Search Results (442)

Using lithium batteries to supply electric machinery and/or equipment in underground mines requires an adequate level of security. This is particularly important in coal mines, especially under the threat of methane explosions and/or fire hazards. Lithium battery cells with a BMS should be effectively isolated from the impact of the surrounding mine environment. This can be achieved by storing all battery systems in a certified explosion-proof enclosure (Ex) in accordance with the relevant regulations and standards. Preliminary tests conducted by the authors indicated that use of lithium cells without a BMS in mines is risky and, in practice, unacceptable. BMSs with passive cell balancing are most commonly employed. They allow for the equalization of cell voltages primarily during the charging process. However, the lowest-capacity cell still determines the overall lifetime of a battery. Furthermore, the use of active balancing systems (BMSs) is rare in practice due to their greater complexity and price. Nevertheless, they can significantly extend battery life through the much more efficient redistribution of energy among the cells, including during the discharge process. This article presents the operation of a modified (hybrid) BMS architecture, combining both passive and active balancing methods when employed for the selected suspended mine vehicle. It enables more safe and more effective charging process, as well as discharging process, which results in the longer time of operation of lithium battery packs, for one charge. This system is intended for use in mining machinery and equipment, as well as in selected energy storage systems powered by lithium-based battery modules. Full article

Functionalized hydrogels represent an emerging class of smart materials being explored for advancing next-generation wearable technologies, owing to their flexibility, biocompatibility, stimuli-responsiveness, and tunable properties. This review provides an overview of recent developments in hydrogel-based wearables, highlighting their potential to enhance adaptive, multifunctional, and environmentally sustainable devices and textiles. It begins by examining progress in wearable sensors, energy storage and harvesting, biosignal monitoring, and smart textiles, as well as the associated challenges, including limited battery life, inadequate skin adhesion, user discomfort, and constrained functionality. The review further explores the synthesis, fabrication techniques, properties, and types of hydrogels tailored for wearable technologies, followed by a detailed discussion of their applications in smart batteries, supercapacitors, sensors, nanogenerators, fabrics and hybrid systems. It also highlights integrating artificial intelligence (AI) and the Internet of Things (IoT) to improve designs; enhance performance through real-time monitoring, data analytics, and user interaction; and expand functionality. Also, it analyzes key limitations of current hydrogels—particularly in energy density, dehydration resistance, fatigue behaviour, and large-scale reproducibility—and outlines strategies based on hierarchical material design, sustainable and biodegradable formulations, and standardized testing and regulatory alignment. The review concludes by affirming the role of hydrogel-based technologies in shaping the future of wearable innovations across healthcare, lifestyle, and beyond and outlines promising research directions. Full article

Accurate state of charge (SOC) estimation is crucial for the safety, reliability, and energy efficiency of lithium-ion battery systems. However, variations in battery parameters and the loss of historical information during the update steps of traditional unscented Kalman filters (UKFs) often lead to decreased estimation accuracy under dynamic operating conditions. To address these issues, this paper proposes a variable forgetting factor recursive least squares (VFFRLS) algorithm combined with a multi-innovation unscented Kalman filter (MIUKF) algorithm. First, a second-order RC equivalent circuit model is established, and the battery parameters are identified online using the VFFRLS method, enabling the model to dynamically adapt to changing operating conditions. Then, multi-innovation theory is incorporated into the standard UKF, extending the single-innovation matrix to a multi-innovation matrix, effectively enhancing the utilization of historical residuals and improving robustness to measurement noise and model uncertainty. Experimental validation under four typical dynamic operating conditions (FUDS, DST, BJDST, and US06) demonstrates that the proposed method significantly improves SOC estimation accuracy. Compared to the traditional UKF, MIUKF reduces MAE and RMSE by 25–30% while maintaining real-time performance, with single-step computation time reaching the microsecond level. Robustness tests under different initial SOC errors further validate MIUKF’s strong robustness to initial biases. In summary, the proposed method provides an effective solution for high-precision SOC estimation of batteries and has the potential for application in battery management systems. Full article

This work proposes an intelligent strategy for the coordinated management of active and reactive power in Battery Energy Storage Systems (BESSs) within AC microgrids operating under both grid-connected (GCM) and islanded (IM) modes to minimize daily operational costs. The problem is formulated as a mixed-variable optimization model that explicitly leverages the control capabilities of BESS power converters. To solve it, a Parallel Particle Swarm Optimization (PPSO) algorithm is employed, coupled with a Successive Approximation (SA) power flow solver. The proposed approach was benchmarked against parallel implementations of the Crow Search Algorithm (PCSA) and the JAYA algorithm (PJAYA), both in parallel, using a realistic 33-node AC microgrid test system based on real demand and photovoltaic generation profiles from Medellín, Colombia. The strategy was evaluated under both deterministic conditions (average daily profiles) and stochastic scenarios (100 daily profiles with uncertainty). The proposed framework is evaluated on a 33-bus AC microgrid that operates in both grid-connected and islanded modes, with a battery energy storage system dispatched at both active and reactive power levels subject to network, state-of-charge, and power-rating constraints. Three population-based optimization algorithms are used to coordinate BESS schedules, and their performance is compared based on daily operating cost, BESS cycling, and voltage profile quality. Quantitatively, the PPSO strategy achieved cost reductions of 2.39% in GCM and 1.62% in IM under deterministic conditions, with a standard deviation of only 0.0200% in GCM and 0.2962% in IM. In stochastic scenarios with 100 uncertainty profiles, PPSO maintained its robustness, reaching average reductions of 2.77% in GCM and 1.53% in IM. PPSO exhibited consistent robustness and efficient performance, reaching the highest average cost reductions with low variability and short execution times in both operating modes. These findings indicate that the method is well-suited for real-time implementation and contributes to improving economic outcomes and operational reliability in grid-connected and islanded microgrid configurations. The case study results show that the different strategies yield distinct trade-offs between economic performance and computational effort, while all solutions satisfy the technical limits of the microgrid. Full article

Background/Objectives: Language impairments are highly prevalent in children with Autism Spectrum Disorder (ASD). In preschoolers (3–6 years), language development predicts future social outcomes. Despite the availability of standardized tests for typically developing children, few studies have specifically examined language impairments in preschool-aged children with ASD using these tools. This study aimed to comprehensively assess receptive and expressive lexicon, receptive comprehension, phonology and articulation using standardized tools, and to evaluate their feasibility. A secondary goal was to compare the results obtained with standardized tests to those from developmental batteries and hetero-assessments (caregiver reports). Methods: Forty-seven children with ASD aged 4 to 6 years participated. Assessments included standardized language tests, developmental batteries and hetero-assessments. The dichotomous Rasch model evaluated feasibility and item performance of standardized tests. Concordance across methods was analyzed via Pearson correlations and stepwise linear regression. Results: Standardized assessments were feasible for most participants despite wide variability in language abilities. Partial but non-equivalent concordance was found among assessment methods, each providing complementary insights into language profiles. Conclusions: Combining multiple assessment methods is crucial to capture the complexity of language development in children with ASD. Standardized tests can be adapted and provide more precise profiles than developmental batteries or hetero-assessments alone. A multimodal approach is essential to accurately identify language strengths and therapeutic targets in preschool-aged children with ASD. Full article

Cerebral ischemia represents a major mortality and disability cause; oxidative stress is the main intensifier mechanism of excitotoxicity, neuroinflammation, blood–brain barrier failure, and neuronal loss; under these circumstances, firm, mechanism-anchored neuroprotection is an absolute necessity. The work includes a exhaustive, PRISMA (Preferred reporting items for systematic review and meta-analysis)-adherent presentation of the effects of antioxidant peptides and small molecules on tissues, unifying disparate readouts into a coherent tissue-level narrative. A systematic interrogation was performed across major databases over a prespecified interval, applying transparent eligibility criteria to studies that quantified canonical endpoints—infarct volume, neuronal integrity (NeuN/MAP2), apoptosis (TUNEL/cleaved caspase-3), gliosis (GFAP/Iba1), and ultrastructural preservation. The evidence coalesces around a strikingly consistent signal: antioxidant strategies converge on smaller infarcts, robust preservation of neuronal markers, attenuation of apoptotic burden, dampened astroglial–microglial reactivity, and stabilization of mitochondrial and axonal architecture—patterns that align with antioxidative, anti-apoptotic, anti-inflammatory, and ferroptosis-modulating mechanisms. While early clinical data echo these benefits, translation is tempered by heterogeneity in models, timing and dosing windows, and outcome batteries. By consolidating the histological landscape and pinpointing where effects are durable versus contingent, this work elevates antioxidant peptide and small-molecule neuroprotection from promising fragments to an integrated framework and sets an actionable agenda—standardized histological endpoints, protocol harmonization, head-to-head comparisons of peptide versus small-molecule strategies, and adequately powered randomized trials embedded with mechanistic biomarkers to decisively test efficacy and accelerate clinical adoption. Full article

Background: Acorus calamus (sweet flag) is widely used in traditional medicine, yet its dermal safety profile remains insufficiently defined under modern regulatory standards. Objective: To comprehensively evaluate the skin irritation, corrosion, and sensitisation potential of A. calamus rhizome oil using new approach methodologies’ (NAMs) test batteries under GLP conditions. Results: The A. calamus rhizome oil was predicted as a Category 2 skin irritant, non-corrosive and GHS Category 1B skin sensitiser. Chemical analysis revealed β-asarone as the major constituent (~40.75%). The reconstructed human epidermis models established reversible irritation without corrosion. Mechanistic concordance across the Direct Peptide Reactivity Assay, KeratinoSens™, and Human Cell Line Activation Test showed activation of the three key events of the skin sensitisation adverse outcome pathway. Using the “2-out-of-3” Defined Approach with the KE 3/1 sequential strategy allowed for hazard classification into GHS Category 1B. Quantitative risk modelling using SARA-ICE models and SCCS parameters yielded conservative safe-use concentrations ranging from 0.13 to 0.78% (w/w) for leave-on products and up to 7.46% (w/w) for rinse-off formulations. Conclusions: The combined evidence from the NAM-based assays showed that A. calamus rhizome oil is a moderate sensitiser and irritant but not corrosive, providing critical data for risk assessment and regulatory decision-making, which was previously unknown. The SARA-ICE PoD-derived safe-use concentrations provide guidance for cosmetic formulators to ensure consumer safety, particularly in leave-on applications such as face and hand creams, where sensitisation risk is highest. This study demonstrates the utility of NAMs for botanical safety assessment and regulatory decision-making. Full article

Background/Objectives: Physical examination techniques are commonly used for the diagnosis and evaluation of Arteriosclerosis Obliterans (ASO). However, these methods do not objectively reflect the degree of claudication or functional impairment reported by patients. Moreover, standardized functional metrics to facilitate consistent clinical communication and prognostic assessments among healthcare providers are lacking. This study aimed to identify performance-based functional tests that enable quantitative assessment of symptoms and gait limitation in patients with ASO and to propose them as objective, reproducible clinical indicators. Methods: Fifty-six participants (27 patients with ASO and 29 healthy controls) underwent multiple functional tests, including the Five Times Sit-to-Stand Test (FTSS), six-minute walk test (SMWT), gait speed, Short Physical Performance Battery (SPPB), and grip strength. Test results were compared between the groups and evaluated against ankle-brachial index (ABI) values for diagnostic and functional relevance. Results: Patients with ASO demonstrated significantly lower SPPB scores, slower gait speed, longer FTSS times, and shorter SMWT distances than controls, whereas grip strength did not differ. Random forest and receiver operating characteristic analyses identified the FTSS, SMWT, and gait speed as significant predictors of ASO. Conclusions: The FTSS, SMWT, and gait speed are simple and clinically meaningful performance-based measures that can complement the ABI in the evaluation of ASO. Combining the FTSS with the SMWT and gait speed may provide a more comprehensive and reliable functional assessment and facilitate early screening, guide clinical decision-making, and enable objective evaluation of functional recovery before and after treatment, while improving patient self-assessment and communication among healthcare providers. Full article

Plastic greenhouses, which account for the majority of protected horticulture facilities in East Asia, are highly susceptible to wind-induced uplift failures that can lead to severe structural and economic damage. To address this issue, this study developed a low-power and low-cost wireless monitoring system applying the concept of structural health monitoring (SHM) to greenhouse foundations. Each sensor node integrates a MEMS-based inertial measurement unit (IMU) for attitude estimation, a LoRa module for long-range alert transmission, and a microSD module for data logging, while a gateway relays anomaly alerts to users through an IP network. Uplift tests were conducted on standard steel-pipe foundations commonly used in plastic greenhouses, and the proposed sensor nodes were evaluated alongside a commercial IMU to validate attitude estimation accuracy and anomaly detection performance. Despite the approximately 30-fold cost difference, comparable attitude estimation results were achieved. The system demonstrated low power consumption, confirming its feasibility for long-term operation using batteries or small solar cells. These results demonstrate the applicability of low-cost IMUs for real-time structural monitoring of lightweight greenhouse foundations. Full article

The increasing need for precise testing in battery and electronic component development has driven the demand for modular and scalable laboratory systems. This paper presents the design and initial implementation of a LabVIEW-based measurement system tailored for ISO/IEC 17025-compliant testing environments. The system’s software architecture is modular and built around a Hardware Abstraction Layer, enabling the integration of various remotely controlled instruments, such as programmable power supplies, electronic loads, and climate chambers. LabVIEW’s object-oriented programming and multi-threaded execution environment allows synchronized control and real-time data acquisition. Test procedures are defined using a JSON-based sequence structure, supporting repeatable testing. A graphical editor provides an intuitive interface for configuring test steps, ensuring ease of use. The system is designed to support future expansion, including high-speed measurement modules and parallel test execution. This solution lays the foundation for a reliable and extensible automated testing platform that aligns with modern industrial and regulatory standards. Full article

To achieve accurate estimates of a lithium-ion battery’s charge level (SOC) and health condition (SOH), this paper tackles key issues in battery management by introducing a framework built around an adaptive square root cubature Kalman filter (ASRCKF) that tracks parameters in real time for better performance in changing environments. It uses ASRCKF to gauge SOC, while an extended Kalman filter (EKF) identifies battery traits online and monitors capacity loss, with a two-way feedback system that feeds SOH updates directly into the SOC calculations. Testing in high-speed driving, the New European Driving Cycle, and urban stop–start conditions showed the method keeps average SOC errors to 0.16% at most and peak errors to 0.33%, beating out standard EKF and SRCKF approaches in accuracy; SOH errors averaged 0.42%. Overall, this setup proves reliable for combined SOC-SOH tracking in diverse real-world situations, helping to ensure safer battery operations. Full article

Background: Falls are a leading cause of injury and disability among older adults. Conventional clinical tests typically do not challenge reactive postural responses to unexpected perturbations, which limits their ability to comprehensively assess fall risk. Objective: To examine the test–retest reliability of five pragmatic, low-cost, perturbation-based tests designed to identify compensatory stepping strategies in older adults, and to explore their concurrent validity against established clinical assessments. Methods: Fifty-seven older adults (44 community-dwelling and 13 institutionalized) completed five compensatory stepping tests (obstacle crossing, forward push, backward pull, and lateral pulls to the right and left) and conventional functional tests [Timed Up and Go (TUG), 30 s Chair Stand, and the Short Physical Performance Battery (SPPB)] on two separate days, ten days apart. Cohen’s weighted kappa (Kw) quantified test–retest reliability, and Pearson’s correlation coefficients assessed relationships with conventional tests. Results: Obstacle (Kw = 0.443), forward push (Kw = 0.518), and backward pull (Kw = 0.438) demonstrated moderate agreement overall. Lateral pull tests showed poor reliability. Nevertheless, moderate correlations were observed between some perturbation tests (particularly obstacle and backward pull) and standard clinical measures, especially TUG and SPPB. Conclusions: Although reliability was limited—most notably for lateral perturbations—specific tests showed meaningful associations with validated functional assessments. Pending methodological refinements, these low-cost tools may offer useful insights for initial fall-risk screening. Full article

The rapid adoption of electric vehicles (BEVs) has increased the need to understand how fast-charging strategies influence long-distance travel times under real-world conditions. While most manufacturers specify maximum charging power and standardized driving ranges, these figures often fail to reflect actual highway operation, particularly in adverse weather. This study addresses this gap by analyzing the fast-charging behaviour, net battery capacity and highway energy consumption of 62 EVs from different market segments. Charging power curves were obtained experimentally at high-power DC stations, with data recorded through both the charging infrastructure and the vehicles’ battery management systems. Tests were conducted, under optimal conditions, between 10% and 90% state of charge (SoC), with additional sessions performed under both cold and preconditioned battery conditions to show thermal effects on the batteries’ fast-charging capabilities. Real-world highway consumption values were applied to simulate 1000 km journeys at 120 km/h under cold (−10 °C, cabin heating) and mild (23 °C, no AC) weather scenarios. An optimization model was developed to minimize total trip time by adjusting the number and duration of charging stops, including a 5 min detour for each charging session. Results show that the optimal charging cutoff point consistently emerges around 59% SoC, with a typical deviation of 10, regardless of ambient temperature. Charging beyond 70% SoC is generally inefficient unless dictated by charging station availability. The optimal strategy involves increasing the number of shorter stops—typically every 2–3 h of driving—thereby reducing total trip. Full article

The Educational Competition Optimizer (ECO) formulates search as a three-stage didactic process—primary, secondary and tertiary learning—but the original framework suffers from scarce information exchange, sluggish late-stage convergence and an unstable exploration–exploitation ratio. We present EECO, which introduces three synergistic mechanisms: a regenerative population strategy that uses the covariance matrix of elite solutions to maintain diversity, a Powell mechanism that accelerates exploitation within promising regions, and a trend-driven update that adaptively balances exploration and exploitation. EECO was evaluated on the 29 benchmark functions of CEC-2017 and nine real-world constrained engineering problems. Results show that EECO delivers higher solution accuracy and markedly smaller standard deviations than eight recent algorithms, including EDECO, ISGTOA, APSM-jSO, LSHADE-SPACMA, EOSMA, GLSRIME, EPSCA, and ESLPSO. Across the entire experimental battery, EECO consistently occupied the first place in the Friedman hierarchy: it attained average ranks of 2.138 in 10-D, 1.438 in 30-D, 1.207 in 50-D, and 1.345 in 100-D CEC-2017 benchmarks, together with 1.722 on the nine real-world engineering problems, corroborating its superior and dimension-scalable performance. The Wilcoxon rank sum test confirms the statistical significance of these improvements. With its remarkable convergence accuracy and reliable stability, EECO emerges as a promising variant of the ECO algorithm. Full article

Electrification of transport is advancing, yet debate continues over whether battery electric vehicles (EVs) are a like-for-like and affordable alternative to internal-combustion engine (ICE) cars. Positioned in a rapidly evolving mainstream market, this study examines structural similarity and relative pricing of EVs versus ICE models available in Poland in 2025. Data on 373 base passenger-car models (excluding hybrids) were analyzed using two clustering methods: k-means and k-medoids. The optimal number of clusters was determined by 23 validity indices, identifying three clusters. The significance of mean price differences between EVs and non-EVs within the specified clusters was tested using a permutation test. Results indicate no statistically meaningful EV price premium within clusters: no EV price exceeded two standard deviations above its cluster mean, and no cluster consisted exclusively of EVs, which points to strong technical similarity across powertrains. Additionally, permutation tests indicated no differences within clusters, except in the cluster with the best technical parameters, where non-EV cars were more expensive, which suggests that the premium segment of the market continues to be dominated by combustion cars. These findings, which show that electric vehicles are price-comparable to non-EVs, challenge the perception that EVs are systematically more expensive and demonstrate that, within market segments defined by technical characteristics. Therefore, the evidence suggests that EVs are becoming a genuine competitive alternative to ICE cars in the Polish market. Full article