Search Results (5,473)

In the event of power outages caused by natural disasters, accidents, or other emergencies, outdoor emergency lighting systems play a critical role in providing illumination to maintain spatial orientation, facilitate evacuation procedures, and help individuals avoid hazardous areas or locate safe shelters. Compared to traditional lighting technologies, LED-based outdoor emergency lighting offers several advantages, including compact size, long operational lifespan, low energy consumption, high safety, resistance to breakage, and the absence of chemical residue or pollution. These characteristics align with contemporary trends in environmental sustainability and energy efficiency. This study proposes a novel LED driver circuit architecture for outdoor emergency lighting applications. The primary circuit topology is based on an improved buck-boost converter integrated with a flyback converter, forming a hybrid buck-boost-flyback configuration. The proposed circuit is capable of recycling the energy stored in the transformer’s leakage inductance, thereby enhancing overall power conversion efficiency. A 12 W (20 V/0.6 A) prototype LED driver circuit was designed and implemented to validate the performance of the proposed system. Experimental measurements, including waveform analysis and efficiency evaluation, demonstrate that the driver circuit achieves a high efficiency exceeding 91%. These results confirm the practical feasibility and effectiveness of the proposed electronic driver for LED-based outdoor emergency lighting applications. Full article

The stability of internal dumps in open-pit coal mines is critical for the safe production and economic performance of the entire mine. To further enhance slope stability and ensure safe production, a new method for constructing trenches (referred to as an anti-sliding trench) on the sloped basal bed of the dump slope in open-pit mines was proposed to improve slope stability. The internal dump slope at the Luzigou anticline of the Anjialing Open-Pit Mine was studied. The slope failure modes of the dumping steps were studied experimentally and by numerical simulations at different widths of anti-slide trenches at the slope’s toe in a staged loading state. Without anti-slide trenches, shear-layer and along-layer failure modes occurred, while the failure modes with anti-slide trenches included shear-layer, along-layer, and squeeze-out failure. Based on the limit equilibrium theory and the determined failure modes, the preset anti-slide trenches at the toe of the dumping steps were theoretically analyzed. The relationships between the slope stability coefficient and the width and depth of anti-slide trenches, as well as the physical and mechanical parameters of the slope body, were derived. Given the physical and mechanical parameters of the slope body and targeted improvement in the slope stability coefficient, the size parameters of anti-slide trenches were designed and optimized through the derived relationships. At the Anjialing Coal Mine, presetting anti-slide trenches with a depth of 1.5 m and a width of 22.68 m at the toe of the dumping steps increased the slope stability coefficient from 1.3095 to 1.6. The proposed method provides a guiding reference for designing similar internal dump slopes in open-pit coal mines and for disaster prevention. Full article

Blockchain is an emerging technology that is being used to create innovative solutions in many areas, including healthcare. Nowadays healthcare systems face challenges, especially with security, trust, and remote data access. As patient records are digitized and medical systems become more interconnected, the risk of sensitive data being exposed to cyber threats has grown. In this evolving time for healthcare, it is important to find a balance between the advantages of new technology and the protection of patient information. The combination of blockchain–InterPlanetary File System technology and conventional electronic health record (EHR) management has the potential to transform the healthcare industry by enhancing data security, interoperability, and transparency. However, a major issue that still exists in traditional healthcare systems is the continuous problem of remote data unavailability. This research examines practical methods for safely accessing patient data from any location at any time, with a special focus on IPFS servers and blockchain technology in addition to group signature encryption. Essential processes like maintaining the confidentiality of medical records and safe data transmission could be made easier by these technologies. Our proposed framework enables secure, remote access to patient data while preserving accessibility, integrity, and confidentiality using Ethereum blockchain, IPFS, and group signature encryption, demonstrating hospital-scale scalability and efficiency. Experiments show predictable throughput reduction with file size (200 → 90 tps), controlled latency growth (90 → 200 ms), and moderate gas increase (85k → 98k), confirming scalability and efficiency under varying healthcare workloads. Unlike prior blockchain–IPFS–encryption frameworks, our system demonstrates hospital-scale feasibility through the practical integration of group signatures, hierarchical key management, and off-chain erasure compliance. This design enables scalable anonymous authentication, immediate blocking of compromised credentials, and efficient key rotation without costly re-encryption. Full article

Background: Hamstring tendon autografts are frequently used for anterior cruciate ligament reconstruction (ACLR), but they are associated with persistent hamstring strength deficits and delayed functional recovery. Current rehabilitation guidelines often delay open kinetic chain (OKC) hamstring exercises due to safety concerns, despite the limited supporting evidence. This uncontrolled, underpowered, and exploratory study aimed to evaluate the safety and effectiveness of introducing OKC hamstring strengthening exercises as early as three weeks after ACLR. Methods: An exploratory retrospective observational study was conducted at a single physiotherapy center on 13 patients (aged 18–35) who underwent primary ACLR with semitendinosus–gracilis grafts. Participants followed a standardized rehabilitation program including isometric leg curls at 60° and 90° knee flexion and long-lever glute bridges twice weekly, starting from postoperative week 3. Safety was assessed through predefined “safety flags” (pain > 4/10, hematoma, clinical hamstring strain). Strength outcomes, including isometric knee flexion strength at 60° and 90°, limb symmetry index (LSI), and endurance tests, were assessed at 6 and 12 weeks. Results: All participants completed the program without major adverse events. Pain remained consistently low (median 2.5/10), with only one transient episode exceeding the threshold. No other complications were recorded. Isometric knee flexion strength significantly improved between week 6 and week 12 at both 60° (p = 0.018) and 90° (p = 0.003), with large effect sizes. LSI at 90° also increased significantly (p = 0.006), whereas improvements at 60° did not reach significance. Endurance testing showed functional gains as early as 6 weeks. Conclusions: The early introduction of OKC hamstring strengthening exercises three weeks after ACLR with hamstring autografts appears safe and promotes clinically meaningful improvements in strength and endurance. These findings, while from a small uncontrolled study, challenge conservative rehabilitation protocols and support the reconsideration of early hamstring loading. Given the retrospective, uncontrolled, and underpowered design, these findings are hypothesis-generating and not generalizable beyond young adults with hamstring autografts; larger randomized trials are required. Full article

This paper presents an integrated downhole risk prevention and control system designed to enhance safety, efficiency and sustainability in deep-well drilling operations. The system incorporates advanced measurement processing, risk evaluation, and intelligent data transmission technologies for real-time monitoring of nine key drilling parameters, such as downhole drilling pressure, bending moment, and torque, etc. Bench tests and field trials demonstrated the system’s reliability in accurately capturing and transmitting data under high-pressure, high-temperature conditions. For instance, it successfully monitored bottom-hole pressure up to 61.4 MPa and temperature to 120.8 °C, allowing for early detection of abnormal events such as pressure kicks and torsional stick-slip. The system was laboratory-tested to withstand bottom-hole pressures up to 61.4 MPa and temperatures of 120.8 °C. During field trials, the tool operated safely under actual downhole conditions of approximately 59.2 MPa and 115 °C, which are within its rated limits. The system also facilitated automated controlled actions, including mud weight and pump rate control, to prevent incidents. These results underscore the system’s potential to significantly improve real-time and intelligent process control, minimize operational risks, and advancing the sustainability of drilling practices. The approach marks a step forward in intelligent drilling technologies, supporting proactive decision-making in energy extraction. Future work will extend this system to ultra-deep and high-temperature wells while integrating advanced AI-based analytics for further optimization. Full article

Controlled demolition is a critical engineering practice that enables the safe and efficient dismantling of structures while minimizing risks to the surrounding environment. This study presents, for the first time, a detailed, structured framework for understanding the fundamental principles of controlled demolition by outlining key procedures, methodologies, and directions for future research. Through original, carefully designed charts and full-scale numerical simulations, including two 23-story building scenarios with different delay and blasting sequences, this paper provides real-life insights into the effects of floor-to-floor versus axis-by-axis delays on structural collapse behavior, debris spread, and toppling control. Beyond traditional techniques, this study explores how emerging technologies, such as real-time structural monitoring via object tracking, LiDAR scanning, and Unmanned Aerial Vehicle (UAV)-based inspections, can be further advanced through the integration of artificial intelligence (AI). The potential Deep learning (DL) and Machine learning (ML)-based applications of tools like Convolutional Neural Network (CNN)-based digital twins, YOLO object detection, and XGBoost classifiers are highlighted as promising avenues for future research. These technologies could support real-time decision-making, automation, and risk assessment in demolition scenarios. Furthermore, vision-language models such as SAM and Grounding DINO are discussed as enabling technologies for real-time risk assessment, anomaly detection, and adaptive control. By sharing insights from full-scale observations and proposing a forward-looking analytical framework, this work lays a foundation for intelligent and resilient demolition practices. Full article

Tumor immunotherapy, a revolutionary cancer treatment, is hindered by inadequate immune cell activation, immunosuppressive tumor microenvironment (TME), and off-target toxicities of immunotherapeutics. These bottlenecks necessitate innovative strategies to enhance efficacy and reduce side effects. Marine polysaccharides have garnered significant attention due to their potential to enhance immune cell activity and regulate the tumor microenvironment, among other benefits. Due to their excellent biocompatibility, modifiability, and relatively low cost, polysaccharides are increasingly being explored as materials for drug delivery systems. The development of marine polysaccharide-based drug delivery systems represents an opportunity for advancing tumor immunotherapy. This review focuses on the application of marine polysaccharide drug delivery systems in tumor immunotherapy, exploring the mechanisms underlying the bioactivity of marine polysaccharides, the design of drug delivery systems, and the interactions between these systems and tumor immunotherapy, aiming to provide a framework for advancing marine polysaccharide-based therapeutics, accelerating the clinical translation of effective, safe, and targeted tumor immunotherapy strategies. Full article

Background: Post-transplant cyclophosphamide (PTCy) is a standard graft-versus-host disease (GVHD) prophylaxis in allogeneic hematopoietic cell transplantation (allo-HCT). While effective, concerns remain about cyclophosphamide-related cardiotoxicity, especially in patients with pre-existing cardiac morbidity, a population often underrepresented in clinical trials. Objectives: To assess the incidence and outcomes of early (ECE, ≤100 days) and late (LCE, >100 days) cardiac events in acute myeloid leukemia (AML) patients with and without baseline cardiac morbidity undergoing allo-HCT with PTCy. Study Design: Retrospective multicenter study by the Grupo Español de Trasplante Hematopoyético y Terapia Celular (GETH-TC) including 461 AML patients (62 with cardiac morbidity) transplanted between 2012 and 2022. Cardiac morbidity was defined by documented cardiac disease or left ventricular ejection fraction < 45%. Cumulative incidence, overall survival (OS), and non-relapse mortality (NRM) were analyzed using competing risks models and adjusted with propensity score matching (PSM) and inverse probability weighting (IPW). Results: Cardiac events occurred in 13.2% of patients: 11% vs. 7% ECE (p = 0.93) and 8% vs. 5.3% LCE (p = 0.85) in those with vs. without cardiac morbidity. Most ECEs were arrhythmias or heart failure. Adjusted analyses confirmed no significant differences in CE incidence, OS, or NRM between groups. Two-year OS was 69% vs. 70% (p = 0.50); NRM was 18% vs. 17% (p = 0.20). ECE was associated with higher mortality in both groups. Conclusions: PTCy is feasible in AML patients with pre-existing cardiac morbidity when combined with comprehensive cardiovascular evaluation and cardio-oncology follow-up, supporting its safe use in broader patient populations with appropriate cardiologic support. Full article

Background/Objectives: Acute myocardial infarction (MI) is a major cause of death worldwide, and it imposes a heavy burden on health care systems. Although diagnostic methods have improved, detecting the disease early and accurately is still difficult. Recently, AI has demonstrated increasing capability in improving ECG-based MI detection. From this perspective, this scoping review aimed to systematically map and evaluate AI applications for detecting MI through ECG data. Methods: A systematic search was performed in Ovid MEDLINE, Ovid Embase, Web of Science Core Collection, and Cochrane Central. The search covered publications from 2015 to 9 October 2024; non-English articles were included if a reliable translation was available. Studies that used AI to diagnose MI via ECG were eligible, and studies that used other diagnostic modalities were excluded. The review was performed per the PRISMA extension for scoping reviews (PRISMA-ScR) to ensure transparent and methodological reporting. Of a total of 7189 articles, 220 were selected for inclusion. Data extraction included parameters such as first author, year, country, AI model type, algorithm, ECG data type, accuracy, and AUC to ensure all relevant information was captured. Results: Publications began in 2015 with a peak in 2022. Most studies used 12-lead ECGs; the Physikalisch-Technische Bundesanstalt database and other public and single-center datasets were the most common sources. Convolutional neural networks and support vector machines predominated. While many reports described high apparent performance, these estimates frequently came from relatively small, single-source datasets and validation strategies prone to optimism. Cross-validation was reported in 57% of studies, whereas 36% did not specify their split method, and several noted that accuracy declined under inter-patient or external validation, indicating limited generalizability. Accordingly, headline figures (sometimes ≥99% for accuracy, sensitivity, or specificity) should be interpreted in light of dataset size, case mix, and validation design, with risks of spectrum/selection bias, overfitting, and potential data leakage when patient-level independence is not enforced. Conclusions: AI-based approaches for MI detection using ECGs have grown quickly. Diagnostic performance is limited by dataset and validation issues. Variability in reporting, datasets, and validation strategies have been noted, and standardization is needed. Future work should address clinical integration, explainability, and algorithmic fairness for safe and equitable deployment. Full article

The design and structural analysis of a cattle slaughtering frame is essential to ensure the safety, efficiency, and durability of the facility. This research was conducted in farms and slaughterhouses to analyze the performance of cattle slaughtering frames under three load variations using the finite element method (FEA). The frame model was created using Autodesk Inventor and simulated in Ansys, considering material properties, dimensions, and frame configuration. The simulated loads represented cow weights ranging from 500 kg/4905 N to 1500 kg/14,715 N. The analysis results showed the distribution of stress and deformation across the frame structure. The highest stress occurred under the 1500 kg/14,715 N load but remained within safe limits. The frame, designed using 1040 carbon steel, demonstrated the ability to withstand a maximum load of 1500 kg/14,715 N with an acceptable safety factor. Although stress and deflection increased with higher loads, the structure stayed within allowable tolerances. These findings confirm that FEA is an effective tool for optimizing structural performance before fabrication. The study provides recommendations for safer and more efficient designs, particularly in selecting materials and reinforcing critical areas. This research is expected to serve as a reference for improving the quality of cattle slaughtering facilities in farms and abattoirs. Full article

Ammonia bunkering is becoming increasingly important in the maritime industry as ammonia is recognized as a viable alternative fuel for reducing carbon emissions in shipping. Bunkering by tank truck plays a crucial role in the early stages of ammonia-fueled ship development. It involves the efficient transportation of ammonia from production facilities to bunkering stations, offering flexibility in refueling vessels at ports, including those lacking extensive infrastructures like pipelines or large storage tanks. However, the safety and regulations surrounding ammonia use in bunkering are paramount to its adoption. This study focuses on analyzing the effectiveness of safeguards designed to reduce the frequency of ammonia releases and mitigate potential leak damage during bunkering operations. We examine how safeguards, such as breakaway couplings and dry disconnect couplings (DDC), can reduce leak occurrences, while excess flow valves (EFVs) and automatic emergency shut-off valves (ESVs) can limit the consequences of such incidents. If the breakaway coupling and DDC are implemented as safeguards in the flexible hose, and maintenance is performed in accordance with ANSI/CGA G-2.1, the probability of hose failure per bunkering operation will be reduced from approximately 10⁻⁵ to 10⁻⁷. Under the worst weather conditions during the day, the probit value (Pr) depends on both the amount of ammonia released and the distance from the release point, with the distance having a greater effect on fatality than the amount of ammonia. The individual risk is analyzed to determine whether the bunkering process using tank trucks is acceptable. The analysis concludes that, with these safeguards in place, the individual risk at a location 20 m from the bunker site can be reduced to the lower limit of the As Low As Reasonably Practicable (ALARP) zone, ensuring a safe and acceptable level of risk for ammonia bunkering operations. The safety integrity level (SIL) of the automatic ESV should be at least 2 or higher, and it should be activated within a few seconds after a gas leak begins. Full article

Background: Melasma is a chronic, relapsing pigmented skin disease with challenging and unsatisfactory treatment outcomes. This study aims to compare the efficacy and safety of different treatments for melasma. Methods: We conducted a comprehensive search of PubMed and EMBASE databases to identify randomized controlled clinical trials (RCTs) for melasma treatment modalities between January 2022 and January 2025. Relative efficacy refers to the comparison of the improvement in melasma severity before and after treatment for all modalities of interest at a specific time point. The Melasma Area Severity Index (MASI) (also known as modified MASI (mMASI) or half-MASI score) was defined as the efficacy index. Safety refers to the incidence of the most common adverse events. The quality of the included trials was assessed using the GRADE method. Results: The analysis included 14 clinical trials with 15 treatment modalities involving 738 women who met the inclusion criteria. The mean difference in efficacy index showed that intradermal PRP (platelet-rich plasma) and intradermal PRP + oTXA (oral tranexamic acid) were the best treatment options compared with HQ4%, intradermal TXA, intradermal PRGF (plasma rich in growth factor) + HQ4 (hydroquinone 4%), followed by intradermal TXALaser (intradermal TXA + Q-switched fractional 1064-nmNd:YAG lasers). The efficacy indices of other modalities were comparable. Most treatment-related adverse events were mild, were well tolerated, or resolved with treatment. The quality of evidence was generally high. Conclusions: This NMA showed that intradermal PRP in combination or alone is an effective and safe treatment option for melasma. PRP may be a direction for the development of new melasma treatment options in the future, but well-designed, comprehensive, large-scale randomized controlled trials are needed to verify it. Full article

Background/Objectives: Standing training is essential for individuals with spinal cord injury (SCI), yet maintaining regular practice after acute rehabilitation remains challenging. To address the need for more practical and accessible standing equipment, we developed a novel spring-assisted standing training device designed to overcome barriers to regular standing practice. This study aimed to assess the safety and feasibility of our newly developed device in individuals with SCI. Methods: Six participants with chronic SCI (neurological level of injury T4-L3, American Spinal Injury Association Impairment Scale A-C; 2 females, mean age 41.7 ± 13.4 years) underwent a single session using our chair-based device incorporating passive gas spring mechanisms. We designed this device to enable independent sit-to-stand transitions without electrical power or complex controls. Primary outcomes included safety (adverse events) and feasibility (number of repetitions, Modified Borg Scale). Changes in Modified Ashworth Scale (MAS) scores were assessed as exploratory measures. Results: All participants successfully completed training without adverse events. Repetitions ranged from 5 to 60 (median 37), with Modified Borg Scale ratings of 0–4. Notably, the participant with T4 complete injury performed the training without requiring trunk orthosis, demonstrating the device’s inherent stability. MAS sum scores showed a reduction from median 8.75 to 4.25, though this did not reach statistical significance (p = 0.13). Conclusions: Our newly developed spring-assisted standing training device proved safe and feasible for individuals with SCI, including those with complete thoracic injuries. The device successfully enabled independent sit-to-stand transitions with low perceived exertion, potentially addressing key barriers to regular standing practice and offering a practical rehabilitation solution. Full article

Phytoremediation has emerged as a sustainable and cost-effective strategy for mitigating contamination in soil and water systems, utilizing plants and their associated microbial consortia to uptake, degrade, or immobilize pollutants. This review synthesizes findings from over 100 peer-reviewed publications and case studies to identify key parameters influencing phytoremediation efficiency, including contaminant bioavailability, chemical speciation, concentration levels (ranging from trace to >100 mg/L), plant species suitability, hydraulic retention time, and temperature ranges (10–35 °C). Despite its proven potential, the absence of standardized design frameworks limits consistent implementation and cross-site performance comparability. To address this, the study proposes a conceptual system design framework supported by measurable performance metrics—such as pollutant removal efficiency (often >70% for heavy metals) and biomass uptake capacity. The review further examines regulatory and policy gaps that hinder the technology’s integration into national remediation strategies, particularly in low- and middle-income countries. It underscores the need for technical guidelines, regulatory benchmarks, and protocols for post-treatment biomass management to enable safe, effective, and scalable deployment. By advocating a multi-stakeholder, evidence-based approach, the study aims to bridge the gap between scientific innovation and environmental governance, positioning phytoremediation as a viable tool for pollution control, ecosystem restoration, and alignment with global sustainability targets. Full article

Power metal-oxide-semiconductor field-effect transistors (MOSFETs) provide numerous advantages and are widely utilized in various power circuits. The junction temperature plays a critical role in determining the reliability, performance, and operational lifetime of power MOSFETs. Therefore, accurate monitoring of the junction temperature of power MOSFETs is essential to ensure the safe operation of power circuit systems. In bridge or motor drive circuits, MOSFETs often operate in a freewheeling state via the body diode, where the freewheeling current is typically variable. The proposed method for junction temperature measurement utilizes the body diode and is designed to accommodate varying forward currents. It also accounts for the temperature-dependent ideality factor to improve measurement accuracy. By integrating the forward voltage and forward current of the body diode, this approach reduces the required sampling frequency. To validate the method’s effectiveness, three representative types of power MOSFETs, a Si MOSFET (IRF520), a SiC MOSFET (C2M0080120D), and an aerospace-grade radiation-hardened MOSFET (RSCS25045T1RH), were used to measure junction temperatures before and after irradiation. Following ideality factor correction, the maximum absolute error compared to reference measurements from thermocouples and a thermal imager remained within 2 K across the temperature range of 300 K to 420 K. Experimental results confirm the feasibility of the proposed method. Full article