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Substation is an important part of power system, and regular inspection is very important to ensure the safe operation of substation. Patrol robot can patrol power equipment in few or unattended substations. In order to obtain the global optimal path of the robot, this paper proposes a navigation path planning based on improved wolf pack algorithm (IWPA). Firstly, the path optimization in discrete domain is studied by introducing position-order coding in initialization stage. Secondly, improve the moving step of the attack behavior and improve the efficiency of the running behavior. Finally, the updating rules of IWPA increase the diversity of wolves to enhance the global optimization ability of the algorithm. Finally, both IWPA and Wolf Pack Algorithm (WPA) are simulated, and the results show that the improved algorithm is more effective in solving the navigation path planning problem of inspection robot.

The spontaneous combustion of coal pile is very easy to cause fires, especially in the closed coal yards. Early detection and disposal of spontaneous-combustion-point (SCP) could avoid large losses. However, the traditional SCP detection methods are confronted with problem of hysteresis, and cannot effectively detect the small SCP in early stage. This paper proposes a novel detection method based on Yolov5s, by using “FPN+ PAN” in the Neck layer to enhance the SCP expressions. To improve the performance of the model in learning the characteristic of small SCP, the block labeling approach is applied in the labeling process. In addition, TensorRT is adopted to accelerate the forward inference of the model, and the deployment test is carried out on Jetson nano. Through comparative analysis, the proposed method outperforms yolov3s and yolov4s in detecting the SCP in very early stage (smoke or flame), and achieves 7 FPS speed in real-time video stream.

Cardiovascular diseases is a major cause of deaths in many developed countries. To treat cardiovascular diseases, minimally invasive cardiac intervention is widely used as an effective yet complicated solution. Training of cardiac intervention thus plays a crucial role. This paper addresses the use of Virtual Reality (VR) technology for the simulated training of cardiac intervention. In particular, the paper describes the architecture of a simulation system for virtual cardiac intervention. The framework proposed consists of hardware component, software component and methodology component. As an enabling technology, Graphics Processing Unit (GPU) is applied in this work to enhance cardiac modeling, cardiac visualization, and cardiac interaction with the VR simulation environment

Much efforts have been made to develop realistic cardiac models for clinical and research purposes. However, to implement these models always needs to handle excessive computational loads due to the complex and dynamic natures of the heart given limited computational power of Central Processing Unit (CPU). In this paper, a real-time approach to cardiac modeling is proposed based on the Graphics Processing Unit (GPU). A hardware platform is first designed and tested with a simplified model to represent the cardiac activities. Motion of mesh-based heart is then approximated to simulate the movement of each vertex. Time functions are used within the GPU platform to describe the cardiac cycle. The parallel computing feature of GPU platform significantly speeds up the computation process in real-time with over 140,000 vertices motion based on the time functions. The program is developed on top of CUDA architecture proposed and developed by nVIDIA. Computational Experiments show visualization of the cardiac dynamics is significantly benefiting from this new solution. Further improvement of the GPU based cardiac simulation is discussed.

The Lipid Mass Spectrum Analysis Database (LMSAD) is an object-relational database encompassing MS data, structures and annotations of biologically relevant lipids. The initial version of this database contains about 80 records, representing mainly sphingolipids. LMSAD supports data searching by any combination of these data fields: LMSAD ID, systematic or common name, mass, formula and category data fields. Search results, in addition to annotations and structure, also include mass spectral data information, which will be shown by an applet tool named LipidMSViewer. LipidMSViewer provides some useful functions to analyze mass spectral data and identify unknown lipids obtained by experiments. The LMSAD is publicly available at http://lipid.zju.edu.cn/

Cardiovascular disease is the number one cause of death today in developed countries and is projected to remain so. Cardiac intervention is a minimally invasive solution to diagnose and treat the disease. Training of young cardiologists is playing an important role towards quality cardiac healthcare. The advance of interactive and graphics technologies has offered a new avenue to train young cardiologists using virtual patients which can tremendously reduce the cost and risk. This paper presents a novel interactive simulation for cardiac intervention. Two-body collision between the catheter and the heart wall is detected based on a boundary representation. GPU based algorithms are developed to enhance the performance of simulator for real-time and realistic cardiac intervention.

Cardiovascular diseases account for a major cause of deaths in many developed countries. To treat cardiovascular diseases, cardiac minimally intervention is widely used as an effective yet complicated solution. Training of cardiac intervention is thus playing a crucial role. This paper addresses the use of Virtual Reality (VR) technology for the simulated training of cardiac intervention. In particular, the paper describes the architecture of a VR simulation system for cardiac intervention focusing on VR hardware, software and methodology is used in As an enabling technology, Graphics Processing Unit (GPU) is applied in this work to enhance cardiac modeling, cardiac visualization, and cardiac interactive simulation with the VR simulation environment.

Summary: QTLNetwork is a software package for mapping and visualizing the genetic architecture underlying complex traits for experimental populations derived from a cross between two inbred lines. It can simultaneously map quantitative trait loci (QTL) with individual effects, epistasis and QTL–environment interaction. Currently, it is able to handle data from F2, backcross, recombinant inbred lines and double-haploid populations, as well as populations from specific mating designs (immortalized F2 and BCnFn populations). The Windows version of QTLNetwork was developed with a graphical user interface. Alternatively, the command-line versions have the facility to be run in other prevalent operating systems, such as Linux, Unix and MacOS. Availability: http://ibi.zju.edu.cn/software/qtlnetwork Contact: jzhu@zju.edu.cn

This paper considers the problem of computing the Bézier representation for a triangular sub-patch on a triangular Bézier surface. The triangular sub-patch is defined as a composition of the triangular surface and a domain surface that is also a triangular Bézier patch. Based on de Casteljau recursions and shifting operators, previous methods express the control points of the triangular sub-patch as linear combinations of the construction points that are constructed from the control points of the triangular Bézier surface. The construction points contain too many redundancies. This paper derives a simple explicit formula that computes the composite triangular sub-patch in terms of the blossoming points that correspond to distinct construction points and then an efficient algorithm is presented to calculate the control points of the sub-patch.