Dermatan Sulfate Affects Breast Cancer Cell Function via the Induction of Necroptosis

Dermatan sulfate (DS) is widespread in the extracellular matrix (ECM) of animal tissues. This glycosaminoglycan is characterized by a variable structure, which is reflected in the heterogeneity of its sulfation pattern. The sulfate groups are responsible for the binding properties of DS, which determine an interaction profile of this glycan. However, the detailed role of DS in biological processes such as the neoplasm is still poorly understood. The aim of the study was to assess the effects of the structural variants of DS on breast cancer cells. We found that DS isoforms from normal and fibrotic fascia as well as from intestinal mucosa were able to quickly induce oxidative stress in the cytoplasm and affect the mitochondrial function in luminal breast cancer cells. Moreover, the variants caused the necroptosis of the cells most likely via the first of these mechanisms. This death was responsible for a reduction in the viability and number of breast cancer cells. However, the dynamics and intensity of all of the DS variants-triggered effects were strongly dependent on the cell type and the structure of these molecules. The most pronounced activity was demonstrated by those variants that shared structural features with the DS from the tumor niche.

Sliding-mode variable structure control for complex automatic systems: a survey

<abstract> <p>Automatic systems (ASs) can automatically control the work of controlled objects without unattended participation. They have been extensively used in industry, agriculture, automobiles, robots and other fields in recent years. However, the performance of the controller cannot meet the work requirements under complex environmental conditions. Therefore, improving the control performance is one of the difficult problems that automated systems should solve. Sliding-mode variable structure control has the advantages of fast response, insensitivity to uncertainty and interference and easy implementation; thus, it has been extensively used in the field of complex control systems. This article analyses and explains the research status of motors, microgrids, switched systems, aviation guidance, robots, mechanical systems, automobiles and unmanned aerial vehicles (UAVs) and prospects for the application of sliding-mode variable structure control in complex ASs.</p> </abstract>

Ship RBF neural network sliding mode PID heading control

In view of the inherent non-linearity, complexity, susceptibility to external wind, wave, and current interference of under-driven ships, and the difficulty of adjusting and adjusting control parameters, to improve the performance of ship’s autopilot, a kind of RBF neural network sliding mode variable structure PID controller is designed. Traditional PID control is sensitive to parameter changes, online tuning is difficult, and easy to overshoot. In order to solve this problem, combining the variable structure characteristics of PID, a differential compensation term is added to the integral term to convert the PID control parameters into three parameters with more obvious physical meanings, and then combined with the RBF neural network learning and identification function to realize online tuning and adaptive control of ship control parameters. Using MATLAB software to simulate the container ship “MV KOTA SEGAR” MMG model shows that the designed RBF neural network sliding mode PID controller can effectively eliminate the ship’s lateral deviation caused by external interference such as wind, waves, currents, etc., with high control accuracy,robustness and strong adaptability.

Diversity and distribution patterns of antennal sensilla in Hydropsychidae (Insecta, Trichoptera)

Structure and distribution of antennal sensilla were studied in males of 19 species of the caddisfly family Hydropsychidae by using scanning electron microscopy (SEM). Eleven types of sensilla were found: long trichoid, chaetoid, thick chaetoid, curved trichoid, coronary, basiconic, styloconic and four types of pseudoplacoid sensilla (mushroom-like, auricillic, ribbed, and T-shaped). Thick chaetoid, ribbed pseudoplacoid, and T-shaped pseudoplacoid sensilla were found only in Macronematinae. The great diversity of pseudoplacoid sensilla originated from a mushroom-like type, which also has a variable structure. Basal flagellomeres in the majority of studied species are equipped with ventrally positioned sensory fields of curved trichoid sensilla. In contrast to Arctopsychinae and Hydropsychinae, the increased number of these sensilla in the fields was noted for Diplectroninae and Smicrideinae. Most Macronematinae show a reduction of sensory fields and a strongly decreased average number of curved trichoid sensilla on distal segments. The great differences found in the studied family probably indicate a rapid function-related evolution of the antennal sensory surface structures in the caddisfly family Hydropsychidae.

Adaptive Smooth Variable Structure Filter Strategy for State Estimation of Electric Vehicle Batteries

Battery Management Systems (BMSs) are used to manage the utilization of batteries and their operation in Electric and Hybrid Vehicles. It is imperative for efficient and safe operation of batteries to be able to accurately estimate the State of Charge (SoC), State of Health (SoH) and State of Power (SoP). The SoC and SoH estimation must remain robust and accurate despite aging and in presence of noise, uncertainties and sensor biases. This paper introduces a robust adaptive filter referred to as the Adaptive Smooth Variable Structure Filter with a time-varying Boundary Layer (ASVSF-VBL) for the estimation of the SoC and SoH in electrified vehicles. The internal model of the filter is a third-order equivalent circuit model (ECM) and its state vector is augmented to enable estimation of the internal resistance and current bias. It is shown that system and measurement noise covariance adaptation for the SVSF-VBL approach improves the performance in state estimation of a battery. The estimated internal resistance is then utilized to improve determination of the battery’s SoH. The effectiveness of the proposed method is validated using experimental data from tests on Lithium Polymer automotive batteries. The results indicate that the SoC estimation error can remain within less than 2% over the full operating range of SoC along with an accurate estimation of SoH.

A Switching-Based Interference Control for Booster Separation of Hypersonic Vehicle

Whether launching from the ground or in the air, hypersonic vehicles need the booster to accelerate to a predetermined window, so as to meet the requirements of scramjet engine ignition. Therefore, there is interference suppression between boosters and hypersonic vehicles under the high dynamic pressure, which has become a key technical problem that affects the success of flight tests, especially when the aircraft is statically unstable. A method of variable structure switching-based control is proposed in this paper for rapid suppression on hypersonic vehicle booster separation interference. Switching control systems in real time according to state changes caused by flow field interference, the method can keep the attitude stability of hypersonic vehicle booster separation under the high dynamic pressure of static instability. The aerodynamic calculation model of the hypersonic vehicle booster separation process is established first, which adopts an unsteady solution and clarifies the aerodynamic interference characteristics of the afterbody on the vehicle in booster separation. Then, according to the characteristics of the flow field, the dynamics of the vehicle in and out of the interference area are converted into subsystems with switching characteristics. Using the dimension reduction and variable structure method, the switching control surface of the control system is established. On the basis of the vehicle state changes caused by flow field, the control system on the orbital change surface can be switched in real time to achieve stable attitude in the process of separation interference. Meanwhile, considering the additional interference torque generated by the afterbody to the vehicle in the separation process, a control system for interference suppression of the booster separation is designed. Simulation results verify that the designed control system can rapidly suppress the booster separation interference when the dynamic pressure is about 150 kPa and the vehicle has the static instability of 5%, thereby realizing the stable attitude of the vehicle.

CONTROL OF REMOTELY OPERATED UNDERWATER VEHICLE USING MODEL PREDICTIVE CONTROL

This paper focuses on application of model predictive control on attitude control of remotely operated underwater vehicle. These vehicles are used in scientific, defence and oceanography applications. Remotely Operated Vehicle (ROV) considered in this paper is nonlinear model and complex. MPC is applied on ROV model to track in desired set point trajectories in the presence of uncertainties. Simulation has been carried out in MATLAB environment. Model Predictive Control has given significantly good results compared to PID, Adaptive and Variable structure control.

Soft Array Surface-Changing Compound Eye

The field-of-view (FOV) of compound eyes is an important index for performance evaluation. Most artificial compound eyes are optical, fabricated by imitating insect compound eyes with a fixed FOV that is difficult to adjust over a wide range. The compound eye is of great significance in the field of tracking high-speed moving objects. However, the tracking ability of a compound eye is often limited by its own FOV size and the reaction speed of the rudder unit matched with the compound eye, so that the compound eye cannot better adapt to tracking high-speed moving objects. Inspired by the eyes of many organisms, we propose a soft-array, surface-changing compound eye (SASCE). Taking soft aerodynamic models (SAM) as the carrier and an infrared sensor as the load, the basic model of the variable structure infrared compound eye (VSICE) is established using an array of infrared sensors on the carrier. The VSICE model is driven by air pressure to change the array surface of the infrared sensor. Then, the spatial position of each sensor and its viewing area are changed and, finally, the FOV of the compound eye is changed. Simultaneously, to validate the theory, we measured the air pressure, spatial sensor position, and the FOV of the compound eye. When compared with the current compound eye, the proposed one has a wider adjustable FOV.