Research on the Nonlinear Computer Torque control of the MR Damper Based Above-knee Prosthesis

Aiming at the motion track controlling of the semi-active magnetorheological damper based above-knee prosthesis (MRAKP), according to the LaSalle’s invariant set theorem, a kind of nonlinear compute torque (NCT) control law for the track controlling of the AKMR, is proposed to promote the robustness and performance of the intelligent above-knee prosthesis. The proposed NCT controller includes the feedforward control and the feedback control. The former one is used to compensate the nonlinear terms in the dynamic model of the MRAKP, such as the Coriolis force, the centripetal force, and the gravity. The feedback control, utilizing a nonlinear PD controller, adaptively adjusts the control gain coefficients and reduces the system error. On these bases, numerical simulations on the MRAKPare carried out to analyze the performance of the proposed NCT controller in ADAMS and simulink. For comparing, the track controlling performance of the PD controller and the CT+PD controller are also presented in the paper. Simulation results indicate that the proposed NCT controller for the MRAKP is able to adaptively adjust the control gain coefficients with lower track error and higher robustness than the conventional PD controller and the CT+PD controller

Inhibition of STAT3 activation mediated by toll-like receptor 4 attenuates angiotensin II-induced renal fibrosis and dysfunction

Background and Purpose: Hypertension adversely affects the kidney and is the second leading cause of kidney failure. Overproduction of angiotensin II greatly contributes to the progression of hypertensive kidney disease. Angiotensin II has recently been shown to activate STAT3 in cardiovascular cells. However, the underlying mechanisms of STAT3 activation by angiotensin II and downstream functional consequences in the kidneys are not fully understood. Experimental Approach: C57BL/6 mice were treated with angiotensin II by subcutaneous infusion for 1 month to develop nephropathy. Mice were treated with either adeno-associated virus expressing STAT3 shRNA or STAT3 inhibitor, S3I-201. Human archival kidney samples from five patients with hypertension and five individuals without hypertension were also examined. In vitro, STAT3 was blocked using siRNA or STAT3 inhibitor S3I-201 in the renal proximal tubular cell line, NRK52E, after exposure to angiotensin II. Key Results: Angiotensin II activated STAT3 in kidney epithelial cells through engaging toll-like receptor 4 (TLR4) and JAK2, which was independent of IL-6/gp130 and angiotensin AT1 receptors. Angiotensin II-mediated STAT3 activation increased fibrotic proteins and resulted in renal dysfunction. Both STAT3 inhibition by the low MW compound S3I-201 and TLR4 deficiency normalized renal fibrosis and dysfunction caused by Ang II in mice, without affecting hypertension. Conclusions and Implications: Our study reveals a novel mechanism of STAT3 activation, induced by angiotensin II, in kidney tissues and highlights a translational significance of a STAT3 inhibitor as potential therapeutic agent for hypertensive kidney disease

Arc fault detection using artificial intelligence: Challenges and benefits

This systematic review aims to investigate recent developments in the area of arc fault detection. The rising demand for electricity and concomitant expansion of energy systems has resulted in a heightened risk of arc faults and the likelihood of related fires, presenting a matter of considerable concern. To address this challenge, this review focuses on the role of artificial intelligence (AI) in arc fault detection, with the objective of illuminating its advantages and identifying current limitations. Through a meticulous literature selection process, a total of 63 articles were included in the final analysis. The findings of this review suggest that AI plays a significant role in enhancing the accuracy and speed of detection and allowing for customization to specific types of faults in arc fault detection. Simultaneously, three major challenges were also identified, including missed and false detections, the restricted application of neural networks and the paucity of relevant data. In conclusion, AI has exhibited tremendous potential for transforming the field of arc fault detection and holds substantial promise for enhancing electrical safety

High acoustic diversity and behavioral complexity of katydids in the Mesozoic soundscape

Acoustic communication has played a key role in the evolution of a wide variety of vertebrates and insects. However, the reconstruction of ancient acoustic signals is challenging due to the extreme rarity of fossilized organs. Here, we report the earliest tympanal ears and sound-producing system (stridulatory apparatus) found in exceptionally preserved Mesozoic katydids. We present a database of the stridulatory apparatus and wing morphology of Mesozoic katydids and further calculate their probable singing frequencies and analyze the evolution of their acoustic communication. Our suite of analyses demonstrates that katydids evolved complex acoustic communication including mating signals, intermale communication, and directional hearing, at least by the Middle Jurassic. Additionally, katydids evolved a high diversity of singing frequencies including high-frequency musical calls, accompanied by acoustic niche partitioning at least by the Late Triassic, suggesting that acoustic communication might have been an important driver in the early radiation of these insects. The Early—Middle Jurassic katydid transition from Haglidae- to Prophalangopsidae-dominated faunas coincided with the diversification of derived mammalian clades and improvement of hearing in early mammals, supporting the hypothesis of the acoustic coevolution of mammals and katydids. Our findings not only highlight the ecological significance of insects in the Mesozoic soundscape but also contribute to our understanding of how acoustic communication has influenced animal evolution

Medial Habenula-Interpeduncular Nucleus Circuit Contributes to Anhedonia-Like Behavior in a Rat Model of Depression

The habenula is a nuclear complex composed of the lateral habenula (LHb) and medial habenula (MHb), two distinct structures. Much progress has been made to emphasize the role of the LHb in the pathogenesis of depression. In contrast, relatively less research has focused on the MHb. However, in recent years, the role of the MHb has begun to gain increasing attention. The MHb connects to the interpeduncular nucleus (IPN) both morphologically and functionally. The MHb-IPN pathway plays an important role in regulating higher brain functions, including cognition, reward, and decision making. It indicates a role of the MHb in the pathogenesis of depression. Thus, we investigated the role of the MHb-IPN pathway in depression. MHb metabolic activity was increased in the chronic unpredictable mild stress (CUMS)-exposed rat model of depression. MHb lesions in the CUMS-exposed rats reversed anhedonia-like behavior, as observed in the sucrose preference test, and significantly downregulated the elevated metabolic activity of the IPN. Substance P (SP)-containing neurons of the MHb were found to innervate the IPN and to be the main source of SP in the IPN. SP content of IPN tissue of the CUMS-exposed rats was increased and MHb lesions reversed this change. In the in vitro experiment, firing rate recordings showed that SP perfusion increased the activity of IPN neurons. Our results suggest that hyperactivity of the MHb-IPN circuit is involved in the anhedonia-like behavior of depression, and that SP mediates the effect of the MHb on IPN neurons

Optimization of Total Flavonoid Compound Extraction from Gynura medica Leaf Using Response Surface Methodology and Chemical Composition Analysis

Optimization of total flavonoid compound (TFC) extraction from Gynura medica leaf was investigated using response surface methodology (RSM) in this paper. The conditions investigated were 30–60% (v/v) ethanol concentration (X1), 85–95 °C extraction temperature (X2) and 30–50 (v/w) liquid-to-solid ratio (X3). Statistical analysis of the experiments indicated that temperature and liquid-to-solid ratio significantly affected TFC extraction (p < 0.01). The Box-Behnken experiment design showed that polynomial regression models were in good agreement with the experimental results, with the coefficients of determination of 0.9325 for TFC yield. The optimal conditions for maximum TFC yield were 55% ethanol, 92 °C and 50 (v/w) liquid-to-solid ratio with a 30 min extraction time. Extracts from these conditions showed a moderate antioxidant value of 54.78 μmol quercetin/g dry material (DM), 137.3 μmol trolox/g DM for 1,1-diphenyl-2-picrylhydrazyl (DPPH) and 108.21 μmol quercetin/g DM, 242.31 μmol trolox/g DM for 2,2-azino-bis-(3-ethylbenzthiazoline-6-sulphonic acid) (ABTS+), respectively. HPLC-DAD-MS analysis showed that kaempferol-3-O-glucoside was the principal flavonoid compound in Gynura medica leaf

Automatic 3D tooth segmentation using convolutional neural networks in harmonic parameter space

Automatic segmentation of 3D tooth models into individual teeth is an important step in orthodontic CAD systems. 3D tooth segmentation is a mesh instance segmentation task. Complex geometric features on the surface of 3D tooth models often lead to failure of tooth boundary detection, so it is difficult to achieve automatic and accurate segmentation by traditional mesh segmentation methods. We propose a novel solution to address this problem. We map a 3D tooth model isomorphically to a 2D harmonic parameter space and convert it into an image. This allows us to use a CNN to learn a highly robust image segmentation model to achieve automated and accurate segmentation of 3D tooth models. Finally, we map the image segmentation mask back to the 3D tooth model and refine the segmentation result using an improved Fuzzy Clustering-and-Cuts algorithm. Our method has been incorporated into an orthodontic CAD system, and performs well in practice

The mid-Miocene Zhangpu biota reveals an outstandingly rich rainforest biome in East Asia

During the Mid-Miocene Climatic Optimum [MMCO, ~14 to 17 million years (Ma) ago], global temperatures were similar to predicted temperatures for the coming century. Limited megathermal paleoclimatic and fossil data are known from this period, despite its potential as an analog for future climate conditions. Here, we report a rich middle Miocene rainforest biome, the Zhangpu biota (~14.7 Ma ago), based on material preserved in amber and associated sedimentary rocks from southeastern China. The record shows that the mid-Miocene rainforest reached at least 24.2°N and was more widespread than previously estimated. Our results not only highlight the role of tropical rainforests acting as evolutionary museums for biodiversity at the generic level but also suggest that the MMCO probably strongly shaped the East Asian biota via the northern expansion of the megathermal rainforest biome. The Zhangpu biota provides an ideal snapshot for biodiversity redistribution during global warming