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Globally, pesticide use continues to rise, estimated to be over four million tonnes yearly. In 2020, it was almost 2.7 million metric tons, up 57% from 1990. Nanotechnology is an innovative and exciting technology that offers new nanoscale molecule designs, formulations, and delivery systems to diminish the hazardous pesticide effects. Many studies on nano-pesticide production have been published, whereas nano-biopesticides are still limited. The purpose of this research is to answer the question of whether nano-biopesticide formulations will emerge along the development of nano-pesticides. The research was conducted by using bibliometric analysis. All nano-pesticide and nano-biopesticide-related publications are extracted from the Scopus with no limitations year. Using VOSviewer, data on research scope, authorship contributions, number of citations, and global research trends are evaluated and mapped. The results show that the publishing of nanoparticles has an exponential trend, with 125 nano-pesticide documents. However, only 14 nano-biopesticide documents are available. India is the most productive country, publishing both nano-pesticides and biopesticides articles, 52 and 9 publications. India connects the Australian and European continents regarding nano-pesticide publications. China is next, with 36 articles about nano-pesticides currently published. Al-Whaibi (average of 86 citations) and Iavicoli have extremely high citation counts (average of 125.5 citations). In synthesizing nano-biopesticide formulations, we found that essential oils are the most common ingredient in nano-biopesticides. In future, the topic related to the impact of nano-biopesticides on crop production and resistance; the combination of nano-biopesticides and nano-fertilizers; the study of nano-biopesticides' effects on the environment; and microbial as nano-biopesticides are some trend in the nano-biopesticide formulation. We predict that research on nano-biopesticides will increase rapidly in the context of eco-friendly issues. Finally, this paper can serve as a basis for the upcoming research on nano-biopesticide formulations, particularly those involving microorganisms as bioactive substances. [ABSTRACT FROM AUTHOR]

In recent years, the human population has reached its peak in both the developing countries and developed countries like India and China. An increase in personnel density ended up being a hard task to maintain or manage people flow in socio-public places. However, people flow management is out of control for humans, which may also cause some safety damages. This paper aims to give an optimal solution for people flow with the help of machine learning, deep learning, and also AI-cameras are used for counting the number of people entering and leaving a user-defined place. Here, also the centroid tracking and centroid detecting algorithms are used to count the number of people together with their direction. This technique helps to replace manual security,in-store traffic management, and much more. [ABSTRACT FROM AUTHOR]

In recent years, the production and the export rate of tea has shown a non-convincing result when compared to other leading tea producing nations like China. China is still the leading tea producing country and for India to compete, the production rate and export rate must be improved. Tea produced in India are one of the finest across the globe and it is because of climate, the way of maintaining tea gardens and also the importance given by people towards tea farming although can be improved by large. An attempt by factor analysis is done to prioritize the factors and focus on those top prioritized factors namely material processing of tea for improving export rates and achieving sustainable productivity. This research paper focuses on this problem by collecting and analysing the sustainability factors in tea material processing using COPRAS and WASPAS tool. [ABSTRACT FROM AUTHOR]

The major problem, nowadays is the novel coronavirus or covid-19 pandemic which has and still infecting people and causing the death of many around the world. Although strict and severe actions have been taken by the government of all over the world to control and minimize the spread of this virus by lockdown, suspending, all travel and sport activity, economic and social activity, quarantines, travel restriction at stations and airport, etc, many of the people around the world have lost their lives and many are suffering. Recently, a conducted study has reported that in China the number of cases that were not documented is 79% as they show no symptom of the virus. In many other countries, the real representation of the patient infected by the virus was different from the real number which was higher in number. Hence, patients with asymptomatic conditions are the major reason for the fast and large covid-19 spread and are also the major reason that caused the people too afraid of the situation. To contribute this global pandemic, in this paper, we propose an investigation which is IoT based system designed to detect both symptomatic-asymptomatic infected people, undocumented, and the place of the pandemic. The aim is to make the authority and people aware of the situation by providing the total numbers of the cases registered, totally recovered, and death of the people caused by the pandemic. In the proposed system, we have used the IoT (internet of things) technology with the NODEMCU-ESP8266, LCD, and Wi- Fi connection to provide information of the important numbers of the patients of covid: cases, recovery, and death of the people in India. This system may keep people more informative, protected, and aware of the danger of the virus so they can take care of themselves and their families in every possible way. [ABSTRACT FROM AUTHOR]

Nobody on this planet is going to be untouched by the impacts of climate change. The ability to cope with climate change varies from region to region, resulting the difference among its effects on fragility. In this paper, we focus on figuring out how the climate change influences the state’s fragility. First, we build Multilevel Fuzzy Mathematic Appraisement Model to assess the grade of the fragility. Then we identify the climate change as an indirect indicator through studying and discussing. Furthermore, after conducting Multiple Linear Regression Models between quantified climate index and twelve factors, we select the indicators that is relevant to climate change to measure the effect of climate change. Then, apply our model to the countries we choose--Sudan and India. We figure out climate change will increase the fragility index by affecting the economy, brain drain and state legitimacy of Sudan, then we quantize the growth by the multiple liner regression equation. For India, we find that when the temperature raise 1.6°C or the fragility index reach 90, India will become fragile. Then we predict by Back-Propagation neural network, finding that it is hard for India to be fragile within 100 years. Additionally, we apply our model to China, finding that its fragility index decreased with its intervention by decreasing most indicator index. Besides, we measure the total cost of intervention by Markal―Macro Model, getting that the total cost takes up 4% of GDP. Finally, because the indicators affecting the fragility of the cities is different from these affecting states, we modified it by altering the indicators we considered to apply in a small “state”, so it could be effective for cities to reflect the climate change impact on fragility. [ABSTRACT FROM AUTHOR]