AN ANALYSIS OF GROWTH AND PERFORMANCE OF KARNATAKA STATE COOPERATIVE AGRICULTURAL AND RURAL DEVELOPMENT BANK IN KARNATAKA

Primary Agricultural Cooperative and Rural Development Banks are playing an important role in meeting the credit requirements of the rural population. The main activity of the Bank is the dispensation of long-term credit for agricultural and rural development under schematic lending approved by NABARD Bank. The lending programs are for productive purposes like integrated loans for agriculture and allied agricultural purposes under major and medium-term projects. The present study was carried out with a broad objective to examine the performance of the Karnataka State Cooperative Agriculture and Rural Development Bank (KSCARD Bank). The study has made use of secondary data (2010- 11 to 2019-20) and the analysis is carried out by using the exponential growth model which has been used to analyze the performance of KSCARD Bank. Finally, it is concluded that the lending performance has very crucial role in Long Term Credit requirements, but the status of the recovery balance of KSCARD bank is very high when compared to the demand and collection of the recovery

Growth and trend analysis of area, production and yield of rice: A scenario of rice security in Bangladesh

Bangladesh positioned as third rice producing country in the world. In Bangladesh, regional growth and trend in rice production determinants, disparities and similarities of rice production environments are highly desirable. In this study, the secondary time series data of area, production, and yield of rice from 1969–70 to 2019–20 were used to investigate the growth and trend by periodic, regional, seasonal and total basis. Quality checking, trend fitting, and classification analysis were performed by the Durbin-Watson test, Exponential growth model, Cochrane-Orcutt iteration method and clustering method. The production contribution to the national rice production of Boro rice is increasing at 0.97% per year, where Aus and Aman season production contribution significantly decreased by 0.48% and 0.49% per year. Among the regions, Mymensingh, Rangpur, Bogura, Jashore, Rajshahi, and Chattogram contributed the most i.e., 13.9%, 9.8%, 8.6%, 8.6%, 8.2%, and 8.0%, respectively. Nationally, the area of Aus and Aman had a decreasing trend with a -3.63% and -0.16% per year, respectively. But, in the recent period (Period III) increasing trend was observed in the most regions. The Boro cultivation area is increasing with a rate of 3.57% per year during 1984–85 to 2019–20. High yielding variety adoption rate has increased over the period and in recent years it has found 72% for Aus, 73.5% for Aman, and 98.4% for Boro season. As a result, the yield of the Aus, Aman, and Boro seasons has been found increasing growth for most of the regions. We have identified different cluster regions in different seasons, indicating high dissimilarities among the rice production regions in Bangladesh. The region-wise actionable plan should be taken to rapidly adopt new varieties, management technologies and extension activities in lower contributor regions to improve productivity. Cluster-wise, policy strategies should be implemented for top and less contributor regions to ensure rice security of Bangladesh.

Predicting Medical Fees for Hospitalized Inpatients and the Determination of Inflection Point

Background: Taiwan’s Bureau of National Health Insurance (BNHI) implemented an inpatient DRG payment system scheduled for January 2008. Many hospital managers urgently invent initiatives to decrease the impacts of DRGs. Predicting medical fees for hospitalized inpatients every day and the corresponding inflection points (IPs) are required for investigations. The aims of this study include (1) verifying the efficacy of the exponential growth model on accumulative publications of mobile health research between 1997 and 2016 in the literature; (2) building the model of predicting medical fees for hospitalized inpatients and determining the inflection points; and (3) demonstrating visualizations of the prediction model online in use for hospital physicians.Methods: An exponential growth model was applied to determine the IP and predict the medical fees to help physicians contain the medical fees of a specific patient during hospitalization. The IP is equal to the item difficulty proven using the differential equation in calculus. An online visual display of the medically contained and predicted inpatient hospitalization was demonstrated in this study.Results: We observed (1) a model accuracy (R2 = 0.99) higher than that (R2 = 0.98) in the literature based on identical data; (2) 231 samples of medical fees for inpatients in the study module with a length of days between 6 and 20 and an IPS falling in the range between 1 and 10 (Q1=0.98, Q3=1.00); and (3) online visualization demonstration of medical fees predicted for hospital inpatients and IP determination on ogive curves.Conclusion: The exponential growth model can be applied to a clinical setting to help physicians consecutively predict medical fees for hospitalized inpatients and upgrade the level of hospital management in the future.

Controlled Release Study on Bifidocin A from a Polyvinyl Alcohol/Chitosan Blend Particle-Based Biodegradable and Active Packaging Coupled with Mechanistic Assessment and Experimental Modeling

On the basis of PVA-CS, which is incorporated with Bifidocin A, anti-microbial biodegradable films were prepared, characterized by their abilities to control the Bifidocin A’s total release rate into foods as needed for packaging of active foods. This study aimed to explore the anti-microbial effects and release kinetics of active substances in polyvinyl alcoholchitosan (PVA-CS) particle composite films added with Bifidocin A. Pseudomonas fluorescens was used as indicator bacteria to evaluate the anti-microbial activity of the films. Fick’s law, power law and negative exponential growth model were applied to further study the release kinetics of Bifidocin A. The results revealed that the composite films of PVA and CS had better mechanical properties and anti-microbial activity when the content of Bifidocin A was 50% with 1:1 PVA/CS, but it impairs the structure of the film, which can be resolved by including a suitable amount of grycerol. The anti-microbial was released faster at higher temperature and concentration of Bifidocin A, and the diffusion coeffcients increased significantlywith the increase of temperature and concentration. According to the thermodynamic parameters, the release of Bifidocin A was endothermic and spontaneous. High correlation factors (R2 > 0.99) were acquired by fitting the release data of the Bifidocin A with the negative exponential growth model. The potential of Bifidocin A to deliver from the films into the food analog appropriately at low temperatures favored the obtained active films to be applied on food packaging, especially suitable for refrigerated foods.

Forecasting Model for the Value of Areca Nut’s Export of Thailand

Having accurate information about the agricultural situation is very important. The predicting trends of agricultural product will allow to make right decision in economy nowadays. The aims of the paper are to demonstrate the trend in areca nut export in Thailand and import in India to specific period and to plan our strategy and policies accordingly to promote areca nut production and export. With this meaning, a study on areca nut export in Thailand and import and production in India from 2013 to 2020 was conducted. The result found that Exponential Growth Model is the most effective for forecasting in the export and import volume of areca nut. The data also was illustrated the trends in 5 years from 2021- 2025. The result revealed that the forecasting trend of export volume of areca nut in Thailand for 2021 – 2025 is linearly decreasing from 3.47610MTs in 2020 to 0.450858MTs in 2025. While, the forecasting trend of import volume of areca nut in India for 2021 – 2025 is linear increasing gradually, from35.5783 MTs in 2020 to 37.2886 MTs in 2025. Areca nut should be considered as an economics crop significantly of Thailand in future for export of Thailand because there are needs in the international market and price still be reasonable. Driving and implementing sustainable agriculture should focus on efficiency and effectiveness truly.

Analysis of Primary Energy Consumption in the United States

This article examines the overall trend in primary energy consumption from 1635 to 2020 in the United States. Based on the exponential growth model, the annual energy consumption average growth rate and the process characteristic time are determined. The anamorphosis method is used to search for the logistic model parameters. Long-term trends analysis and the corresponding time series fluctuations are carried out. For the fluctuations' analysis, the trend component is preliminarily excluded based on the proportions theory. Near-period values are determined using shift and autocorrelation functions. To predict further energy consumption dynamics, the ARIMA autoregressive model is used, on which basis a local increase in the annual energy consumption level to 97.66 quads Btu is expected by 2025. The US energy consumption dynamics by resource type is considered. A forecast up to 2025 for the primary energy resources consumption shares in their total volume is built on an autoregressive model basis

Estimating COVID-19 cases infected with the variant alpha (VOC 202012/01): an analysis of screening data in Tokyo, January-March 2021

Background In Japan, a part of confirmed patients’ samples have been screened for the variant of concern (VOC), including the variant alpha with N501Y mutation. The present study aimed to estimate the actual number of cases with variant alpha and reconstruct the epidemiological dynamics. Methods The number of cases with variant alpha out of all PCR confirmed cases was estimated, employing a hypergeometric distribution. An exponential growth model was fitted to the growth data of variant alpha cases over fourteen weeks in Tokyo. Results The weekly incidence with variant alpha from 18–24 January 2021 was estimated at 4.2 (95% confidence interval (CI): 0.7, 44.0) cases. The expected incidence in early May ranged from 420–1120 cases per week, and the reproduction number of variant alpha was on the order of 1.5 even under the restriction of contact from January-March, 2021, Tokyo. Conclusions The variant alpha was predicted to swiftly dominate COVID-19 cases in Tokyo, and this has actually occurred by May 2021. Devising the proposed method, any country or location can interpret the virological sampling data.

Models for Predicting Global Plastic Waste

For more than half a century, plastic prod-ucts have been a part of people’s lives. When plastic waste is thrown into nature, it can cause a sequence of dangerous effects. Previous researchers esti-mated that global plastic waste in 2020 will be more than 400 million tons. To reduce plastic waste, they built scientific models to analyze the sources of plas-tic and provided solutions for regenerating these plastic wastes. However, their models are static and inaccurate, which may cause some false predictions.In this paper, we first observe the distribution of the real-world plastic waste data. Then, we build simple exponential growth model and logistics model to match these data. By testing different models on our plots, we discover that the SELF-ADAPTIVE MODEL is the best to describe and correctly predict our future plastic waste production, as this model combines the benefits of SIMPLE EXPONENTIAL GROWTH MODEL and the LOGISTIC MODEL. The self-Adaptive model has the potential to minimize the error rate and make the predictions more accurate. Based on this model, we can develop more accurate and informative solu-tions for the real-world plastic problems.