NLRP3 Inflammasome as a Molecular Marker in Diabetic Cardiomyopathy

Diabetic cardiomyopathy (DCM), a common consequence of longstanding diabetes mellitus, is initiated by death of cardiomyocyte. Hyperglycemia-induced reactive oxygen species (ROS) overproduction is a major contributor of the chronic low-grade inflammation that characterizes as the DCM. ROS may promote the activation of nucleotide-binding oligomerization domain like receptor (NLR) pyrin domain containing 3 (NLRP3) inflammasome, a novel regulator of inflammation and cell death, by nuclear factor-kB (NF-κB) and thioredoxin interacting/inhibiting protein (TXNIP). NLRP3 inflammasome regulates the death of cardiomyocyte and activation of fibroblast in DCM, which is involved in the structural and functional disorder of DCM. However, comprehensive understanding of molecular mechanisms linking NLRP3 inflammasome and disorder of cardiomyocyte and fibroblast in DCM is lacking. Here, we review the molecular mechanism(s) of NLRP3 inflammasome activation in response to hyperglycemia in DCM

Monitoring Water and Energy Cycles at Climate Scale in the Third Pole Environment (CLIMATE-TPE)

A better understanding of the water and energy cycles at climate scale in the Third Pole Environment is essential for assessing and understanding the causes of changes in the cryosphere and hydrosphere in relation to changes of plateau atmosphere in the Asian monsoon system and for predicting the possible changes in water resources in South and East Asia. This paper reports the following results: (1) A platform of in situ observation stations is briefly described for quantifying the interactions in hydrosphere-pedosphere-atmosphere-cryosphere-biosphere over the Tibetan Plateau. (2) A multiyear in situ L-Band microwave radiometry of land surface processes is used to develop a new microwave radiative transfer modeling system. This new system improves the modeling of brightness temperature in both horizontal and vertical polarization. (3) A multiyear (2001–2018) monthly terrestrial actual evapotranspiration and its spatial distribution on the Tibetan Plateau is generated using the surface energy balance system (SEBS) forced by a combination of meteorological and satellite data. (4) A comparison of four large scale soil moisture products to in situ measurements is presented. (5) The trajectory of water vapor transport in the canyon area of Southeast Tibet in different seasons is analyzed, and (6) the vertical water vapor exchange between the upper troposphere and the lower stratosphere in different seasons is presented

JOINT DESIGN AND MOTION RESEARCH OF ENTERTAINMENT ANTHROPOMORPHIC ROBOT

Joint design and motion research is key to the design and research of entertainment Anthropomorphic robot,It direct impact on attitude and balance of robot motion. So,we focus on research Joint structure design and joint movement. Joint of robot hand and foot is designed by human engineering principle and finite element analysis method. Solution of joint position and velocity is obtained base on establishing joint coordinates and calculation. Effective solve robot movement in the process of stability with analysis of the balance of motion. Find a way to achieve robot walking,turning and lateral movement and other humanoid movements by the study the effect of the slip and calculation of the sliding force. A fixed frequency current control method is proposed,and realized robot key gait planning

A Robust Text Detection Algorithm in Images and Video Frames

In this paper, an algorithm for detecting text in images and video frames is proposed. The algorithm contains two steps: initial detection and verification. In the first step, edge feature and morphology operation are employed to locate edge-dense image blocks. Empirically rules are applied on these blocks to get candidate text. In the second step, wavelet-based features are employed to represent the texture property of text. A SVM classifier is used to identify text from the candidate ones. Experiments show that this algorithm has 93.9 % detection rate for English text and a 92.4 % detection rate for Chinese text. The algorithm is robust to language, font- color and size. 1

A novel compressed domain shot segmentation algorithm on H.264/AVC

This paper presents a novel shot segmentation algorithm on the H.264/AVC video, which operates in the compressed domain. First, the algorithm exploits the intra prediction mode histogram to locate those potential GOPs, where shot transitions occur with great probability. Secondly, to further find shot boundaries at the frame level, we count the number of macroblocks with different inter prediction modes as the features and exploit HMMs to automatically model different cases in which shot transitions can occur among I, P and B frames. Since H.264/AVC provides more motion compensation modes, using HMMs can avoid the tediousness of manually tuning multiple thresholds simultaneously. The experimental results show that the algorithm is efficient and robust, and it can not only locate cuts, but also work for gradual shot transitions. 1

GL-STGCNN: Enhancing Multi-Ship Trajectory Prediction with MPC Correction

In addressing the challenges of trajectory prediction in multi-ship interaction scenarios and aiming to improve the accuracy of multi-ship trajectory prediction, this paper proposes a multi-ship trajectory prediction model, GL-STGCNN. The GL-STGCNN model employs a ship interaction adjacency matrix extraction module to obtain a more reasonable ship interaction adjacency matrix. Additionally, after obtaining the distribution of predicted trajectories using the model, a model predictive control trajectory correction method is introduced to enhance the accuracy and reasonability of the predicted trajectories. Through quantitative analysis of different datasets, it was observed that GL-STGCNN outperforms previous prediction models with a 31.8% improvement in the average displacement error metric and a 16.8% improvement in the final displacement error metric. Furthermore, trajectory correction through model predictive control shows a performance boost of 44.5% based on the initial predicted trajectory distribution. While GL-STGCNN excels in multi-ship interaction trajectory prediction by reasonably modeling ship interaction adjacency matrices and employing trajectory correction, its performance may vary in different datasets and ship motion patterns. Future work could focus on adapting the model’s ship interaction adjacency matrix modeling to diverse environmental scenarios for enhanced performance

A Multi-Source Data Fusion Method for Assessing the Tunnel Collapse Risk Based on the Improved Dempster–Shafer Theory

Collapse is the main engineering disaster in tunnel construction when using the drilling and blasting method, and risk assessment is one of the important means to significantly reduce engineering disasters. Aiming at the problems of random decision-making and misjudgment of single indices in traditional risk assessment, a multi-source data fusion method with high accuracy based on improved Dempster–Shafer evidence theory (D-S model) is proposed in this study, which can realize the accurate assessment of tunnel collapse risk value. The evidence conflict coefficient K is used as the identification index, and the credibility and importance are introduced. The weight coefficient is determined according to whether the conflicting evidence is divided into two situations. The advanced geological forecast data, on-site inspection data and instrument monitoring data are trained by Cloud Model (CM), Gradient Boosting Decision Tree (GBDT) and Support Vector Classification (SVC), respectively, to obtain the initial BPA value. Combined with the weight coefficient, the identified conflict evidence is adjusted, and then the evidence from different sources is fused to obtain the overall collapse risk value. Finally, the accuracy is selected to verify the proposed method. The proposed method has been successfully applied to Wenbishan Tunnel. The results show that the evaluation accuracy of the proposed multi-source information fusion method can reach 88%, which is 16% higher than that of the traditional D-S model and more than 20% higher than that of the single-source information method. The high-precision multi-source data fusion method proposed in this paper has good universality and effectiveness in tunnel collapse risk assessment

Characteristics of Unorganized Hydrogen Sulfide Dispersion for Industrial Building Layout Optimization

Hydrogen sulfide (H2S) is the main toxic pollutant emitted to the atmosphere from auto-coating wastewater. Its unorganized dispersion poses a health challenge for workers. Defining safe working distance, which transfers the H2S occupational exposure limit into industrial construction design regulation, would be a useful approach for reducing H2S exposure risk. Therefore, in this study, an H2S dispersion prediction, within 25 m, was performed by a computational fluid dynamics (CFD) method to explore the influence of temperature and wind speed on H2S dispersion. With the temperature changes from 288 K to 303 K, the H2S concentration at different observing points decreased. With wind speed changes from 2 m/s to 20 m/s, the plume layer structure was studied in the whole process. According to the H2S distribution characteristics, when the sedimentation tank treatment capacity is less than or equal to 10 m3/h, the safe working distance of H2S unorganized dispersion is 10 m. Hence, when there are workplaces within 10 m of the tank, closed measures should be taken for the sedimentation tank, or the manufacturer layout should be optimized to protect the environment and human health