Search Results (427)

Existing approaches to social media sentiment analysis typically focus on static classification, offering limited foresight into how public opinion evolves. This study addresses that gap by introducing the Multi-Feature Sentiment-Driven Forecasting (MFSF) framework, a novel pipeline that enhances sentiment trend prediction by integrating rich contextual information from text. Using state-of-the-art transformer models on the Sentiment140 dataset, our framework extracts three concurrent signals from each tweet: sentiment polarity, aspect-based scores (e.g., ‘price’ and ‘service’), and topic embeddings. These features are aggregated into a daily multivariate time series. We then employ a SARIMAX model to forecast future sentiment, using the extracted aspect and topic data as predictive exogenous variables. Our results, validated on the historical Sentiment140 Twitter dataset, demonstrate the framework’s superior performance. The proposed multivariate model achieved a 26.6% improvement in forecasting accuracy (RMSE) over a traditional univariate ARIMA baseline. The analysis confirmed that conversational aspects like ‘service’ and ‘quality’ are statistically significant predictors of future sentiment. By leveraging the contextual drivers of conversation, the MFSF framework provides a more accurate and interpretable tool for businesses and policymakers to proactively monitor and anticipate shifts in public opinion. Full article

Background: Pharmacy technicians are increasingly involved in immunization services, enhancing vaccine accessibility and reducing pharmacies’ workload. This scoping review aims to (1) provide a comprehensive overview of pharmacy technicians’ involvement in immunization services across various healthcare settings and countries, and (2) conduct a comparative analysis of training curricula for pharmacy technicians on immunization. Methods: A scoping review was conducted following the Arksey and O’Malley framework. A comprehensive search of the PubMed and Scopus databases was performed using keywords and MeSH terms such as “pharmacy technician(s)”, “immunization”, “vaccination”, “role”, and “involvement”. Studies included assessed pharmacy technicians’ roles in vaccine administration, training, and public health outcomes. Descriptive and thematic analyses were used to synthesize the findings. In addition, a supplementary analysis of immunization training curricula was conducted, reviewing programs from different countries to identify similarities, differences, and gaps in course structure, content, and delivery formats. Lastly, a comprehensive toolkit was developed, offering guidelines intended to facilitate the implementation of immunization training programs. Results: A total of 35 articles met the inclusion criteria, primarily from the United States of America (n = 30), Canada (n = 2), Ethiopia (n = 1), Denmark (n = 1) and United Kingdom (n = 1). The findings indicate that pharmacy technicians contribute significantly to vaccine administration, patient education, and workflow optimization, particularly in community pharmacies. The COVID-19 pandemic accelerated their involvement in immunization programs. Key challenges include regulatory barriers, a lack of standardized training, and resistance from other healthcare professionals. Facilitators include legislative support (e.g., the PREP Act), structured training programs, and collaborative pharmacist–technician models. Conclusions: Pharmacy technicians can play a vital role in expanding immunization services, improving vaccine uptake, and reducing pharmacist workload. Addressing regulatory inconsistencies, enhancing training, and fostering interprofessional collaboration are crucial for their effective integration of immunization programs. Since immunization by pharmacy technicians is not yet allowed in many EU countries, this review will provide a foundational basis to address their potential to support the healthcare workforce and improve access to immunization services. Full article

Interrow management in vineyards significantly contributes to sustainable viticulture, particularly in water-scarce European regions. Grassy and herbaceous cover crops have been proven to enhance multiple regulating ecosystem services, including soil conservation, carbon sequestration, and improved water infiltration. However, the potential for water competition with vines necessitates region-specific approaches. This review aims to analyze the effects of different cover crop types and interrow tillage methods on water management and regulating ecosystem services, focusing on main European vineyard areas. The research involved a two-stage literature review by Google Scholar and Scopus, resulting in the identification of 67 relevant scientific publications, with 11 offering experimental data from European contexts. Selected studies were evaluated based on climate conditions, soil properties, slope characteristics, and interrow treatments. Findings highlight that the appropriate selection of cover crop species, sowing and mowing timing, and mulching practices can optimize vineyard resilience under climate stress. Practical recommendations are offered to help winegrowers adopt cost-effective and environmentally adaptive strategies, especially on sloped or shallow soils, where partial cover cropping is often the most beneficial for both yield and ecological balance. Cover crops and mulching reduce erosion, enhance vineyard soil moisture, relieve water stress consequences, and, as a result, these cover cropping techniques can improve yield and nutritional values of grapes (e.g., Brix, pH, K concentration), but effects vary; careful, site-specific, long-term management is essential for best results. Full article

Research on ecosystem carbon sequestration services and ecological compensation is crucial for advancing carbon neutrality. As a public good, ecosystem carbon sequestration services inherently lead to externalities. Therefore, it is essential to consider externalities in the flow of sequestration services. However, few studies have examined intra- and inter-regional ecosystem carbon sequestration flows, making regional ecosystem carbon sequestration flows less comprehensive. Against this background, the research objectives of this paper are as follows. The flow of carbon sequestration services between Henan Province and out-of-province regions is studied. In addition, this study clarifies the beneficiary and supply areas of carbon sink services in Henan Province and the neighboring regions at the prefecture-level city scale to obtain a more systematic, comprehensive, and actual flow of carbon sequestration services for scientific and effective eco-compensation and to promote regional synergistic emission reductions. The research methodologies used in this paper are as follows. First, this study adopts a meta-coupling framework, designating Henan Province as the focal system, the Central Urban Agglomeration as the adjacent system, and eight surrounding provinces as remote systems. Regional carbon sequestration was assessed using net primary productivity (NEP), while carbon emissions were evaluated based on per capita carbon emissions and population density. A carbon balance analysis integrated carbon sequestration and emissions. Hotspot analysis identified areas of carbon sequestration service supply and associated benefits. Ecological radiation force formulas were used to quantify service flows, and compensation values were estimated considering the government’s payment capacity and willingness. A three-dimensional evaluation system—incorporating technology, talent, and fiscal capacity—was developed to propose a diversified ecological compensation scheme by comparing supply and beneficiary areas. By modeling the ecosystem carbon sequestration service flow, the main results of this paper are as follows: (1) Within Henan Province, Luoyang and Nanyang provided 521,300 tons and 515,600 tons of carbon sinks to eight cities (e.g., Jiaozuo, Zhengzhou, and Kaifeng), warranting an ecological compensation of CNY 262.817 million and CNY 263.259 million, respectively. (2) Henan exported 3.0739 million tons of carbon sinks to external provinces, corresponding to a compensation value of CNY 1756.079 million. Conversely, regions such as Changzhi, Xiangyang, and Jinzhong contributed 657,200 tons of carbon sinks to Henan, requiring a compensation of CNY 189.921 million. (3) Henan thus achieved a net ecological compensation of CNY 1566.158 million through carbon sink flows. (4) In addition to monetary compensation, beneficiary areas may also contribute through technology transfer, financial investment, and talent support. The findings support the following conclusions: (1) it is necessary to consider the externalities of ecosystem services, and (2) the meta-coupling framework enables a comprehensive assessment of carbon sequestration service flows, providing actionable insights for improving ecosystem governance in Henan Province and comparable regions. Full article

Background/Objectives: Grief in cancer patients represents a multidimensional psychological response encompassing anticipatory, existential, and identity-related distress. While the recent literature has examined grief in caregivers, family members, and even healthcare professionals, the psychological grief experienced by patients themselves following a cancer diagnosis remains comparatively understudied and insufficiently characterized in empirical research. This systematic review aims to evaluate observational studies that used validated psychometric instruments to measure grief in adult cancer patients and to synthesize findings on the significance of grief in this population. Methods: Following PRISMA 2020 guidelines, a systematic search of PubMed, CINAHL, and PsycINFO was conducted to identify observational studies that employed validated tools to assess grief among adult cancer patients. The inclusion criteria required the use of psychometrically validated grief instruments and the collection of quantitative data. Fifteen studies met eligibility criteria and were included in the final analysis. Results: Grief symptoms were consistently present at moderate to high levels across diverse cancer types, care settings, and geographic regions. Preparatory Grief in Advanced Cancer (PGAC) scores often exceeded thresholds associated with clinical concern, with correlations observed between grief and psychological variables such as anxiety (r = 0.63), depression (r = 0.637), hopelessness (r = 0.63), and dignity (r = 0.654). Demographic factors (e.g., younger age, female gender) and illness perceptions (e.g., identity centrality, stigma) further intensified grief. Grief was a predominant psychological concern even when general distress measures failed to capture its presence. Conclusions: Future research is essential to identify an effective public health strategy for addressing grief through structured screening conducted in primary care and outpatient medical settings, coupled with accessible referral pathways to community-based support groups and coordinated follow-up services to facilitate grief management. Full article

This study investigates how demographic characteristics, severity of intimate partner violence (IPV), social support, gender equality awareness, and demographic factors (e.g., living with children at home) influence help-seeking behaviors among 2527 IPV-experienced women in Beijing, Shanghai, Guangzhou, and Shenzhen. Drawing on the help-seeking model and conservation of resource theory, the study distinguishes between formal (e.g., police, legal aid) and informal (e.g., family, friends) help-seeking. Logistic regression results reveal that greater violence severity, stronger perceived social support, and higher gender equality awareness significantly increase both formal and informal help-seeking. Notably, living with children is associated with a higher likelihood of seeking formal help, possibly due to increased concerns for children’s safety and the desire to change the abusive environment. While help-seeking behavior is on the rise overall, particularly among women with strong support networks and progressive gender attitudes, structural and cultural barriers remain. The findings underscore the need to improve public education, reduce stigma, and enhance accessibility of support systems. This study contributes to the growing literature on IPV in China and provides evidence for refining policy interventions and service delivery. Full article

The integration of artificial intelligence (AI) into educational environments is fundamentally transforming the learning process, raising new questions regarding student engagement and motivation. This empirical study investigates the relationship between AI-based learning support and the experience of flow, defined as the optimal state of deep attention and intrinsic motivation, among university students. Building on Csíkszentmihályi’s flow theory and current models of technology-enhanced learning, we applied a validated, purposefully developed AI questionnaire (AIFLQ) to 142 students from two Hungarian universities: the Ludovika University of Public Service and Eszterházy Károly Catholic University. The participants used generative AI tools (e.g., ChatGPT 4, SUNO) during their academic tasks. Based on the results of the Mann–Whitney U test, significant differences were found between students from the two universities in the immersion and balance factors, as well as in the overall flow score, while the AI-related factor showed no statistically significant differences. The sustainability of the flow experience appears to be linked more to pedagogical methodological factors than to institutional ones, highlighting the importance of instructional support in fostering optimal learning experiences. Demographic variables also influenced the flow experience. In gender comparisons, female students showed significantly higher values for the immersion factor. According to the Kruskal–Wallis test, educational attainment also affected the flow experience, with students holding higher education degrees achieving higher flow scores. Our findings suggest that through the conscious design of AI tools and learning environments, taking into account instructional support and learner characteristics, it is possible to promote the development of optimal learning states. This research provides empirical evidence at the intersection of AI and motivational psychology, contributing to both domestic and international discourse in educational psychology and digital pedagogy. Full article

With the advent of Autonomous Vehicles (AV) technology, extensive research around the design of on-demand mobility systems powered by such vehicles is performed. An important part of these studies consists in the evaluation of the economic impact of such systems for involved stakeholders. In this work, a cost–benefit analysis (CBA) is applied to the introduction of AV services in Paris-Saclay, an intercommunity, south of Paris, simulated through MATSim, an agent-based model capable of capturing complex travel behaviors and dynamic traffic interactions. AVs would be implemented as a feeder service, first- and last-mile service to public transit, allowing intermodal trips for travelers. The system is designed to target the challenges of public transport accessibility in periurban areas and high private car use, which the AV feeder service is designed to mitigate. To our knowledge, this study is one of the first CBA analyses of an intermodal AV system relying on an agent-based simulation. The introduction of AV in a periurban environment would generate more pressure on the road network (0.8% to 1.7% increase in VKT for all modes, and significant congestion around train stations) but would improve traveler utilities. The utility gains from the new AV users benefiting from a more comfortable mode offsets the longer travel times from private car users. A Stop-Based routing service generates less congestion than a Door-to-Door routing service, but the access/egress time counterbalances this gain. Finally, in a periurban environment where on-demand AV feeder service would be added to reduce the access and egress cost of public transit, the social impact would be nuanced for travelers (over 99% of gains captured by the 10% of most benefiting agents), but externality would increase. This would benefit some travelers but would also involve additional congestion. In that case, a Stop-Based routing on a constrained network (e.g., existing bus network) significantly improves economic viability and reduces infrastructure costs and would be less impacting than a Door-to-Door service. Full article

Artificial intelligence (AI)-powered mental health chatbots have evolved quickly as scalable means for psychological support, bringing novel solutions through natural language processing (NLP), mobile accessibility, and generative AI. This systematic literature review (SLR), following PRISMA 2020 guidelines, collates evidence from 25 published, peer-reviewed studies between 2020 and 2025 and reviews therapeutic techniques, cultural adaptation, technical design, system assessment, and ethics. Studies were extracted from seven academic databases, screened against specific inclusion criteria, and thematically analyzed. Cognitive behavioral therapy (CBT) was the most common therapeutic model, featured in 15 systems, frequently being used jointly with journaling, mindfulness, and behavioral activation, followed by emotion-based approaches, which were featured in seven systems. Innovative techniques like GPT-based emotional processing, multimodal interaction (e.g., AR/VR), and LSTM-SVM classification models (greater than 94% accuracy) showed increased conversation flexibility but missed long-term clinical validation. Cultural adaptability was varied, and effective localization was seen in systems like XiaoE, okBot, and Luda Lee, while Western-oriented systems had restricted contextual adaptability. Accessibility and inclusivity are still major challenges, especially within low-resource settings, since digital literacy, support for multiple languages, and infrastructure deficits are still challenges. Ethical aspects—data privacy, explainability, and crisis plans—were under-evidenced for most deployments. This review is different from previous ones since it focuses on cultural adaptability, ethics, and hybrid public health incorporation and proposes a comprehensive approach for deploying AI mental health chatbots safely, effectively, and inclusively. Central to this review, symmetry is emphasized as a fundamental idea incorporated into frameworks for cultural adaptation, decision-making processes, and therapeutic structures. In particular, symmetry ensures equal cultural responsiveness, balanced user–chatbot interactions, and ethically aligned AI systems, all of which enhance the efficacy and dependability of mental health services. Recognizing these benefits, the review further underscores the necessity for more rigorous academic research into the development, deployment, and evaluation of mental health chatbots and apps, particularly to address cultural sensitivity, ethical accountability, and long-term clinical outcomes. Full article

The consequences of climate change directly affect food production and threaten food security. Therefore, efforts are needed to reduce environmental impacts while ensuring access to food. Massive food services play a key role in this context; however, related literature lacks comparative studies between home cooking and restaurants. Through life-cycle assessment, this research compares the environmental impacts generated by stewed chickpeas, a nutritious and flavorful meal prepared at a large food service offered by a public university, and those prepared at home using two recipes. The system boundaries consider the impact of ingredient production, processing, cooking, cooling, and reheating, as well as waste and wastewater generation. The functional unit (FU) weighs 100 g to facilitate comparison. The findings indicate that the recipe from the massive food service has a significant impact on human health, resulting in 3.54·10⁻⁷ DALY; meanwhile, the other two scenarios generate approximately 7.2·10⁻⁷ DALY. Moreover, regarding biodiversity impact, the recipe from the massive food service reaches 8.57·10⁻¹⁰ species.yr; by contrast, the other scenarios generate around 1.01·10⁻¹⁰ species.yr. Massive food services exhibit a lower environmental impact than home meals in preparing stewed chickpeas. This difference is primarily attributed to the cooling and reheating stages that occur when eating outside the home. Full article

The article explores the capacity of zero-emission urban public transport (PT) and proposes a standardised method for calculating it across different PT corridors (bus, tram, metro and urban railway). As the European Union (EU) tightens regulations on emissions, targeting also PT, cities are increasingly shifting to electric and hydrogen-powered vehicles. A significant challenge was the lack of a unified methodology to calculate the capacity of zero-emission vehicles, e.g., battery-powered buses carry fewer passengers than diesel ones due to weight restrictions. The article addresses this gap by creating capacity matrices for various vehicle types based on standardised assumptions. Vehicle capacity is calculated based on seating and standing space, with standing passenger space standardised to 0.2 m²/person (E Level of Service). A detailed rolling stock analysis shows how modern designs and floor layouts impact passenger space. Matrices were developed for each mode of transport, showing the number of transported passengers per hour depending on vehicle type and service frequency. The highest capacity is achieved by metro and urban railway systems (up to 95,000+ passengers/hour/direction), while buses offer the lowest (up to 7800 passengers/hour/direction). The authors recommend standardising calculation methods and integrating matrices into planning tools for urban PT corridors. Full article

Urban public toilets are essential for improving urban and rural living environments. Traditional evaluations have relied on statistical indicators such as total numbers and network coverage, but have overlooked population demand, limiting their ability to reflect actual service levels and optimize spatial allocation. This study assesses the public toilet service capacity according to spatial accessibility and offers insights into layout optimization. The main urban area of Kunming was considered as the case study. First, the Gaussian two-step floating catchment area (G2SFCA) method was used to calculate public toilet accessibility. The service level of public toilets at the community scale was assessed based on the calculation results. Finally, recommendations for the optimization of the spatial layout of public toilet provision are proposed based on the evaluation findings. Results indicate that (1) 57 communities lacked access to public toilets within a 5 min walk, while only two lacked access within 20 min; all communities had access within 30 min; (2) increasing stalls in old public toilets by 50% would meet the policy requirements for most residents; (3) transportation accessibility has a significant impact on residents’ convenience in accessing public toilets. Areas with lower transportation connectivity tend to have poorer toilet accessibility. The construction of new public toilets near road networks can effectively enhance overall restroom convenience for residents in the study area. By integrating public toilet accessibility with resident restroom demand, this study proposes targeted strategies for optimizing the spatial layout of urban public toilets, offering valuable insights and feasible solutions for improving the scientific and rational allocation of urban public resources. Full article

The accessibility of nature trails for people with motor disabilities and impairments stands as a significant challenge for inclusive tourism. In the present study, we would like to present a review of research, approaches, and solutions to enable people with motor impairments to enjoy nature trails independently or with assistance. The study is conducted from the perspective of public bodies that aim to reduce the accessibility barriers for People with Disabilities (PwDs) by adapting and improving the conditions of the trails and by providing clear and comprehensive information about the difficulties that hikers may encounter on a trail while using a specific aid. The paper initially presents the wide variety of aids for outdoor mobility, including both those to be used independently (i.e., self-propelled wheelchairs that can be equipped with additional small wheels, off-road wheels and/or auxiliary drives) and those that require assistance (e.g., single-wheeled wheelchairs). Then, we shift focus onto the difficulty classification of trails for PwDs, analysing papers and guidelines that tried to define objective evaluation criteria such as the slope, the trail surface, and the length of the sloping sections. Starting from these studies, the paper proposes a synthesis of the different classifications that consider, for the first time, all the aids available on the market, thus filling the gaps of the single studies. In the last sections, we present some national and international guidelines with tailored and practical solutions to improve the accessibility of nature trails and some studies about the inclusive planning that directly involves PwDs, as well as on the need for a better training of tourism service providers. The present work aims to stimulate a debate on the barriers and opportunities related to the accessibility of hiking trails, contributing to making nature a truly accessible experience for all. Full article

In network function virtualization (NFV) environments, dynamic network traffic prediction with unique symmetric and asymmetric traffic patterns is critical for efficient resource orchestration and service chain optimization. Traditional centralized prediction models face risks of cross-provider data privacy leakage when network service providers collaborate with resource providers to deliver services. To address this issue, we propose a decentralized federated learning method for network traffic prediction, which ensures that historical network traffic data remain stored locally without requiring cross-provider sharing. To further mitigate interference from malicious provider behaviors on network traffic prediction, we design a node incentive mechanism that dynamically adjusts node roles (e.g., “Aggregator”, “Worker Node”, “Residual Node”, and “Evaluator”). When a node exhibits malicious behavior, its contribution score is reduced; otherwise, it is rewarded. Simulation experiments conducted on an NFV platform using public network traffic datasets demonstrate that the proposed method maintains prediction accuracy even in scenarios with a high proportion of malicious nodes, alleviates their adverse effects, and ensures prediction stability. Full article

With the ongoing globalization, traditional villages around the world face the challenge of balancing modernization with the preservation of their cultural and spatial integrity. Heijing Village, a representative traditional settlement in Yunnan, showcases this global phenomenon through its distinctive spatial form and rich multi-ethnic cultural heritage. This study examines the landscape morphology of Heijing Village to reveal its spatial organization, cultural significance, and adaptive evolution. By applying fractal theory, we quantify the spatial complexity and self-similarity of the village, uncovering underlying patterns in land use that contribute to its sustainability and historical continuity. This study’s innovation lies in its use of fractal analysis to assess the village’s dynamic landscape, offering a novel method for understanding the interplay between traditional spaces and modern demands. The findings demonstrate variations in fractal dimension values before and after model optimization, indicating an enhanced ability to capture the intricate spatial structure of Heijing Village. Notably, changes in fractal dimensions across different land use types (e.g., residential areas: 1.4751 to 1.5323 and public service areas: 1.2846 to 1.3453) suggest improvements in quantification accuracy rather than actual physical transformations. This refined methodological framework provides a robust and replicable tool for planners to quantitatively assess the morphological characteristics of traditional settlements, supporting more evidence-based conservation strategies. Full article