bluuebunny/crossref_metadata_2025_split huggingface dataset:
Exploring Barriers to AI Course Assistant Adoption: A Mixed-Methods Study on Student Non-Utilization
Authors: Hanshaw George , Sullivan Christopher 
Published: February 2025

Abstract

This research investigates the factors behind the non-utilization of the AI course assistant Spark among students at Los Angeles Pacific University (LAPU). Despite AI’s proven ability to enhance academic performance, motivation, and efficiency, a significant portion of students choose not to engage with this technology. Through a mixed-methods exploratory approach, key barriers to adoption are identified, including perceptions of unnecessity, lack of interest, and unfamiliarity with AI tools. External challenges, such as technical issues and a preference for traditional learning methods, are also examined. By combining sentiment analysis with thematic analysis of student survey responses, the findings offer a comprehensive understanding of the reasons for non-use. Targeted strategies—improving communication about AI’s benefits, providing training to build familiarity, and integrating AI more seamlessly into coursework—are recommended to increase adoption. Addressing these barriers is crucial, as non-utilization not only limits individual academic growth but also undermines efforts to equip students with essential skills for an AI-driven future. This research contributes to the growing literature on AI in education and provides actionable insights for educators and institutions seeking to maximize the impact of AI on learning outcomes.
Technology enhanced health professions education (TEHPE) in Eastern and Southern Africa: a Needs Assessment
Authors: Chipamaunga Shalote Rudo , Prozesky Detlef , Kafumukache Elliot , Katowa-Mukwato Patricia , Dithole Kefalotse , Merwe Lynette van der , Owusu-Sekyere Samuel , Molwantwa Mmoloki Cornelius , Gwini Rudo 
Published: February 2025

Abstract

Background
The COVID-19 pandemic escalated the adoption and development of technology-enhanced health professions education during large-scale lockdown mandated in multiple countries. Although the use of technology is a hallmark of the education of healthcare professionals, including clinical education, challenges including poor availability, lack of skills and support for technology-enhanced learning and teaching are reported. This study aimed to assess the needs for technology enhanced health professions education in higher education institutions in Eastern and Southern Africa.
Methods
This was a descriptive, cross-sectional survey to yield quantitative and qualitative data from healthcare students, educators and managers. The Substitution, Augmentation, Modification, Redefinition Model, our conceptual framework, underpinned our study and served as an organizing framework.
Results
Twelve program directors, 35 educators and 264 students responded from undergraduate nursing and medical programs. The findings indicate that ‘Other technologies used’ were relatively few – only 89 instances were mentioned by 299 respondents, and of these 89 some were basic hardware (laptops, data projectors) and online data source, which could fall under one or more of the 13 types that were drawn from the literature and the individual experiences of the researchers. There was extreme variation (between programmes and institutions) in the use of technologies. This finding is best explained by variations in the way in which programmes are offered and ‘educator’ preferences – there is clearly no ‘one size fits all’. On reasons for using educational technology, there is wide variation between categories of respondent, programmes and institutions. The main obstacles to the use of technology include that staff and students lack the required skills; no training is available; poor connectivity; lack of hardware and of funds to buy software; and lack of online learning resources.
Conclusions
The information generated, in such detail was not available before and opens many opportunities for further research as well as for planning and implementing improvements in technology enhanced health professions education. Based on the data, we propose practical recommendations organized around: Infrastructure Development, Training and Capacity Building, Curriculum reviews to align with technology, Institutional Support and Policy Development, Collaboration and Resource Sharing and Addressing Equity and Inclusion.
JNK pathway suppression drives resistance to combination endocrine therapy and CDK4/6 inhibition in ER+ breast cancer
Authors: Caldon C. , Alexandrou Sarah , Lee Christine , Fernandez Kristine , Wiharja Celine , Eshraghi Leila , Reeves John , Reed Daniel , Portman Neil , Phan Zoe , Milioli Heloisa , Nikolic Iva , Cadell Antonia , Croucher David , Simpson Kaylene , Lim Elgene , Hickey Theresa , Millar Ewan , Alves Carla , Ditzel Henrik 
Published: February 2025

Abstract

Endocrine therapy in combination with CDK4/6 inhibition doubles the progression-free survival of patients with advanced ER + breast cancer, but resistance is inevitable, leaving patients with limited treatment options. Here, we performed unbiased genome-wide CRISPR/Cas9 knockout screens using ER + breast cancer cells to identify novel drivers of resistance to combination endocrine therapy (tamoxifen) and CDK4/6 inhibitor (palbociclib) treatment. Our screens identified the inactivation of JNK signalling, including loss of the kinase MAP2K7, as a key driver of combination resistance. We developed multiple CRISPR/Cas9 knockout ER + breast cancer cell lines (MCF-7 and T-47D) to investigate the effects of MAP2K7 and downstream MAPK8 and MAPK9 loss. MAP2K7 knockout increased metastatic burden in vivo and led to impaired JNK-mediated stress responses, as well as promoting cell survival and reducing senescence entry following endocrine therapy and CDK4/6 inhibitor treatment. Mechanistically, this occurred via loss of the AP-1 transcription factor c-JUN, leading to an attenuated response to combination endocrine therapy plus CDK4/6 inhibition. Furthermore, we analysed ER + advanced breast cancer patient cohorts and found that inactivation of the JNK pathway was associated with increased metastatic burden, and low pJNKT183/Y185 activity correlated with a poorer response to systemic endocrine and CDK4/6 inhibitor therapies. Overall, we demonstrate that suppression of JNK signalling enables persistent growth during combined endocrine therapy and CDK4/6 inhibition. Our data provide a pre-clinical rationale to screen patients’ tumours for JNK signalling deficiency prior to receiving combined endocrine therapy and CDK4/6 inhibition.
Group Therapy for Depression in People Living with HIV in Kampala, Uganda
Authors: Lofgren Sarah , Akinyange Vanessa , Arinda Anita , Sebuliba Raymond , Bond David J , Boulware David R , Nakasujja Noeline 
Published: February 2025

Abstract

Depression in people living with HIV (PWH) is associated with reduced medication adherence, viral suppression, and retention-in-care. In low-resourced settings, depression interventions are needed for PWH to improve outcomes.
We conducted a randomized trial at a large, public HIV clinic. We enrolled PWH who started HIV medications <3 months prior and had depression. We randomized participants 1:1 to either an 8-week group therapy intervention or enhanced usual care. We measured depression with the Patient Health Questionnaire (PHQ-9) and Hamilton depression rating scale.
Between 2021-2023, we enrolled 137 PWH. The median age was 30 years. The median CD4 count was 332 cells/mcL. Female participants made up 64%. Baseline depression metrics were not different between groups. Most subjects had mild depression. Moderate-severe depression (PHQ-9 >10) was present in 37% of the intervention group and 38% of the control group. At three months, we found that the percentage of mild depression was significantly lower in the intervention compared to the control (11% (5/47) versus 34% (21/62), p=0.005). By 6 months, depression metrics were not statistically different as depression had resolved in 3% (3/102). The change in PHQ-9 was significantly greater in the intervention group compared to the control group.
An 8-week group therapy depression intervention was successful in relieving depression in PWH at three months compared to enhanced usual care. Group therapy can be adapted to different settings and effectively improves mood in PWH. Further work is needed to adapt psychological interventions to different settings among people with HIV in low- and middle-income settings.
A Lightweight Algorithm for Steel Surface Defect Detection Using Improved YOLOv8
Authors: Ma Shuangbao , Zhao Xin , Wan Li , Zhang Yapeng , Gao Hongliang 
Published: February 2025

Abstract

In response to the issues of low precision, a large number of parameters and high model complexity in steel surface defect detection, a lightweight algorithm using improved YOLOv8 is proposed. Firstly, GhostNet is utilized as the backbone network in order to reduce the number of model parameters and computational complexity. Secondly, the MPCA((MultiPath Coordinate Attention, MPCA) attention mechanism is integrated to enhance feature extraction capabilities. Finally, the SIoU (Simplified IoU, SIoU) is used to replace the traditional CIoU loss function, which can make the anchor frame more fast and accurate in the regression process, to improve the stability and the robustness of detection. The experimental results indicate that these enhancements have led to a reduction of 37% in calculation amount for the improved YOLOv8n algorithm, a decrease of 32% in parameter count, and an increase in average detection accuracy (mAP) by 1.2%. This model achieves a balance between lightweighting and detection accuracy while providing a viable solution for deployment in computationally resource-constrained edge computing environments such as embedded systems and mobile devices.
Identification of Low Observable Targets in Through Wall Imaging(TWI) Using Parallel Analytical Compressive Sensing (PACS) method
Authors: Taslimi M. , Ebrahimzadeh A. , Zakeri B. , Andargoli S. M. Hesseini 
Published: February 2025

Abstract

Through Wall Imaging (TWI) can be implemented using compressive sensing (CS) with fewer measurements, and a real model scenario of TWI can be realized using the finite difference time domain (FDTD) method. We propose parallel analytical compressive sensing (PACS) method to improve dielectric objects detection through the wall. We also present an optimized convolutional perfectly matched layers (CPML) using artificial bee colony (ABC) algorithm to reduce low frequency harmonics reflection of the ultra-wide band (UWB) transmitted signal from CPML layers. The PACS method calculates the measurement matrix based on the local maximums of the received signals. This process involves converting the norm-1 cost function into norm-2, providing a closed form formula to solve the CS problem. Coherence condition is satisfied by singular value decomposition (SVD) of the measurement matrix which in turn reduces the hardware complexity of the receiver. Closed form formula is executed separately for each target using a novel algorithm and their answers are added up. The proposed method achieves a compression ratio of 15% and is compared with the CFAR-BP algorithm for different SNRs which demonstrates its performance accuracy.
Bioinspired Navigation Based on Distributed Mechanoreception in the Leech
Authors: Gill Jeffrey , Nichols Sebastian , Mota Bruno , Harley Cynthia , Taylor Brian 
Published: February 2025

Abstract

Water waves help aquatic animals locate environmental stimuli. While previous studies suggest that leech mechanoreceptors have evolved to respond to relevant wave frequencies, the underlying neural processing remains unclear. This work presents a simplified computational model that mimics leech goal seeking behavior in an agent-based simulation. A simulated leech was tasked with finding the source of an artificial water wave stimulus. The agent's distributed mechanoreceptor array detected wave motion, which was processed with a computational neuroscience Winner-Take-All (WTA) framework to generate motion commands. The computational model's performance aligned with data from animal experiments. The model also suggested how different patterns of sensor ablation or placement might affect navigation performance. Our model can complement animal experiments by enabling questions to be posed that are challenging to address with live animals. Our study may also provide insights into novel approaches for processing data from multiple sensors in man-made systems.
Bibliometric Analysis of Disaster Volunteers Using Vosviewer And Biblioshiny With Data From Scopus And Web of Science
Authors: DOĞRU SALİH , PEKER İSKENDER 
Published: February 2025

Abstract

Disasters, characterized by their suddenness, unpredictability, and chaos, often overwhelm official aid teams, making it difficult for them to respond adequately or reach affected areas promptly. At such critical moments, disaster volunteers (DVs) play a vital role by quickly arriving at disaster zones and addressing essential needs. Therefore, raising awareness and conducting more studies on disaster volunteering is crucial. This study provides a bibliometric and visualization analysis of 752 studies retrieved from the Web of Science and Scopus databases in September 2024, covering the years 1989–2024. The analysis, performed using VOSviewer and Bibliometric R-tool software, aims to present the current status and trends in disaster volunteering research. Key aspects explored include annual publication performance, leading authors, institutions, countries, publication types, and research fields. Coauthorship, co-citation, and co-occurrence analyses highlight collaborative efforts and emerging topics in this field. Findings indicate that disaster volunteering is a growing area of research, with new publications increasing by approximately 12% annually. While studies in this field began in 1989, there has been a significant rise in output since 2012, predominantly in the social sciences. Frequently used keywords include "disaster," "volunteering," "disaster management," and "emergency management." Based on the results, it is anticipated that promoting disaster volunteering, enhancing community-based disaster management, improving the coordination and sustainability of volunteers, and increasing the effectiveness of spontaneous volunteers will help reduce the loss of life and property during disasters. These efforts are expected to significantly contribute to the success of disaster management processes.
Stem Cell Recruitment of Bionic Hydrogels Enhances Vascularized Bone Regeneration through Macrophage Reprogramming
Authors: Zhang Huaiyuan , Wang Yu , Qiao Wenyu , Hu Xueneng , Qiang Huifen , Xia Kuo , Du Longhai , Yang Luling , Bao Yi , Zhang Tinglin , Gao Jie , Yu Zuochong C. 
Published: February 2025

Abstract

The local inflammatory microenvironment, insufficient vascularization, and inadequate bone repair materials are the three key factors that constrain the repair of bone defects. Here, we synthesized a composite nanoparticle, TPQ (TCP-PDA-QK), with a core-shell structure. The core consists of nanotricalcium phosphate (TCP), and the shell is derived from polydopamine (PDA). The surface of the shell is modified with a vascular endothelial growth factor (VEGF) mimic peptide (QK peptide). TPQ was then embedded in porous methacrylate gelatin (GelMA) to form a TPQGel hydrogel. In the inflammatory environment, the TPQGel hydrogel can gradually release drugs through pH responsiveness, promoting M2 macrophage polarization, vascularization and bone regeneration in turn. In addition, reprogrammed M2 macrophages stimulate the generation of anti-inflammatory and pro-healing growth factors, which provide additional support for angiogenesis and bone regeneration. The TPQGel hydrogel not only can accurately fill irregular bone defects but also possesses excellent mechanical properties and biocompatibility, making it highly suitable for the minimally invasive treatment of bone defects. Transcriptomic tests revealed that the TPQGel hydrogel achieved macrophage reprogramming by regulating the PI3K-AKT signaling pathway. Overall, the TPQGel hydrogel can be harnessed for safe and efficient therapeutics that accelerate the repair of bone defects.
Amyris balsamifera essential oil promotes anesthesia in Colossoma macropomum (Cuvier, 1818): electrophysiological tools in the indication of a therapeutic window
Authors: Lins Axell Timotheo Lima Acioli , de Araújo Daniella Bastos , Eiró-Quirino Luciana , Paz Clarissa Araújo da , Reis Thaysa de Sousa , de Souza Luana Vasconcelos , Manito Alicia Chaves , Libório Mahara de Souza , Goyana Gabriela Paula , Bittencourt Daniella Rocha , Barbosa Gabriela Brito , Macchi Barbarella Matos , Hamoy Moisés 
Published: February 2025

Abstract

Currently, anesthesia is widely used in aquaculture, which raises concerns about the choice of anesthetic agent to be administered. Amyris sandalwood essential oil has muscle relaxant characteristics due to its chemical composition, which indicates its potential as an anesthetic product. Therefore, this study evaluates the anesthetic potential of Amyris balsamifera essential oil in Colossoma macropomum as a therapeutic window through behavioral tests and electrocardiographic recordings. The fish were exposed to Amyris balsamifera essential oil at concentrations of 20 µL.L -1, 25 µL L -1, 30 µL.L -1, 35 µL.L -1 and 40 µL.L -1, in immersion baths. The behavioral test showed that can caused a loss of the postural reflex in fish, with a reversible effect and recovery times dependent on the concentration of oil used. In addition, this study showed that sandalwood essential oil has the potential to decrease heart rate and maintain sinus rhythm with a dose-dependent effect. These findings were made possible by behavioral analysis parameters and electrocardiographic recordings. These results demonstrate the existence of a safe therapeutic window for the use of Amyris balsamifera essential oil, given that in the present study, there was a noticeable difficulty in recovering the postural reflex at higher doses, such as 40 µL. L -1, and a more immediate recovery at a dose of 20 µL. L -1, occurring in an adequate time of up to 5 minutes or less, which guarantees its anesthetic safety.
Cost-effectiveness of annual trivalent inactivated influenza vaccine program by age and risk status
Authors: Yu Zilian , Jiang Changzheng , Zhang Junfeng , Xiang Yi , Hu Yu 
Published: February 2025

Abstract

Background
The study was aimed to evaluate the cost-effectiveness of annual trivalent inactivated influenza vaccine (IIV3) under the context of Zhejiang province.
Methods
A state transition simulation model was constructed to estimate the health and economic outcomes of IIV3 vaccination compared to no vaccination for hypothetical cohorts of Zhejiang province stratified by age and risk status. Model input parameters were derived from multiple sources. The analysis used societal perspectives and a one-year time horizon, and permanent outcomes were also included. The primary outcome was the incremental cost-effectiveness ratio (ICER), with expression of US dollars per quality adjusted life years (QALYs) gained.
Results
In non-high risk subgroups, the ICER ranged from $6268/QALY(adults aged 50–64 years) to $11260/QALY (children aged from 6 months to 4 years). In high risk subgroups, the ICER ranged from cost-saving (adults aged ≥ 65 years) to $5260/QALY (children aged from 6 months to 4 years). Results were most sensitive to changes in the probability of influenza illness, vaccine effectiveness, probability of systematic reactions for adults aged 18–49 years with non-high risk status, while were most sensitive to changes in probability of influenza illness, cost of hospitalization, probability of death for the same subgroup.
Conclusions
Our findings indicated the ICERs of annual influenza vaccination varied by age and risk status but was less than one time of the Gross Domestic Product (GDP) per capita of Zhejiang province ($17745 in 2023), which remained cost-effective for all-age and different risk status groups from a societal perspective.
Immediate Effect of Kinesiology Taping on Dual Task Performance and Balance in Patients with Acute Stroke
Authors: Kocabal Ayşegül Akgül , Alioğlu Zekeriya , Erden Arzu , Özyaşar Ali Faruk , Erten Kübra 
Published: February 2025

Abstract

Introduction: Kinesiological taping is utilized to enhance muscle control and function by targeting the golgi tendon organ and muscle fascia in stroke rehabilitation. Within the broader objectives of stroke rehabilitation, dual tasks hold significant importance in improving attention, balance, and coordination skills. This study aimed to explore the immediate effect of kinesiological taping applied to the lower extremities on dual-task performance and dynamic balance in individuals with acute stroke.
Methods: The study involved a sample of thirty volunteer patients who experienced their first stroke within the past month. Participants were required to have upper and lower extremity stage of 5 or above according to the Brunnstrom scale and a score of 24 or higher on the Standardized Mini-Mental Test. The evaluation of bilateral task performance was conducted using the 10-meter walk test, while the dynamic balance was assessed using the sit and stand test. The dual-task and dynamic balance of the participants were compared both pre-and post-kinesiological taping application.
Results: A statistically significant difference was observed in the dual-task performance during the 10-meter walk test before and after the application of kinesiological taping (p = 0,009). Furthermore, a significant improvement in dynamic balance was observed pre-and post-kinesiological taping (p < 0,001). No significant differences were found between genders.
Conclusion: The application of kinesiological taping to the lower extremities of individuals with acute stroke demonstrated effectiveness in improving both dual-task performance and dynamic balance. It is concluded that incorporating the use of kinesiological taping techniques into rehabilitation programs may be effective.
Deep Learning for Bifurcation Detection: Extending Early Warning Signals to Dynamical Systems with Coloured Noise
Authors: Maghsoodlo Yazdan Babazadeh , Dylewsky Daniel , Anand Madhur , Bauch Chris T. 
Published: February 2025

Abstract

Deep learning models have demonstrated remarkable success in recognising tipping points and providing early warning signals. However, there has been limited exploration of their application to dynamical systems governed by coloured noise, which characterizes many real-world systems. In this study, we demonstrated that, using the normal form theorem, it is possible to leverage the normal forms of three primary types of bifurcations (Fold, Transcritical, and Hopf) to construct a training set that enables deep learning architectures to perform effectively. Furthermore, we showed that this approach could accommodate coloured noise by replacing white noise with red noise during the training process. To evaluate the classifier trained on red noise compared to one trained on white noise, we tested their performance on mathematical models using ROC curves and AUC scores. Our findings reveal that the DL architecture can be effectively trained on colored noise inputs, as evidenced by high validation accuracy and minimal sensitivity to redness (ranging from 0.83 to 0.85). However, classifiers trained on white noise also demonstrate impressive performance in identifying tipping points in colored time series. This is further supported by high AUC scores (ranging from 0.9 to 1) for both classifiers across different colored stochastic time series.