Search Results (41,747)

The paper investigates the design and operation of microgrid arrangements, with a focus on renewable power systems, system architectures, and storage solutions. The research evaluates stochastic and multi-objective optimization methods to show how demand response systems improve operational flexibility. The study evaluates 183 journal articles to select those that address microgrid design in conjunction with optimization models and demand response approaches. The articles are classified into three essential categories, which include microgrid design optimization methods and demand response integration. The review establishes that microgrid performance depends on three fundamental design parameters, which include energy generation systems, storage capabilities, and load demand control mechanisms. The review demonstrates that advanced optimization approaches, such as stochastic and multi-objective optimization methods, offer effective solutions for managing renewable energy variability. The paper demonstrates that demand response strategies are crucial for reducing costs and enhancing system flexibility. However, current published research falls short of establishing an integrated system that combines real-time demand response with stochastic optimization. This integration, while not yet fully realized, is suggested as a critical advancement for ensuring both system performance optimization and long-term sustainability. Therefore, this paper calls for further research to develop resilient hybrid renewable microgrids that integrate flexibility with sustainability through advanced optimization models and demand response strategies. Full article

Background: While many factors contribute to weight regain after bariatric surgery, the role of dietary intake and behaviors remains underexplored in specific populations. This study aims to explore the long-term outcomes of bariatric surgery in Saudi Arabia, focusing on the impact of dietary intake and eating behaviors on weight regain. Methods: A cross-sectional study was conducted using phone interviews to assess the dietary patterns and eating behaviors of 335 participants who underwent bariatric surgery at least three years prior. Data were collected through a structured validated questionnaire covering food consumption and eating habits. Results: Of the 335 participants who completed the survey, 81.8% experienced weight regain, defined as a ≥20% increase from their nadir weight, after bariatric surgery. Several dietary behaviors were associated with weight regain. Higher consumption of pastries (OR = 0.382, p = 0.014), sweets (OR = 0.498, p = 0.036), and moderate bread intake (OR = 0.287, p = 0.038) were associated with lower odds of obesity. Additionally, frequent consumption of traditional dishes such as kabsah (OR = 0.411, p = 0.008) was associated with lower odds of obesity. Conclusions: This study highlights the complexity of dietary patterns in post-bariatric surgery weight management. Although certain foods, such as pastries, sweets, and kabsah, were associated with lower odds of obesity in this sample, the cross-sectional design prevents causal interpretation. These findings should therefore be viewed as exploratory signals, emphasizing the need for cautious interpretation and reinforcing the call for longitudinal, representative studies to clarify the long-term determinants of weight regain and to guide clinical follow-up strategies. Full article

Inland Waterway Transport (IWT) is widely recognised as an energy-efficient freight mode, yet its decarbonisation is increasingly constrained not by propulsion technology, but by the absence of infrastructure capable of delivering clean energy where and when it is needed. This paper presents a structured review of over a decade of academic, policy and technical literature, identifying systemic gaps in current decarbonisation strategies. The analysis shows that most pilot projects are vessel-specific, and poorly scalable, with infrastructure planning rarely based on vessel-level energy demand data, leaving energy provision as an afterthought. Current approaches overemphasise technology readiness while neglecting the complexity of aligning supply chains, operational diversity, and infrastructure deployment. This review reframes IWT decarbonisation as a problem of provision, not propulsion. It calls for demand-led, demand driven, fuel agnostic infrastructure models and proposes a roadmap that integrates technical, operational, and policy considerations. Without rethinking energy access as a core design challenge—on par with vessel systems and regulatory standards—the sector risks investing in stranded assets and missing climate and modal shift targets. Aligning vessel operations with dynamic, scalable energy delivery systems is essential to achieve a commercially viable, fully decarbonised IWT sector. Full article

The necessity to produce new biodegradable polymeric materials, to overcome the economic model, based on the linear economy, and to apply the circular economy model is a global problem. As a result, components unutilized derived from industrial processes are becoming increasingly valuable and useful to create new materials. This work focuses on the production of bioplastics based on poly (vinyl) alcohol (PVA) that have been modified with flavonoid fraction, liquid fraction obtained after digestion with cellulase and pectinase, and the solid material remaining after enzyme treatment, obtained from Citrus bergamia by-product (the so-called “pastazzo”). This last one is an almost completely unutilized product, although it is a potential rich source of biological active compounds. Enzymatic and non-enzymatic green extraction protocol have been employed to separate the different fractions and to make it more suitable to functionalize the PVA, suppling new properties to the bioplastics in a dose-dependent manner. Morpho-functional analysis was conducted by SEM, XRD, colorimetry, UV–visible and ATR-FTIR spectroscopy. Regarding optical properties, the obtained results show that transparency of the film in terms of light transmittance (T%) for PVA alone is very high, but when functionalized it had a reduced T%. From the data obtained, the functionalized films acquire antioxidant activity, as well as good mechanical properties, making them good candidates for biodegradable packaging for preserving the shelf life of different fruits and vegetables as confirmed by the food fresh-keeping test performed on apple samples. Full article

Introduction: Cushing syndrome (CS) is a medical condition resulting from prolonged hypercortisolemia. The most common reason for endogenous CS is ACTH overproduction by pituitary adenoma, and then it is called Cushing disease (CD). The gold standard of CD diagnostic remains bilateral inferior petrosal sinus sampling (BIPSS); nevertheless, non-invasive diagnostic methods are being sought to provide a higher safety profile. The aim of this study was to evaluate whether [¹¹C]C-MET PET/CT can serve as a non-invasive alternative to BIPSS and MRI in CD diagnosis. Methods: This prospective study included 21 patients with CD who underwent BIPSS, MRI of the pituitary, and [¹¹C]C-MET PET/CT. Results: Sensitivity of BIPSS, MRI and [¹¹C]C-MET PET/CT was 100%, 59% and 24%, respectively, while specificity was 100%, 75%, and 13%. Next, we retrospectively compared PET/CT results for patients with corticotrope pituitary adenomas (n = 18) with those for individuals with no pituitary pathology (n = 18), and the results showed significantly higher SUV_max in the study group (3.74 ± 0.90 vs. 1.87 ± 1.17; p < 0.001). In ROC curve analysis, the area under the curve (AUC) was 0.889 (p <0.001; 95% CI 0.784–0.994). For SUV_max 2.60, the calculated sensitivity and specificity were 89% and 78% respectively, and for SUV_max 3.56, sensitivity and specificity were 67% and 89%, respectively. Conclusions: [¹¹C]C-MET PET/CT seems not to be a reliable diagnostic option in the diagnosis of pituitary corticotropic adenomas. BIPSS proved still to be the best diagnostic option for CD. Nevertheless, a higher than normal pituitary accumulation of the radiotracer may suggest the presence of increased amino acid metabolism, thus, the presence of adenoma. Full article

Urban resilience has gained significant further attention since the COVID-19 pandemic, resulting in various assessments comparing cities’ ability to respond to, and recover from, diverse shocks. This paper responds to the call for grounding urban resilience in context by examining a case study of the city regions on the island of Hainan Province, China, following the onset of the COVID-19 outbreak. After content analysis to trace the lineage of urban resilience in the Chinese context, an exploratory study, including analysis and mapping of statistical data, was conducted to examine the city’s economic and social performance from 2018 to 2021 and beyond. Our study suggests a largely positive trend in the bouncing back and forward of city regions shortly after the pandemic began, as well as a rural–urban gap and growing regional disparities that need to be addressed to enhance resilience for all. This study provides a contextualized understanding of Hainan as it navigates pandemic stresses and builds capacities during state-supported structural transformations in its development as a free trade port. Furthermore, this study suggests a valuable city region analytical lens and a geographical perspective for implementing the urban resilience concept and building urban resilience efforts in China and elsewhere. Full article

With the surge in global maritime trade of new energy vehicles (NEVs), the roll-on/roll-off (Ro-Ro) shipping market faces a severe supply–demand imbalance, pushing shipping rates to persistently high levels. To tackle this challenge, NEV manufacturers and other automakers have begun establishing their own Ro-Ro fleets, creating an urgent need for optimized operational scheduling of these proprietary fleets. Against this context, this study focuses on optimizing the operational scheduling of automakers’ self-owned Ro-Ro fleets. Under the premise of deterministic automobile export transportation demands, a mixed-integer programming model is developed to minimize total fleet operational costs, with decision variables covering vessel port call sequence/selection, port loading and unloading quantities, and voyage speeds. A genetic algorithm is designed to solve the model, and the effectiveness of the proposed approach is validated through a real-world case study. The results demonstrate that the optimization method generates clear, actionable scheduling schemes for self-owned Ro-Ro fleets, effectively helping automakers refine their maritime logistics strategies for proprietary fleets. This study contributes to the field by focusing on automaker-owned Ro-Ro fleets and filling the research gap in cargo-owner-centric scheduling, providing a practical tool for automakers’ overseas logistics operations. Full article

Non-contact, automated health monitoring is a cornerstone of modern precision livestock farming, crucial for enhancing animal welfare and productivity. Infrared thermography (IRT) offers a powerful, non-invasive means to assess physiological status. However, its practical use on farms is limited by a key challenge: accurately locating regions of interest (ROIs), like the eyes and face, in the blurry, low-resolution thermal images common in farm settings. To solve this, we developed a new framework called ID-APM, which is designed for robust ROI registration in agriculture. Our method uses a trinocular system and our RAP-CPD algorithm to robustly match features and accurately calculate the target’s 3D position. This 3D information then enables the precise projection of the ROI’s location onto the ambiguous thermal image through inverse disparity estimation, effectively overcoming errors caused by image blur and spectral inconsistencies. Validated on a self-built dataset of farmed sika deer, the ID-APM framework demonstrated exceptional performance. It achieved a remarkable overall accuracy of 96.95% and a Correct Matching Ratio (CMR) of 99.93%. This research provides a robust and automated solution that effectively bypasses the limitations of low-resolution thermal sensors, offering a promising and practical tool for precision health monitoring, early disease detection, and enhanced management of semi-wild farmed animals like sika deer. Full article

This research delves into the central position of digital technology as a stimulator of sustainable economic advancement. This study examines the complementary convergence of policy structures, law, and environmental economics that unleashes this advancement. This research finds and explores converging strategies in tapping digital innovation towards sustainability goals through benchmarking China, the EU, and the USA. This study bridges a gap in the literature since it undertakes a systematic, cross-disciplinary analysis and offers policymakers valuable inputs to craft effective strategies leveraging technology to a prosperous, sustainable world future. The results prove that new technologies enhance environmental law efficacy, transparency, and enforcement. It provides a prospective framework integrating digital solutions into policy and legal design, connecting economic growth with environmental degradation. Imperial methods in the form of qualitative research grounded on literature review, secondary data, green growth sustainable development, circular economy project studies, and smart conurbations to evaluate the efficacy of digital policy machinery indicate that digitally empowered policies significantly enhance resource productivity, maximise environmental taxation and cap-and-trade instruments, and enhance green innovation. This paper concludes with a policy road map for integrating digital to achieve synergistic economic and environmental objectives, calling for a new paradigm in environmental economic policy and law. Full article

Introduction: For pregnant women with a history of fetal and neonatal alloimmune thrombocytopenia (FNAIT) or hemolytic disease of the fetus and newborn (HDFN), prenatal intervention in subsequent pregnancies may be necessary to prevent complications for the fetus. A non-invasive prenatal diagnostic procedure (NIPD) is recommended for fetal blood group genotyping. RT-PCR is used for fetal RHD determination as a reliable screening method with high sensitivity and specificity. For other antigens with variants involving single-base substitutions, droplet digital PCR (ddPCR) and next-generation sequencing (NGS) are recommended to reduce the risk of false-negative results. Only NGS offers the possibility of determining the cell-free fetal DNA (cffDNA) fraction in maternal plasma by sequencing additional gene fragments in parallel, but no standard exists for assay validation. Material and Methods: A custom-made primer panel was designed to target the common platelet and red cell antigens involved in fetal red cell and platelet incompatibilities, as well as additional anonymous single-nucleotide polymorphism (SNP) targets for use as an internal control. Amplicon-based NGS was carried out using semiconductor sequencing. For HPA-1a (HPA*1A, ITGB3) and K (KEL*01.01, KEL) assay validation, the limit of detection (LOD) and limit of quantification (LOQ) were estimated, as were false-positive antithetic alleles, linearity, and inter-assay variation, using cell-free DNA (cfDNA) extracted from the blood samples of healthy blood donors. An additional analysis was performed using 23 diagnostic samples from 21 pregnant women. Results: Regression analysis of dilution series using HPA-1a- and K-positive cell-free plasma samples in antigen-negative donor plasma showed that recovery is definitely feasible up to an HPA*1A and KEL*01.01 allele frequency of 1%. Base calls of false-positive antithetic alleles were detected with a maximum of 0.25% using 21 healthy blood donors. The LOD was estimated to be 0.2057% (mean + 3 SD) for HPA*1A with a LOQ of 0.6298% (mean + 10 SD). For KEL*01.01, the LOD was 0.1706% (mean + 3 SD) and the LOQ was 0.5314% (mean + 10 SD). The analysis of 15 of 21 cases with diagnostic samples from pregnant women with neonatal blood available for confirmatory testing resulted in 100% concordant results. The fetal fraction of these samples was calculated with a median of 11.03% (95% CI: 8.89, 13.20). Conclusions: NGS for non-invasive fetal blood group genotyping is an accurate and reliable method. In-house validation of the used assays can be performed using healthy donors to determine the LOD, LOQ and sensitivity. The threshold for paternally inherited fetal HPA*1A and KEL*01.01 alleles could be set at 1% (i.e., 2% fetal fraction) to obtain reliable test results. Internal controls for assessing the fetal fraction are essential to avoid false-negative test results. Full article

Virtual experiments (VE) can be used to assess the measurement uncertainty of complex measurements. The typical calculation procedure implemented in such a VE, called VE-DA in this paper, is based on a Monte Carlo method involving simulating possible measurement errors and possible measurement data based on extensive modeling of the measurement instrument, followed by applying a data analysis function (DA) to evaluate the measurement data. This procedure is similar to the propagation of distributions using a Monte Carlo method (PoD) procedure presented in the written standard JCGM-101, in which the Monte Carlo method is applied to an explicit mathematical model for the measurand involving simulating and applying possible corrections to the observed measurement data. However, in this paper, we show that the uncertainty provided by the VE-DA procedure can be both larger and smaller than the uncertainty evaluated based on applying the PoD to the correct measurement model, when available. This is important to realize by users of the VE-DA procedure when claiming conformity of an uncertainty evaluation with JCGM-101. Full article

Permafrost degradation, driven by the thawing of ground ice, results in the progressive thinning and eventual loss of the permafrost layer. This process alters hydrological and ecological systems by increasing surface and subsurface water flow, changing vegetation density, and destabilising the ground. The thermal and hydraulic conductivity of permafrost are strongly temperature-dependent, both increasing as the soil warms, thereby accelerating thaw. In addition, thawing permafrost releases large quantities of greenhouse gases, establishing a feedback loop in which global warming both drives and is intensified by permafrost loss. This paper reviews the mechanisms and consequences of permafrost degradation, including reductions in strength and enhanced deformability, which induce landslides and threaten the structural integrity of foundations and critical infrastructure. Permafrost has been investigated and modelled extensively, and various approaches have been devised to address the consequences of thawing permafrost on communities and the built environment. Some techniques focus on keeping the ground frozen via insulation, while others propose local replacement of permafrost with more stable materials. However, given the scale and pace of current changes, systematic remediation appears unfeasible. This calls for increased efforts towards adaptation, informed by interdisciplinary research. Full article

This work presents the development of an intelligent system designed to support the predictive maintenance of the Colombian Navy’s maritime vessels through the estimation of remaining useful life and unsupervised anomaly detection, within the framework of the project called “Colombian Integrated Platform Supervision and Control System” (SISCP-C). This project seeks to guarantee the sustainability of the vessels over time, increase their operational availability, and optimize their life cycle cost, in accordance with the institution’s strategic direction established in the Naval Development Plan 2042. The system provides useful information to the crew, enabling informed decision-making for intelligent and efficient maintenance strategies. To address the limited availability of normal operating data, synthetic data generation techniques with seeding are implemented, including tabular variational autoencoders, conditional tabular generative adversarial networks, and Gaussian copulas. Among these, tabular variational autoencoders achieved the best performance and are used to generate synthetic datasets under normal conditions for the Wärtsilä 6L26 diesel engine (manufactured by Wärtsilä Italia S.p.A., Trieste, Italy). These datasets are used to train several unsupervised anomaly detection models, including one-class support vector machines, classical autoencoders, and long short-term memory-based autoencoders. The long short-term memory autoencoders outperformed the others in terms of detection metrics. Dedicated multivariate long short-term memory autoencoders are subsequently trained for each engine subsystem. By calculating the mean absolute error of the reconstructions, a subsystem-specific health index is computed, which is used to estimate the remaining useful life. Full article

Background: Family caregivers of patients with chronic diseases face high levels of burden, anxiety, and burnout, which may negatively affect both their well-being and patient outcomes. Low-cost, accessible telemedicine approaches may provide practical support in resource-limited settings. Methods: We conducted a prospective, parallel-group controlled study in Timisoara, Romania, between April 2024 and March 2025 and included 161 caregivers of older adults with chronic diseases, allocated 1:1 to receive either structured low-cost telemedicine support (weekly phone calls and SMS reminders; n = 82) or usual care (n = 79). Data were collected at baseline, three months, and six months through structured interviews. The primary outcome was caregiver burden measured by the Zarit Burden Interview (ZBI). Secondary outcomes included caregiver anxiety, burnout, satisfaction, and patient-related outcomes such as emergency room (ER) visits, hospital readmissions, and medication adherence. Analyses were performed using ANCOVA and logistic regression, adjusting for baseline values and relevant covariates. Results: At three months, caregivers in the intervention group had significantly lower burden scores compared to controls (adjusted mean difference −2.9; 95% CI −4.7 to −1.1; p = 0.002). Reductions in anxiety (−1.4; p = 0.02) and burnout (−1.6; p = 0.01) were also observed. These effects persisted at six months, though slightly attenuated. Patient outcomes favored the intervention: ER visits were lower at six months (27.50% vs. 41.02%; aOR 0.55, 95% CI 0.30–0.99; p = 0.047), while medication adherence and readmissions showed consistent but non-significant improvements. No adverse effects were reported. Conclusions: A simple, low-tech telemedicine program reduced caregiver burden, anxiety, and burnout and decreased ER visits. Improvements in medication adherence and readmissions were observed, but did not reach statistical significance. This pragmatic intervention can easily be integrated into primary care follow-up or community-based caregiver support programs, providing an affordable and low-cost technique to promote chronic disease management and caregiver well-being, especially in resource-limited health systems. Full article

The discrete element method (DEM) is widely employed in various fields for analyzing rock and soil movement. However, the traditional DEM involves a large number of calculations, which leads to reduced computational efficiency. Deep-learning presents a promising solution to this issue by utilizing neural networks to approximate DEM calculations. Moreover, the consistency between the arrangement of discrete particles and the structure presented in graph neural networks further reinforces the validity of this approach. In this study, we propose a novel model called Graph-DEM based on graph neural networks, which significantly enhances the speed of DEM calculations. Meanwhile, our model demonstrates the capability of adaptive learning across various constitutive relationships. To evaluate the model’s performance, we measure particle-trajectory prediction accuracy on three scenario datasets (dynamic, static, and principle experiments) and on two public datasets. In addition, the computational efficiency of the Graph-DEM model are compared against the traditional DEM. The experimental results demonstrate the superiority of the model in terms of accuracy, universality, and computational efficiency. Full article