Software development is not an easy affair. When it’s come to develop large and complex software there is a need to use reusable components by the means of Component based Software Engineering (CBSE) Framework. In Component Based Software Engineering, component is basically developed in two categories i.e. Commercial Component and In-House Component. Developing and using reusable components is not an easy task for the software industry. To develop high quality software, various testing methods can test but when it comes to test any software that is developed using a reusable component then there is a requirement to first test the component itself for its quality. In this article the main focus is on the issue like controllability, observability, understand ability and challenges like develop reusability test case, test drivers etc in component testing in component based software engineering.

The Internet of Things (IoT) which is dynamic, intelligent, and ubiquitous. Academic and commercial organizations mostly prefer the Internet of Things for research. Day by day, IoT publicity is increasing. An intelligent network that concatenates all things (IP or non-IP based) to the Internet for information interchange and communication is the Internet of Things (IoT). This paper provides the IoT system with its applications, challenges, and open issues and discusses the state-of-the-art methods of the IoT system and its layered architecture. Sensors and actuators are combined in the IoT system for new services and products with highly efficient, low costs, and user friendly. The IoT is ordinarily composed of various advanced technologies like software, actuators, sensors, and electronics because of Micro-Electro-Mechanical Systems (MEMS) comprising electronic and mechanical components at
the micron level.

Arsenic (As), a naturally occurring element may induce oxidative stress and is a potent carcinogen. The present study aimed to find the lethal and sub-lethal concentration of arsenic trioxide and explore its effect on survival of fruit fly Drosophila melanogaster. Amelioration using polyphenols (curcumin and soya extract) have been introduced as a successful strategy to overcome this problem. The study showed significant decrease in lifespan of flies treated with arsenic trioxide. 50% mortality was seen in media with 0.5 mM arsenic trioxide and 100% mortality at 0.75 mM. Increased lifespan was observed in medium containing arsenic trioxide (0.55mM) with curcumin (Curcuma longa) and soya extract (Glycine max) respectively. Best survival rate was found in 0.55mM arsenic medium with 1 mM Curcumin and 1.5 mM Soya extract respectively. Lipid peroxidation assay showed significant increase in malondialdehyde (MDA) values in the flies treated with arsenic trioxide as compared to control. The MDA values decreased significantly in flies treated with arsenic mixed with curcumin and soya extract respectively. The results indicate that exposure to sub lethal concentration of arsenic trioxide may cause oxidative stress and affect the lifespan of D. melanogaster. Curcumin and soya extract may help in reducing the impact of oxidative stress and toxicity caused by arsenic trioxide.

Since the outbreak of COVID-19 Pandemic and the following lockdown, online food delivery services have been evolving like never before. Although technology is not the first thing that comes to mind when we think of food delivery, technology indeed is becoming an integral part of the online food delivery industry. One of the technologies which has revolutionized the food delivery industry is Artificial Intelligence (AI). AI in simplest terms, is the ability of computers and machines to learn, think, and decide just as humans do. AI not only lets food delivery companies estimate user choices and preferences, it also allows them to function more efficiently and accurately. This paper explores how online food delivery platforms are continuously leveraging AI to enhance customer satisfaction by keeping up with the rapidly-changing consumer behaviour. This paper also attempts to identify the facets of AI, the benefits and opportunities AI offers, and the challenges associated with its use. The research is limited to the Indian context and secondary sources of data have been used for the purpose.

The Enterprise Neurosystem Group is an AI and machine learning (ML) open source research community effort which includes representatives from several large and small industrial and academic institutions. The goal of the group is to facilitate the development of technologies, documentation and best practices which are needed to create the enterprise nervous system, a large interconnected collection of various AI models that can provide a C-suite executive with insights into all aspects of corporate operations in real-time. The academic partners in this group include Stanford Stanford Linear Accelerator Center, Harvard Analytics and University of Cali- fornia Berkeley’s Data-X program. The industrial participants include personnel from America Movil, Reliance Jio, Equinix, Ericsson AI, IBM Research, Intel, Kove, Penguin Computing, PerceptiLabs, Seagate and Yahoo! In this paper, we perform a case study on this group, with an overview of its vision, its structure, and different activities within the group.

Cyberspace has become the most popular carrier of information exchange in every corner of our life, which is beneficial for our life in almost all aspects. With the continuous development of science and technology, especially the quantum computer, cyberspace security has become the most critical problem for the Internet in near future. In this paper, we focus on analyzing characteristics of the quantum cryptography and exploring its advantages of it in the future Internet. It is worth noting that we analyze the quantum key distribution (QKD) protocol in the noise-free channel. To include real practical stimulators, there are developed various QKD Schemes for the noisy channels. Here we develop the unconditional security of quantum cryptography theoretically, which is suitable for the Internet as ever-increasing challenges are inevitable in the future.

Quantum key distribution (QKD) uses individual light quanta in quantum superposition states to guarantee unconditional communication security between distant parties. In practice, the achievable distance for QKD has been limited to a few hundred kilometers, due to the channel loss of fibers or terrestrial free space that exponentially reduced the photon rate. Also experimentally it is proved that the Satellite-based QKD promises to establish a global-scale quantum network by exploiting the negligible photon loss and decoherence in the empty space.

In this paper, we also give some introduction to various public-key cryptography and also touch on the various functions, advantages, and disadvantages of quantum cryptography and the need for quantum cryptography in the future as in data encoding, and digital signatures, and many more. It also covers the various securities issue of our current cryptography system. Different protocols BB84 i.e., the first QKD protocol also some other protocols, and finally the future directions of quantum cryptography followed by the conclusion of the paper.

Soil is the most important gift of nature formed in hundreds/thousands of years covering the land surface but soil cover is depleting day by day due to geological and/or anthropological activities. Erosion is one of the most important geological processes in reducing the soil cover. Hence, there is a requirement to conserve the soil cover and the first thing which can be done in order to conserve the soil is the identification of vulnerable areas. Identification of vulnerable areas is of foremost importance which could be done by scientific methods. Hydrological Parameters are one of them which can be calculated using Geographic Information System. In this study, Digital Elevation Models have been processed in geographic Information System to calculate three important hydrological indices i.e., Sediment Transport Index, Topographic Wetness Index and Stream Power Index along with other parameters like Slope. Maps showing variability in Slope, Sediment Transport Index, Topographic Wetness Index and Stream Power Index have been prepared to understand the variability and the importance of each parameter in marking the vulnerable areas to erosion. With this, an Erosion Hazard Vulnerability Map of the study area (in and Around Kharagpur Hills, Munger-Jamui, Bihar) has been prepared using Weighted method of Geographic Information System. It has been found that Soil cover over the hills with Steep Slopes are more prone to erosion whereas Soil cover over the very gentle slopes or in the flat areas are least prone to erosion. Along with this it has also been found that river sediments deposited in the point bars along the banks of the river Ganges are also moderately to highly prone to erosion. The importance of spatial analyst tool of geographic information system has been utilized in delineating the vulnerable areas.

SARS-CoV-2 (Severe Acute Respiratory Syndrome coronavirus) poses an unprecedented public health threat to the mankind globally since December 2019. Considering the escalating number of positive cases, the World Health Organization announced public health crisis on 11^th March 2020 worldwide. The pathogenesis of SARS-CoV-2 (causal agent of COVID-19) is not clearly understood till date and the role of antiviral therapeutics is yet to be established for this pandemic. The objective of our study was to compare the SARS-CoV-2 sequence of Wuhan virus with those of Indian SARS-CoV-2 isolates; only those mutations which occurred in the helicase (nsp13) region were addressed and used for subsequent study. For mutational characterization multiple sequence alignment was done followed by protein dynamics study using Chimera and Dynamut software. Altogether, 51 mutations were detected in the nsp13 of Indian SARS-CoV-2, out of them 7 mutants were used for subsequent study. Furthermore, prediction of secondary structure as well as protein dynamics study revealed that these mutations altered the structural stability and flexibility of helicase protein. In this in silico study, predictive tools of immunoinformatic were used for the prediction of B-cell, T-cell and MHCI epitopes. Two mutations have been detected in the predicted epitope region of SARS-CoV-2 helicase that might induce its conformational changes and considered as a major challenge in the development of vaccine. The present investigation was, therefore, undertaken to analyze one of the crucial drug target like helicase which is indispensable for the replication /transcription machinery of SARS-CoV-2.

Diabetic nephropathy is a common disease of type-1 diabetes and type-2 diabetes. It is a usual problem and main cause of death in people with diabetes. Uncontrolled diabetes can damage the blood vessels in kidneys so that filter of the waste in your blood can not be done properly. This will lead to kidney damage and high blood pressure .The high blood pressure can cause further damage to the kidneys by increasing the pressure in the delicate filtering system of the kidneys.The complications of diabetic nephropathy may develop gradually over months or years. In this work study of ensemble algorithm included Bagging, AdaBoost and Random Forest, Gradient Boosting,Bayesian Networks technique is done

The use of nanotechnology for drinking water purification becomes the emerging field around the world. Usually the nanoparticles are synthesized by variety of chemicals which are quite toxic, flammable in nature and their modes of working are unethical for mankind. The extensive application of the AgNP results in their inevitable release into the environment. Silver nanoparticle is known as excellent antimicrobial agents and therefore they could be used as alternative disinfectant agents. It was found that the aggregation of AgNPs depends on the properties of the background ions, such as Na⁺ and Ca²⁺ at different water chemistry conditions. The antimicrobial properties of AgNPs when coated with different organic compounds using natural water conditions. The results obtained showed that silver nanoparticles in surface water and ground water are stable.

The composition of AgNPs - impregnated RO-filters and silver- impregnated RO-filters. This study was performed using different water chemistry condition and different manufacturing materials. The results showed that AgNPs- impregnated RO Water filters are more appropriate for this application due to the lesser amount of silver nitrate treated filters.

The bacterial removal performance of the AgNPs-treated RO- Water filters and concentration of viable bacteria in the filters are dose-dependent on the amount of silver applied.