Diabetes, A Global Epidemic

The International Diabetes Federation notes that diabetes is a global epidemic affecting approximately 537 million adults (20-79 years) worldwide. The total number of people living with diabetes is projected to rise to 643 million by 2030 and 783 million by 2045. In the United States, 37.3 million people (about 1 in 10) have diabetes, and the incidence is 1.4 million every year. 38.0% (96 million) aged 18 and above have prediabetes (National diabetes statistics report, 01/2020). More than 8 in 10 do not know they have prediabetes (About Prediabetes and Type 2 Diabetes | National Diabetes Prevention Program | Diabetes | CDC, 2022). The estimated cost of care in 2012 was $240 billion, which increased to$327 billion in 2017 (Economic Costs of Diabetes in the U.S. in 2017 | Diabetes Care | American Diabetes Association, n.d.). It has been the seventh leading cause of death in the U.S. since 2019 (Statistics About Diabetes / ADA, n. d.). Epidemiological research to assess the effect of lifestyle modification on the development of T2DM produced evidence that a structured lifestyle modification program can cut the risk of developing T2DM by 58% for people under 60 and 71% for people over 60 years old (CDC - About the Program - National Diabetes Prevention Program - (Diabetes DDT, 2021). Lifestyle intervention is a safe, cost-effective, and efficacious way of diabetes prevention (Glechner et al., 2018). It is recommended that early screening of patients with prediabetes that exhibit risk for T2DM and implementing lifestyle modifications or referral to the National Diabetes Prevention Program will help address this public health issue. More training and an increased workforce are needed to open conversation in T2DM prevention strategies

Studies on some speciality Cardo Polymers

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ECALTOOL: fuzzy logic based computer program to calibrate the Hargreaves equation for accurate estimation of evapotranspiration

A reference evapotranspiration rate (ET0) is vital information for irrigation scheduling as well as plant growth modeling.  Estimation of evapotranspiration using environmental variables is a convenient approach compare to direct measurement.  Several mathematical models have been proposed for the estimation of ET0.  Among all these, the Hargreaves equation has received maximum attention of the agricultural fraternity as it needs minimum weather data.  However, requirement of minimal weather data in the Hargreaves equation makes it a simple and pragmatic model for estimation of ET0.  The minimalist approach makes the equation incapable to estimate ET0 accurately under extreme weather conditions.  The calibration or adjustment of the Hargreaves equation parameter CH and EH for different climate conditions is well accepted approach to accomplish error free estimation from the equation.  The establish calibration methods are empirical and time consuming.  Further, the results obtained by these methods are valid only for the restricted area and season only.  This paper presents Evapotranspiration CALibration TOOL (ECALTOOL), which is a fuzzy based universal computer program developed on the platform of NI LabVIEW to calibrate CH and EH.  The key features of the tool are its ability to provide calibration of ET0 for 1100 locations of 190 countries, and its user friendliness.  The performance of the tool is compared and validated against the benchmark Penman-Monteith equation as well as the experimentally calibrated values for various locations with diverse climate conditions.  Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) is in the range of 0.4856 – 1.1562 and 1.21%– 2.06% respectively.  The calibrated values of CH and EH are proved to be accurate in comparison with experimentally carried out calibration.  The developed tool eliminates the need of location specific experimental calibration process for the Hargreaves equation.Keywords: evapotranspiration, fuzzy logic, Hargreaves equation, LabVIE

Localization Algorithm for Mobile Sensor Nodes Using 3D Space in Wireless Sensor Network

On the problem of wireless sensor network localization; few true three - dimensional (3D) methods have been developed to satisfy the practical needs. In this work we proposed range - based 3D localization algorithm that is accurate, anchor - free, scalable and physical position available. A novel combination of distance and direction measurement techniques introduced to estimate ranges between neighbours. Based on this information local coordinate systems are constructed and then converge to form a global network wide coordinate system ,which finally leads to nodes absolute positions. Simulation results have shown that our algorithm achieves good trade - off between localization percentage and precision

A CommonKADS Model Framework for Web Based Agricultural Decision Support System

Increased demand of farm products and depletion of natural resources compel the agriculture community to increase the use of Information and Communication Technology (ICT) in various farming processes. Agricultural Decision Support Systems (DSS) proved useful in this regard. The majority of available Agricultural DSSs are either crop or task specific. Less emphasis has been placed on the development of comprehensive DSS, which are non-specific regarding crops or farming processes. The crop or task specific DSSs are mainly developed with rule based or knowledge transfer based approaches. The DSSs based on these methodologies lack the ability for scaling up and generalization. The Knowledge engineering modeling approach is more suitable for the development of large and generalized DSS. Unfortunately the model based knowledge engineering approach is not much exploited for the development of Agricultural DSS. CommonKADS is one of the popular modeling frameworks used for the development of Knowledge Based System (KBS). The paper presents the organization, agent, task, communication, knowledge and design models based on the CommonKADS approach for the development of scalable Agricultural DSS. A specific web based DSS application is used for demonstrating the multi agent CommonKADS modeling approach. The system offers decision support for irrigation scheduling and weather based disease forecasting for the popular crops of India. The proposed framework along with the required expert knowledge, provides a platform on which the larger DSS can be built for any crop at a given location

Evaluation of Shear Wall-RC Frame Interaction of High-Rise Buildings using 2-D model Approach

The usefulness of structural walls in the framing of buildings has long been recognized. It is generally preferred to use shear wall in combination with moment resisting frame. In the present study, an effort is also made to investigate the shear wall-RC frame interaction using 2-D modeling of 20, 30 and 35 storey RC frame building with shear wall. In equivalent simplified 2-D model, two exterior frames with shear wall modeled as single frame with double stiffness, strength and weight. The interior frames without shear wall are modeled as a single frame with equivalent stiffness, strength and weight. The modeled frames are connected with rigid link at each floor level. Using 2-D plane frame model the lateral force distribution between Exterior frame with shear wall and Interior frame without shear wall is investigated. From the analysis, it is observed that up to bottom seven/eight storey more than 50% load is taken by frame with shear wall and the lower most three storeys take about 75% of total storey shear