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In order to reduce the drag torque under high speed conditions, the equivalent radius is introduced into the traditional low speed torque model of a wet clutch with track vehicle, and the calculation model of the drag torque with radial groove is derived. An optimization design model is established with 3 working condition parameters of the clutch and 5 structural parameters of the friction plate as design variables, and the minimum drag torque as the optimization objective. The objective function is solved based on the whale optimization algorithm (WOA) , and the drag torque is reduced by 35.6% after optimization. The dynamic response model of the objective function is established by Simulink software, and the optimization results are verified. The results show that the optimization method is effective and can provide some reference for structural design and parameter optimization of wet clutches.

At present, there are some problems with fiber-based artifical mucles, such as harsh stimulation conditions, chemical toxicity, and high cost, To remove the barriers of their application in intelligent textiles, was investigated the fabrication, performance and application of a kind of skin-friendly woolen yarn artificial muscles. The natural wools are twisted and folded a to form a self-balanced double-helical structure. Oxygen plasma was used to clean and activate the wool surface. The as-prepared woolen yarn artificial muscles were further fabricated into woven fabric muscle actuators. By using the scan electric microscope, tensile tester and high-speed camera, the actuation performance and affecting factors were discussed. The results show that the rapid response to dry and wet state and reversible torsion deformation are realized, and the rotation degree of the woolen yarn artificial muscles can reach 373(°)/cm with good cyclic performance. Fabric actuators show good curling performance under the stimulation of water fog, providing a new strategy for the application of moisture-sensing smart textiles.

The Dongzhongla deposit is a skarn-type lead–zinc ore deposit located in the eastern segment of the Gangdese metallogenic belt, situated in the Xizang province, China. The high-altitude mountainous terrain of the region poses significant challenges to ground-based exploration. To facilitate more accurate mineral exploration in the deposit and its surrounding area, a high-resolution airborne magnetic survey was conducted over the mining area and its periphery. The airborne magnetic data were processed using derivative and Euler deconvolution methods, yielding results that reflect the geological structural features of the study area. By integrating the geological characteristics of the ore deposit, we inferred that the areas of magnetic anomaly extensions and the peripheries of other magnetic anomalies are favorable zones for mineralization, providing positive leads for further mineral exploration. [ABSTRACT FROM AUTHOR]

The coupling model between unwinding tension and various factors is crucial for understanding warp beam unwinding characteristics and designing tension control systems. However, currently established models are simple and fail to reflect the complexity of the actual unwinding process. Additionally, the traditional unified PID control method for multiple warp beams is difficult to ensure stable unwinding tension for single warp beam, negatively impacting the quality and efficiency of the sizing process. To address these issues, coupling models between tension, radius, speed, turns and air pressure during the warp beam unwinding process were established and validated using constructed detection devices. Experimental results showed that the four types of measured warp beams fit the three coupling models with R 2 values exceeding 90%, confirming the accuracy of these models. Subsequently, a novel fuzzy adaptive PID control system for single warp beam unwinding tension was proposed based on these models. Unlike traditional methods that measure tension directly, the system utilizes unwinding turns detection device to monitor the real-time changes. Simulation results confirmed that the proposed system maintains constant tension under different reference tensions and unwinding radius. Compared to traditional PID control, it significantly reduces tension fluctuation, with reductions of 64.49% under different speed step disturbances and 23.66% under noise disturbances. The validated models and proposed tension control system in this paper provide a solid theoretical foundation and practical guidance for optimizing the new generation of sizing machines. [ABSTRACT FROM AUTHOR]

Sudden cardiac death (SCD) represents a critical acute cardiovascular event characterized by rapid onset of cardiac and respiratory arrest, posing a significant threat to patients due to its high fatality rate. Monitoring indices related to SCD using wearable devices holds profound implications for preemptive measures aimed at reducing the incidence of such life-threatening events. Hence, this study proposed a predictive algorithm for SCD leveraging single-lead electrocardiogram (ECG) signals featuring low signal-to-noise ratios. Initially, simulated electrode motion artifact noise was introduced to ideal ECG signals to emulate the signal conditions with low signal-to-noise ratios encountered in everyday scenarios. To meet the criteria of simplicity and cost-effectiveness required for wearable devices, the analysis focused exclusively on single-lead signals. The proposed algorithm in this study employed a lightweight machine learning approach to extract 12-dimensional features encompassing ventricular late potentials, T-wave electrical alternation, and corrected QT intervals from the signal. The algorithm achieved an average prediction accuracy of 93.22% within 30 min prior to SCD onset, and 95.43% when utilizing a normal sinus rhythm database as a control, demonstrating robust performance. Additionally, a comprehensive Sudden Cardiac Death Index (SCDI) was devised to quantify the risk of SCD, formulated by integrating pivotal two-dimensional features contributing significantly to the algorithm. This index effectively distinguishes high-risk signals indicative of SCD from normal signals, thereby offering valuable supplementary insights in clinical settings. [ABSTRACT FROM AUTHOR]

The excellent load-bearing performance of sized warp yarns can reduce the end-breakage rate and enable them to complete weaving smoothly. Evaluating the load-bearing performance of sized warp yarn can guide the sizing process and weaving production. For this purpose, the study evaluated the load-bearing performance of cotton sized warp yarn. First, based on the JN-01 tester, a weaving load simulation tester of sized warp yarn, the test sample capacity for the load-bearing life was determined to be 50 ends using a U-test. Second, by testing three cotton sized warp yarns with different linear densities, the universality of the parameter conditions of the tester was verified. Third, with the JN-01 tester, the breaking strength and hairiness under different load-bearing cycles were measured, and it was found that the breaking strength of the sized yarn was linearly related to the load-bearing cycles. In contrast, the hairiness of the sized yarn was logarithmically related to the load-bearing cycles. According to regression analyses, evaluation indicators were extracted to characterize the strength loss resistance and anti-fuzzing performance of sized warp yarns, which were the residual enhancement rate and hairiness after friction. The evaluation results of sized warp yarns, with different linear densities and different sizing ratios, showed the effectiveness of the evaluation indicators. Finally, by verifying the effectiveness of samples from three factories, based on the evaluation indicators in this paper, the results revealed that the constructed evaluation method effectively evaluated the load-bearing performance of cotton sized warp yarn. [ABSTRACT FROM AUTHOR]

Warp sizing significantly influences both the efficiency of weaving machines and the overall quality of the woven fabric, playing a crucial role in the weaving preparation process. Ensuring precise control of process parameters and equipment status during the sizing process is essential to maintain desirable sizing quality. This paper clarified the research significance of squeezing from the perspective of its application in warp sizing. Moreover, research advances in the squeezing device, including the structure, material, surface state of squeezing and sizing rollers, the configuration of the squeeze and sizing rollers, the spraying device, the pressurization methods for the squeezing roller, and their influence on sizing performance were reviewed in detail. A comprehensive analysis and summary were conducted to explore the correlations between sizing quality and diverse squeezing technical parameters, encompassing squeezing force, surface hardness of rubber-covered sizing and the squeezing roller, squeezing width, warp speed, and immersion time. In addition, this article also outlines the mathematical models related to the squeezing process and the characterization methods of the squeezing effect. Finally, it offers a glimpse into potential future research directions concerning the squeezing process. [ABSTRACT FROM AUTHOR]