Enhanced Path Planning and Obstacle Avoidance Based on High-Precision Mapping and Positioning.

High-precision positioning and multi-target detection have been proposed as key technologies for robotic path planning and obstacle avoidance. First, the Cartographer algorithm was used to generate high-quality maps. Then, the iterative nearest point (ICP) and the occupation probability algorithms were combined to scan and match the local point cloud, and the positions and attitudes of the robot were obtained. Furthermore, Sparse Matrix Pose Optimization was carried out to improve the positioning accuracy. The positioning accuracy of the robot in x and y directions was kept within 5 cm, the angle error was controlled within 2°, and the positioning time was reduced by 40%. An improved timing elastic band (TEB) algorithm was proposed to guide the robot to move safely and smoothly. A critical factor was introduced to adjust the distance between the waypoints and the obstacle, generating a safer trajectory, and increasing the constraint of acceleration and end speed; thus, smooth navigation of the robot to the target point was achieved. The experimental results showed that, in the case of multiple obstacles being present, the robot could choose the path with fewer obstacles, and the robot moved smoothly when facing turns and approaching the target point by reducing its overshoot. The proposed mapping, positioning, and improved TEB algorithms were effective for high-precision positioning and efficient multi-target detection.

Visual Sensing and Depth Perception for Welding Robots and Their Industrial Applications.

With the rapid development of vision sensing, artificial intelligence, and robotics technology, one of the challenges we face is installing more advanced vision sensors on welding robots to achieve intelligent welding manufacturing and obtain high-quality welding components. Depth perception is one of the bottlenecks in the development of welding sensors. This review provides an assessment of active and passive sensing methods for depth perception and classifies and elaborates on the depth perception mechanisms based on monocular vision, binocular vision, and multi-view vision. It explores the principles and means of using deep learning for depth perception in robotic welding processes. Further, the application of welding robot visual perception in different industrial scenarios is summarized. Finally, the problems and countermeasures of welding robot visual perception technology are analyzed, and developments for the future are proposed. This review has analyzed a total of 2662 articles and cited 152 as references. The potential future research topics are suggested to include deep learning for object detection and recognition, transfer deep learning for welding robot adaptation, developing multi-modal sensor fusion, integrating models and hardware, and performing a comprehensive requirement analysis and system evaluation in collaboration with welding experts to design a multi-modal sensor fusion architecture.

Instance Segmentation and Ensemble Learning for Automatic Temperature Detection in Multiparous Sows.

The core body temperature serves as a pivotal physiological metric indicative of sow health, with rectal thermometry prevailing as a prevalent method for estimating core body temperature within sow farms. Nonetheless, employing contact thermometers for rectal temperature measurement proves to be time-intensive, labor-demanding, and hygienically suboptimal. Addressing the issues of minimal automation and temperature measurement accuracy in sow temperature monitoring, this study introduces an automatic temperature monitoring method for sows, utilizing a segmentation network amalgamating YOLOv5s and DeepLabv3+, complemented by an adaptive genetic algorithm-random forest (AGA-RF) regression algorithm. In developing the sow vulva segmenter, YOLOv5s was synergized with DeepLabv3+, and the CBAM attention mechanism and MobileNetv2 network were incorporated to ensure precise localization and expedited segmentation of the vulva region. Within the temperature prediction module, an optimized regression algorithm derived from the random forest algorithm facilitated the construction of a temperature inversion model, predicated upon environmental parameters and vulva temperature, for the rectal temperature prediction in sows. Testing revealed that vulvar segmentation IoU was 91.50%, while the predicted MSE, MAE, and R2 for rectal temperature were 0.114 °C, 0.191 °C, and 0.845, respectively. The automatic sow temperature monitoring method proposed herein demonstrates substantial reliability and practicality, facilitating an autonomous sow temperature monitoring.

DAssd-Net: A Lightweight Steel Surface Defect Detection Model Based on Multi-Branch Dilated Convolution Aggregation and Multi-Domain Perception Detection Head.

During steel production, various defects often appear on the surface of the steel, such as cracks, pores, scars, and inclusions. These defects may seriously decrease steel quality or performance, so how to timely and accurately detect defects has great technical significance. This paper proposes a lightweight model based on multi-branch dilated convolution aggregation and multi-domain perception detection head, DAssd-Net, for steel surface defect detection. First, a multi-branch Dilated Convolution Aggregation Module (DCAM) is proposed as a feature learning structure for the feature augmentation networks. Second, to better capture spatial (location) information and to suppress channel redundancy, we propose a Dilated Convolution and Channel Attention Fusion Module (DCM) and Dilated Convolution and Spatial Attention Fusion Module (DSM) as feature enhancement modules for the regression and classification tasks in the detection head. Third, through experiments and heat map visualization analysis, we have used DAssd-Net to improve the receptive field of the model while paying attention to the target spatial location and redundant channel feature suppression. DAssd-Net is shown to achieve 81.97% mAP accuracy on the NEU-DET dataset, while the model size is only 18.7 MB. Compared with the latest YOLOv8 model, the mAP increased by 4.69%, and the model size was reduced by 23.9 MB, which has the advantage of being lightweight.

Soybean image dataset for classification.

This paper presents a dataset with 5513 images of individual soybean seeds, which encompass five categories: (Ⅰ) Intact, (Ⅱ) Immature, (Ⅲ) Skin-damaged, (Ⅳ) Spotted, and (Ⅴ) Broken. Furthermore, there are over 1000 images of soybean seeds in each category. Those images of individual soybeans were classified into five categories based on the Standard of Soybean Classification (GB1352-2009) [1]. The soybean images with the seeds in physical touch were captured by an industrial camera. Subsequently, individual soybean images (227×227 pixels) were divided from the soybean images (3072×2048 pixels) using an image-processing algorithm with a segmentation accuracy of over 98%. The dataset can serve to study the classification or quality assessment of soybean seeds.

Design and analysis of welding inspection robot.

Periodic inspection, commonly performed by a technician, of weld seam quality is important for assessing equipment reliability. To save labor costs and improve efficiency, an autonomous navigation and inspection robot is developed. The development process involves the design of chassis damping, target detection mechanism, control system, and algorithms. For performing weld inspection in complex, outdoor, environments, an algorithm is developed for the robot to avoid any obstacles. This algorithm for planning the inspection route is based on an improved timed-elastic-band (TEB) algorithm. The developed robot is capable of conducting inspection tasks in complex and dangerous environments efficiently and autonomously.

Preparation of Electrode Materials Based on Carbon Cloth via Hydrothermal Method and Their Application in Supercapacitors.

Supercapacitors have the unique advantages of high power density, fast charge and discharge rates, long cycle life, high safety, and reliability, and are increasingly being used for applications including automobiles, rail transit, communication equipment, digital electronics, and aerospace equipment. The supercapacitor industry is currently in a stage of rapid development; great breakthroughs have also been made in improving the performance of supercapacitors and the expansion of their application. Electrode technology is the core of supercapacitors. Transition-metal compounds have a relatively high theoretical capacity and have received widespread attention as electrode materials for supercapacitors. In addition, there is a synergistic effect between the different components of various electrode composite materials. Due to their superior electrochemical performance, supercapacitors are receiving increasing research attention. Flexible supercapacitors have been hailed for their good plasticity, resulting in a development boom. This review article mainly outlines the development process of various electrode materials, including carbon materials, conductive polymers, metal compounds, and composite materials, as well as flexible electrode materials based on carbon cloth.

Induction of Necroptosis in Human Breast Cancer Drug-Resistant Cells by SMAC Analog LCL161 After Caspase Inhibition Requires RIP3.

LCL161 is a second mitochondrial activator of caspases (SMAC) mimetic and inhibitor of apoptosis protein (IAP) antagonist that has oral bioavailability, exhibits anti-tumor effects and improves the chemical sensitivity of many cancers. The aim of this study was to ascertain the effects and mechanisms of the SMAC analog LCL161 on breast cancer drug-resistant cells after undergoing caspase inhibition. This was achieved through use of colony formation and CCK-8 assays to detect cell proliferation. Flow cytometry, Western blot analysis, ATP assay, immunofluorescence and siRNA transfection were used to study the molecular mechanisms of LCL161-induced death of cisplatin-resistant MCF-7 cells after caspase inhibition. LCL161 exhibited an inhibitory effect on MCF-7/DDP cells including after inhibition of caspase. However, LCL161 could not on its own induce a necroptosis effect on MCF-7/DDP cells (P < 0.01 or P < 0.001). When used jointly with the caspase inhibitor z-VAD-fmk, it significantly decreased intracellular ATP levels (P < 0.01 or P < 0.05). This induction of necroptosis occurred through the activation of the RIP1-RIP3-MLKL programmed cell necrosis cascade. Knockdown of RIP3 using siRNA protected against the combined LCL161 / z-VAD-fmk-induced cell death (P < 0.01 or P < 0.001). These findings support the hypothesis that LCL161 combined with caspase inhibition can induce a necroptosis effect on MCF-7/DDP cells, suggesting that it has potential to be an effective treatment for breast cancer.

Synthesis and Characterization of WO3/Graphene Nanocomposites for Enhanced Photocatalytic Activities by One-Step In-Situ Hydrothermal Reaction.

Tungsten trioxide (WO3) nanorods are synthesized on the surface of graphene (GR) sheets by using a one-step in-situ hydrothermal method employing sodium tungstate (Na2WO4·2H2O) and graphene oxide (GO) as precursors. The resulting WO3/GR nanocomposites are characterized by X-ray diffraction, Raman spectroscopy, transmission electron microscopy, scanning electron microscopy and X-ray photoelectron spectroscopy. The results confirm that the interface between WO3 nanorod and graphene contains chemical bonds. The enhanced optical absorption properties are measured by UV-vis diffuse reflectance spectra. The photocatalytic activity of the WO3/GR nanocomposites under visible light is evaluated by the photodegradation of methylene blue, where the degradation rate of WO3/GR nanocomposites is shown to be double that of pure WO3. This is attributed to the synergistic effect of graphene and the WO3 nanorod, which greatly enhances the photocatalytic performance of the prepared sample, reduces the recombination of the photogenerated electron-hole pairs and increases the visible light absorption efficiency. Finally, the photocatalytic mechanism of the WO3/GR nanocomposites is presented. The synthesis of the prepared sample is convenient, direct and environmentally friendly. The study reports a highly efficient composite photocatalyst for the degradation of contaminants that can be applied to cleaning up the environment.

[Effect of all trans retinoid acid (ATRA) on differentiation and apoptosis of HL-60 cell].

BACKGROUND & OBJECTIVE: Treatment of premyeloid leukemia with all trans retinoid acid (ATRA) is a milestone in the history of chemotherapy of malignant tumor. Previous studies suggested that the mechanism of treating premyeloid leukemia with ATRA is inducing premyeloid leukemia cells to differentiate along myelocyte lineage, but the fate of differentiated tumor cells is not clear. This study was designed to investigate the relationship between the differentiation of HL-60 induced by ATRA and apoptosis. METHODS: HL-60 cells influenced by ATRA (10 micromol/L) capable of inducing differentiation for different time were used as the subject. The differentiation marker on the cell surface and cell cycle were analyzed using flow cytometry. The differentiated cells were identified by confocal microscope after having been stained with propidium iodide (PI). Meanwhile,the changes of the apoptosis of the cells induced by ATRA at different time were analyzed using flow cytometry. RESULTS: (1)With drug-inducing time increasing, the volume of the differentiated cells was enlarged gradually. After 72 hours, the differentiated cells began to express differentiating marker CD11b and the nuclei morphology of the differentiated cells was changed. (2)After 96 hours of drug-inducing, the induced cells began to show apoptosis peak, but when the cells was washed once after 72 hours of drug-inducing with RPMI 1640 medium and resuspended in RPMI 1640 medium supplemented with 10% fetal calf serum and then cultured in 5%CO2, 37 centigrade for 8 hours,the cells began to show apoptosis peak,and the apoptosis peak was higher than that of the cells after 96 hours of drug-inducing. CONCLUSION: ATRA cannot induce HL-60 to achieve terminal differentiation,but the differentiation of HL-60 can be induced by ATRA and the differentiated leukemia cells are easy to apoptosis.