Search Results (769)

Feline infectious peritonitis (FIP) is a major disease of cats which, unless promptly diagnosed and treated, is invariably fatal. Although it has long been recognised that the condition is the result of an aberrant immune response to infection with feline coronavirus, there remain significant gaps in our understanding of its pathogenesis. Consequently, diagnosis is complex and relies on the combined interpretation of numerous clinical signs and laboratory biomarkers, many of which are non-specific. In the case of effusive FIP, a commonly encountered acute form of the disease where body cavity effusions develop; the interpretation of fluid analysis results is key to diagnosing the condition. We hypothesised that machine learning could be applied to fluid analysis test data in order to help diagnose effusive FIP. Thus, historical test records from a veterinary laboratory dataset of 718 suspected cases of effusive disease were identified, representing 336 cases of FIP and 382 cases that were determined not to be FIP. This dataset was used to train an ensemble model to predict disease status based on clinical observations and laboratory features. Our model predicts the correct disease state with an accuracy of 96.51%, an area under the receiver operator curve of 96.48%, a sensitivity of 98.85% and a specificity of 94.12%. This study demonstrates that machine learning can be successfully applied to the interpretation of fluid analysis results to accurately detect cases of effusive FIP. Thus, this method has the potential to be utilised in a veterinary diagnostic laboratory setting to standardise and improve service provision. Full article

Postsocialist peri-urban spaces are characterized by a chaotic development as a result of the transition from communism to capitalism. Recent research has highlighted that liveability in peri-urban spaces encounters challenges of adaptation to the peri-urban areas. The aim of the present study is to identify and analyze patterns and contrasts that occur between age groups and gender in relation to the level of liveability as well as to better understand the daily mobility practices and commuting dependencies and how mobility shapes key contrasts and emerging tensions within Timișoara’s postsocialist peri-urban spaces. As liveability relates to local development, commuting, and accessibility to service facilities in the residential environment, the identification of patterns and differences is imperative when considering the perception of local residents on potential (un)sustainable liveability in peri-urban areas. This study utilizes a quantitative analysis, informed by a survey of considerable size (N = 954) conducted in peri-urban settlements of Timisoara, Romania, with a view to elucidating the distinctions and commonalities in the perceptions held by the local populace. The findings indicate that the elderly population exhibits a greater reluctance to adapt to the emerging peri-urban environment. In contrast, the younger and more educated demographic demonstrates a higher degree of adaptability to the contemporary challenges posed by peri-urban expansion and hazardous development. Daily mobility, including commuting, is directly influenced by the effects of dispersed and chaotic development (e.g., more than 79% of respondents rely on private cars for commuting), as well as the lack of facilities and services (e.g., 2.21 level of satisfaction regarding cultural events). This highlights Timisoara’s dependence on external services, as well as the significant role of personal vehicles in providing access to the city center and its neighborhoods. Therefore, we can observe the peri-urban area undergoing a transitional phase as it navigates the initial stages of sustainable urban development and pursues an enhanced quality of life. Finally, we propose several policy recommendations for local authorities, offering solutions for enhancing liveability in peri-urban areas. Full article

Electric buses can help cities address environmental concerns, such as air quality and greenhouse gas emissions, and contribute to a cleaner city. The transition process from conventional fuel buses to electric buses is a growing concern for stakeholders, as industries and governments struggle to nurture the initial phase maturity of electric buses in the marketplace. This research examines the current state and development of electrification in public transport within a city, as well as the challenges and barriers encountered in adopting electric buses for electrification. Present research connects to the experience of cities that have already electrified their urban bus fleets. It relates to the role of charging technologies in cost and the implementation of battery and grid infrastructure in developing countries. It briefly presents the context of the Bus Rapid Transit System use and the electrification of public transport in Ahmedabad. Furthermore, policy recommendations for electric vehicle purchases are outlined based on service levels for sustainable transportation. Full article

Background/Objectives: Emergency Medical Services (EMSs) frequently provide the first medical contact for sepsis patients, but recognition is challenging. This study thus aimed to determine how often EMSs suspect sepsis and to evaluate the diagnostic accuracy of the quick Sequential Organ Failure Assessment (qSOFA), the Prehospital Early Sepsis Detection (PRESEP) score, and the Modified Early Warning Score (MEWS). Methods: A retrospective observational study of all EMS transports to one emergency department during a one-month period in 2023 was conducted. Prehospital vital signs, EMS working diagnoses, and final in-hospital diagnoses were abstracted. Scores were calculated post hoc. The primary outcome was the diagnostic accuracy of the EMSs’ working diagnosis of “suspected sepsis.” Secondary outcomes included the sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) of qSOFA, PRESEP, and MEWS. Results: Among 786 EMS encounters, 597 met the inclusion criteria. Twelve patients (2.0%) were ultimately diagnosed with sepsis. EMSs explicitly suspected sepsis in three of them (25.0%; sensitivity 16.7%, specificity 99.8%). Retrospective application of scores yielded markedly higher sensitivity: qSOFA 83.3%, PRESEP 91.7%, and MEWS 83.3%. Specificities were 74.2% for qSOFA, 41.2% for PRESEP, and 77.6% for MEWS. The AUCs were 0.838 for qSOFA, 0.695 for PRESEP, and 0.863 for MEWS, with MEWS significantly outperforming PRESEP (p = 0.0215). Conclusions: EMS personnel rarely labeled patients with sepsis, recognizing 3 of 12 cases (25%). Retrospective use of scoring systems based on routine vital signs substantially improved diagnostic accuracy, with MEWS performing best overall. Structured screening tools should be prospectively validated and potentially implemented in EMS. Full article

Background/Objectives: Smartphone-based leisure reservation platforms increasingly shape how individuals participate in leisure, yet little is known about how such technology-mediated engagement influences users’ awareness of multidimensional health benefits. The purpose of this study is to investigate how regular users of smartphone-based leisure reservation platforms perceive multidimensional health benefits associated with their leisure activities. Methods: Based on a constructivist/interpretivist approach, this study applied Interpretative Phenomenological Analysis (IPA). Ten participants with at least one year of platform use completed semi-structured interviews. Data were analyzed through iterative coding and theme development, with trustworthiness ensured through member checking, peer debriefing, and triangulation. Results: Participants reported three dimensions of health awareness. (1) App-enabled accessibility as a catalyst for physical health awareness (i.e., physical health benefits) included improved vitality and increased motivation to maintain exercise routines. (2) App-based planning and anticipation in supporting mental well-being (i.e., mental health benefits) involved stress reduction, emotional recovery, enjoyment, and heightened self-care awareness. (3) Platform-mediated social encounters and the construction of social health (i.e., social health benefits) reflected expanded social networks, strengthened interpersonal relationships, and a greater sense of belonging fostered through shared leisure experiences. Conclusions: Smartphone-based leisure platforms play a meaningful role in enhancing users’ awareness of multidimensional health benefits. By improving accessibility, diversifying leisure options, and facilitating social interaction, these platforms support holistic well-being. The findings contribute to understanding technology-mediated leisure and offer practical implications for designing digital leisure services that promote physical, mental, and social health. Full article

Background: Neurogenic bowel dysfunction (NBD) is a major chronic sequela of spinal cord injury (SCI) with substantial implications for rehabilitation and long-term management. However, population-level evidence describing how gastrointestinal (GI) diagnostic codes are used following SCI, particularly within administrative healthcare systems, remains limited. Methods: We conducted a nationwide retrospective cohort study using administrative claims data from the Korean National Health Insurance Service (NHIS). A total of 584,266 adults with trauma-related SCI encounters between 2009 and 2019 were identified. GI diagnostic codes—paralytic ileus (K56), irritable bowel syndrome (K58), and functional bowel disorders (K59)—were evaluated as administrative proxies for bowel dysfunction. Demographic characteristics, disability status, regional factors, and health behaviors were analyzed using multivariable logistic regression. Results: GI diagnostic codes were frequently recorded after SCI, most commonly irritable bowel syndrome (approximately 30%) and functional bowel disorders (approximately 37%), whereas paralytic ileus was uncommon. Greater disability severity, female sex, older age, and rural residence were consistently associated with higher odds of GI diagnostic coding. Physical activity showed robust inverse associations across all models. Inverse associations observed with smoking and alcohol consumption were interpreted as reflecting residual confounding or health-related selection, rather than biological protective effects. Conclusions: Patterns of GI diagnostic coding after SCI likely reflect the clinical burden and management needs of neurogenic bowel dysfunction within healthcare systems, rather than the development of new gastrointestinal diseases. These findings underscore the importance of individualized bowel management, incorporation of structured physical activity into rehabilitation programs, and equitable access to SCI rehabilitation services, particularly for individuals with greater disability or those living in rural areas. Full article

International shopping is a significant motive for outbound travel; however, evidence on the experiential drivers of luxury travel retail among Chinese luxury travelers remains limited. This study investigates the factors shaping overseas shopping experiences and assesses the adequacy of the luxury customer experience (LCX) framework in this episodic, time-constrained, cross-border context. A quantitative survey of Chinese luxury travelers (N = 407) was conducted and analyzed using IBM SPSS Statistics (Version [30.0], Mac) within the LCX framework. The results show that modern artistic visual merchandising positively predicts overall experience evaluation (β = 0.162, p < 0.001), and emotional connection significantly predicts repurchase intention (β = 0.197, p < 0.001). We find that overall experience evaluation and subsequent behavioral responses are shaped by specific drivers, including service-related post-purchase factors, emotional fulfillment and brand trust, visual appeal, and affective/cognitive evaluations. These results point to possible gaps in theory when LCX is used in short-term travel retail contexts. To address these gaps, we propose the transient experience, relationship quality, action outcomes, connection, and engagement (TRACE) conceptual framework for analyzing feedback-driven encounters throughout the travel experience. Overall, this study extends LCX to episodic, time-constrained contexts and introduces TRACE as a conceptual complementary model to guide future theory testing and model validation in luxury travel retail contexts. Full article

Language Assessment Literacy (LAL) is critical for teachers to perform their assessment tasks, but many teachers in low-resource contexts do not receive adequate assessment training. This qualitative multiple-case study examined the impact of a short-term Professional Development (PD) program on three in-service English as a Foreign Language (EFL) teachers in developing their LAL and in shaping their assessment conceptions, knowledge and practices as assessors. The PD training program consisted of a 30 h workshop delivered over one week and integrated theory, practice, collaborative learning, reflection, and feedback. Data collection instruments included classroom observations and interviews. Findings showed that the PD program improved teachers’ LAL by developing their assessment conceptions, knowledge, skills, and confidence, although the degree of improvement varied across participants. The findings also identified challenges teachers encountered in their assessment practices, including limited time, large class sizes, insufficient resources, and sociocultural factors that constrained teachers’ assessment conceptions and restricted their LAL development. The findings showed that PD programs could strengthen teachers’ professional identity as assessors by incorporating relevant content, practice opportunities, feedback, a supportive learning community, and self-reflection. The study findings have broader implications for professional development of LAL in other low-resource and exam-oriented EFL contexts with strong sociocultural constraints. Full article

The explosive growth of artificial intelligence (AI) services has led to massive scaling of GPU computing clusters, causing sharp rises in power consumption and carbon emissions. Although hardware-level accelerator enhancements and deep neural network (DNN) model compression techniques can improve power efficiency, they often encounter deployment barriers and risks of accuracy loss in practice. To address these issues without altering hardware or model architectures, we propose a novel Carbon-Aware Resource Management (CA-RM) framework for GPU clusters. In order to minimize the carbon emission, the CA-RM framework dynamically adjusts energy usage by combining real-time GPU core frequency scaling with intelligent workload placement, aligning computation with the temporal availability of renewable generation. We introduce a new metric, performance-per-carbon (PPC), and develop three optimization formulations: carbon-constrained, performance-constrained, and PPC-driven objectives that simultaneously respect DNN model training deadlines, inference latency requirements, and carbon emission budgets. Through extensive simulations using real-world renewable energy traces and profiling data collected from NVIDIA RTX4090 GPU running representative DNN workloads, we show that the CA-RM framework substantially reduces carbon emission while satisfying service-level agreement (SLA) targets across a wide range of workload characteristics. Through experimental evaluation, we verify that the proposed CA-RM framework achieves approximately 35% carbon reduction on average, compared to competing approaches, while still ensuring acceptable processing performance across diverse workload behaviors. Full article

Background/Objectives: Pediatric asthma remains a pressing public health issue, especially among low-income, minority children living in subsidized housing. Methods: This study employed a community-based participatory research approach to explore barriers and potential solutions for improving asthma management in this vulnerable population. Semi-structured interviews were conducted with 22 caregivers of children with asthma and 8 community health workers in Washington, DC—a city marked by high childhood asthma rates and concentrated subsidized housing. Results: Thematic analysis identified six core findings: (1) families frequently encountered multiple home environmental asthma triggers, including pests, mold, secondhand smoke, leaks, poor ventilation, and aging infrastructure; (2) healthy housing services were under implemented, often due to unresponsive landlords, inadequate inspections, and poor maintenance; (3) existing services such as pest control, mold remediation, and smoke-free policies were ineffectively implemented; (4) challenges to service delivery included difficulties faced by landlords and structural barriers tied to geography, race, and socioeconomic status; (5) substandard housing conditions contributed to residents’ feelings of powerlessness, frustration, and distrust, with some taking legal action to address persistent hazards; and (6) participants recommended stronger housing code enforcement, sustained funding for home-based environmental interventions, housing-health liaisons, strengthened landlord accountability, support for landlords to facilitate repairs, centering families’ voices, and advocacy. Conclusions: This study underscores the persistent challenges caregivers face in managing asthma triggers in subsidized housing. The findings highlight the critical need for improved housing conditions, greater landlord and housing authority accountability, and policy reforms to ensure consistent, equitable, and sustainable healthy housing services that reduce pediatric asthma disparities. Full article

Network function virtualization (NFV) is an emerging technology that is gaining popularity for network function migration. NFV converts a network function from a dedicated hardware device into a virtual network function (VNF), thereby improving the agility of network services and reducing management costs. A complex network service can be expressed as a service function chain (SFC) request, which consists of an ordered sequence of VNFs. Given the inherent heterogeneity and dynamic nature of network services, effective SFC deployment encounters significant unpredictable challenges. Machine learning-based methods offer the flexibility to predict and select the optimal next action based on existing data models. In this paper, we propose a deep reinforcement learning-based approach for bandwidth-aware service function chaining (DRL-BSFC). Aiming to simultaneously improve the acceptance ratio of SFC requests and maximize the total revenue for Internet service providers, DRL-BSFC integrates a graph convolutional network (GCN) for feature extraction of the underlying physical network, a sequence-to-sequence (Seq2Seq) model for capturing the order information of an SFC request, and a modified A3C (Asynchronous Advantage Actor–Critic) algorithm of deep reinforcement learning. To ensure efficient resource utilization and a higher acceptance ratio of SFC requests, the bandwidth cost for deploying an SFC is explicitly incorporated into the A3C’s reward function. The effectiveness and superiority of DRL-BSFC compared to the existing DRL-SFCP scheme are demonstrated via simulations. The performance measures include the acceptance ratio of SFC requests, the average bandwidth cost, the average remaining link bandwidth, and the average revenue-to-cost ratio under different SFC request arrival rates. Full article

In recent years, there has been a notable increase in the development of social media and humanitarian applications based on bots, designed to provide assistance during large-scale natural disasters. These applications play a crucial role in managing the chaos and useful to satisfy the urgent needs for rescue and relief that arise when catastrophes disrupt daily routines. However, they often encounter challenges during emergencies, such as dynamic and unpredictable variations in user workload, which can affect service quality and application stability. To tackle these challenges, we propose a capacity planning methodology to determine the optimal number of replicas and partitions for each component of an application and distributes them across virtual machines in server clusters. By bridging the gap between the algorithms executed in the applications and the performance characteristics of their implementations, this methodology enables applications to scale efficiently. It helps maintain response times and average utilization within user-defined ranges while providing fault tolerance to prevent component saturation. We validate the proposed methodology with tree bot-based applications devised to be use after a natural disaster strikes. Our experimental results show the effectiveness of the methodology, with estimation errors ranging from 1% to 15% for utilization and average response times. Furthermore, the methodology serves as an effective elasticity tool, allowing for the adjustment of component replicas based on user’s requests. Full article

Background: Women’s empowerment has been significantly associated with improved child health outcomes. Cambodia, amid a rapid socioeconomic transition, offers a critical setting to examine how advancements in women’s empowerment over the past decade have influenced child immunization completion within the first two years of life. Methods: Data from the Cambodia Demographic and Health Surveys conducted in 2010, 2014, and 2021–22, encompassing 9222 women with recent births, were analyzed. Empowerment was measured across literacy and information access, employment, and decision-making domains. Multinomial logistic regression assessed associations between empowerment factors and completion of oral polio (OPV), diphtheria–tetanus–pertussis (DTP), pneumococcal conjugate (PCV), and measles–rubella (MR) vaccines, adjusting for demographic and socioeconomic variables. Results: Between 2010 and 2022, women’s empowerment in Cambodia improved significantly, marked by higher literacy rates, nearly half of women completing primary education, and expanded digital access, with 82.4% owning mobile phones and approximately 50% using the internet daily. While non-working women slightly increased, agricultural employment declined by 20%, and cash earnings rose from 48.7% to 82.5%. Most women participated in major household decision-making, either independently or jointly. Completion rates for OPV, DTP, and PCV ranged from 79% to 83%, while just over half of children were fully vaccinated against measles. Higher maternal education and cash earnings were positively associated with OPV, DTP, and PCV completion but negatively associated with measles vaccination. Women in agricultural work were less likely to complete measles vaccination for their children than non-working women. Joint decision-making regarding the use of respondents’ income was associated with a higher likelihood of measles non-completion (OR = 2.26, 95% CI: 1.13–4.51), whereas joint decision-making about respondents’ health care was associated with a higher likelihood of measles completion (OR = 0.42, 95% CI: 0.21–0.83). Conclusions: Women’s empowerment remains a key determinant of vaccination outcomes in Cambodia. The distinct pattern observed for measles suggests that vaccines scheduled for older ages encounter greater structural and behavioral barriers. To overcome these challenges, strategies should focus on enhancing defaulter tracking, implementing reminder systems, expanding outreach and catch-up programs, and improving the convenience of vaccination services. Full article

Background: Survivors of sudden cardiac arrest frequently experience long-lasting problems with fatigue, cognition and mood. European Resuscitation Council (ERC) guidelines recommend functional assessment of physical/non-physical issues prior to discharge, and systematic review within three months covering at least cognition, mood, fatigue, and support for patients and their families. How these recommendations are implemented and what barriers are encountered in routine care remains unknown. Methods: We conducted a multicentric, prospective 6-month audit across four tertiary cardiac-arrest centres in England where temporarily funded follow-up pathways were in place. Five operational criteria were developed based on ERC guidelines. Adherence was quantified, and reasons for non-completion were collected and mapped onto the Theoretical Domains Framework (TDF) to identify behavioural and contextual factors influencing implementation. Results: A total of 143 OHCA survivors were discharged alive. Pre-discharge assessments were offered to 116/143 patients (81%) but only completed in 81 (57%). Reasons for non-completion included early discharge, severe cognitive impairment and, less frequently, patient refusal. Of 132 survivors eligible for follow-up, 108 (82%) were contacted and 87 (66%) attended. Only 25% of follow-ups occurred within the recommended 3-month period (median 185 days, IQR 81–225). Among those seen, assessments were completed for cognition (44%), mood (52%), and fatigue (51%). Reasons for omission included patient refusal, clinical discretion, and time constraints. Survivors’ family members were invited in all cases, but only 45% attended. Conclusions: Adherence to guideline-recommended assessments was variable and dependent on local practices, resource limitations, and patient/clinician-related factors. Key barriers mapped to the TDF domains of ‘Environmental context and resources’, ‘Beliefs about consequences’ and ‘Social influences’. Structural policies excluding out-of-area and non-ICU patients, together with clinician judgement and patient engagement, were major determinants of implementation. These findings can guide targeted service development and support sustainable post-resuscitation care pathways. Full article

Background: Fintech companies have revolutionized the financial services industry in India in recent years. This is especially true for the growth of digital payment methods. India’s unbanked are being introduced to banking by fintech companies. Despite the country’s strong banking system, many residents find it difficult to get government financial services. This is particularly true for rural or low-income people. This vacuum has been addressed by fintech solutions including digital banking, micro-lending applications, mobile wallets, and UPI platforms. Objectives: to study the impact of financial technology businesses on increasing financial inclusion for India’s underbanked and unbanked population and Challenges encountered by financial technology enterprises in their endeavors to access unbanked populations, encompassing concerns of infrastructure with special reference to western Uttar Pradesh. Method: This mixed-methods study examines how FinTech is narrowing the financial gap for unbanked people using quantitative econometric analysis and qualitative case study assessments. Results: Digital financial innovation and regulatory support encourage inclusive growth in underdeveloped economies, whereas rich nations benefit from sophisticated banking institutions. This is indicated by the small influence of GDP per capita (β = 0.22–0.32, p < 0.05). Findings: The study found that inclusive finance is revolutionized when FinTech is used with the help of robust regulatory frameworks and digital infrastructure. Policymakers should prioritize cybersecurity, public-private partnerships to improve digital literacy, and rural connection if they want more people to take part in the digital financial ecosystem. Implications: FinTech can remove obstacles to accessing financing. The proper coordinated improvements in regulatory frameworks, digital infrastructure and financial literacy among the people are necessary to achieve full financial inclusion. Full article