163 research outputs found

    LAND USE/LAND COVER CHANGES IN SEMI-ARID MOUNTAIN LANDSCAPE IN SOUTHERN INDIA: A GEOINFORMATICS BASED MARKOV CHAIN APPROACH

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    Nowadays land use/ land cover in mountain landscape is in critical condition; it leads to high risky and uncertain environments. These areas are facing multiple stresses including degradation of land resources; vagaries of climate and depletion of water resources continuously affect land use practices and livelihoods. To understand the Land use/Land cover (Lu/Lc) changes in a semi-arid mountain landscape, Kallar watershed of Bhavani basin, in southern India has been chosen. Most of the hilly part in the study area covers with forest, plantation, orchards and vegetables and which are highly affected by severe soil erosion, landslide, frequent rainfall failures and associated drought. The foothill regions are mainly utilized for agriculture practices; due to water scarcity and meagre income, the productive agriculture lands are converted into settlement plots and wasteland. Hence, land use/land cover change deduction; a stochastic processed based method is indispensable for future prediction. For identification of land use/land cover, and vegetation changes, Landsat TM, ETM (1995, 2005) and IRS P6- LISS IV (2015) images were used. Through CAMarkov chain analysis, Lu/Lc changes in past three decades (1995, 2005, and 2015) were identified and projected for (2020 and 2025); Normalized Difference Vegetation Index (NDVI) were used to find the vegetation changes. The result shows that, maximum changes occur in the plantation and slight changes found in forest cover in the hilly terrain. In foothill areas, agriculture lands were decreased while wastelands and settlement plots were increased. The outcome of the results helps to farmer and policy makers to draw optimal lands use planning and better management strategies for sustainable development of natural resources

    SPATIO-TEMPORAL ANALYSIS OF NATURAL HUMAN HABITABILITY ENVIRONMENT ALONG THE COASTAL TALUKS OF TAMIL NADU, INDIA

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    In this present world, due to the increasing adverse effect of anthropological activities on the natural environment causes a large scale environmental degradation which directly reduces the suitable natural environment for human habitation. As a consequence, in recent years, human realised the need for a favourable natural environment which is adoptable for habitation. In this present study, some of the following five criterions such as Land Surface Temperature (LST), vegetation coverage, impervious surface, wetness and water condition derived from the remotely sensed data were used to evaluate the Natural Human habitation Environment Suitability Index (NHESI) along the coastal taluks of Tamil Nadu. Landsat-7 (ETM+) images and Landsat-8 (OLI/TIRS) images with a spatial resolution of 30m have been used to derive the evaluation factors of NHESI for the year of 2000 and 2018. Multi Criteria Evaluation (MCE) based Analytical Hierarchical Process (AHP) and fuzzy linear membership has been used in this study to evaluate the weighs and ratings of each criterion and its classes. The best NHESI is seen in 2000 where a total area of about 13902.9 km2 comes under the habitable region, against an area of 7726.9 km2 in 2018. The study area is further classified into moderately habitable, marginally habitable and uninhabitable regions. This study clearly indicates the degradation of the natural environmental conditions for human habitation. This kind of habitability study will help the researchers, decision makers and government agencies in creating awareness and adopting policies in the spatial planning of human land utilization for habitability

    Classification and Regression Tree (CART) analysis to predict influenza in primary care patients

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    Abstract Background The use of neuraminidase-inhibiting anti-viral medication to treat influenza is relatively infrequent. Rapid, cost-effective methods for diagnosing influenza are needed to enable appropriate prescribing. Multi-viral respiratory panels using reverse transcription polymerase chain reaction (PCR) assays to diagnose influenza are accurate but expensive and more time-consuming than low sensitivity rapid influenza tests. Influenza clinical decision algorithms are both rapid and inexpensive, but most are based on regression analyses that do not account for higher order interactions. This study used classification and regression trees (CART) modeling to estimate probabilities of influenza. Methods Eligible enrollees ≥ 5 years old (n = 4,173) who presented at ambulatory centers for treatment of acute respiratory illness (≤7 days) with cough or fever in 2011–2012, provided nasal and pharyngeal swabs for PCR testing for influenza, information on demographics, symptoms, personal characteristics and self-reported influenza vaccination status. Results Antiviral medication was prescribed for just 15 % of those with PCR-confirmed influenza. An algorithm that included fever, cough, and fatigue had sensitivity of 84 %, specificity of 48 %, positive predictive value (PPV) of 23 % and negative predictive value (NPV) of 94 % for the development sample. Conclusions The CART algorithm has good sensitivity and high NPV, but low PPV for identifying influenza among outpatients ≥5 years. Thus, it is good at identifying a group who do not need testing or antivirals and had fair to good predictive performance for influenza. Further testing of the algorithm in other influenza seasons would help to optimize decisions for lab testing or treatment.http://deepblue.lib.umich.edu/bitstream/2027.42/134640/1/12879_2016_Article_1839.pd

    The Impact of HAART on the Respiratory Complications of HIV Infection: Longitudinal Trends in the MACS and WIHS Cohorts

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    Objective: To review the incidence of respiratory conditions and their effect on mortality in HIV-infected and uninfected individuals prior to and during the era of highly active antiretroviral therapy (HAART). Design: Two large observational cohorts of HIV-infected and HIV-uninfected men (Multicenter AIDS Cohort Study [MACS]) and women (Women's Interagency HIV Study [WIHS]), followed since 1984 and 1994, respectively. Methods: Adjusted odds or hazards ratios for incident respiratory infections or non-infectious respiratory diagnoses, respectively, in HIV-infected compared to HIV-uninfected individuals in both the pre-HAART (MACS only) and HAART eras; and adjusted Cox proportional hazard ratios for mortality in HIV-infected persons with lung disease during the HAART era. Results: Compared to HIV-uninfected participants, HIV-infected individuals had more incident respiratory infections both pre-HAART (MACS, odds ratio [adjusted-OR], 2.4; 95% confidence interval [CI], 2.2-2.7; p<0.001) and after HAART availability (MACS, adjusted-OR, 1.5; 95%CI 1.3-1.7; p<0.001; WIHS adjusted-OR, 2.2; 95%CI 1.8-2.7; p<0.001). Chronic obstructive pulmonary disease was more common in MACS HIV-infected vs. HIV-uninfected participants pre-HAART (hazard ratio [adjusted-HR] 2.9; 95%CI, 1.02-8.4; p = 0.046). After HAART availability, non-infectious lung diseases were not significantly more common in HIV-infected participants in either MACS or WIHS participants. HIV-infected participants in the HAART era with respiratory infections had an increased risk of death compared to those without infections (MACS adjusted-HR, 1.5; 95%CI, 1.3-1.7; p<0.001; WIHS adjusted-HR, 1.9; 95%CI, 1.5-2.4; p<0.001). Conclusion: HIV infection remained a significant risk for infectious respiratory diseases after the introduction of HAART, and infectious respiratory diseases were associated with an increased risk of mortality. © 2013 Gingo et al

    TURBOMOLE: Modular program suite for ab initio quantum-chemical and condensed-matter simulations

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    TURBOMOLE is a collaborative, multi-national software development project aiming to provide highly efficient and stable computational tools for quantum chemical simulations of molecules, clusters, periodic systems, and solutions. The TURBOMOLE software suite is optimized for widely available, inexpensive, and resource-efficient hardware such as multi-core workstations and small computer clusters. TURBOMOLE specializes in electronic structure methods with outstanding accuracy–cost ratio, such as density functional theory including local hybrids and the random phase approximation (RPA), GW-Bethe–Salpeter methods, second-order Møller–Plesset theory, and explicitly correlated coupled-cluster methods. TURBOMOLE is based on Gaussian basis sets and has been pivotal for the development of many fast and low-scaling algorithms in the past three decades, such as integral-direct methods, fast multipole methods, the resolution-of-the-identity approximation, imaginary frequency integration, Laplace transform, and pair natural orbital methods. This review focuses on recent additions to TURBOMOLE’s functionality, including excited-state methods, RPA and Green’s function methods, relativistic approaches, high-order molecular properties, solvation effects, and periodic systems. A variety of illustrative applications along with accuracy and timing data are discussed. Moreover, available interfaces to users as well as other software are summarized. TURBOMOLE’s current licensing, distribution, and support model are discussed, and an overview of TURBOMOLE’s development workflow is provided. Challenges such as communication and outreach, software infrastructure, and funding are highlighted

    TURBOMOLE: Modular program suite for ab initio quantum-chemical and condensed-matter simulations

    Get PDF
    TURBOMOLE is a collaborative, multi-national software development project aiming to provide highly efficient and stable computational tools for quantum chemical simulations of molecules, clusters, periodic systems, and solutions. The TURBOMOLE software suite is optimized for widely available, inexpensive, and resource-efficient hardware such as multi-core workstations and small computer clusters. TURBOMOLE specializes in electronic structure methods with outstanding accuracy–cost ratio, such as density functional theory including local hybrids and the random phase approximation (RPA), GW-Bethe–Salpeter methods, second-order Møller–Plesset theory, and explicitly correlated coupled-cluster methods. TURBOMOLE is based on Gaussian basis sets and has been pivotal for the development of many fast and low-scaling algorithms in the past three decades, such as integral-direct methods, fast multipole methods, the resolution-of-the-identity approximation, imaginary frequency integration, Laplace transform, and pair natural orbital methods. This review focuses on recent additions to TURBOMOLE’s functionality, including excited-state methods, RPA and Green’s function methods, relativistic approaches, high-order molecular properties, solvation effects, and periodic systems. A variety of illustrative applications along with accuracy and timing data are discussed. Moreover, available interfaces to users as well as other software are summarized. TURBOMOLE’s current licensing, distribution, and support model are discussed, and an overview of TURBOMOLE’s development workflow is provided. Challenges such as communication and outreach, software infrastructure, and funding are highlighted

    ASXL2 is essential for haematopoiesis and acts as a haploinsufficient tumour suppressor in leukemia

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    Additional sex combs-like (ASXL) proteins are mammalian homologues of additional sex combs (Asx), a regulator of trithorax and polycomb function in Drosophila. While there has been great interest in ASXL1 due to its frequent mutation in leukemia, little is known about its paralog ASXL2, which is frequently mutated in acute myeloid leukemia patients bearing the RUNX1-RUNX1T1 (AML1-ETO) fusion. Here we report that ASXL2 is required for normal haematopoiesis with distinct, non-overlapping effects from ASXL1 and acts as a haploinsufficient tumour suppressor. While Asxl2 was required for normal haematopoietic stem cell self-renewal, Asxl2 loss promoted AML1-ETO leukemogenesis. Moreover, ASXL2 target genes strongly overlapped with those of RUNX1 and AML1-ETO and ASXL2 loss was associated with increased chromatin accessibility at putative enhancers of key leukemogenic loci. These data reveal that Asxl2 is a critical regulator of haematopoiesis and mediates transcriptional effects that promote leukemogenesis driven by AML1-ETO

    The clinical relevance of oliguria in the critically ill patient : Analysis of a large observational database

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    Funding Information: Marc Leone reports receiving consulting fees from Amomed and Aguettant; lecture fees from MSD, Pfizer, Octapharma, 3 M, Aspen, Orion; travel support from LFB; and grant support from PHRC IR and his institution. JLV is the Editor-in-Chief of Critical Care. The other authors declare that they have no relevant financial interests. Publisher Copyright: © 2020 The Author(s). Copyright: Copyright 2020 Elsevier B.V., All rights reserved.Background: Urine output is widely used as one of the criteria for the diagnosis and staging of acute renal failure, but few studies have specifically assessed the role of oliguria as a marker of acute renal failure or outcomes in general intensive care unit (ICU) patients. Using a large multinational database, we therefore evaluated the occurrence of oliguria (defined as a urine output 16 years) patients in the ICON audit who had a urine output measurement on the day of admission were included. To investigate the association between oliguria and mortality, we used a multilevel analysis. Results: Of the 8292 patients included, 2050 (24.7%) were oliguric during the first 24 h of admission. Patients with oliguria on admission who had at least one additional 24-h urine output recorded during their ICU stay (n = 1349) were divided into three groups: transient - oliguria resolved within 48 h after the admission day (n = 390 [28.9%]), prolonged - oliguria resolved > 48 h after the admission day (n = 141 [10.5%]), and permanent - oliguria persisting for the whole ICU stay or again present at the end of the ICU stay (n = 818 [60.6%]). ICU and hospital mortality rates were higher in patients with oliguria than in those without, except for patients with transient oliguria who had significantly lower mortality rates than non-oliguric patients. In multilevel analysis, the need for RRT was associated with a significantly higher risk of death (OR = 1.51 [95% CI 1.19-1.91], p = 0.001), but the presence of oliguria on admission was not (OR = 1.14 [95% CI 0.97-1.34], p = 0.103). Conclusions: Oliguria is common in ICU patients and may have a relatively benign nature if only transient. The duration of oliguria and need for RRT are associated with worse outcome.publishersversionPeer reviewe
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