Search

Background. The purpose of this study was to evaluate the sex differences in myocardial structure, tissue characteristics, and myocardial function in type 2 diabetes mellitus (T2DM) patients. Methods. A total of 62 T2DM patients and 40 controls were prospectively recruited for the study. All the participants were scanned using cardiovascular magnetic resonance (CMR) cine and underwent native and postcontrast T1 mapping to obtain left ventricular (LV) structure, function, and tissue characteristics. The differences between the control and T2DM patients were compared in males and females, respectively. Results. For myocardial structure, T2DM was associated with a larger ratio of myocardial mass to end-diastolic volume (MVR, T2DM: 0.87 ± 0.20 vs. controls: 0.73 ± 0.14 , p = 0.008 ) and thicker wall thickness (WT, T2DM: 6.5 ± 1.1 mm vs. controls: 5.6 ± 1.0 mm, p = 0.002 ) in females. For tissue characteristics, T2DM was associated with a similar T1 value, elevated extracellular volume fraction (ECV, T2DM: 27.8 ± 3.6 % vs. controls: 25.1 ± 2.5 %, p = 0.002 ), and increased extracellular matrix volume index (ECMVi, T2DM: 15.8 ± 3.8 ml/m2 vs. controls: 13.4 ± 2.7 ml/m2, p = 0.008 ) in males. For myocardial function, in male, compared with control, T2DM was associated with decreased peak longitudinal diastolic strain rate (PLDSR, T2DM: 0.97 ± 0.19 1/s vs. control: 1.13 ± 0.29 1/s, p = 0.030 ). Conclusions. There might be sex differences in myocardial remodeling induced by T2DM, including LV structural concentric remodeling in female patients and extracellular matrix remodeling and subclinical diastolic dysfunction in male patients.

Optimal control problems are common in aerospace engineering. A Python software program called PySCP is described for solving multiple-phase optimal control problems using sequential convex programming methods. By constructing a series of approximated second-order cone programming subproblems, PySCP approaches to the solution of the original optimal control problem in an iterative way. The key components of the software are described in detail, including convexification, discretization, and the adaptive trust region method. The convexification of the first-order differential dynamic equation is implemented using successive linearization. Six discretization methods, including zero-order hold, first-order hold, Runge-Kutta, and three hp pseudospectral collocation methods, are implemented so that different types of optimal control problems can be tackled efficiently. Adaptive trust region method is employed, and robust convergence is achieved. Both free-final-time problem and fixed-final-time problem can be solved by the software. The application of the software is demonstrated on three optimal control problems with varying complexity. PySCP provides researchers a useful toolkit to solve a wide variety of optimal control problems using sequential convex programming.

Small satellites have gradually become an important mean of space scientific exploration. The Tsinghua University developed a spherical small satellite, Q-SAT, which is aimed at detecting the Earth gravity and atmosphere parameters. In the current paper, thermal control for Q-SAT is discussed. For heat exchange between the satellite and the environment, radiation plays the main part. Different from traditional cuboid satellites, the current spherical satellite has no individual heat input and output plane which brings challenges to the thermal design of the satellite. In addition, the cost of small satellites is required to be as low as possible. A passive thermal control solution based on integrated spherical structure is employed on the Q-SAT. The combination of two integrated hemispheres is designed to facilitate the heat conduction. Different materials are utilized to control the heat transfer path. Firstly, a set of numerical simulations demonstrate that the current design can be well adapted to complex flight environment. Next, the thermal design is verified by thermal tests. As the traditional heat radiation lamps cannot meet the test requirements of the spherical satellite, an external heat flow test method which is based on distributed heaters is proposed. Results from numerical simulations agree well with the experimental test results. Both results show that the thermal system can guarantee the functions of the satellite. Q-SAT was successfully launched into orbit on August 6, 2020. The telemetry data from Q-SAT verified the effectiveness of the satellite thermal system. The thermal design and test method proposed in present paper can potentially be adopted to other small scientific satellites as well.

In order to explore the curative effect of early enteral nutrition nursing on patients with severe acute pancreatitis and the improvement of patients’ mental health and inflammation levels, this paper compares the curative effect of early enteral nutrition nursing and traditional care on patients with severe acute pancreatitis and the improvement effects of patients’ mental health and inflammation levels through controlled trials. Moreover, this paper combines statistical methods for data processing and visually expresses data through statistical graphs and statistical tables. Through the comparison of experiments, it can be seen that the improvement effect in all aspects of patients in the test group is significantly higher than that in the control group. Finally, through the analysis of the test results, it can be known that the use of early enteral nutrition nursing for patients with acute severe acute pancreatitis has a certain effect in improving their nutritional status, regulating immune function, and promoting mental health.

By using the techniques of Manifold Embedding and Laplacian Eigenmaps, a novel strategy has been proposed in this paper to detect the chaos of Dow Jones Industrial Average. Firstly, the chaotic attractor of financial time series is assumed to lie on a low-dimensional manifold that is embedded into a high-dimensional Euclidean space. Then, an improved phase space reconstruction method and a nonlinear dimensionality reduction method are introduced to help reveal the structure of the chaotic attractor. Next, the empirical study on the financial time series of Dow Jones Industrial Average shows that there exists an attractor which lies on a manifold constructed by the time sequence of Moving average convergence divergence; finally, Determinism Test, Poincaré section, and translation analysis are used as test approaches to prove both whether it is a chaos and how it works.

A novel model for cascading failures in a directed logic network based on the degree strength at a node was proposed. The definitions of in-degree and out-degree strength of a node were initially reconsidered, and the load at a nonisolated node was proposed as the ratio of in-degree strength to out-degree strength of the node. The cascading failure model based on degree strength was applied to the logic network for three types of cancer including adenocarcinoma of lung, prostate cancer, and colon cancer based on their gene expression profiles. In order to highlight the differences between the three networks by the cascading failure mechanism, we used the largest-scale cascades and the cumulative cascade probability to depict the damage. It was found that the cascading failures caused by hubs are usually larger. Furthermore, the result shows that propagations against the networks were correlated with the structures motifs of connected logical doublets. Finally, some genes were selected based on cascading failure mechanism. We believe that these genes may be involved in the occurrence and development of three types of cancer.

Real-time astronaut visual tracking is the most important prerequisite for flying assistant robot to follow and assist the served astronaut in the space station. In this paper, an astronaut visual tracking algorithm which is based on deep learning and probabilistic model is proposed. Fine-tuned with feature extraction layers’ parameters being initialized by ready-made model, an improved SSD (Single Shot Multibox Detector) network was proposed for robust astronaut detection in color image. Associating the detection results with synchronized depth image measured by RGB-D camera, a probabilistic model is presented to ensure accurate and consecutive tracking of the certain served astronaut. The algorithm runs 10 fps at Jetson TX2, and it was extensively validated by several datasets which contain most instances of astronaut activities. The experimental results indicate that our proposed algorithm achieves not only robust tracking of the specified person with diverse postures or dressings but also effective occlusion detection for avoiding mistaken tracking.

In this study, a model predictive control (MPC) method is developed for a servicer spacecraft autonomously approaching a tumbling failed spacecraft at an ultraclose range. Flight safety and collision avoidance are basic requirements during the approach. Two types of a failed spacecraft with complex configurations are considered, and a double-ellipsoid composite envelope strategy is designed to model their keep-out zones. Given the keep-out zone of the servicer, two expanded ellipsoids are subsequently introduced to determine the collision and sufficient conditions for collision avoidance are derived by using the form of concave constraint. The tumbling motion of the target is considered, and a CW-based translational dynamics and derived attitude dynamics of the target are formulated to predict the motion of the docking point and keep-out zone. The MPC is formulated to drive the servicer tracking the docking point with collision avoidance and handle constraints including control input saturation and relative velocity bound. Convexification of the collision avoidance constraint and sequential convex programming are adopted for the implementation of MPC. Scenarios on the servicer with different initial positions approaching the target with different angular velocities are simulated, and the simulation results indicate that the proposed MPC method is effective.

Detailed and innovative analysis of gene regulatory network structures may reveal novel insights to biological mechanisms. Here we study how gene regulatory network inSaccharomyces cerevisiaecan differ under aerobic and anaerobic conditions. To achieve this, we discretized the gene expression profiles and calculated the self-entropy of down- and upregulation of gene expression as well as joint entropy. Based on these quantities the uncertainty coefficient was calculated for each gene triplet, following which, separate gene logic networks were constructed for the aerobic and anaerobic conditions. Four structural parameters such as average degree, average clustering coefficient, average shortest path, and average betweenness were used to compare the structure of the corresponding aerobic and anaerobic logic networks. Five genes were identified to be putative key components of the two energy metabolisms. Furthermore, community analysis using the Newman fast algorithm revealed two significant communities for the aerobic but only one for the anaerobic network. David Gene Functional Classification suggests that, under aerobic conditions, one such community reflects the cell cycle and cell replication, while the other one is linked to the mitochondrial respiratory chain function.

We consider a single-machine scheduling problem with upper bounded actual processing time and upper bounded maintenance time under deteriorating effect. The actual processing time of a job is a position-dependent power function. If the actual processing time of a job exceeds the upper bound, tardiness penalty of the job should be paid. And if the maintenance time exceeds the corresponding upper bound, tardiness penalty of the maintenance should also be paid. The maintenance duration studied in the paper is a position-dependent exponential function. The objective is to find jointly the optimal maintenance frequency and the optimal job sequence to minimize the total cost, which is a linear function of the makespan and the total tardiness. We show that the studied scheduling problem can be transformed as a classic assignment problem to solve. There is also shown that a special case of the scheduling problem can be optimally solved by a lower order algorithm.