Search Results (803)

The scientific site selection for pallet pooling systems is pivotal to enhancing logistics efficiency and environmental performance. However, previous studies mainly adopt single-objective optimization approaches, which fail to simultaneously account for economic, environmental, and operational performance factors. The contribution of this paper lies in proposing an integrated decision-making method based on BWM-GIS-DEA to address the site selection problem for pallet pooling service centers. First, the Best-Worst Method (BWM) determines the weights of 13 criteria across 5 dimensions: economic, transportation, geographical location, technological, and service coverage. These criteria include factors such as the distribution density of pallet manufacturers and potential customers. Then, suitability maps are generated using Geographic Information System (GIS) spatial overlay technology to identify 6 alternative cities. Finally, a two-layer Data Envelopment Analysis (DEA) model is applied to measure the efficiency of the alternative sites. This method is applied in Inner Mongolia, China, and Ejin Horo Banner is identified as the optimal site with an efficiency score of 1.156, demonstrating superior resource allocation characterized by lower land costs and higher pallet turnover rates. The proposed framework not only fills a methodological gap in sustainable facility location research but also provides a replicable and policy-ready tool to guide practical decision-making. Full article

Background/Objectives: Severe acute pancreatitis (SAP) carries substantial morbidity and resource burden, and early risk stratification remains challenging with conventional scores that require serial observations. The aim of this study was to develop and compare supervised machine-learning (ML) pipelines—integrating feature selection and SHAP-based explainability—for early prediction of SAP at emergency department (ED) presentation. Methods: This retrospective, single-center cohort was conducted in a tertiary-care ED between 1 January 2022 and 1 January 2025. Adult patients with acute pancreatitis were identified from electronic records; SAP was classified per the Revised Atlanta criteria (persistent organ failure ≥ 48 h). Six feature-selection methods (univariate AUROC filter, RFE, mRMR, LASSO, elastic net, Boruta) were paired with six classifiers (kNN, elastic-net logistic regression, MARS, random forest, SVM-RBF, XGBoost) to yield 36 pipelines. Discrimination, calibration, and error metrics were estimated with bootstrapping; SHAP was used for model interpretability. Results: Of 743 patients (non-SAP 676; SAP 67), SAP prevalence was 9.0%. Compared with non-SAP, SAP patients more often had hypertension (38.8% vs. 27.1%) and malignancy (19.4% vs. 7.2%); they presented with lower GCS, higher heart and respiratory rates, lower systolic blood pressure, and more frequent peripancreatic fluid (31.3% vs. 16.9%) and pleural effusion (43.3% vs. 17.5%). Albumin was lower by 4.18 g/L, with broader renal–electrolyte and inflammatory derangements. Across the best-performing models, AUROC spanned 0.750–0.826; the top pipeline (RFE–RF features + kNN) reached 0.826, while random-forest-based pipelines showed favorable calibration. SHAP confirmed clinically plausible contributions from routinely available variables. Conclusions: In this study, integrating feature selection with ML produced accurate and interpretable early prediction of SAP using data available at ED arrival. The approach highlights actionable predictors and may support earlier triage and resource allocation; external validation is warranted. Full article

Background/Objectives: Childbirth is a natural and joyfully anticipated life event for parents and relatives. Yet, in some cases, it can be a medical emergency requiring immediate intervention, i.e., neonatal resuscitation. The majority of newborns breathe spontaneously; a small number, though, may receive basic life support (assisted transition), and an even smaller but clinically significant number require advanced life support (resuscitation). Within the context of family-centered care, the presence of parents during resuscitation has emerged as a factor with potential implications for emotional adjustment, communication with healthcare providers, and early parent–infant bonding. However, the presence of family members during neonatal resuscitation remains a subject of ongoing debate among healthcare professionals (HCPs). Despite increasing recognition of its potential benefits, HCPs’ views on parental presence during such critical procedures have not been extensively investigated in Greece. This study aims at developing and validating a tool to assess healthcare professionals’ views on parental presence during neonatal resuscitation. Methods: A preliminary questionnaire was developed based on the principles of family-centered care and adapted to the Greek population. The first phase included expert assessment of validity, clarity, and relevance using a modified Delphi method. Item Content Validity Index (I-CVI) and Scale CVI (S-CVI) were calculated. Pilot testing was conducted to assess test–retest reliability. Reliability was assessed using the Intraclass Correlation Coefficient (ICC) and Bland–Altman analyses. The study followed the principles of the Declaration of Helsinki, ensuring anonymity, informed consent, and confidentiality. Results: The questionnaire includes 37–50 items allocated in four sections. It demonstrated excellent content validity (CVI = 1.00) and good test–retest reliability (ICC = 0.86). Qualitative feedback indicated that the tool is user-friendly and comprehensive. Interestingly, participants expressed genuine concerns regarding the implementation of parental presence in neonatal resuscitation. Conclusions: The questionnaire development process led to a comprehensive tool, ready for large-scale testing in order to further establish its validity and internal consistency. Full article

Urban regeneration has increasingly become a global strategy for promoting sustainable urban development, with the renewal of deteriorating residential communities serving as a key dimension of this process. Within the framework of a people-centered development paradigm, growing attention has been directed toward the necessity of securing residents’ satisfaction in community renewal initiatives. This study employs advanced textual analysis of resident submissions collected from government–citizen interaction platforms to investigate the determinants of satisfaction with renewal projects. Leveraging the semantic comprehension capabilities of large language models (LLMs), we identify both salient keywords and sentiment orientations embedded in residents’ narratives. Guided by the theoretical framework of resident satisfaction, the extracted keywords are organized into seven thematic domains: basic infrastructure improvement, quality-enhancement renovation, solicitation of residents’ preferences, residents’ decision-making power, policy transparency, construction governance, and community-level communication. Regression modeling is subsequently applied to assess the relative influence of these thematic domains on residents’ satisfaction. The findings suggest that insufficient integration of residents’ preferences at the preliminary stages of participation constitutes a principal source of dissatisfaction during the implementation of renewal projects. Furthermore, the study compares Latent Dirichlet Allocation (LDA) topic modeling with LLM-based topic clustering, revealing the latter’s superior capacity to capture thematic structures in complex, long-form textual data. These results underscore the potential of LLMs to enhance the analytical rigor of research on urban regeneration and citizen participation. Full article

The growing prevalence of digital labor platforms has fundamentally transformed business models by creating interconnected value systems that redefine how work is organized, delivered, and monetized in today’s digital economy. This study examines platform-based business model innovation through the lens of value co-creation processes, analyzing user-generated content from digital work platforms including Reddit, FlexJobs, Toptal, and Deel. Using Latent Dirichlet Allocation (LDA) topic modeling on 342 semantically filtered reviews from platform workers, we identified six key themes characterizing stakeholder experiences: User Experience and Platform Evaluation (23.77%), Financial Concerns and Time Management (18.49%), Platform Satisfaction and Recommendation System (16.60%), Paid Services and Investment Strategies (15.09%), Job Search Processes and Remote Work Alternatives (13.96%), and Overall Platform Performance and Account Management (12.08%). These findings reveal how digital platforms create value through complex interactions between technology infrastructure, governance mechanisms, and stakeholder experiences within interconnected ecosystems. The dominance of user experience concerns over purely economic considerations challenges traditional labor economics frameworks and highlights the critical role of platform design in worker satisfaction. Our analysis demonstrates that successful plsatform business models depend on balancing technological capabilities with human-centered value propositions, requiring innovative approaches to ecosystem orchestration, stakeholder engagement, and value distribution. The study contributes to understanding how digital business models can leverage interconnected value systems to drive sustainable innovation, offering strategic insights for platform design, ecosystem governance, and business model optimization in the digital era. Full article

Education has become one of the important drivers of residential mobility. The school district system in China has transformed school choice into a competition for housing ownership based on family capital, resulting in the capitalization of education and gentrification. Understanding the patterns of education-driven residential mobility is therefore of significant importance for urban planning, educational policy and social equity research. In this study, we depicted and analyzed the heterogeneity of residential mobility formed by the interaction of schooling choice, diversity of family characteristics, and housing preferences. Based on the household questionnaire survey conducted in Tianjin, we identified five typical education-driven residential mobility patterns by using the K-Prototype clustering algorithm. The empirical results implied that in China, particularly in megacities like Tianjin with a strict school district system tied to housing, wealthy families approach high-quality education through their socio-economic advantages for cultural reproduction; families sacrifice living conditions to access leading schools by acquiring old second-hand housing or smaller new-commercial housing; lower-income families relocate to within a short distance of the city center to change home ownership status for basic school eligibility; and families opting out of school districts achieve residential improvements and display greater locational diversity in relocation. Education-driven residential mobility is reshaping urban space, and may intensify socio-spatial stratification, even influencing long-term urban sustainability through patterns of resource allocation, neighborhood stability, and social equity. While this study focuses on Tianjin, the impacts of such school-housing-linked policies hold broader relevance for global cities facing similar challenges. Full article

To achieve precise trajectory tracking and lateral-roll stability during the coordinated control of high-speed autonomous vehicles under lane-changing conditions, this paper proposes an integrated control strategy based on state estimation with a high-order sliding mode and a double-power sliding mode. Firstly, establish a three-degrees-of-freedom vehicle dynamics model and trajectory-tracking error model that includes yaw lateral-roll coupling, and use an extended Kalman filter to estimate real-time unmeasurable states such as the center of mass roll angle, roll angle, and angular velocity. Then, for the trajectory-tracking subsystem, a high-order sliding-mode controller is designed. By introducing a virtual control variable and an arbitrary-order robust differentiator, the switching signal is implicitly integrated into the derivative of the control variable, significantly reducing chattering and ensuring finite-time convergence. Furthermore, in the lateral stability loop, a double-power convergence law sliding-mode controller is constructed to dynamically allocate yaw moment and roll moment with estimated state as feedback, achieving the decoupling optimization of stability and tracking performance. The joint simulation results show that the proposed strategy significantly outperforms traditional sliding-mode schemes in terms of lateral deviation, heading deviation, and key state oscillations under typical high-speed lane-changing conditions. This can provide theoretical basis and engineering reference for integrated control of autonomous vehicles under high dynamic limit conditions. Full article

Ensuring the smooth production and distribution of agricultural products is a crucial pathway to achieving a balance between supply and demand. However, the information within the agricultural product supply chain is characterized by its dynamic and asymmetric nature, compounded by frequent outbreaks of infectious diseases that lead to supply interruptions and allocation difficulties. These factors collectively undermine the operational efficiency and resilience of the agricultural product supply chain. This study develops an integrated allocation-location optimization model for emergency agricultural product supply chains based on a rolling horizon approach. The model accounts for both supply shortage and sufficient scenarios, with objectives to maximize the comprehensive material satisfaction rate, minimize the activation cost of distribution centers, and minimize allocation time. The proposed model is solved using the Benders decomposition algorithm. Finally, a case study based on the Shanghai pandemic outbreak is conducted for numerical simulation. The results demonstrate the effectiveness of the model: the comprehensive material satisfaction rate increases progressively over the rolling periods, rising from approximately 84% in period 1 to 100% by period 3. Furthermore, fairness analysis confirms that the model also effectively ensures equitable distribution of supplies. Full article

Underwater acoustic communication faces significant challenges including limited bandwidth, high propagation delays, severe multipath fading, and stringent energy constraints. While integrated sensing and communication (ISAC) has shown promise in radio frequency systems, its adaptation to underwater environments remains challenging due to the unique acoustic channel characteristics and the inadequacy of traditional delay-based performance metrics that fail to capture the spatio-temporal value of information in dynamic underwater scenarios. This paper presents a comprehensive underwater ISAC framework centered on a novel Spatio-Temporal Information-Theoretic Freshness metric that fundamentally transforms resource allocation from delay minimization to value maximization. Unlike conventional approaches that treat all data equally, our spatio-temporal framework enables intelligent prioritization by recognizing that obstacle detection data directly ahead of an autonomous underwater vehicle (AUV) require immediate processing. Our framework addresses key underwater ISAC challenges through spatio-temporal-guided power allocation, adaptive beamforming, waveform optimization, and cooperative sensing strategies. Multi-agent reinforcement learning algorithms enable coordinated resource allocation and mission-critical information prioritization across heterogeneous networks comprising surface buoys, AUVs, and static sensors. Extensive simulations in realistic Munk profile acoustic environments demonstrate significant performance improvements. The spatio-temporal framework successfully filters spatially irrelevant data, resulting in substantial energy savings for battery-constrained underwater nodes. Full article

Background: Hip fractures in geriatric patients represent a major public health burden, with a clinically important subset presenting with concomitant upper extremity (UE) fractures. The independent impact of these dual injuries on clinical outcomes remains incompletely characterized. Methods: A retrospective study of patients aged ≥65 years who underwent surgical treatment for hip fracture at tertiary medical center, between January 2010 and January 2024. Patients were stratified based on the presence of a UE fracture sustained at the same time as the hip fracture. Multivariable regression models were used to assess outcomes, adjusting for age, sex, hip fracture type, and comorbidity burden. Primary outcomes were hospital length of stay and mortality at 30 days and 1 year. Secondary outcomes included readmission rates, revision surgery, and infection complications. Results: Of 7488 patients, 251 (3.4%) had concomitant upper extremity (UE) fractures. These patients had a longer mean hospital stay compared with isolated hip fractures (20.2 vs. 17.5 days, p = 0.047), with no significant difference in 30-day mortality (p = 0.439) and a trend toward lower 1-year mortality (p = 0.058). In the concomitant UE fracture group, operative treatment was associated with longer hospitalization (26.2 vs. 19.2 days, p = 0.05) and higher revision surgery rates (14.0% vs. 3.1%, p = 0.01). Subgroup analyses by fracture type showed similar trends, with longer hospital stays observed in intracapsular fractures with concomitant injury (p = 0.05). Subgroup analysis by UE fracture location showed significantly longer stays for distal radius fractures compared with isolated hip fractures, whereas no significant differences were observed for proximal humerus or other UE fracture locations. Conclusions: Concomitant UE fractures in geriatric hip fracture patients are associated with prolonged hospitalization. Operative management of UE fractures results in longer hospital stays and an increased risk of revision surgery. These findings highlight the importance of tailored perioperative planning and resource allocation for this vulnerable patient group. Full article

This study evaluates the operational efficiency of accredited private healthcare facilities in Italy, a sector increasingly complementing the public National Health Service. Unlike previous studies that aggregate public and private providers, this research focuses exclusively on private facilities, providing a consistent and detailed evaluation of their performance. Utilizing game-theoretic cross-efficiency Data Envelopment Analysis (DEA) combined with Classification and Regression Tree (CART) analysis, this study identifies endogenous and exogenous efficiency drivers. Results indicate that private facilities operate at high efficiency levels (mean cross-efficiency = 0.923), with smaller facilities outperforming larger ones, though resources remain underutilized. Inactive ward and bed non-occupancy rates emerge as key inefficiency factors. Regional analysis highlights minimal disparities between the north–center and south, but significant local variations persist, shaped by governance, funding allocation, and institutional frameworks. This study also identifies an “efficiency paradox”, as in deficit regions, private expenditure correlates with higher efficiency, whereas in surplus regions, greater spending does not necessarily improve performance. These findings provide actionable insights for healthcare managers and policymakers, emphasizing the need to maximize capacity utilization, optimize staffing, and structure public–private partnerships strategically. Methodologically, integrating game cross-efficiency DEA with CART strengthens accuracy, offering a robust tool for benchmarking and improving private healthcare performance. Full article

The microaxial flow pump (mAFP) is a mechanical circulatory support device designed to directly unload the left ventricle, restore cardiac output, and improve systemic perfusion in the setting of cardiogenic shock (CS). CS is a devastating complication of acute myocardial infarction (AMI) and advanced heart failure, characterized by systemic hypoperfusion and myocardial dysfunction, carrying an in-hospital mortality of 30–50%. However, there has been controversy about whether these theoretical physiological mechanisms behind mAFP translate into actual survival or recovery in this patient population that has historically been difficult to study in prospective trials. The lack of consensus has resulted in differing national guidelines, resource allocation, and clinical decision-making in time-sensitive clinical scenarios. Earlier studies were limited to retrospective analyses and a single small, underpowered randomized trial, none of which showed a mortality benefit. In 2024, the DanGer Shock trial emerged as the first multi-center trial to demonstrate mortality benefit in patients with STEMI complicated by CS treated with Impella CP, albeit at the cost of increased risk of major bleeding, hemolysis, and vascular complications, an effect sustained in the 10 year outcomes published in 2025. In this review, we examine reasons for the differing results of preceding studies and compare how multinational guidelines have reacted to this new evidence. Finally, we provide practical considerations regarding the use, complications, and troubleshooting of this technology, and identify gaps in evidence regarding patient selection and timing of placement. Full article

Background: The Nursing Work Environment (NWE) plays a critical role in determining the quality of care, staff well-being, and organizational performance, particularly in oncology settings. Despite increasing attention, a comprehensive synthesis of organizational factors shaping oncology NWEs has been lacking. This scoping review aimed to describe the key features of oncology NWEs and to explore the outcomes associated with these characteristics. Methods: A scoping review was conducted following the Joanna Briggs Institute guidelines. Peer-reviewed studies published in English or Italian were included without time restrictions. Literature searches were performed in MEDLINE via PubMed, CINAHL, and Scopus between January and April 2025. Results: Twenty studies met the inclusion criteria. Key organizational characteristics of oncology NWEs were grouped into the following four domains: leadership and organizational support; workload and resource availability; ethical climate and collegial relationships; and physical and structural conditions of care settings. Across the studies, a positive NWE was frequently reported to be associated with improved nurse-related outcomes and, to a lesser extent, with patient-related outcomes. However, these associations should be interpreted with caution due to the heterogeneity of contexts and the predominance of cross-sectional designs. Conclusions: The NWE is a strategic element in delivering effective, safe, and sustainable oncology care. Practical actions for nurse managers and healthcare leaders include implementing leadership training programs, ensuring adequate staffing and resource allocation, fostering open communication, and promoting interdisciplinary collaboration. These measures are essential to protect staff well-being and guarantee high-quality, patient-centered care. Full article

As intelligent transportation systems (ITSs) evolve rapidly, the increasing computational demands of connected vehicles call for efficient task offloading. Centralized approaches face challenges in scalability, security, and adaptability to dynamic network conditions. To address these issues, we propose a blockchain-based decentralized task offloading framework with network-aware resource allocation and tokenized economic incentives. In our model, vehicles generate computational tasks that are dynamically mapped to available computing nodes—including vehicle-to-vehicle (V2V) resources, roadside edge servers (RSUs), and cloud data centers—based on a multi-factor score considering computational power, bandwidth, latency, and probabilistic packet loss. A blockchain transaction layer ensures auditable and secure task assignment, while a proof-of-stake (PoS) consensus and smart-contract-driven dynamic pricing jointly incentivize participation and balance workloads to minimize delay. In extensive simulations reflecting realistic ITS dynamics, our approach reduces total completion time by 12.5–24.3%, achieves a task success rate of 84.2–88.5%, improves average resource utilization to 88.9–92.7%, and sustains >480 transactions per second (TPS) with a 10 s block interval, outperforming centralized/cloud-based baselines. These results indicate that integrating blockchain incentives with network-aware offloading yields secure, scalable, and efficient management of computational resources for future ITSs. Full article

Against the backdrop of urban–rural integrated development, special ecological function zones, as spatial carriers with significant regional ecological value and rural development functions, are confronted with a striking conflict between ecological conservation and regional advancement. This contradiction is comprehensively reflected in the interactions among land use functions (LUFs) that differ in nature and intensity. Therefore, exploring the trade-off and synergy (TOS) among regional LUFs is not only of great significance for optimizing territorial spatial patterns and advancing rural revitalization but also provides scientific evidence for the differentiated administration of regional land use. Taking 185 townships in the Funiu Mountain area of China as research units, this study constructs a land use assessment system based on the ‘Production–Living–Ecological’ (PLE) framework, utilizing multi-source datasets from 2000 to 2020. Spearman correlation analysis, geographically weighted regression (GWR), and bivariate local spatial autocorrelation methods are employed to examine the spatio-temporal dynamics of LUFs and the spatial non-stationarity of their TOSs. The findings indicate that, throughout the research period, the production function (PF) displayed a fluctuating declining trend, whereas the living function (LF) and ecological function (EF) demonstrated a fluctuating increasing trend. Notably, EF held an absolute dominant position in the overall structure of LUFs. This is highly consistent with the region’s positioning as a special ecological function zone and also a direct reflection of the effectiveness of continuous ecological construction over the past two decades. Spatially, PF is stronger in southern, eastern, and northern low-altitude townships, correlating with higher levels of economic development; LF is concentrated around townships near county centers; and high EF values are clustered in the central and western areas, showing an opposite spatial pattern to PF and LF. A synergistic relationship is observed between PF and LF, while both PF and LF exhibit trade-offs with EF. The TOSs between different function changes demonstrate significant spatial non-stationarity: linear synergy was the primary type for PF-LF, PF-EF, and LF-EF combinations, but each combination exhibited unique spatial characteristics in terms of non-stationarity. Notably, towns identified as having different types of trade-off relationships in the study of spatial non-stationarity are key areas for township spatial governance and optimization. Through the allocation of regional resources and targeted policy tools, the functional relationships can be adjusted and optimized to attain sustainable land use. Full article