Search Results (816)

The compression deformation of seed cotton has been identified as a key factor affecting the working reliability of the baling device and the quality of bale molding. However, due to the complex working conditions of seed cotton in the continuous compression process in a confined space, it has proven to be difficult to study the compression molding mechanism of machine-harvested seed cotton in the baling process. The present study employs a universal testing machine to compress the seed cotton. In addition, pressure sensors are utilised to ascertain the internal axial load transfer law of the seed cotton. Furthermore, the internal density distribution equation of the seed cotton is established. Moreover, the Fiber model is employed to establish a spatial helix structure model of the cotton fibre. Finally, the compression simulation test is conducted to calibrate its material parameters. The results of the study indicate that seed cotton exhibits hysteresis in its internal stress–strain transfer. Through the polynomial fitting of the compression–displacement curve, it has been demonstrated that as the seed cotton approaches the compressed side, the rate of change in compression increases. The internal density distribution of the seed cotton must be calculated when it is compressed to a density of 220 kg·m⁻³. It is found that the density of the upper layer of the seed cotton is slightly greater than that of the lower layer of the seed cotton. The density distribution equation must then be obtained through regression fitting. The parameters of the compression model must be calibrated by means of uniaxial compression tests. Finally, the density distribution equation of the cotton fibre must be obtained through the compression test. The parameters of the simulation model, as determined by the uniaxial compression test calibration, are of significant importance. This is particularly evident in the context of the Poisson’s ratio of cotton fibre and the cotton fibre elastic modulus under pressure. The regression equation was obtained through analysis of variance, and the simulation of contact parameter optimisation. The optimal parameter combination was determined to be 0.466, and the pressure at this time. The relative error was found to be 2.96%, and the compression of specific performance was determined to be 10.14%. These findings serve to validate the simulation model. The findings of this study have the potential to provide a theoretical foundation and simulation assistance for the design and optimisation of cotton picker baling devices. Full article

Objectives: Shoulder joint strength and muscle activation during overhead reaching are critical for ergonomic task design, rehabilitation, and exoskeleton support. The objective of this study was to characterize maximum shoulder torque and flexor muscle activation profiles across functional elevation angles in healthy adult males. Methods: A total of 14 healthy male participants performed maximum voluntary isometric contractions at eight arm elevation angles (90–160°, sagittal plane, and standing). Shoulder torque was measured using a calibrated force sensor and normalized to each participant’s overall maximum. Electromyography (EMG) was recorded from the anterior deltoid, medial deltoid, biceps brachii, and clavicular pectoralis major; EMG for the medial deltoid, biceps brachii, and pectoralis major was normalized to muscle-specific isometric MVCs, whereas the anterior deltoid was normalized to the peak value at 90° during the main task. All EMG signals were smoothed using a 0.5 s RMS-based moving average window. Linear regression was used to analyze the torque–angle relationship, and linear mixed-effects models were used to test EMG differences across angles. Summary statistics included mean ± SD, coefficient of variation, R², p-values (significance threshold: p < 0.05), Cohen’s d, and 95% confidence intervals where appropriate. Results: Maximum torque declined with elevation angle (y = −0.6317x + 157.21; R² = 0.99), from 77.2 Nm at 90° to 43.2 Nm at 160°, with normalized values from 99.6% to 55.3%. Medial deltoid activation increased significantly with elevation (p < 0.001, from 87.5 ± 19.9% at 90° to 109.4 ± 25.6% at 150°), while pectoralis major declined sharply (p < 0.001, from 68.9 ± 24.2% at 90° to 19.8 ± 5.6% at 160°). Anterior deltoid and biceps brachii activations were high and showed no systematic change with angle (p = 0.37 and 0.81, respectively), remaining within approximately 95–102% and 70–85% of their reference levels across 90–160°. Normalization reduced inter-participant variability, clarifying muscle-specific trends. Conclusions: This study provides preliminary biomechanical reference values for shoulder torque and muscle activation across elevation angles in healthy males under isometric standing conditions, confirming an inverse torque–angle relationship and distinct muscle activation strategies at higher positions. These findings may inform ergonomic assessment and exoskeleton design, while recognizing that generalization to dynamic tasks and other populations requires caution. Full article

(1) Background: As an innovative drug derived from botulinum neurotoxin serotype E, TrenibotulinumtoxinE^® demonstrates a rapid onset and shorter effect. Due to concerns regarding specificity, test throughput, and animal welfare, a new cell-based potency assay (CBPA) method was developed for BoNT/E drug substance and drug product; independent evaluation of this new CBPA was required. (2) Methods: The CBPA for BoNT/E is a quantitative assay that measures the accumulated cleaved SNAP25₁₈₀ in human neuroblastoma cells. It involves sequential culturing, differentiation of cells, and then treatment with drug products. Data were analyzed using a quadratic parallel model via statistical software. Linearity was determined using five effective concentration levels. Key assay parameters including accuracy, linearity, repeatability, intermediate precision and range were evaluated. (3) Results: The overall assay’s accuracy was 98%, and the intermediate precision was 6.3%. The coefficient of determination (R²) and slope were determined as 0.963 and 0.942, respectively. The root mean squared error (RMSE) was 0.057, and the intercept was 0.032 for the combined data. The repeatability was 2.4%, which is well within the acceptance criterion of ≤8%. (4) Conclusions: The evaluation was carried out within a single laboratory under controlled conditions; the new CBPA meets all acceptance criteria and can be used for BoNT/E potency determination. Full article

Brake particulate matter (PM) represents a significant portion of the non-exhaust related soot emissions from all forms of transport, posing significant environmental and health concerns. Euro 7 standards only regulate road automotive emissions, while no regulation covers train transportation. This study compares two brake PM samples from rail and automotive applications. Rail brake PM was generated from composite brake pads subjected to real-world urban rapid transit braking conditions, while automotive brake PM was generated using ECE brake pads and discs under World Harmonized Light-Duty Test Cycle (WLTC) conditions. Transmission electron microscopy (TEM) and energy-dispersive X-ray (EDX) analyses were performed to assess PM morphology and composition. Both samples showed PM in coarse (10–2.5 µm), fine (2.5–0.1 µm), and ultrafine (<0.1 µm) size ranges, with angular flakes in automotive PM and rounded particles in rail PM. The rail PM exhibited a uniform size distribution, with a mean Feret diameter of 1 µm. In contrast, the automotive PM shifted toward larger particles, with ultrafine PM representing only 4% of the population. Excluding carbon and oxygen, automotive PM was dominated by iron (6 at.%) and magnesium (1 at.%). Rail PM showed lower iron (0.6 at.%) and higher aluminium (0.7 at.%) and calcium (0.8 at.%), with a broader non-C/O composition. This study tackles source-specific PM features, thereby supporting safer and more efficient non-exhaust emissions regulations. Full article

In the modern globalized context, innovation represents a key driver of economic growth, while international trade plays an important role in fostering it. This study examines the relationship between the degree of trade openness and innovation performance across 27 EU member states over the period 2018–2024. The period under review covers the COVID-19 pandemic. The data were analyzed using dynamic cluster analysis (K-means). In addition to simple linear regression, FE mixed-model analysis (REML) was also used to test the robustness of relationships. Dynamic cluster analysis from the perspective of trade openness and innovation identified three statistically significant and stable heterogeneous groups of countries—innovation leaders, emerging economies and countries with high economic openness. The mixed model included the variables trade-to-GDP, R&D expenditure, digitalization and GDP. The results confirmed a statistically significant positive relationship between trade openness and innovation performance in EU countries. The findings show a significant positive impact of Trade-to-GDP, digitalization and R&D expenditure (triple interaction) on innovation rates as a synergistic innovation effect. The findings highlight that the impact of trade openness on innovation is heterogeneous and conditioned by other specific factors, thus requiring differentiated innovation and trade policies within the European Union. Innovation policies should optimize all parameters influencing innovation and exploit their synergistic effect. Full article

Aircraft with a twin vertical tail and leading-edge extension configuration may experience vertical tail buffeting during high-angle-of-attack maneuvering flight. This issue can lead to structural fatigue damage in the vertical tail, shortening its service life and increasing maintenance costs, ultimately compromising flight safety. Therefore, accurate prediction of buffeting loads and responses is essential during design. In the preliminary stage, wind tunnel testing is the primary means to obtain dynamic data such as fluctuating pressure and acceleration response, which can be transformed to full-scale conditions through similitude principles. However, the elastic scaling model used in buffeting tests is usually established for a specific flight condition. When the flow velocity or objective flight condition changes, the similitude relationship becomes invalid, limiting the applicability of test results and preventing full-envelope strength verification. To overcome this limitation, this study proposes a multi-objective point response prediction method for vertical tail buffeting. The method enables the prediction of full-scale responses at multiple objective flight conditions using wind tunnel data that do not strictly satisfy similitude criteria. A complete aircraft vertical tail buffet (rigid/elastic) hybrid model was developed for testing, and an Adjusted Model incorporating elastic scaling transformation was established. The proposed method was validated through experiments, demonstrating improved test data utilization and prediction accuracy across multiple-objective flight conditions. Full article

Background/Objectives: Candida biofilms exhibit high resistance to antifungal treatment, motivating investigation of adjunctive physical disinfection methods. To quantitatively assess the effect of Er:YAG laser fluence on growth inhibition and viability of single-species Candida biofilms in vitro using a 7 mm full-beam handpiece. Methods: Biofilms of Candida albicans ATCC 10231, C. glabrata ATCC 90030, C. parapsilosis ATCC 22019, and C. krusei ATCC 6258 were grown on Sabouraud agar. In phase 1, growth inhibition zones (GIZs) were evaluated after non-contact Er:YAG irradiation (2 Hz, 300 µs, 10 mm distance, no air or water spray) at fluences from 0.3 to 3.4 J/cm², with incubation for 24 to 96 h. In phase 2, 96 h mature biofilms were irradiated for 120 s at 0.8, 1.0, 1.5, or 2.0 J/cm², and viability was quantified by colony-forming unit (CFU) imprinting. All experimental conditions were tested in quadruplicate. Results: GIZ diameters increased significantly with fluence for all species (p < 0.05) and remained stable up to 96 h. At the highest fluence, mean GIZs reached approximately 8.0 mm for C. albicans, 7.7 mm for C. parapsilosis, 7.0 mm for C. krusei, and 5.2 mm for C. glaxfbrata. In mature biofilms, CFU counts decreased significantly with increasing fluence (p < 0.05). For C. albicans, CFUs were reduced from 164.0 ± 25.1 at 0.8 J/cm² to 16.5 ± 5.2 at 2.0 J/cm², while C. glabrata decreased from 103.5 ± 5.4 to 20.8 ± 1.7. C. parapsilosis and C. krusei showed maximal reductions at 1.0–1.5 J/cm², followed by partial CFU rebound at 2.0 J/cm². Conclusions: Er:YAG irradiation delivered over a large, uniformly illuminated area induces stable, fluence-dependent inhibition and significant reduction of Candida biofilm viability in vitro. Optimal fluence ranges are species specific, underscoring the need for parameter optimization and further evaluation in more complex biofilm models before clinical extrapolation. Full article

To prevent swine fever transmission, swine farms in China adopt enclosed management, making strict farm personnel biosecurity essential for minimizing the risk of pathogen introduction. However, current shower-in procedures and personnel movement records on many farms still rely on manual logging, which is prone to omissions and cannot support enterprise-level supervision. To address these limitations, this study develops a digital personnel management system designed specifically for the changing-room environment that forms the core biosecurity barrier. The proposed three-tier architecture integrates distributed identification terminals, local central controllers, and a cloud-based data platform. The system ensures reliable identity verification, synchronizes templates across terminals, and maintains continuous data availability, even in unstable network conditions. Fingerprint-based identity validation and a lightweight CAN-based communication mechanism were implemented to ensure robust operation in electrically noisy livestock facilities. System performance was evaluated through recognition tests, multi-frame template transmission experiments, and high-load CAN/MQTT communication tests. The system achieved a 91.4% overall verification success rate, lossless transmission of multi-frame fingerprint templates, and stable end-to-end communication, with mean CAN-bus processing delays of 99.96 ms and cloud-processing delays below 70.7 ms. These results demonstrate that the proposed system provides a reliable digital alternative to manual personnel movement records and shower duration, offering a scalable foundation for biosecurity supervision. While the present implementation focuses on identity verification, data synchronization, and calculating shower duration based on the interval between check-ins, the system architecture can be extended to support movement path enforcement and integration with wider biosecurity infrastructures. Full article

This study compared the external [movement load (ML)] and internal [rating of perceived exertion (RPE), mean and peak heart rate (HRmean, HRpeak)] loads, performance and enjoyment between time-matched (~12 min) traditional (TRAD) and small-sided game (SSG) warm-ups in youth basketball players. Using a counterbalanced crossover design, 24 male players (16.0 ± 0.1 years) performed both warm-up types after reporting fatigue (ROF) and completing an 8 min standardized pre-warm-up. Before and after each warm-up, players completed 20 m sprint and countermovement jump (CMJ) tests; enjoyment (ENJ) was assessed post-warm-up. No significant differences were found between warm-ups for ROF (p = 0.053), RPE (p = 0.259), or HRmean (p = 0.053). However, SSG induced a higher HRpeak than TRAD (p = 0.001), while ML was greater in TRAD (p < 0.001). No interaction, time effect, or typology effect emerged for performance in sprinting and change of direction, although CMJ was higher after TRAD (p = 0.047). Enjoyment did not differ significantly (p = 0.066), although with a large effect size (r = 0.612). The greater ML in TRAD may reflect more dynamic basketball actions compared with SSG, which emphasized static tasks (e.g., screening, boxing out) yet produced higher HRpeak. Coaches may consider SSG warm-ups to replicate game-specific conditions while controlling the external load and maintaining adequate physiological preparation. Full article

Building placement strongly conditions performance, experience, and meaning in architecture and urban planning, yet siting rationales in design studio work are rarely made explicit or examined systematically. This post hoc, observational study analyzes 22 student proposals for a paddle school on a defended coastal headland in Cascais, Portugal, to reveal siting patterns and test convergence toward an expert recommendation. Each project is mapped onto a common grid and encoded as building mass and external paths, and a site-specific expert prior is formalized as a polygon that follows the defended wall and upper terrace, combining edge protection, elevation, and ocean prospect. Alignment with this prior is assessed using exact permutation tests under uniform and elevation-stratified random siting, and each proposal is summarized by three descriptors that capture where mass concentrates, how far it extends, and how broadly it uses the site. Results show a pronounced nucleus along the upper terrace, a contour-parallel circulation spine, and extensive underused areas elsewhere, with alignment to the expert prior significantly above chance. Clustering projects by the three descriptors differentiates siting families, from edge-anchored schemes to prospect-led variants and a small set of deliberate counterexamples. The framework turns studio designs into auditable evidence of how cohorts occupy a site and makes siting heuristics explicit and testable, supporting more transparent discussion of site strategies in architectural education and informing practice-oriented design guidance. Full article

Dynamic loads on a vehicle’s running gear generated when driving over uneven roads or surfaces have a destructive effect on its components and, consequently, on the vehicle’s reliability. Special vehicles, especially off-road vehicles, are operated differently from traditional vehicles. Deformable surfaces can induce significant dynamic loads on vehicle running gear components even at low speeds, significantly limiting safe driving speeds. This article presents experimental vehicle tests conducted on four test track sections at three predefined vehicle speeds (10, 20, and 30 km/h). The experimental results demonstrate a clear dependence of dynamic loads on the off-road vehicle’s speed on dirt surfaces. Differences were observed between the measurement sections, suggesting that standard road profile metrics (e.g., RMS (Root Mean Square) profile height change) do not fully predict actual loads, requiring continuous monitoring of vehicle operating conditions. Compared to paved roads, where loads are more predictable, ground surfaces generate unique vibration patterns even at low driving speeds. RMS values for the measurement sections ranged from 0.02 to 0.06 m. Therefore, it is necessary to adapt test methods to specific ground conditions, with driving speed as a key research parameter. Full article

This study presents the first systematic investigation into the influence of spectral enhancement techniques on the segmentation accuracy of specific soil and vegetation marks associated with palaeochannels. These marks are often subtle and can be seasonally obscured by vegetation dynamics and soil variability. Spectral enhancement methods, such as spectral indices and statistical aggregations, are routinely applied to improve their visual discriminability and interpretability. Despite recent progress in automated detection workflows, no prior research has rigorously quantified the effects of these enhancement techniques on the performance of deep learning–based segmentation models. This gap at the intersection of remote sensing and AI-driven analysis is critical, as addressing it is essential for improving the accuracy, efficiency, and scalability of subsurface feature detection across large and heterogeneous landscapes. In this study, two state-of-the-art deep learning architectures, U-Net and YOLOv8, were trained and tested to assess the influence of these spectral transformations on model performance, using Sentinel-2 imagery acquired across three seasonal windows. Across all experiments, spectral enhancement techniques led to clear improvements in segmentation accuracy compared with raw multispectral inputs. The multi-temporal Median Visualisation (MV) composite provided the most stable performance overall, achieving mean IoU values of 0.22 ± 0.02 in April, 0.07 ± 0.03 in August, and 0.19 ± 0.03 in November for U-Net, outperforming the full 12-band Sentinel-2 stack, which reached only 0.04, 0.02, and 0.03 in the same periods. FCC and VBB also performed competitively, e.g., FCC reached 0.21 ± 0.02 (April) and VBB 0.18 ± 0.03 (April), showing that compact three-band enhancements consistently exceed the segmentation quality obtained from using all spectral bands. Performance varied with environmental conditions, with April yielding the highest accuracy, while August remained challenging across all methods. These results highlight the importance of seasonally informed spectral preprocessing and establish an empirical benchmark for integrating enhancement techniques into AI-based archaeological and geomorphological prospection workflows. Full article

Electroencephalography (EEG)-based brain–computer interface (BCI) mimics the brain’s intrinsic information-processing mechanisms by translating neural oscillations into actionable commands. In motor imagery (MI) BCI, imagined movements evoke characteristic patterns over the sensorimotor cortex, forming a biomimetic channel through which internal motor intentions are decoded. However, this biomimetic interaction is highly vulnerable to signal degradation, particularly in mobile or low-resource environments where low sampling frequencies obscure these MI-related oscillations. To address this limitation, we propose a robust MI classification framework that integrates spatial, spectral, and temporal dynamics through a filter bank common spatial pattern with time segmentation (FBCSP-TS). This framework classifies motor imagery tasks into four classes (left hand, right hand, foot, and tongue), segments EEG signals into overlapping time domains, and extracts frequency-specific spatial features across multiple subbands. Segment-level predictions are combined via soft voting, reflecting the brain’s distributed integration of information and enhancing resilience to transient noise and localized artifacts. Experiments performed on BCI Competition IV datasets 2a (250 Hz) and 1 (100 Hz) demonstrate that FBCSP-TS outperforms CSP and FBCSP. A paired t-test confirms that accuracy at 110 Hz is not significantly different from that at 250 Hz (p < 0.05), supporting the robustness of the proposed framework. Optimal temporal parameters (window length = 3.5 s, moving length = 0.5 s) further stabilize transient-signal capture and improve SNR. External validation yielded a mean accuracy of 0.809 ± 0.092 and Cohen’s kappa of 0.619 ± 0.184, confirming strong generalizability. By preserving MI-relevant neural patterns under degraded conditions, this framework advances practical, biomimetic BCI suitable for wearable and real-world deployment. Full article

Background: Migraine is a highly prevalent neurological disorder and a leading cause of disability, particularly among working-age adults. Although the Work Productivity and Activity Impairment (WPAI) questionnaire is widely used to assess the functional impact of health conditions, no validated Arabic version specific to migraine is currently available. This study was conducted to validate the Arabic version of the WPAI:Migraine questionnaire among Arabic-speaking migraine patients in Saudi Arabia. Methods: A cross-sectional psychometric validation study was conducted at a tertiary headache clinic between June 2023 and January 2024. Adult patients diagnosed with episodic or chronic migraine, based on the International Classification of Headache Disorders, 3rd edition (ICHD-3), completed the Arabic version of the WPAI:Migraine and the validated Arabic version of the Migraine Disability Assessment Scale (MIDAS). Test–retest reliability was assessed after two weeks. Psychometric properties, including reliability, criterion validity, and known-group validity, were evaluated using intraclass correlation coefficients (ICCs), Pearson’s and Spearman’s correlations, and one-way ANOVA. Results: Eighty-two patients completed the study (76.8% female; mean age 38 ± 11 years). The Arabic WPAI:Migraine questionnaire demonstrated substantial-to-almost-perfect test–retest reliability (ICC range: 0.68–0.84). WPAI:Migraine domain scores correlated significantly with MIDAS scores—particularly for activity impairment (r = 0.576), presenteeism (r = 0.526), and absenteeism (r = 0.522)—and increased consistently across MIDAS disability grades, supporting validity. Conclusions: The Arabic WPAI:Migraine questionnaire is a valid and reliable instrument for assessing work productivity and activity impairment among Arabic-speaking migraine patients, suitable for clinical and research use. Full article

Soft and weak rocks present challenges for construction activities in various environments. Their genetic origin, geological and tectonic evolution, and exposure to atmospheric conditions control their weathering and degradation over time. Therefore, a sound characterization of the associated rock parameters is essential. Numerous tests have been developed and standardized or defined in recommendations to assess various geomechanical, petrological, and mineralogical parameters. However, these tests are still subject to modification or extension to address project-specific issues. Additionally, standardized tests do not consider regional climatic conditions that may affect weathering, meaning they do not reflect the degradation behavior that is observed in the field. The present study investigates the slaking resistance and degradability of a range of soft rocks. The workflow of widely used tests is employed to evaluate their representativeness for different rock types in practical applications. Depending on their genetic origin and mineral composition, fabric alterations affect the rate and style of rock disintegration differently. Soft sedimentary rocks react already to static slaking, i.e., water immersion, whereas crystalline and grain-bound rocks slake under dynamic action while undergoing attrition in a rotating slake durability drum. Zones of structural weakness, such as foliation planes, are responsible for material removal in the latter; sedimentary rocks, on the other hand, are subject to surface particle separation (suspension) and suction due to the presence of clay minerals. This study presents an approach that combines the results of several routine tests to help identify and refine the slaking susceptibility of different rock types. A routine for inspecting and documenting the evaluated slaking characteristics for infrastructure maintenance is proposed, and the wider implications in light of climate change are discussed. Some limitations of the transferability of laboratory values to field sites still have to be evaluated and validated in the future. Full article