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Abstract Aiming to address the challenge where existing methods struggle to predict accurate disparities for imperfectly rectified stereo images, and that supervised training requires a considerable amount of ground truth, a self‐supervised binocular depth estimation algorithm with self‐rectification for autonomous driving is proposed. Firstly, a subnetwork dedicated to stereo rectification, aiming to estimate the homography between stereo images is developed. This homography facilitates the transformation of stereo image pairs, aligning their corresponding pixels horizontally. Secondly, a foundational self‐supervised framework primarily centred on minimizing errors in stereo image reconstruction, combined with the generative‐adversarial strategy is introduced. Finally, a vertical offset prediction module (VOPM) is incorporated into the basic framework to further enhance the resistance of the stereo matching network to pixel‐level vertical offset errors. Experimental results on the public KITTI dataset for autonomous driving demonstrate the effectiveness of this approach in improving the disparity prediction performance for imperfectly rectified stereo images. Moreover, the self‐supervised training framework exhibits superiority over state‐of‐the‐art methods.

Deterioration of stainless steel is significantly influenced by the characteristics of corrosion products. Evolution of corrosion products of 17-4 PH martensitic stainless steel (17-4 PH MSS) in the tropical marine environment was systematically studied by field-exposure, combined with morphological observation, compositional characterization and electrochemical testing in this work. The corrosion process of 17-4 PH MSS was divided into three stages: stage I–rapid formation and shedding of corrosion products, stage II–adhesion and transformation of corrosion products and stage Ⅲ–remarkable increase in the protective properties of corrosion products. Corrosion rate of 17-4 PH MSS was maximum in the first stage and then decreased continuously in the second and third stages, which is closely related to the morphology, distribution and composition of the corrosion products. In terms of morphological evolution, corrosion products of 17-4 PH MSS showed the dynamic cycle characteristic of ''nucleation-growth-cracking-shedding''. In view of compositional transformation, the high content of Cr, Ni, and Cu in stainless steel is involved in the formation of corrosion products, and the production of Cr2O3, Cr(OH)3, FeCr2O4, NiFe2O4, and CuFeO2 after 6 months of exposure was an important shift. Argument from protective properties, increase in coverage percentage and the generation of Cr-containing products are responsible for the enhancement of protective properties of the corrosion products. This work prepares the way for further research on the generation and growth mechanism of pitting under corrosion products and provides technical support for the design, selection, and protection of stainless steel in tropical marine environments.

This paper introduces a model, M0RV, that improves the MuZero algorithm through data reuse and loss function optimization. It proposes reusing training trajectories generated by Monte Carlo Tree Search (MCTS) after filtering through an evaluation function trace into the training process, and on this basis, employs the Advantage-Value method to optimize the neural network loss function, ultimately optimizing the training process. A comparative analysis is conducted between the baseline MuZero algorithm, its A0GB algorithm-enhanced variant M0GB, and the further refined M0RV algorithm, across a spectrum of Atari and intricate board games. Notably, M0RV outperforms its predecessors in both the Lunar Lander and Breakout games, as well as in the board game Hex, under consistent steps parameters and unified reward benchmarks. The empirical findings demonstrate that the M0RV model, in comparison to the MuZero model, substantially enhances training efficacy, successfully fulfilling the objective of optimizing the training methodology.

The purpose of monocular semantic scene completion is to predict detailed 3D scene with semantic information using only one image. In order to improve the ability of extracting image features of the classical network and achieve better semantic scene completion effect, we propose a monocular semantic scene completion method based on context transformer and recurrent residual convolution. The context transformer module was added between the encoder and decoder of the image feature extraction network, which uses context information to guide the learning of the dynamic attention matrix and improve the visual representation ability. We also introduce a recurrent residual convolution module into the decoder to accumulate features at different time steps, thus helping to distinguish similar objects. Experimental results show that, on indoor dataset NYUv2 and outdoor traffic scene dataset Semantic KITTI, compared with the baseline method, the evaluation metrics mIoU of the semantic scene completion task is improved by 5% and 8% respectively.

Meteorological identification and observation are crucial in production activities closely related to meteorology, such as agricultural production. Currently, some machine learning methods applied in meteorological identification exhibit low richness of semantic features and weak transferability in pre-trained models, leading to insufficient feature extraction capabilities. Additionally, these models often have relatively simple classification layers, and they tend to train as a holistic model. To address the aforementioned shortcomings, this paper proposes a mechanism of fused training, constructing a meteorological identification model based on the enhanced fusion of EVA02 and Linear Support Vector Classification (LinearSVC). The model fine-tunes the pre-trained EVA02 backbone network, fully stimulating the qualitative transformation of transfer learning’s high-level semantic abstractions and meteorological data representations. This enhances feature extraction capabilities. Additionally, the model integrates the Nystroem method with the LinearSVC algorithm for classification, further improving classification accuracy and the robustness of the model on small datasets. Through simulation experiments, the model achieves F1-scores on the public datasets MWD and WEAPD that surpass the current state-of-the-art methods by 0.75% and 9.89%, respectively, demonstrating the effectiveness of the proposed method.

Detection based on LiDAR and camera fusion is increasingly popular for researchers in the autonomous driving domain. Compared to the camera-only and LiDAR-only methods, the fusion-based methods indeed improve the detection accuracy on public-available datasets. However, due to the complexity of the projection or fusion mechanism, few of these methods can run in real time even on an advanced desktop GPU. Thus, in this paper, we propose a new fusion detection model G-Fusion with a light and fast image view-transform module. According to our receptive field analysis of image feature maps, we directly project image features to only one voxel layer located on the ground, then fuse the LiDAR and image features by concatenation and convolution. With this delicately designed module, G-Fusion greatly boosts the state-of-the-art speed performance on the nuScenes dataset, achieving a good balance with the competitive detection scores. Meanwhile, since the precision of sensor extrinsic parameters is important for most fusion-based methods, we also deeply dig into our model’s calibration error tolerance ability and discover the failure noise condition.

The cultivation of microalgae from municipal wastewater, while simultaneously removing nutrients from the water column, has the potential to aid biodiesel production and carbon dioxide fixation, thereby alleviating the pressure of energy shortages. In this research, different ratios of sodium bicarbonate and glucose were used to prepare simulated municipal wastewater. The results demonstrated that microalgae were most effectively treated under one-stage direct treatment conditions. During direct culture, the most effective treatment was observed for IAA-3, which exhibited a dry weight of 1.4363 g/L and a lipid content of 25.05% after stimulation with 0.0005 M NaHCO3. In contrast, NaHCO3-2 demonstrated optimal performance during the secondary culture, with a dry weight of 1.6844 g/L and a lipid content of 18.05%. Finally, the economic, social and environmental benefits of direct treatment (IAA-3) and secondary treatment NaHCO3-2 were analyzed. The benefits of direct treatment were found to be USD 0.50989/L, while those of secondary treatment were USD 0.43172/L. For each tonne of municipal wastewater treated, the carbon sequestration benefits of IAA-3 during direct treatment and NaHCO3-2 during secondary treatment were USD 0.45645 and USD 0.85725, respectively.

Abstract Background In recent years, obesity in early adulthood has become an urgent global public health concern. Body dissatisfaction may have adverse effects on lifestyle habits, leading to obesity. However, research on nutritional status and body dissatisfaction among Chinese young adults is still insufficient. Therefore, this study aimed to analyze the relationship between body dissatisfaction, dietary habits, physical activity, and nutritional status among university students. In addition, we explored the feasibility of improving university students’ nutritional status by improving the levels of body dissatisfaction. Methods This study was conducted in Ganzhou City, Jiangxi Province, China, at a randomly selected university. All 1900 undergraduate students volunteered to participate and signed the consent form. Students were required to completed anthropometric measurements and three questionnaires, which included the Physical Activity Rating Scale-3 (PARS-3), Chinese version of the Dutch Dietary Behavior Questionnaire (C-DEBQ), and Body Dissatisfaction. Of these, 1714 students (age: 18–24 years; men: 933, women: 781) with complete and valid data were included. Results Higher obesity levels were observed in men compared to women (p

Abstract Molybdenum supported on zeolites has been extensively studied as a catalyst for methane dehydroaromatization. Despite significant progress, the actual intermediates and particularly the first C-C bond formation have not yet been elucidated. Herein we report evolution of methyl radicals during non-oxidative methane activation over molybdenum single sites, which leads selectively to value-added chemicals. Operando X-ray absorption spectroscopy and online synchrotron vacuum ultraviolet photoionization mass spectroscopy in combination with electron microscopy and density functional theory calculations reveal the essential role of molybdenum single sites in the generation of methyl radicals and that the formation rate of methyl radicals is linearly correlated with the number of molybdenum single sites. Methyl radicals transform to ethane in the gas phase, which readily dehydrogenates to ethylene in the absence of zeolites. This is essentially similar to the reaction pathway over the previously reported SiO2 lattice-confined single site iron catalyst. However, the availability of a zeolite, either in a physical mixture or as a support, directs the subsequent reaction pathway towards aromatization within the zeolite confined pores, resulting in benzene as the dominant hydrocarbon product. The findings reveal that methyl radical chemistry could be a general feature for metal single site catalysis regardless of the support (either zeolites MCM-22 and ZSM-5 or SiO2) whereas the reaction over aggregated molybdenum carbide nanoparticles likely facilitates carbon deposition through surface C-C coupling. These findings allow furthering the fundamental insights into non-oxidative methane conversion to value-added chemicals.

Most lower limb rehabilitation robots are limited to specific training postures to adapt to stroke patients in multiple stages of recovery. In addition, there is a lack of attention to the switching functions of the training side, including left, right, and bilateral, which enables patients with hemiplegia to rehabilitate with a single device. This article presents an exoskeleton robot named the multistage hemiplegic lower-limb rehabilitation robot, which has been designed to do rehabilitation in multiple training postures and training sides. The mechanism consisting of the thigh, calf, and foot is introduced. Additionally, the design of the multi-mode limit of the hip, knee, and ankle joints supports delivering therapy in any posture and training sides to aid patients with hemiplegia in all stages of recovery. The gait trajectory is planned by extracting the gait motion trajectory model collected by the motion capture device. In addition, a control system for the training module based on adaptive iterative learning has been simulated, and its high-precision tracking performance has been verified. The gait trajectory experiment is carried out, and the results verify that the trajectory tracking performance of the robot has good performance.

Abstract Endometrial cancer (EC) is a common gynecological cancer that endangers women health. Although substantial progresses of EC management have been achieved in recent years, the incidence of EC still remains high. Obesity has been a common phenomenon worldwide that increases the risk of EC. However, the mechanism associating obesity and EC has not been fully understood. Metabolic reprogramming as a remarkable characteristic of EC is currently emerging. As the primary factor of metabolic syndrome, obesity promotes insulin resistance, hyperinsulinemia and hyperglycaemia. This metabolic disorder remodels systemic status, which increases EC risk and is related with poor prognosis. Glucose metabolism in EC cells is complex and mediated by glycolysis and mitochondria to ensure energy requirement. Factors that affect glucose metabolism may have an impact on EC initiation and progression. In this study, we review the glucose metabolic reprogramming of EC not only systemic metabolism but also inherent tumor cell metabolism. In particular, the role of glucose metabolic regulation in malignant properties of EC will be focused. Understanding of metabolic profile and glucose metabolism-associated regulation mechanism in EC may provide novel perspective for treatment.

Inspired from sharing economy and advanced energy storage technologies, hybrid shared energy storage (HSES), as an innovative business model, can provide flexible storage leasing services to new energy stations (NESs) and bring additional profits to the energy storage owner. Under this business model, pricing and planning issues are the main focus of the HSES operator to increase revenues but are rarely considered in current studies. Therefore, a Stackelberg game-based three-stage optimal pricing and planning strategy of HSES is formulated for the operator. First, an HSES model considering two leasing options is developed to provide two kinds of short-term use rights of energy storage resources for NESs. Then, the interactions between selfish NESs and the HSES operator are characterized as a Stackelberg game, and a bi-level pricing and planning strategy optimization model is developed to help the HSES operator make optimal decisions. Finally, considering different characteristics in each stage of the Stackelberg game, a three-stage solution method based on the genetic algorithm (GA) and mixed-integer linear programming (MILP) models is proposed to solve the optimization problem. Case studies on six NESs in a certain region are taken to verify the effectiveness of the proposed strategy. Simulation results show that the HSES operator can obtain maximum profit under the proposed pricing and planning strategy. In addition, the proposed HSES leasing model can provide additional benefits to both the operator and NESs.

Microbiota succession in spontaneous fermentation of Cabernet Sauvignon cultivated under the rain-shelter was characterized, with open-field cultivation as the control. For both cultivation modes, Saccharomyces, Starmerella, and Mycosphearella were the principal fungi, and Tatumella, Gluconobacter, and Acinetobacter were the prevailing bacteria. Rain-shelter reduced the abundance of Hanseniaspora, Candida, Starmerella, Gluconobacter, and Lactococcus. During fermentation, fungal microbiota diversity in samples from the rain-shelter cultivation decreased more drastically than the control (p

Microbiota-relevant signatures have been investigated for human papillomavirus-related cervical cancer (CC), but lack consistency because of study- and methodology-derived heterogeneities. Here, four publicly available 16S rRNA datasets including 171 vaginal samples (51 CC versus 120 healthy controls) were analyzed to characterize reproducible CC-associated microbial signatures. We employed a recently published clustering approach called VAginaL community state typE Nearest CentroId clAssifier to assign the metadata to 13 community state types (CSTs) in our study. Nine subCSTs were identified. A random forest model (RFM) classifier was constructed to identify 33 optimal genus-based and 94 species-based signatures. Confounder analysis revealed confounding effects on both study- and hypervariable region-associated aspects. After adjusting for confounders, multivariate analysis identified 14 significantly changed taxa in CC versus the controls (P < 0.05). Furthermore, predicted functional analysis revealed significantly upregulated pathways relevant to the altered vaginal microbiota in CC. Cofactor, carrier, and vitamin biosynthesis were significantly enriched in CC, followed by fatty acid and lipid biosynthesis, and fermentation of short-chain fatty acids. Genus-based contributors to the differential functional abundances were also displayed. Overall, this integrative study identified reproducible and generalizable signatures in CC, suggesting the causal role of specific taxa in CC pathogenesis.

The present work, in which cellulose isolated from formic acid fractionation (FAC) is decorated with polyetherimide (PEI) to attain highly efficient cellulose-derived PdAgbimetallic catalyst (PdAg-PEI-FAC), has been investigated, and the catalyst properties are characterized by XRD, XPS, BET, ICP-AES and HAADF-STEM. The as-obtained Pd3.75Ag3.75-PEI-FAC exhibits excellent catalytic performance for H2 evolution from a sodium formate-free formic acid (FA) aqueous medium at ambient temperature and the turnover frequency (TOF) reaches a high value of 2875 h−1, which is superior to most of the previously reported Pd-based heterogeneous catalysts supported on a carbon matrix in the literature. The remarkable catalytic activities of PdAg-PEI-FAC result from high dispersion Pd and synergistic effects between the PdAg bimetallic system. Furthermore, the amide (-NH) group in PEI coated on cellulose acting as a proton scavenger efficiently improves the catalytic property of catalyst. In addition, the critical factors affecting H2 release, such as FA concentration, reaction temperature, PdAg compositions and support matrix type, are also evaluated. Based on the experimental results, the probable three-step mechanism of H2 evolution from FA over Pd3.75Ag3.75-PEI-FAC is proposed. In the end, the activation energy (Ea) of Pd3.75Ag3.75-PEI-FAC catalyst is calculated to 53.97 kJ mol-1, and this catalyst shows unique robustness and satisfactory re-usability with no loss of catalytic activity after five recycles. The findings in this work provide a novel routine from lignocellulose fractionation towards cellulose-derived catalyst for H2 evolution.

Abstract Background & Aims To clarify the biological roles, circularization process and secretion pathway of circRHOBTB3 in colorectal cancer (CRC) progression. Methods We performed a comprehensive analysis of circRNA levels in serum exosomes from multiple types of cancer patients in public databases and verified the higher level of circRHOBTB3 in CRC sera versus healthy donors by RT-qPCR. Then, the function of circRHOBTB3 in CRC was investigated in vitro and in vivo. RNA-seq and RNA pull-down assays together with mass spectrometry identified the downstream signals and the binding proteins of circRHOBTB3. Finally, Antisense oligonucleotides (ASOs) were designed to target circularization and secretion elements of circRHOBTB3 for CRC therapy. Results circRHOBTB3 levels were increased in the sera but was downregulated in tissue samples in CRC, and the downregulation was associated with poor prognosis. Furthermore, circRHOBTB3 acts a tumor-suppressive circRNA by repressing metabolic pathways, intracellular ROS production in CRC. Several key elements were discovered to regulate circRHOBTB3 circularization and exosomal secretion. Moreover, SNF8 was identified that sorts circRHOBTB3 into exosomes. Interestingly, we found that CRC cells could actively secrete more circRHOBTB3 than normal cells. According to the sequence of regulatory elements for circularization and exosomal secretion, we designed and synthesized ASOs, which increased circRHOBTB3 expression and blocked circRHOBTB3 exosomal secretion. More importantly, ASOs could inhibit CRC growth and metastasis in vitro and in vivo. Conclusions circRHOBTB3 plays a tumor-suppressive role in CRC and has to be excreted out of cells to sustain cancer cell fitness. ASOs targeting regulatory elements for circularization and exosomal secretion will become a novel antitumor strategy.

This paper presents a novel image hiding method with improved block matching way and high embedding capacity that allows the Important Image (IM) to be several times larger than the cover image. Multi-layered Least-Significant-Bit (LSB) planes of the Cover Image (CI) are obtained for constructing the Candidate Block-Matching Set (CBMS) by using the features fusion which consists of the texture features of wavelet transform and gray level difference; By combining features way to search the best-matching blocks from the CBMS, and the Huffman coding is used to compress the data including the indices of the best-matching blocks, the not-well-matched blocks part of IM and the parameters into a secret information flow which is embedded into the double-layered bit planes of CI by using a high embedding rate encoder. Because the high embedding payload we need, the SPAM features will be chosen to test the performance of resisting steganalysis attack which can obviously improve the security of the stego images.

With the promotion of carbon peaking and carbon neutrality goals and the construction of renewable-dominated electric power systems, renewable energy will become the main power source of power systems in China. Therefore, ensuring frequency stability and system security will emerge as pivotal challenges in the future development process. Created by combining a Li-ion battery and a supercapacitor, a hybrid energy storage system (HESS), which possesses robust power regulation capabilities and rapid response capabilities, holds promise for supporting the frequency stability of power systems. In this context, the assessment of the economic viability of HESSs providing multitype frequency response services becomes a critical factor in their deployment and promotion. In this paper, an economic analysis approach for a Li-ion battery–supercapacitor HESS towards a multitype frequency response is presented. First, a multitype frequency response-oriented operational mode for the HESS is designed, outlining the roles and functions of the Li-ion battery and the supercapacitor in delivering distinct services. Moreover, building upon the analysis of the power trajectory of Li-ion batteries, a lifetime model for the HESS is proposed based on the rain-flow counting method. Furthermore, considering the competitive landscape for the HESS in the frequency regulation ancillary service market, a full lifecycle economic assessment model is proposed. Finally, case studies on actual power system frequency data and PJM market data are performed to verify the effectiveness of the proposed method, and the simulation results confirm that the HESS exhibits robust performance and a competitive advantage in providing multitype frequency response services. Additionally, it demonstrates commendable economic benefits, establishing its potential as a valuable contributor to frequency response services.

BackgroundEmerging evidence has demonstrated a close association between perturbations in vaginal microbiota composition in women and human papillomavirus (HPV) infection, cervical lesions, and cervical cancer (Ca); however, these findings are highly heterogeneous and inconclusive.AimTo perform a comprehensive systematic review of the global disturbance in the vaginal microbiota, specifically in women with HPV-associated cervical diseases, and to further conduct within- and across-disease comparisons.MethodTwenty-two records were identified in a systematic literature search of PubMed, Web of Science, and Embase up to February 28, 2022. We extracted microbial changes at the community (alpha and beta diversity) and taxonomic (relative abundance) levels. Within- and across-disease findings on the relative abundance of taxonomic assignments were qualitatively synthesized.ResultsGenerally, significantly higher alpha diversity was observed for HPV infection, cervical lesions, and/or cancer patients than in controls, and significant differences within beta diversity were observed for the overall microbial composition across samples. In within-disease comparisons, the genera Gardnerella, Megasphaera, Prevotella, Peptostreptococcus, and Streptococcus showed the greatest abundances with HPV infection; Sneathia and Atopobium showed inconsistent abundance with HPV infection, and Staphylococcus was observed in Ca. Across diseases, we find increased levels of Streptococcus and varying levels of Gardnerella were shared across HPV infections, high-grade squamous intraepithelial lesions, and Ca, whereas Lactobacillus iners varied depending on the HPV-related disease subtype.ConclusionsThis systematic review reports that vaginal microbiome disturbances are correlated to the depletion of Lactobacillus, enrichment of anaerobes, and increased abundance of aerobic bacteria in HPV infection and related cervical diseases. Moreover, L. iners may exert either protective or pathogenic effects on different HPV-related diseases.

Conventional lower-limb rehabilitation robots are large, complicated to wear, and require moving the patient to a designated position. To solve these problems, a new single-legged lower-limb rehabilitation robot (S-LLRR) that is easy to move and suitable for different height carriers was proposed. The mechanical leg has a variable working space, and its rotating joints are designed with mechanical limiters. The series configuration of the S-LLRR was analyzed, and trajectory planning was performed based on continuous linear motion training. Meanwhile, an active training control method based on the sand model was proposed to enhance the motion sensation of patients, and an active participation degree evaluation model was designed based on human physiological information. The simulation and experimental results showed that S-LLRR had a large workspace and good motion accuracy, and the accuracy of the active participation degree evaluation model could reach more than 85%. This research could provide a theoretical basis for improving the standardization and compliance of lower-limb robot rehabilitation training.

Enterprise Zone is an important part of the regional economic development strategy. This paper investigates the impact of overall urban development and construction of the National Big Data (Guizhou) Experimental Area on the housing prices and found out that the construction of the National Big Data (Guizhou) Experimental Area is more conducive to the rise in suburban housing transaction prices. The paper empirically proves that the construction of the National Experimental Zone is more conducive to small family housing and leads to the increase in the suburban housing trading area, which further implies that the National Big Data (Guizhou) Experimental Area project may lead to the migration of residents to the suburbs, thus the increasing the housing price. Such regional planning is conducive to the changing spatial distribution of the residents, relocating the residents to find jobs and live in the suburbs, and increasing the value of suburban areas. This paper provides evidence to quantify the externalities and the premium of the housing prices in the surrounding area and provides empirical evidence on the spatial externalities in the literature.

With the promotion of carbon peaking and carbon neutrality goals and the construction of renewable-dominated electric power systems, renewable energy will become the main power source of power systems in China. How to ensure the accommodation of renewable energy will also be the core issue in the future development process of renewable-dominated electric power systems. In this context, shared energy storage (SES), a novel business model combined with energy storage technologies and the sharing economy, has the potential to play an important role in renewable energy accommodation scenarios. This paper systematically organizes the application prospect, development status and key technologies of SES in the renewable energy accommodation scenario in the context of China, providing helpful references for the promotion of the business model. Firstly, a typical SES framework for renewable energy accommodation is described, and three basic forms of SES in this scenario are presented. Moreover, the application prospect of SES in the renewable energy accommodation scenario is quantitatively analyzed based on the renewable energy generation planning under the carbon peaking goal and the current guarantee mechanism of renewable energy accommodation. Furthermore, the rules for energy storage systems that provide the peak-regulation ancillary service in typical regions and provincial administrative regions in China are summarized, and the development status of SES in the renewable energy accommodation scenario is analyzed, combined with the actual market data. Finally, the key technologies to promote the further development of SES for renewable energy accommodation are presented.

The glycolytic enzyme enolase 2 (ENO2) is dysregulated in many types of cancer. However, the roles and detailed molecular mechanism of ENO2 in colorectal cancer (CRC) metastasis remain unclear. Here, we performed a comprehensive analysis of ENO2 expression in 184 local CRC samples and samples from the TCGA and GEO databases and found that ENO2 upregulation in CRC samples was negatively associated with prognosis. By knocking down and overexpressing ENO2, we found that ENO2 promoted CRC cell migration and invasion, which is dependent on its interaction with the long noncoding RNA (lncRNA) CYTOR, but did not depend on glycolysis regulation. Furthermore, CYTOR mediated ENO2 binding to large tumor suppressor 1 (LATS1) and competitively inhibited the phosphorylation of Yes-associated protein 1 (YAP1), which ultimately triggered epithelial–mesenchymal transition (EMT). Collectively, these findings highlight the molecular mechanism of the ENO2–CYTOR interaction, and ENO2 could be considered a potential therapeutic target for CRC.

Spherical parallel robots (SPR) are widely used in industries and robotic rehabilitation. Designing such systems for better balance properties is still a challenge. This paper presents a work to minimize the shaking moment for a fully force-balanced SPR by combining the counterweight (CW) and adjusting the kinematic parameters (AKP). An approximate model of the shaking moment of the SPR is proposed for computational efficiency (specifically allowing for a gradient-based optimization algorithm available in MATLAB) yet without the loss of much accuracy. The effectiveness of the proposed approach has been confirmed based on simulation, especially with the software system SPACAR due to its high reliability and easy availability. Specifically, the simulation result shows that compared with the unbalanced SPR, the shaking moment of the balanced SPR can decrease by more than 90%. It is worth mentioning that the AKP approach is an excellent example of mechatronics by combining the capability of re-planning the joint motion from the end-effector motion and adjusting the kinematic parameters to redistribute the mass of the whole robot for canceling the shaking force and shaking moment—inertia-induced force and moment to the ground. In short, the main contributions of this paper are: (1) a combined CW and AKP approach to the partial moment balancing of the SPR enhanced with a simplified mathematical model of the shaking moment of the SPR, and (2) a new design of the SPR which can be fully force balanced yet partially moment balanced. A note is taken that the simplified model is under the condition that the parameters of the link have certain geometric relations, which is a limitation of our approach.

Induction cladding may provide an innovative approach for repairing or remanufacturing grey cast iron components. A complete analysis of the induction cladding technology is important for promoting practical applications. Three commonly used alloy powders were chosen for the research, and the induction cladding technology was thoroughly investigated from three aspects: the coating properties, energy consumption, and unit cost. The porosity, microhardness, and frictional performance were defined as the coating properties. An energy consumption measurement system was set up to quantitatively assess the energy consumption during the induction cladding process. Finally, the unit costs of alloy powders used for the induction cladding were assessed. The results suggest that the Ni-based coating possesses the best coating properties except for a porosity that is relatively high (but still lower than that of coatings fabricated using other surface coating technologies). The microhardness values of Ni-based and Fe-based coatings are higher than that of the Co-based coating, and the Ni-based coating has the lowest coefficient of friction and smallest wear volume. The energy consumptions per unit coating of the three alloy powders are similar, although that of the Fe-based coating is slightly lower. The unit cost of the Co-based alloy powder is approximately three times higher than that of Ni-based and Fe-based alloy powders. Therefore, based on comprehensive assessment, the Ni-based alloy coating shows the best performance.

Abstract Background Long non-coding RNAs (lncRNAs) function as key molecules in cancer progression. The lncRNA CYTOR plays oncogenic roles in multiple types of cancer, yet the detailed molecular mechanisms of those roles remain unknown. The aim of this study was to investigate the clinical significance, biological function and interacting partners of CYTOR in colorectal cancer (CRC). Methods A systematic and comprehensive analysis of CYTOR expression was performed in 138 CRC samples and in the TCGA and GEO databases. Biological function was investigated through knockdown and overexpression of CYTOR in vitro and in vivo. In addition, its protein binding partner was identified and validated using ChIRP-MS and RNA immunoprecipitation assays. Their key interaction sites on CYTOR were verified by CRISPR/Cas9 and a series of mutant constructs. Furthermore, the downstream targets of CYTOR were confirmed via immunoblotting and luciferase reporter assays. Results CYTOR was significantly up-regulated in CRC samples and associated with poor prognosis, promoting proliferation and metastasis in vitro and in vivo. NCL and Sam68 could recognize their specific motifs and directly bind to EXON1 of CYTOR. Moreover, EXON1 was the key functional site mediating the interaction of CYTOR with NCL and Sam68. NCL and Sam68 functioned as oncogenes to promote CRC progression. Furthermore, we confirmed that the heterotrimeric complex of CYTOR, NCL and Sam68 activated the NF-κB pathway and EMT to contribute to CRC progression. Conclusion CYTOR plays important roles in CRC progression by interacting with NCL and Sam68 and may serve as a prognostic biomarker and/or an effective target for CRC therapies.

A new applicable sitting/lying lower limb rehabilitation robot is proposed to help stroke patients. It can realize the sitting/lying training postures to fit people in all the rehabilitation stages. Based on the modularization design, the movable seat can be separated from and grouped into the lower limb rehabilitation robot, which is convenient for patients to sit down. As the most important part of lower limb rehabilitation robot, the mechanical leg design theory is introduced in detail. According to the physician clinical suggestions, a new trajectory planning method is proposed based on the dual quartic polynomial interpolation method. It could realize the adjustment of each joint maximum velocity during the training on account of patient recovery. The accelerations of the joints at target position equal zero, which will reduce impact loads on the patients damaged leg. Also, the dwell time the joints staying at the target angular positions can be increased. Those advantages make the lower limb rehabilitation robot more suitable for stroke patient passive training. Combined with the virtual reality technique, a specific motion-playback scene is designed to improve the patient enthusiasm in the training. Finally, a preliminary experimental trial has been conducted to demonstrate the design of the prototype, the motion-playback scene, and the trajectory planning method feasible.

This study presents a hierarchical background modelling and subtraction approach for real‐time detection of moving objects. At the first level, a novel pixel‐wise background modelling method is proposed for coarse detection. The method can dynamically assign the optimal number of components for each pixel with the borrow–lend strategy. And a flexible learning rate which is variable and different for each component is presented to adapt to scene changes. Additionally, a new mechanism using a framework of finite state machine is introduced to maintain and update the background models. At the second level, in order to deal with sudden illumination changes, a block‐wise foreground validation approach is adopted for refined detection. The authors compare the proposed approach with state‐of‐the‐art methods and experimental results under various scenes demonstrate the robustness and effectiveness of the proposed approach.

A bioactive chemical constituent, doliroside A, from Chinese traditional herbal medicine Dolichos falcata Klein was isolated, purified and identified by 60% ethanol extraction, thin layer chromatography (TLC), high performance liquid chromatography (HPLC) and nuclear magnetic resonance (NMR) spectroscopy. Molecular interaction mechanism between doliroside and amyloid β42 protein was evaluated by thioflavin T fluorescence (ThT), circular dichroism (CD), atomic force microscope (AFM), and differential scanning calorimeter (DSC) from the aspects of kinetics, secondary structure, morphology, and thermodynamics, respectively. Results show that the purity of doliroside A is 99.9% by HPLC, and its chemical structure is identified by 1H- and 13C-NMR. Doliroside A is observed to be concentration-dependent inhibiting the fibrillation of Aβ42 with the IC50 value of 26.57 ± 1.6 μM. CD and DSC results imply that doliroside A can bind to the nuclei and oligomers of Aβ42 to form a stable complex and suppress Aβ42 fibrillation. AFM images show that doliroside A, after bound to the nuclei and oligomers, redirect Aβ42 into off-pathway, amorphous oligomers. These findings not only provide a full insight into the molecular interaction mechanisms between Aβ42 and doliroside A, but also facilitate the development of new native anti-AD drug of doliroside A compound.

Lower-limb function in elderly people gradually degenerates with age, and poor rehabilitation conditions preventing the elderly from receiving scientific rehabilitation training result in the decline of social labor force and the increased economic burden of the elderly. Aiming at the characteristics of the single function and the complex structure of an existing telescopic leg trainer combined with the needs of the application group, a new type of leg-stretching training device with multiple training modes for lower extremity extension and flexion of the elderly is proposed. A new mechanical structure and electrical system is designed. At the same time, the anti-resistance training man−machine model is analyzed, aiming at the isokinetic resistance training mode, and a training controller strategy based on a fuzzy synovial algorithm is proposed. Finally, the feasibility of the designed controller strategy and the proposed leg training device are verified by prototype experiments, which will guide further research.

SLC7A11 is a cystine transporter and ferroptosis inhibitor. How the stability of SLC7A11 is coordinately regulated in response to environmental cystine by which E3 ligase and deubiquitylase (DUB) remains elusive. Here, we report that neddylation inhibitor MLN4924 increases cystine uptake by causing SLC7A11 accumulation, via inactivating Cullin-RING ligase-3 (CRL-3). We identified KCTD10 as the substrate-recognizing subunit of CRL-3 for SLC7A11 ubiquitylation, and USP18 as SLC7A11 deubiquitylase. Upon cystine deprivation, the protein levels of KCTD10 or USP18 are decreased or increased, respectively, contributing to SLC7A11 accumulation. By destabilizing or stabilizing SLC7A11, KCTD10, or USP18 inversely regulates the cystine uptake and ferroptosis. Biologically, MLN4924 combination with SLC7A11 inhibitor Imidazole Ketone Erastin (IKE) enhanced suppression of tumor growth. In human breast tumor tissues, SLC7A11 levels were negatively or positively correlated with KCTD10 or USP18, respectively. Collectively, our study defines how SLC7A11 and ferroptosis is coordinately regulated by the CRL3KCTD10/E3-USP18/DUB axis, and provides a sound rationale of drug combination to enhance anticancer efficacy. [ABSTRACT FROM AUTHOR]

Upon the request and guidance of SC 6/AG 4 Convenor Kingston ZHANG, a research group has been formed for study the potential impact of Artificial Intelligence on MCS Innovation and to evaluate how can AG 4's work contribute to the next stage of SC 6/WG 7's Future Network standardization program. This is a preliminary report. [ABSTRACT FROM AUTHOR]