Search Results (9,223)

Truck congestion around international ports poses persistent challenges for safety, efficiency, environmental performance, and accessibility, particularly during container terminal disruptions when long queues of trucks accumulate. Traditional responses often address isolated components of the problem and fail to capture the interdependencies of sociotechnical systems, where multiple actors pursue partly conflicting goals. This study explores the usefulness of combining Sociotechnical Systems (STS) principles with the Systems-Theoretic Accident Model and Processes (STAMP) to analyze such complexity more holistically. Using the case of truck re-routing procedures during terminal closures at the Port of Rotterdam, structured interviews and document analyses were used to apply parallel STS and System-Theoretic Process Analyses (STPA). The STS analysis identified misalignments among procedures, actor intentions, infrastructure, and communication practices, clarifying why diversion protocols often fail in practice. The STPA complemented this diagnosis by modeling control relationships and feedback loops, identifying 92 unsafe control actions and 407 loss scenarios that informed 16 design recommendations. Together, the two approaches demonstrate how sociotechnical and control-theoretic perspectives can be combined to generate both diagnostic and prescriptive insights. The study highlights the potential of a combined STS–STPA framework as a transferable analytical tool for understanding and redesigning complex transport systems. Full article

This study focuses on the knowledge and attitudes of Orthodox clergy in Greece regarding religious psychopathology, which refers to the complex phenomena where religious experiences or beliefs intersect with mental disorders. The sample included 125 clergy members with varying levels of education and pastoral experience. The findings reveal significant gaps in the understanding of basic concepts of religious psychopathology, despite recognition of the need for collaboration with mental health professionals. Formal education proved to be a decisive factor in understanding religious psychopathology, as clergy with higher educational levels demonstrated significantly better knowledge. In contrast, clergy opinions towards mental health issues appeared to be shaped by multiple factors beyond education alone. Experience in collaboration with psychologists or psychiatrists was positively associated with higher knowledge levels and more realistic, positive attitudes toward managing religious psychopathology. Additionally, clergy who had direct experience with cases of religious psychopathology showed greater sensitivity and differentiated perspectives. The study highlights the urgent need to incorporate knowledge of religious psychopathology into theological education in Greece and to strengthen cooperation between the Church and mental health services. Such initiatives can improve pastoral care, reduce the stigma surrounding mental illness, and holistically support members of religious communities Full article

Urban parks provide diverse cultural ecosystem services (CESs), which are crucial for residents’ mental well-being. However, few studies have investigated how urban parks’ CESs and their interactions vary across seasons. In this study, we used the downtown area of Chengdu, China, as a case study, and evaluated urban parks’ CESs based on social media comments and further explored their seasonal dynamics. We then analysed the seasonal trade-offs/synergies of these CESs for service pairs using Pearson correlation and for multiple services using bundle identification. The results show the following: (1) Most CESs except for social interaction had the highest intensities in autumn, and recreational activities and education were the CESs with the highest and lowest intensities among the four seasons, respectively. Education service showed the greatest seasonal variation, while recreational activities and physical and mental recovery were stable among different seasons. (2) Some CES pairs exhibited trade-offs/synergies, but those relationships changed over seasons. Specifically, there were trade-off/synergy relationships between seven CES pairs in spring, three CES pairs in summer and autumn, and four CES pairs in winter. (3) In terms of the trade-offs/synergies among multiple CESs, we identified three types of CES bundles, i.e., physical and mental recovery- and aesthetics-dominated, inspiration- and education-dominated, and social interaction- and recreation-dominated bundles. More than 50% of the urban parks exhibited the physical and mental recovery- and aesthetics-dominated bundle in four seasons, and the seasonal change between this bundle and the social interaction and recreation-dominant bundle was the most obvious among all the bundle changes. This study revealed urban parks’ CES seasonal dynamics and identified the seasonal variations in CES trade-offs/synergies, providing a reference for CES management in urban parks. Full article

Public service media (PSM) are undergoing essential digital transformations to compete in an audiovisual ecosystem dominated by new technological players that have reshaped traditional media consumption habits. This article examines how the digital developments of Spanish public media, within platformization processes, particularly in the field of digital audio and podcasts, integrate public service values based on a framework which identifies twelve key dimensions: universality, quality, independence, diversity, responsibility, innovation, social commitment, civic participation, media literacy, territorial cohesion, social justice, and cooperation. Using a qualitative multiple-case study methodology, these values are compared with the strategies of Radiotelevisión Española (RTVE), the media organizations grouped in the Federation of Regional Radio and Television Entities (FORTA), and Canal Extremadura. The results indicate that PSM, to varying degrees, incorporate public service values in their platformization processes. However, the findings also reveal significant challenges that, if addressed, could maximize the impact of their digital strategies. Full article

Background/Objectives: Central nervous system (CNS) infections remain a significant public health challenge and require rapid and accurate diagnosis to guide clinical management. Although the incidence of bacterial meningitis has declined owing to widespread vaccination, viral etiologies continue to dominate CNS infections. The aim of this study was to assess the epidemiological trends, age distribution, and seasonality of CNS infections using multiplex PCR. Methods: A retrospective analysis was conducted on cerebrospinal fluid (CSF) samples collected between January 2021 and December 2022 from patients with CNS infections at King Abdulaziz Medical City. A BioFire FilmArray Meningitis/Encephalitis (ME) panel was used to detect pathogens. Patient demographics, pathogen distribution, and seasonal trends were analyzed. Results: A total of 2,460 CSF samples were tested, of which 130 (5%) were positive for at least one pathogen. Viral pathogens accounted for 82.3% of the infections, with human herpesvirus-6 (HHV-6) (31%) and enterovirus (EV) (20%) being the most common. Bacterial pathogens represented 17.7% of the cases, with Streptococcus pneumoniae (6%) and Escherichia coli K1 (5%) being the predominant bacterial agents. The highest infection burden was observed in infants aged 0–6 months, with a marked male predominance. Seasonal analysis revealed multiple peaks in viral infections, particularly of HHV-6 and EVs, whereas bacterial infections were sporadic, with Streptococcus agalactiae and Streptococcus pneumoniae peaking in October and November. Conclusions: Viral infections, particularly HHV-6 and EVs, dominated CNS infections, with distinct seasonal and age-related variations. These findings underscore the value of multiplex PCR in improving the rapid diagnosis of CNS infections and aiding in timely treatment and antimicrobial stewardship. Full article

Since it is difficult to obtain the positions of dynamic loads on structures, this paper suggests a new method to identify the locations of dynamic loads step-by-step based on the correlation coefficients of dynamic responses. First, a recognition model for dynamic load position based on a finite-element scheme is established, with the finite-element domain divided into several regions. Second, virtual loads are applied at the central points of these regions, and acceleration responses are calculated at the sensor measurement points. Third, the maximum correlation coefficient between the calculational and measured accelerations is obtained, and the dynamic load is located in the region with the virtual load corresponding to the maximum correlation coefficient. Finally, this region is continuously subdivided with the refined mesh until the dynamic load is pinpointed in a sufficiently small area. Different virtual load construction methods are proposed according to different types of loads. The frequency response function, unresolvable for the actual problem due to the unknown location of the real dynamic load, can be transformed into a solvable form, involving only known points. This transformation simplifies the analytical process, making it more efficient and applicable to analysis of the dynamic behavior of the system. The identification of the dynamic load position in the entire structure is then transformed into a sub-region approach, focusing on the area where the dynamic load acts. Simulations for case studies are conducted to demonstrate that the proposed method can effectively identify positions of single and multiple dynamic loads. The correctness of the theory and simulation model is verified with experiments. Compared to recent methods that use machine learning and neural networks to identify positions of dynamic loads, the approach proposed in this paper avoids the heavy computational cost and time required for data training. Full article

As a critical component of China’s major infrastructure, the quality and safety of hydraulic engineering projects are directly linked to national economic security. Therefore, research on construction quality management of hydraulic concrete is of great importance. Traditional quality gain–loss functions often fail to fully capture the correlations among multiple quality characteristics, the varying weights of these characteristics in overall quality performance, and the presence of multiple influencing factors. To address these limitations, this study employs Gaussian process regression to construct a multivariate and multidimensional quality gain–loss function model. The signal-to-noise ratio is used to represent the interactions among different quality characteristics, while a gain–loss cost matrix is introduced to account for the contribution of each characteristic to the overall function. A case study on summer dam concrete construction is presented to demonstrate the applicability of the proposed model. The results show that the gain–loss values range from a minimum of 1.09 to a maximum of 11.7, which are significantly lower than those obtained using the dimensionless standardized multivariate quality gain–loss function developed by Artiles-León, thereby validating the effectiveness and rationality of the proposed approach. Full article

Objectives: The purpose of this study was to analyze the effect of daily intake of cladribine tablets on the course of multiple sclerosis (MS) while monitoring for 1–4 years during and after the course in several neurological clinics from different regions of the Russian Federation. Materials and Methods: Information was collected on 235 patients from 12 neurological clinics and regional centers for MS, who were observed for an average of 3.4 years after starting treatment with cladribine. Results: An independent analysis of cases of prescription of cladribine in tablets showed that the reason for prescription of cladribine was highly active MS (HAMS) in 159 patients (67.7%), rapidly progressive MS (RPMS) in 20 patients (8.5%), active remitting MS in 50 patients (21.3%) and secondary progressive MS (SPMS) with exacerbations in 6 (2.5%). Among them, only 12 patients (5.1%) had not previously received DMTs, i.e., in these cases, the drug was prescribed as the first DMT. In total, 22 patients had previously received natalizumab, 5—ocrelizumab, and in 1 case—fingolimod. The remaining 207 patients were crossed over from the first-line DMTs. In all cases, there was a decrease in the frequency of exacerbations during and after the completion of the course of cladribine. Exacerbations between the first and second courses of cladribine were noted in 36 patients (15.3% of all treated), almost half of the cases—those who previously received natalizumab (17 exacerbations, or 47.2% of all exacerbations between the 1st and 2nd courses of cladribine), and in 3 cases—from ocrelizumab (in 60% of all patients crossed over from ocrelizumab). During 4 years of follow-up after a full course of cladribine, exacerbations were in 14 patients (6% of all patients included in the analysis), of which in 6 cases—after crossover from natalizumab. Discussion and Conclusions: The data obtained are generally consistent with the results of meta-analyses and reviews published recently, but high probability of exacerbations in patients who were crossed over from second-line drugs such as natalizumab and ocrelizumab were seen. The crossover from natalizumab is carried out more often due to the increased risk of developing progressive multifocal encephalopathy (PML). It is likely that the restoration of MS activity after the withdrawal of natalizumab is quite frequent, cladribine tablets were not able to fully prevent this. Such a crossover does not seem to be optimal, unlike the crossover from first-line DMTs. If such a crossover is still planned, it could be performed within 4 weeks after stopping natalizumab. Full article

Amidst global climate warming and increasingly severe food security challenges, the agroforestry economy, a green ecological industry that balances ecological conservation and economic development, has attracted widespread attention. This study constructs a theoretical analytical framework based on the diamond model to systematically identify key factors influencing the development of the agroforestry economy. Using 56 practical cases from the agroforestry economy in China as samples, the study applies Necessary Condition Analysis (NCA) and fuzzy-set Qualitative Comparative Analysis (fsQCA) to further explore the multiple driving paths of agroforestry economic development and their supporting elements. The research findings show that (1) forest resources, technological innovation, market demand, enterprise forms, related industries, and government support do not constitute necessary conditions for the development of the agroforestry economy. The path to the development of the agroforestry economy exhibits complex and concurrent multi-faceted characteristics. (2) Technological innovation has always been at the core of all configurations, and strengthening technological innovation plays a universal role in enhancing the level of agroforestry economic development. The role of government support in the process of the development of the agroforestry economy is limited. (3) The system identified four driving paths, including the endogenous type, characterized by resource technology enterprises; the collaborative type, characterized by a resource technology market with light promotion by the government; the external expansion type, characterized by market technology enterprises; and the linkage type, characterized by market technology enterprises assisted by related industries. The consistency level of the overall solution reached 0.91, and the coverage was 0.54. It reveals the different driving mechanisms with different combinations of elements for the development of the agroforestry economy. Therefore, each region should strengthen scientific and technological research, innovation, and the transformation and application of research outcomes. It should promote the coordinated development of diverse factors, establish tailored regional development models, and explore suitable pathways for developing the agroforestry economy based on its unique resource endowments. Full article

The transition to sustainable energy systems is essential for attaining global carbon neutrality targets. Demand-side flexibility for carbon mitigation is investigated, and a low-carbon operational strategy tailored for industrial park energy systems is proposed. Demand response (DR) is classified into price-based and alternative categories, with respective models developed utilizing a price elasticity matrix and accounting for electricity-to-heat conversion. Integrated energy system (IES) involvement in the carbon trading market is incorporated through a stepped carbon pricing mechanism to regulate emissions. A mixed-integer linear programming model is constructed to characterize IES operations under ladder-type carbon pricing and DR frameworks. The model is resolved via the off-the-shelf commercial solver, facilitating effective optimization of dispatch over multiple time intervals and complex market interactions. Case study findings indicate that implementing stepped carbon pricing alongside DR strategies yields a 44.45% reduction in carbon emission costs, a 9.85% decrease in actual carbon emissions, and a 10.62% reduction in total system costs. These results offer a viable approach toward sustainable development of IES, achieving coordinated improvements in economic efficiency and low-carbon performance. Full article

Objectives: To evaluate perioperative outcomes, renal function preservation, and short-term oncologic results of off-clamp, sutureless, or selectively sutured robotic-assisted partial nephrectomy (RAPN) in patients with renal tumors treated at multiple high-volume centers. Methods: This multicenter retrospective study included 250 patients who underwent off-clamp, sutureless/selectively sutured RAPN between January 2018 and December 2024. Patients with solitary kidneys, tumors > 7 cm, or prior renal surgery were excluded. All procedures were performed without renal artery clamping, using hemostatic agents and selective suturing when necessary. Perioperative, functional, and oncologic outcomes were compared with 313 patients who underwent standard RAPN with parenchymal suturing. Results: The median operative time was 110 min (IQR 100–140), and the median estimated blood loss was 180 mL (IQR 100–250). The overall complication rate was 8.4%, predominantly Clavien–Dindo grade I–II, with no conversions to open surgery. The median decline in estimated glomerular filtration rate (eGFR) at three months was 5.5% (IQR 3.5–8.9; p = 0.56), and no cases of acute kidney injury were recorded. The positive surgical margin rate was 3.7%, and no tumor recurrences were observed during the 12-month follow-up period. Conclusions: Off-clamp, sutureless or selectively sutured robotic-assisted partial nephrectomy (RAPN) was not associated with increased perioperative risk, renal functional decline, or compromised short-term oncologic control compared with conventional sutured RAPN. These findings indicate that the technique is feasible and safe in appropriately selected patients, although prospective studies with longer follow-up are needed to confirm long-term outcomes and refine patient selection criteria. Full article

Background: Primary central nervous lymphoma (PCNSL) is a rare, aggressive, non-Hodgkin’s lymphoma. Outcomes are poor with standard induction of high-dose methotrexate (HD-MTX)-based regimens and consolidation. We present retrospective data from the Georgia Cancer Center. Methods: A single retrospective chart review was conducted on all PCNSL patients from 2013 to 2023 to assess for various factors influencing care. Results: Of a total of 38 PCNSL patients, 6 died and 2 were lost to follow-up prior to therapy initiation, leading to a total of 30 patients for analysis. The median age was 62.3 (21–82 years). One patient had HIV/AIDS. Two patients were on immunosuppression for either kidney transplant or multiple sclerosis (MS). The HIV and MS cases were Epstein-Barr Virus (EBV)-positive. Completion of ≥six cycles of induction was predictive of response. Conclusions: PCNSL remains an area of high unmet need. Recent studies have shown that HD-MTX-based therapy and autologous stem cell transplantation afterwards leads to improved outcomes regardless of age; however, non-relapse mortality is important to consider. Our data from a primarily elderly and sub-rural cohort reiterate the efficacy of combination chemoimmunotherapy and impact of induction cycle number on response, regardless of age. A multidisciplinary approach and targeted agent maintenance should be considered to improve outcomes in the elderly. Full article

Hospitals are complex systems that function most effectively when operations are coordinated and supported by real-time information and feedback loops. Sustained growth, quality improvement, and financial viability increasingly rely on data-based management (DBM), yet adoption and use vary widely across healthcare institutions. This study examined the enabling and hindering factors influencing DBM, with the aim of generating insights to strengthen data use and improve management of eye hospitals. A qualitative multiple case study design was employed in six purposefully selected eye hospitals in India, varying in size and baseline capacity for DBM. At each site, five to six key personnel were interviewed. Data collection involved audio-recorded interviews, transcripts, and field notes, and analysis followed a grounded theory approach using open and axial coding to identify themes, relationships, and develop a conceptual framework. Findings reaffirmed the core enablers—leadership commitment, data availability, and technology adoption. Additional drivers included operational adaptability, regulatory demands, systematic improvement practices, daily reporting, information policies, and the use of communication platforms such as WhatsApp. Key barriers were incomplete data entry, software limitations, inadequate analytical reporting, and inconsistent adherence to processes. Overall, effective DBM requires both foundational enablers and contextual drivers, while addressing barriers to institutionalizing data use and improving outcomes. Full article

The management of waste has become increasingly complex due to the growing volume and diversity of waste generated by modern societies. Effective collection systems are essential for mitigating environmental impacts and promoting sustainability. However, the increasing complexity of waste management requires a comprehensive approach that considers multiple criteria in order to evaluate the performance of these systems. This study evaluates the environmental performance of waste collection systems by comparing various methods using the Analytic Hierarchy Process (AHP). The research involves identifying key performance indicators (KPIs) that could be relevant for all the stakeholders involved and important for environmental sustainability. These KPIs are then used as criteria for the AHP model, allowing for a detailed comparison of each collection method. Data is collected from a case study in the Friuli-Venezia Giulia region in Italy. The preliminary results indicate significant variations in environmental performance and user fruitfulness across different collection methods. Door-to-door collection was found to be the preferred methodology with an absolute weight of 0.527. The AHP framework proves to be a robust tool for integrating diverse criteria and stakeholder preferences, facilitating informed decision-making in waste management. Moreover, it underscores the importance of adopting a holistic approach to evaluate and improve recycling systems. By leveraging AHP, policymakers and waste management professionals can identify optimal strategies that align with environmental sustainability goals. Full article

Under the influence of global climate change, extreme weather events have become more frequent, and earth and rockfill dams often encounter unconventional working conditions such as sudden changes in reservoir water levels during operation. These abrupt changes are characterized by their strong suddenness and rapid rate of change, which can be challenging for traditional numerical analysis methods due to slow modeling and time-consuming calculations, presenting certain limitations. Therefore, an approach has been developed that integrates seepage monitoring data into the failure probability analysis and early warning methods for earth and rockfill dams. Based on the model’s prediction results, dynamic safety warning indicators for the effect of single measurement points on earth and rockfill dams under sudden reservoir water level changes have been quantitatively designed. A risk probability function reflecting the relationship between the residuals of seepage monitoring effects and the risk rate has been constructed to calculate the risk rate of single measurement points for dam seepage effects. By employing the Copula function, which considers the differences and correlations in monitoring effect amounts across different parts of the dam, the single-point seepage risk rates are elevated to a multi-point seepage risk rate analysis. This enables the quantification of the overall seepage risk rate of dams under sudden reservoir water level changes. Case study results show that the safety model has high prediction accuracy. The joint risk rate of the dam based on the Copula function can simultaneously consider spatial correlations and individual differences among multiple measurement points, effectively reducing the interference of randomness in the calculation of single-point risk rates. This method successfully achieves the dynamic transformation of actual seepage effect measurements into risk rates, providing a theoretical basis and technical support for the operational management and safety monitoring of earth and rockfill dams during emergency events. Full article