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In this work, the tracking control problem for a class of nonlinear strict-feedback systems with input nonlinearity is addressed. In response to the influence of input nonlinearity, an auxiliary control system is constructed to compensate for it. To process unknown nonlinear dynamics, radial basis function neural networks (RBFNNs) are introduced to approximate them, and some adaptive updating control laws are designed to estimate unknown parameters. Furthermore, during the dynamic surface control (DSC) design process, first-order low-pass filters are introduced to solve the complexity explosion problems caused by repeated differentiation. After that, an NN-based adaptive dynamic surface tracking controller is proposed to achieve the tracking control. By applying the proposed controller, it can be guaranteed that not only the output of the system can track the desired trajectory, but also that the tracking error can converge to a small neighborhood of zero, while all signals of the closed-loop system are bounded. Finally, the effectiveness of the proposed controller is verified through two examples. [ABSTRACT FROM AUTHOR]

The extensive use of polymeric materials has resulted in significant environmental pollution, prompting the need for a deeper understanding of their degradation processes and impacts. This review provides a comprehensive analysis of the degradation of polymeric materials in the environment and their impact on the health of experimental animals. It identifies common polymers, delineates their degradation pathways, and describes the resulting products under different environmental conditions. The review covers physical, chemical, and biological degradation mechanisms, highlighting the complex interplay of factors influencing these processes. Furthermore, it examines the health implications of degradation products, using experimental animals as proxies for assessing potential risks to human health. By synthesizing current research, the review focuses on studies related to small organisms (primarily rodents and invertebrates, supplemented by fish and mollusks) to explore the effects of polymer materials on living organisms and underscores the urgency of developing and implementing effective polymer waste management strategies. These strategies are crucial for mitigating the adverse environmental and health impacts of polymer degradation, thus promoting a more sustainable interaction between human activities and the natural environment. [ABSTRACT FROM AUTHOR]

As a class of multifunctional reagents, organic peroxides play vital roles in the chemical industry, pharmaceutical synthesis and polymerization reactions. Metal-catalyzed asymmetric catalysis has emerged as one of the most straightforward and efficient strategies to construct enantioenriched molecules, and an increasing number of metal-catalyzed asymmetric reactions enabled by organic peroxides have been disclosed by researchers in recent years. Despite remarkable progress, the types of asymmetric reactions facilitated by organic peroxides remain limited and the catalysis systems need to be further broadened. To the best of our knowledge, there is still no review devoted to summarizing the reactions from this perspective. In this review, we will endeavor to highlight the advances in metal-catalyzed asymmetric reactions enabled by organic peroxides. We hope that this survey will summarize the functions of organic peroxides in catalytic reactions, improve the understanding of these compounds and inspire future developments in this area. [ABSTRACT FROM AUTHOR]

Transmembrane channel-like (TMC) proteins are a highly conserved ion channel family consisting of eight members (TMC1-TMC8) in mammals. TMC1/2 are components of the mechanotransduction channel in hair cells, and mutations of TMC1/2 cause deafness in humans and mice. However, the physiological roles of other TMC proteins remain largely unknown. Here, we show that Tmc7 is specifically expressed in the testis and that it is required for acrosome biogenesis during spermatogenesis. Tmc7 -/- mice exhibited abnormal sperm head, disorganized mitochondrial sheaths, and reduced number of elongating spermatids, similar to human oligo-astheno-teratozoospermia. We further demonstrate that TMC7 is colocalized with GM130 at the cis -Golgi region in round spermatids. TMC7 deficiency leads to aberrant Golgi morphology and impaired fusion of Golgi-derived vesicles to the developing acrosome. Moreover, upon loss of TMC7 intracellular ion homeostasis is impaired and ROS levels are increased, which in turn causes Golgi and endoplasmic reticulum stress. Taken together, these results suggest that TMC7 is required to maintain pH and ion homeostasis, which is needed for acrosome biogenesis. Our findings unveil a novel role for TMC7 in acrosome biogenesis during spermiogenesis., Competing Interests: JW, YY, LY, JQ, ZW, CQ, YG, GL, FG, ZC, XZ, HL, ZL No competing interests declared, (© 2024, Wang et al.)

This paper presents a 3D registration method with maximal cliques (MAC) for 3D point cloud registration (PCR). The key insight is to loosen the previous maximum clique constraint and mine more local consensus information in a graph for accurate pose hypotheses generation: 1) A compatibility graph is constructed to render the affinity relationship between initial correspondences. 2) We search for maximal cliques in the graph, each representing a consensus set. 3) Transformation hypotheses are computed for the selected cliques by the SVD algorithm and the best hypothesis is used to perform registration. In addition, we present a variant of MAC if given overlap prior, called MAC-OP. Overlap prior further enhances MAC from many technical aspects, such as graph construction with re-weighted nodes, hypotheses generation from cliques with additional constraints, and hypothesis evaluation with overlap-aware weights. Extensive experiments demonstrate that both MAC and MAC-OP effectively increase registration recall, outperform various state-of-the-art methods, and boost the performance of deep-learned methods. For instance, MAC combined with GeoTransformer achieves a state-of-the-art registration recall of 95.7% / 78.9% on 3DMatch / 3DLoMatch. We perform synthetic experiments on 3DMatch-LIR / 3DLoMatch-LIR, a dataset with extremely low inlier ratios for 3D registration in ultra-challenging cases. Code will be available at: https://github.com/zhangxy0517/3D-Registration-with-Maximal-Cliques.