection is a crucial aspect of the textile industry. H owever, the detection accuracy is often low due to the small size of textile de fects and the influence of fabric texture background. To address these issues, we propose a textile defect detection algorithm based on YOLOv8.The reparameter ized structure was introduced to the original YOLOv8 to achieve hardware effici ency with the RepGhost module. The head section incorporates a new GD Mechanism and includes the Wasserstein Distance loss function.This method accurately ide ntifies the location and type of defects in textiles with high precision under complex backgrounds, meeting the needs of industrial textile production. We con ducted training and comparison experiments on different models using the AITEX public dataset and Roboflow open source dataset. We also designed ablation expe riments to verify the considerable improvement of each enhancement on the evalu ation index. The experimental results indicate that the detection accuracy of t he enhanced YOLOv8 model in the task of detecting textile defects has increased by 18.9% to 93.8% on the public dataset. The number of parameters has increase d by 10.94MB, and the FLOPs have increased from 8.2G to 11.3G. The improved alg orithm has significantly enhanced the accuracy. It can effectively handle large amounts of data and recognize defects even under complex backgrounds, meeting the fast, complex, and high-precision requirements of the textile industry.
An Interest-Aware Graph based Recommendation Model for Unveiling User Preferences
Authors: Brown Katherine , Wong Ethan , Dubois Gabriela , Matthew Lucas
Published: April 2024

The rise of the Internet has ushered in an era of unprecedented data proliferation, presenting users with a daunting information overload dilemma when navigating a vast array of choices. This phenomenon has underscored the need for effective recommendation systems to assist users in navigating this abundance of information. Indeed, recommender systems have emerged as indispensable technologies for diverse online platforms, tasked with predicting user engagement with various projects. Many recommendation algorithms based on graph neural networks predominantly rely on user and item ID information to extract features, overlooking valuable user-item features embedded in additional data such as review texts. Alternatively, some approaches utilize auxiliary information to augment network training, adding complexity to the process. While models like GCMC and those presented in literature attempt to aggregate synergistic signals at different rating levels separately, they still do not adequately address the discrepancies in user viewpoints when amalgamating signals from multiple levels. Building upon the aforementioned considerations, this paper introduces an interest-aware message passing recommendation model. The proposed model employs two distinct methods to partition the graph into subgraphs: one for partitioning users and another for partitioning items separately. Through high-order graph convolution operations conducted within these subgraphs, the model aims to learn node representations for users and items, leveraging both weak user-item relationships within subgraphs and weak item-item relationships between subgraphs, thereby enhancing the expression of users' interests and preferences.
Electronic medical record system user satisfaction and its implications for individual work performance: The case of a university teaching hospital in Rwanda
Authors: Uwamungu Evode , Marara Alpha Arsene , Munyaneza Emmanuel , Pinney Joel
Published: April 2024

Information system user satisfaction has been extensively documented as a key component and a surrogate of success and a determinant of individual and organizational performance. However, most related studies have focused on measuring user satisfaction and its impact through mathematical models, which might not exhaustively capture the issues affecting user satisfaction and performance. This study was conducted at the “Centre Hospitalier Universtaire de Kigali”, one of the two tertiary public and university teaching hospitals in Rwanda. This hospital has been implementing OpenClinic as an electronic medical record system since 2007, and few studies have focused on its evaluation. In addition, no study has focused on understanding the implications of user satisfaction for individuals’ work performance in this hospital. This study was cross-sectional mixed research using an explanatory embedded design. The data were collected from a convenient sample of OpenClinic users through questionnaires, which included closed- and open-ended questions, to capture both quantitative and qualitative data. The OpenClinic user satisfaction was high (91%), as was the proportion of users who perceived it as having a positive impact on their work performance (94%). The relationship between user satisfaction and perceived impact was statistically significant, and satisfied users were 20 times more likely to perceive that the impact was positive than unsatisfied users. Important concerns were expressed by users, and the main concerns were the poor functionality of the system due to unstable internet, the limited capacity for use and the scarcity of computers. Therefore, the implementation of the Electronic Medical Record system at the hospital has been successful, and user satisfaction has led to a perceived positive impact; however, further improvements are needed for optimal success. The inclusion of a qualitative component in future studies is recommended for a better understanding of IS success.
I need to see me on TV: Parasocial affirmations of sexual and gender identity development of LGBTQ+ mass media consumers
Authors: Lowe Don
Published: April 2024

This project presents a new cycle model of media usage by LGBTQ+ community members in the United States that reveals a purpose previously unnamed and undefined. While parasocial contact, parasocial interaction, and parasocial relationships have been present in the academic literature for quite some time (as early as 1956 when Horton and Wohl first wrote of the phenomenon), use of media to parasocially affirm one’s LGBTQ+ status is unique to this study. This study used qualitative methods to examine a specific mass media audience, LGBTQ+ individuals, and asked them, in one-on-one interviews, how they utilize mass media to assist with their sexual and gender identity development.
Arguably, the most important finding is that: instead of parasocial interactions or parasocial relationships participants reported parasocial affirmations. Parasocial affirmations are defined by this project as usage experiences of media characters/personalities that allow for visualization of self-acceptance. These affirming associations in turn create a need for additional experiences and the process starts again. The affirmations include information about successful negotiation of sexual and/or gender identity and therefore, affirming their own sexual and gender identity. Theoretical implications of this study include an extension of the parasocial interaction/relationship theory with the addition of parasocial
Cotranscriptional folding and fragment-based drug discovery of regulatory mRNA
Authors:   , Völklein Albrecht Eduard
Published: April 2024

This work investigated cyclic-di-nucleotide (CDN) riboswitches, gaining a detailed understanding of their folding during transcription and the feasibility of 19F-NMR fragment-based screening for RNA binding lead structures for riboswitch aptamers.
Monitoring of pollutants in air of Bishkek, Kyrgyz Republic
Authors:   Kyrgyz-Russian Slavic University named after B.N. Yeltsin, Glazunov Dmitrii , Ordobaev Beishenbek ,   Kyrgyz-Russian Slavic University named after B.N. Yeltsin, Smetankin Yarosla ,   Kyrgyz-Russian Slavic University named after B.N. Yeltsin
Published: April 2024

The air quality in the capital of the Kyrgyz Republic Bishkek was analyzed. The study established that there is a problem of pollution, especially in the autumn-winter period. It was shown that the main sources of emissions into the air are thermal power plants, heating in the private sector and urban transport. Priority pollutants have been identified – these are particles 2,5 and 10 microns (PM2,5 and PM10) in size. It was concluded that it is necessary to develop a modern system for monitoring harmful substances in the air. The methodology for conducting comprehensive studies to obtain a large amount of information on priority components and sources of pollution was discussed. Examples of the air monitoring in the urban environment of Bishkek were provided. The Kyrgyz-Russian Slavic University has been testing a technique for automatic monitoring of atmospheric air in the urban environment and on highways. The article discussed the use of software developed by the university. This software complements the capabilities of the Russian “Ecologist” program and can be used in any region of the Kyrgyz Republic.
Labor safety improvement at heat and power supply facilities
Authors:   Occupational Safety and Health Administration, Mochalov Roman , Elkin Anatoly ,   Nizhny Novgorod State Technical University Named by R.E. Alekseev
Published: April 2024

Improving the occupational safety management system involves the development of recommendations for implementing modern methods for assessing occupational risks and the hazards of technological processes, using effective collective and individual protection tools, making decisions on the development of investment programs intended to improve conditions and labor protection at enterprises. The purpose of the study is to analyze accidents and injuries at heat and power supply facilities and develop measures to improve occupational safety management and reduce man-made risks. The procedure for selecting an optimal method for managing occupational safety, assessing professional risks, and the method of informing about working conditions using digital technologies were used. Measures aimed to manage occupational risks at heat and power supply facilities were developed. It was recommended to involve qualified specialists and psychologists in labor safety management, to implement digital technologies to calculate the level of occupational risks and inform workers about working conditions. Recommendations on occupational safety culture as a measure aimed to improve industrial safety were given. The proposed measures may improve safety and working conditions at heat and power supply facilities, improve social responsibility and safety culture, and simplify the procedure for informing workers about occupational risks.
A lattice pairing-field approach to ultracold Fermi gases
Authors: Ehmann Florian , Drut Joaquín E. , Braun Jens
Published: April 2024

We develop a pairing-field formalism for ab initio studies of non-relativistic two-component fermions on a (d+1)-dimensional spacetime lattice. More specifically, we focus on theories where the interaction between the two components can be described by the exchange of a corresponding pairing field. The introduction of a pairing field may indeed be convenient for studies of, e.g., the finite-temperature phase structure and critical behavior of, e.g., ultracold atomic Fermi gases. Moreover, such a formalism allows to directly compute the momentum and frequency dependence of the pair propagator, from which the pair-correlation function can be extracted. For a first illustration of the application of our formalism, we compute the density equation of state and the superfluid order parameter for a gas of unpolarized fermions in (0+1) dimensions by employing the complex Langevin approach to surmount the sign problem.
Anomalous coupling studies with intact protons at the LHC
Authors: Royon Christoph
Published: April 2024

We describe the reaches on quartic \gamma \gamma \gamma \gammaγγγγ, \gamma \gamma WWγγWW, \gamma \gamma ZZγγZZ, \gamma \gamma \gamma ZγγγZ, \gamma \gamma t \bar{t}γγtt‾ anomalous couplings at the LHC using intact protons in the final state measured in AFP in ATLAS or PPS in CMS-TOTEM.
TO EXPLORE THE EFFECT OF EXERGAMES FOR INCREASING THE RANGES OF THE SHOULDER JOINT IN INCOMPLETE SPINAL CORD INJURY PATIENTS: A CASE STUDY
Authors:   Assistant Professor, Department of Physiotherapy, Sardar Bhagwan Singh University, Dehradun, Uttarakhand., Verma Vishal , Kumar Sandilya Abhishek ,   Student Researcher, Department of Physiotherapy, Sardar Bhagwan Singh University, Dehradun, Uttarakhand., Kashyap Divya ,   Student Researcher, Department of Physiotherapy, Sardar Bhagwan Singh University, Dehradun, Uttarakhand., Ahmed Khan Zahid ,   Assistant Professor, Department of Physiotherapy, Mansarovar Global University, Bhopal, Madhya Pradesh.
Published: April 2024

This case study explores the impact of exergames on increasing shoulder joint range of motion (ROM) among individuals with incomplete spinal cord injuries (ISCIs). Subjects with ISCI participated in a 6 week structured exergaming program. Shoulder joint motion was measured pre and post intervention to evaluate changes. The results discovered a significant improvement in shoulder joint ROM following the exergaming intervention. These findings present evidence that exergames shows potential as a rehabilitation tool for addressing ISCI related impairments and, in particular, for increasing upper extremity function. Further, research with a larger sample, including control groups, is necessary to validate these findings and to determine underlying mechanisms that contributed to the changes discovered.
EXPERIMENTAL INVESTIGATION ON MECHANICAL PROPERTIES OF GEOPOLYMER MORTARS FOR REPAIR APPLICATIONS: IMPACT OF BINDER TO SAND RATIO
Authors:   Students, Department of Civil Engineering, Sethu Institute of Technology, Pullor, Kariapatti., Balahariharan K. , Ganeshpandian M.P. ,   Students, Department of Civil Engineering, Sethu Institute of Technology, Pullor, Kariapatti., Hariharan S. ,   Students, Department of Civil Engineering, Sethu Institute of Technology, Pullor, Kariapatti., Mahalingam C. ,   Students, Department of Civil Engineering, Sethu Institute of Technology, Pullor, Kariapatti., Rajeswaran P. ,   Assistant Professor, Department of Civil Engineering, Sethu Institute of Technology, Pullor, Kariapatti.
Published: April 2024

Deterioration of concrete structures made with ordinary Portland cement (OPC) as a binder is inevitable, and this requires repair or rehabilitation using appropriate repair materials. A strong and highly adhesive repair material is very important in order to ascertain the safety of damaged concrete structures. The existing repair materials, especially those that utilized conventional OPC-based materials, appear to require a certain curing condition, which prior studies have revealed to result in a weak link between the repair material and the repaired structures. Hence, an alternative material which is geopolymer mortar was utilized in this study as a repair material, and the impact of geopolymer mortars with various binder-to-sand ratios was evaluated. The physical and mechanical properties of the geopolymer mortars were assessed in addition to their performance as a repair material in terms of their bonding characteristics to conventional concrete. Findings from this study revealed that geopolymer mortar with a binder-to-sand ratio of 1:2 exhibited the highest bonding strength. In addition, geopolymer mortars with a binder-to-sand ratio of 1:3 to 3:1 exhibited better bonding strength compared to when geopolymer paste was used. NaOH& Na2SiO3.
IMPACT OF SOCIOECONOMIC STATUS ON ANTHROPOMETRIC MEASUREMENTS OF PATIENTS WITH CEREBRAL PALSY
Authors:   Post Graduate Resident, Department of Pediatrics, Government Medical College, Srinagar., Pattu Arshee , Tariq Syed ,   Professor, Department of Pediatrics, Government Medical College, Srinagar.
Published: April 2024

Introduction: Cerebral palsy is disorder of movement and posture caused by non-progressive disturbances in developing brain caused by number of factors. (1,2) Prevalence of malnutrition among children with cerebral palsy is higher than that in normal children (4-7). Some studies suggest an association between socioeconomic status and cerebral palsy whereas others refute it. Our study will discuss the impact of socioeconomic status on various anthropometric indices. Objectives: To study the relation between socioeconomic status and anthropometric indices in patients with cerebral palsy. Materials And Methods: This was a cross sectional observational study conducted in a tertiary care hospital of Srinagar from January 2021 to November 2022 which enrolled inpatient cerebral palsy children aged 1-18 years old. Height for age (stunting), weight for age (underweight), weight for height (wasting), BMI for age were derived and z scores were assessed through WHO Anthroplus and WHO anthro 3.2 softwares. Socioeconomic status was assessed by modified kuppuswamy scale updated for the year 2019. The data was analyzed with Jamovi 2.3.21. Nutritional status of children was classified as per WHO standards for z scores (i.e., -2 SD to +2 SD : Normal -2 SD to -3 SD : Moderately undernourished and <-3 SD : Severely undernourished). Relation between categorical variables was analyzed by chi square test. Statistical significance was assessed and p values < 0.05 were considered significant. The study was approved by ethical committee of our institute Results: 35 out of 102 participants (34.3%) belong to upper lower socioeconomic class. 25 out of 102 participants (24.5%) patients belong to lower middle socioeconomic class. 19 out of 102 participants (18.6%) belong to upper middle class. 14 out of 102 participants (13.7%) belong to lower class and 9 out of 102 participants (8.8%) belong to upper class.