bluuebunny/crossref_metadata_2025_split huggingface dataset:
The experiences of medical and pharmacy students participating in a Collaborative Online International Learning on social accountability and Global Health: a qualitative study
Authors: Rault Anne-Emmanuelle , Giard Janie , Ladner Joël , Kra Ouffoue , Randrianarivo Raphaël , Chenault Marceau , Leaune Edouard 
Published: March 2024

Abstract

Background
Social accountability aims to promote a collective ethic that upholds the fundamental values of equity, efficiency, solidarity, and social justice in healthcare and is now considered as a critical mission of academic health centers. Collaborative Online International Learning (COIL) is a pedagogical approach that uses digital technology to provide experiential international learning, specifically for increasingly diverse and multicultural healthcare work environments. The SOLID'AIRS program is an innovative French-language COIL that aims to set up international exchanges and workshops on social accountability between medical and pharmacy students. The aim of our study was to assess the impact of participation in the SOLID'AIRS program on medical and pharmacy students
Method
Five universities in four different countries were involved in SOLID’AIRS. We conducted a qualitative study by performing individual, semi-directed interviews with students who participated in the program from 2021 to 2022. A thematic analysis was conducted in five chronological phases: (1) reading, (2) descriptive coding, (3) conceptual coding, (4) identification of themes and (5) production of a coherent thematic structure.
Results
After including sixteen student participants, of whom 13 were medical students, we reached saturation point and identified four main themes related to the impact of participation: 1) 'background in social accountability', 2) 'perception of the program', 3) 'perceived impacts of the program', and 4) 'difficulties encountered and avenues to improve the program'. Overall, the program was well received by all participants. The students identified the advantages and limitations of the program's distance learning format. The primary advantage of this format was its feasibility. The participants noted both professional and personal benefits of the program for their future practice. Based on the challenges faced during the first edition of SOLID'AIRS, particularly in coordinating group work and communication, participants suggested increased supervision of group projects by collaborators and organizing at least one in-person meeting for future editions of the program. The participants reported encountering difficulties during the COIL and suggested ways to improve the program.
Conclusion
Participating in a COIL on social accountability appears to be an effective way to adopt a reflective approach to medical practice and should be implemented and evaluated in other educational contexts.
Using 2% PVPI topical solution for serial intravitreous injections and ocular surface findings: a case control study
Authors: Casemiro José Henrique , Oguido Ana Paula , Casella Antonio Marcelo Barbante 
Published: March 2024

Abstract
Background
The use of povidone-iodine for ocular surface asepsis is widespread for intravitreal injections. They became frequent procedures, leading to serial exposure of patients' eyes to iodinated solutions. In this study, we investigate the changes in the ocular surface in patients submitted to repeated use of povidine for intravitreal injection of anti-VEGF asepsis, analyzing Ocular Surface Disease Index, non-invasive break up time, blinking quality, lipid layer, meniscus height and osmolarity.
Methods
This case-control study included 34 individuals (68 eyes), 14 males, 20 females aged 48 to 94. Inclusion criteria were individuals who received application of 2% povidone-iodine eyedrops for intravitreal injections treatment with the non-treated contralateral eye used as control. Ocular surface examinations were performed at a single occasion. A pre-intravitreal injection asepsis protocol with povidone-iodine was applied. All statistical analysis was performed using the STATA® 18.0 Software and a p-value = 0.05 was considered as the statistical significance value in all tests.
Results
The median number of IVIs in treated eyes was 12 (range 6–20). The results in treated eyes compared with untreated eyes were respectively : median OSDI 16 (IQR 6–39) and 12.5 (IQR 8–39) (p = 0.380); mean NIBUT 10.30 (SD ± 2.62) and 10.78 (SD ± 2.92) ( s, p = 0.476); median blinking quality 100 (IQR 100) and 100 (IQR 100 ) (%, p = 0.188); median lipid layer 87 (IQR 77–90) and 86 (IQR 74–100) (nm, p = 0.451); median meniscus height 0.22 (IQR 0.19-0,31) and 0.24 (IQR 0.20–0.27) (mm, p = 0.862), median Meiboiman gland loss 33 (IQR 24–45) and 31.5 (IQR 25–39) (%, p = 0.524); and mean osmolarity 306.6 (SD ± 21.13) and 313.8 (SD ± 29) (mOsm, p = 0.297). There was no statistically significant relationship between the repetitive use of 2% iodinated solution and signs or symptoms compatible with dry eye syndrome in this group of patients.
Conclusions
The use of iodine on the ocular surface was not statistically related to any parameter we use to evaluate ocular surface. A local anti-inflammatory and protective surface effect of the anti-VEGF used in IVIs should be considered an further studies with repetitive use of PVPI in different eye procedures will be needed to support these results.
The Influence of Social and Task Peer-Leaders on Team Cohesion and Collective Efficacy in Sports: A Meta-Analytical Review
Authors: Piasecki Piotr A. , Filho Edson 
Published: March 2024

Abstract
Background: Effective peer-leadership is paramount to team functioning, as peer-leaders help to facilitate the development of various team processes.
Aims: In the present study we examined the influence of social leadership and task leadership on cohesion and collective efficacy.
Methods: We adhered to the PRISMA guidelines and searched for relevant papers across six databases. A total of 168 papers were screened.
Results: Seven studies, representing 3548 participants and ten different sports, met our inclusion criteria. Our analysis revealed a statistically significant relationship between task leadership and social cohesion (r = .26, p< .01), social leadership and social cohesion (r = .23, p = .01), task leadership and collective efficacy (r = .21, p < .01), and social leadership and task cohesion (r = .23, p = .04).
Conclusions: These results suggest that developing task leaders will help foster social cohesion and collective efficacy, and that social leaders positively influence teammates’ feelings of cohesion and collective efficacy beliefs. Therefore, practitioners should develop peer-leadership programs that equip athletes with both task and social dimensions.
Modeling change in public sentiment with nonlocal reaction-diffusion equations
Authors: Shomberg Joseph 
Published: March 2024

Abstract
This is a brief ''proof of concept'' article that shows a nonlocal variant of a reaction-diffusion equation, which is already well suited to the study of pattern formation, is a plausible tool for the particular application of modeling change in public sentiment. Public sentiment is ubiquitous in modern society; from the marketing of consumer goods to the choice of political rhetoric, we are all affected by it.Modeling change in public sentiment has an important role when analyzing and predicting the course society is on.Of course, change is permanent. Perhaps the best-known feature in public sentiment is polarization.By this, we mean the development or establishment of a certain subset of a population whose views on a given subject are fixed to one end of the spectrum.It is when public sentiment undergoes a change do we witness the emergence of polarization.In large part we see polarization arise through the use of persuasion and rhetoric.Moreover, some marketing or arguments are more effective on certain individuals, thus leading these people into a polarized regime. Our model captures this emergence of the polarized regime. In addition, in some cases, we see the development of true polar opposites (which we call mixed polarity).Our method features:
• We use a nonlocal Chafee–Infante reaction-diffusion equation to model the evolution of public sentiment in a population that interacts with other individuals.
• We employ a pseudo-random convolution kernel as a symmetric matrix of lognor-mally distributed values. This kernel models the influence of individuals when interacting with others.
• Change in sentiment emerges and may converge to a polarized state expressed by a double-well potential. Other more complicated states occur whereby a mixed polarization emerges.
Parental experiences in the use of fluoxetine for management of ‘disruptive behaviours’ in children and youth with autism and pathological demand avoidance – a mixed methods exploratory study (Fluoxetine study)
Authors: Lim Rebecca , Yip Johnny , Richardson Anamaria 
Published: March 2024

Abstract
Background
Pathological demand avoidance (PDA) is a relatively new profile described in autism spectrum disorder (ASD), characterised by an extreme resistance to everyday demands and social interactions and may present as aggressive, destructive behaviours. This study aims to explore (through use of parental recall) the utility of fluoxetine in managing disruptive behaviours attributed to PDA.
Methods
Mixed-methods study incorporating surveys and semi-structured interviews with caregivers.
Results
Extreme Demand Avoidance 8-item measure (EDA-8) survey results showed a significant decrease in most behaviours attributed to PDA, including a decrease in frequency of the child obsessively resisting and avoiding ordinary demands and requests and having difficulties complying with demands unless they were carefully presented. The majority of participants in this study indicated that their child had either a co-occurring diagnosis of an anxiety disorder or that their child experienced anxiety. After initiating fluoxetine, parents noted improvement in their child’s behaviours and consequently improvement in their family’s quality of life.
Conclusion
Fluoxetine shows promise as an effective treatment in improving disruptive behaviours in children with PDA. Given the high prevalence of anxiety in children with PDA, we propose that the disruptive behaviours of PDA are secondary to an embodied experience of anxiety in children with autism.
The frequency degeneracy range of transverse mode in an off-axis end-pumped solid-state lasers
Authors: Li Jia'ning , Song Shengbo , Huang Gang , Jiang Zeqian , Xie Pengjian , Liao Wenbin , Lin Zhanglang , Li Bingxuan , Zhang Ge 
Published: March 2024

Abstract

The degenerate phenomena of transverse modal frequency in an off-axis end-pumped solid-state lasers was researched based on a semi-confocal cavity. Experimental results showed that at the large off-axis distance the transverse mode pattern changed from the Hermite-Gaussian mode to the geometric mode and finally back to the Hermite-Gaussian mode as cavity length varied. At the large off-axis distance, the degeneracy range of transverse mode patterns was a cavity length to mirrors radius ratio from 0.4958 to 0.5092 and the frequency degeneracy range was a cavity length to mirrors radius ratio from 0.4974 to 0.5025. The degeneracy range by observing beating frequency changes was more accurate and more useful than the method by comparing the transverse pattern changes. Furthermore, it was found that the off-axis pumping did not significantly alter the degeneracy position and range.
Exploring Resampling Techniques in Credit Card Default Prediction
Authors: Lokanan Mark 
Published: March 2024

Abstract
In the field of machine learning, the preparation of data is a pivotal step in optimizing model performance. This paper delves into the crucial role of data cleaning and transformation, with a particular emphasis on resampling techniques tailored for addressing imbalanced datasets. By emphasizing the significance of tailored data preparation methodologies, this study underscores the role of resampling techniques in optimizing model performance, especially when dealing with imbalanced datasets. Through an exploration of both undersampling and oversampling methods, the study delves into their nuanced impacts on classification performance and explores the potential trade-offs inherent in each approach. Focusing on the domain of credit card default prediction, the research leverages the UCI Credit Card dataset to provide a comprehensive analysis. The results demonstrate that NearMiss outperformed other undersampling techniques across all classifiers and evaluation metrics. Similarly, K-MeansSMOTE emerged as the top-performing oversampling technique across all classifiers and evaluation metrics. Among the techniques investigated in the study, K-MeansSMOTE oversampling yielded the highest performance accuracy. The findings from this paper enhance our understanding of the performance of different resampling techniques and contribute to the scholarship on handling imbalanced datasets. The results show the pros and cons of different resampling methods used with different machine learning algorithms. They also show how important customized methods are for getting accurate predictions. While offering valuable insights, the study acknowledges the necessity for further research to refine and generalize these techniques across diverse domains and real-world applications, thereby contributing to the broader landscape of machine learning methodologies.
GIS assisted Multi-Camera surveillance system with novel calibration approach for critical facilities
Authors: Punna Rajasekhar , G Aravamuthan , Kar Soumitra 
Published: March 2024

Abstract
The protection of any strategic and critical facilities from physical intrusionsis of prime importance to the authorities. Now-a-days, a lot of video camerasare installed for surveillance to detect intrusions along the perimeter of suchfacilities. However, monitoring through video feed from a large number of camerassimultaneously by security personnel is tedious and often error prone. This paperdescribes an intelligent system developed to assist in surveillance by detectingintrusions from the video feed of already existing infrastructure of cameras andby marking the intrusion on a GIS map in real time. GIS mapping integratesthe output of multiple cameras in a single bird’s eye view to provide a pictureof entire perimeter in a glance. The intrusions are detected using deep learningbased object detection model and the pixel location of intrusions are transformedto GIS coordinates. This approach helps in reducing the number of watch towers,patrolling frequency etc., which in turn reduces the costs to security. This alsoacts as an assisting tool to the security by pointing at the right camera feed, inwhich a probable intrusion is occurring. This approach has been implementedat a critical facility with feed from geographically isolated multiple surveillancecameras located along the perimeter of 7km stretch. The video stream is collectedand processed at a centralised server with CUDA enabled GPU devices. Thesystem achieves a frame rate of 10fps for 75 cameras. This software architectureis modular and seamlessly scales-up to handle any number of cameras
BRAF V600E Mutation in Thyroid Carcinoma: A Large-Scale Study in Han Chinese Population
Authors: Cong Rong , Ouyang Hui , Zhou Di , Li Xinying , Xia Fada 
Published: March 2024

Abstract

Background The prevalence of genetic mutations in thyroid cancer varies significantly among different ethnic backgrounds. The present study aimed to investigate the clinical potential of BRAF V600E in a large group of homogenous Han Chinese patients.
Methods From 2018 to 2021, 6232 thyroid disease patients who underwent thyroidectomy at our hospital were enrolled. We measured the diagnostic value of BRAF and plotted ROC curves. Patients with full clinical-pathological data were selected and divided into the BRAF mutation and wild type groups. We conducted univariate and multivariate analyses to quantify the differences in potential predictive factors of papillary thyroid carcinoma (PTC) patients between the groups. Kaplan-Meier survival analysis was used to estimate overall recurrence and recurrence rate.
Results The prevalence of BRAF V600E mutation was 86.0% in PTCs. The sensitivity and specificity of BRAF mutation for diagnosing PTC from suspicious lesions were 85.5% and 100%, respectively. The sensitivity and specificity of BRAF analysis in the indeterminate cytology group were 72.5% and 100%, respectively. BRAF mutation showed an independent association with older age, negative HT, larger tumor size, extrathyroidal extension, and multifocality in PTCs. In micro-PTCs (tumor size ≤1), the mutation was also positively correlated with progressive phenotypes of extrathyroidal extension and multifocality. BRAF mutation was associated with poorer recurrence-free probability in Kaplan-Meier survival analysis.
Conclusions This large single-center study revealed that BRAF V600E is highly prevalent in the Han Chinese population and demonstrated BRAF V600E mutation testing has high diagnostic accuracy and its strong association with the progress of aggressiveness in PTCs and a higher probability of recurrence. BRAF mutation can serve as an accurate marker for diagnosis and decision-making with great value.
Identification of novel tumor antigens and immune subtypes in breast cancer patients for mRNA vaccine development
Authors: Yu Haiyan , Liu Junping , Li Lintai , He Jingquan , Li Dandan , Hou Xianliang , Cai Wanxia , Chen Yumei , Dai Yong , Tang Donge , Tang Min , Zhang Wei 
Published: March 2024

Abstract

Background:Breast cancer has overtaken lung cancer as the world's most common malignancy. Despite the development of some mRNA vaccines, no satisfactory vaccination for breast cancer has entered clinical application.Methods:In this study, we used multiple analyses of expression datasets from public sources to find new possible tumor antigens for breast cancer and to hunt for potential treatment-sensitive patients.Results:We identified the antigens DST, ANO6, LAMA3, and NEDD9 as putative candidates. Furthermore, we found five predictive genes to identify specific patients inclined for vaccination, namely TRBC2, CD3D, CD27, CD3E, and TRBV28. Following that, we discovered three immunological subtypes of breast cancer, Cluster 1 and Cluster 3, which were recognized as "cold tumors" with minimal immune activity and were more likely to respond to vaccination. We uncovered that Cluster 1 and Cluster 3 could be further separated into two subgroups, each with distinct immune cell infiltration patterns, suggesting that vaccine responses could differ among these patients. The findings of our study lay theoretical foundation for the development of mRNA vaccine and provide new opportunities for personalized treatment.
Predictors of In-Hospital Mortality and Years of Life Lost in Patients with Severe Traumatic Brain Injury: A Retrospective Study in the Metropolitan Region of Vitória, Brazil
Authors: FILHO WALTER GOMES DA SILVA , DE ALMEIDA RODRIGO FREIRE , GONÇALVES JESSICA VAZ , VASCONCELOS HELLEN SILLER , LOUZADA CARLA BERNARDO , RAMOS LARISSA CUNHA SILVA SANTOS , RODRIGUES THAIS DA SILVA , DE ALMEIDA HANNA SOUZA , PEREIRA RAMON DA SILVA , GROBERIO RODRIGO MIRANDA , NASCIMENTO LUCAS RODRIGUES , ARÊAS FERNANDO ZANELA DA SILVA 
Published: March 2024

Abstract
Traumatic Brain Injury (TBI) poses a notable incidence in both developed countries and emerging economies worldwide. Each year, approximately 70 million people are affected by TBI, and around 11% of these events are classified as severe. Data from the Global Burden of Disease (GBD) in 2019 revealed that Brazil accounts for 1.1% of all moderate/severe TBI incidents worldwide. Within this context, falls stand out as the primary cause, representing 67% of cases. Analyzing the statistics at the state level, it is observed that Espírito Santo is responsible for 14% of all TBI incidents in Brazil, with falls also being the main cause, at a percentile of 67%. The discovery of predictors of TBI mortality is crucial to support intervention and prognosis strategies, potentially guiding public health policies. Due to the scarcity of studies in this area, our objective was to identify predictors of mortality in severe TBI and analyze the burden of TBI in the metropolitan region of Vitória, Espírito Santo. We conducted a retrospective observational cohort study at a trauma reference hospital in the state, including all individuals diagnosed with severe TBI from 2019 to 2022. The dependent variable analyzed was the outcome of hospital mortality. After applying the inclusion criteria, 863 individuals were included in the study, of which 450 (52.14%) had a fatal outcome, and 413 (47.86%) survived. The mean age was 48.67 years, with 82.5% being male. Falls (55.56%) were the leading cause of death in the population. The final binomial logistic regression model indicated that age up to 59 years, time up to 10 days in orotracheal intubation (OTI), and the type of trauma from falls were variables with notable predictive power for severe TBI-related mortality in the population. The calculation of Years of Life Lost (YLLs) revealed that TBI had an accumulated impact of 10,870.23 years of life lost prematurely in the study population. This is the first retrospective study to analyze predictive variables and the burden of TBI in the Greater Vitória region. However, it is important to note that unanalyzed factors may influence outcomes, such as the sample restriction to patients from a single reference hospital in the region, potentially limiting the understanding of variations in epidemiological profiles and adjacent health services.
FEDRETAIL: A Framework for Distributed Retail Data Analysis and Learning Toward E-commerce 5.0
Authors: Chongder Sumit 
Published: March 2024

Abstract
Retail data analysis has been identified as a crucial component in the pursuit of E-commerce 5.0. The recent rapid development of Information and Communication Technology (ICT) has revolutionized retail data analysis by providing advanced technologies such as big data analysis and machine learning. However, the privacy of customers has become a significant concern, making retail institutions hesitant to share their customer data. This reluctance forms isolated data islands, hindering the realization of comprehensive retail data analysis. I propose a federated learning-based retail data analysis framework, FEDRETAIL, to address this challenge. This framework allows retail data analysis federations to be formed by several institutions. None of these institutions need to exchange their customer data with each other directly, and they always keep the data in their place to ensure their customers’ privacy. We apply our FEDRETAIL framework to analyze a retail dataset via different federated learning paradigms. The experimental results show that our framework not only guarantees the customers’ privacy but also effectively breaks the borders of data islands by achieving higher analysis quality. FEDRETAIL framework closely approaches the performance of centralized analysis, which requires data collection in a commonplace, posing a risk of privacy exposure. In conclusion, the FEDRETAIL framework presents a promising solution for privacy-preserving retail data analysis in the era of E-commerce 5.0, paving the way for more effective and secure data-driven decision-making in the retail industry.