Assessing The Vulnerability Index Of Covid-19 Pandemic In India

The coronavirus (COVID-19) outbreak has created havoc all across the States and Union Territories (UTs) of India since its beginning on 30th January 2020. As of 1st January 2021, India has recorded 10,305,788 cases and 149,218 deaths from this deadly pandemic. It has been observed through the data; across states and UTs, the trend and pattern of this disease are not similar at all. There are many reasons for these dissimilarities which are categorized into indicators to assess the vulnerability in this study. We have examined vulnerabilities in 28 states and 8 UTs of India. Livelihood Vulnerability Index (LVI) has been applied with certain modifications to calculate the Vulnerability Index (VI). The figure resulting from the vulnerability assessment corresponds that the factors involved in the three-section exposure, sensitivity, and adaptive capacity had a significant impact on deciding the vulnerability of the population. The result identified the states and UTs which are more vulnerable and need more attention from the government and policymakers. The proposed method of study is unique in its sense as vulnerability index calculation is purely based on a secondary source of data and therefore has an expectation of a higher degree of practical application.

Incorporating Setup Effects into the Reliability Analysis of Driven Piles

Driven-pile setup is referred to a phenomenon in which the bearing capacity of driven piles increases with time after the end of driving (EOD). The setup effect can significantly improve the bearing capacity (ultimate resistance) of driven piles after initial installation, especially the ultimate shaft resistance. Based on the reliability theory and considering the setup effects of driven piles, this article presents an increase factor (Msetup) for the ultimate resistance of driven piles to modify the reliability index calculation formula. At the same time, the correlation between R0 and Rsetup is comprehensively considered in the reliability index calculation. Next, the uncertainty analysis of load and resistance is conducted to determine the ranges of relevant parameters. Meanwhile, the influence of four critical parameters (factor of safety FOS, the ratio of dead load to live load ρ = QD/QL, Msetup, the correlation coefficient between R0 and Rsetup, and ρR0,Rsetup) on reliability index are analyzed. This parametric study indicates that ρ has a slight influence on the reliability index. However, the reliability index is significantly influenced by FOS, Msetup, and ρR0,Rsetup. Finally, by comparisons with the existing results, it is concluded that the formula proposed in this study is reasonable, and more uncertainties are considered to make the calculated reliability index closer to a practical engineering application. The presented formula clearly expresses the incorporation of the pile setup effect into reliability index calculation, and it is conducive to improving the prediction accuracy of the design capacity of driven piles. Therefore, the reliability analysis of driven piles considering setup effects will present a theoretical basis for the application of driven piles in engineering practice.

A Methodology for CO2 Retrieval Applied to Hyperspectral PRISMA Data

The aim of this work is to develop and test a simple methodology for CO2 emission retrieval applied to hyperspectral PRISMA data. Model simulations are used to infer the best SWIR channels for CO2 retrieval purposes, the weight coefficients for a Continuum Interpolated Band Ratio (CIBR) index calculation, and the factor for converting the CIBR values to XCO2 (ppm) estimations above the background. This method has been applied to two test cases relating to the LUSI volcanic area (Indonesia) and the Solfatara area in the caldera of Campi Flegrei (Italy). The results show the capability of the method to detect and estimate CO2 emissions at a local spatial scale and the potential of PRISMA acquisitions for gas retrieval. The limits of the method are also evaluated and discussed, indicating a satisfactory application for medium/strong emissions and over soils with a reflectance greater than 0.1.

Strengthening Pancasila Characters Through The Role Of Mosque Youth Organizations: A Mixed Method Study

The human character of Pancasila which is based on faith in God. This research aims to identify the nationalist character produced through the Leadership Camp program, measure the level of nationalism character education, and analyze the strategies carried out by the mosque youth organizations at the Al Azhar Youth Leadership Institute in strengthening the nationalist character of youth. The quantitative method with the type of survey to 100 respondents uses EFA and the nationalism character education index. According to students in the Leadership Training, the nationalist leadership they get is integrity, cooperation, character, nationalism, devotion to worship, and independence. Religious nature consists of morals and obedience to worship. The nationalist Character Education index calculation is 92.51%, which means that the program classifies as a high portion of the nationalism character education learning. The best strategy that AYLI can choose is consistency with a program that is already running well.

Monitoring Meteorological Drought in Southern China Using Remote Sensing Data

Severe meteorological drought is generally considered to lead to crop damage and loss. In this study, we created a new standard value by averaging the values distributed in the middle 30–70% instead of the traditional mean value, and we proposed a new index calculation method named Normalized Indices (NI) for meteorological drought monitoring after normalized processing. The TRMM-derived precipitation data, GLDAS-derived soil moisture data, and MODIS-derived vegetation condition data from 2003 to 2019 were used, and we compared the NI with commonly used Condition Indices (CI) and Anomalies Percentage (AP). Taking the mid-to-lower reaches of the Yangtze River (MLRYR) as an example, the drought monitoring results for paddy rice and winter wheat showed that (1) NI can monitor well the relative changes in real precipitation/soil moisture/vegetation conditions in both arid and humid regions, while meteorological drought was overestimated with CI and AP, and (2) due to the monitoring results of NI, the well-known drought event that occurred in the MLRYR from August to October 2019 had a much less severe impact on vegetation than expected. In contrast, precipitation deficiency induced an increase in sunshine and adequate heat resources, which improved crop growth in 78.8% of the area. This study discusses some restrictions of CI and AP and suggests that the new NI index calculation provides better meteorological drought monitoring in the MLRYR, thus offering a new approach for future drought monitoring studies.

Oxygen Desaturation Index calculation: impact of different methodologies

Obstructive Sleep Apnea (OSA) is a syndrome characterized by episodes of airway obstruction, which causes oxygen desaturation events. These events can be identified by oximetry analysis and are used as one of the parameters to diagnose OSA. However, desaturation events have an inaccurate definition in manuals and in most of the literature. Thus, this work aims to evaluate whether different methodologies for the calculation of desaturation events impact the Oxygen Desaturation Index (ODI) and the diagnosis of OSA. The results indicated that the ODI values are significantly different from each other (p <0.001) and the methodologies provided variable performance for the diagnosis of OSA.