Search Results (12,062)

This paper presents a systematic approach to the development and validation of a monitoring and protection system based on the IEC 61850 standard, evaluated through hardware-in-the-loop (HIL) testing. The study utilized an already existing model of a modern power grid consisting of the IEEE 9-bus power system integrated with a large-scale wind power plant (LSWPP). The SEL-487B Relay was configured to protect the PCC using a low-impedance busbar differential monitoring and protection system equipped with adaptive setting group logic that automatically transitions between Group 1 and Group 2 based on system loading conditions. Significant steps were followed for selecting and configuring instrument transformers and implementing relay logic in compliance with IEEE and IEC standards. Real-time digital simulation using Real-Time Digital Simulator (RTDS) hardware and its software, Real-time Simulation Computer-Aided Design (RSCAD), was used to assess the performance of the overall monitoring and protection system, focusing on the monitoring and publishing of the selected electrical and mechanical measurements from a selected wind turbine generator unit (WTGU) on the LSWPP side through the IEC 61850 standard network, and on the behavior of the monitoring and protection system under initial and increased load conditions through monitoring of differential and restraint currents. The overall monitoring and protection system was tested under both initial and increased load conditions, confirming its capability to reliably publish analog values from WTGU13 for availability on the IEC 61850 standard network while maintaining secure protection operation. Quantitatively, the measured differential (operate) and restraint currents were 0.32 PU and 4.38 PU under initial loading, and 1.96 PU and 6.20 PU under increased loading, while total fault clearance times were 606.667 ms and 706.667 ms for faults under initial load and increased load demand conditions, respectively. These results confirm that the developed framework provides accurate real-time monitoring and reliable operation for faults, while demonstrating a practical and replicable solution for monitoring and protection at transmission-level PCCs within renewable-integrated networks. Full article

Background: Mixed martial arts (MMA) is becoming increasingly popular and is developing dynamically in terms of training methods and number of participants involved, while weightlifting, powerlifting, and other kinds of strength disciplines are well established. In this study, the aim was to compare the body composition, as an anthropometric effect of training in MMA fighters and strength athletes, and then analyze and find reasoning for observed differences. Methods: Thirty-four young healthy male participants (body weight 84.9 ± 10.2 kg, body height 182.0 ± 6.8 cm, BMI 25.8 ± 2.51 kg/m², tier 2/3 in McKay’s sports level classification) represented two groups: MMA (n = 17) and powerlifting athletes (STR, n = 17). The measured anthropometric characteristics were skeletal muscle mass (SMM), percentage of body fat (PBF), body fat mass (FM) and visceral fat mass (VFM). Phase angle (º) was measured as an indicator of tissue quality and we performed detailed investigations of soft fat-free tissue mass (SLM) and of fat mass in body parts separately in each lower and upper limb and trunk. Results: The groups did not differ in terms of body weight, height, BMI, SMM, PBF, FM, VFM, SLM in upper limbs and trunk, FM in the body parts, or the phase angle (all p > 0.05). The statistically significant differences were only observed in the SLM of both lower limbs (greater in STR, p < 0.05) but, after statistical correction with the Holm’s method, these parameters also did not show statistically significant differences despite high effect sizes. Conclusions: The MMA athletes do not differ significantly from strength training athletes in measured anthropometric parameters despite distinct differences in training methodology. The reasons for these observations need future research, combining anthropometric measurements with training and competing load monitoring. Full article

The study evaluates the impact of massive electric vehicle (EV) penetration on Quito’s 138 kV distribution system in Ecuador, employing a probabilistic approach to support a sustainable energy transition. The rapid adoption of EVs, as projected by Ecuador’s National Electromobility Strategy, poses significant challenges to the capacity and reliability of the city’s electrical infrastructure. The objective is to analyze the system’s response to increased EV load and assess its readiness for this scenario. A methodology integrating dynamic battery modeling, Monte Carlo simulations, and power flow analysis was employed, evaluating two penetration levels: 800 and 25,000 EVs, under homogeneous and non-homogeneous distribution scenarios. The results indicate that while the system can handle moderate penetration, high penetration levels lead to overloads in critical lines, such as L10–15 and L11–5, compromising normal system operation. It is concluded that specific infrastructure upgrades and the implementation of smart charging strategies are necessary to mitigate operational risks. This approach provides a robust framework for effective planning of EV integration into the system, contributing key insights for a transition toward sustainable mobility. Full article

Directive (EU) 2024/3019 on urban wastewater treatment requires municipal wastewater treatment plants (WWTPs) to achieve energy neutrality by 2045. This study assessed the energy efficiency of a WWTP in central Poland over eight years (2015–2022), considering influent variability, electricity use and cost, and biogas recovery. The facility served 41,951–44,506 inhabitants, with treated wastewater volumes of 3.08–3.93 million m³/year and a real population equivalent (PE) of 86,602–220,459. Over the study period, the specific energy demand remained stable at 0.92–1.20 kWh/m³ (average 1.04 ± 0.09 kWh/m³), equivalent to 17.4–36.3 kWh/PE∙year. Energy efficiency indicators (EEIs) per pollutant load removed averaged 1.12 ± 0.28 kWh/kgBODrem, 0.53 ± 0.12 kWh/kgCODrem, 1.18 ± 0.36 kWh/kgTSSrem, 12.1 ± 1.5 kWh/kgTNrem, and 62.3 ± 11.7 kWh/kgTPrem. EEI per cubic meter of treated wastewater proved to be the most reliable metric for predicting energy demand under variable influent conditions. Electricity costs represented 4.48–13.92% of the total treatment costs, whereas co-generation from sludge-derived biogas covered 18.1–68.4% (average 40.8 ± 13.8%) of the total electricity demand. Recommended pathways to energy neutrality include co-digestion with external substrates, improving anaerobic digestion efficiency, integrating photovoltaics, and optimizing electricity use. Despite fluctuations in influent quality and load, the ultimate effluent quality consistently complied with legal requirements, except for isolated cases of exceeded phosphorus levels. Full article

Bovine leukemia virus (BLV), an oncogenic retrovirus of the genus Deltaretrovirus, causes enzootic bovine leukosis (EBL), the most prevalent neoplastic disease in cattle and a major source of economic loss. While BLV prevalence has been studied in commercial breeds, data on native Latin American cattle remain limited. This study assessed BLV infection and proviral load in 244 animals from six native breeds: Argentine Creole (CrAr), Patagonian Argentine Creole (CrArPat), Pampa Chaqueño Creole (CrPaCh), Bolivian Creole from Cochabamba (CrCoch), Saavedreño Creole (CrSaa), and Siboney (Sib), sampled across Argentina, Bolivia, Paraguay, and Cuba. BLV-CoCoMo-qPCR-2 assay detected BLV provirus in 76 animals (31.1%), with a mean load of 9923 copies per 10⁵ cells (range: 1–79,740). Infection rates varied significantly by breed (9.8% in CrAr to 83.8% in CrPaCh) and country (15.6% in Argentina to 83.8% in Paraguay) (p = 9.999 × 10⁻⁵). Among positives, 57.9% exhibited low proviral load (≤1000 copies), and 13.2% showed moderate levels (1001–9999), suggesting potential resistance to EBL progression. This is the first comprehensive report of BLV proviral load in Creole cattle across Latin America, offering novel epidemiological insights and highlighting the importance of native breeds in BLV surveillance. Full article

Amid the global energy transition, rapidly expanding wind and solar installations challenge power grids with variability and uncertainty. We propose an adaptive framework for renewable energy accommodation assessment under high-dimensional uncertainties, integrating three innovations: (1) Response Surface Methodology (RSM) is adopted for the first time to construct a closed-form polynomial of renewable energy accommodation in terms of resource hours, load, installed capacity, and transmission limits, enabling millisecond-level evaluation; (2) LASSO-regularized RSM suppresses high-dimensional overfitting by automatically selecting key interaction terms while preserving interpretability; (3) a Bayesian kernel density extension yields full posterior distributions and confidence intervals for renewable energy accommodation in small-sample scenarios, quantifying risk. A case study on a renewable-rich grid in Northwest China validates the framework: two-factor response surface models achieve R² > 90% with < 0.5% mean absolute error across ten random historical cases; LASSO regression keeps errors below 1.5% in multidimensional space; Bayesian density intervals encompass all observed values. The framework flexibly switches between deterministic, sparse, or probabilistic modes according to data availability, offering efficient and reliable decision support for generation-transmission planning and market clearing under multidimensional uncertainty. Full article

Biomarkers are important for the diagnosis and follow-up of neuromuscular diseases. Creatine kinase (CK) is a widely used marker of active muscle damage; however, it is not suitable for assessing muscle mass loss. Therefore, additional biomarkers are required to monitor skeletal muscle damage and loss. Titin plays an essential role in the structure and function of muscle fibers. It provides stability and elasticity to the sarcomeres. During sarcomere damage, fragments of titin and other proteins are released from muscle fibers and can be detected in blood and urine. Urinary titin-N fragment (UTN) detection is a noninvasive method for assessing and monitoring the extent of muscle damage. In addition to muscular dystrophies, elevated UTN levels have been observed in patients with sarcopenia. The UTN level increased significantly during eccentric muscle strain, indicating muscle damage, whereas the concentric load was associated with only a minimal increase in UTN. As titin is also present in the heart muscle, UTN can help diagnose cardiomyopathies and predict disease prognosis. In summary, the detection of urinary titin fragments is a promising tool for diagnosing and monitoring neuromuscular and cardiac diseases. While both CK and UTN rise and are related in acute conditions, their relationship is less clear in chronic diseases where muscle tissue damage and muscle mass loss are combined. Full article

To address the challenge of long-term stiffness retention of subgrades in humid–hot climates, this study evaluates expansive soil stabilized with construction and demolition waste (CDW), focusing on the resilient modulus (M_r) under coupled stress states and wetting–drying histories. Basic physical and swelling tests identified an optimal CDW incorporation of about 40%, which was then used to prepare specimens subjected to controlled. Wetting–drying cycles (0, 1, 3, 6, 10) and multistage cyclic triaxial loading across confining and deviatoric stress combinations. M_r increased monotonically with both stresses, with stronger confinement hardening at higher deviatoric levels; with cycling, M_r exhibited a rapid then gradual degradation, and for most stress combinations, the ten-cycle loss was 20%–30%, slightly mitigated by higher confinement. Grey relational analysis ranked influence as follows: the number of wetting–drying cycles > deviatoric stress > confining pressure. A Lytton model, based on a modified prediction method, accurately predicted M_r across conditions (R² ≈ 0.95–0.98). These results integrate stress dependence with environmental degradation, offering guidance on material selection (approximately 40% incorporation), construction (adequate compaction), and maintenance (priority control of early moisture fluctuations), and provide theoretical support for durable expansive soil subgrades in humid–hot regions. Full article

Background: Bioelectrical impedance analysis (BIA) is a widely used field technique for assessing body composition in football. However, its reliance on population-specific regression equations limits its accuracy. Objective: This scoping review aimed to map the scientific literature on BIA applications in professional and semi-professional football, highlighting uses, limitations, and research opportunities. Methods: A comprehensive search was conducted in the scientific databases PubMed, EMBASE, Web of Science, and SPORTDiscus. Identified studies involved the use of BIA in professional and semi-professional football players (≥16 years) in the context of routine training and competition. Results: From 14,624 records, 39 studies met the inclusion criteria and were included. Three main applications were identified: (1) quantitative body composition assessment, (2) qualitative/semi-quantitative analysis (e.g., bioelectrical impedance vector analysis (BIVA)), and (3) muscle health and injury monitoring. Seven specific research areas emerged, including hydration monitoring, cross-method validation of body composition analyses, development of predictive models, sport phenotype identification, tracking training adaptations, performance/load assessment via phase angle, and localized BIA for injury diagnosis and recovery. Conclusions: While quantitative BIA estimates may lack individual-level precision, raw parameter analyses may offer valuable insights into hydration, cellular integrity, and muscle injury status, yet further research is needed to fully realize these applications. Full article

Shaft deflection degrades roller alignment and intensifies stress concentration/edge effects at roller-ends and raceway edges, ultimately compromising service performance of tapered roller bearings (TRBs). Therefore, a dynamic model was developed for a TRB subjected to a deflected shaft in which Johnson’s load–deformation relationship was applied to reflect non-uniform cross-sectional structures of the tapered rollers and raceways, viscous damping was integrated into the roller/cage interaction, and friction actions at the raceways and flange areas were treated separately. Then, moment load and angular misalignment of the tapered roller were analyzed under various shaft deflection and operating conditions. Results indicate that tilt angle remains orders of magnitude smaller than skew angle. Shaft deflection amplifies both skew and tilt, and the influence level is proportional to the bearing size. Centrifugal effect primarily affects skew motion, whereas gyroscopic effect mainly influences tilt motion. Axial forces exert greater influence on roller skew than tilt. The flange typically constrains roller skew, whereas both raceways may induce bidirectional tilt/skew motion. Full article

This paper investigates frequency regulation of an airport microgrid (AIM) through the application of an integral absolute error (IAE)-assisted control approach. The islanded AIM is initially captured using a linearized transfer function model to accurately reflect its dynamic characteristics. This model is then simplified using a first-order plus dead time (FOPDT) approximation derived via a reaction-curve-based method, which balances between model simplicity and accuracy. Two different proportional–integral–derivative (PID) controllers are designed to meet distinct objectives: one focuses on set-point tracking (SPT) to maintain the target frequency levels, while the other addresses load disturbance rejection (LDR) to reduce the effects of load fluctuations. A thorough comparison of these controllers demonstrates that the SPT-mode PID controller outperforms the LDR-mode controller by providing an improved transient response and notably lower error measures. The results underscore the effectiveness of combining IAE-based control with reaction curve modeling to tune PID controllers for islanded AIM systems, contributing to enhanced and reliable frequency regulation for microgrid operations. Full article

The aim of this study is to investigate how the positioning of outrigger systems affects the seismic performance of high-rise buildings with either reinforced concrete (RC) shear walls or buckling-restrained braces (BRBs) in the core. Two important questions emerge as the focus and direction of the study: (1) How does the structural performance change when outriggers are placed at various positions? (2) How do outrigger systems affect structural behavior under sequential earthquake scenarios? Nonlinear time history analyses were employed as the primary methodology to evaluate the seismic response of the two reinforced concrete buildings with 24 and 48 stories, respectively. Each building type was developed for two different core configurations: one with a reinforced concrete shear wall core and the other with a BRB core system. Each analysis model also includes outrigger systems constructed with BRBs positioned at different floor levels. Five sequential ground motion records were used to assess the effects of main- and aftershocks. The analysis results were evaluated not only based on displacement and force demands but also using a damage measure called the Park-Ang Damage Index. In addition, displacement-based metrics, particularly the maximum inter-story drift ratio (MISD), were also utilized to quantify lateral displacement demands under consecutive seismic loading. With the results obtained from this study, it is aimed to provide design-oriented insights into the most effective use of outrigger systems formed with BRB in high-rise RC buildings and their functions in increasing seismic resistance, especially in areas likely to experience consecutive seismic events. Full article

In this paper, we present a unique method to determine the level of bot contamination of web-based user agents. It is common practice for bots and robotic agents to masquerade as human-like to avoid content and performance limitations. This paper continues our previous work, using over 600 million web log entries collected from over 4000 domains to derive and generalize how the prominence of specific web browser versions progresses over time, assuming genuine human agency. Here, we introduce a parametric model capable of reproducing this progression in a tunable way. This simulation allows us to tag human-generated traffic in our data accurately. Along with the highest confidence self-tagged bot traffic, we train a Transformer-based classifier that can determine the bot contamination—a botness metric of user-agents without prior labels. Unlike traditional syntactic or rule-based filters, our model learns temporal patterns of raw and heuristic-derived features, capturing nuanced shifts in request volume, response ratios, content targeting, and entropy-based indicators over time. This rolling window-based pre-classification of traffic allows content providers to bin streams according to their bot infusion levels and direct them to several specifically tuned filtering pipelines, given the current load levels and available free resources. We also show that aggregated traffic data from multiple sources can enhance our model’s accuracy and can be further tailored to regional characteristics using localized metadata from standard web server logs. Our ability to adjust the heuristics to geographical or use case specifics makes our method robust and flexible. Our evaluation highlights that 65% of unclassified traffic is bot-based, underscoring the urgency of robust detection systems. We also propose practical methods for independent or third-party verification and further classification by abusiveness. Full article

Background: Late sternocutaneous fistulas (SCFs), secondary to chronic sternal osteomyelitis, are uncommon sequelae of median sternotomy and present significant therapeutic challenges. They are frequently linked to low-virulence microorganisms forming biofilms on retained foreign materials. While antibiotic-impregnated polymethylmethacrylate (PMMA) beads are established in managing chronic osteomyelitis in other anatomical locations, reports describing their use for post-sternotomy SCFs are limited to two early postoperative cases. Case Presentation: We describe a 62-year-old man with a history of triple-vessel coronary artery disease who underwent coronary artery bypass grafting via median sternotomy. Two months postoperatively, he developed an SCF in the upper sternum, initially treated with wire removal, negative pressure wound therapy, and intravenous vancomycin. Recurrence occurred one month later without systemic signs of infection. Imaging revealed inflammatory changes at the level of the manubriosternal junction. Definitive surgery included extensive sternal and costosternal debridement, bilateral anterior arthrolysis of the second ribs, and pulse lavage with 10 L of Microdacyn. The remaining defect was filled with vancomycin- and gentamicin-loaded PMMA beads. The patient had an uneventful recovery with no recurrence at six months. Conclusions: This case suggests that local antibiotic delivery via PMMA beads can be a valuable adjunct in the surgical management of recurrent, late-presenting SCFs after cardiac surgery. Full article

For large-scale tropical tuna purse-seine fisheries, it is prohibitively costly to obtain adequate sampling coverage to estimate fleet-level catch composition solely from sample data. Logbook or observer data, with complete fleet coverage, are often available but may be considered unreliable for species composition. Previous studies have developed models, trained with sample data, to predict set-level species compositions based on environmental and operational covariates. Here, models were developed to predict well-level species composition from uncorrected observer data and covariates affecting the observers’ view of the catch during loading, with port-sampling data as the response variable. The analysis used paired, well-level data from sets made on floating objects by the Eastern Pacific Ocean tuna purse-seine fleet during 2023–2024. Results indicated that, overall, observer data proportions of bigeye (BET) and yellowfin tunas tended to be greater than the model-estimated proportions, with the opposite occurring for skipjack tuna (SKJ). However, vessel effects sometimes modified these tendencies. Model complexity was greatest for BET and least for SKJ. For BET, observer data proportions and model-estimated proportions were more similar when the vessel had a hopper. They were also more similar in 2023 as compared to 2024, suggesting sample data for bias adjustments should be collected annually. The approach shows potential for predicting the species composition of unsampled wells. Full article