Search Results (12,597)

Health and spa tourism is a rapidly growing sector that merges traditional healing with modern innovations to meet increasingly diverse client needs. Understanding professionals’ perspectives is crucial for developing sustainable strategies that enhance service quality, organizational performance, and long-term business viability. Drawing on qualitative narrative analysis and thematic network analysis, this study explores the key factors that spa tourism professionals in Băile Felix—the largest spa resort in Romania—associate with business success, competitive differentiation, and sustainable development. Data were collected through semi-structured interviews with 41 entrepreneurs and managers who provided detailed narratives on their strategic goals and market positioning. Rather than measuring customer psychological constructs directly, this study captures professionals’ expert attributions regarding service quality, staff professionalism, infrastructure investment, and economic objectives, and interprets these as managerial perceptions grounded in operational experience. Five research propositions guided the interpretive analysis: (P1) professionals narratively associate service quality and treatment diversity with perceived business performance and guest retention signals; (P2) staff professionalism and attitude are attributed as the primary drivers of competitive differentiation; (P3) infrastructure investment and innovation are framed as prerequisites for sustaining market positioning; (P4) the identified themes form a structurally interconnected network with key bridging nodes; and (P5) professional narratives reveal tensions between short-term economic objectives and longer-term commitments to service quality and sustainability. Thematic network analysis identified four central constructs—service quality and treatment diversity, staff professionalism and attitude, innovation and infrastructure investment, and economic and development objectives—and mapped 16 interconnected sub-themes, with modularity analysis (Q = 0.42) confirming a moderately cohesive structure. Sustainable innovation was operationalized across environmental efficiency, social value, and economic resilience dimensions, and found to be embedded systemically across multiple thematic clusters rather than treated as an isolated practice. The originality of this study lies in integrating narrative and thematic network analysis to reveal how these constructs co-evolve within a sustainability-oriented system, offering a novel methodological lens for spa tourism research in post-transitional Central and Eastern European contexts. Findings provide actionable insights for spa managers, policymakers, and investors seeking to balance modernization with tradition in resource-constrained destinations. Full article

Background/Objectives: Hypertensive disorders of pregnancy (HDPs) affect approximately one in seven hospital deliveries in the United States and increase the risk of pregnancy-associated mortality. Home blood pressure monitoring (HBPM) for patients with HDPs has emerged as a model of care poised to improve ascertainment of blood pressure and triage of care during pregnancy and postpartum periods. However, the strength of evidence supporting HBPM approaches has been variable. This rapid review aimed to understand how HBPM approaches for pregnant and postpartum populations with HDPs have been evaluated in order to strengthen future research. Methods: Search criteria included peer-reviewed literature in English and French published during 2018–2024 that assessed HBPM approaches for pregnant and postpartum populations in high-income countries. A total of 370 records were screened and reviewed to identify 52 eligible articles. Key study characteristics, methodologies, and outcome measures were extracted. Identified outcome measures were mapped by outcome type (implementation, health service, and client) to assess gaps in evaluation of HBPM approaches. Results: A range of study designs were employed to evaluate HBPM approaches: experimental (17%), observational (52%), qualitative (10%), mixed method (10%), and economic (11%) designs. Over a third employed a comparison group, most of which compared HBPM approaches to usual antepartum or postpartum care. Only 11 studies reported on impact outcomes (long-term blood pressure control, adverse maternal and perinatal outcomes). Significant gaps were identified among the implementation outcomes examined. While patient engagement measures were common, assessment of provider adherence and engagement was limited. Hospital admissions and emergency department visits were often employed as proxies to measure HBPM effectiveness, efficiency, and safety. However, no studies adequately reported effectiveness measures for remote patient triage. Conclusions: Our results call for improved HBPM metrics to ensure patients are receiving high-quality care responsive to their clinical condition. Future studies on HBPM approaches should prioritize more transparent reporting on health actor engagement. A composite measure including both patient and provider adherence to monitoring and triage processes will provide stronger evidence on the effectiveness of HBPM for pregnant and postpartum patients and share impactful learning for health systems interested in adopting HBPM approaches. Full article

Task scheduling in cloud computing environments is a complex NP-hard problem that requires maximizing resource utilization while satisfying quality-of-service (QoS) constraints. Traditional meta-heuristic algorithms often become stuck in local optima, while single deep reinforcement learning (DRL) models exhibit instability when exploring large-scale solution spaces. To address this, this paper proposes a hybrid scheduling algorithm based on multi-objective sand cat colony optimization (MoSCO). This algorithm utilizes a D3QN network to extract task features and guide population initialization, followed by a multi-objective Sand Cat Swarm Optimization (SCSO) algorithm for refined local search. Results from 50 independent replicate experiments conducted in a simulated cloud environment, coupled with an analysis of the dynamic convergence process, demonstrate that MoSCO exhibits significant superiority and robustness. Scatter plot convergence analysis further confirms that MoSCO’s knowledge injection mechanism effectively overcomes the blind exploration phase of traditional algorithms and successfully breaks through the local optimum bottleneck in the late iteration stages of single reinforcement learning, achieving higher-quality, denser, and more stable convergence. Furthermore, 3D and 2D Pareto front analyses show that MoSCO generates highly competitive, well-distributed non-dominated solutions, offering flexible trade-off options for conflicting objectives. Compared to PureD3QN, H-SCSO, and NSGA-II, MoSCO exhibits the smallest performance fluctuations in box plots. Specifically, MoSCO elevates the average resource utilization of clusters to 92.20%, while reducing the average maximum Makespan and Tardiness to 528 and 4187, respectively. Experimental data confirm that MoSCO effectively balances global exploration with local exploitation, delivering stable, high-quality solutions for dynamic cloud task scheduling. Full article

Agriculture in the Pacific is driven primarily by small-scale private farmers, many of whom do not have access to soil testing services or advice, nor the means to interpret analytical results into soil management and agronomic recommendations. Soil degradation through the process of acidification poses a significant risk to food and income security as it directly threatens crop productivity. The nutritional quality of food crops may also be affected through sub-optimal nutrient uptake by plants and nutrient imbalances. The dataset reported here provides a useful platform for the development of a decision-support tool (DST) that will assist Fiji farmers in understanding and managing soil pH and soil acidity. The DST will enable making informed decisions about liming to help correct soil pH. To support this development, historical soil pH data available from the Pacific Soils Portal were combined with updated analyses of agricultural soils from 17 locations in Viti Levu Island (Fiji) collected during a field campaign undertaken in August 2025. The soils were sampled at two depth intervals (0–15 and 15–30 cm) and analyzed for pH using a variety of methods. These methods included direct field measurements using a portable pH-meter as well as traditional laboratory determinations. Of the soils sampled, it was found that most soils exhibited pH levels below 7, which were observed for both depth intervals. Across all samples taken in 2025, it was found that 54.3% of them had soil pH < 5, 38.6% had soil pH between 5 and 6, and 7.1% had pH > 6 (based on soil pH_1:5 soil-to-water method). Depending upon specific land uses, climate and cropping intensity, it was recommended that routine liming be built into soil fertility management programs to help farmers overcome soil acidity-related constraints to production. Liming frequency, timing of application and application rate will need to be determined for specific soil and cropping situations; however, it was suggested that soil pH was not changed by more than 1 unit each time lime was applied. Such an approach should reduce the risk of soil organic matter loss through accelerated mineralization, which would be challenging to restore in that environment if soils remained under continuous cropping. The analytical information contained in this article expanded and updated the datasets available in the Pacific Soils Portal. Furthermore, this work provided an opportunity to build analytical expertise in aspects of soil chemistry at local organizations to support academic and extension activities as well as the ongoing development of the Pacific Soils Portal. Full article

AI data-center (DC) growth is increasingly constrained by limited deliverable electricity, interconnection capacity, and cooling demand. This study develops a boundary-consistent screening framework for waste-to-energy (WtE)-coupled AI DC cooling, treating cooling as an energy service that can be supplied through grade matching rather than solely through electricity-driven mechanical chilling. The framework translates plant-side exportable heat into corridor-level planning objects by explicitly accounting for thermal attenuation, absorption-based conversion, and parasitic electricity associated with delivery and auxiliaries. Three results structure the analysis. First, a reference-case energy-service ledger shows how a representative regulated WtE plant with municipal solid-waste throughput of 1500 t/day and lower heating value of 10 MJ/kg yields ~78.1 MWth of exportable driving heat and, at a 20 km corridor, ~53.0 MWcool of delivered cooling and ~8.0 MWe of net avoided cooling electricity after parasitic debiting. Second, the coupled system is governed by operating regimes, not a single efficiency score. Under the baseline package, full thermal coverage is maintained up to ~20.9 km, the stricter quality-adjusted criterion remains positive to ~22.9 km, and the electricity–relief criterion remains positive to ~44.7 km. Third, deployment-scale translation for a 1 GW IT campus (u = 0.70, L = 5 km) implies a net grid relief of ~116.9–264.4 MW across scenario packages, while the required WtE footprint ranges from roughly three to 148 equivalent representative plants, or about 0.6–40 full-load-equivalent plants at a 25% displacement target. The contribution is a siting-ready planning framework that identifies when WtE-coupled cooling remains corridor-feasible, when it becomes hybrid and marginal, and when infrastructure scale rather than thermodynamic benefit becomes the binding constraint. It is intended as a screening tool for planning and comparison, not as a project-specific hydraulic or plant-cycle design. Full article

Under growing urbanization and environmental challenges, sustainable urban mobility has become a critical priority for cities worldwide. Public Transport (PT) systems play a central role in reducing car dependency, lowering emissions, increasing network capacity, and promoting more equitable and efficient access to urban spaces for all users. Hence, the present paper aims to investigate PT preferences in the city of Larissa, Greece. Larissa is a medium-sized city currently serviced only by buses, and is currently focusing on the potential introduction of a new tram system to operate in parallel with existing bus services. To this end, a SP survey was designed and implemented, resulting in 972 observations that were collected for further statistical analysis. Survey results show a slight preference for trams over buses, with 54.63% selecting the tram and 45.37% favoring the buses. Moreover, a context-based segmentation pipeline was established using PCA, DBSCAN and t-SNE algorithms, aiding the visualization of existing clusters for transport choice approaches. Afterwards, a series of mixed logit models was applied, and statistically significant variables influencing mode choice were determined. The study also examines Value of Time (VoT) metrics and finds that respondents assign lower VoTs to trams than to buses, especially in out-of-vehicle segments of the journey, such as waiting and walking, and therefore consider trams as more pleasant and less burdensome. The findings also indicate that passengers place a high value on the quality of infrastructure related to access and waiting times, underlining the need to improve the overall user experience beyond the vehicle itself. In summary, the present research offers valuable insights into how the introduction of a tram system could possibly reshape PT usage patterns when compared with the legacy existing bus services. Full article

Financial technologies (Fintech) have rapidly reshaped access to financial services, particularly in developing countries where traditional banking remains limited. This study investigates fintech’s role in advancing financial inclusion by analyzing panel data from 89 developing economies gathered from Global Findex reports (2011–2021), complemented by International Monetary Fund (IMF), UNU-WIDER, and PRIO datasets. We applied a random-effects regression model and GMM, incorporating fintech adoption alongside macroeconomic and institutional variables such as education, governance quality, and trade openness. Our results show that fintech is the most significant driver of financial inclusion, especially in expanding account ownership, with education and institutional quality further enhancing outcomes. Conversely, we show that population growth and income disparities constrain progress, while government expenditure and GDP growth display mixed effects. We also find that fintech reduces transaction costs and barriers, yet its impact depends on digital literacy, infrastructure, and governance. In conclusion, our findings highlight that fintech represents a transformative but unevenly utilized tool, capable of fostering broader economic participation and reducing inequality when paired with supportive policies and institutional frameworks. Full article

This study explored how smart governance can foster city demographic sustainability by shaping youth retention intention in developed cities. In the case of Busan, South Korea, a structural model was constructed and tested to link the dimensions of perceived value of smart governance (PV)—including Accessibility and Efficiency of Public Services (PV-A), Transparency and Information Accessibility of Governance (PV-T), Participation and Responsiveness (PV-P), Career Development and Innovation Support (PV-C), and Contribution to Urban Quality of Life (PV-Q)—with perceived demographic sustainability (PDS) and youth retention intention (YRI). On the basis of 939 valid questionnaires, confirmatory factor analysis and a structural equation model were used to test the measurement validity, model fitting, and mediating effects. Consequently, all the dimensions of smart governance had a positive effect on youth retention intention (YRI), with all path coefficients statistically significant at p < 0.001, and perceived demographic sustainability (PDS) partially mediated the effects of each dimension on youth retention intention (YRI), with indirect effects significant at p < 0.05. Among the dimensions, PV-T had the strongest effect, with a standardized coefficient of β = 0.283 at p < 0.001, followed by PV-P (β = 0.185, p < 0.001) and PV-Q (β = 0.167, p < 0.001), while PV-A and PV-C showed comparatively weaker but still statistically significant effects. In view of governance orientation and cognitive mechanism, this study provides empirical support for demographic sustainability design in smart cities. Full article

Objective: This study aimed to evaluate the health-related quality of life (HRQoL) of informal caregivers providing primary care to elderly chronically ill patients receiving home health care services in Türkiye and to identify patient and caregiver characteristics independently associated with HRQoL. Methods: This cross-sectional study included 499 patient–caregiver dyads enrolled in home health care services at a training and research hospital in İzmir, Türkiye. Data were collected through face-to-face interviews using a sociodemographic questionnaire, the Palliative Performance Scale (PPS), and the Short Form 36 (SF-36). One-sample t-tests compared SF-36 scores with Turkish normative values. Multivariate linear regression identified independent predictors of the Physical Component Summary (PCS) and Mental Component Summary (MCS) scores. Results: Caregivers scored significantly lower than population norms across all SF-36 subdimensions (p < 0.001), with the largest impairments in Role Physical (mean difference: −53.0) and Role Emotional (−42.9). In multivariate analyses, independent predictors of poorer physical health (PCS) were severe patient functional dependence (PPS ≤ 30: β = −0.260, p < 0.001), older caregiver age (≥65 years: β = −0.089, p = 0.044), unemployment (β = −0.118, p = 0.014), additional care recipients (β = −0.095, p = 0.026), and caregiver’s own chronic illness (β = −0.169, p < 0.001). Poorer mental health (MCS) was independently associated with caregiver’s own chronic illness (β = −0.138, p = 0.002), receipt of caregiving payment (β = −0.137, p = 0.004), and university-level education (β = −0.108, p = 0.040), whereas the presence of a support person was protective (β = 0.096, p = 0.038). Conclusions: Informal caregivers of home health care-dependent elderly patients experience significantly reduced quality of life across all health domains compared with the general population. The independent determinants of caregiver health are multidimensional, encompassing patient-related factors, socioeconomic characteristics, and psychosocial resources. These findings underscore the urgent need for health systems to implement tailored interventions that address the distinct physical and mental health needs of caregivers, with particular attention to those who are elderly, chronically ill, socioeconomically disadvantaged, or highly educated. Full article

The spatiotemporal evolution of ecosystem services and the elucidation of their driving mechanisms constitute a central scientific issue in territorial spatial optimization and regional sustainable development. Taking Gansu Province, a core area of the ecological security barrier in northwestern China, as the study area, this study integrates land-use, natural geographic, and socioeconomic data from 2000 to 2020. Using a land-use transfer matrix, the InVEST model, the Geographical Detector, and the PLUS model, we constructed a comprehensive analytical framework that combines historical evolution analysis, spatial differentiation identification, and multi-scenario simulation and prediction. The framework was used to systematically reveal the spatiotemporal dynamics of four core ecosystem services, namely carbon storage (CS), water yield (WY), habitat quality (HQ), and soil retention service (SDR), and to analyze their natural and socioeconomic driving mechanisms, while also simulating land-use change and ecosystem-service responses under the natural development, ecological protection, and urban expansion scenarios in 2030. The results show that, from 2000 to 2020, land use in Gansu Province was dominated by grassland (average proportion: 33.34%) and unused land (average proportion: 41.35%). Urban land expanded from 660.52 km² to 2227.36 km², with its share increasing from 0.15% to 0.50%, mainly through the conversion of cropland and grassland. Ecosystem services exhibited marked spatial differentiation: CS increased from east to west; WY showed an increasing pattern from northwest to southeast; HQ was lower in the central and southeastern regions and higher in the western and southern regions; and SDR was dominated by low-value areas in the northwest (average proportion: 84.81%). Driving-mechanism analysis indicated that slope was the core natural factor affecting CS, HQ, and SDR (q = 0.18–0.45), while mean annual precipitation dominated the variation in WY (q = 0.31–0.35). The influence of socioeconomic factors such as GDP increased gradually over time, showing an evolutionary trend from natural dominance to coordinated natural–socioeconomic regulation. Multi-scenario simulation further showed that, under the ecological protection scenario, grassland area increased significantly (+0.60%), the proportions of medium-value CS zones and high-value WY zones increased, and ecosystem services were optimized overall; under the urban expansion scenario, cropland and urban land expanded (+0.87% and +0.23%, respectively), imposing potential pressure on part of the ecosystem-service functions. These findings provide a scientific basis for optimizing territorial spatial planning, strengthening the ecological security barrier, and promoting regional sustainable development in Gansu Province. The methodological framework also offers a broadly applicable reference for ecologically sensitive arid and semi-arid regions in northwestern China. Full article

Extreme fast charging (XFC) infrastructure is becoming increasingly necessary as the number of electric vehicles continues to grow. However, deploying such stations introduces several challenges related to power quality and compliance with regulatory standards. This work presents an alternative XFC station designed for charging multiple vehicles while ensuring low harmonic distortion in the grid currents, without the need for sinusoidal filters, by employing the Zero Harmonic Distortion (ZHD) converter. The proposed system offers galvanic isolation for each charging interface and supports additional functionalities, including the integration of Distributed Energy Resources (DERs) and the provision of ancillary services. These features are enabled through the combination of a bidirectional grid-connected active front-end operating at low switching frequency with high-frequency silicon carbide (SiC)-based dc/dc converters on the vehicle side. Hardware-in-the-loop (HIL) simulation results demonstrate a total demand distortion (TDD) of 1.12% for charging scenarios involving both 400 V and 800 V battery systems, remaining within the limits specified by IEEE 519-2022. Full article

Background: In 2021, an Australian Hospital Nursing Research Hub sponsored 13 healthcare staff to complete the Graduate Certificate (Clinical Redesign), to build capability in health service improvement though work-integrated learning (WIL). Healthcare professionals undertaking workplace-based WIL likely experience significant challenges including balancing professional and student roles and aligning work with academic requirement. These pressures were likely intensified during the Coronavirus disease 2019 (COVID-19) pandemic. This study aimed to explore and understand the experiences of hospital healthcare staff completing WIL redesign projects, including the impacts of COVID-19. Methods: A qualitative descriptive inquiry approach was used to explore individual student experiences. Thirteen staff, mostly nurses, who enrolled in the 2021 course were invited to participate. Online semi-structured interviews were conducted. Data were analyzed using a general inductive thematic analysis approach. Results: Four participants (36%) took part; all were female and working full-time. Five main themes were identified that centered around: COVID-19, Support, Motivation, Alignment and Relevance, and Success. Conclusions: Novel insights include the need to reconceptualize “success” to improve student experience, the critical role of organizational–university–student alignment in enabling WIL studies, and the unique pressures of completing WIL during crisis conditions that direct impact the health sector, such as COVID-19. Although not generalizable, these findings are likely to be important considerations more broadly to strengthen WIL design, support and student experiences, ultimately enhancing health service staff capability to lead quality improvement in the workplace. Full article

The sixth-generation (6G) mobile communication systems are anticipated to be operational by 2030, prompting extensive research efforts by governments and private entities. Designed to meet societal, economic, and technological demands unaddressed by fifth-generation (5G) networks, 6G integrates scalability, security, and reliability with ubiquity and resource-intensive artificial intelligence. Envisaged as multi-band, decentralized, autonomous, flexible, and user-centric, 6G networks incorporate innovative technologies, including cell-free (CF), three-dimensional heterogeneous networks (3D HetNet), reconfigurable intelligent surfaces (RIS), integrated sensing and communication (ISAC), as well as artificial intelligence/machine learning (ML). In 6G 3D HetNets, the densification of access points (APs) continues, accommodating increased connections and traffic volumes, alongside the use of higher frequency bands. Although 6G networks are not fully standardized, they target demanding Quality of Service (QoS) standards, such as a peak data rate of 1.0 Tbps and latency of 0.1 ms. This paper conducts a comprehensive literature review on radio resource management (RRM) in 6G cell-free and 3D HetNet systems, emphasizing challenges such as interference mitigation. It presents a taxonomy of RRM approaches, systematically studying, categorizing, and qualitatively analyzing recent techniques, outlining the current state, and indicating future trends, technologies, and challenges shaping 6G systems. Full article

Parallel, data-intensive applications are now commonly executed on infrastructures that combine Cloud, Fog, and Edge resources. In these environments, execution takes place on devices with markedly different computational power and over networks whose latency and bandwidth can fluctuate over time. Under these conditions, overall performance is influenced not only by processing speed but also by communication delays arising from data dependencies between tasks. This leads to a basic issue: whether scheduling strategies developed under computation-focused assumptions continue to perform well once communication costs are made explicit. This work examines the behavior of simple and widely adopted scheduling heuristics when network effects are modeled directly within the system. No new scheduling algorithms are introduced. Instead, the analysis focuses on how execution time and monetary cost change for deterministic parallel workloads deployed on hierarchical Cloud–Edge infrastructures exposed to stochastic latency and bandwidth variations. For this purpose, we introduce CLOWNSim, a lightweight discrete-event simulation framework that supports large-scale Monte Carlo experiments on fixed task graphs, allowing infrastructural and scheduling effects to be examined independently of workload variability. The experimental analysis covers fully centralized Cloud deployments, intermediate Fog configurations, and resource-constrained IoT scenarios. Scheduling policies based on computational speed, execution cost, or random device selection are evaluated across these settings. In Cloud and Fog environments, communication latency and data transfers represent a substantial portion of the overall makespan, weakening the impact of scheduling decisions driven primarily by computation. In IoT scenarios, limited processing capacity becomes the main limiting factor, while communication overhead remains present but less influential in comparison. The results indicate that performance trends across the Cloud–Edge continuum cannot be attributed to scheduler choice alone. Execution behavior arises from the combined effects of workload structure, placement decisions, and network properties, with different elements becoming dominant depending on the deployment context. The proposed simulation framework offers a practical way to study these interactions and to assess cost–performance trade-offs under communication conditions that reflect realistic operating environments. Full article