Search Results (10,652)

This study addresses the problem of efficient utilization of aspiration dust (AD) generated during crushing of high-carbon ferrochrome (HCFeCr). To solve this issue, a briquetting technology was proposed, involving aspiration dust blended with dry gas-cleaning dust (20 wt.% as filler) and an organic polymer binder (3 wt.%). The produced briquettes demonstrated high mechanical strength (average 195 kg per briquette in splitting strength and 98% drop resistance), ensuring maximum integrity during transportation and handling. Pilot-industrial remelting of 35 tons of briquettes in a 1.8 MVA direct current electric arc furnace (DC EAF) confirmed the effectiveness of the proposed technology for HCFeCr production. Chromium recovery into the alloy reached 94%, which is 3–4% higher compared to remelting of loose dust. The specific electric energy consumption was 1600 kWh/t, representing a 29% reduction compared to loose dust processing. The produced metal met commercial grades FeCr800–FeCr900 specifications. Additional advantages included elimination of dust formation, reduction in fines generation during crushing of the final metal to 15%, and improved environmental performance. The developed technology represents an economically and environmentally viable solution for comprehensive recycling of ferroalloy dust waste. Full article

Side-scan sonar is essential to underwater target detection, yet its effectiveness is hindered by scarce annotated data and complex acoustic artifacts. This study systematically evaluates four YOLO variants, YOLOv8n, YOLOv10n, YOLOv11n, and the newly released YOLOv13n, on two public side-scan sonar datasets with limited samples and severe class imbalance. We assess detection accuracy, computational efficiency, inference speed, and transfer learning using COCO pre-trained weights, as well as the impact of optimizer choice between SGD and AdamW. The results reveal distinct strengths: YOLOv8n achieves the fastest inference at 60.98 FPS, with a competitive mAP50 of 0.906, ideal for real-time applications. YOLOv11n offers the best accuracy–efficiency balance, attaining the highest recall of 0.859 and mAP50 of 0.917. YOLOv13n demonstrates exceptional precision of 0.993 and high-IoU localization, with an mAP75 of 0.760. Transfer learning consistently boosts performance, with average mAP50:95 gains exceeding 54% on the more challenging dataset, highlighting its critical role in overcoming data scarcity. SGD generally outperforms AdamW, confirming its suitability as the default optimizer. These findings provide practical guidelines: YOLOv8 for real-time needs, YOLOv11 for balanced performance, and YOLOv13 for precision-critical tasks with ample resources. This work also establishes a benchmark for future underwater autonomous system research. Full article

The accumulation of copper smelting slags generated by non-ferrous metallurgy represents both an environmental challenge and a potential source of technogenic raw materials for value-added products. In this study, the feasibility of producing magnesia–quartz proppants from secondary copper smelting slag formed after the pyrometallurgical extraction of iron and zinc was investigated. The slag, primarily composed of oxides of the SiO₂–CaO–Al₂O₃–MgO system, was processed by centrifugal melt granulation to obtain spherical granules suitable for proppant applications. The initial granules exhibited an amorphous glassy structure and insufficient mechanical strength, with up to 70% of particles destroyed under a pressure of 34.5 MPa. Controlled heat treatment within the temperature range of 300–1000 °C induced crystallization of silicate and aluminosilicate phases, leading to a significant improvement in mechanical performance. Optimal properties were achieved after holding at 800 °C for 60 min, where the fraction of crushed granules decreased to 10%, meeting the requirements of GOST R 54571-2011. The influence of MgO content on microstructure and strength was also examined. Increasing the MgO concentration from 5 to 16 wt.% resulted in grain refinement and improved crushing resistance, reducing the fraction of destroyed granules to 3%. To enhance chemical durability, a phenol–formaldehyde protective coating was applied, decreasing proppant solubility in a hydrochloric–hydrofluoric acid mixture from 19% to 2%. These results demonstrate that secondary copper smelting slag can serve as a promising raw material for producing standard-compliant proppants while contributing to the efficient utilization of metallurgical waste. Full article

Aircraft noise monitoring systems deployed at major airports typically rely on scalar energy-based indicators, which primarily describe integrated sound energy but provide limited representation of the spectral–temporal structure and perceptual attributes of aircraft noise. To address this limitation, this study proposes a sensor-based psychoacoustic feature extraction and spatiotemporal analysis framework for continuous aircraft noise monitoring under high-density operational conditions. An automatic noise monitoring system compliant with ISO 20906 was deployed to synchronously acquire acoustic waveforms and ADS-B trajectory data. A cascaded spatiotemporal fusion algorithm was developed to associate noise events with aircraft flight paths, followed by a model-stratified multidimensional IQR-based data cleaning strategy to suppress environmental interference and non-stationary outliers. Based on the cleaned dataset, a suite of psychoacoustic features—including loudness, sharpness, roughness, fluctuation strength, and tonality—was extracted to characterize the perceptual structure of aircraft noise beyond conventional energy metrics. Experimental results demonstrate that, under equivalent sound exposure levels, psychoacoustic features retain substantial discriminative information that is lost in scalar energy indicators. The coefficients of variation for fluctuation strength and tonality reach 43.2% and 22.1%, respectively, corresponding to 15–69 times higher sensitivity compared to traditional energy-based metrics. Furthermore, nonlinear manifold mapping using UMAP reveals clear topological separation between new-generation and legacy aircraft models in the psychoacoustic feature space, whereas severe overlap persists in energy-based representations. Correlation analysis further indicates decoupling between macro-level physical design parameters (e.g., bypass ratio, thrust) and perceptual feature dimensions, highlighting the limitations of energy-centric monitoring schemes. The proposed framework demonstrates the feasibility of integrating psychoacoustic feature extraction into continuous sensor-based aircraft noise monitoring systems. It provides a scalable signal processing pipeline for enhancing the resolution and interpretability of aircraft noise measurements in complex operational environments. Full article

Zinc titanate (ZnTiO₃) is a chemically stable and non-toxic oxide perovskite whose photovoltaic potential remains largely unexplored due to its wide indirect bandgap. This study evaluates whether oxygen-vacancy (F-center) engineering can tailor its electronic structure and improve its suitability as a photovoltaic absorber. Density Functional Theory (DFT) calculations using VASP (PAW − GGA/PBE + U) were performed to evaluate structural stability, electronic properties, and electron affinity, while optical absorption was modeled through a combined Tauc–Gaussian approach. Device performance was assessed via SCAPS-1D simulations in an FTO/ZnO/ZnTiO₃/Spiro-OMeTAD architecture. Oxygen vacancies induce bandgap narrowing from ~2.96 eV to ~1.47 eV and generate Ti-3d-dominated donor-like and deep intragap states. The calculated electron affinity is ~3.77 eV. Simulated single-layer devices reach Voc ≈ 1.11 V, Jsc ≈ 8.27 mA·cm⁻², FF ≈ 83%, and a maximum efficiency of ~7.65%, primarily limited by moderate absorption strength and defect-assisted recombination. Multilayer configurations indicate that geometric optimization can significantly enhance projected efficiency, approaching 19.25% under idealized conditions. Although vacancy engineering extends visible-light absorption, the intrinsic indirect band-gap character constrains the ultimate photovoltaic performance of ZnTiO₃. Full article

Cellulose nanocrystals (CNCs) are highly desirable nanomaterials for reinforcing biopolymer films. Coconut husks are generated in massive quantities after harvesting and processing, leading to waste management issues. This study isolated and characterized CNCs from young (y-CNCs) and mature (m-CNCs) coconut husks via acid hydrolysis (32% H₂SO₄, 50 °C, 5 h), comparing them with commercial CNCs (c-CNCs) to evaluate their performance in gelatin-based films. TEM confirmed rod-shaped morphology for all CNCs. Notably, m-CNCs exhibited a smaller particle size (199 nm), a higher surface charge (−46.8 mV), and superior crystallinity (63.98%), demonstrating properties comparable to c-CNCs. FTIR and XRD confirmed characteristic cellulose functional groups and crystalline structure, while TGA demonstrated excellent thermal stability above 300 °C for all samples. Incorporation of CNCs into gelatin films significantly improved tensile strength (from 15.63 to 24.93 MPa) and reduced water vapor permeability (from 2.65 to 2.43 × 10⁻¹⁰ g m m⁻² s⁻¹ Pa⁻¹; p < 0.05). These findings demonstrate how coconut husk residues can be upcycled into high-value nanomaterials fostering economic growth with innovation in sustainable manufacturing. This research also promotes responsible waste utilization, highlighting the benefits of biodegradability and a reduced carbon footprint for sustainable food packaging applications. Full article

Background and Objectives: Cross-country skiing requires high levels of upper-body strength and efficient respiratory function to sustain performance during sport-specific movements. This study aimed to examine the effects of an eight-week ski ergometer-based training program on upper-extremity isokinetic muscle strength and pulmonary function in competitive cross-country skiers. Materials and Methods: A total of 20 cross-country skiers voluntarily participated in the study (experimental group: n = 10, control group: n = 10). The research was conducted using a quasi-experimental controlled design. During the eight-week training period, the experimental group performed ski ergometer training three times per week at an intensity of 80–90% of maximal heart rate, with a target distance of 2.5 km per session, in addition to their regular training program. Measurements were obtained before and after the intervention. Results: Following the ski ergometer training period, significant increases were observed in FVC (F = 18.565, p < 0.001, ηp² = 0.508) and FEV₁ (F = 8.789, p = 0.008, ηp² = 0.328), which were associated with enhanced respiratory muscle endurance and ventilatory capacity. Regarding the isokinetic strength parameters, the DPPE60 variable showed significant main effects of time (F = 33.770, p < 0.001, ηp² = 0.652) and time × group interaction (F = 18.590, p < 0.001, ηp² = 0.508), indicating higher upper-extremity strength values across the measurement period. Additionally, strong positive correlations were found between dominant and nondominant limbs (r = 0.79–0.92; p < 0.05), indicating balanced bilateral strength development and high neuromuscular coordination. Conclusions: Ski ergometer-based training was associated with improvements in upper-extremity peak power (DPPE60) and ventilatory capacity (FVC) beyond general training-related adaptations. These findings suggest that SkiErg training may be a useful complementary method for enhancing selected performance-related physiological parameters in cross-country skiers. Full article

Nonlinear structural analysis serves as a fundamental tool for accurately predicting structural bearing capacity and ultimate strength. The incremental-iterative solution scheme represents the prevailing methodology for tracing nonlinear load–displacement responses and is implemented in most commercial finite element software. To enhance the robustness and computational efficiency of existing schemes, this paper first revisits the incremental-iterative framework, providing a detailed analysis that clarifies the distinct roles of the load increment factor in the predictor and corrector phases. Subsequently, a novel framework of updated orthogonal iterative schemes (UOIS) is established. Within this framework, the current generalized stiffness parameter (CGSP) and a cumulative indicator S_i are introduced in the predictor phase to adaptively control the magnitude and sign of the load increment, respectively. In the corrector phase, four enhanced orthogonal iteration strategies are formulated. Furthermore, to improve computational efficiency, a novel acceleration strategy is proposed, which embeds a secant prediction operator in the predictor phase, thereby circumventing the costly assembly and inversion of the tangent stiffness matrix. The results demonstrate that: (1) compared to the conventional generalized stiffness parameter (GSP), the proposed CGSP exhibits superior stability in tracking stiffness variations, offering a more reliable indicator for adaptive step-size control; (2) the cumulative indicator S_i reliably identifies load limit points and accurately distinguishes between loading and unloading regimes; (3) the UOIS framework demonstrates strong convergence in tracing complex equilibrium paths with multiple critical points and exhibits significantly superior robustness under large increment sizes compared to the generalized displacement control method (GDCM); and (4) the secant-prediction acceleration strategy achieves substantial improvements in computational efficiency without compromising solution accuracy. Full article

This paper presents a comprehensive study on constructing exact and approximate solutions to Cauchy problems for time-fractional systems with variable coefficients. An innovative iterative approach is developed for solving functional equations with initial conditions, combining rigorous mathematical foundations with practical computational efficiency. The proposed technique effectively handles the nonlocal nature of fractional operators through a carefully designed iterative scheme that maintains simplicity while achieving high accuracy. It demonstrates particular strength in solving nonlinear systems with well-defined conditions and variable coefficients, where traditional methods often fail. Through systematic theoretical analysis and numerical validation, we establish the method’s convergence properties and computational advantages, showing its capability to generate both exact closed-form solutions, when available, and high-precision approximations otherwise. The approach remains computationally tractable even for complex cases where variable coefficients and memory effects of fractional systems present significant challenges to conventional solution approaches. Full article

Understanding the composition and amount of waste is crucial for the health and development of communities. Panic and the unpredictable situation of COVID-19 caused significant demands for food, which resulted in high pressure on food waste and waste management systems. To determine the change in waste composition in Northern Cyprus during the COVID-19 pandemic, questionnaires were prepared and distributed through the media and via email. This study found that household waste generation per capita was 0.91 kg with a 6% error when compared with a conventional waste composition study performed by the European Union in 2016. According to the results, the quantity of domestic waste decreased during the pandemic, while garden waste increased. Additionally, the results show that 27% of plastic waste came from cleaning purposes. As face mask usage and tea consumption increased during the pandemic, these materials were incorporated as additives into marble-dust-modified cement paste to develop sustainable construction composite. The mechanical performance of the proposed material was evaluated by measuring the flexural and compressive strengths of specimens cured for 7, 28, and 56 days. Eco-efficiency metrics derived directly from mechanical data provided strong environmental engineering insight. When assessed per unit of compressive function, cement intensity increased with mask dosage, indicating reduced binder efficiency despite batch-level cement savings. Furthermore, waste diversion per unit strength increased with mask content, but progressively larger compressive penalties accompanied this benefit. Within this trade-off, low to intermediate mask dosages offered the most validified balance between waste diversion and mechanical performance. Full article

This article presents the results of investigations into washed mineral waste (WMW) from grit chambers, fly ash generated during the thermal treatment of municipal sewage sludge (SSA), and their mixtures prepared in varying proportions. Their general physicochemical characteristics and heavy metal concentrations were presented. An experiment was conducted to assess the mobility of metals in the analyzed samples during extraction with distilled water and groundwater. The feasibility and safety of using the recovered materials in the ground environment, as soil backfills, and as materials for the construction of roads and flood embankments, were assessed. The feasibility of safely using materials in the indicated construction solutions was demonstrated for WMW and mixtures with a dominant WMW content. These results will be helpful in further research on solid waste applications. To the best of the authors’ knowledge, this study is the first to confirm the ecological safety of the analyzed wastes, as evidenced by assessments of heavy metal content and mobility. Furthermore, taking into account the laboratory and field costs associated with waste verification to obtain appropriate values for other physical and mechanical parameters (e.g., compaction index or shear strength), and the need to determine the level of waste contamination before practical application, the physicochemical tests carried out are economically justified. Full article

Clinical discharge summaries contain rich patient information but remain difficult to convert into structured representations for downstream analysis. Recent advances in large language models (LLMs) have introduced new approaches for clinical text extraction, yet their relative strengths compared with supervised methods remain unclear. This study presents a controlled evaluation of three dominant strategies for structured clinical information extraction from electronic health records: prompting-based extraction using LLMs, retrieval-augmented generation for terminology canonicalization, and supervised fine-tuning of domain-specific transformer models. Using discharge summaries from the MIMIC-IV dataset, we compare zero-shot, few-shot, and verification-based prompting across closed-source and open-source LLMs, evaluate retrieval-augmented canonicalization as a post-processing mechanism, and benchmark these methods against a fine-tuned BioClinicalBERT model. Performance is assessed using a multi-level evaluation framework that combines exact matching, fuzzy lexical matching, and semantic assessment via an LLM-based judge. The results reveal clear tradeoffs across approaches: prompting achieves strong semantic correctness with minimal supervision, retrieval augmentation improves terminology consistency without expanding extraction coverage, and supervised fine-tuning yields the highest overall accuracy when labeled data are available. Across all methods, we observe a consistent $40-50\%$ gap between exact-match and semantic correctness, highlighting the limitations of string-based metrics for clinical Natural Language Processing (NLP). These findings provide practical guidance for selecting extraction strategies under varying resource constraints and emphasize the importance of evaluation methodologies that reflect clinical equivalence rather than surface-form similarity. Full article

This study developed a biomimetic jumping robot inspired by frogs to enhance its obstacle-crossing capabilities. The biological principles underlying the jumping biomechanics of frog hindlimbs were integrated into the robotic mechanism; quantitative analysis of the bionic structure and its jumping performance not only provides mechanical engineering insights for investigating frog locomotion mechanics but also offers practical design references for the development of biomimetic mobile robots. Through theoretical calculations and application scenario analysis, a six-bar linkage mechanism was designed to simulate the force generation of frog hindlimbs, with tension springs mimicking the elastic energy storage function of the semimembranosus and gastrocnemius muscles. A reducer was integrated into the trunk to enable energy storage, and an adjustable single-hinge structure was adopted for the forelegs to realize take-off angle adjustment and shock absorption. Finite element simulations were conducted to validate the load-bearing capacity and strength of critical components. Multi-body dynamics and the particle swarm optimization (PSO) algorithm were employed to explore the relationship between input parameters and output performance metrics (jumping height and jumping distance), while orthogonal experimental analysis was used for comprehensive parameter evaluation. Finally, a physical prototype was fabricated, and its performance parameters were tested. The prototype has a mass of 150 g, generates a ground push force of 50 N, attains a jumping height of 380 mm, and achieves a maximum jumping distance of 500 mm. This study establishes a biologically inspired working principle for jumping robots and provides a novel practical prototype for research into biomimetic mobile robots. Full article

Background/Objectives: Drug repurposing represents a promising strategy to expand therapeutic options for inflammatory bowel disease (IBD), a chronic condition with persistent unmet clinical needs. This study aimed to identify existing drugs with potential relevance for IBD by exploring inverse associations in the FDA Adverse Event Reporting System (FAERS) as a hypothesis-generating, real-world data approach. Methods: In this retrospective observational pharmacovigilance study, drug–IBD associations were extracted from the FAERS database using OpenVigil 2.1. Inverse associations were identified based on reporting odds ratios (ROR) < 1 with adjusted p-values < 0.05. Identified drug–event pairs were further evaluated for pharmacokinetic feasibility, clinical applicability, and biological plausibility in the context of IBD, with the exclusion of drugs with implausible indications, contraindications, or mechanisms inconsistent with IBD pathophysiology. Given the immune-mediated nature of IBD and the breadth of the identified candidates, detailed evaluation focused on immunomodulatory agents. Results: Among the 3585 initial drug–IBD combinations, 73 candidates met the predefined criteria for statistical significance and feasibility. From these, nine drugs were prioritized based on inverse signal strength and mechanistic relevance to immune modulation pathways implicated in IBD. The strongest inverse association with IBD was observed for lenalidomide (ROR 0.056, 95% CI 0.043–0.073), followed by dupilumab (ROR 0.213, 95% CI 0.185–0.245), cyclophosphamide (ROR 0.215, 95% CI 0.175–0.265), fingolimod (ROR 0.216, 95% CI 0.205–0.334), dimethyl fumarate (ROR 0.332, 95% CI 0.275–0.400), apremilast (ROR 0.357, 95% CI 0.296–0.431), imatinib (ROR 0.423, 95% CI 0.339–0.527), glatiramer acetate (ROR 0.446, 95% CI 0.352–0.565), and interferon beta-1a (ROR 0.594, 95% CI 0.533–0.662). These agents possess immunomodulatory properties relevant to inflammatory pathways implicated in IBD; however, clinical evidence supporting the therapeutic efficacy of some candidates remains variable or incomplete. Conclusions: By integrating inverse signal detection with clinical and biological assessment, this study demonstrates how pharmacovigilance data can be extended from traditional safety surveillance toward systematic drug repurposing applications. The findings generate testable hypotheses and highlight candidate therapies that warrant further experimental and clinical investigation in IBD. Full article

In this study, the comparative residual performance of fire-exposed reinforced concrete (RC) beams with rectangular and T-shaped cross-sections is investigated. Two concrete beams, one with a T-section and the other with a rectangular section, were tested under the combined effects of fire exposure and structural loading. Data generated in the tests during and following fire exposure is utilized to compare the thermal and structural response of the beams. The results indicate a notable difference in the temperature evolution, mid-span deflection, and the residual capacity of the beams. The T-beam experienced greater deflection and stiffness degradation due to its larger exposed surface area (approximately 17% higher than the rectangular beam) and flange geometry, despite comparable peak rebar temperatures. A simplified approach, based on the maximum concrete and rebar temperatures and corresponding strength reductions, is proposed to evaluate the residual capacity of fire-exposed RC beams. For equal cover depth to reinforcement, peak rebar temperature is unaffected by cross-section shape as long as the web of the T-beam is not slender. T-shaped beams with similar overall depth exhibit greater post-fire strength retention than rectangular beams when the neutral axis lies within the flange. A 20% reduction in the web thickness and a combined reduction of 20% in web and 37% in flange thickness result in a comparable decrease in the flexural capacity to that of the rectangular beams of similar depth, indicating that the flange plays a key role in maintaining post-fire performance. Full article