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"Rao, S. S"
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The finite element method in engineering
The Finite Element Method in Engineering is the only book to provide a broad overview of the underlying principles of finite element analysis and where it fits into the larger context of other mathematically based engineering analytical tools. This is an updated and improved version of a finite element text long noted for its practical applications approach, its readability, and ease of use. Students will find in this textbook a thorough grounding of the mathematical principles underlying the popular, analytical methods for setting up a finite element solution based on mathematical equations. The book provides a host of real-world applications of finite element analysis, from structural design to problems in fluid mechanics and thermodynamics. It has added new sections on the assemblage of element equations, as well as an important new comparison between finite element analysis and other analytical methods showing advantages and disadvantages of each. This book will appeal to students in mechanical, structural, electrical, environmental and biomedical engineering.
eBook
Leading and managing in the social sector : strategies for advancing human dignity and social justice
\"This book explores leadership and management in social sector organizations, which include, NGOs, non-profits, social enterprises, social businesses, and cross-sector collaborations focusing on advancing human dignity and social justice. It provides social sector leaders with an overview of current trends, issues, and challenges in the field as well as best practices to foster effective programs, sustain organizations and meet the growing demands of the sector. The enclosed chapters cover topics such as cross-sector organizational design, innovation for client services, gender management dynamics, policy advocacy, and the growing social entrepreneurship movement.\"--Publisher's website.
Book
Precipitation climatology over India: validation with observations and reanalysis datasets and spatial trends
Changing rainfall patterns have significant effect on water resources, agriculture output in many countries, especially the country like India where the economy depends on rain-fed agriculture. Rainfall over India has large spatial as well as temporal variability. To understand the variability in rainfall, spatial–temporal analyses of rainfall have been studied by using 107 (1901–2007) years of daily gridded India Meteorological Department (IMD) rainfall datasets. Further, the validation of IMD precipitation data is carried out with different observational and different reanalysis datasets during the period from 1989 to 2007. The Global Precipitation Climatology Project data shows similar features as that of IMD with high degree of comparison, whereas Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation data show similar features but with large differences, especially over northwest, west coast and western Himalayas. Spatially, large deviation is observed in the interior peninsula during the monsoon season with National Aeronautics Space Administration-Modern Era Retrospective-analysis for Research and Applications (NASA-MERRA), pre-monsoon with Japanese 25 years Re Analysis (JRA-25), and post-monsoon with climate forecast system reanalysis (CFSR) reanalysis datasets. Among the reanalysis datasets, European Centre for Medium-Range Weather Forecasts Interim Re-Analysis (ERA-Interim) shows good comparison followed by CFSR, NASA-MERRA, and JRA-25. Further, for the first time, with high resolution and long-term IMD data, the spatial distribution of trends is estimated using robust regression analysis technique on the annual and seasonal rainfall data with respect to different regions of India. Significant positive and negative trends are noticed in the whole time series of data during the monsoon season. The northeast and west coast of the Indian region shows significant positive trends and negative trends over western Himalayas and north central Indian region.
Journal Article
Psychological impact of COVID-19 lockdown: An online survey from India
Background: The COVID-19 pandemic has led to a complete shut-down of the entire world and almost all the countries are presently in a \"lockdown\" mode. While the lockdown strategy is an essential step to curb the exponential rise of COVID-19 cases, the impact of the same on mental health is not well known.
Aim: This study aimed to evaluate the psychological impact of lockdown due to COVID-19 pandemic on the general public with an objective to assess the prevalence of depression, anxiety, perceived stress, well-being, and other psychological issues.
Materials and Methods: It was an online survey conducted under the aegis of the Indian Psychiatry Society. Using the Survey Monkey platform, a survey link was circulated using the Whatsapp. The survey questionnaire included perceived stress scale, Patient Health Questionnaire-9, Generalized Anxiety Disorder-7, Warwick-Edinburgh Mental Well-being Scale to assess perceived stress, anxiety, depression, and mental well-being, respectively. The survey link was circulated starting from April 6, 2020 and was closed on April 24, 2020.
Results: During the survey, a total of 1871 responses were collected, of which 1685 (90.05%) responses were analyzed. About two-fifth (38.2%) had anxiety and 10.5% of the participants had depression. Overall, 40.5% of the participants had either anxiety or depression. Moderate level of stress was reported by about three-fourth (74.1%) of the participants and 71.7% reported poor well-being.
Conclusions: The present survey suggests that more than two-fifths of the people are experiencing common mental disorders, due to lockdown and the prevailing COVID-19 pandemic. This finding suggests that there is a need for expanding mental health services to everyone in the society during this pandemic situation.
Journal Article
ACG Clinical Guideline: Small Intestinal Bacterial Overgrowth
Small intestinal bacterial overgrowth is defined as the presence of excessive numbers of bacteria in the small bowel, causing gastrointestinal symptoms. This guideline statement evaluates criteria for diagnosis, defines the optimal methods for diagnostic testing, and summarizes treatment options for small intestinal bacterial overgrowth. This guideline provides an evidence-based evaluation of the literature through the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) process. In instances where the available evidence was not appropriate for a formal GRADE recommendation, key concepts were developed using expert consensus.
Journal Article
Identification of COVID-19 can be quicker through artificial intelligence framework using a mobile phone–based survey when cities and towns are under quarantine
We propose the use of a machine learning algorithm to improve possible COVID-19 case identification more quickly using a mobile phone–based web survey. This method could reduce the spread of the virus in susceptible populations under quarantine.
Journal Article
A comparison of the diagnostic ability of vessel density and structural measurements of optical coherence tomography in primary open angle glaucoma
To compare the diagnostic abilities of vessel density measurements of the optic nerve head (ONH), peripapillary and macular regions on optical coherence tomography (OCT) angiography in eyes with primary open angle glaucoma (POAG) with that of the ONH rim area, peripapillary retinal nerve fiber layer (RNFL) thickness and the macular ganglion cell complex (GCC) thickness measurements.
In a cross sectional study, 78 eyes of 50 control subjects and 117 eyes of 67 POAG patients underwent vessel density and structural measurements with spectral domain OCT. POAG was diagnosed based on the masked evaluation of optic disc stereo photographs. Area under receiver operating characteristic curves (AUC) and sensitivities at fixed specificities of vessel densities in ONH, peripapillary and macular regions were compared with rim area, RNFL and GCC thickness.
The AUC (sensitivity at 95% specificity) of average vessel densities within the ONH, peripapillary and macular region were 0.77 (31%), 0.85 (56%) and 0.70 (18%) respectively. The same of ONH rim area, average RNFL and GCC thickness were 0.94 (83%), 0.95 (72%) and 0.93 (62%) respectively. AUCs of vessel densities were significantly lower (p<0.05) than that of the corresponding structural measurements. Pre-treatment IOP (coefficient: 0.08) affected (p<0.05) the AUC of ONH vessel density but not of any other vessel density or structural measurements.
Diagnostic abilities of ONH, peripapillary and the macular vessel densities in POAG were significantly lower than ONH rim area, peripapillary RNFL and macular GCC measurements respectively. At fixed levels of glaucoma severity, the diagnostic ability of the ONH vessel density was significantly greater in eyes with higher pre-treatment IOP.
Journal Article
Shot-noise limited, supercontinuum-based optical coherence tomography
We present the first demonstration of shot-noise limited supercontinuum-based spectral domain optical coherence tomography (SD-OCT) with an axial resolution of 5.9 μm at a center wavelength of 1370 nm. Current supercontinuum-based SD-OCT systems cannot be operated in the shot-noise limited detection regime because of severe pulse-to-pulse relative intensity noise of the supercontinuum source. To overcome this disadvantage, we have developed a low-noise supercontinuum source based on an all-normal dispersion (ANDi) fiber, pumped by a femtosecond laser. The noise performance of our 90 MHz ANDi fiber-based supercontinuum source is compared to that of two commercial sources operating at 80 and 320 MHz repetition rate. We show that the low-noise of the ANDi fiber-based supercontinuum source improves the OCT images significantly in terms of both higher contrast, better sensitivity, and improved penetration. From SD-OCT imaging of skin, retina, and multilayer stacks we conclude that supercontinuum-based SD-OCT can enter the domain of shot-noise limited detection.
Journal Article
Global and regional trends of atmospheric sulfur
The profound changes in global SO2 emissions over the last decades have affected atmospheric composition on a regional and global scale with large impact on air quality, atmospheric deposition and the radiative forcing of sulfate aerosols. Reproduction of historical atmospheric pollution levels based on global aerosol models and emission changes is crucial to prove that such models are able to predict future scenarios. Here, we analyze consistency of trends in observations of sulfur components in air and precipitation from major regional networks and estimates from six different global aerosol models from 1990 until 2015. There are large interregional differences in the sulfur trends consistently captured by the models and observations, especially for North America and Europe. Europe had the largest reductions in sulfur emissions in the first part of the period while the highest reduction came later in North America and East Asia. The uncertainties in both the emissions and the representativity of the observations are larger in Asia. However, emissions from East Asia clearly increased from 2000 to 2005 followed by a decrease, while in India a steady increase over the whole period has been observed and modelled. The agreement between a bottom-up approach, which uses emissions and process-based chemical transport models, with independent observations gives an improved confidence in the understanding of the atmospheric sulfur budget.
Journal Article