Cells in vivo exist in a dynamic environment where they experience variable mechanical influences. The precise mechanical environment influences cell-cell interactions, cell-extracellular matrix interactions, and in-turn, cell morphology and cell function. Therefore, the ability of each cell to constantly and rapidly alter their behavior in response to variations in their mechanical environment is essential for cell viability, development, and function. Mechanotransduction, the process by which mechanical force is translated into a biochemical signal to activate downstream cellular responses, is thus crucial to cell function during development and homeostasis. Although much research has focused on how protein complexes at the cell cortex respond to mechanical stress to initiate mechanotransduction, the nucleus has emerged as crucial to the ability of the cell to perceive and respond to changes in its mechanical environment. This additional method for mechanosensing allows for direct transmission of force through the cytoskeleton to the nucleus, which can increase the speed at which a cell changes its transcriptional profile. This review discusses recent work demonstrating the importance of the nucleus in mediating the cellular response to internal and external force, establishing the nucleus as an important mechanosensing organelle.
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http://dx.doi.org/10.1002/cm.21277 | DOI Listing |
Sensors (Basel)
December 2024
The State Key Laboratory of Fluid Power and Mechatronic Systems, School of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China.
In physical spaces, pointing interactions cannot rely on cursors, rays, or virtual hands for feedback as in virtual environments; users must rely solely on their perception and experience to capture targets. Currently, research on modeling target distribution for pointing interactions in physical space is relatively sparse. Area division is typically simplistic, and theoretical models are lacking.
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December 2024
School of Mechanical Engineering and Automation, Foshan University, Foshan 528225, China.
Inspection robots, which improve hazard identification and enhance safety management, play a vital role in the examination of high-risk environments in many fields, such as power distribution, petrochemical, and new energy battery factories. Currently, the position precision of the robots is a major barrier to their broad application. Exact kinematic model and control system of the robots is required to improve their location accuracy during movement on the unstructured surfaces.
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December 2024
State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan 430074, China.
Applying deep learning to unsupervised bearing fault diagnosis in complex industrial environments is challenging. Traditional fault detection methods rely on labeled data, which is costly and labor-intensive to obtain. This paper proposes a novel unsupervised approach, WDCAE-LKA, combining a wide kernel convolutional autoencoder (WDCAE) with a large kernel attention (LKA) mechanism to improve fault detection under unlabeled conditions, and the adaptive threshold module based on a multi-layer perceptron (MLP) dynamically adjusts thresholds, boosting model robustness in imbalanced scenarios.
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December 2024
SCAI Connect s.r.l., Via Vincenzo Lamaro 51, 00173 Rome, Italy.
The development and calibration of a measurement system designed for assessing the performance of the avalanche photodiodes (APDs) used in the Compton scattering polarimeter of the CUSP project is discussed in this work. The designed system is able to characterize the APD gain GAPD and energy resolution across a wide range of temperatures (from -20 °C to +60 °C) and bias voltages Vbias (from 260 V to 410 V). The primary goal was to experimentally determine the GAPD dependence on the and Vbias in order to establish a strategy for stabilizing GAPD by compensating for fluctuations, acting on Vbias.
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December 2024
Research Center of Structural Health Monitoring and Prognosis, State Key Laboratory of Mechanics and Control for Aerospace Structures, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China.
The aircraft smart skin (ASS) with structural health monitoring capabilities is a promising technology. It enables the real-time acquisition of the aircraft's structural health status and service environment, thereby improving the performance of the aircraft and ensuring the safety of its operation, which in turn reduces maintenance costs. In this paper, a miniaturized and ultra-low-power wireless multi-parameter monitoring system (WMPMS) for ASS is developed, which is capable of monitoring multiple parameters of an aircraft, including random impact events, vibration, temperature, humidity, and air pressure.
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