Search Results (2,737)

The increasing adoption of electric delivery fleets introduces significant challenges related to uneven energy utilization and suboptimal scheduling efficiency. Vehicle-to-Vehicle (V2V) energy sharing presents a promising solution, but its effectiveness critically depends on precise matching and co-optimization within dynamic urban traffic environments. This paper proposes a hierarchical optimization framework to minimize total fleet operational costs, incorporating a comprehensive analysis that includes battery degradation. The core innovation of the framework lies in coupling high-level path planning with low-level real-time speed control. First, a high-fidelity energy consumption surrogate model is constructed through model predictive control simulations, incorporating vehicle dynamics and signal phase and timing information. Second, the spatiotemporal longest common subsequence algorithm is employed to match the spatio-temporal trajectories of energy-provider and energy-consumer vehicles. A battery aging model is integrated to quantify the long-term costs associated with different operational strategies. Finally, a multi-objective particle swarm optimization algorithm, integrated with MPC, co-optimizes the rendezvous paths and speed profiles. In a case study based on a logistics network, simulation results demonstrate that, compared to the conventional station-based charging mode, the proposed V2V framework reduces total fleet operational costs by a net 12.5% and total energy consumption by 17.4% while increasing the energy utilization efficiency of EV-Ps by 21.4%. This net saving is achieved even though the V2V strategy incurs a marginal increase in battery aging costs, which is overwhelmingly offset by substantial savings in logistical efficiency. This study provides an efficient and economical solution for the dynamic energy management of electric fleets under realistic traffic conditions, contributing to a more sustainable and resilient urban logistics ecosystem. Full article

Background/Objectives: The aim of this study was to evaluate fluid administration and intraoperative bleeding of patients who had major hepatic resection. We used artery pulse contour analysis monitor (ProAQT™) and personalized hemodynamic target-guided therapy, in which the administration of fluid, inotropes and vasopressors is guided by stroke volume, pulse pressure variation (SVV, PPV) and continuous cardiac index (CI). Methods: This trial was a prospective, randomized, parallel-group in adults scheduled for major hepatic resection. Participants were randomly assigned in equal numbers to one of two groups: (1) a control group receiving conventional perioperative care, and (2) an intervention group managed with goal-directed hemodynamic therapy guided by radial artery pulse contour analysis. Results: 45 patients were randomized to the GDHT (n = 16) and control group (n = 19). Blood loss was significantly higher in the control group than in GDHT group (728.13 ± 618.59 versus 292.63 ± 274.06, p = 0.009). The number of patients receiving intraoperative transfusion was significantly higher in the first group (6 ± 16 versus 0 ± 19, p = 0.005). Total volume infused was significantly higher in control group (CG) than in GDHT group (GG) (2853.13 ± 1432.18 versus 1125.79 ± 751.2, p = 0.001). Conclusions: Personalized goal-directed therapy optimizes intraoperative fluid administration during major liver resection and reduces blood transfusion. Full article

Background/Objectives: Engaging in regular physical activity (PA) and reducing sedentary behaviors benefits youth health, especially for those with disabilities. However, two-thirds of European children remain insufficiently active. In schools, Active Breaks, brief 5–15 min PA sessions led by teachers during or between lessons, offer a feasible strategy to increase movement. This study investigated teachers’ perceptions of ABs by comparing implementers and non-implementers, examining facilitators and barriers to implementation, and exploring their potential to support the inclusion of students with disabilities. Methods: An observational cross-sectional study was conducted among primary and secondary school teachers in the Emilia-Romagna region (Italy), all of whom had completed a 6 h training course on the implementation of ABs. Data were collected using an ad hoc questionnaire consisting of four sections: sociodemographic data, an adapted Attitudes Toward Physical Activity scale, ABs’ practicality/sustainability, and inclusiveness. Results: Overall, 65% of teachers reported implementing ABs, with higher adoption in primary (69.5%) than secondary schools (58.6%). Implementers reported more positive perceptions and attitudes across individual, classroom, and school-support domains (p < 0.05). In addition, primary teachers consistently scored higher than their secondary counterparts, particularly in terms of class characteristics and benefit perceptions (p < 0.001). Most teachers, especially in primary schools (84.2%), reported no difficulties, although one-third of secondary teachers reported challenges. Exploratory factor analysis on barrier items identified two dimensions (practical/logistical feasibility; institutional/procedural difficulties), but internal consistency was low. Teachers mainly reported using motor activities, with sessions lasting 5–10 min, typically scheduled mid-morning. Inclusion analysis revealed that 60% of teachers had students with disabilities in their classes. While most students participated without adjustments, 25% required occasional or consistent modifications. Conclusions: ABs are a practical and inclusive strategy to reduce SBs in schools. However, not all teachers are currently able to implement them, due to varying contextual constraints, levels of support, and perceived barriers. Primary school settings appear more conducive to their integration, whereas secondary schools may require more tailored support. Fostering teacher confidence, peer collaboration, and inclusive planning can enhance both the implementation and long-term sustainability of educational initiatives. Full article

In recent years, with the development of the electricity market, electricity users have also been able to participate in electricity trading. The energy storage capacity configuration of microgrids with renewable energy considering demand response is of great significance for reducing microgrid costs, improving renewable energy consumption levels, and enhancing microgrid performance. This study first establishes a microgrid model considering demand response. Constraints and economic models of the microgrid are then provided to obtain the cost of the microgrid. To identify the energy storage capacity and the energy scheduling strategy that minimizes the operation cost of the microgrid, this study proposes a two-layer optimization model. The inner layer uses solvers to optimize the transferable loads, interruptible loads, and the energy storage power under the demand response mechanism to minimize the short-term cost. The outer layer uses the particle swarm optimization (PSO) algorithm to optimize the energy storage capacity and minimize the long-term cost. A case analysis shows that the demand response mechanism and reasonable energy storage configuration have a significant effect on reducing the operation cost of the microgrid. In addition, energy storage can reduce power fluctuations in connecting lines and improve the stability of the microgrid. Full article

This study evaluated the acute toxicity of the hydroethanolic extract and the butanolic fraction of Piper marginatum Jacq., following the OECD Guideline 423. Oral and intraperitoneal exposure of CD-1 mice was used in single-dose and repeated-dose schedules. No mortality or significant behavioral alterations were observed. Body weight remained stable during treatment, and histopathological analysis revealed only mild to moderate alterations, mainly in the liver, kidneys, and lungs. These results indicate the absence of acute systemic toxicity under the conditions evaluated. Preliminary phytochemical analysis and metabolomic profile analysis by LC-QTOF/MS revealed a diverse composition of secondary metabolites, including alkaloids, flavonoids, phenylpropanoids, and sphingolipids. Compounds with known biological activity and some with potential toxicity were identified. The findings support the safe use of Piper marginatum extracts in short-term applications and suggest further subchronic toxicity studies and mechanistic evaluation. This research provides fundamental data for preclinical characterization and standardization of extracts of plant origin. Full article

Background: The hepatitis A virus (HAV) is a major cause of acute viral hepatitis and a significant global health concern. This study provides a pre-vaccination baseline for Oman, enabling longitudinal comparison with post-hepatitis A vaccination cohorts. This study aimed to determine the pre-vaccination seroprevalence of HAV antibodies (anti-HAV) in Oman and explore the associated demographic factors. Methods: A cross-sectional study was conducted from April 2014 to August 2015 among patients attending the medical outpatient clinic of the Medical City Hospital for Military and Security Services. Demographic data were collected via a structured questionnaire, and serum samples were tested for anti-HAV immunoglobulin IgG and IgM using enzyme-linked immunosorbent assays. Multivariate analysis was performed to identify the predictors of anti-HAV seroprevalence. Results: Among 1975 participants, 88.1% were positive for anti-HAV IgG. The mean age was 37.4 ± 16.1 years; however, those negative for anti-HAV IgG were considerably younger (mean age: 24.8 ± 15.7 years). Anti-HAV IgG seroprevalence was 37% in individuals aged ≤18 years and 91% in those >18 years (p < 0.001). The factors associated with seropositivity included older age (p < 0.001), consuming food prepared outside the home (p < 0.001), occupation (p < 0.001), and education level (p = 0.003). In the multivariable analysis, only age showed a strong independent association with serostatus: per 10-year increase, the aOR for anti-HAV IgG seropositivity was 2.87 (95% CI 2.25–3.63; p < 0.001). Conclusions: Our study estimates show high anti-HAV IgG seroprevalence and serve as a pre-vaccination baseline for evaluating the hepatitis A vaccination program in Oman over time. Given the lower natural exposure among younger cohorts, continued routine vaccination, scheduled serosurveys, and strengthened surveillance are required to identify emerging immunity gaps and prevent future HAV outbreaks. Full article

Background/Objectives: Monitoring human papillomavirus (HPV) vaccine coverage worldwide can provide valuable insight into cervical cancer prevention. The aim of this manuscript was to assess the HPV vaccination coverage among the primary target cohort (9–14-year-old girls) in the world from 2010 to 2024. Methods: A descriptive epidemiological study (with an ecological study design) was carried out. Trends in HPV vaccination coverage were examined using the joinpoint regression analysis. Results: The HPV vaccination was introduced into the national schedule of 147 countries in 2024. Globally, coverage with the first dose of the HPV vaccine in the primary target cohort (9–14-year-old girls) was estimated at 56.9% in 2024. The growth trend in HPV vaccination coverage was significant mainly in the most developed countries (e.g., such as the USA, Canada and Germany), while trends were 10 times faster in other countries such as Armenia, Indonesia and Tanzania. A decline in trends of HPV vaccination coverage was significant in some developing countries (e.g., such as Panama, Sri Lanka, and Suriname) and in one of the most developed countries—the United Kingdom. Conclusions: A better understanding of changes in HPV vaccination coverage worldwide and further efforts to improve coverage to the target of 90% may contribute to more effective disease prevention. Full article

At the international level, new measures, policies, and technologies are being developed to reduce greenhouse gas emissions and, more broadly, air pollutants. Road transportation is one of the main contributors to such emissions, as vehicles are extensively used in logistics operations, and many fleet owners of fossil-fueled trucks are adopting new technologies such as electric, hybrid, and hydrogen-based vehicles. This paper addresses the Hybrid Fleet Capacitated Vehicle Routing Problem with Time Windows (HF-CVRPTW), with the objectives of minimizing costs and mitigating environmental impacts. A mixed-integer linear programming model is developed, incorporating split deliveries, scheduled arrival times at stores, and a carbon cap-and-trade mechanism. The model is tested on a real case study provided by Decathlon, evaluating the performance of internal combustion engine (ICE), electric (EV), and hydrogen fuel cell (HV) vehicles. Results show that when considering economic and emission trading costs, the optimal fleet deployment priority is to use ICE vehicles first, followed by EVs and then HVs, but considering only total emissions, the result is the reverse. Further analysis explores the conditions under which alternative fuel, electricity, or hydrogen prices can achieve competitiveness, and a further analysis investigates the impact of different electricity generation and hydrogen production pathways on overall indirect emissions. Full article

Due to the complexity of shipyards’ operating scenes and the inconsistency of ship parts’ type and size, current sorting operations for ship parts mainly rely on laborers, resulting in weak control over the production process and key nodes. With the gradual advancement of intelligent manufacturing technology in the shipbuilding process, the trend of machines replacing humans is obvious. In order to promote the automation of the sorting process, intelligent scene recognition and route planning algorithms are needed. In this work, we introduce a localization method based on a laser line profile sensor and ship parts layout analysis algorithm, aiming at obtaining the information needed for sorting route planning. In addition, a heuristic-based route planning algorithm is proposed to solve the built mathematical model of the ship part sorting process. The proposed method can optimize the sorting order of parts, realize stable stacking, shorten sorting distance (taking about 490 m for 43 parts), and thereby improve operation efficiency. These results show that the proposed approach can make intelligent and comprehensible sorting route planning for the ship parts layout. Full article

The construction industry significantly impacts environmental degradation, making sustainable practices like green building construction projects (GBCPs) essential. Although GBCPs offer substantial benefits, they also come with unique risks related to their sustainable nature and common construction challenges. Research on GBCP risks is often fragmented, lacks proper classification, and misses a global perspective, with insufficient focus on empirical assessment and risk mitigation strategies. This study addresses these gaps by systematically identifying risks associated with GBCPs, empirically assessing them using data from global experts, and proposing mitigation strategies. Utilising reliability tests, descriptive statistics, one-sample t-tests, hypothesis testing, and correlation analysis, 42 risk factors were determined and assigned to nine groups: legal and regulatory, technical, financial, material-related, design, schedule and planning, communication and awareness, performance and operational, and environmental. Green product certification and re-evaluation charges, client finance difficulties, the high cost of green materials and equipment, the absence of qualified project teams, and additional expenditures for green building design and construction are the top five concerns. The study also identifies 45 mitigation strategies, enhancing understanding of GBCP risks and guiding stakeholders in effective risk management and sustainable construction practices. Full article

This paper addresses the trajectory tracking control problem of Autonomous Underwater Vehicles (AUVs). A comprehensive mathematical model is first established based on Newtonian mechanics, incorporating both kinematic and dynamic equations. By reasonably neglecting the minor influence of roll motion, a five-degree-of-freedom (5-DOF) underactuated AUV model is derived. Considering the strong nonlinearities, high coupling, and time-varying hydrodynamic parameters typical of underwater environments, a fuzzy adaptive PID controller is proposed. This controller combines the adaptability of fuzzy logic with the structural simplicity and reliability of PID control, making it well-suited to the demanding requirements of AUV motion control. Extensive simulation experiments are conducted to evaluate the controller’s performance under various operating conditions. The results show that the fuzzy adaptive PID controller significantly outperforms conventional PID and standalone fuzzy logic controllers in terms of convergence speed and oscillation suppression. Furthermore, a theoretical stability analysis is provided to ensure that the proposed control system remains stable under time-varying fuzzy gain scheduling, confirming its effectiveness and potential for practical application in underwater vehicle control. Full article

This study addresses the systematic optimization of Low-Rank Adaptation (LoRA) parameters for architectural knowledge integration in diffusion models, where existing AI research has provided limited guidance for establishing plausible parameter ranges in architectural massing applications. While diffusion models show increasing utilization in architectural design, general models lack domain-specific architectural knowledge, and previous studies have offered insufficient hyperparameter optimization frameworks for architectural massing studies—fundamental components for expressing architectural knowledge. This research establishes a comprehensive LoRA training framework specifically for architectural mass generation, systematically evaluating caption detail levels, optimizers, learning rates, schedulers, batch sizes, and training steps. Through analysis of 220 architectural mass images representing spatial transformation operations, the study recommends the following parameter settings: detailed captions, Adafactor optimizer, learning rate 0.0003, constant scheduler, and batch size 4, achieving significant improvements in prompt-to-output fidelity compared to baseline approaches. The contribution of this study is not in introducing a new algorithm, but in providing a systematic application of LoRA in the architectural domain, serving as a bridging milestone for both emerging architectural-AI researchers and advanced scholars. The findings provide practical guidelines for integrating AI technologies into architectural design workflows, while demonstrating how systematic parameter optimization can enhance the learning of architectural knowledge and support architects in early-stage massing and design decision-making. Full article

In the pursuit of sustainable development, optimizing water resources management while maintaining ecological balance is crucial. This study introduces a Chaos-enhanced Harris Hawks Optimizer (CEHHO) aimed at optimizing natural flow patterns in cascade reservoirs. First, an ecological scheduling model considering ensuring guaranteed output is established based on the similarity of ecological flows. Subsequently, the CEHHO algorithm is proposed, which uses tilted skew chaos mapping for population initialization, improving the quality of the initial population. In the exploration phase, an adaptive strategy enhances the efficiency of group search algorithms, enabling effective navigation of the complex solution space. A random difference mutation strategy, combined with the Q-learning algorithm, mitigates premature convergence and maintains algorithmic diversity. Comparative analysis with the existing technology under different typical hydrological frequency shows that the search accuracy and convergence efficiency of the proposed method are significantly improved. Under the guaranteed output limit of 1000 MW, the proposed method enhances the optimal, median, mean, and worst values by 293.92, 493.23, 422.14, and 381.15, respectively, compared to the HHO. Furthermore, the results of the multi-purpose guaranteed output scenario highlight the superior detection and exploitation capabilities of this algorithm. These findings highlight the great potential of the proposed method for practical engineering applications, providing a reliable tool for optimizing water resources management while maintaining ecological balance. Full article

Background: Appropriate medication management before surgery is essential to minimise perioperative risk. Patient adherence to preoperative medication advice demonstrates considerable variability and is influenced by multiple interacting factors. This study assessed patient understanding and adherence to preoperative medication advice provided in the Pre-Admission Clinic (PAC) and identified factors contributing to non-adherence. Methods: A cross-sectional survey study was conducted over 12 weeks in 2022 at a tertiary hospital. Adult patients scheduled for elective surgery who received preoperative medication advice in PAC were surveyed on the day of surgery. Data collected included demographics, clinical characteristics, adherence, reasons for non-adherence, and communication preferences. Descriptive and inferential statistics were used for analysis. Results: Of 156 participants, 91 (58.3%) adhered to medication advice, while 65 (41.7%) did not. Common reasons for non-adherence included forgotten advice (35.4%), misunderstood advice (33.8%), and intentional deviation due to surgery (18.5%). Non-adherence rates were highest for NSAIDs (50.0%) and P2Y12 inhibitors (45.5%). Two surgeries were cancelled due to the delayed cessation of anticoagulants. Non-adherence was significantly associated with a greater number of medications requiring perioperative management (p = 0.004) and a longer duration between PAC and surgery (p = 0.010). Most non-adherent patients (64.7%) preferred a combination of verbal and written advice. Conclusions: A substantial proportion of patients were non-adherent to preoperative medication advice, often due to unclear communication or a lack of understanding of the clinical rationale for the advice. Multimodal strategies, including written or digital reinforcement of verbal advice, multidisciplinary collaboration, and patient-centred education, may improve adherence and reduce preventable cancellations. Future studies should evaluate the impact of these interventions. Full article

Background: Degenerative lumbar spine disease is a prevalent cause of chronic low back pain that significantly impairs daily function and quality of life. While conservative management is the first line of treatment, many patients ultimately require instrumented lumbar spine surgery. However, postoperative outcomes vary considerably, with emerging evidence suggesting that preoperative psychological factors such as anxiety, depression, and pain catastrophizing may influence recovery. The SAP-LD (Scale for Anxiety and Pain in Lumbar Degeneration) study was designed to assess the prognostic role of these psychological and physical parameters in surgical outcomes. Methods: This prospective observational study enrolled 70 adult patients with degenerative lumbar spine pathology scheduled for instrumented surgical treatment at the University of Brescia and ASST Spedali Civili di Brescia between March and December 2024. Preoperative assessments included demographic, clinical, and radiologic data along with validated scales: the Oswestry Disability Index (ODI), 36-Item Short Form Health Survey (SF-36), Visual Analogue Scale (VAS), Pain Catastrophizing Scale (PCS), and Hospital Anxiety and Depression Scale (HADS). Follow-up evaluations were performed at 45 days and at 6 months, and statistical analyses were conducted using correlation tests, ANOVA, and regression modeling. Results: The demographic analysis of the 70 enrolled patients shows a balanced gender distribution (38 females, 34 males) with a mean age of 61 years (range 23–81). The educational level distribution indicates that the majority of patients (44.29%) have a secondary education level, while 35.71% have a tertiary education level. Regarding employment status, 50% of the patients are retired or not working. Patients with clinically significant anxiety and/or depression showed higher levels of perceived pain, pain catastrophizing, and disability at baseline. These patients reported significantly worse scores on the Visual Analogue Scale (VAS), Pain Catastrophizing Scale (PCS), and Oswestry Disability Index (ODI). The Oswestry Disability Index (ODI) demonstrates a clinically significant improvement (reduction) in disability between the preoperative period (t0) and the 45-day follow-up (t2), with the median decreasing from 39.00 to 13.00. However, there is a partial regression at the 6-month follow-up (t3), with the median increasing to 27.00. For the SF-36 Health Survey, the General Health subscale shows an improvement between t0 and t2 (median increasing from 55.00 to 60.00), followed by a slight decrease at t3 (median 55.00). Similar patterns are observed in most other subscales, with initial improvement followed by partial regression. The Pain Catastrophizing Scale (PCS) shows a substantial reduction in catastrophizing between t0 and t2 (median decreasing from 16.00 to 3.00), followed by an increase at t3 (median 11.00), though still below baseline levels. Pain intensity as measured by the Visual Analogue Scale (VAS) shows a significant reduction at t2 (median decreasing from 5.00 to 3.00), but increases again at t3 (median 6.00), even exceeding the preoperative level. For the Hospital Anxiety and Depression Scale (HADS), no significant differences were observed across time points, with values indicating mild symptoms throughout the study period. Correlation analyses confirmed that higher preoperative anxiety and depression scores were predictive of poorer postoperative outcomes. Specifically, higher HADS scores at baseline are associated with higher ODI scores (increased disability) at all time points (p = 0.002), higher VAS scores (increased pain) at all time points (p = 0.015), and lower scores on SF-36 subscales, particularly Emotional Well-being (p = 0.00023) and Social Functioning (p = 0.002). Higher PCS scores at baseline are associated with higher ODI scores at all time points (p = 0.001), higher VAS scores at all time points (p = 0.008), and lower scores on SF-36 subscales, particularly Pain (p = 0.00023) and Physical Functioning (p = 0.04254). The mixed linear models analysis confirms these findings, showing that the ODI score decreases significantly between t0 and t2 (p = 0.00023) and increases between t2 and t3, though this increase is not statistically significant (p = 0.079). For VAS scores, there is a significant decrease between t0 and t2 (p = 0.00023) and a significant increase between t2 and t3 (p = 0.04254). Patients with elevated preoperative HADS scores tended to have slower recovery trajectories and reported lower satisfaction levels. These findings reinforce the prognostic value of psychological assessments in spine surgery and suggest that targeted psychological interventions could improve patient outcomes. Conclusions: By identifying psychological predictors of postoperative recovery, this study underscores the importance of integrating preoperative psychological screening into routine clinical practice. The results suggest that a multidisciplinary approach, including both surgical and psychological care, could enhance long-term functional outcomes and quality of life for patients undergoing instrumented lumbar spine surgery. Full article