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S.C.A.R.R or ‘Station Controlled Advance Reconnaissance Rover’ presents a modern approach for surveillance at desired areas, remote border locations, buffer zones, or strategic military deployment areas using a multifunctional robot based on the Arduino development board. The purpose of designing and constructing a surveillance robot is simple; it is to adapt to the advancements in technology in the field of modern warfare as well as to have a pragmatic and reliable solution to ever-increasing surveillance demands due to hostile activities. This robotic vehicle can potentially substitute human deployment in concerned areas to provide surveillance and perform desired tasks. The robotic vehicle works as a manually controlled vehicle through Dual Tone Multi-Frequency (DTMF) technology and is equipped with a Radio AV Night Vision camera which can work both day and night to provide real-time video feed. This robot can be used to detect the presence of the enemy in both friendly territory and buffer zones and capture through the camera to give live streaming to authorized personnel. Surveillance is major and active field role while working in the border area and for the same, there is a need for a robot for surveillance purposes. A smart surveillance robot for military and counter-threat applications is presented in this paper. A well-rounded approach to testing, of all the physical and technical factors, was considered and taken into action in the form of improving the rover.

This paper introduces a comprehensive and systematic Design of Experiments based methodology deployed in conjunction with a multi-physics engine air-path and combustion co-simulation, leading to the development of a global transient simulation capability for engine out NOx emissions. The proposed multi-physics engine simulation framework couples a real-time one-dimensional air flow model with a Probability Density Function based Stochastic Reactor Model that accounts for detailed in-cylinder combustion chemistry to predict combustion emissions. The integration challenge stemming from the different computation complexities and time scales required to ensure adequate fidelity levels across multi-physics simulations was addressed through a comprehensive Design of Experiments methodology to develop a reduction of the slower Stochastic Reactor Model simulation to enable a transient simulation focussed on NOx emissions. The Design of Experiments methodology, based on Optimal Latin Hypercube design experiments, was deployed on the multi-physics engine co-simulation platform and systematically validated against both steady state and transient light-duty Diesel engine test data. The surrogate selection process included the evaluation of a range of metamodels, with Kriging metamodels selected based on both the statistical performance criteria and consideration of physical phenomena trends. The transient validation was carried out on a simulated New European Drive Cycle against the experimental data available, showing good capability to capture transient NOx emission behaviour in terms of trends and values. The significance of the results is that it proves the transient and drive cycle capability of the multi-physics simulation platform, suggesting a promising potential applicability for early powertrain development work focussed on drive cycle emissions.

Coffee is known to be one of the popular beverages today on the globe. Due to its easy availability and preparation, it is consumed by the population of almost all countries. This wonder crop was discovered in the 6th century in Ethiopia. Since then, people have also used various brewing methods to extract hundreds of the bioactive compounds present in these aromatic seeds. No doubt, excessive consumption of the same can be harmful too. As a functional food, coffee is known to have multiple health benefits. Coffee beans contain vitamins, minerals, caffeine, chlorogenic acid, and various other biologically active ingredients. This review briefly describes the major biologically active compounds present in these seeds – caffeine, trigonelline, diterpenes, and chlorogenic acid (CGA). It also aims to describe various bioactive activities such as antioxidant, antiproliferative, antibacterial, antiviral, etc., against variable hallmarks. Thus, explaining different pharmacological effects for the welfare of the human population.

The present study revealed the chromium toxicity and its health measures in L. rohita from the Yamuna river at Mathura- Agra region. Samples were taken in triplicate from both sites i.e. Vrindavan (Bihar ghat) and Agra (Renuka Ghat). The study was carried out on Four different organs (i.e. gills, muscles, liver, and kidney) of the fish sample. The sampling was done from Oct 2018 to January 2020. Chromium concentration in different organs of the fish was analyzed by Atomic absorption spectrophotometer(AAS). The average Cr concentration in gills was highest (9.64 mg/l) at the Mathura site followed byAgra sites (7.78 mg/l) for the month of April 2019. The concentration of Cr was highest in samples taken in the month of April 2019 and it was lowest in October 2018. The significantly high Cr concentration values were observed in the Mathura region than the Agra region for both seasons. In all samples, Cr concentration was above the standards stated by WHO except in the Kidney. In the present study, the bioaccumulation factor showed the chromium concentration in the tissues followed the order of gill > liver > muscle > kidney. HPI, MQI, and Pearson’s correlation coefficient analysis were also done in which HPI was observed very high and there was a positive correlation between all the samples. Keywords: Chromium, BCF, HPI, MQI, AAS, Fish Organs

The present study aims to determine the impact of COVID-19 pandemic confinement on air quality among populous sites of four major metropolitan cities in India (Delhi, Mumbai, Kolkata, and Chennai) from January 1, 2020 to May 31, 2020 by analyzing particulate matter (PM2.5 and PM10), nitrogen dioxide (NO2), ammonia (NH3), sulfur dioxide (SO2), carbon monoxide (CO), and ozone levels. The most prominent pollutant concerning air quality index (AQI) was determined by Pearson's correlation analysis and unpaired Welch's two-sample t test was carried out to measure the statistically significant reduction in average AQI for all the four sites. AQI significantly plummeted by 44%, 59%, 59%, and 6% in ITO-Delhi, Worli-Mumbai, Jadavpur-Kolkata, and Manali Village-Chennai respectively. The findings conclude a significant improvement in air quality with respect to reduction of 49-73%, 17-63%, 30-74%, and 15-58% in the mean concentration of PM2.5, PM10, NH3, and SO2 respectively during the confinement for the studied locations. The p values for all of the four studied locations were found significantly less than the 5% level of significance for Welch's t test analysis. In addition, reduced AQI values were highly correlated with prominent pollutants (PM2.5 and PM10) during Pearson's correlation analysis. These positive results due to pandemic imprisonment might aid to alter the current policies and strategies of pollution control for a safe and sustainable environment. Graphical abstract.

The effect of adding a nano inclusion (Alumina) to polymer matrix (polypropylene) has been analyzed after making a numerical model. On addition, interphase formation in between the inclusion and the polymer matrix occurs. The properties vary in this layered interphase. A solid model of the Representative Volume Element (RVE) of polymer nanocomposite was prepared and calculations were done based on types of variations and these properties were entered into the solid model and mesh model was prepared. On imposing various boundary conditions and taking displacement under small strain case, solutions were done. On comparing these obtained results with the reference values, huge improvement in the mechanical properties like Young Modulus and Poisson ratio was observed.

This work is based on the effect of various alloying elements with varying cooling rate on the properties of steel. Micro alloying specifically signifies the addition of a considerably low amount of the alloying element. Various micro alloying elements like Vanadium, Niobium, Titanium etc. are having different sets of influences on the behavior of steel. It has been significantly studied prior to this work. Different set of cooling rates are having different influences on the microstructure and properties of micro alloy steel. Various observed microstructure and their studies are shown in this work. Also during alloying, a consideration is to be taken to maintain a balance between toughness and hardness from application viewpoint.

Microalloyed vanadium steels are high strength low alloy steel. Although by precise addition of nitrogen in the alloy extract the vanadium from the solid solution and can form vanadium based carbonitrides. In current work prechosen composition of Vanadium-Nitrogen based micro alloy steel was austenitized at 1000 °C. A set of experimental steels are subjected to hot compression using Thermo-Mechanical Simulator (Gleeble 3800®) at 800 °C under the control environment and then cooled to room temperature within the simulator, at a cooling rate of 80 °C/s. Microstructural characterization was done using optical and Scanning microscope. Mechanical testing are done using Instron 1186 testing machine. The characterization study reveals the acicular type of transformation product. That indicates the formation of precipitate of vanadium carbonitrides (V(C,N)). The tensile test result of austenitized sample shows increased ultimate tensile strength due to strain induced precipitate.

Prediction of engine-out emissions with high fidelity from in-cylinder combustion simulations is still a significant challenge early in the engine development process. This article contributes to this fast evolving body of knowledge by focusing on the evaluation of NO x emission prediction capability of a probability density function–based stochastic reactor engine models for a Diesel engine. The research implements a systematic approach to the study of the stochastic reactor engine model performance, underpinned by a detailed space-filling design of experiments (DoE)-based sensitivity analysis of both external and internal parameters, evaluating their effects on the accuracy in matching physical measurements of both in-cylinder conditions and NO x output. The approach proposed in this article introduces an automatic stochastic reactor engine model calibration methodology across the engine operating envelope, based on a multi-objective optimization approach. This aims to exploit opportunities for internal stochastic reactor engine model parameters tuning to achieve good overall modelling performance as a trade-off between physical in-cylinder measurements accuracy and the output NO x emission predictions error. The results from the case study provide a valuable insight into the effectiveness of the stochastic reactor engine model, showing good capability for NO x emissions prediction and trends, while pointing out the critical sensitivity to the external input parameters and modelling conditions.

Difficulty in welding of Aluminium alloy through conventional technique and requirement of light weight welded structure for the aerospace, marine and industry application led to the development of novel welding technique i.e., Friction Stir welding. Friction stir enabled additive manufacturing proved to be a solution to repair aluminium alloys used for aerospace and defence industries. In the present work, FEM model is established for the Friction stir welding analysis and results are confirmed with the experimental study. Arbitrary Eulerian Lagrangian(ALE) approach is used for the computational system to avoid large distortions in mesh around the tool. Three-dimensional nonlinear thermal numerical simulations are performed using Altair Hyper Weld Friction Stir Welding (FSW) tool for the joint of AA6061 (aluminium alloy) material plates. Thermal solutions are considered for the Welding process simulation. Furthermore, influence of various process parameters on welding of AA6061 aluminium alloys is investigated to enhance the material properties. Translation, and rotational spindle speed are the process variables considered for the study. Analysis conclude that temperature in the FSW process is symmetrically distributed along the welding line. Increase in Rotational Speed increases the Peak temperature whereas, increase in Translation speed results slight decrease in Peak Temperature. The numerical simulations obtained and validated are proposed to illustrate the accuracy of the presented methodology and its potential to study real Friction Stir welding processes. Altair’s Hyper Weld Friction Stir Welding module proved to be potential tools for the analysis of friction stir welded joints.

Increased uses of resources with less use of manpower are linked with growth in manufacturing of different commodities and also with industrial farming. The model of linear economy, which is based on the manufacturing of goods and services, tells that energy with different commodities production always leads to generation of waste. However, circular economy approach has been recently replaced the linear economy approach, because of its sustainable development approach. It promotes the sustainable use of resources rather than wasting the resources. This approach is based on the ‘close to nature’ model, in which the main motive is to minimize the waste, and also this waste should be reused and recycled. On this circular economy approach, an idea of circular bioregions has been derived in the Lodz declaration held in Poland. This declaration gives an idea of bioregions, a sustainable renewable energy system including biorefineries and distributed prosumer energy for reducing carbon dioxide (CO2) emissions (Lodz Declaration of Bioregions 2016). Numerous problems associated with underdeveloped nations and more importantly in industrially advanced nations are declining water quality, overproduction of waste or overuse of artificial fertilizers in the agricultural practices, so that CB concept and sustainable economic development become most significant in these places (Jezierska-Thole et al. 2016). The global atmospheric CO2 concentration is exceeding due to growing overexploitation of natural resources in terms of burning of non-renewable fuel sources, industrial development and temporal changes in land use and land cover (LULC) (Raupauch et al. 2007; Giri et al. 2018; Giri and Pant 2019a). The negative effects of human induced variation in climate will be changed in the seasonal weather pattern and increased in sea water level (Solomon et al. 2009). So the above-mentioned concept of circular bioregions is closely associated with production of Biochar and its various applications with the aim to mitigate the impact of climate change by reducing the CO2− emissions. The complete decomposition of biomass brought about by high temperatures in the oxygen absence (pyrolysis) for producing carbon-rich concrete material is called Biochar (Antal and Gronli 2003). Biomasses used in this process are organic wastes, agricultural wastes, livestock dung, etc (Lehman et al. 2003). The improvement in soil quality, enhancement in agricultural sustainability concomitant and also reducing GHG emissions can be done through prompting Biochar application in farming practices. Biochar applications become popular recently because of its potential of carbon sequestration, betterment of physical condition of soil, reducing soil compaction, increasing nutrient uptake from soil and help in reducing NO2 emissions (Lehmann et al. 2005; Lehmann 2007). The broad difference in ambient production of carbon and carbon consumption of other compartments’ is attributed to the increasing concentration of atmospheric CO2 (9.5 Pg carbon per annum) (Peters et al. 2013; Giri and Pant 2019b). Therefore, it is important to create a substitute for the permanent accumulation of carbon which can be preserved for a longer period in the atmosphere. In order to draw out carbon present in the atmosphere and manufacturing of eco-friendly materials, biochar industrial manufacturing recently became a major part of the manufacturing plan for clean bio-energy. In the pyrolysis process of biomass, 50–80% of biomass is transformed into fuel compounds and/or fumes which can be used for bio-energy manufacturing. The biochar is the solid by-product converted from remaining 20–50% of the biomass that retains some remaining unprocessed material properties, and it has necessarily the composition of coal-type substances and polycondensed aromatic crystallites with scattered void space and ash (Dutta 2014).

Conventional methods used to remediate toxic substances from the environment have failed drastically, and thereby, advancement in newer remediation techniques can be one of the ways to improve the quality of bioremediation. The increased environmental pollution led to the exploration of microorganisms and construction of genetically engineered microbes (GEMs) for pollution abatement through bioremediation. The present review deals with the successful bioremediation techniques and approaches practised using genetically modified or engineered microbes. In the present scenario, physical and chemical strategies have been practised for the remediation of domestic and industrial wastes but these techniques are expensive and toxic to the environment. Involving engineered microbes can provide a much safer and cost effective strategy in comparison with the other techniques. With the aid of biotechnology and genetic engineering, GEMs are designed by transforming microbes with a more potent protein to overexpress the desired character. GEMs such as bacteria, fungi and algae have been used to degrade oil spills, camphor, hexane, naphthalene, toluene, octane, xylene, halobenzoates, trichloroethylene etc. These engineered microbes are more potent than the natural strains and have higher degradative capacities with quick adaptation for various pollutants as substrates or cometabolize. The road ahead for the implementation of genetic engineering to produce such organisms for the welfare of the environment and finally, public health is indeed long and worthwhile.

Nanotechnology has been proclaimed as an industrial revolution. Early spurt in agrarian development rate as an after effect of the ‘First Green Revolution’ has resulted sprung the rate in agricultural growth. However, it is now experiencing a slowdown. Demands have been rising for enhancing agricultural productivity through several measures and nanotechnology is one of them. Application of nanotechnology in agriculture has been a key interest of public and researchers especially over the last decades. Potential of nanotechnology in bringing changes in agricultural industry is promising. Invention of nanotech-based tools and equipment has the aim of increasing agricultural efficiency as well as to overcome challenges faced. Nanomaterial application may be the key element to nutrient optimizing management that will reduce nutrient loss in fertilization, as well as reduction in plant protection products application. The present chapter discusses the overview of possible nanotechnology field applications in food and agricultural industries, as well as assessing its pros and cons.

Seventy three germplasm of field pea were tested under glasshouse and field condition against rust disease caused by Uromyces viciae fabae (Pers.) de Bary. Among screened germplasms, 30 susceptible, 40 highly susceptible and 3 belonged to moderately resistance group. The susceptible germplasm showed leaf area with symptoms (LAS) ranged from 30 to 65% with area under disease progressive curve (AUDPC) values from 77.5 to 1290 and apparent infection rate from 0.0134 to 0.1698 and highly susceptible germplasm showed LAS ranged from 60 to 95% with AUDPC values ranged from 1075 to 2179. Apparent infection rate ranged from 0.0616 to 0.6950 while moderately resistance germplasm showed LAS ranged from 20 to 24% with AUDPC values ranged from 350 to 438 and apparent infection rate ranged from 0.1180 to 0.1198 in field as well as glasshouse conditions. The moderate resistance germplasm JPF 99025, KPMR 615 and KPMR 551showed lowest LAS, AUDPC value and apparent infection rate, hence, these germplasms could be used in breeding programme.

Pathway analysis is widely used in omics studies. Pathway-based data integration and visualization is a critical component of the analysis. To address this need, we recently developed a novel R package called Pathview. Pathview maps, integrates and renders a large variety of biological data onto molecular pathway graphs. Here we developed the Pathview Web server, as to make pathway visualization and data integration accessible to all scientists, including those without the special computing skills or resources. Pathview Web features an intuitive graphical web interface and a user centered design. The server not only expands the core functions of Pathview, but also provides many useful features not available in the offline R package. Importantly, the server presents a comprehensive workflow for both regular and integrated pathway analysis of multiple omics data. In addition, the server also provides a RESTful API for programmatic access and conveniently integration in third-party software or workflows. Pathview Web is openly and freely accessible at https://pathview.uncc.edu/.

The progression of pipeline industry require good standard for corrosion resistivity in steel. It will lead a huge concern for endless steel manufacturers. The mechanical properties of stainless steel can be astoundingly improved through sensible alloying component, for example, V, Nb and Cr and legitimate planning of thermo-mechanical handling with boundaries that refine and homogenize the microstructure. After complete the way toward moving, control of cooling rate is basic to shape the vital stages in the last microstructure. Present assessment intends to think about the effect of cooling rate and thermo-mechanical dealing with boundaries on the microstructure and mechanical properties of stainless steel. The study is done on optical, SEM and Transmission electron microscopy (TEM). The investigation shows that improvement in grain refinement and precipitation thickness scattering.

Nanocomposites has floated in the market as the best in class material related to many sectors of manufacturing. Base material is embedded with nanoparticles to form nanocomposites. Afterwards, layered formation known as interphase starts to take place. It is the link (interface) between the base material (polymer) and the nanoparticle. Up till now, the problem of finding the material properties in this interphase has become a challenge for researchers and scientists. This piece of work corresponds to analyzing the possible types of variations in properties within interphase. Some power law may govern the distribution of material properties in nanocomposites and unit cell of same may be investigated. For getting the values of final properties of polymer nanocomposites, ideation of variation in the interphase area is quite essential. The huge improvement in the material properties in nanocomposites is observed just because of the zone of interphase. As it is a very difficult area, as far as its property analysis is concerned, So extensive literature survey is required for proceeding ahead. Nanocomposites have nowadays also coined in the form of novel materials for various processes like additive manufacturing.

Vehicle industry assume unequivocal role in the financial development of the nation. The significant test before car industry is to deliver light weight parts without diminishing strength parts, for example, connecting rod and driveline segment, this can be accomplished by utilizing high strength low alloy steel. In all metal forming process forged parts posses high yield strength due to the favored direction of grains. Accordingly present exploration work zeroed in on Micro basic and Mechanical Behavior of As-Cast and Hot Forged Microalloy Steel. Impact of thermo-mechanical handling and cooling rate is additionally considered. Characteristic evaluation investigation of As-projected steel and hot fashioned steel is contemplated utilizing optical and SEM technique. Tensile testing performed on Instron testing machine. It is observed that due to the thermomechanical handling of steel there is development of strain instigated precipitate that advantage as far as effect strength and toughness of steel.

In general solutions and outcomes to an issue in image processing, a ton of trail and examination with an enormous assortment of test photographs is incorporated. Pediastrum, which comprises of pigments like carotene, xanthophyll, chlorophylls, and other nourishing elements like complex sugars, major and minor minerals, and protein, enzymes, fiber, is a minute coccal shaped colony forming green algae. In this research, an attempt was made to solve the problem of identifying and classifying different species of Pediastrum with the aid of CNN based deep learning model. The informational collection comprising of 12,000 algal pictures was being utilized by, AlexNet CNN (Convolution Neural Network) model for the training and validating purposes. The features like the presence of sporopollenin in the cell wall, the structures and the functions of the cells, and the structural properties of coenobia make the basis for automated classification by AlexNet deep learning model. The efficacy of the proposed approach is demonstrated by an experimental outcome of 99.54 percent classification accuracy with precision and Fl-score more than 0.98.