Design of an intelligent system for diabetes prediction by integrating rough set theory and genetic algorithm

Diabetes causes a lot of damage to the internal organs and body parts. To find out the primary symptoms or features to detect and prevent the disease from its severity, an intelligent healthcare system is needed to analyse the disease data to save the patients with proper medication beforehand. The modern healthcare system requires proper IT solutions to process the medical data in disease management for diagnosis and prevention. Data analytics in the healthcare field demands both medical expertise and IT expertise. The feature selection process selects the important features from the feature pool and is generally applied as a pre-processing step prior to extracting the interesting classification rules from the data. In the paper, a rough set theory-based genetic algorithm (GA) method is proposed to select optimal feature set (called reduct)/symptoms from the diabetes dataset to predict the disease efficiently. Benchmark disease datasets are collected from the UCI repository. The experimental result shows that the selected features are important to predict the diabetes by providing good classification accuracy on existing benchmark classifiers, which proves the efficiency of the method

A prospective study on drug utilization pattern of anti-diabetic drugs in a tertiary care teaching hospital of eastern Uttar Pradesh, India

Background: Diabetes mellitus is a metabolic disorder with common denominator of hyperglycemia, arising from a variety of pathogenic mechanisms. The aim of the study was to evaluate the drug utilization pattern of anti-diabetic drugs in diabetic patients and observe adverse drug events (ADEs) associated with anti-diabetic therapy in a prospective way.Methods: A prospective study was carried out in diabetic patients visiting the Departments of General Medicine in a tertiary care teaching hospital. Demographic data, drug utilization pattern and ADEs due to Anti-diabetic drugs were summarized.Results: In the present study, 153 (54%) of the 282 diabetic patients were males and 129 (46%) were females. Majority of patients were in the age group of 51-60 years (31.20%) and most of the patients (31.56%) had a diabetic history of 11-15 years. Metformin was the most commonly prescribed drug (64.89%). Majority of the patients (36.87%) were on multidrug therapy. Co-morbid condition was found in 232 patients (82.26%) where hypertension (22.69%) being the most common co-morbid condition. 32 ADRs were observed with Nausea being the most common ADR reported.Conclusions: The present study helps to find out current prescribing pattern of oral diabetic medications with different co-morbidities with respect to diagnosis, cost of treatment and it also highlight the need for comprehensive management of diabetic patients, including life style changes, dietary control, hypoglycemic agents, cardiovascular prevention, treatment of complications and co-morbidity. Therefore, through the existing prescribing patterns, attempts can be made to improve the quality and efficiency of drug therapy

Self-heating and trapping effect in AlGaN/GaN high electron mobility transistors on CVD-diamond

GaN-based high-electron-mobility Transistors (HEMTs) are widely used for high frequency, high voltage and high-power applications. However, there are still many major challenges facing these devices such as thermal management, size reduction and long-term reliable operation, especially when they are operating at very high voltage (e.g., VD≥48 V). In such an operating condition, the device suffers substantial self-heating and encounters enhanced phonon scattering, which degrades device current due to the decrease of 2-DEG mobility and electron velocity as a result of the increased junction temperature. These problems are predominant particularly when GaN HEMTs are fabricated on conventional low thermal conductive substrates (e.g., Si (KSi=130 W/m-K), Sapphire (KSa=46 W/m-K) and SiC (KSiC= 450 W/m-K)). The usage of high thermal conductivity substrates such as diamond (1000-2000 W/m-K) is now emerging as a viable technique to extract the heat under high-power operations for GaN-based high-electron-mobility transistors (HEMTs). Typically, for GaN-on-Diamond process development, both the host Si or SiC substrate and the growth-defect-rich stress mitigation transition layers are first removed. The remaining HEMT layers are then bonded onto CVD-diamond, which then acts as the new substrate. Thus, the HEMTs fabricated on transferred GaN-on-Diamond will have different behaviour of self-heating and trapping than that of conventional HEMTs fabricated on GaN-on-Si. In this thesis, the main objectives are to investigate the self-heating effect on DC and RF performance, and the trapping behaviour in GaN HEMTs-on-CVD Diamond. The major contributions of this thesis are summarized below: (1) The quantitative investigation of the self-heating effect on DC and RF performances was carried out for AlGaN/GaN HEMTs on CVD-Diamond (GaN/Dia) and Si (GaN/Si) substrates. The GaN/Dia HEMTs were found to exhibit ~5.7-times lower rate of ID reduction than GaN/Si HEMTs. This behaviour was also confirmed by 2D device simulation. The fT reduction rate was ~6.75-times lower in the case of GaN/Dia than GaN/Si HEMTs whereas no significant reduction of fmax was observed in GaN/Dia HEMTs. Small signal measurements and equivalent circuit parameter extraction were done to analyze the variation in the performance of the devices. The comparatively lower reduction rate of µeff and veff in GaN/Dia HEMTs made its performance less degraded (~15%) as compared to (~50%) GaN/Si HEMTs. These results show that GaN/Dia HEMTs can be operated even at higher VD as well as at higher PD which are paramount features for developing compact high power SSPAs for CW application. (2) The hetero-interface trapping characteristics in AlGaN/GaN HEMT on CVD-diamond were investigated at different temperatures (25 °C to 200 °C) using the conductance method. The fast traps (0.16 to 10.01 µs) were identified as the dominating traps in our HEMT structure. The density of fast traps (DTf) increases with temperature from 6.7×1010 cm-2 eV-1 at 25 °C to 1.4×1012 cm-2eV-1 at 200 °C. For 25 °C to 200 °C, the interface trap state energy (ET) was obtained to be between 0.27 and 0.51 eV below the conduction band. The observation of increased DT with temperature could be due to the excitation of additional traps deeper in the bandgap. A lower value of DTfmin for GaN-on-CVD Diamond compared to GaN on Silicon devices is attributed to the removal of the defect-rich GaN transition layer during the substrate transfer process. Finally, the temperature-dependent pulsed IDS-VDS measurements revealed good agreement with the behaviour of DT with temperature obtained using the conductance method. Further to improve the device performance, GaN-MISHEMTs-on-CVD diamond was fabricated and analyzed the gm linearity, gate leakage, and interface trap behavior. (3) For the first time, the investigation of interface traps in AlGaN/GaN metal-insulator-semiconductor (MIS) HEMTs on CVD-diamond was reported in this work. The critical issue in MIS-HEMTs is the dielectric interface trap behaviour. The detailed investigation of dielectric interface and hetero-interface is carried out in AlGaN/GaN MISHEMTs on CVD-diamond and compared with the conventional Schottky AlGaN/GaN HEMTs on CVD-diamond. The finding of slow and fast type of traps in MISHEMTs on the contrary to only fast traps in conventional HEMTs indicated the source of traps. Such a study of interface trap behaviour in the device will help to identify and improve the reliability of AlGaN/GaN HEMTs and MISHEMTs-on-CVD diamond.Doctor of Philosoph

Terahertz planar antennas for next generation communication

This book describes various methods to enhance the directivity of  planar antennas, enabling the next generation of high frequency, wireless communication.  The authors discuss various applications to the terahertz regime of the electromagnetic spectrum, with an emphasis on gain enhancement mechanisms.  The numerical models of these antennas are presented and the analytical results are supported, using commercial simulators. The multilayer substrate microstrip transmission line at terahertz frequency is also explored and a method to obtain the various parameters of this interconnect at high frequency is described.  This book will be a valuable resource for anyone needing to explore the terahertz band gap for future wireless communication, in an effort to solve the bandwidth (spectrum scarcity) problem. • Enables development of terahertz communication systems in a license-free band of the electromagnetic spectrum; • Describes methods to design a multi-layered substrate transmission line to reduce various losses in the terahertz band; • Includes methods to enhance the directivity of planar antennas using electromagnetic bandgap material, double layered substrate material and frequency selective surface (FSS) in the terahertz band

Ethanolic Leaf Extract of Gymnema sylvestre Ameliorates Hyperglycemia and Pancreatic Oxidative Stress in Alloxan induced Diabetic Rats

Diabetes mellitus (DM) is a serious metabolic disorder with altered carbohydrate, fat, and protein metabolism. In the last four decades, India has emerged as an epicenter of the global diabetes mellitus pandemic. Rapid changes in the developmental scenario, demographic changes, and living style in the Indian subcontinent have led to the explosive increase in diabetes. Present research probes with ethanolic extract of Gymnema sylvestre (500 mg/kg.b.w) for treatment of hyperglycemia and related oxidative stress caused by Alloxan (100 mg/kg.b.wt), as a diabetogenic agent. 25 rats were included in the research divided into 5 groups, each containing 5 rats. Group 1 (normal rats), Group II (Diabetic rats (DM), Group III (DM+ treated for 10 days), Group IV (DM+20 days treated), Group V (DM+30 days treated). Blood samples and pancreatic tissues were collected at each interval of time. The blood sample was used for biochemical parameter and tissues were used for the anti-oxidant assay. Gymnema sylvestre extract (GSE) showed glucose-lowering property meanwhile, insulin secretion also increased as compared to Diabetic rats. Other tests like amylase, lipase, ALT, and AST also showed significant recovery after the extract administration. Oxidative stress was found in the Diabetic group, but after extract treatment concentration of superoxide dismutase, Glutathione-S-transferase, catalase, Glutathione peroxidase, Glutathione, and Total thiol was regained. Imbalance in serum electrolyte recovered and dysregulated hematological parameters due to stress and hyperglycemia showed convincing results. The finding suggests Gymnema sylvestre could be used as a hypoglycemic as well as an anti-oxidant agent in diabetes