System Design of a Cheetah Robot Toward Ultra-high Speed

High-speed legged locomotion pushes the limits of the most challenging problems of design and development of the mechanism, also the control and the perception method. The cheetah is an existence proof of concept of what we imitate for high-speed running, and provides us lots of inspiration on design. In this paper, a new model of a cheetah-like robot is developed using anatomical analysis and design. Inspired by a biological neural mechanism, we propose a novel control method for controlling the muscles' flexion and extension, and simulations demonstrate good biological properties and leg's trajectory. Next, a cheetah robot prototype is designed and assembled with pneumatic muscles, a musculoskeletal structure, an antagonistic muscle arrangement and a J-type cushioning foot. Finally, experiments of the robot legs swing and kick ground tests demonstrate its natural manner and validate the design of the robot. In the future, we will test the bounding behaviour of a real legged system

Learning adaptive reaching and pushing skills using contact information

In this paper, we propose a deep reinforcement learning-based framework that enables adaptive and continuous control of a robot to push unseen objects from random positions to the target position. Our approach takes into account contact information in the design of the reward function, resulting in improved success rates, generalization for unseen objects, and task efficiency compared to policies that do not consider contact information. Through reinforcement learning using only one object in simulation, we obtain a learned policy for manipulating a single object, which demonstrates good generalization when applied to the task of pushing unseen objects. Finally, we validate the effectiveness of our approach in real-world scenarios

One-Step Preparation of High Performance TiO 2 /CNT/CQD Nanocomposites Bactericidal Coating with Ultrasonic Radiation

© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).As an environmental semiconductor material, TiO2 has important applications in the fields of environmental protection and water treatment. The preparation of P25 particles into nano-functional material films with a high specific surface area has always been a bottleneck limiting its large-scale application. In this paper, a one-step method of preparing TiO2 nanocomposites by doping carbon nanotube (CNT) and carbon quantum dots (CQD) with tetrabutyltitanate and P25 TiO2 under ultrasonic radiation is proposed to synthesize a novel antifouling material, which both eliminates the bacterium of Escherichia coli and shows good photoelectric properties, indicating a great value for the industrial promotion of TiO2/CNT. This mesoporous composite exhibits a high specific surface area of 78.07 M2/g (BET) and a tested pore width range within 10–120 nm. The surface morphology of this composite is characterized by TEM and the microstructure is characterized through XRD. This preparation method can fabricate P25 particles into a nano-functional material film with a high specific surface area at a very low cost.Peer reviewe

Ethylene Glycol Monomethyl Ether–Induced Toxicity Is Mediated through the Inhibition of Flavoprotein Dehydrogenase Enzyme Family

Ethylene glycol monomethyl ether (EGME) is a widely used industrial solvent known to cause adverse effects to human and other mammals. Organs with high metabolism and rapid cell division, such as testes, are especially sensitive to its actions. In order to gain mechanistic understanding of EGME-induced toxicity, an untargeted metabolomic analysis was performed in rats. Male rats were administrated with EGME at 30 and 100 mg/kg/day. At days 1, 4, and 14, serum, urine, liver, and testes were collected for analysis. Testicular injury was observed at day 14 of the 100 mg/kg/day group only. Nearly 1900 metabolites across the four matrices were profiled using liquid chromatography-mass spectrometry/mass spectrometry and gas chromatography-mass spectrometry. Statistical analysis indicated that the most significant metabolic perturbations initiated from the early time points by EGME were the inhibition of choline oxidation, branched-chain amino acid catabolism, and fatty acid β-oxidation pathways, leading to the accumulation of sarcosine, dimethylglycine, and various carnitine- and glycine-conjugated metabolites. Pathway mapping of these altered metabolites revealed that all the disrupted steps were catalyzed by enzymes in the primary flavoprotein dehydrogenase family, suggesting that inhibition of flavoprotein dehydrogenase–catalyzed reactions may represent the mode of action for EGME-induced toxicity. Similar urinary and serum metabolite signatures are known to be the hallmarks of multiple acyl-coenzyme A dehydrogenase deficiency in humans, a genetic disorder because of defects in primary flavoprotein dehydrogenase reactions. We postulate that disruption of key biochemical pathways utilizing flavoprotein dehydrogenases in conjugation with downstream metabolic perturbations collectively result in the EGME-induced tissue damage

Multiview Discriminative Marginal Metric Learning for Makeup Face Verification

Makeup face verification in the wild is an important research problem for its popularization in real-world. However, little effort has been made to tackle it in computer vision. In this research, we first build a new database, i.e., Facial Beauty Database (FBD), which contains paired facial images of 8933 subjects without and with makeup in different real-world scenarios. To the best of our knowledge, FBD is the largest makeup face database to date compared with existing databases for facial makeup research. Moreover, we propose a new discriminative marginal metric learning (DMML) algorithm to deal with this problem in the wild. Inspired by the fact that interclass marginal faces are usually more discriminative than interclass nonmarginal faces in learning the discriminative metric space, we use the interclass marginal faces to depict the discriminative information. Simultaneously, we wish that those interclass marginal faces without makeup relations are separated from each other as far as possible, so that more discriminative information between facial images without and with makeup can be exploited for verification. Furthermore, since multiple features could provide comprehensive information in describing the facial representations from diverse points of view and extract more informative cues from facial images, we also introduce a multiview discriminative marginal metric learning (MDMML) algorithm by effectively learning a robust metric space such that multiple features from different points of view can be integrated to effectively enhance the performance of makeup face verification. Experimental results on two real-world makeup face databases are utilized to show the effectiveness of our method and the possibility of verifying the makeup relations from facial images in real-world

Two distinct waxy alleles impact the granule-bound starch synthase in sorghum

The granule-bound starch synthase (GBSS) is the enzyme responsible for amylose synthesis in starch granules. Loss of GBSS activity results in starch granules containing mostly amylopectin and little or no amylose, a phenotype described as waxy

Z-Scheme CuOx/Ag/TiO2 Heterojunction as Promising Photoinduced Anticorrosion and Antifouling Integrated Coating in Seawater

In the marine environment, steel materials usually encounter serious problems with chemical or electrochemical corrosion and fouling by proteins, bacteria, and other marine organisms. In this work, a green bifunctional Z-scheme CuOx/Ag/P25 heterostructure coating material was designed to achieve the coordination of corrosion prevention and antifouling by matching the redox potential of the reactive oxygen species and the corrosion potential of 304SS. When CuOx/Ag/P25 heterostructure was coupled with the protected metal, the open circuit potential under illumination negatively shifted about 240 mV (vs. Ag/AgCl) and the photoinduced current density reached 16.6 μA cm−2. At the same time, more reactive oxygen species were produced by the Z-shape structure, and then the photocatalytic sterilization effect was stronger. Combined with the chemical sterilization of Ag and the oxide of Cu, the bacterial survival rate of CuOx/Ag/P25 was low (0.006%) compared with the blank sample. This design provides a strategy for developing green dual-functional coating materials with photoelectrochemical anticorrosion and antifouling properties