What impacts have geographical locations on the cases and deaths from COVID-19/SARS-CoV-2 pandemic in 36 states and union territories of India:-observational analysis in India - V2

Background: Curiosity and need are the major forces driving invention and discoveries. The covid-19 pandemic is said to be originated from Wuhan of Hubei province in china. This statement has raised many questions and doubts about origin and spread of disease and the controversy is still going on. The geographical location of Wuhan in relation to sea is of significant value in relation to covid-19 pandemic as observed in this research. The city of Wuhan is located on both banks of the Changjiang (the Great River, a.k.a the Yangtze River) about six hundred miles upstream from Shanghai and the Pacific Ocean. It is about four hundred miles upstream from Nanjing. Its location is supremely strategic, being where the Hanshui (Han River) joins the Changjiang. The Wuhan Huanan Seafood Wholesale Market was in news and highlighted by several media and news agency as probable source of origin of covid-19. The Huanan Seafood Market located in Wuhan is a live animal and seafood market in Jianghan District, Wuhan City, and the capital of Hubei Province in Central China. Objective: This continuous observational research analysis aimed to assess the impact of geographical locations particularly coastal influence on the total/average/maximum/minimum confirmed cases and deaths from COVID-19/SARS-CoV-2 pandemic in 36 states and union territories of India, during COVID-19 pandemic from the beginning of pandemic cases in January 2020 in India with special focus on coastal states and union territories of India. The coast is also known popularly as the coastline or seashore is the area where land meets the sea or ocean, or as a line that forms the boundary between the land and the ocean. The term coastal state and union territories is used to refer to a state where interactions of sea and land of states occur. The study also aims to find safest geographical location in covid-19 pandemic.Methods: This is a novel cross-sectional mixed (quantitative and Qualitative) continuous observational research study. The information on the number of cases and deaths due to COVID-19 pandemic in 36 states and union territories of India is obtained from Health Department, Ministry of Health and Family Welfare (MoHFW), Government of India, and data were matched and analyzed from online websites as well. The impact of geographical locations on the total/average/maximum/minimum confirmed cases and deaths from COVID-19/SARS-CoV-2 pandemic in 36 states and union territories of India was analyzed with Microsoft office and with more data collection stata 15.1 for windows (64bit) will be used when required with Microsoft office in next version-3 of article (for bigger analysis) for epidemiological comparison by calculating incidence, prevalence, mortality rate and other indicators. The study for global correlation of this research is also under process by the author. For the purpose of research India is divided into four geographical areas, 1 Coastal states and union territories (total ten in numbers), 2 Island groups (three in numbers), 3 north eastern states and east area i.e. Laddakh 4 other states and union territories having plain areas (14 in numbers).Results: The findings showed that total numbers of death from covid-19 is highest in coastal states and union territories with a count of 323674 since beginning of the pandemic whereas the islands group reported the lowest total 184 numbers of deaths from covid-19 as on 05 Jan 2022, 08:00 IST (GMT+5:30) . The average death from covid-19 is highest in coastal states and union territories group with a count of 32367.4 followed by other states and union territories group with a count of 10431.21429. The islands group reported the lowest average numbers of death from covid-19 with a count of 61.33. A similar trend was found for numbers of confirmed cases with coastal states on top having largest number of covid-19 cases. In this version 2 the prevalence rates are also calculated per 100000.Conclusions: The research observation found that coastal states and union territories of India have larger number of daily cases of COVID-19 and mortality 867 per 100000 as compared to other geographical locations of the country. The observation also found that islands have least number of cases and deaths 115 per 100000 due to covid-19 pandemic. This study also gives rise to hypothesis that coastal locations are at greater risk of covid-19 infection and mortality whereas islands are safest places in covid-19 pandemics.

What impacts have geographical locations on the cases and deaths from COVID-19/SARS-CoV-2 pandemic in 36 states and union territories of India:-observational analysis in India – V2

Background: Curiosity and need are the major forces driving invention and discoveries. The covid-19 pandemic is said to be originated from Wuhan of Hubei province in china. This statement has raised many questions and doubts about origin and spread of disease and the controversy is still going on. The geographical location of Wuhan in relation to sea is of significant value in relation to covid-19 pandemic as observed in this research. The city of Wuhan is located on both banks of the Changjiang (the Great River, a.k.a the Yangtze River) about six hundred miles upstream from Shanghai and the Pacific Ocean. It is about four hundred miles upstream from Nanjing. Its location is supremely strategic, being where the Hanshui (Han River) joins the Changjiang. The Wuhan Huanan Seafood Wholesale Market was in news and highlighted by several media and news agency as probable source of origin of covid-19. The Huanan Seafood Market located in Wuhan is a live animal and seafood market in Jianghan District, Wuhan City, and the capital of Hubei Province in Central China. Objective: This continuous observational research analysis aimed to assess the impact of geographical locations particularly coastal influence on the total/average/maximum/minimum confirmed cases and deaths from COVID-19/SARS-CoV-2 pandemic in 36 states and union territories of India, during COVID-19 pandemic from the beginning of pandemic cases in January 2020 in India with special focus on coastal states and union territories of India. The coast is also known popularly as the coastline or seashore is the area where land meets the sea or ocean, or as a line that forms the boundary between the land and the ocean. The term coastal state and union territories is used to refer to a state where interactions of sea and land of states occur. The study also aims to find safest geographical location in covid-19 pandemic.Methods: This is a novel cross-sectional mixed (quantitative and Qualitative) continuous observational research study. The information on the number of cases and deaths due to COVID-19 pandemic in 36 states and union territories of India is obtained from Health Department, Ministry of Health and Family Welfare (MoHFW), Government of India, and data were matched and analyzed from online websites as well. The impact of geographical locations on the total/average/maximum/minimum confirmed cases and deaths from COVID-19/SARS-CoV-2 pandemic in 36 states and union territories of India was analyzed with Microsoft office and with more data collection stata 15.1 for windows (64bit) will be used when required with Microsoft office in next version-3 of article (for bigger analysis) for epidemiological comparison by calculating incidence, prevalence, mortality rate and other indicators. The study for global correlation of this research is also under process by the author. For the purpose of research India is divided into four geographical areas, 1 Coastal states and union territories (total ten in numbers), 2 Island groups (three in numbers), 3 north eastern states and east area i.e. Laddakh 4 other states and union territories having plain areas (14 in numbers).Results: The findings showed that total numbers of death from covid-19 is highest in coastal states and union territories with a count of 323674 since beginning of the pandemic whereas the islands group reported the lowest total 184 numbers of deaths from covid-19 as on 05 Jan 2022, 08:00 IST (GMT+5:30) . The average death from covid-19 is highest in coastal states and union territories group with a count of 32367.4 followed by other states and union territories group with a count of 10431.21429. The islands group reported the lowest average numbers of death from covid-19 with a count of 61.33. A similar trend was found for numbers of confirmed cases with coastal states on top having largest number of covid-19 cases. In this version 2 the prevalence rates are also calculated per 100000.Conclusions: The research observation found that coastal states and union territories of India have larger number of daily cases of COVID-19 and mortality 867 per 100000 as compared to other geographical locations of the country. The observation also found that islands have least number of cases and deaths 115 per 100000 due to covid-19 pandemic. This study also gives rise to hypothesis that coastal locations are at greater risk of covid-19 infection and mortality whereas islands are safest places in covid-19 pandemics.Keywords: coastal states, COVID 19, Mortality, confirmed cases, union territories, geographical impact,

What Impacts Have Geographical Locations On The Cases And Deaths From Covid-19/ Sars-Cov-2 Pandemic In 36 States And Union Territories Of India:-Observational Analysis In India

Background: Curiosity and need are the major forces driving invention and discoveries. The covid-19 said to originated from Wuhan of Hubei province in china have raised so many questions and doubts about origin and spread of disease and the controversy is still going on. The geographical location of Wuhan in relation to sea is of significant value in relation to covid-19 pandemic as observed in this research. The city of Wuhan is located on both banks of the Changjiang (the Great River, a.k.a the Yangtze River) about six hundred miles upstream from Shanghai and the Pacific Ocean. It is about four hundred miles upstream from Nanjing. Its location is supremely strategic, being where the Hanshui (Han River) joins the Changjiang. The Wuhan Huanan Seafood Wholesale Market was in news and highlighted by several media and news agency as probable source of origin of covid-19. The Huanan Seafood Market located in Wuhan was a live animal and seafood market in Jianghan District, Wuhan City, and the capital of Hubei Province in Central China. My research aimed to assess the impact of geographical locations particularly coastal influence on the total/average/maximum/minimum confirmed cases and deaths from COVID-19/SARS-CoV-2 pandemic in 36 states and union territories of India, during COVID-19 pandemic from the beginning of pandemic cases in January 2020 in India with special focus on coastal states and union territories of India. The coast is also known popularly as the coastline or seashore is the area where land meets the sea or ocean, or as a line that forms the boundary between the land and the ocean. The term coastal state and union territories is used to refer to a state where interactions of sea and land of states occur. The study also aims to find safest geographical location in covid-19 pandemic. Methods: The information on the number of cases and deaths due to COVID-19 pandemic in 36 states and union territories of India was obtained from Health Department, Ministry of Health and Family Welfare (MoHFW), Government of India, and data were matched and analyzed from online websites as well. The impact of geographical locations on the total/average/maximum/ minimum confirmed cases and deaths from COVID-19/SARS-CoV-2 pandemic in 36 states and union territories of India was analyzed with Microsoft office and stata 15.1 for windows (64bit) will be used with Microsoft office in next version-2 of article for epidemiological comparison by calculating incidence, prevalence, mortality rate and other indicators. The study for global correlation of this research is also under process by the author. For the purpose of research India is divided into four geographical areas, 1 Coastal states and union territories (total ten in numbers), 2 Island groups (three in numbers), 3 north eastern states and east area i.e. Laddakh 4 other states and union territories having plain areas (14 in numbers). Results: The findings showed that total numbers of death from covid-19 is highest in coastal states and union territories with a count of 240628 since beginning of the pandemic whereas the islands group reported the lowest total numbers of death from covid-19. The average death from covid-19 is highest in coastal states and union territories group with a count of 24062.8 followed by other states and union territories group with a count of 9754.07. The islands group reported the lowest average numbers of death from covid-19 with a count of 58.67. A similar trend was found for numbers of confirmed cases with coastal states on top having largest number of covid-19 cases. Conclusions: The research observation found that coastal states and union territories of India have larger number of daily cases of COVID-19 and mortality as compared to other geographical locations of the country. The observation also found that islands have least number of cases and deaths due to covid-19 pandemic. This study also gives rise to hypothesis that coastal locations are at greater risk of covid-19 infection and mortality whereas islands are safe places in covid-19 pandemics.

AWARENESS OF ANEMIA AMONG RURAL PREGNANT WOMEN IN BAGERHAT DISTRICT OF BANGLADESH

Background: Anemia in pregnancyis a decrease in the total red blood cells (RBCs) or hemoglobin in the blood duringpregnancyor in the period following pregnancy. It is the condition of having a lower-than-normal number of red blood cells or quantity of hemoglobin. Anemia diminishes the capacity of the blood to carry oxygen. Patients with anemia may feel tired, fatigue easily, appear pale, develop palpitations, and become shortness of breath. Objectives: The purpose of the present study was to investigate about the awareness of anemia among rural pregnant women in Bagerhat district of Bangladesh Materials and Method: A sample of 29 pregnant women (PW) from a total of listed 111 women from three upazilas of Bagerhat district was considered for assessing the awareness of Anemia. Those three upazilas were taken at random first from the nine upazilas of Bagerhat district.Data on different variables were collected directly from the selected women through a prescribed questionnaire. Descriptive statistics e.g., maximum, minimum, mean, standard deviation, skewness, kurtosis, etc. of the variables together with their standard error of their estimates were considered foranalyzing sample characteristics of the study. The relationship between two nominal variables is assessed by cross tabulation with test statistics Phi and Cramers V. The bootstrapresampling method was used to understand the population parameters. Results: About86% pregnant women have no idea about anemia and also their causes. All respondents feel weakness that indicates they have the symptom of anemia. The phi andcramersV imply that the relationship between heard about anemia and the source of information is highly significant (p= 0.000). Among the awarded women in Bagerhat district, probability of getting awareness from service provider was0.917 and that from relatives was 0.083. Among the population, the probability of contribution of the service provider was0.379. Probability of unknown was 0.586 indicating much populationin Bagerhat district werenot aware about anemia. Probability of getting information of anemia from mother was zero indicating very recently service providers have started their program in Bagerhat district. Conclusion: Probability of getting information of anemia from mother is zero indicating very recently service providers have started their program in Bagerhat district. Therefore, this program should be continued until the probability of getting information from mother will be closed to 1. Recommendation: Government as well as the NGOs should continue & enhance the present awareness program in Bagerhat district.

Sub-soil temperature variation and estimation of soil heat flux at Pune

Utilising experimental data from 23 November to 8.December 1989. temperature and heat storage variations at Pune have been studied, based on 3 hourly observations.. pattern of penetration of .thermal wave within the soil has been examined and time of occurrence of maximum/minimum temperatures discussed for various depths. Temperature ranges in different layers have been theoretically computed and compared with those based on actual observations. Heat balance at various depths has also been presented and discussed.

GPRChinaTemp1km: a high-resolution monthly air temperature dataset for China (1951–2020) based on machine learning

An accurate spatially continuous air temperature dataset is crucial for multiple applications in environmental and ecological sciences. Existing spatial interpolation methods have relatively low accuracy and the resolution of available long-term gridded products of air temperature for China is coarse. Point observations from meteorological stations can provide long-term air temperature data series but cannot represent spatially continuous information. Here, we devised a method for spatial interpolation of air temperature data from meteorological stations based on powerful machine learning tools. First, to determine the optimal method for interpolation of air temperature data, we employed three machine learning models: random forest, support vector machine, and Gaussian process regression. Comparison of the mean absolute error, root mean square error, coefficient of determination, and residuals revealed that Gaussian process regression had high accuracy and clearly outperformed the other two models regarding interpolation of monthly maximum, minimum, and mean air temperatures. The machine learning methods were compared with three traditional methods used frequently for spatial interpolation: inverse distance weighting, ordinary kriging, and ANUSPLIN. Results showed that the Gaussian process regression model had higher accuracy and greater robustness than the traditional methods regarding interpolation of monthly maximum, minimum, and mean air temperatures in each month. Comparison with the TerraClimate, FLDAS, and ERA5 datasets revealed that the accuracy of the temperature data generated using the Gaussian process regression model was higher. Finally, using the Gaussian process regression method, we produced a long-term (January 1951 to December 2020) gridded monthly air temperature dataset with 1 km resolution and high accuracy for China, which we named GPRChinaTemp1km. The dataset consists of three variables: monthly mean air temperature, monthly maximum air temperature, and monthly minimum air temperature. The obtained GPRChinaTemp1km data were used to analyse the spatiotemporal variations of air temperature using Theil–Sen median trend analysis in combination with the Mann–Kendall test. It was found that the monthly mean and minimum air temperatures across China were characterized by a significant trend of increase in each month, whereas monthly maximum air temperature showed a more spatially heterogeneous pattern with significant increase, non-significant increase, and non-significant decrease. The GPRChinaTemp1km dataset is publicly available at https://doi.org/10.5281/zenodo.5112122 (He et al., 2021a) for monthly maximum air temperature, at https://doi.org/10.5281/zenodo.5111989 (He et al., 2021b) for monthly mean air temperature and at https://doi.org/10.5281/zenodo.5112232 (He et al., 2021c) for monthly minimum air temperature.

A NFT verification method for distributed AI system

This paper proposes a method invention, namely an efficient NFT data inspection method with minimum granularity and probability comparison. The invention establishes a fast comparison method of AI model and data, that is, the direct comparison of small files priority and the maximum-minimum interval comparison. The invention takes the substantial identity inside the NFT data and the processing method of NFT data coincidence into account, so that the data content outside the token of the NFT publicly shared by the AI distributed system can also be unique on the Internet. Therefore, it can avoid the problem of incremental packaging and repeated packaging, and can successfully balance the efficiency and security of the comparison process. portions given in this document

Seasonality of confirmed malaria cases from 2008 to 2017 in Togo: a time series analysis by health district and target group

Background This study aimed to assess the seasonality of confirmed malaria cases in Togo and to provide new indicators of malaria seasonality to the National Malaria Control Programme (NMCP). Methods Aggregated data of confirmed malaria cases were collected monthly from 2008 to 2017 by the Togo’s NMCP and stratified by health district and according to three target groups: children < 5 years old, children ≥ 5 years old and adults, and pregnant women. Time series analysis was carried out for each target group and health district. Seasonal decomposition was used to assess the seasonality of confirmed malaria cases. Maximum and minimum seasonal indices, their corresponding months, and the ratio of maximum/minimum seasonal indices reflecting the importance of malaria transmission, were provided by health district and target group. Results From 2008 to 2017, 7,951,757 malaria cases were reported in Togo. Children < 5 years old, children ≥ 5 years old and adults, and pregnant women represented 37.1%, 57.7% and 5.2% of the confirmed malaria cases, respectively. The maximum seasonal indices were observed during or shortly after a rainy season and the minimum seasonal indices during the dry season between January and April in particular. In children < 5 years old, the ratio of maximum/minimum seasonal indices was higher in the north, suggesting a higher seasonal malaria transmission, than in the south of Togo. This is also observed in the other two groups but to a lesser extent. Conclusions This study contributes to a better understanding of malaria seasonality in Togo. The indicators of malaria seasonality could allow for more accurate forecasting in malaria interventions and supply planning throughout the year.

PRODUCTION OF ENZYMES IN PREDOMINANT THERMOPHILIC FUNGI AVAILABLE FROM ORGANIC SUBSTRATES

Present investigation describes that the study site comes under Aurangabad Division Maharashtra and it falls in Deccan Plateau Zone of India. It was collected different types of organic substrates viz. vermiompost, poultary manure, baggase, farm yard manure (FYM), soil, Ash etc. Isolated thermophilic predominant fungi thermophilic fungi viz.Aspergillus niger, Mucor mucedo,Humicola insolens,Trichoderma harzianum,T. viride,Penicillium duponti,Fusarium oxysporun and Chaetomium thermophilum were carried out for the production of enzymes. Isolated predominant thermophilic fungi were evaluated on different types of enzymes. Among tested thermophilic fungi, the highest ativity was observed in C. thermophilium (20mm) followed by T. harzianum (19.50mm) In lipase, M. mucedo (15.40mm) was found maximum followed by F. oxysporun. Cellulase activity was found highest in A. nige (25mm) followed by others. In case of xylanase, catalase, peroxidase and esterase activities were found maximum, minimum and medium even negative in some fungi. Maximum pectinase activity was detected from H. insolens (52.26 @ 0 min) and (74.25 @ 10 min) and in case of M. mucedo, F. oxysporun and C. thermophilium was found most extreme while least in A. niger (30.12) and P. duponti (33.47) @ 0 minute. Key words: Organic Substrates, Thermophilic Fungi, Enzymes