Variable structure based control strategy for treatment of HCV infection

Hepatitis C is such a harmful disease which can lead to serious health problems and it is caused by the Hepatitis C Virus (HCV) which causes liver inflammation and sometimes liver cancer. In this work, the control treatment strategy for HCV infection has been proposed. The advanced nonlinear dynamical mathematical model of HCV that has two control inputs and three state variables such as virions, infected hepatocytes and uninfected hepatocytes are considered for controller design in this research work. Moreover, four nonlinear controllers such as the Fractional Order Terminal Sliding Mode Controller (FOTSMC), Integral Terminal Sliding Mode Controller (ITSMC), Double Integral Sliding Mode Controller (DISMC) and Integral Sliding Mode Controller (ISMC) have been proposed in this work for HCV infection control inside the human body. In order to control the amount of uninfected hepatocytes to its required maximum safe limit, controllers are designed for antiviral therapy in which the amount of virions and infected hepatocytes are tracked to zero. One control input is ribavirin which blocks virions production and the other is pegylated interferon (peg-IFN-a) that acts as reducing infected hepatocytes. By doing so, uninfected hepatocytes increase and achieve the required maximum safe limit. To prove the stability of the whole system, Lyapunov stability analysis is used in this work. Simulation results and comparative analysis are carried out by using MATLAB/Simulink. It can be depicted from the given results that the virions and infected hepatocytes are reduced to their required levels completely using FOTSMC and the Sustained Virologic Response (SVR) rate is also enhanced in it. It reduces the treatment period as compared to previous strategies introduced in the literature and also system behaves very nicely even in the presence of un-modeled disturbances

Variable Structure-Based Control for Dynamic Temperature Setpoint Regulation in Hospital Extreme Healthcare Zones

In critical healthcare units, such as operation theaters and intensive care units, healthcare workers require specific temperature environments at different stages of an operation, which depends upon the condition of the patient and the requirements of the surgical procedures. Therefore, the need for a dynamically controlled temperature environment and the availability of the required heating/cooling electric power is relatively more necessary for the provision of a better healthcare environment as compared to other commercial and residential buildings, where only comfortable room temperature is required. In order to establish a dynamic temperature zone, a setpoint regulator is required that can control the zone temperature with a fast dynamic response, little overshoot, and a low settling time. Thus, two zone temperature regulators have been proposed in this article, including double integral sliding mode control (DISMC) and integral terminal sliding mode control (ITSMC). A realistic scenario of a hospital operation theater is considered for evaluating their responses and performance to desired temperature setpoints. The performance analysis and superiority of the proposed controllers have been established by comparison with an already installed Johnson temperature controller (JTC) for various time spans and specific environmental conditions that require setpoints based on doctors’ and patients’ desires. The proposed controllers showed minimal overshoot and a fast settling response, making them ideal controllers for operation theater (OT) zone temperature control

Modified Flower Pollination Algorithm for Energy Forecasting and Demand Management Coupled with Improved Battery Life for Smart Building Micro-Grid

This paper presents the Modified Flower Pollination Algorithm-based Multi-Layer Perceptron Neural Network (MFPA-MLPNN) as an optimization technique for efficient power flow management in a Smart Building Microgrid (SBMG) integrated with solar and wind generation, and Electric Vehicle Batteries (EVBs) within grid connected structure while concurrently reducing optimization processing time. To achieve both technical and economic superiority, two optimization objectives are addressed. Firstly, a Demand Response (DR) framework is harnessed to accommodate the stochastic behavior and forecasting errors associated with intermittent sources. Secondly, the degradation of EVBs is considered, ensuring an economically viable power flow proposed strategy for both EV owners and microgrid (MG) authorities. Power generation of Variable Renewable Energy Sources (VRES) has been forecasted using MLPNN. Battery degradation and system stability under the action of the proposed topology have been evaluated using a simulation-based environment. Results show a significant decrease in battery degradation and processing time using the proposed MFPA-MLPNN optimization architectur

A Reverse transcription-polymerase chain reaction (RT-PCR) based detection of foot and mouth disease in District Faisalabad, Pakistan during the Year 2016

Foot and mouth disease is an economically devastating disease of livestock that mainly effect cloven-hoofed animals i.e. sheep, goat, cattle, pig, buffalo, deer etc. The aim of this study was to determine the serotypes circulating in the region during 2016. Sampling was done from different outbreaks initially on the basis of clinical signs and later reverse transcriptase-polymerase chain reaction (RT-PCR) was employed for the confirmation of FMDV genome. Out of total 72 samples, 65 were found positive which were then serotyped into type O (n=30), Asia1 (n=19) and A (n=5). Some samples (n=5) were found positive for more than one serotype that were subjected to reverse transcriptase loop-mediated isothermal amplification assay (RT-LAMP) for serotype determination