Prescribed performance-based powered descent guidance for step-shaped hazardous terrains

The planetary powered descent guidance problem for step-shaped hazardous terrains is investigated in this article based on prescribed performance function (PPF) methodology. Initially, the distances between the lander and step-shaped terrains around the landing site have been formulated in a new form boundaryfunction using PPF, in which a new step-shaped boundary PPF is specifically designed to constrain the lateral motion. Furthermore, a fixed-time convergent PPF is chosen to coordinate the vertical motion. Next, to avoid the collision with step-shaped terrains and planetary surface, a feedback guidance algorithm is proposed based on the backstepping method. Considering a large guidance gain is beneficial for the lander to move away from the boundary PPF, but excessive control acceleration will be generated when the landing error is large. To solve this problem, an adaptive guidance gain is designed using Gaussian function. Finally, the feasibility and effectiveness of the proposed algorithm have been verified through typical numerical simulations inspired by realistic Martian terrains. Moreover, this attempt using PPF methodology here can be easily reformulated to adjust the powered descent problem with collision avoidance for a flat surface or glide-slope constraint.</p

Barrier Lyapunov function-based planetary landing guidance for hazardous terrains

The landing guidance based on the barrier Lyapunov function (BLF) for hazardous terrains is investigated. Three suitable spatial geometric shapes (frustum-shape, cone-shape, and &lt;formula&gt;&lt;tex&gt;$n$&lt;/tex&gt;&lt;/formula&gt;-step-shape) have been chosen to describe the possible obstacles on the planetary surface. Next, a novel and general form of the barrier function (BF) has been developed using selected spatial geometric shape information, specifically designed to constrain the lateral motion. For these three different spatial geometric shapes, only the segment number of BF is different, and the segment number is determined by the spatial geometric shape. Furthermore, a fixed-time convergent function is selected as the upper boundary to coordinate the vertical motion, guaranteeing that the lander completes the landing mission within the predefined time. Next, a new nonlinear feedback guidance is designed using the asymmetric BLF constructed by the BF, keeping the lander from colliding with the obstacle and achieving the pinpoint soft landing. Finally, numerical simulations with different hazardous terrains are performed to verify the feasibility and effectiveness of the proposed algorithms.</p

Additional file 1: of Preclinical modeling and multimodality imaging of chronic myocardial infarction in minipigs induced by novel interventional embolization technique

Classic methods have been fully described by previous investigators and introduced. (DOCX 29 kb

Study design of deep learning based automatic detection of cerebrovascular diseases on medical imaging: a position paper from Chinese Association of Radiologists

In recent years, with the development of artificial intelligence, especially deep learning technology, researches on automatic detection of cerebrovascular diseases on medical images have made tremendous progress and these models are gradually entering into clinical practice. However, because of the complexity and flexibility of the deep learning algorithms, these researches have great variability on model building, validation process, performance description and results interpretation. The lack of a reliable, consistent, standardized design protocol has, to a certain extent, affected the progress of clinical translation and technology development of computer aided detection systems. After reviewing a large number of literatures and extensive discussion with domestic experts, this position paper put forward recommendations of standardized design on the key steps of deep learning-based automatic image detection models for cerebrovascular diseases. With further research and application expansion, this position paper would continue to be updated and gradually extended to evaluate the generalizability and clinical application efficacy of such tools