Jawaharlal Nehru Technological University, Hyderabad

Hydrogen is the most efficient energy carrier. Hydrogen can be obtained from different sources of raw materials including water. Among many hydrogen production methods, eco-friendly and high purity of hydrogen can be obtained by water electrolysis. However, In terms of sustainability and environmental impact, PEM water electrolysis was considered as most promising techniques for high pure efficient hydrogen production from renewable energy sources and emits only oxygen as byproduct without any carbon emissions. Moreover, the produced hydrogen (H2) and oxygen (O2) directly used for fuel cell and industrial applications. However, overall water splitting resulting in only 4% of global industrial hydrogen being produced by electrolysis of water, mainly due to the economic issues. Nowadays, increased the desire production of green hydrogen has increased the interest on PEM water electrolysis. Thus the considerable research has been completed recently in the development of cost effective electrocatalysts for PEM water electrolysis. In this present review, we discussed about the recent developments in the PEM water electrolysis including high performance low cost HER and OER electrocatalysts and their challenges new and old related to electrocatalysts and PEM cell components also addressed. This review will contribute further research improvements and a road map in order to support in developing the PEM water electrolyser as a commercially feasible hydrogen production purpose. Keywords: Hydrogen production, PEM water electrolysis, Electrocatalysts, Hydrogen evolution reaction (HER), Oxygen evolution reaction (OER)

This paper presents a new method to solve the network reconfiguration problem in the presence of distributed generation (DG) with an objective of minimizing real power loss and improving voltage profile in distribution system. A meta heuristic Harmony Search Algorithm (HSA) is used to simultaneously reconfigure and identify the optimal locations for installation of DG units in a distribution network. Sensitivity analysis is used to identify optimal location s for installation of DG units. Different scenarios of DG placement and reconfiguration of network are considered to study the performance of the proposed method. The constraints of voltage and branch current carrying capacity are included in the evaluation of the objective function. The method has been tested on 33-bus and 69-bus radial distribution systems at three different load levels to demonstrate the performance and effectiveness of the proposed method. The results obtained are encouraging.

Tissue engineering (TE) and regenerative medicine integrate information and technology from various fields to restore/replace tissues and damaged organs for medical treatments. To achieve this, scaffolds act as delivery vectors or as cellular systems for drugs and cells; thereby, cellular material is able to colonize host cells sufficiently to meet up the requirements of regeneration and repair. This process is multi-stage and requires the development of various components to create the desired neo-tissue or organ. In several current TE strategies, biomaterials are essential components. While several polymers are established for their use as biomaterials, careful consideration of the cellular environment and interactions needed is required in selecting a polymer for a given application. Depending on this, scaffold materials can be of natural or synthetic origin, degradable or nondegradable. In this review, an overview of various natural and synthetic polymers and their possible composite scaffolds with their physicochemical properties including biocompatibility, biodegradability, morphology, mechanical strength, pore size, and porosity are discussed. The scaffolds fabrication techniques and a few commercially available biopolymers are also tabulated.

In this paper, a simple and facile surfactant assisted combustion synthesis is reported for the ZnO nanoparticles. The synthesis of ZnO-NPs has been done with the assistance of non-ionic surfactant TWEEN 80. The effect of fuel variations and comparative study of fuel urea and glycine have been studied by using characterization techniques like X-ray diffraction (XRD), transmission electron microscope (TEM) and particle size analyzer. From XRD, it indicates the presence of hexagonal wurtzite structure for ZnO-NPs. Using X-ray broadening, crystallite sizes and lattice strain on the peak broadening of ZnO-NPs were studied by using Williamson-Hall (W-H) analysis and size-strain plot. Strain, stress and energy density parameters were calculated for the XRD peaks of all the samples using (UDM), uniform stress deformation model (USDM), uniform deformation energy density model (UDEDM) and by the size-strain plot method (SSP). The results of mean particle size showed an inter correlation with W-H analysis, SSP, particle analyzer and TEM results.

Electrical distribution network reconfiguration is a complex combinatorial optimization process aimed at finding a radial operating structure that minimizes the system power loss while satisfying operating constraints. In this paper, a harmony search algorithm (HSA) is proposed to solve the network reconfiguration problem to get optimal switching combination in the network which results in minimum loss. The HSA is a recently developed algorithm which is conceptualized using the musical process of searching for a perfect state of harmony. It uses a stochastic random search instead of a gradient search which eliminates the need for derivative information. Simulations are carried out on 33- and 119-bus systems in order to validate the proposed algorithm. The results are compared with other approaches available in the literature. It is observed that the proposed method performed well compared to the other methods in terms of the quality of solution.

The Present work outlines the antibacterial activity of Fe3O4 nanoparticles synthesized through chemical combustion method where ferric nitrate is used as precursor material and urea as fuel with the assistant of Tween 80, a non-ionic surfactant. The obtained Fe3O4 nanoparticles were characterized by X-ray diffraction, differential thermal analysis/thermo gravimetric analysis (DTA/TGA), particle size analyzer, SEM with EDAX and TEM. Various parameters such as dislocation density, micro strain, analysis of weight loss and surface morphological studies were calculated. The particle size was calculated from XRD and it was found to be 33–40 nm. Using well diffusion method antibacterial activity of Fe3O4 nanoparticles was tested against gram-positive and gram-negative Staphylococus aureus, Xanthomonas, Escherichia coli and Proteus vulgaris. Fe3O4 nanoparticles exhibited strong antibacterial activity against bacterial species.

Global warming is considered one of the world's leading challenges in the 21st century as it causes severe concerns such as climate change, extreme weather events, ocean warming, sea-level rise, declining Arctic sea ice, and acidification of oceans.

The coumarin (benzopyran-2-one, or chromen-2-one) ring system, present in many natural products, displays diverse pharmacological properties. It has attracted the attention of chemists and medicinal chemists for decades. Many molecules based on the coumarin ring system have been described utilizing innovative synthetic methods. These synthetic routes have led to interesting analogues of coumarins which possess pharmacological activities like anti-HIV, antimicrobial, antiinflammatory, anticancer, anti-TB, anticonvulsant and MAO inhibitory properties. Details of these studies, correlating structure with biological activity are described in this review. Keywords: Anticancer, anticonvulsant, anti-inflammatory, antimicrobial, antioxidant, coumarin, MAO inhibitory, pharmacological properties.

An attempt has been made in the present investigation to determine the acute toxicity of hexavalent chromium and its toxicological effects on survival, physiological, hematological and biochemical parameters of the widely consumed Indian major carp, Labeo rohita. Short-term acute toxicity tests were performed adopting renewal bioassay technique (USEPA, 1975) over a period of 96 h, using different concentrations of potassium dichromate to the fish and the 96 h LC[50] value was found to be 111.45 mg/l (Cr(+6) as 39.40 mg/l). ANOVA results showed that the normal respiratory activity of the fish was significantly affected and there is a depression in the metabolic rate at the end of 24, 48, 72 and 96 h exposure. The metal also induced significant decrease (p<0.001) in the hematological parameters of the fish like total erythrocyte count, hemoglobin percent and absolute value Mean cell hemoglobin (MCH) both at the end of 24h and 96 h exposure indicating anemia. Appreciable decline in the biochemical profiles such as total glycogen, total lipids and total protein contents of the fish was also observed. However, the decrease in protein content was significant only at the end of 96 h. This study reflects the extent of the toxic effects of hexavalent chromium and the metal induced cumulative deleterious effects at various functional levels in the widely consumed freshwater fish, Labeo rohita.

Machine Learning (ML) is considered as one of the contemporary approaches in predicting, identifying, and making decisions without having human involvement. ML is quickly evolving in the medical industry ranging from diagnosis to visualization of diseases and the study of disease transmission. These algorithms were developed to identify the problems in medical image processing. Numerous studies previously attempted to apply these algorithms on MRI (Magnetic Resonance Image) data to predict AD (Alzheimer's disease) in advance. The present study aims to explore the usage of support vector machine (SVM) in the prediction of dementia and validate its performance through statistical analysis. Data is obtained from the Open Access Series of Imaging Studies (OASIS-2) longitudinal collection of 150 subjects of 373 MRI data. Results provide evidence that better performance values for dementia prediction are achieved by low gamma (1.0E-4) and high regularized (C = 100) values. The proposed approach is shown to achieve accuracy and precision of 68.75% and 64.18%. Keywords: Machine learning, OASIS, Support vector machines, Kernel, Gamma, Regularization (C)

Groundwater quality in Hyderabad has special significance and needs great attention of all concerned since it is the major alternate source of domestic, industrial and drinking water supply. The present study monitors the ground water quality, relates it to the land use / land cover and maps such quality using Remote sensing and GIS techniques for a part of Hyderabad metropolis. Thematic maps for the study are prepared by visual interpretation of SOI toposheets and linearly enhanced fused data of IRS-ID PAN and LISS-III imagery on 1:50,000 scale using AutoCAD and ARC/INFO software. Physico-chemical analysis data of the groundwater samples collected at predetermined locations forms the attribute database for the study, based on which, spatial distribution maps of major water quality parameters are prepared using curve fitting method in Arc View GIS software. Water Quality Index (WQI) was then calculated to find the suitability of water for drinking purpose. The overall view of the water quality index of the present study area revealed that most of the study area with >50 standard rating of water quality index exhibited poor, very poor and unfit water quality except in places like Banjara Hills, Erragadda and Tolichowki. Appropriate methods for improving the water quality in affected areas have been suggested.

Mesenchymal stem cells (MSCs) are defined as undifferentiated cells that are capable of self renewal and differentiation into several cell types such as chondrocyte, adipocyte, osteocyte, myocyte, hepatocyte, and neuron-like cells. MSC can be isolated from bone marrow, umbilical cord blood, adipose tissue, placenta, periosteum, trabecular bone, synovium, skeletal muscle, and deciduous teeth. Immunomodulatory of MSCs is one of the important issues nowadays, because this aspect can be clinically applied for graft-versus-host and autoimmune diseases. In this review, we tried to discuss in detail about cytokines and factors such as members of the transforming growth factor superfamily (transforming growth factor-β), hepatic growth factors (HGF), prostaglandin E2 (PGE2), IL-10, indolamine 2,3-dioxygenase (IDO), nitric oxide (NO), heme oxygenase-1 (HO-1), and human leukocyte antigen-G (HLA-G) that are involved in immunomodulatory of MSCs.

This research explores numerically the impact of the aligned magnetic field on Williamson's nanofluid on a stretching surface with convective boundary conditions. The ordinary differential equations (ODE's) are obtained from the partial differential equations (PDE's) employing the transformation of similarity. Such equations are computed with the respective limits with Runge-Kutta – Fehlberg's fourth-fifth order method along with a shooting procedure. The functions of the many parameter values on the flow field profiles are graphically presented and examined. The current results agree well with previous works. The local skin friction, the local Nusselt number, and the local Sherwood number are shown with graphs and tables for changed values of the flow constraints.

A numerical model is employed for the nanofluid flow and heat transfer from an infinite vertical plate in the existence of a magnetic field, thermal radiation and viscous dissipation. The solution of the basic governing equations was obtained by the finite element procedure. A collection of nanofluids with a fraction of nanoparticle volume comprising nanoparticles of aluminium oxide, copper, and titanium oxide is included less than or equal to 0.04. With the aid of non-dimensional flow parameters, the mathematical results of velocity and temperature distributions are analysed and shown diagrammatically. It is found that velocity and Temperature profiles enhance by enhancing the value of radiation parameter. The current simulations outlined are relevant for the processing of magnetic nanomaterials in the chemical industry and the metallurgy sector.

An efficient energy management system for a small-scale hybrid wind-solar-battery based microgrid is proposed in this paper. The wind and solar energy conversion systems and battery storage system have been developed along with power electronic converters, control algorithms and controllers to test the operation of hybrid microgrid. The power balance is maintained by an energy management system for the variations of renewable energy power generation and also for the load demand variations. This microgrid operates in standalone mode and provides a testing platform for different control algorithms, energy management systems and test conditions. A real-time control is performed by rapid control prototyping to test and validate the control algorithms of microgrid system experimentally. The proposed small-scale renewable energy based microgrid can be used as a test bench for research and testing of algorithms in smart grid applications.

Abstract Tailoring personalized cancer nanomedicines demands detailed understanding of the tumor microenvironment. In recent years, smart upconversion nanoparticles with the ability to exploit the unique characteristics of the tumor microenvironment for precise targeting have been designed. To activate upconversion nanoparticles, various bio‐physicochemical characteristics of the tumor microenvironment, namely, acidic pH, redox reactants, and hypoxia, are exploited. Stimuli‐responsive upconversion nanoparticles also utilize the excessive presence of adenosine triphosphate (ATP), riboflavin, and Zn 2+ in tumors. An overview of the design of stimulus‐responsive upconversion nanoparticles that precisely target and respond to tumors via targeting the tumor microenvironment and intracellular signals is provided. Detailed understanding of the tumor microenvironment and the personalized design of upconversion nanoparticles will result in more effective clinical translation.

Environmentally beneficial composites can be made by replacing synthetic fibers with various types of cellulosic fibers. Fibers from pine wood, coir, sisal, abaca, coir, etc. are all good candidates. The most important factor in finding good fiber reinforcement in the composites is the strength of adhesion between matrix polymer and fiber. Due to the presence of hydroxyl groups and other polar groups in various constituents of abaca, the moisture absorption is high, which leads to poor wettability and weak interfacial bonding between fibers and the more hydrophobic matrices. Therefore, it is necessary to impart a hydrophobic nature to the fibers by suitable chemical treatments in order to develop composites with better mechanical properties. In the present work, the effect of alkali treatment on the moisture absorption tendency of single abaca fiber was investigated. The results shown that the alkali treated fiber absorbs less moisture than the untreated raw fiber.

Geopolitical concerns (unstable supply of gasoline, environmental pollution, and regular price hikes), economic, and employment concerns have been prompting researchers, entrepreneurs, and policy makers to focus on harnessing the potential of lignocellulosic feedstock for fuel ethanol production and its commercialization. The carbohydrate skeleton of plant cell walls needs to be depolymerised into simpler sugars for their application in fermentation reactions as a chief carbon source of suitable ethnologic strains for ethanol production. The role of cellulolytic enzymes in the degradation of structural carbohydrates of the plant cell wall into ready-to-fermentable sugar stream is inevitable. Cellulase synergistically acts upon plant cell wall polysaccharides to release glucose into the liquid media. Cellulase predominantly dominates all the plant cell wall degrading enzymes due to their vast and diverse range of applications. Apart from the major applications of cellulases such as in detergent formulations, textile desizing, and development of monogastric feed for ruminants, their role in biorefinery is truly remarkable. This is a major area where new research tools based upon fermentation based formulations, biochemistry, and system biology to expedite the structure-function relationships of cellulases including cellulosomes and new designer enzymatic cocktails are required. In the last two decades, a considerable amount of research work has been performed on cellulases and their application in biomass saccharification. However, there are still technical and economic impediments to the development of an inexpensive commercial cellulase production process. Advancements in biotechnology such as screening of microorganisms, manipulation of novel cellulase encoding traits, site-specific mutagenesis, and modifications to the fermentation process could enhance the production of cellulases. Commercially, cheaper sources of carbohydrates and modified fermentation conditions could lead to more cost-effective production of cellulases with the goal to reduce the cost of ethanol production from lignocellulosics. Implementation of integrated steps like cellulase production and cellulase mediated saccharification of biomass in conjunction with the fermentation of released sugars in ethanol in a single step so called consolidated bio-processing (CBP) is very important to reduce the cost of bioethanol. This paper aims to explore and review the important findings in cellulase biotechnology and the forward path for new cutting edge opportunities in the success of biorefineries.

With significant advances in holographic display technology, a plethora of interactive applications, such as tele-conferencing and tele-surgery, are well on their way to integrating holographic technologies. However, hologram-based applications will place significant demands on networking infrastructure, which are not supported today. These include support for ultra-low delays, high bandwidth, and the ability to coordinate, synchronize, and dynamically adapt multiple data streams. This article articulates these challenges and points out gaps in existing networks that solutions must address. In addition, it provides an experimental analysis of novel network architectures that address one of these challenges, namely the ability to dynamically set up new flows with very low latency incurred by the first packet.

In this paper, the specific heat capacity and viscosity properties of water-based nanofluids containing alumina nanoparticles of 47 nm average particle diameter at low concentrations are studied. Nanofluids were prepared with deionised water as base fluid at room temperature by adding nanoparticles at low volume concentration in the range of 0.01%–1% to measure viscosity. The effect of temperature on viscosity of the nanofluid was determined based on the experiments conducted in the temperature range of 25°C to 45°C. The results indicate a nonlinear increase of viscosity with particle concentration due to aggregation of particles. The estimated specific heat capacity of the nanofluid decreased with increase of particle concentration due to increase in thermal diffusivity. Generalised regression equations for estimating the viscosity and specific heat capacity of nanofluids for a particular range of particle concentration, particle diameter and temperature are established.