Search Results (17,107)

Cities around the world are facing growing challenges related to climate change, urban sprawl, infrastructure strain, and digital transformation. In response, smart and sustainable urban development has become a global focus, aiming to integrate technology and environmental stewardship to improve the quality of life. The smart and sustainable city concept is typically applied at the city scale; however, its impact is most tangible at the neighborhood level, where residents interact directly with infrastructure, services, and community spaces. A variety of global frameworks have been developed to assess sustainability and technological integration. However, these models often fall short in addressing localized needs, particularly in regions with distinct environmental and cultural contexts. In Saudi Arabia, Vision 2030 emphasizes livability, sustainability, and digital transformation, yet there remains a lack of tailored tools to evaluate smart and sustainable progress at the neighborhood scale. This study develops HayyScore, a localized evaluation framework and prototype digital platform developed to assess neighborhood performance across five core categories: (i) Environment and Urban Resilience, (ii) Smart Infrastructure and Governance, (iii) Mobility and Accessibility, (iv) Quality of Life and Social Inclusion, and (v) Economy and Innovation. The HayyScore platform operationalizes this framework through an interactive web-based tool that allows users to input data through structured forms, calculate scores, receive category-based and overall certification levels, and view results through visual dashboards. The methodology involved a comprehensive review of global frameworks, expert input to define localized indicators, and iterative prototyping of the platform using Python 3.13.5 and Streamlit 1.45.1. To demonstrate its practical application, the prototype was tested on two Saudi neighborhoods: King Abdullah Petroleum Studies and Research Center (KAPSARC) and King Fahd University of Petroleum and Minerals (KFUPM). Key platform features include automated scoring logic, category weighting, certification generation, dynamic performance charts, and a rankings page for comparing multiple neighborhoods. The platform is designed to be scalable, with the ability to add new indicators, support multilingual access, and integrate with real-time data systems in future iterations. Full article

This article examines the paradigm shift in Christian mission from conversion-centered models toward dialogical and justice-oriented praxis. Taking the Steyler Missionaries as a case study, this approach engages post-Vatican II theology, postcolonial critique, and Comparative Theology to demonstrate how mission can embody epistemic humility, contextual sensitivity, and theological hospitality. Based on qualitative interviews and textual analysis, the study highlights how dialogical mission reshapes Christian identity through mutual transformation rather than doctrinal transmission. The findings indicate that Comparative Theology provides a significant methodological and theological resource for interreligious engagement, enabling missionaries to move beyond hegemonic proclamation toward relational and ethically grounded witness. By integrating theological reflection with empirical insight, the article demonstrates how dialogical mission contributes to a reconfiguration of Christian witness in pluralistic and postcolonial contexts and offers a constructive framework for the future of mission practice. Full article

Museum collections around the world contain millions of objects related to religion that can be considered classic sources for religious studies. To date, however, there is no method in religious studies for systematically critiquing such objects from museum collections as sources. Religious studies must therefore expand their methods in order to be able to systematically use such objects as sources for their own research. Various examples show that museum objects can only be made accessible for religious studies research with the help of provenance research. The main focus of the selected examples is on dolls with a religious background—or, rather, on museum objects that have been classified as dolls in collections. Using such objects as examples, this article provides insight into the problems of provenance and the resulting consequences. The aim is to use the examples to show how objects find their way into museum collections, what intentions may lie behind the acquisition of such objects, and how and in what context such objects may be presented to the public. The background to such a scientific approach lies in the analysis of the changing perspective on such objects, since the meaning and attribution of an object are never static. Rather, these objects are subject to a permanent change in perspective due to changing social processes. Or they are presented as something they never really were. And all this can be revealed by systematic provenance research. The article is therefore intended as a plea for the expansion of religious studies methods to include provenance research. Full article

In the context of Industry 4.0 and smart manufacturing, predicting cutting tool remaining useful life (RUL) is crucial for enabling and enhancing the reliability and efficiency of CNC machining. This paper presents an innovative predictive model based on the data fusion architecture of Graph Neural Networks (GNNs) and Transformers to address the complexity of shallow multimodal data fusion, insufficient relational modeling, and single-task limitations simultaneously. The model harnesses time-series data, geometric information, operational parameters, and phase contexts through dedicated encoders, employs graph attention networks (GATs) to infer complex structural dependencies, and utilizes a cross-modal Transformer decoder to generate fused features. A dual-head output enables collaborative RUL regression and health state classification of cutting tools. Experiments are conducted on a multimodal dataset of 824 entries derived from multi-sensor data, constructing a systematic framework centered on tool flank wear width (VB), which includes correlation analysis, trend modeling, and risk assessment. Results demonstrate that the proposed model outperforms baseline models, with MSE reduced by 26–41%, MAE by 33–43%, R² improved by 6–12%, accuracy by 6–12%, and F1-Score by 7–14%. Full article

Leadership is context-dependent in its influence on various employee attitudes and behaviors, particularly in high-risk environments. Despite this, few studies have explored the role of leadership in shaping safety-related outcomes within high-risk public sector settings. This study posits that leadership’s impact may differ in high-risk contexts such as firefighting, where safety is of utmost importance. Using survey data collected from firefighters in Gyeonggi-do, the largest province in South Korea, this study examines the relationship between transformational leadership, perceived accident likelihood, and three safety-related attitudes: safety motivation, safety compliance, and safety participation. With sample sizes for the three dependent variables ranging from 1502 to 1504, the ordinary least squares (OLS) regression results indicate that transformational leadership is positively associated with all three safety attitudes. However, perceived accident likelihood shows a positive relationship with only one of the safety-related attitudes: safety motivation. More importantly, perceived accident likelihood moderates the relationship between transformational leadership and safety attitudes; as perceived accident likelihood increases, the positive impact of transformational leadership on these attitudes diminishes. These findings underscore the contextual nature of leadership effectiveness in high-risk settings and highlight the importance of contextual factors in understanding leadership styles. Full article

Background: The aging evolution of Taurasi, an Aglianico-based DOCG wine from southern Italy, has been comprehensively characterized here for the first time. Known for its high levels of bioactive metabolites with potential health benefits, this variety was analyzed using an integrated analytical and computational approach to explore the evolution of its composition during bottle aging. Methods: The analytical framework encompassed physicochemical profiling (density, pH, °Brix) and targeted spectrophotometric analyses for polyphenols (Folin–Ciocâlteu), antioxidant capacity (DPPH, ABTS), and anthocyanins (TAC). The phenolic and volatile fractions were analyzed in detail qualitatively and quantitatively using HPLC-UV-DAD and HS-SPME-GC/MS, respectively. Results: The aging process was characterized by a profound phenolic reorganization, with a significant decrease in monomeric phenols and an accumulation of key phenolic acids and stilbenes. The net result of these opposing trends was an overall increase in antioxidant capacity, a significant decrease in total anthocyanins, and an aromatic shift from primary fruity esters to a complex tertiary bouquet. Additionally, machine learning techniques were employed to predict aging-related variations in antioxidant activity and chemical parameters, establishing links between compositional shifts and potential bioactivity. Conclusions: This study marks the first-ever investigation of Taurasi Aglianico wine aging, offering a novel multidisciplinary approach that provides comprehensive insights into the wine’s chemical evolution. The findings emphasize the potential of Taurasi Aglianico in both enological and health-related contexts, highlighting its unique aging dynamics and bioactive potential. Full article

Background: Healthcare systems worldwide face growing challenges in anticipating and managing patient surges, particularly in times of public health crises, natural disasters, or seasonal peaks. The ability of healthcare organisations to forecast and respond to such demand fluctuations—referred to as organisational readiness for patient capacity surge—has become a critical determinant of service continuity and patient outcomes. Despite the urgency, there remains a lack of consolidated evidence on how healthcare authorities measure, evaluate, and operationalise this readiness. This systematic review aims to identify and synthesise existing literature that presents case studies, methodologies, and strategic frameworks used to evaluate organisational preparedness for patient surge capacity. It also explores resource allocation mechanisms, hospital capacity planning algorithms, and temporary facility strategies documented in healthcare settings. Methods: The review was conducted across two major scientific repositories, i.e., PubMed and Web of Science (WoS). A set of four structured search queries were formulated to capture the breadth of the topic, focusing on demand forecasting, hospital capacity planning, workforce models, and resource management within the context of healthcare surge demand. The search was limited to publications from the last 10 years (2014–2024) to ensure the inclusion of contemporary practices and technologies. Resutls: A total of 142 articles were selected for detailed analysis. The articles were categorised into six thematic groups: (i) empirical case studies on healthcare surge management; (ii) hospital resources and capacity scaling; (iii) ethical frameworks guiding surge response; (iv) IT-driven algorithms and forecasting tools; (v) policy evaluations and actionable lessons learned; and (vi) existing systematic reviews in related domains. Notably, several articles provided evidence-based frameworks and simulation models supporting predictive planning, while others highlighted real-world implementation of temporary care facilities and staff redeployment protocols. Conclusions: The review underscores the fragmented yet growing body of literature addressing the multidimensional nature of surge preparedness in healthcare. While algorithmic forecasting and capacity modelling are advancing, gaps remain in standardising metrics for organisational readiness and incorporating ethical considerations in surge planning. Limitations of this review include potential selection bias and the subjective categorisation of articles. Future research should aim to develop integrative frameworks that couple technical, operational, and ethical readiness for patient surge scenarios. Full article

Background and Objectives: Dry eye disease (DED) is a multifactorial ocular surface disease that markedly diminishes quality of life. Although diabetes mellitus is well-known for its retinal consequences, anterior segment symptoms including dry eye disease are often overlooked. Chronic hyperglycemia causes metabolic, neurovascular, and immunological changes that undermine tear film stability, corneal innervation, and ocular surface integrity. This review seeks to consolidate existing knowledge regarding the concealed impacts of diabetes on ocular surface homeostasis, highlighting processes, diagnostic difficulties, and treatment prospects. Materials and Methods: A narrative review of the literature was performed by searching PubMed for publications from January 2020 to July 2025 using the terms “diabetic dry eye,” “hyperglycemia AND ocular surface,” “tear proteomics AND diabetes,” “corneal nerves AND diabetes,” and “neurotrophic keratitis.” Eligible studies were experimental research, clinical trials, and translational investigations concerning tear film function, corneal neuropathy, inflammatory indicators, or lacrimal gland dysfunction in diabetes. The exclusion criteria were non-English language, lack of primary data, and inadequate methodological description. Results: Hyperglycemia compromises lacrimal gland functionality, modifies lipid secretion from Meibomian glands, and diminishes corneal nerve density, resulting in neurotrophic deficits. Inflammatory cytokines and oxidative stress compromise epithelial integrity, but proteome alterations in tears serve as sensitive indicators of disease. Diagnosis is impeded by corneal hypoesthesia, resulting in a disconnection between symptoms and findings. Progress in imaging, proteomics, and artificial intelligence may facilitate earlier detection and improved risk assessment. Novel therapeutics, such as neurotrophic drugs, antioxidants, and customized anti-inflammatory approaches, show promise but remain under clinical evaluation. Conclusions: Diabetes-related dry eye disease is a multifaceted and underappreciated condition influenced by systemic metabolic dysfunction. The ocular surface may act as an initial indicator for systemic disease load. Narrative synthesis emphasizes the necessity for customized diagnostic instruments, individualized treatment approaches, and collaborative management. Reconceptualizing diabetic dry eye disease within the context of systemic metabolic care presents prospects for precision medicine strategies that enhance both ocular and systemic results. Full article

Background: Beverage intake is a consequential yet underappreciated driver of health in Mediterranean settings. Comparative evidence for Spain and Italy based on harmonised measures is scarce. This study addresses that gap by profiling beverage portfolios and their sociodemographic correlates in parallel adult samples from both countries. Methods: We conducted a cross-sectional analysis of adults in Spain (n = 483) and Italy (n = 403) using aligned, validated instruments (NutSo-HH; NutSo-HH-Ita). Outcomes were water (Wtr), sugar-sweetened soft drinks (Sfd), juice (Juc), energy drinks (End), coffee (Cff), alcohol (Alc), and episodes of intoxication (Gtd). Associations were assessed via non-parametric tests, multivariable linear models, and an EBIC-selected Gaussian graphical model (GGM). Main results: Italians reported higher Alc and Gtd; Spaniards reported higher Sfd and Juc. Wtr was comparable across countries, and Cff differences were marginal. Age and sex emerged as the most consistent correlates (older age and male sex with higher Alc; younger age with higher Sfd), whereas education and income were not stable determinants. The GGM suggested behavioural clustering of Sfd–Juc–End, with weak partial correlations for other beverages after adjustment. Implications: Distinct country profiles imply differentiated priorities. In Spain, interventions could prioritise reducing sugar-sweetened beverage intake among younger adults through age-targeted primary care counselling, mandatory water (and unsweetened milk) availability in schools, tiered excise taxes on sugar-sweetened drinks, and restrictions on child- and youth-directed marketing of high-sugar beverages. In Italy, primary care and community health services could routinely screen adults for risky alcohol use and deliver brief, culturally attuned advice that promotes lower-risk patterns of wine consumption during meals. Given the cross-sectional design, self-report measures, and non-probabilistic sampling, findings should be interpreted as context-sensitive markers rather than causal determinants; nevertheless, they highlight concrete prevention approaches and regulatory levers for each country’s beverage-related health risks. Full article

Animal hoarding is a complex and multifactorial phenomenon that poses serious risks to animal welfare, public health, and environmental balance. Despite increasing attention, current interventions often remain fragmented and lack integration across medical, psychological, and social domains. Based on a critical review of existing tools and field experience in the Italian context, this study proposes a structured operational protocol to support multidisciplinary teams in the assessment and management of animal hoarding cases. The protocol integrates three complementary tools: a preliminary observational form, a clinical-relational interview, and a veterinary health form. Designed to be modular, replicable, and shareable among professionals from diverse backgrounds, the protocol aims to promote a One Welfare approach, recognizing the systemic interconnection between animal suffering, human psychological distress, and environmental degradation. While further experimental validation is required, this conceptual model provides a concrete operational basis for structured interventions and consistent data collection in support of research and public health. Full article

Rapid advancements in technology have resulted in the proliferation of self-driving vehicles, which have already presented significant challenges to the field of legal science. In the context of automated decision-making, the question of liability is invariably pertinent. The question of whether liability should be assigned to a non-human entity or to a group of people is a contentious one. Furthermore, the question of which entity should be held liable for compensation for damage caused and which entity should be criminally liable remains unresolved. In the context of self-driving vehicles operating at a lower level of automation, the identification of the driver’s liability, ostensibly a straightforward undertaking, gives rise to a multitude of intricate ethical dilemmas. In addition to the prevailing assumptions regarding liability, which have previously been discussed in detail in the literature, the study also addresses the issue of transparency in automated decision-making related to legal remedies. Full article

Higher education (HE) has become a central site where the relations between democracy, pedagogy and technology are being reshaped through algorithmic infrastructures. In this context, a specific tension becomes visible: as educational processes become intertwined with systems of classification, prediction and optimization, recognition risks becoming conditional on data legibility, while pedagogical judgement is redirected toward procedural efficiency. Against this background, this article investigates how subjectivity, recognition and pedagogical responsibility can be conceptually framed when formative encounters are mediated through pedagogical practice as well as through algorithmic operations. To address this question, it develops the DEA model (Democratic Education under Algorithmic Conditions) as a reflexive, education–theoretical heuristic grounded in educational theory, subjectivation research, democratic thought and critical data studies. The model positions education, democracy and digitalisation as interdependent fields and specifies three analytical dimensions: formative, normative and inferential. These are elaborated through relational vectors and framing structures that include societal discourses, institutional configurations, cultural imaginaries and biographical conditions. The reconstruction shows how pedagogical responsibility becomes vulnerable to displacement by optimization routines, how recognition is reorganised by regimes of data legibility and how didactic relations are reconfigured through automated feedback and recommendation systems. Rather than prescribing technical solutions, the DEA model offers a conceptual orientation for diagnosing how algorithmic mediation redistributes recognition, responsibility and legitimacy in HE, and for sustaining Bildung and democratic subject formation under digital conditions. Full article

The global malnutrition crisis—marked by the simultaneous presence of hunger, undernutrition, and obesity—affects billions of people worldwide. This complex and widespread issue is deeply intertwined with today’s escalating environmental challenges, including climate change, soil degradation, and biodiversity loss. These problems are largely driven by the current food systems, which not only fail to provide adequate nutrition for all but also contribute significantly to environmental degradation. Argentina, as a major global food producer, exemplifies this paradox: despite its vast agricultural capacity, nearly 70% of its population suffers from some form of malnutrition. This paper examines the potential of organic agriculture and agroecology to transform food systems in ways that promote sustainability and health, aligning with the United Nations Sustainable Development Goals (SDGs). Focusing on Buenos Aires, the study investigates the availability, cost, and affordability of organic and agroecological diets in accordance with both international and national dietary guidelines. This is the first study in Argentina—and among the first internationally—to analyze the affordability of diets exclusively based on organic and agroecological products. Linear programming is applied to assess these diets in relation to the basic food basket, revealing economic challenges and opportunities within the city’s food landscape. The results demonstrate the validity of the model in identifying the costs and potential economic accessibility of such diets for the population, providing valuable insights for segmenting and clarifying potential pathways for scaling these diets, as well as comparing different contexts and realities. Full article

This study investigates innovation performance through the lens of the Internet of Things (IoT) and in the context of supply chain globalization. For theoretical support this study employs dynamic capabilities theory; however, data analysis was performed using SPSS. Results demonstrate that IoT capabilities (i.e., smart environmental creation, data processing) have both direct and indirect relations with innovation performance. Perceived business force (competition and policies) and environmental uncertainty are both moderating variables in the proposed research framework, whereas supply chain integration and supply chain agility are demonstrated to be positive mediators between IoT and innovation performance. These results extend the application of dynamic capability theory in the context of the digital supply chain and offer actionable insights for managers seeking to leverage IoT capabilities to drive innovation under uncertain business environments. Full article

The objective of this paper is to analyze the constitutional principles that govern the Spanish model of relations between the State and religious organizations, within the context of the model of cooperation between the State and religious organizations. The 1978 Constitution guarantees the right to religious freedom, establishes the principle of religious neutrality of public authorities, and indicates that public authorities shall cooperate with religious organizations and the Catholic Church. In line with this approach, this paper studies the advantages and disadvantages of the Spanish model of cooperation between the State and religious organizations, taking into account the fact that the State has currently signed cooperation agreements with both the Catholic Church and so-called religious minorities. This has generated a cooperation model that favors organizations with cooperation agreements over those without and discriminates between religious organizations with cooperation agreements based on the content of the respective agreements. All of this contradicts the constitutional principle of equality and non-discrimination on religious grounds, as well as the principle of religious neutrality of public authorities. Full article