A prognostic estimation model based on mRNA-sequence data for patients with oligodendroglioma

BackgroundThe diagnosis of oligodendroglioma based on the latest World Health Organization Classification of Tumors of the Central Nervous System (WHO CNS 5) criteria requires the codeletion of chromosome arms 1p and 19q and isocitrate dehydrogenase gene (IDH) mutation (mut). Previously identified prognostic indicators may not be completely suitable for patients with oligodendroglioma based on the new diagnostic criteria. To find potential prognostic indicators for oligodendroglioma, we analyzed the expression of mRNAs of oligodendrogliomas in Chinese Glioma Genome Atlas (CGGA).MethodsWe collected 165 CGGA oligodendroglioma mRNA-sequence datasets and divided them into two cohorts. Patients in the two cohorts were further classified into long-survival and short-survival subgroups. The most predictive mRNAs were filtered out of differentially expressed mRNAs (DE mRNAs) between long-survival and short-survival patients in the training cohort by least absolute shrinkage and selection operator (LASSO), and risk scores of patients were calculated. Univariate and multivariate analyses were performed to screen factors associated with survival and establish the prognostic model. qRT-PCR was used to validate the expression differences of mRNAs.ResultsA total of 88 DE mRNAs were identified between the long-survival and the short-survival groups in the training cohort. Seven RNAs were selected to calculate risk scores. Univariate analysis showed that risk level, age, and primary-or-recurrent status (PRS) type were statistically correlated with survival and were used as factors to establish a prognostic model for patients with oligodendroglioma. The model showed an optimal predictive accuracy with a C-index of 0.912 (95% CI, 0.679–0.981) and harbored a good agreement between the predictions and observations in both training and validation cohorts.ConclusionWe established a prognostic model based on mRNA-sequence data for patients with oligodendroglioma. The predictive ability of this model was validated in a validation cohort, which demonstrated optimal accuracy. The 7 mRNAs included in the model would help predict the prognosis of patients and guide personalized treatment

Analysis of Stability for the Controlled Spacecraft with a Deployable Flexible Appendage

Conference Name:IEEE International Conference on Control and Automation. Conference Address: Christchurch, NEW ZEALAND. Time:DEC 09-11, 2009.In this paper we analyze the stability of the controlled spacecraft with a deployable flexible appendage. The center body of the spacecraft is controlled by PD controller. According to Lyapunov stable theory and yeTaeB unstable theory, we firstly give the new stability criterion about finite time and then deduce the sufficient conditions which will guarantee the closed-loop system stable or will cause the system unstable during deploying the appendage. At last we verify the existence of these sufficient conditions by examples and the results of numerical simulations are coherent to the theoretic results given by the new stability criterion. The research of this paper is instructive for designing the control law and the proper rate of deployment of the appendage to guarantee the system asymptotic stable

Adaptive multivariable golden section control based characteristic model for attitude maneuver control of flexible fuel-filled spacecraft

Conference Name:Proceedings of the 33rd Chinese Control Conference, CCC 2014. Conference Address: Nanjing, China. Time:July 28, 2014 - July 30, 2014.Systems Engineering Society of China; Technical Committee on Control Theory of Chinese Association of AutomationThe present paper deals with dynamics modeling and controller designing for a large flexible spacecraft, such as Tracking and Data Relay Satellite (TDRS) with several flexible appendages and a liquid fuel tank. Hybrid coordinate is used to describe the configuration of the large flexible liquid-filled spacecraft. A controller is designed and that is adaptive multivariable golden section control based characteristic model. The control mission consists of attitude maneuvering the central rigid body and the large antennas to track the pre-selected motion laws, stabilizing the spacecraft in an inertial space and suppressing the elastic vibration of the appendages. A numerical example is given to prove the validity of the control laws. The cooperation of the adaptive multivariable golden section controller and the new derivative controller based rotational inertia is efficient for various complicated spacecrafts with nonlinearities and uncertainties. ? 2014 TCCT, CAA

An Adaptive Control Method for Electro-hydrostatic Actuator Based on Virtual Decomposition Control

This paper presents an adaptive control method for Electro-hydrostatic Actuator (EHA) based on Virtual Decomposition Control (VDC) under higher-order model, nonlinearities and uncertainties. In the fifth-order dynamic model of EHA, its nonlinear factors make the superior control very difficult. This paper decomposes EHA into four subsystems according to energy conversion, designs the control law for each subsystem, and provides an adaptive control based on VDC. The proposed adaptive controller can solve the problems of multiple uncertainties and nonlinearities in the system and guarantee the stability of EHA. The stability of the subsystems and EHA system are rigorously proven. The simulation results show that the proposed method can effectively control the EHA position and improve the EHA control performance compared with the conventional control method.acceptedVersionPeer reviewe

Fixed-Point Control of Airships Based on a Characteristic Model: A Data-Driven Approach

Factors such as changes in the external atmospheric environment, volatility in the external radiation, convective heat transfer, and radiation between the internal surfaces of the airship skin will cause a series of changes in the motion model of an airship. The adaptive control method of the characteristic model is proposed to extract the relationship between input and output in the original system, without relying on an accurate dynamic model, and solves the problem of inaccurate modeling. This paper analyzes the variables needed for two-dimensional path tracking and combines the guidance theory and the method of wind field state conversion to determine specific control targets. Through the research results, under the interference of wind, the PD control method and the reinforcement learning-based method are compared with a characteristic model control method. The response speed of the characteristic model control method surpasses the PD control method, and it reaches a steady state earlier than the PD control method does. The overshoot of the characteristic model control method is smaller than that of the PD control method. Using the control method of the characteristic model, the process of an airship flying to a target point will be more stable under the influence of an external environment. The modeling of the characteristic model adaptive control method does not rely on a precise model of the system, and it automatically adjusts when the parameters change to maintain a consistent performance in the system, thus reflecting the robustness and adaptability of the characteristic model adaptive control method in contrast with reinforcement learning

Design and Evaluation of A Novel Passive Shoulder Exoskeleton Based on VSM Torque Generator

This paper presents the design and evaluation of a portable passive shoulder exoskeleton based on the variable stiffness mechanism (VSM). The exoskeleton aims to reduce physical effort during repetitive manual handling tasks in industrial settings. The design comprises a lightweightstructure and torque generators. With adoption of VSM, a compact and configurable torque generator is designed to provide torque assisting arm carrying and lifting. Experimental results show that the exoskeleton effectively reduces physical effort while remaining comfortable and easy to use