Impact of adverse drug reaction on quality of life in drug resistant tuberculosis

Background: India has largest population of drug resistant tuberculosis, the treatment of which is long and full of adverse drug reactions. Despite the ongoing research in clinical and pharmacological aspects, quality of life in drug-resistant tuberculosis remains less explored. This study aims to study the quality of life in drug-resistant tuberculosis patients before and after treatment of the adverse drug reactions. Methods: This hospital based cross-sectional study done in the at tertiary care center in Surat, from January 2019 to February 2020, enrolling patients above 18 years, with multi-drug/ extensively drug resistant tuberculosis, who suffered > 1 adverse drug reaction after commencing treatment. SF-36 was administered at start of treatment and after treatment of first adverse drug reaction, and scores compared. Paired Student T Test was used for comparison of pre - post scores. p -value < 0.05 is considered statistically significant. Results: Among the 120 patients studied, majority (87.5%) were had pulmonary tuberculosis. 92.5% and 7.2% were multi-drug resistant and extensively drug resistant respectively. A significant improvement in QOL scores was seen in all 3 domains post treatment of adverse drug reaction- physical domain: After vs. Before: 55.2±6.8 vs. 25.2±4.2; (p-value < 0.0001), mental domain: After vs. Before: 66.8±6.7 vs. 39.4±2.1; (p-value < 0.0001) and social domain After vs. Before: 65.4±5.5 vs. 39.7±2.0; p-value < 0.0001). Conclusions: Drug-resistant tuberculosis along with its associated adverse drug reactions greatly impacts the quality of life in all domains. However, prevention and effective treatment of such adverse effects, especially in systematic protocolised manner can do wonders in improving the life of these patients

Assessment of Seasonal and Site-Speci�c Variations in Soil Physical,Chemical and Biological Properties Around Opencast Coal Mines

Coal mining adversely affects soil quality around opencast mines. Therefore, a study was conducted in 2010 and 2011 to assess seasonal and site-specific variations in physical, chemical, and biological properties of soil collected at different distances from mining areas in the Jharia coalfield, India. Throughout the year, the soil in sites near coal mines had a significantly higher bulk density, temperature, electrical conductivity, and sulfate and heavy metal contents and a significantly lower water-holding capacity, porosity, moisture content, pH, and total nitrogen and available phosphorus contents, compared with the soil collected far from the mines. However, biological properties were site-specific and seasonal. Soil microbial biomass carbon (MBC) and nitrogen (MBN), MBC/MBN,and soil respiration were the highest during the rainy season and the lowest in summer, with the minimum values in the soil near coal mines. A soil quality index revealed a significant effect of heavy metal content on soil biological properties in the coal mining areas

CDBMGCIG: Design of a Cross-Domain Bioinspired Model for identification of Gait Components via Iterated GANs

This Gait identification assists in recognition of human body components from temporal image sequences. Such components consist of connected-body entities including head, upper body, lower body regions. Existing Gait recognition models use deep learning methods including variants of Convolutional Neural Networks (CNNs), Q-Learning, etc. But these methods are either highly complex, or do not perform well under complex background conditions. Moreover, most of these models are validated on a specific environmental condition, and cannot be scaled for general-purpose deployments. To overcome these issues, this text proposes design of a novel cross-domain bioinspired model for identification of gait components via Iterated Generative Adversarial Networks (IGANs). The proposed model initially extracts multidomain pixel-level feature sets from different images. These include frequency components via Fourier analysis, entropy components via Cosine analysis, spatial components via Gabor analysis, and window-based components via Wavelet &Convolutional analysis. These feature sets are processed via a Grey Wolf Optimization (GWO) Model, which assists in identification of high-density & highly variant features for different gait components. These features are classified via an iterated GAN, which comprises of Generator & Discriminator ssModels that assist in evaluating connected body components. These operations generate component-level scores that assist in identification of gait from complex background images. Due to which, the proposed model was observed to achieve 9.5% higher accuracy, 3.4% higher precision, and 2.9% higher recall than existing gait identification methods. The model also uses iterative learning, due to which its accuracy is incrementally improved w.r.t. number of evaluated image sets

Parking Management System: A Review

In today?s transport related concerns, vehicle parking has become a major issue in urban areas. Lack of parking facilities and increased amount of vehicles, due to this, drivers who are searching for parking space keep roaming around the city in peak hours. This causes traffic, waste of time and money. To solve these problems, a Smart Parking Management System can be designed. Earlier many efforts were done on it, to reduce these problems, such as by presenting drivers with real-time description about vacancy of parking slots through the mobile application. To sense car and analyse the count of vacant slots, Ultrasonic sensors and Raspberry pi were castoff at the entrance of parking areas. Also there was an effort to activate an idea which uses the video surveillance camera for tracking those vacant locations, also Matrix Laboratory(MATLAB) to practice the computer vision techniques like background deletion and addition for the update of vacancy and occupancy of spots. Sensor circuits were also designed, which includes Radio Frequency Identification(RFID) tag, a mode of digital payment and a different theft management feature. A smart parking system was also designed which was grounded on the amalgamation of the technologies of Ultra High Frequency(UHF), RFID and Wireless Sensor Network, for the same purpose desired. A parking system was also developed for motorcycles as those are the majority mode of transportation in Taiwan, which includes management system that was based on the wide concept of RFID system, Visual Basic (VB) language and My Structured Query Language(MySQL) system. Likewise, a model came up with the concept of Internet of Things(IoT) and theft management facility, a sensor circuit and RFID tag. It could be accessed and monitored remotely through the application

Product Development from Apple, Grapes and Berries Food Waste: Market Research, Industry Analysis and Opportunity Assessment

This study focuses on the apples, berries, and grapes wastage produced by the population of North America and Europe. The research is aims to conduct in-depth comparison between these two regions based on volume and monetary value of fruit waste produced. The research was conducted by an inquiry based primary research with industry experts product development scientist and good waste management companies, and secondary research was conducted by collecting information from company’s websites, annual reports, white papers, and financial reports. This research open the reusability opportunity of fruit waste, optimize the food processing and manufacturing industry. The waste from apples, berries, and grapes are high in moisture and biologically active components (BACs) which make them ideal raw materials for the functional food product industry. The market research conducted in the study highlights the potential in the waste produced by apples, berries, and grapes during food processing and manufacturing through ingredient analysis and comparing it to the functional food ingredient requirements. The results of the market research and industry analysis will assist industries and researchers in finding and optimizing processes to reduce waste and maximize the extraction of fruits’ nutrients content. KEYWORDS: Food waste, Recycle, biologically active compounds, apple pomace, grape pomace, market valu

Digital image watermarking based on FPGA and spintronic logic and study of some aspects of spintronic logic based circuits.

The growth of high speed computer networks and that of Internet, in particular has explored means of new business , scientific , entertainment and social opportunities .Digital media offer several advantages over analog media like high quality ,easy editing ,high fidelity copying . There are enormous chances of duplicating and distribution of digital information which has led to the need for effective copyright protection tools . DIGITAL WATERMARKING is a kind of protection tool in which a data is hidden in an image ,audio file or video file .Watermarking is either “visible” or ”invisible” . Albeit visible or invisible are visual terms watermarking is not limited to images , it can also be used to protect other types of multimedia object . This project work is on Spatial Domain Image Watermarking using FPGA and Spintronic logic and applications of single spin logic where the spin of electron is used in addition to its charge .For the application of spintronics MAGNETIC TUNNEL JUNCTIONS (MTJ) are used as a spintronic device and different logic and ALU operations are performed and are compared with the conventional electronic devices based operation . The spintronic devices have lots of advantages over the conventional devices like they are non-volatile ,they consume less power ,timing and area