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This paper describes a robust autonomous disinfection tunnel to disinfect external surfaces of COVID-19 virus such as clothes and open body sections in public places such as airports, office complexes, schools, and malls. To make the tunnel effective and highly efficient, it has been provided with two chambers with three disinfection processes. Due to the multiple processes, the possibility of neutralizing the virus is quite high and higher than other solutions available at this point for this purpose. Chamber 1 sprays the solution of a disinfectant on the person. This solution can be either a dilute solution of approved chemical or any Ayurvedic/herbal disinfectant. Once the person enters chamber 2, he/she is exposed to hot air at 70 °C along with far-ultraviolet C rays (207–222 nm). Both chambers function autonomously by detecting a person in a chamber using ultrasonic sensors. The proposed tunnel is developed under industry–academia collaboration jointly by Technopark@iitk and ALIMCO under the ambit of the Ministry of Human Resources Development and the Ministry of Social Justice and Empowerment, respectively. The tunnel is referred to as the ‘Techno Advanced Disinfection Tunnel’ (TADT).

This work explored the performance of solar still using different nanoparticle doped in black paint coating. Nanoparticles such as reduced graphene oxide (RGO), CuO and TiO2 of size 30–50 nm were selected, then a solution comprised of turpentine/black paint (1:4) was taken and these nanoparticles were mixed and the solution was stirrer to achieved homogeneous solution of three different type. Four solar still, one with absorber coated using bare black paint and the other three solar still with different nano particle coated absorber were fabricated and tested in Jaipur, India. Maximum heat transfer coefficient was demonstrated by RGO coated SS, owing to the excellent solar absorption behavior along with higher thermal conductivity. Conventional SS with bare black paint coated absorber showed maximum hourly water yield of 0.7 L. The maximum hourly water yield of 0.88 L was shown by RGO coated absorber due to phenomenal thermo-physical properties, which promotes higher heat transfer rate and evaporation rate. However, CuO and TiO2 showed maximum hourly water yield of 0.84 L, and 0.77 L, respectively.

This paper focuses on the principle and results of the alteration of the straight wind vertical axis wind turbine. A modification to the aerofoil profile is tested using a notch. This research focuses on the lift coefficient values, the drag, and moment coefficient as these are the essential parameters used to calculate the turbine power provided by inviscid turbulence models which are used to simulate the mean flow characteristics of turbulent flow in computational fluid dynamics. Both design modifications and simulation research were done using ANSYS Fluent, utilizing computational fluid dynamics. In ANSYS, the FLUENT (CFX) module is used for performing the simulation process. Standard profile blades are analyzed and are compared with that of the modified profile blade values. In this analysis process, symmetrical 4-digit aerofoil models such as NACA0012, NACA0015, and NACA0018 are used. The whole analysis was conducted based on the lift and drag characteristics of each profile at 2°, 4°, 8°, 10° angles and compared these with the standard ones. Inviscid flow models are used to avoid unnecessary friction for the flow, and the flow is presumed to be ideal flow to prevent the backflow pressure. This fundamental research is based on how the forces act on the aerofoil profile when fluid strikes with different velocities and at a different angle of attacks.

Among other renewable energy sources, harnessing wind energy is the least expensive method. A fundamentally different approach to capture wind energy by further reducing prices is being used by Bladeless Wind Power production. The device absorbs the energy of the vortex, an aerodynamic influence. If the wind flows through a buff body, it changes its flow and creates a cyclical vortex pattern. The fixed structure begins to oscillate until the forces caused by these vortices are strong enough. The model maximizes the resulting oscillation and captures the energy instead of preventing these aerodynamic instabilities. Instead of the usual tower, nacelle, and blades as used in conventional turbines, the device has a fixed mast to capture wind energy, a power generator, and a shaft. The purpose of this paper is to ameliorate the understanding of this technology by developing a simulation model, considering parameters like wind velocity.

A thermal modeling of advanced design solar still is shown in the present paper. The aim of the present experiment is to show the performance of solar still with variation of tilt angles. The objective is to see the effect of solar still on the productivity due to differential tilt angles of glass cover. To achieve this, three different angles-based solar stills (11°, 26°, and 41°) have been installed at the M.I.T.S, Gwalior Campus (latitude of Gwalior city is 26.2183° N). As a result, it was found that the latitude angle-based solar still has higher productivity than other angle-based solar still. The productivity of latitude angle-based (26°) solar still was 31.95% and 20.96% higher than 11° and 41°-based solar stills, respectively.

Lung cancer is one of the severe diseases nowadays and one of the major causes of growing deaths. So, medical experts believe that diagnosing malignant cells in the early phase can reduce the risk of patients’ death. Present-time Deep learning is contributing lots of services in different sectors for automating human tasks with ease. As the introduction of many deep learning models such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and various other models. With little advancement in these models, humans are capable of solving complex tasks such as image recognition, natural language processing, object detection, object segmentation, and language translation and achieved state-of-the-art performance. However, problems like lack of viewpoint invariance lead to the introduction of a supervised deep learning model known as Capsule Network (CapsNet) with the intent of achieving human-level efficiency. Our proposed methodology is based on CapsNet to detect lung cancer nodules and further, we apply pre-trained FixEfficientNet to classify CT images as it requires fewer parameters. We train these models using publicly available datasets: LUNA-16 and LIDC-IDRI and validate on these benchmarks. We achieved an accuracy of 98.47% in nodule detection and 93.59% in nodule classification.

Crop residue burning is an emerging problem due to shortage of manual labor and mechanization of agricultural practices. It affects not only soil microbial community and nutrient transformation processes in soil but also human and animal health adversely. Soil is a medium for plant growth and a support system of millions of fauna and flora, greatly affected by repeated burning of crop residue in farms. Changes in microbial activity upon crop residue burning depend on soil temperature, length of burning, rain incidence after burning, dominant group of microorganisms, and time of sampling. The adverse effects of residue burning on soil biota and thus on soil health will continue for long term, and that eventually affects sustainable crop production. The increased soil temperature at the time of residue burning not only kills the soil microbes but also depletes soil organic carbon level, which is vital for keeping soil living. In short, adopting suitable location-specific technology is necessary to ensure proper residue management without harming the various life forms on earth. Also, encouraging and incentivizing the farming community for enriching the soil with carbon will help in discouraging the practice of crop residue burning.

Vegetable fiber- bolstered polymer composites are locating their role extensively in structural engineering ranging from civil structures to automobile fabricating because of the properties, like easy availability, low density, biocompatibility, bio decomposability and ease to handle. Over past few decades these products had been evaluated for their mechanical and chemical resistance strength and were contrasted with those of artificial fibers bolstered composite materials. In addition to above properties, evaluation of thermal characteristics of vegetable fibers and their composites have been also a topic of count because they decide the overall performance of the resulted products. Impact of temperature on adhesion of fiber with matrix, on matrix curing, on matrix cross linking and fire damage during fabrication have been also a part of thermal study. No doubt, there are numerous works have been mentioned in literature on thermal stability of natural fibers and these fibers reinforced thermoplastic/thermosetting matrix based composites. However, in present chapter we will very well take a look at thermal behaviour of different raw vegetable fibers, phenolic matrix and vegetable fibers reinforced phenolic matrix composites. In addition, impacts of fiber’s surface functionalization on thermal behaviour of fibers and fibers reinforced phenolic composites will be also a part of our study in this chapter.

More than two-third of the world population depends on groundwater for drinking purpose. Several countries are on the verge of water crisis due to the overexploitation of groundwater for irrigational and industrial purposes. The available sources of water are currently affected by a large number of geogenic (As, F, NO3, etc.) and anthropogenic contaminants (Pb, Cd, Hg, etc.). These contaminants cause severe health effects both carcinogenic and mutagenic. There are several remediation technologies employed for the groundwater as well as soil remediation including pump and treat, air sparging, natural attenuation and containment. For the second and third world countries, permeable reactive barrier (PRB) can prove to be a major replacement for the already existing methods like the pump and treat. The topics which are discussed in the chapters following PRBs are its design, mechanisms, softwares, reactive materials, case studies in developed countries and its economic viability. The important aspects of using PRBs are easily available adsorbent material like compost, limestone, etc.; the time scale for which it can be used is decades, and the operational and maintenance cost are low. The chapter also includes favorable hydrogeological conditions for the installation of PRBs. It also brings the different set of adsorbents (reactive materials) that can be used for a different type of contaminants organic and inorganic. We have also looked out for the mechanism of degradation being a reduction, sorption, etc. This chapter also includes the possibility and problems which we can face during the installation of PRB in pilot-scale before implementing it at a larger scale. At last, we have compared different case studies, the filler material used, the type of construction used, the date of operational setup and cost analysis of PRBs. The chapter has been concluded in a good note depicting all the pros and cons of PRBs.

Composite materials are widely considered nowadays for several kinds of structural applications. In the analysis of the beam, particularly for a composite using experimental or numerical method, it is quite challenging in comparison with the regular conventional materials. Hence, in the present work, carbon fiber and glass fiber beam are considered for vibration analysis of composite beam. In the numerical modeling, three aspect ratios (i.e., L/H) in the range of 100–150 are considered with multilevel orientations (i.e., [0/0]3, [45/90]3, [90/0]3 [0/0]4, [45/90]4, [90/0]4). Two boundary conditions (cantilever, simply supported) are considered for the beams. From the numerical analysis, it is observed that glass fiber composite beams have a higher natural frequency in comparison to carbon fiber composite beam.

Vitality and water are need of humanity that impacts the advancement of any country. Today, the creation of crisp drinking water is a significant issue. Drinking water lack is relied upon to end up noticeably one of the most concerning issues confronted by world. Solar still is a device which is used to convert brackish water into distilled water with the help of solar energy, but it has limited productivity. In this work, comparative study of productivity of single-basin solar still having nano fluid Al2O3 + water inside basin with same depth of water and absorber plate inside water basin as copper and aluminum has been examined. Water basin was black painted inside to absorb maximum solar radiation. Due to high thermal conductivity of copper plate and addition of energy-absorbing nano fluid Al2O3, rate of evaporation of water from basin to glass surface got increased and maximum productivity of distilled water of 4.77 L was achieved for copper-based absorber plate as compared to 4.41 L for aluminum-based absorber plate. Energy-absorbing medium such as metallic plate and nano fluid helped in maintaining a fair productivity when solar radiation value reduced, and they helped to enhance productivity of solar still.

Urban Sprawl, a burning global phenomenon, refers to that extent of city or urbanisation, which may driven by industrialisation, population growth, settlement on the periphery of the city and large-scale migration. India, with population of over one billion, which is one-sixth of the world’s total population, phenomenon of Urban Sprawl is affecting its natural resources like never before. This results in multiple problems such as unmanageable transportation, unemployment which results in poverty, illegal housing colonies, slums, etc. This study illustrates the use of Geospatial and Statistical Techniques to highlight the extent of Urban Sprawl in Shimla Municipal Corporation, Himachal Pradesh, India; at a detailed level. In the present work, four temporal satellite images of Landsat Thematic Mapper have been used over a period of nearly two decades (i.e. 1991–2011). Landsat imageries of two time periods (Landsat Thematic Mapper (TM) of 1991 and 2011; and ETM+ (Enhanced Thematic Mapper) 2001), were used and quantified for studying the decadal change in land use/land cover. Supervised classification methods have been employed using Support Vector Machine in ENVI 5.0 and ERDAS 2014. The study area is categorized into five different classes, viz. water bodies, forest area, built-up area, agriculture and open space. The results indicate that built-up area is the major land use in study area. During the period 1991–2011, the area under built-up land has increased by 529.65 ha (26.48)% due to construction of new buildings on forest land, agricultural land and open spaces. As a result, the area under vegetation (forest), open space and water bodies decreased by −361.71 ha (−18 09%), −178.02 ha (−8.90%), 0.36 ha (0.02%) respectively. Urban built-up density was calculated in percentage (%) for 25 wards of the city for 1991, 2001 and 2011. Depending on the density levels, it categorized as low, medium and high density. The process of urban expansion in the Shimla City during 1991, 2001 and 2011 are further studied by examining a distance decay concept from a major road. The study also highlights the nature, rate and location of change; and the importance of digital change detection techniques in land use planning for sustainable growth of the study area. The Shannon’s Entropy Index and Landscape Metrics have been computed in order to quantify the urban growth using built-up area as a spatial unit. Further, Stepwise Regression techniques were used to explore the relationship between the urban growth and its contributory factors. Further, Stepwise Regression was used to study the impact of Independent Variables (population density, female literacy rate, road density, total workers, sex ratio, α-population, number of HH, β-population) and Dependent Variables (percentage of built-Up area) factors on urban growth. The result shows that the growing population triggers the increase in built-up area in study area. This study also demonstrates the potentials of geospatial data in mapping, measuring and modelling the urban sprawl, which could be helpful to decision makers to form/make particular decision support system for sustainable growth of hilly urban areas or in making Smart City planning.

The ever-evolving ubiquitous online social networks have been witnessing plethora of precarious, enigmatic and flabbergasted information imposing a probe on its credibility, in the recent state of affairs. This has posed interesting challenges in context of research on information credibility, pinpointing the trustworthiness, necessity and influence of privacy and security in online social media. This paper primarily focuses on the increasing inundation of idiosyncrasies in online social media, the significance of ensuring credibility of information, and incidental collated compromises apropos to online reviews. The crux of this paper implicates investigation of the prevalent opinion spammers that distorts the perceived quality of a product via fraudulent reviews. These falsified reviews’ progressive proliferation have been explored, exemplified and experimented with the tools, viz. “Fakespot,” “ReviewMeta” and “Review Index” demonstrating action, detection and prevention from the coherent and inherent fraud-bots which are intentionally targeted on large online app review databases entailing deceptive and skeptic opinions.

Increasing population pressure and rapid urbanization have put added pressure on land for higher food production per unit area for ensuring food security, which has led to intensive agriculture resulting in deterioration in soil quality. To protect the soil from degradation and for its sustainable management, soil quality assessment strategies are required. Hence, monitoring of soil quality is important and can be achieved through assessment of physical, chemical, and biological parameters of soil. Among the different soil quality parameters, biological parameters are more responsive to changes in management practices. With the accessibility of new tools and techniques, assessments of microbiological parameters have become more rapid, reproducible, and informative. The shift in conventional methods like microbial biomass carbon and soil respiration to modern tools like molecular methods and high-throughput enzyme assay techniques not only gives more information about what is happening in an ecosystem, but also helps to formulate a strategy for sustainable land management for future.

In this paper two interacting species in presence of adaptation (dormancy of the predators such as resting eggs) has been discussed. The dormant stage is an equipment to survive in harsh environment. We have discussed the stability analysis of system without diffusion and in presence of diffusion. Our numerical investigation reveals that above the critical value of interference among the zooplankton the system become stable. Spatiotemporal pattern shows a transient complex spatiotemporal pattern by increasing the time and space.

The community detection in a given network is the idea to find a cluster in the structure. A community is the most densely populated part of the graph. The observed network is mostly sparse having multiple dense partitions in it, for example, a protein–protein interaction network where different proteins interact with each other. Here, communities can be detected by finding the cluster of proteins in the network to find different functional modules. Another example is of Facebook friendship network. Several authors try to find the structure and communities in this type of network. Multiple clusters in one network can also be detected which can overlap with each other. This paper covers the classification of different community detection techniques in dynamic networks and then compares them on the basis of different features, e.g., parallelization, network models, community instability, temporal smoothness, etc.

Cross-domain recommendation Systems (CDRS) is a significant research area which has been target of many companies these days. From last few years, there is amount of publications in CDRS domain including recommendation systems which have been rising sharply alongside information retrieval and machine learning. Recommender systems help companies to specifically identify preferences of the user from the collected data from various sources. These data values are then used to identify user preferences also known as recommendations. In cross-domain, we use the data from one domain such as movies to recommend items in other domains, for instance, Books. There are numerous issues which recommender systems suffer together with sparse data, synonymy, data privacy, algorithm scalability, perspective awareness (context) and cold start problems. Data sparsity is a major issue in recommender systems, especially in the presence of novel users or items, or when user drift exists. This paper reviews recent efforts made for CDRS sparsity and user drift which are prevalent in most CDRSs such as user-based, item-based or knowledge transfer. This paper formalizes the CDRS illustrates sparsity related issues which are addressed in prior works and finally proposes for future research trail.

Freshwater scarcity and growing vitality essential are among the most important issues around the world. In the current work, an effort is made to improve the yield of existing single-slope single-basin solar still (SS) with basin area of 1 m2 using various energy absorbing material such as black granite stone, metal scrap of mild steel and nanoparticle Al2O3 in the water basin, and the freshwater yield was compared with and without the energy storing material (ESM) for the water depth of 0.01 m. Yield of freshwater augmented by 11.6%, 25.1% and 33.5% by using metal scrap, black granite and nanofluid Al2O3 inside the water basin, respectively, and the full day efficiency augmented by 15.5%, 26.8% and 33.6% as compared to the conventional SS. It was concluded that the solid nanometric size particle Al2O3 inside the water basin helps in achieving the maximum yield of the freshwater. SS is also proficient to eliminate the impurities of brackish water and convert it to pure and distilled water with PPM ranging below 50 and makes it ideal for the rural Indian villages with economical and hygienic point of view.

The paper makes a critical study of colonial writings on history of Northeast India; identifies inherent bias and prejudices, questions their reliability and validity at the backdrop of political and epistemological crisis that had gone into the creation and argues in favour of interdisciplinary approaches in the process of reconstructing the past history of the Northeast societies; which are predominantly pre-literate and do not have any written tradition. The paper examines the role of colonial ethnographical accounts; discounts projection of tribes as cultural isolates and suggests reconstructing the history in terms of shared past and shared culture; economic dependence; and precisely in the framework of interaction. The paper advocates for historical analysis of the socio-economic life; political and cultural developments on the basis of social science principles and universalism based upon the parameters of causes and effects.

Machine learning is one of the most widely used approaches in current day for effective analysis and prediction purpose in the domain of image processing applications. This paper thus makes a study of existing image retrieval methods. It has been a challenge to implement human recognition method in machines for a long time now. In this process number of methods and procedures are developed to implement the human recognition system in machines. It is however still not possible to achieve the accuracy human are bestowed with. There are number of ways in which different researchers have attempted this task. The paper describes the method along with the parameters used, processing method, and the accuracy achieved. The latest method being machine learning, this study concentrates on the development of supervised learning and thereof the progress made by the unsupervised learning methods. The two techniques Text-based Image Retrieval and Content-Based Image Retrieval are the important retrieval methods dealt with.

Dynamic graphs model time-varying interactions between related entities in a network. Extensive studies have been carried out on the mining of frequent, regular, and periodic behavior of such interactions. Some of the previous research focused on providing users the platform to mine periodic patterns on a single aspect (structure, weight, or direction) at a time. However, the designed tool needs to be run multiple times, to mine significant information that is gained by the study of multiple aspects simultaneously in a network. Moreover, it lacks capability of mining the regular patterns in a network, and the applicability of which lies in wide-ranging domains. In the present research, a tool, the Multi-aspect Dynamic Graph Miner, is proposed that fills up these gaps by providing users an integrated platform for mining regular and periodic patterns on multiple aspects. Besides the primary features, it facilitates easy visualization of tool output and provides a converter for the users of previous works that some portion of our software is based on. We further discuss its applicability by testing on real-world and synthetic datasets.

The soil scientists along with microbiologists had a big responsibility to come forward with a sustainable solution to enhance soil nutrient supplying capacity, without applying the agrochemical and mineral fertilizers. The only way out to this problem is through the use of efficient microbes which plays a vital role as organic or biological agents in facilitating uptake of many primary and secondary nutrients. Moreover, the fertility of any soil is directly proportional to the microbial biomass and its potential of functional activity and diversity. Billions of microbes which are present in soil are major key players of nutrient cycling and their solubilization and mineralization. This fact has been known and scientifically reported for a number of decades, but still its significance has not yet channelized into the mainstream of intensive agriculture. Thus, in this chapter, exhaustive overview of the different groups of agriculturally important microbes has been given which are responsible for enhancing nutrient availability particularly nitrogen, phosphorus, potassium, sulphur, iron and zinc in agricultural soils.

The term hydrogel was coined in 1894 as it was employed to explain a colloidal gel. The first report on the application of hydrogels was given by Wichterle and Lim in 1960, which was in the biomedical field. Hydrogels generally absorb a large amount of water, and this swelling is responsible for the rubbery and soft properties of hydrogel. Hydrogels have found applications in environmental, biomedical, food, etc., fields. This chapter presents a brief review of hydrogels—basic definition, classifications, preparations and applications. This chapter highlights among others, the application of polysaccharide-based hydrogels in adsorption and dye removal in water treatment.

This study proposed an analytical model of contaminant solute transport with an impact of elemental recharge rate of aquifer. The domain of study is considered as a heterogeneous porous media. Dispersion is directly proportional to the square of the seepage velocity, whereas the velocity is a function of both time and distance variables. Initially, the aquifer is not pollutant free; some background concentration is present there. Temporally dependent exponentially decreasing input source is considered, and the concentration gradient is assumed to be zero at the exit boundary. Laplace transform technique (LTT) is used to obtain the analytical solution and is validated with the numerical solution which is obtained using explicit finite difference method.

The present study deals with two-dimensional solute transport equation with time-dependent source in homogeneous semi-infinite aquifer. Linear isotherm is taken into consideration due to interaction between solid and liquid phases. Initially, the domain is not solute-free. Initially, space-dependent exponentially increasing form with initial concentration is taken into consideration. At the one end of the domain, time-dependent source concentration is taken into account. Due to no mass flux at the other end of the domain concentration gradient is assumed to be zero. Laplace integral transform technique (LITT) is used for analytical solution, whereas explicit finite difference (EFD) scheme is used for numerical approximation. The exponentially decreasing and asymptotic form velocity function is taken into consideration for the graphical representation of the solutions.

Water is necessary for all living beings. It is particular the most important factor for the sustenance of mankind. More than 66% of the earth is covered with water in which 97% of available water from various sources stands brackish which includes some harmful microbes, and 2% water is frozen in the form of icy masses and freezing tops. Solar still (SS) is a device used to convert brackish water into distilled water, but it has very limited productivity which is the major concern. To improve the yield of simple solar still (SS) in this work, black paint is mixed with Al2O3 + water to make it nano-paint and it is coated outside the glass cover of solar still. Al2O3 can be placed inside water sink to increase the vaporization rate, and due to this, yield productivity increases. Experiments were conducted from 25 June to 27 June for common depth of 0.01 m for simple solar still and nano-fluid in water basin of solar still and nano-paint with nano-fluid both combined for SS in climatic conditions of Jaipur, India. The theoretical performance of the passive solar still and nano-paint and nano-fluid in solar still is compared with effectiveness and yield productivity. Simple solar still gives the water output of 4.47 L for 0.01 m water depth whereas simple SS with Nano fluid give output of give output of 5.25 L and SS with Nano fluid in water basin and Nano paint on glass cover of SS give yield of 5.56 L for all three cases for same water depth.

The diversity of microbes present in the rhizosphere plays a significant role in nutrient cycling and soil sustainability. Plant–microbe-modulated phytoremediation is a viable technology for the cleanup of contaminated environments. Several plants that were identified have various degrees of capacity to eliminate, degrade or detoxify, metabolize, or immobilize a wide range of soil contaminants. Plant-based remediation technologies are not yet commercialized because of its major limitation of slow process and restricted bioavailability of the contaminants, and it is greatly influenced by the climatic factors. The extensive use of plants can overcome most of the limitations by exploring the potential of microbe–plant–metal interaction. The biogeochemical process occurring in the root zone can influence on several rhizobacteria and mycorrhizae directly linked with microbial metabolite synthesis. Thus, a holistic approach of novel remediation technologies and understanding of plant–microbe–contaminant interaction would help for customizing phytoremediation process in relation to site-specific contamination. There is a huge challenge to remediation of contaminated sites by long-term accumulation of heavy metal. Unlike organic contaminants, metals are very much resistant to degradation, and in the long run, continuous accumulation may cause food chain contamination. It is very important to decontaminate the polluted sites in order to reach safe level of metal concentration below the threshold limit of toxicity. Recent studies revealed that phytoextraction, mainly the use of hyperaccumulator plants to extract toxic metals from the contaminated sites, has emerged as a cost-effective, eco-friendly cleanup technology. Novel, efficient microbes and their potential use in the plant rhizosphere could further enhance the phytoremediation for wider range of soil contaminants.