Search Results (7,443)

High-performance musical instrument training is a demanding discipline that engages cognitive, neurological, and physical skills. Professional musicians invest substantial time and effort into mastering their repertoire and developing the muscle memory and reflexes required to perform complex works in high-stakes settings. While existing surveys have explored the use of music in therapeutic and general training contexts, there is a notable lack of work focused specifically on the needs of professional musicians and advanced instrumental practice. This topical review explores the potential of EEG-based brain–computer interface (BCI) technologies to integrate real-time feedback of biomechanic and cognitive features in advanced musical practice. Building on a conceptual framework of technology-enhanced musical practice (TEMP), we review empirical studies of broad contexts, addressing the EEG signal decoding of biomechanic and cognitive tasks that closely relates to the specified TEMP features (movement and muscle activity, posture and balance, fine motor movements and dexterity, breathing control, head and facial movement, movement intention, tempo processing, ptich recognition, and cognitive engagement), assessing their feasibility and limitations. Our analysis highlights current gaps and provides a foundation for future development of BCI-supported musical training systems to support high-performance instrumental practice. Full article

Situated at the intersection of social history and psychology, this study examines how early Christian communities in Bithynia-Pontus navigated the persecution narrated in Pliny the Younger’s Epistle X 96. Through systematic textual analysis of Latin and Greek sources—triangulated with comparative evidence from Tacitus and corroborating archaeological data—and interpreted through Conservation-of-Resources and Social Identity theoretical frameworks, we reconstruct the repertoire of collective coping strategies mobilised under Roman repression. Our findings show that ritualised dawn assemblies, mutual economic assistance, and a theologically grounded expectation of post-mortem vindication converted external coercion into internal cohesion; these practices neutralised informer threat, sustained group morale, and ultimately expanded Christian networks across Asia Minor. Moreover, Pliny’s ad hoc judicial improvisations reveal the governor’s own bounded rationality, underscoring the reciprocal nature of stress between the persecutor and persecuted. By mapping the dynamic interaction between imperial policy and subaltern agency, the article clarifies why limited, locally triggered violence consolidated rather than extinguished the nascent movement. The analysis contributes a theoretically informed, evidence-based account of religious-minority resilience, enriching both early Christian historiography and broader debates on group survival under systemic duress. Full article

This review synthesizes research on smart insole prototypes and their designs, focusing on those incorporating artificial intelligence (AI) and a wireless communication/transmission system. The main objective of this work is to summarize existing studies, identify key trends, evaluate the performance of these innovative biomechanical tools, and recognize the factors that could lead to optimization. This comprehensive analysis includes studies from PubMed, Scopus, and Web of Science databases and other investigations on the critical themes to consider. It follows strict inclusion and exclusion criteria, ensuring the quality and accuracy of the overview. The findings emphasize significant progress in smart insoles, particularly in AI-enhanced prototypes, while addressing existing challenges and problems. This review helps guide potential future research and define practical application directions. The growing importance of biomechanics, especially on smart insoles, underscores the considerable potential of these innovations to monitor and improve human movement in both clinical and non-clinical settings, promising a future of more effective and personalized health and performance interventions. This protocol was registered with the International Platform of Registered Systematic Review and Meta-Analysis Protocols (INPLASY) on 6 February 2025 and was last updated on 6 February 2025. Full article

The utilization of ocean wave energy through environmentally sustainable technologies plays a pivotal role in the transition toward renewable energy sources. Among such technologies, the Submerged Horizontal Plate (SHP) stands out as a viable option for clean power production. This study focuses on the system’s application in a region on the southern coast of Brazil, identified as a potential site for future installation. To investigate this system, a three-dimensional numerical wave tank was developed to simulate wave behavior and hydrodynamic loads using the Navier–Stokes framework in the computational fluid dynamics software ANSYS FLUENT 2022 R2. The volume of fluid approach was adopted to track the free surface. The setup for wave generation in the numerical wave tank was verified against analytical solutions to ensure precision and validated under the SHP’s non-oscillating condition. To represent the oscillating condition, boundary conditions constrained motion along the x- and y-axes, allowing movement exclusively along the z-axis. A parametric analysis of 54 cases, with varying geometric configurations, wave characteristics, and submersion depths, indicated that the oscillating SHP configuration elongated perpendicular to wave propagation, combined with specific wave conditions, achieved a theoretical mean efficiency of 76.61%. Full article

The integration of technology in the classroom should be based on low-cost devices and affordable solutions, allowing educators to fully explore their potential benefits. Product design education is undergoing a profound transformation in response to these changes. The aim of this study is to demonstrate the integration of low-cost eye-tracking (ET) technology within a product design process. This research presents a practical case involving a group of design students who incorporated an ET device, as well as an alternative tracking method (AT) that simulates eye movement, to develop a product following a custom design methodology. The impact of both the methodology and the low-cost technology was evaluated through surveys administered to forty-seven students. The evaluation focused primarily on “utility, novelty, and relevance” as key aspects. The results showed consistently high approval ratings for both technologies. However, ET received significantly higher and more favorable evaluations. A detailed analysis of the evaluated elements indicated a strong preference for ET in terms of utility, novelty, and relevance. Furthermore, a correlational analysis revealed that students associated the integration of low-cost technology with usefulness and a positive experience. The findings of this case study highlight that low-cost devices and innovative methodologies are effective tools for enhancing teaching and learning experiences for students, educators, and researchers. Full article

Aiming at key issues in harvesting film-covered potatoes in hilly and mountainous areas—incomplete residual film collection, poor potato–soil separation, and high damage from potato-collecting devices—this study developed a crawler self-propelled potato harvester suitable for these regions. This study first expounds the overall structure and working principle of the potato harvester and then conducts principal analysis and structural design for key components (film-collecting device, digging device, primary conveying and separating device, secondary conveying and separating device, and intelligent potato-collecting device) from the perspectives of material force and movement. Finally, field performance tests were carried out in Huangzhong County, Xining City, Qinghai Province. The test results show that the machine can achieve an operation effect with a potato harvest loss rate of 2.4%, a potato damage rate of 1.4%, an impurity content rate of 2.8%, a skin-breaking rate of 2.7%, and a residual film cleaning rate of 89.6%, meeting the potato harvesting needs of this region. The lightweight self-propelled crawler potato harvester designed in this paper can realize functions such as residual film collection, potato–soil vibration separation, manual auxiliary sorting, and intelligent potato boxing, providing technical and equipment references for the harvesting of film-covered potatoes in complex terrain areas. Full article

The shear strength parameters of landslide zones are the necessary data basis for landslide stability evaluation and landslide surge disaster chain research. It is important to determine the physical and mechanical parameters of landslide zones scientifically and reasonably. In this study, four small residual landslide deposits near the Hei Duo Village road in Diebu County, Gansu Province, were investigated. The research involved detailed field investigations, the construction of landslide engineering geological models, and the use of the transfer coefficient method for simultaneous/inverse inversion and sensitivity analysis of the strength parameters of the four landslides. Based on the inversion results, an analysis of the landslide formation mechanism was conducted. The inversion results yielded the shear strength parameters of the sliding surface soil as c = 30.12 kPa and φ = 21.08°. It was found that the excavation at the base of the slope is the direct triggering factor for the landslides, with the 3# landslide being the most affected by the base excavation. In terms of the type of movement, all four landslides belong to the retrogressive landslide, with the maximum shear strain increment mainly concentrated at the slope angle after excavation. The slope body experiences shear failure, which is in good agreement with the field conditions. The study provides reference for stability prediction and disaster prevention and control of reservoir bank slope. Full article

The human body posture and trajectory are important parameters of the optimal path in speed climbing, and current researchers are focused on them. However, the performance of the newly developed analysis tools for synchronously and accurately analyzing climbing posture and trajectory is limited. This study develops an innovative speed climbing analysis system (SCAS) that integrates three-dimensional trajectory tracking using HTC Vive trackers and full-body posture capture with BlazePose. And the system is validated. Climbing trials were recorded from twelve professional athletes (speed climbers, eight males and four females; age 22 ± 2.2 years, all with ≥1 year of competitive experience) on a standard International Federation of Sport Climbing (IFSC) speed wall. The SCAS’s accuracy was analyzed by comparing its trajectory measurements to a video-based reference: the mean deviation was 0.061 ± 0.005 m (mean ± SD, 95% confidence interval [0.058, 0.064] m), indicating high precision. Trajectory metrics between genders were compared using independent-sample t-tests, revealing that male climbers had significantly shorter average path lengths (p < 0.05) and fewer movement inflections than female climbers. Finally, the group-optimal path derived from the data showed only slight deviations from the top-performing climbers’ paths. The proposed SCAS enables synchronous, millimeter-level tracking of climbing trajectory and posture, and can provide coaches with quantitative feedback for each athlete’s climbing strategy. Full article

The ATP-binding cassette (ABC) gene family represents one of the most extensive and evolutionarily conserved groups of proteins, characterized by ATP-dependent transporters that mediate the movement of substrates across cellular membranes. Despite their well-documented functions in various biological processes, the specific contributions of ABC transporters in eggplant (Solanum melongena L.) remain unexplored. To address this gap, we conducted a comprehensive genome-wide identification and expression profiling of ABC transporter-encoding genes in eggplant. Our investigation identified 159 SmABC genes encoding ABC transporter that were irregularly dispersed across all 12 chromosomes. The encoded proteins exhibited considerable diversity in size, with amino acid lengths varying from 55 to 2628 residues, molecular weights ranging between 4.04 and 286.42 kDa, and isoelectric points spanning from 4.89 to 11.62. Phylogenetic analysis classified the SmABC transporters into eight distinct subfamilies, with the ABCG subfamily being the most predominant. Subcellular localization predictions revealed that most SmABC proteins were localized to the plasma membrane. Members within the same subfamily exhibited conserved motif arrangements and exon–intron structures, suggesting functional and evolutionary conservation. Promoter analysis identified both shared and unique cis-regulatory elements associated with transcriptional regulation. We identified 9 tandem duplication gene pairs and 20 segmental duplication pairs in the SmABC gene family, with segmental duplication being the major mode of expansion. Non-synonymous to synonymous substitutions (Ka/Ks) analysis revealed that paralogs of SmABC family genes underwent mainly purifying selection during the evolutionary process. Comparative genomic analysis demonstrated collinearity between eggplant, Arabidopsis thaliana, and tomato (Solanum lycopersicum), confirming homology among SmABC, AtABC, and SlABC genes. Tissue-specific expression profiling revealed differential SmABC expression patterns, with three distinct genes, SmABCA16, SmABCA17 and SmABCG15, showing preferential expression in purple-peeled fruits (A1, A3, and A5 accessions), implicating their potential involvement in anthocyanin transport. Functional validation via SmABCA16 silencing led to a significant downregulation of SmABCA16 and reduced purple coloration, indicating its regulatory role in anthocyanin transport in eggplant fruit peel. This comprehensive genomic and functional characterization of ABC transporters in eggplant establishes a critical foundation for understanding their biological roles and supports targeted breeding strategies to enhance fruit quality traits. Full article

This study introduces a novel deep learning architecture for vessel trajectory prediction based on Automatic Identification System (AIS) data. The motivation stems from the increasing importance of maritime transport and the need for intelligent solutions to enhance safety and efficiency in congested waterways—particularly with respect to collision avoidance and real-time traffic management. Special emphasis is placed on river navigation scenarios that limit maneuverability with the demand of higher forecasting precision than open-sea navigation. To address these challenges, we propose a Principal Component Analysis (PCA)-driven layered attention mechanism integrated within an encoder–decoder model to reduce redundancy and enhance the representation of spatiotemporal features, allowing the layered attention modules to focus more effectively on salient positional and movement patterns across multiple time steps. This dual-level integration offers a deeper contextual understanding of vessel dynamics. A carefully designed evaluation framework with statistical hypothesis testing demonstrates the superiority of the proposed approach. The model achieved a mean positional error of 0.0171 nautical miles (SD: 0.0035), with a minimum error of 0.0006 nautical miles, outperforming existing benchmarks. These results confirm that our PCA-enhanced attention mechanism significantly reduces prediction errors, offering a promising pathway toward safer and smarter maritime navigation, particularly in traffic-critical riverine systems. While the current evaluation focuses on short-term horizons in a single river section, the methodology can be extended to complex environments such as congested ports or multi-ship interactions and to medium-term or long-term forecasting to further enhance operational applicability and generalizability. Full article

Understanding the mechanisms and speed of paleo-aridification in the Qaidam Block—driven by tectonic uplift and shifts in atmospheric circulation—provides critical long-term context for assessing modern climate variability and anthropogenic impacts on water resources and desertification. This knowledge is essential for informing sustainable development strategies. We reconstruct the post-Triassic–Jurassic extinction tectonic-climatic evolution of the Qaidam Block on the northern Qinghai-Tibet Plateau margin through an integrated analysis of sedimentary facies, palynological assemblages, and Chemical Index of Alteration values from Late Triassic to Jurassic strata. The Indo-Eurasian convergence drove the uplift of the East Kunlun Orogen and strike-slip movement along the Altyn Tagh Fault, establishing a basin-range system. During the initial Late Triassic to Early Jurassic period, warm-humid conditions supported gymnosperm/fern-dominated ecosystems and facilitated coal formation. A Middle Jurassic shift from extensional to compressional tectonics coincided with a climatic transition from warm-humid, through cold-arid, to hot-arid states. This aridification, evidenced by a Bathonian-stage surge in drought-tolerant Classopollis pollen and a sharp decline in Chemical Index of Alteration values, intensified in the Late Jurassic due to the Yanshanian orogeny and distal subduction effects. Resultant thrust-strike-slip faulting and southeastward depocenter migration, under persistent aridity and intensified atmospheric circulation, drove widespread development of aeolian dune systems (e.g., Hongshuigou Formation) and arid fluvial-lacustrine environments. The tectonic-climate-ecosystem framework reveals how Jurassic tectonic processes amplified feedback to accelerate aridification. This mechanism provides a critical geological analog for addressing the current sustainability challenges facing the Qaidam Basin. Full article

In factory-controlled recirculating aquaculture systems, precise regulation of water velocity is crucial for optimizing shrimp feeding behavior and improving aquaculture efficiency. However, quantitative analysis of the impact of water velocity on shrimp behavior remains challenging. This study developed an innovative multi-objective behavioral analysis framework integrating detection, tracking, and behavioral interpretation. Specifically, the YOLOv8 model was employed for precise shrimp detection, ByteTrack with a dual-threshold matching strategy ensured continuous individual trajectory tracking in complex water environments, and Kalman filtering corrected coordinate offsets caused by water refraction. Under typical recirculating aquaculture system conditions, three water circulation rates (2.0, 5.0, and 10.0 cycles/day) were established to simulate varying flow velocities. High-frequency imaging (30 fps) was used to simultaneously record and analyze the movement trajectories of Litopenaeus vannamei during feeding and non-feeding periods, from which two-dimensional behavioral parameters—velocity and turning angle—were extracted. Key experimental results indicated that water circulation rates significantly affected shrimp movement velocity but had no significant effect on turning angle. Importantly, under only the moderate circulation rate (5.0 cycles/day), the average movement velocity during feeding was significantly lower than during non-feeding periods (p < 0.05). This finding reveals that moderate water velocity constitutes a critical hydrodynamic window for eliciting specific feeding behavior in shrimp. These results provide core parameters for an intelligent Litopenaeus vannamei feeding intensity assessment model based on spatiotemporal graph convolutional networks and offer theoretically valuable and practically applicable guidance for optimizing hydrodynamics and formulating precision feeding strategies in recirculating aquaculture systems. Full article

Field hockey involves repetitive high-intensity movements and physical contact, posing a high risk of injury. However, studies developing injury prediction models without relying on expensive tools such as GPS remain limited. This study aimed to develop an explainable AI model that predicts injury occurrence using only simple questionnaire-based data and visually identifies key predictors. Survey data were collected from 239 adult players registered with the Korea Field Hockey Association in 2024, including university and professional team athletes. Ten variables were used: sex, team affiliation, playing experience, player level, warm-up duration, weekly training hours and days, and physical indicators (age, height, weight). Injury was defined as an event within the past year that resulted in being unable to train for more than 24 h. Logistic Regression, Random Forest, and XGBoost models were compared. The final model—Logistic Regression—underwent SHAP-based visualization for interpretability. The Logistic Regression model showed the best performance in recall (0.6810 ± 0.0983), F1-score (0.6260 ± 0.0499), and AUC (0.6515 ± 0.0393). SHAP analysis identified Group, Training Time, Weight, and Player Level as key predictors, and visualized their contributions to individual predictions. This study demonstrates that a lightweight, interpretable injury prediction model using only simple survey data can achieve practical performance. This approach offers valuable insights for real-world applications and the development of injury prevention strategies. Full article

Background: Motor imagery (MI) is defined as the cognitive ability to simulate motor movements while suppressing muscular activity. The electroencephalographic (EEG) signals associated with lower limb MI have become essential in brain–computer interface (BCI) research aimed at assisting individuals with motor disabilities. Objective: This systematic review aims to evaluate methodologies for acquiring and processing EEG signals within brain–computer interface (BCI) applications to accurately identify lower limb MI. Methods: A systematic search in Scopus and IEEE Xplore identified 287 records on EEG-based lower-limb MI using artificial intelligence. Following PRISMA guidelines (non-registered), 35 studies met the inclusion criteria after screening and full-text review. Results: Among the selected studies, 85% applied machine or deep learning classifiers such as SVM, CNN, and LSTM, while 65% incorporated multimodal fusion strategies, and 50% implemented decomposition algorithms. These methods improved classification accuracy, signal interpretability, and real-time application potential. Nonetheless, methodological variability and a lack of standardization persist across studies, posing barriers to clinical implementation. Conclusions: AI-based EEG analysis effectively decodes lower-limb motor imagery. Future efforts should focus on harmonizing methods, standardizing datasets, and developing portable systems to improve neurorehabilitation outcomes. This review provides a foundation for advancing MI-based BCIs. Full article

To investigate the movement law of top coal and the influencing factors of coal caving ratio in fully mechanized top coal caving faces, this study adopts the theory of dispersoid mechanics. First, a top coal flow model was established without considering the influence of the support. Then, the effect of the support was analyzed, and it was found that the sliding resistance of the top coal body increases with the square of both the support width and the top coal thickness. Furthermore, the positive stress on the coal particles was derived through a microelement force analysis, and a theoretical formula for arching probability was proposed. The mobility of top coal was evaluated using a flow factor, and the influence of lump size on arching tendency was quantitatively analyzed. Based on these insights, several measures to improve top coal flowability and recovery rate were proposed, including increasing mining height, enlarging the coal caving opening, enhancing the initial support force, extending the caving step, and applying multiple alternating loads to pre-break top coal. These strategies provide a theoretical basis and practical guidance for enhancing top coal caving efficiency. Full article