bluuebunny/crossref_metadata_2025 huggingface dataset:
“CULTURA DE RUA, POESIA SE MANIFESTA: SLAM DIVERSA”
Authors: Hachler Ricardo Karoline , De Oliveira Thiago , Costa Fernandes Ranyane , Schultz Wittizorecki Elisandro
Published: February 2025

Este estudo, no contexto de uma pesquisa-ação participante realizada com o sexto ano do ensino fundamental de uma escola pública de Porto Alegre/RS, com intencionalidade político-pedagógica decolonial e intercultural nas aulas de Educação Física, tem o objetivo de analisar e discutir as potências do ensino e da aprendizagem com e pela arte na escola através da manifestação artística e cultural periférica do Slam. Para tanto, discorre sobre os acontecimentos da manhã integrativa da Gincana da Consciência Negra na Escola Abya Yala que possibilitaram à comunidade escolar, especialmente aos(às) estudantes e aos(às) professores(as), tanto atravessarem a temática do racismo estrutural como experimentarem o corpo no centro do processo educativo por meio da manifestação artística e cultural do Slam. Compreendemos, a partir deste trabalho, que apesar de os processos de colonialidade na educação interferirem significativamente nos sujeitos de modo a silenciar os saberes-fazeres produzidos a partir da corporeidade, a experiência artística com o Slam na escola mostrou que é possível (e potente) ensinar e aprender com e a partir de corpos encantados pelo desejo de presença, envolvidos com a dimensão sensível, estética e afetiva do mundo vivido, e que estão envoltos na reflexividade, na circularidade e na reversibilidade de sentidos.
CHATGPT E EDUCAÇÃO NA CIBERCULTURA: FUNDAMENTOS E PRIMEIRAS APROXIMAÇÕES COM INTELIGÊNCIA ARTIFICIAL
Authors: Coradini Fabio
Published: February 2025

A emergência das inteligências artificiais generativas marca um ponto de inflexão na cibercultura contemporânea, sobretudo no campo educacional. O livro “ChatGPT e Educação na Cibercultura: Fundamentos e Primeiras Aproximações com Inteligência Artificial”, organizado por Edméa Santos, Alexandre Chagas e João Batista Bottentuit Jr., assume o desafiador papel de analisar criticamente os impactos, desafios e potencialidades dessa tecnologia na transformação das práticas pedagógicas. No contexto da cibercultura, onde as interações são mediadas por sistemas digitais e os processos de aprendizagem se tornam cada vez mais multimodais, a integração da inteligência artificial (IA) à educação reflete não apenas uma questão técnica, mas também cultural e política.
LA IDENTIDAD PROFESIONAL DEL TRABAJO SOCIAL SANITARIO: UN ENFOQUE DE MÉTODOS MIXTOS EN UN CONTEXTO HOSPITALARIO
Authors: Alfaro-González Isabel , Carbonell Àngela
Published: February 2025

El presente estudio explora la identidad profe-sional del Trabajo Social enmarcado en el contexto sanitario, específicamente en el hospitalario, atendiendo a dos visiones: la de las profesionales de la Unidad de Trabajo Social del Hospital General Universitario de València (España), como la del personal sanitario con el que comparten espacio laboral. Se llevó a cabo un estudio de métodos mixtos, mediante encuestas y entrevistas, en el que participaron 87 profesionales y cinco trabajadoras sociales. Los resultados reflejan que el personal sanitario valora positivamente el Trabajo Social. No obstante, desconocen los roles y funciones de las trabajadoras sociales, vinculándolas principalmente con la burocracia y la gestión de ayudas y recursos. Por su parte, las trabajadoras sociales se identifican con la profesión y la valoran, considerando fundamental que el Trabajo Social sea reconocido como una profesión sanitaria. Asimismo, se sienten desplazadas del equipo multidisciplinar y creen que se tiene una imagen y percepción distorsionada del Trabajo Social, tanto desde el resto de profe-sionales como desde la sociedad.
FACTORES PROTECTORES EN LA CRIANZA DEL TRAUMA INFANTIL DESDE EL TRABAJO SOCIAL
Authors: Merino Lorente Susana
Published: February 2025

Las relaciones con los cuidadores familiares son importantes para el desarrollo óptimo biopsicosocial en la infancia. La disponibilidad y la calidad del vínculo del cuidado del niño es primordial. Las experiencias traumáticas pueden afectar las relaciones de apego entre el cuidador primario y el niño de varias maneras diferentes, asimismo repercuten en el desarrollo psicosocial del menor. Este artículo examina las posibles asociaciones entre el trauma originado en la infancia, la salud mental junto con la calidad de la relación parento-filial y factores protectores como el trabajo social. Se expone como se transmite a nivel epigenético las experiencias traumáticas, condicionadas por el entorno a través de los factores de riesgo o protectores que están determinados por el tipo de apego, las estrategias comportamentales, cognitivas y afectivas aprendidas. Desde este entendimiento el trabajo social puede fomentar recursos protectores, y revertir los efectos adversos de la transición a la etapa adulta y epigenética.
LA REHABILITACIÓN PSICOSOCIAL CON PERSONAS QUE SUFREN DAÑO CEREBRAL ADQUIRIDO
Authors: Olmedo Vega Verónica , Martín Cepeda Celia
Published: February 2025

El daño cerebral adquirido (DCA) es una lesión producida en el cerebro, posterior al nacimiento, debido a diferentes causas, entre ellas, el ictus. Éste, es un problema sanitario de gran impacto social en el que la intervención del/la trabajador/a social sanitario/a de neurología cobra gran importancia para desarrollar al máximo su potencial físico, psicológico y social. Para ello, se precisa de un tratamiento social que se llevará a cabo mediante un plan de rehabilitación psicosocial continuado. Se presenta en este artículo una propuesta de modelo de rehabilitación psicosocial administrado por el profesional de Trabajo Social Sanitario de neurología del HCUV a personas con ictus.
Prioritizing orthopaedic evidence uncertainties
Authors: Iken Annabelle R. , Gademan Maaike G. J. , Snoeker Barbara A. M. , Vliet Vlieland Thea P. M. , Poolman Rudolf W.
Published: February 2025

Aims

To develop a multidisciplinary health research agenda (HRA) utilizing expertise from various disciplines to identify and prioritize evidence uncertainties in orthopaedics, thereby reducing research waste.

Methods

We employed a novel, structured framework to develop a HRA. We started by systematically collecting all evidence uncertainties from stakeholders with an interest in orthopaedic care, categorizing them into 13 sub-themes defined by the Dutch Orthopaedic Association (NOV). Subsequently, a modified two-phased Delphi study (two rounds per phase), adhering to the Conducting and REporting DElphi Studies (CREDES) guideline, was conducted. In Phase 1, board members assessed the collected evidence uncertainties on a three-point Likert scale to confirm knowledge gaps. In Phase 2, diverse stakeholders, including orthopaedic surgeons, rated the confirmed knowledge gaps on a seven-point Likert scale. Panel members rated one self-selected sub-theme and two randomly assigned sub-themes. The results from Phase 2 were ranked based on the overall average score for each uncertainty. Finally, a focus group discussion with patient associations’ representatives identified their top-ranked uncertainty from a predefined consensus process, leading to the final HRA. An advisory board, the Federation of Medical Specialists, and the NOV research coordinator oversaw the process.

Results

Of the 687 collected evidence uncertainties, 160 (zero to 33 per theme) were confirmed by 41 panel members (three to five per theme). In Phase 2, 124 panel members prioritized 41 evidence uncertainties (zero to five per theme). The focus group members identified 12 key evidence uncertainties leading to the final HRA. The remaining 29 evidence uncertainties will be addressed after research on the HRA’s prioritized evidence uncertainty is completed.

Conclusion

Our framework resulted in a multidisciplinary HRA, enabling an inclusive approach to consensus-building among healthcare professionals and patients on future research priorities within orthopaedic care. We anticipate this innovative framework will enhance inclusivity and transparency, leading to broader acceptance and optimized resource allocation, ultimately reducing research waste.

Cite this article: Bone Jt Open 2025;6(2):206–214.
Capsid transfer of the retrotransposon Copia controls structural synaptic plasticity in Drosophila
Authors: M’Angale P. Githure , Lemieux Adrienne , Liu Yumeng , Wang Shuhao , Zinter Max , Alegre Gimena , Simkin Alfred , Budnik Vivian , Kelch Brian A. , Thomson Travis
Published: February 2025

Transposons are parasitic genome elements that can also serve as raw material for the evolution of new cellular functions. However, how retrotransposons are selected and domesticated by host organisms to modulate synaptic plasticity remains largely unknown. Here, we show that the Ty1 retrotransposon Copia forms virus-like capsids in vivo and transfers between cells. Copia is enriched at the Drosophila neuromuscular junction (NMJ) and transported across synapses, and disrupting its expression promotes both synapse development and structural synaptic plasticity. We show that proper synaptic plasticity is maintained in Drosophila by the balance of Copia and the Arc1 (activity-regulated cytoskeleton-associated protein) homolog. High-resolution cryogenic-electron microscopy imaging shows that the structure of the Copia capsid has a large capacity and pores like retroviruses but is distinct from domesticated capsids such as dArc1. Our results suggest a fully functional transposon mediates synaptic plasticity, possibly representing an early stage of domestication of a retrotransposon.
Social induction dynamics of the causal social R0 on clinical weight loss: Randomized trial evidence of social propagation from Amman, Jordan
Authors: Zoughbie Daniel E. , Huddleston Dillon , Ding Eric L.
Published: February 2025

An unresolved debate persists in public health, concerning a distinction between communicable diseases that are causally linked to microbes or viruses and “non-communicable diseases” that are not. We offer evidence in support of the view that public health categories need rethinking; that more precise and granular ones are needed; and that “non-communicable” and “non-infectious” can be tautological misnomers. The scientific literature suggests an underlying socially “infectious” phenomenon and we put forth a fundamental Social Contagion Hypothesis: that social networks constitute a propagating force; that this force can be quantified in socio-biological terms; and that it can be leveraged for public health. Yet a major question still remains unanswered: if weight loss, like biological pathogens, cascades through host populations, and can be mitigated through interventions targeting risky social behaviors, then can a social reproductive number (Social R0) for metabolic and cardiovascular disease be estimated and modulated? We present the first known evidence from a randomized trial, demonstrating the epidemiological dynamics of socially infectious diseases. We find that health propagation can achieve epidemic proportions (including changes in weight, 1<R0 = 1.3, p<0.01); and that public health systems can intervene to modify the R0 value thereby potentially managing, preventing, or reversing social infections at epidemic scale (yielding population-averaged comparative R0 ratios, 244<Rc<368, p<0.01, for weight change). To facilitate adoption of the methodologies, macros and code for use with various statistical software packages are included. The results indicate that the social induction of health interventions are not only possible, but that propagation can both be isolated causally via trial design and be quantified over time. This bodes enormous promise for developing and quantifying future self-sustaining public health interventions.
Signal demixing using multi-delay multi-layer reservoir computing
Authors: Tavakoli S. Kamyar , Longtin André
Published: February 2025

Brain circuitry involves a large number of recurrent feedback loops whose dynamics depend on interaction delays. Brain-inspired reservoir computing leverages the rich recurrent dynamics of interconnected units for performing tasks on inputs. In particular, time-delay reservoir computing uses the high-dimensional transient dynamics in nonlinear delayed feedback loop architectures for e.g. time series prediction and speech classification. The modification of the dynamical properties of delay-differential systems through the inclusion of multiple delays has also recently been shown to improve the performance of time-delay reservoir computing. Here we explore another aspect of such neuro-inspired computing of fundamental and technological importance: the ability to separate and predict two signals in a mixture, where each has some intrinsic predictability due to its underlying dynamics. This is illustrated using multi-delay and multi-layer reservoir computing with chaotic input signal mixtures. In contrast to Independent Component Analysis and related unsupervised learning techniques, the context here consists in the parallel supervised learning of the dynamics for each signal in order to predict each of them beyond the training set. Further, the superposition of the chaotic signals into a single input channel adds to the difficulty of the task. We quantify and explain this performance with various signals emanating from both deterministic and stochastic systems. Additionally, we explore the architecture of deep time-delay reservoir computers. Our findings demonstrate that multi-delay reservoir computing can learn and predict the future of two superimposed deterministic signals. Prediction—and thus separation—accuracy can be significantly higher in single and multi-layer time-delay reservoir computing when the first layer contains multiple delays. Bandpass filtering of the mixed signal to remove lower and higher frequencies improved the prediction by a few percent. In some cases, paradoxically, increasing the proportion of one chaotic signal in the mixture can actually help the learning of another chaotic signal, and thus slightly improve its prediction.
Bursting dynamics and network structural changes towards and away from a Pavlovian-conditioned neural network
Authors: Jeong In Hoi , Lee Kyoung J.
Published: February 2025

Understanding the intricate relationship between neural network morphology, spiking dynamics, and function is a fundamental challenge in neuroscience. This study delves into this relationship in the renowned Pavlovian conditioning model proposed by Izhikevich to address the “distal reward problem.” The model consists of spiking neurons connected by synapses whose weights evolve based on dopamine-modulated spike-timing dependent plasticity and undergoes a specific Pavlovian conditioning protocol. Throughout conditioning, the network architecture undergoes a dramatic transformation, shifting from random recurrent connections to a predominant feed-forward structure, positioning a specific subpopulation of neurons targeted during conditioning at the network’s apex. Remarkably, this new structure, termed Pavlovian memory, can persist despite spontaneous population bursting activity driven by stochastic noise and residual recurrent connections. However, significantly elevated basal dopamine levels gradually induce morphological multi-stability, including a state of complete memory loss. These findings vividly illustrate the interplay of spiking dynamics, network morphology, and memory state within a dopamine-modulated Pavlovian conditioning system. We anticipate that employing a similar systematic approach could advance our understanding of more complex functions of spiking neural networks in both machine learning and the brain.
Coverage and contextual factors associated with insecticide-treated net use among women of reproductive age in Nigeria: evidence from the 2021 malaria indicator survey data
Authors: Barrow Amadou , Ogidan Oluwakemi Christie , Nzoputam Chimezie Igwegbe , Ekholuenetale Michael
Published: February 2025

Nigeria continues to face a serious public health problem due to malaria, which contributes around 27% of all cases worldwide. Although insecticide-treated nets (ITNs) are essential interventions for preventing malaria, their use in Nigeria is still sub-optimal. Understanding the factors influencing ITN use is essential to improve malaria control strategies. This study aimed to investigate the prevalence of and factors associated with ITN use among women of reproductive age in Nigeria. We conducted a secondary data analysis of the 2021 Malaria Indicator Survey (NMIS). The sample included 14,476 women of reproductive age (15–49 years) from 567 clusters across Nigeria’s six geopolitical zones. Multilevel logistic regression was used to examine the contextual factors associated with ITN use, accounting for both fixed and random effects. Statistical significance was set at p<0.05, with 95% confidence intervals reported for all estimates. The weighted prevalence of ITN use was 41.5% (95% CI: 39.7, 43.3). The results showed Muslim women had 21% (aOR= 0.79; 95% CI: 0.67–0.94) lower odds of ITN use, when compared with the Christian women. Those who had living children were more likely to report ITN use, when compared with women with no child. The non-poor women had higher odds of ITN use, when compared with the poor women (aOR= 1.35; 95% CI: 1.19–1.52). In addition, women from multi-ethnic had 26% lower odds of ITN use, when compared with those from mono-ethnic community (aOR= 0.74; 95% CI: 0.57–0.94). The geographical region was significantly associated with ITN use among Nigerian women. Those from high-level community poverty had 53% reduction in the odds of ITN use, when compared with women from low-level community poverty (aOR= 0.47; 95% CI: 0.32–0.68). ITN use among women of reproductive age in Nigeria remained below the national target. Interventions to increase ITN use should consider the complex interplay of individual and community-level factors. Targeted strategies addressing socioeconomic disparities, leveraging cultural contexts, and implementing community-based approaches are crucial for improving ITN utilization and reducing the malarial burden in Nigeria.
Phylogenetic analysis of Mycobacterium bovis reveals animal and zoonotic tuberculosis spread between Morocco and European countries
Authors: Yahyaoui Azami Hind , Perea Claudia , Stuber Tod , Bouslikhane Mohammed , Berrada Jaouad , Aboukhassib Hamid , Allepuz Palau Alberto Oscar , Reis Ana C. , Cunha Mónica V. , Thacker Tyler C. , Robbe-Austerman Suelee , Salvador Liliana C. M. , Quinn Frederick D.
Published: February 2025

Livestock production is a fundamental pillar of the Moroccan economy. Infectious diseases of cattle and other species represent a significant threat to the livestock industry, animal health, and food safety. Bovine tuberculosis (bTB), mainly caused by Mycobacterium bovis, generates considerable direct and indirect economic losses, and an underestimated human health burden caused by zoonotic transmission. Previous studies have suggested likely M. bovis transmission links between Morocco and Southern Europe, however, limitations inherent with the methods used prevented definitive conclusions. In this study, we employed whole genome sequencing analysis to determine the genetic diversity of the first 55 M. bovis whole-genomes in Morocco and to better define the phylogenetic links between strains from Morocco and a large dataset from related and neighboring countries. With a total of 780 M. bovis sequences extracted from cattle, wildlife or humans and representing 36 countries, we discovered two new M bovis spoligotypes in Morocco and that the Moroccan clonal complexes are classified as belonging to Europe or Unknown, supporting previous studies that the Sahara Desert might be playing a key role in preventing M. bovis transmission between North Africa and Sub-Saharan Africa. Furthermore, our analysis showed a close M. bovis genetic relationship between cattle from Morocco and cattle from Spain, France, Portugal and Germany, and from cattle in Morocco and humans in Italy, Germany, and the UK. These results suggest that animal trade and human migration between Morocco and these countries might be playing a role in disease transmission. Our study benefits from a large sample size and a rich dataset that includes sequences from cattle, wildlife and humans from Morocco and neighboring countries, enabling the delineation of M. bovis genetic links across countries and host-species. Our study calls for further investigation of animal and zoonotic TB spread in Morocco and in other countries, which is important to inform future TB control measures at the animal-human interface.
Analysis of differential expression of matrix metalloproteinases and defensins in the nasopharyngeal milieu of mild and severe COVID-19 cases
Authors: Imtiaz Khekashan , Farooqui Nida , Ahmed Khalid , Zhamalbekova Alnara , Anwar Muhammad Faraz , Nasir Asghar , Ansar Zeeshan , Gul Khitab , Hussain Azhar , Sarría-Santamera Antonio , Abidi Syed Hani
Published: February 2025

Introduction

A subset of COVID-19 disease patients suffers a severe form of the illness; however, underlying early pathophysiological mechanisms associated with the severe form of COVID-19 disease remain to be fully understood. Several studies showed the association of COVID-19 disease severity with the changes in the expression profile of various matrix metalloproteinases (MMPs) and defensins (DA). However, the link between the changes in the expression of MMPs and DA in the nasopharyngeal milieu during early phases of infection and disease severity remains poorly understood. Therefore, we performed differential gene expression analysis of MMPs and DA in the nasopharyngeal swab samples collected from normal (COVID-19 negative), mild, and severe COVID-19 cases and examined the association between MMP and DA expression and disease severity.

Material and method

A total of 118 previously collected nasopharyngeal samples from mild and severe COVID-19 patients (as per the WHO criteria) and 10 healthy individuals (COVID-19 negative, controls) were used in this study. A real-time qPCR assay was used to determine the viral loads and assess the mRNA expression of MMPs and DA. One-way ANOVA was applied to perform multiple comparisons (estimate differences) in MMPs and defensin gene expression in the normal vs mild vs severe groups. In addition, a multivariable logistic regression analysis was carried out with all the variables from the data set using ‘severity’ as the outcome variable.

Results

Our results showed that as compared to controls, DA1, DA3, and DA4 expression was significantly (p < 0.05) upregulated in the mild group, whereas the expression of DA6 was significantly downregulated in both mild and severe groups (p-value < 0.05). Similarly, compared to controls, the expression of MMP1 and MMP7 was significantly downregulated in both mild and severe groups, whereas MMP2 expression was upregulated in the mild group (p-value < 0.05). Additionally, the regression analysis showed that the expression of MMP1, MMP2, and MMP9 was significantly associated with the severity of the disease.

Conclusion

The early detection of changes in the expression of MMPs and defensins may act as a useful biomarker/predictor for possible severe COVID-19 disease, which may be useful in the clinical management of patients to reduce COVID-19-associated morbidity and mortality.
Changes in vaginal Ureaplasma and Lactobacillus due to antibiotic regimen for premature rupture of membranes
Authors: Kawaguchi Haruna , Nakura Yukiko , Yamamoto Ryo , Hayashi Shusaku , Takeuchi Makoto , Ishii Keisuke , Yanagihara Itaru
Published: February 2025

Preterm premature rupture of membranes (PPROM) is associated with preterm delivery and neonatal complications. PPROM is often complicated by intra-amniotic inflammation and/or microbial invasion of the amniotic cavity with Ureaplasma or Mycoplasma. Various prophylactic antibiotic therapies have been proposed to prolong latency between PPROM and delivery, reduce the risk of clinical chorioamnionitis, and improve neonatal complications. However, information on the potential of azithromycin administration to reduce the microbial load of vaginal Ureaplasma and Mycoplasma remains lacking. This prospective cohort study included singleton pregnancies managed with prophylactic antibiotics for PPROM at less than 36 weeks of gestation. All patients received the standard antibiotic regimen for PPROM, which consisted of a single oral azithromycin and intravenous ampicillin every for 2 days followed by 5 days of oral amoxicillin. Vaginal swabs samples were collected when PPROM was confirmed and after the antibiotic regimen administration. The main outcome measures were to investigate the changes in vaginal Ureaplasma, Mycoplasma, and Lactobacillus spp. due to the antibiotic regimen. In addition, the association between the presence and changes in vaginal Ureaplasma and Mycoplasma, pregnancy outcomes, and neonatal complications were examined. Out of 82 eligible PPROM, 51 had positive vaginal Ureaplasma. Thirty-six patients (52.2%) completed the antibiotic regimen. Among those with positive vaginal Ureaplasma who completed the antibiotic regimen, 75% experienced an increase in vaginal Ureaplasma levels. For those who delivered before completing all antibiotic doses, 40% had increased vaginal Ureaplasma levels. Furthermore, the antibiotic regimen resulted in decreased Lactobacillus spp. in almost all cases. It was suggested that azithromycin and ampicillin may not be effective when targeting Ureaplasma or Mycoplasma. Since this study did not search for resistance genes, it cannot be determined that azithromycin resistance in Ureaplasma or Mycoplasma is responsible for the present results. In addition, vaginal Ureaplasma changes were not found to be associated with neonatal sepsis or bronchopulmonary dysplasia. Future studies are needed to revalidate current antibiotic therapy for PPROM.
Multi-agent deep reinforcement learning-based robotic arm assembly research
Authors: Cao Guohua , Bai Jimeng
Published: February 2025

Due to the complexity and variability of application scenarios and the increasing demands for assembly, single-agent algorithms often face challenges in convergence and exhibit poor performance in robotic arm assembly processes. To address these issues, this paper proposes a method that employs a multi-agent reinforcement learning algorithm for the shaft-hole assembly of robotic arms, with a specific focus on square shaft-hole assemblies. First, we analyze the stages of hole-seeking, alignment, and insertion in the shaft-hole assembly process, based on a comprehensive study of the interactions between shafts and holes. Next, a reward function is designed by integrating the decoupled multi-agent deterministic deep deterministic policy gradient (DMDDPG) algorithm. Finally, a simulation environment is created in Gazebo, using circular and square shaft-holes as experimental subjects to model the robotic arm’s shaft-hole assembly. The simulation results indicate that the proposed algorithm, which models the first three joints and the last three joints of the robotic arm as multi-agents, demonstrates not only enhanced adaptability but also faster and more stable convergence.
Top-down effects on translucency perception in relation to shape cues
Authors: Nagai Takehiro , Kiyokawa Hiroaki , Kim Juno
Published: February 2025

It is well established that object shape perception significantly influences the perception of translucency. However, how object shape cues such as motion and binocular disparity affect the perception of translucency in rich environments, like virtual reality or real visual environments, remains unclear. This study aims to psychophysically measure the extent to which multiple object shape cues influence the perception of translucency. Additionally, we examined whether top-down factors, such as changes in cognitive attitude caused by the sequence of experiments, affect translucency perception. The results revealed that while motion and binocular disparity enhance translucency perception, this effect is confined to situations where shape cues are poor. Moreover, the effect became particularly pronounced when the experiments began with weak specular reflection stimuli, followed by the experiments using stimuli with specular reflection. In the case of translucent objects without specular reflection, strong shape information cannot be derived solely from shading patterns. These findings thus suggest that top-down factors related to shape modulate the influence of shape cues on translucency perception.
Study on R&D result subsidy strategies for PEV enterprises based on heterogeneous consumer technology thresholds and preferences under anxiety issues
Authors: Wang Ye
Published: February 2025

Many governments worldwide hoped to stimulate Pure Electric Vehicle(PEV) enterprises’ R&D and sales through R&D result subsidy policies, but the anxiety issues significantly reduced PEV sales and weakened the policy effectiveness. To achieve better incentive effects, considering the impact of anxiety issues on subsidy strategies is necessary. As anxiety problems stem from typical behavior characteristics of PEV consumers——consumer technology thresholds, reasonable study should understand them and quantify their impact from the perspective of consumer technology thresholds. Therefore, it constructs a sequential game model among the government, the PEV company, and consumers with two dimensions of heterogeneous behavior characteristics——technology thresholds and preferences. It also determines the optimal R&D result subsidy strategies and analyzes the impact of the technology thresholds and preferences on them. It shows that the government should provide subsidies except for PEV enterprises with R&D efficiency in the higher range, and its optimal strategies must consider consumer technology threshold and preference conditions. The lower the technology thresholds of PEV consumers, the lower the optimal subsidy ratio until the technology level of the enterprise is already high enough, and there is no need for subsidies. Higher consumer technology preferences of PEV consumers will achieve the same effect. The numerical simulation shows that compared to other models, the model considering PEV consumer technology thresholds can optimize the subsidy ratio and achieve better incentive effects.
Fixed point results for ℑ-Contractions in JS-generalized metric spaces with an application
Authors: Iqbal Bilal , Saleem Naeem , Aphane Maggie , Razzaque Asima
Published: February 2025

The goal of this work is to establish ℑ-contractions and to show some novel fixed point theorems for these contractive conditions in the setting of generalized metric spaces in the sense of Jleli and Samet. Finally, using proven fixed point results, an existence result for a solution of the RLC circuit’s current differential equation is established.
Carsharing operation optimization with the comprehensive consideration of economic and social benefits
Authors: Zhong Yiping , Luo Qingyu , Gao Tingting , Long Yangyang , Liu Ling
Published: February 2025

Carsharing is regarded as a new mode of transportation that can meet the diversity of travel demands. This study develops a bi-level programming model to design operating strategies aiming to maximize economic and social benefits by determining the site location, number, size and carsharing pricing. In the upper model, a new mixed integer linear programming model is pro-posed to plan the site location, number, size, and pricing of carsharing jointly. Based on the stochastic user equilibrium principle, the lower model is a variational inequality model of travel mode and route choice, to understand the evolution of the transportation system structure after the introduction of shared cars. The results of the case study show the designed scheme can increase the economic benefits of carsharing enterprises and the social benefits of the government, and the site location, number, size, and pricing scheme impact benefits significantly. Furthermore, the setting of shared car sites at public transfer points can promote the interaction between shared cars and other modes of transportation. This study is helpful for carsharing enterprises to increase their economic benefits, enhance their capacity for sustainable growth, and improve the accessibility and flexibility of urban public transportation through sound operational strategies.
Spatiotemporal variation in fish species distribution and abundance in the Vaishav stream, Kashmir Himalaya–India
Authors: Rashid Gowhar , Singh Rahul , Kumar Abhinav , Paramasivam Prabhu
Published: February 2025

Exploring the intricate dynamics of aquatic ecosystems present study investigates the spatio-temporal variations in the ecological parameters of the fish community within the Vaishav stream, Kashmir Himalayas. Monthly field investigations were conducted at three distinct sites (SI, SII & SIII) throughout the four seasons (winter, spring, summer, autumn) from November 2019 to October 2020. The findings encompass a total of 630 specimens belonging to 11 fish species, three orders Cypriniformes, Siluriforms and Salmoniformes and four families including Cyprinidae, Nemachelidae, Siluridae and Salmonidae were reported from the study sites. Among collected specimens, Cypriniformes were dominant with nine species followed by order Siluriformes and Salmoniformes with one species each. Out of eleven fish species, six fish species belongs to family Cyprinidae, three to Nemachelidae, one to Siluridae and Salmonidae each. The analysis, employing non-metric multidimensional scaling (NMDS), Principal component analysis (PCA), Analysis of similarity (ANOSIM) and Per-mutational multivariate analysis of variance (PERMANOVA) on fish abundance data highlighted significant differences among the various sites but not across seasons. The results unveil a diverse occurrence and distribution pattern of fishes from upstream to downstream. Furthermore, diversity metrics confirm higher diversity index values downstream, indicating a more conducive environment for fish survival. Jaccard’s index reveals greater similarity in fish fauna between site-II and site-III than site-I and site-III in terms of overlap of fish species composition. The study concludes that anthropogenic activities in the stream catchment area have led to a reduction in fish diversity and abundance, with landscape features significantly influencing fish abundance in this unique Himalayan ecosystem.
Altered resting-state amplitudes of low-frequency fluctuations in offspring of parents with a diagnosis of bipolar disorder or major depressive disorder
Authors: Boisvert Mélanie , Dugré Jules R. , Potvin Stéphane
Published: February 2025

Offspring of parents with bipolar disorder (BD) or major depressive disorder (MDD) are at high biological risk (HR) of these disorders given their significant heritability. Thus, studying neural correlates in youths at HR-MDD and HR-BD appears essential to understand the development of mood disorders before their onset. Resting-state amplitudes of low-frequency fluctuations (ALFF) and fractioned ALFF (fALFF) shows moderate to high test-retest reliability which makes it a great tool to identify biomarkers. However, this avenue is still largely unexplored. Using the Healthy Brain Network biobank, we identified 150 children and adolescents HR-MDD, 50 HR-BD and 150 not at risk of any psychiatric disorder (i.e., the control group). We then examined differences in relative ALFF/fALFF signals during resting-state. At a corrected threshold, participants HR-MDD displayed lower resting-state ALFF signals in the dorsal caudate nucleus compared to the control group. The HR-BD group showed increased fALFF values in the primary motor cortex compared to the control group. Therefore, robust differences were noted in regions that could be linked to important symptoms of mood disorders, namely psychomotor retardation, and agitation. At an uncorrected threshold, differences were noted in the central opercular cortex and the cerebellar. The database is a community-referred cohort and heterogeneous in terms of children’s psychiatric diagnosis and symptomatology, which may have altered the results. ALFF and fALFF results for the comparison between both HR groups and the control group overlapped, suggesting good convergence. More studies measuring ALFF/fALFF in HR are needed to replicate these results.
Persistent advanced HIV disease in rural KwaZulu-Natal, South Africa: Trends, characteristics, and the urgent need for targeted interventions
Authors: Kitenge Marcel K. , Fatti Geoffrey , Eshun-Wilson Ingrid , Nyasulu Peter S.
Published: February 2025

Background

Advanced HIV disease (AHD) remains a persistent public health challenge. Data regarding the burden, characteristics and predictors of AHD is scarce specifically for rural settings of sub-Saharan Africa. This study aimed to describe trends in annual CD4 count distribution and to characterise adult persons living with HIV (PLWH) on ART who have AHD in rural KwaZulu-Natal, South Africa.

Methods

A retrospective cohort design of annual CD4 count distribution was conducted among antiretroviral therapy (ART) patients aged 18 years and older. We used routinely collected data from adults receiving ART in Eshowe and Mbongolwane areas in KwaZulu-Natal, South Africa, between January 1, 2008, and June 30, 2021. Fine-Greys competing risks regression with proportional sub-distribution hazard models was used to determine factors associated with time to CD4 recovery.

Results

A total of 34,729 patients were included of which 68.5% were females. The median age of the study sample was 33.5 years (interquartile range [IQR] 27–41 years), and the median CD4 count was 277 cells/μL (IQR, 149–452 cells/μL). The proportion of patients entering care with AHD declined over time from 62% in 2008 to 20% in 2021. Across all periods, those entering care with AHD were more likely to be men when compared to women (Relative risk [RR] 1.49; 95% 1.33–1.67). In addition, the proportion of patients with AHD who were ART-experienced increased from 4% in 2008 to 63% in 2021. Among ART-experienced, men were more likely to present with AHD compared to women (RR 1.79; 95% CI 1.52–2.11). Among those with AHD, the cumulative incidence of CD4 recovery to > 350 cells/μL was 3.21 (95% CI 3.13–3.29) per 100 adult-years follow-up time.

Conclusion

Over time fewer patients with AHD are entering care in KwaZulu-Natal, South Africa. However, the proportion of PLWH entering care with AHD remains consistently high, affecting 1 in 4 PLWH accessing HIV services. In addition, there is an increasing number of ART-experienced patients with AHD. Implementation of male-friendly services, combined with intensified adherence support and re-engagement initiatives should be considered to reduce mortality risk for PLWH in rural regions in South Africa.
Development and validation of interpretable machine learning models for triage patients admitted to the intensive care unit
Authors: Liu Zheng , Shu Wenqi , Liu Hongyan , Zhang Xuan , Chong Wei
Published: February 2025

Objectives

Developing and validating interpretable machine learning (ML) models for predicting whether triaged patients need to be admitted to the intensive care unit (ICU).

Measures

The study analyzed 189,167 emergency patients from the Medical Information Mart for Intensive Care IV database, with the outcome being ICU admission. Three models were compared: Model 1 based on Emergency Severity Index (ESI), Model 2 on vital signs, and Model 3 on vital signs, demographic characteristics, medical history, and chief complaints. Nine ML algorithms were employed. The area under the receiver operating characteristic curve (AUC), F1 Score, Positive Predictive Value, Negative Predictive Value, Brier score, calibration curves, and decision curves analysis were used to evaluate the performance of the models. SHapley Additive exPlanations was used for explaining ML models.

Results

The AUC of Model 3 was superior to that of Model 1 and Model 2. In Model 3, the top four algorithms with the highest AUC were Gradient Boosting (0.81), Logistic Regression (0.81), naive Bayes (0.80), and Random Forest (0.80). Upon further comparison of the four algorithms, Gradient Boosting was slightly superior to Random Forest and Logistic Regression, while naive Bayes performed the worst.

Conclusions

This study developed an interpretable ML triage model using vital signs, demographics, medical history, and chief complaints, proving more effective than traditional models in predicting ICU admission. Interpretable ML aids clinical decisions during triage.
Identification of biomarkers in Alzheimer’s disease and COVID-19 by bioinformatics combining single-cell data analysis and machine learning algorithms
Authors: Li Juntu , Tao Linfeng , Zhou Yanyou , Zhu Yue , Li Chao , Pan Yiyuan , Yao Ping , Qian Xuefeng , Liu Jun
Published: February 2025

Background

Since its emergence in 2019, COVID-19 has become a global epidemic. Several studies have suggested a link between Alzheimer’s disease (AD) and COVID-19. However, there is little research into the mechanisms underlying these phenomena. Therefore, we conducted this study to identify key genes in COVID-19 associated with AD, and evaluate their correlation with immune cells characteristics and metabolic pathways.

Methods

Transcriptome analyses were used to identify common biomolecular markers of AD and COVID-19. Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were performed on gene chip datasets (GSE213313, GSE5281, and GSE63060) from AD and COVID-19 patients to identify genes associated with both conditions. Gene ontology (GO) enrichment analysis identified common molecular mechanisms. The core genes were identified using machine learning. Subsequently, we evaluated the relationship between these core genes and immune cells and metabolic pathways. Finally, our findings were validated through single-cell analysis.

Results

The study identified 484 common differentially expressed genes (DEGs) by taking the intersection of genes between AD and COVID-19. The black module, containing 132 genes, showed the highest association between the two diseases according to WGCNA. GO enrichment analysis revealed that these genes mainly affect inflammation, cytokines, immune-related functions, and signaling pathways related to metal ions. Additionally, a machine learning approach identified eight core genes. We identified links between these genes and immune cells and also found a association between EIF3H and oxidative phosphorylation.

Conclusion

This study identifies shared genes, pathways, immune alterations, and metabolic changes potentially contributing to the pathogenesis of both COVID-19 and AD.
A community based, bottom-up, multi-pronged, technology integrated approach to enhance tuberculosis related awareness and treatment adherence in Uganda: The ACTS model
Authors: Turyahabwe Stavia , Ramachandra Srikrishna Sulgodu , Quraishi Subhi , Fasih Ilmana , Quraishi Hilmi , Peddapalegani Palavardhan , Ahmad Akram
Published: February 2025

Background

Tuberculosis (TB) is still a major public health challenge globally and Uganda is one among the top 30 high TB burden countries. One of the key factors determining TB treatment success rates and thereby Cure Rates is the adherence to TB treatment, which is still a major challenge globally. WHO DOTS (Directly Observed Treatment Short course) strategy has several limitations and WHO End TB Strategy 2017 suggests a suite of new interventions to improve adherence.

Objectives of the study

a. To present the development and design of ZMQ’s Active Care and Treatment Strategy (ACTS) Model.

b. To present the results of a pilot study done using the ACTS Model.

c. To compare Treatment Adherence Rates between DOTS and Video Observed Treatment (VOT) in the four districts of Uganda.

Materials and methods

Includes presenting the ACTS Model, a pilot study to assess the AGB and ACF by way of a pre-post (Quasi-experimental) study (n = 1000) to assess the impact of AGB exercises, Focus Group Discussions (FGD) to get insights into factors contributing to treatment non-adherence and a comparison between VOT (n = 800) vs. DOTS for treatment adherence.

Results

There was a significant improvement (p<0.01) in knowledge and awareness levels of community members post the AGB exercises which included creating awareness using digital storytelling, house visits and more. TB treatment adherence rates among TB patients using VOT was significantly better (p<0.01) than those using DOTS.

Conclusion

AGB and ACF play a significant role in creating more awareness amongst the community members and identifying more number of cases. It helps in better treatment seeking behaviour, improved treatment rates and treatment adherence rates and in turn better cure rates. VOT is far more superior to DOTS, as a strategy for TB treatment adherence and VOT decreases the resources required in terms of human resource, time and money and is also a more sustainable mode of treatment adherence.
Analysis of the network structure characteristics and influencing factors of regional tourism economy
Authors: Feng Xiao-Bing
Published: February 2025

The tourism economic network is a crucial factor influencing regional tourism interrelations and economic behaviors. This study selects Sichuan Province, China, as the research area and employs social network analysis to evaluate the spatial network structure of its tourism economy from 2015 to 2022. Additionally, the Quadratic Assignment Procedure (QAP) analysis method is used to explain the influencing factors of the tourism economic spatial network structure. The results show that: (1) The volume of regional tourism economic connections is on a rapid growth trajectory, with the radiation capacity and spillover effects of core node areas continuously strengthening. (2) The density of spatial networks in regional tourism economics remains low, showing a trend from loose to tight connections, essentially forming a spatial distribution pattern of “one axis with multiple branches” in tourism economic connections. (3) There are differences in the centrality of tourism economic connection networks among various cities and prefectures within the region, with differing statuses and roles in the tourism economic spatial network. (4) Geographic proximity, tourism resource endowment, economic development levels, and tourism reception capacity positively promote inter-regional tourism economic connections, while the shortest road distance negatively impacts regional tourism economic connections.