Search Results (9,830)

Identifying the multi-scale drivers of ecosystem service (ES) trade-off intensity is essential for promoting regional sustainability. However, the existing multi-scale ES studies typically rely on predefined administrative units or fixed grid sizes due to the absence of scientifically sound scale-partitioning approaches, which limits the identification of characteristic scales and obscures scale-dependent interactions. This study broke new ground by combining continuous wavelet transform (CWT) and optimal parameter geographic detector (OPGD) to automatically identify the characteristic scales of trade-offs between ecosystem services, thus opening up a new avenue in multi-scale studies. Taking China’s plain–mountain transition zone as a case study, we evaluate trade-off intensity among four key ecosystem services—water yield (WY), habitat quality (HQ), soil conservation (SC), and carbon storage (CS). The results show that the following: (1) The identification of 36 characteristic scales (ranging from 5 km to 55 km) indicates that ecosystem service trade-offs operate across a wide range of spatial extents, implying that a single management scale cannot effectively address all ES interactions. (2) From 2000 to 2020, CS-HQ, SC-HQ, and WY-HQ trade-off intensities were jointly driven by both natural conditions and human activities, whereas CS-SC was predominantly influenced by natural and climatic factors. The trade-off intensities between CS-WY and WY-SC were mainly controlled by climatic forces. (3) The explanatory power (q value) of each factor varied distinctly with spatial scale, and the interaction effects between multiple factors were substantially stronger than their individual effects. This indicates that ecosystem service trade-offs are primarily governed by coupled processes rather than isolated drivers. Consequently, management strategies targeting single drivers are unlikely to be effective. Instead, ecosystem management should be designed around combinations of drivers that operate at specific spatial scales and provide a concrete pathway for translating trade-off analyses into spatially differentiated management actions. Full article

Urban parks are essential to sustainable cities, providing climate regulation, supporting biodiversity, and offering vital spaces for recreation and overall well-being. At the same time, their soils can act as long-term reservoirs for persistent organic pollutants (POPs), reflecting decades of atmospheric deposition, diffuse urban emissions, and historical land-use practices. This review synthesises current knowledge on the occurrence, sources, and environmental behaviour of priority POPs, including OCPs, PCBs, PCDD/Fs, PBDEs, PFAS, and PAHs, in the soils of urban parks and gardens worldwide. Evidence from multiple regions reveals consistent patterns: urban parks accumulate complex mixtures of legacy and emerging contaminants, reflecting both historical inputs and ongoing urban activities. These contaminants primarily contribute to scenarios of chronic, low-level exposure through the ingestion of soil and dust, inhalation of resuspended particles, dermal contact, and, in some cases, dietary intake when food is cultivated in contaminated park soils. While such exposure pathways have been associated with a range of adverse health outcomes in toxicological and epidemiological studies, the presence of POPs in park soils does not imply that urban parks represent hazardous environments. Instead, it emphasises the importance of proportionate, evidence-based assessments within spaces that yield substantial net benefits to public health. Despite growing research interest, significant gaps remain, including limited understanding of mixture toxicity, insufficient data on temporal trends, a lack of harmonised monitoring strategies, and the absence of exposure scenarios specifically tailored to recreational soils. This review also examines major international and European regulatory frameworks and soil-quality guideline approaches relevant to urban and recreational soils, identifying mismatches between scientific evidence and regulatory practice. By integrating perspectives from environmental chemistry, toxicology, urban ecology, and policy, this review highlights the importance of targeted monitoring and context-specific management strategies to ensure that urban parks remain safe, healthy, and equitable components of increasingly complex urban landscapes. Full article

Rural freight mobility and logistics face persistent challenges, including inadequate road infrastructure, high transportation costs, safety risks, tolls at link access points, and dispersed demand. Traditional inventory routing models often fail to address these complexities, especially in rural contexts where alternative routing options and integrated in-haul/back-haul operations are essential for improving efficiency and reducing empty miles. This study proposes a bi-objective mathematical model for the inventory routing problem in rural logistics, incorporating multiple routing attributes (transportation costs, risks, link-access tolls, and distances) and inventory dynamics (integrated in-haul and back-haul visits). The model aims to minimize total logistics costs and accident risk while balancing operational expenses and safety considerations. Risk estimation is derived from crash data along rural road links connecting distribution nodes. A real-world case study involving Walmart distribution centers in Macclenny, Baker County, Florida, and several rural Supercenters is conducted to validate the model. A modified Non-Dominated Sorting Genetic Algorithm II (NSGA-II) is developed and compared with CPLEX for solution efficiency across small and large-scale problem instances. Results indicate that the proposed approach outperforms classical methods, improves routing decisions in rural logistics systems, and achieves cost savings of up to 17% for the evaluated objectives, emphasizing the importance of using multi-attribute, multi-route network structures in rural logistics optimization. Full article

The sustainable transformation of electronics supply chains (ESCs) increasingly relies on effective green supply chain planning under carbon pricing and demand uncertainty. However, prior studies often lack an integrated framework that jointly considers carbon taxation, green technology investment, and profitability—environment trade-offs in forward and reverse supply chains. To address this gap, this study proposes a fuzzy multi-goal optimization model using linear goal programming under progressive carbon taxation. The model incorporates fuzzy demand (triangular fuzzy numbers), carbon emissions, carbon taxes, and green investment costs and is converted into a solvable linear form via a defuzzification-based procedure to simultaneously achieve multiple aspiration levels for economic and environmental objectives. A real-world ESC case validates the model. The results show that carbon taxation and green investments can reduce emissions while maintaining profitability, with total cost and emission sensitivity of ±10–20% across different policies and demand uncertainty settings. The findings support adaptive, policy-aware planning by guiding green investment intensity and forward–reverse logistics decisions to balance cost efficiency and emissions reduction and provide actionable insights for managers facing progressive carbon pricing regulations. Full article

Indonesia is a country of vast geographical and cultural diversity, hosting numerous cultural festivals annually, such as Sekaten, Labuhan, and the Lembah Baliem Festival. However, as the world’s largest archipelago country, Indonesia faces geographical challenges in terms of ensuring the reliability of communication networks, particularly in maintaining user experience in high-density, short-duration traffic burst environments, such as festivals. The nation’s network connectivity relies heavily on satellite networks and Palapa Ring, a national fibre-optic backbone network that comprises a combination of inland and underwater networks, connecting major and remote islands to the global internet. Although this solution can provide a baseline for broadband connectivity, an adaptive intelligent mobile edge-based solution is needed to complement the existing network infrastructure in order to meet the dynamic demands of localised and transient traffic surges across multiple temporary, geographically dispersed festival sites in both urban and rural areas. In this paper, we present a multimodal study that combines network connectivity measurements during a festival with an extensive user analysis of festival participants and organisers to investigate reliability gaps in user experience regarding network connectivity. Our findings show that internet connectivity was intermittently disrupted during the festival, and our user analysis revealed a gap between customer expectations and perceptions of network service quality and the provision of application services in a heterogeneous festival environment. To address this challenge, we propose a novel next-generation intelligent festival mobile edge framework, MobiFest, which integrates the multi-layer Cognitive Cache which has geospatial–temporal edge intelligence for localised service provisioning to improve the delivery of application services in both urban and rural festival environments. In our extensive experiments, we employ smart garbage as our use case and demonstrate how our complex, multimodal intelligent network protocol SmartGarbiC, designed based on MobiFest for garbage management services, outperforms state-of-the-art and benchmark protocols. Full article

Background: In high-risk non-muscle-invasive bladder cancer (NMIBC), adjuvant therapies, such as intravesical Bacillus Calmette–Guérin (BCG) instillation, are widely employed; however, BCG treatment poses challenges due to potential adverse effects and ongoing supply limitations. This study aimed to evaluate treatment patterns, therapeutic efficacy, incidence of adverse events, and clinical predictors of recurrence and progression in patients with high-grade pT1 urothelial carcinoma (HG-T1 UC) of the bladder. Methods: This retrospective cohort study included 204 patients diagnosed with HG-pT1 UC who underwent transurethral resection of bladder tumor (TURBT) at Toho University Sakura Medical Center between 2010 and 2021. Clinical data encompassing treatment modalities (BCG or intravesical chemotherapy), complications, and oncological outcomes were collected. Recurrence-Free Survival (RFS), Progression-Free Survival, and Cancer-Specific Survival were analyzed using Kaplan–Meier analyses and multivariate regression models. Results: Maintenance BCG therapy was significantly associated with prolonged RFS compared to other treatments, including among ‘very high-risk’ patients. However, 52.4% of patients receiving BCG maintenance experienced adverse events, with dose reductions required in 59% of cases. Notably, recurrence rates did not significantly differ based on dose reduction or the total number of BCG instillations. Tumor multiplicity emerged as an independent risk factor for recurrence. Conclusions: Although maintenance BCG therapy remains essential for managing HG-T1 UC, especially in high-risk patients, treatment should be individualized due to concerns about tolerability and availability. The study results support the importance of personalized strategies based on risk stratification as outlined in clinical guidelines for preventing recurrence in NMIBC. Full article

Background: Inherited retinal dystrophies are a heterogeneous group of progressive disorders impacting photoreceptor function, often limiting the usefulness of standard electroretinography in advanced cases. Full-field stimulus test (FST) testing has become a sensitive psychophysical technique for detecting residual visual function when traditional electrophysiology is non-recordable. This study evaluated the ability of chromatic FST to differentiate rod–cone from cone photoreceptor dysfunction in patients with genetically confirmed inherited retinal dystrophies. Methods: Cross-sectional FST data were analyzed from 39 patients (mean age 45.7 ± 20.0 years) with genetically confirmed inherited retinal dystrophies at a tertiary academic center. All participants underwent standardized FST testing using white, red, and blue stimuli. Patients were classified into rod–cone dystrophy (n = 27) or cone dystrophy (n = 12) groups based on genetic and clinical criteria. Group comparisons focused on FST thresholds and especially blue–red threshold differences as markers of photoreceptor-mediated function. Bonferroni correction was applied to adjust for multiple comparisons across four primary FST parameters. Additional analyses by genotype were performed with nonparametric tests. Results: Eight different genetic mutations were represented, including Phosphodiesterase 6A (PDE6A) (n = 10), Rhodopsin (RHO) (n = 7), Phosphodiesterase 6B (PDE6B) (n = 6), Cyclic Nucleotide-Gated Channel Beta 1 (CNGB1) (n = 4), Cyclic Nucleotide-Gated Channel Alpha 3 (CNGA3) (n = 4), Nuclear Receptor Subfamily 2 Group E Member 3 (NR2E3) (n = 4), Guanylate Cyclase 2D (GUCY2D) (n = 2), and Cyclic Nucleotide-Gated Channel Beta 3 (CNGB3) (n = 2). Blue–red FST threshold differences exhibited moderate group discrimination in uncorrected analysis, with rod–cone dystrophies averaging −8.35 ± 10.37 dB and cone dystrophies −11.20 ± 14.60 dB. The area under the receiver operating characteristic curve for blue–red difference was 0.74 (95% CI: 0.59–0.90), with 75% sensitivity and 70.4% specificity at a −10 dB cutoff. However, no chromatic FST parameter maintained statistical significance between groups after Bonferroni correction. Inter-eye FST correlation was high (r = 0.758, p < 0.001), supporting test reliability. Conclusions: Chromatic FST testing provides a practical and sensitive means to assess photoreceptor function in advanced inherited retinal dystrophies, particularly when standard electrophysiologic methods are uninformative. Although the blue–red threshold difference offers moderate discrimination between rod–cone and cone dystrophies in uncorrected analysis, no chromatic parameter reached statistical significance after adjustment for multiple testing. Chromatic FST should be considered a supplementary approach for clinical monitoring and therapeutic studies in advanced retinal dystrophies, with further validation needed in larger cohorts. Full article

Computer-aided diagnosis (CAD) systems based on deep learning have shown significant potential for Alzheimer’s disease (AD) stage classification from Magnetic Resonance Imaging (MRI). Nevertheless, challenges such as class imbalance, small sample sizes, and the presence of multiple slices per subject may lead to biased evaluation and statistically unreliable performance, particularly for minority classes. In this study, a Vision Transformer (ViT)-based framework is proposed for multi-class AD classification using a Kaggle dataset containing 6400 MRI slices across four cognitive stages. A subject-wise data-splitting strategy is employed to prevent information leakage between the training and testing sets, and the statistical unreliability of near-perfect scores in underrepresented classes is critically examined. An ablation study is conducted to assess the contribution of key architectural components, demonstrating the effectiveness of self-attention and patch embedding in capturing discriminative features. Furthermore, attention-based visualization maps are incorporated to highlight brain regions influencing the model’s decisions and to illustrate subtle anatomical differences between MildDemented and VeryMildDemented cases. The proposed approach achieves a test accuracy of 97.98%, outperforming existing methods on the same dataset while providing improved interpretability. It supports early and accurate AD stage identification. Full article

This study examines multi-celebrity deployment as a destination branding practice, using Seoul as an empirical case. The analysis draws on 172 official tourism promotional videos released by the Seoul Tourism Organization between 2011 and 2025, featuring 67 identifiable celebrities and 438 destination references. A qualitative content analysis examines how celebrity endorsement is organized as a branding mechanism, focusing on who appears, what is represented, and how representations are communicated across media formats over time. The findings show that Seoul’s tourism promotion operates through a structured multi-celebrity branding system in which multiple endorsers are coordinated across campaigns and periods. Endorser selection is anchored in Hallyu-affiliated celebrities who function as primary carriers of destination meaning, while emerging, non-Hallyu, and heritage-linked figures occupy complementary roles that broaden representational scope and reduce reliance on individual figures. Celebrity endorsement continues to emphasize major and symbolically dense attractions, while also extending visibility to everyday neighborhoods and locally oriented urban landscapes. Long-term ambassador-led campaigns coexist with travel vlogs and other creative video formats, enabling variation in narrative tone and experiential framing. Theoretically, the study extends celebrity endorsement research by conceptualizing multi-celebrity deployment as a coordinated branding system. Practically, the findings show how destination marketing organizations can mobilize a broad pool of celebrity resources to structure endorsement portfolios over time. Coordinated use of celebrities with different levels of familiarity supports wider spatial representation, enables ongoing narrative renewal, and maintains promotional continuity across changing media environments. This configuration is most applicable to destinations with strong cultural visibility and an established celebrity ecosystem, and may be less transferable to destinations with limited access to influential figures. Full article

To address the “silo effect” in construction waste management and the inefficiency of resource allocation in large-scale, multi-section engineering projects, this study developed a cloud-based regional collaborative platform for construction waste management. The platform adopts a technical framework based on Java 1.8.0, Spring Boot 2.4.4, and MySQL 8.0.16, and integrates a visual interactive interface. It supports dynamic access, data entry, quality review, and scheduling of construction waste information across multiple sections and projects. Validated through a case study on the Changhu section of the Guangdong Guanshen–Changhu Expressway expansion project, the platform successfully achieved spatial–temporal optimization of 740 thousand cubic meters of diversified construction waste across seven sections. The comprehensive utilization rate of construction waste increased by more than 25%. Practice has shown that the platform effectively promotes carbon emission reduction in earthworks, enhances resource circularity, and provides digital support for construction quality control. This platform presents an innovative informatics-driven approach to construction waste management, serving as a replicable model. Full article

Sub-Saharan Africa’s cereal yields remain ~60% below global benchmarks, while unmanned aerial vehicle (UAV) adoption in smallholder systems averages below 2–3% across major economies, revealing a performance–adoption disconnect that requires systematic investigation. This Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 synthesis of 127 sources quantifies the performance of UAV sensors and identifies mechanisms that constrain their adoption across regional agricultural systems. Random-effects meta-analysis synthesized evidence from 81 quantitative studies, yielding 101 total observations. Pooled detection accuracy was estimated from 49 studies contributing 52 observations (mean 90.2%, 95% confidence interval (CI): 89.8–92.6%). Yield prediction performance was assessed from 32 studies contributing 49 observations (pooled coefficient of determination (R²) = 0.841, 95% CI: 0.827–0.855), validating technical feasibility. Cost-effectiveness analysis reveals significant performance–price differentiation: red-green-blue (RGB) sensors achieve 89.4% accuracy at United States Dollar (USD) 16.50 per percentage point versus hyperspectral systems at 93.7% accuracy but at USD 132.17 per point, resulting in a 25.6 times cost differential. Yield prediction models demonstrate robust performance (R² = 0.81; cereal crops R² = 0.82). Barrier analysis identifies economic constraints as the primary limiter, with capital requirements reaching 0.8–3.1 times the annual smallholder income. Infrastructure deficits impose secondary constraints, particularly in rural electrification, below 50%. Case study synthesis reveals that coordinated interventions addressing multiple barriers simultaneously—cooperative ownership, off-grid infrastructure, and streamlined regulation—achieve substantially higher adoption than isolated approaches. Engineering economics positions RGB platforms for individual deployment and multispectral systems for cooperative scales (20–50 farmers), establishing feasible deployment pathways for tens of million regional smallholder operations. Full article

Background: Maternal serum screening remains widely implemented for prenatal aneuploidy assessment despite increased uptake of cell-free DNA testing. Evidence suggests that fetal sex may influence placental endocrine function and maternal serum biomarker levels; however, available studies are inconsistent and often limited by sample size or incomplete adjustment for maternal factors. Objective: The aim of this study was to determine whether fetal sex independently modifies first- and second-trimester maternal serum marker Multiple of the Median (MoM) values and whether sex-related biochemical variation affects trisomy-21 screen-positive classification. Methods: A retrospective cohort was identified from institutional screening records (10,384 screened pregnancies), of which 5040 first-trimester and 1476 second-trimester cases had complete biochemical data. First-trimester PAPP-A and free β-hCG, as well as second-trimester AFP, uE3, and free β-hCG, were measured. Implausible MoM values (<0.10 or >5.00) were excluded. Multivariable linear and logistic regression models adjusted for maternal age, maternal weight, gestational age at sampling, and parity assessed independent associations. Results: Pregnancies with female fetuses showed significantly higher MoM values for first-trimester PAPP-A and free β-hCG as well as second-trimester AFP and uE3. The magnitude of these differences was small, and no significant differences were observed in trisomy-21 screen-positive rates between fetal sex groups. Conclusions: Fetal sex independently influences several maternal serum markers across both trimesters but does not result in clinically meaningful differences in trisomy-21 screening outcomes under current algorithms. Any potential relevance of fetal sex for risk interpretation should be regarded as hypothesis-generating and requires outcome-validated investigation before clinical application. Full article

With the rapid development of renewable energy technologies, numerous distributed energy resources (DERs) have been integrated into power systems. How to fully exploit renewable energy while maintaining the stable operation of power systems remains an urgent challenge. Furthermore, the diversity of DERs’ ownership requires scheduling approaches that account for the distinct interests and characteristics of multiple stakeholders. To address these challenges, this study introduces a two-stage operational optimization framework for the virtual power plant (VPP), which is grounded in a Stackelberg game model. This strategy innovatively combines two conventional control methods: the day-ahead stage employs direct control for global pre-scheduling, leveraging its cost optimization capability; the intraday stage utilizes dynamic pricing to guide prosumers, tapping into DERs’ flexibility while accommodating their individual energy usage preferences. The Stackelberg game is resolved through a tiered solution methodology employing particle swarm optimization (PSO). To enhance solution efficiency, a Kriging surrogate model is introduced to replace the prosumers’ models, significantly reducing the computational burden of the PSO. Case studies demonstrate that the proposed strategy can balance operating costs and energy usage preferences, and the proposed solution approach can significantly enhance solution efficiency. Full article

This study stems from the clear need to understand why and how organizations in Romania integrate emerging digital technologies into circular economy (CE) practices, given the critical role of this integration in improving resource efficiency and supporting sustainable business models. Data were collected through a structured questionnaire applied to 149 organizations of different sizes, ranging from SMEs (fewer than 50 employees) to large corporations (over 500 employees), operating across multiple sectors, including agriculture, construction, security, services and research. The questionnaire assessed organizations’ familiarity with CE principles, their stage of CE implementation, and their adoption of digital technologies, including artificial intelligence (AI), Internet of Things (IoT), blockchain, cloud computing and robotics. The results indicate that most organizations are aware of the potential benefits of digital technologies, particularly in terms of resource efficiency, enhanced product traceability and support for sustainability goals. However, effective implementation remains quite limited in many cases due to inadequate or outdated infrastructure, lack of technical skills, and organizational resistance to changes. At the same time, the findings further reveal a growing strategic interest in digitalization: approximately 41% of SMEs and 59% of large organizations plan to increase investments in digitalization, primarily to improve sustainability performance and foster innovation. Overall, the study provides a comprehensive overview of the current state of digitalization in support of CE in Romania and proposes practical recommendations for organizations and decision-makers, highlighting both emerging opportunities and persistent barriers. Full article

We present a fully controlled thermodynamic study of the two-dimensional dipolar Q-state clock model on small square lattices with free boundaries, combining exhaustive state enumeration with noise-free evaluation of canonical observables. We resolve the complete energy spectra and degeneracies $\{E_n,c_n\}$ for the Ising case ($Q=2$) on lattices of size $L=3,4,5$, and for clock symmetries $Q=4,6,8$ on a $3\times 3$ lattice, tracking how the competition between exchange and long-range dipolar interactions reorganizes the low-energy manifold as the ratio $\alpha =D/J$ is varied. Beyond a finite-size characterization, we identify several qualitatively new thermodynamic signatures induced solely by dipolar anisotropy. First, we demonstrate that ground-state level crossings generated by long-range interactions appear as exact zeros of the specific heat in the limit $C(T\to 0,\alpha )$, establishing an unambiguous correspondence between microscopic spectral rearrangements and macroscopic caloric response. Second, we show that the shape of the associated Schottky-like anomalies encodes detailed information about the degeneracy structure of the competing low-energy states: odd lattices ($L=3,5$) display strongly asymmetric peaks due to unbalanced multiplicities, whereas the even lattice ($L=4$) exhibits three critical values of $\alpha$ accompanied by nearly symmetric anomalies, reflecting paired degeneracies and revealing lattice parity as a key organizing principle. Third, we uncover a symmetry-driven crossover with increasing Q: while the $Q=2$ and $Q=4$ models retain sharp dipolar-induced critical points and pronounced low-temperature structure, for $Q\ge 6$, the energy landscape becomes sufficiently smooth to suppress ground-state crossings altogether, yielding purely thermal specific-heat maxima. Altogether, our results provide a unified, size- and symmetry-resolved picture of how long-range anisotropy, lattice parity, and discrete rotational symmetry shape the thermodynamics of mesoscopic magnetic systems. We show that dipolar interactions alone are sufficient to generate nontrivial critical-like caloric behavior in clusters as small as $3\times 3$, establishing exact finite-size benchmarks directly relevant for van der Waals nanomagnets, artificial spin-ice arrays, and dipolar-coupled nanomagnetic structures. Full article