COMPUTERIZED SOFTWARE QUALITY EVALUATION WITH NOVEL ARTIFICIAL INTELLIGENCE APPROACH

Software quality assurance has grown in importance in the fast-paced world of software development. One of trickiest parts of creating and maintaining software is predicting how well it will perform. The term "computer evaluation" refers to use of advanced AI techniques in software quality assurance, replacing human evaluations and paving the way for a new era in software evaluation. We proposed Hybrid Elephant herding optimized Conditional Long short-term memory (HEHO-CLSTM) to estimate Software Quality Prediction. Software quality prediction and assurance has grown in importance in ever-changing world of software development. Software quality prediction encompasses a wide range of activities aimed at improving the quality of software systems via the use of data-driven approaches for prediction, evaluation and enhancement. We have collected Software Defects data and we feature extracted the attributes using linear discriminant Analysis (LDA). The suggested system improves the accuracy, AUC and Buggy instance compared with the current methods

Differentially localized survivin and STAT3 as markers of gastric cancer progression: Association with Helicobacter pylori

BackgroundLocalization and differential expression of STAT3 and survivin in cancer cells are often related to distinct cellular functions. The involvement of survivin and STAT3 in gastric cancer has been reported in separate studies but without clear understanding of their kinetics in cancer progression.MethodsWe examined intracellular distribution of STAT3 and survivin in gastric adenocarcinoma and compared it with normal and precancer tissues using immunoblotting and immunohistochemistry.ResultsAnalysis of a total of 156 gastric samples comprising 61 histologically normal, 30 precancerous tissues (comprising intestinal metaplasia and dysplasia), and 65 adenocarcinomas, collected as endoscopic biopsies from treatment naïve study participants, revealed a significant (P < .001) increase in overall protein levels. Survivin expression was detectable in both cytoplasmic (90.8%) and nuclear (87.7%) compartments in gastric adenocarcinomas lesions. Precancerous dysplastic gastric lesions exhibited a moderate survivin expression (56.7%) localized in cytoplasmic compartment. Similarly, STAT3 and pSTAT3 expression was detected at high level in gastric cancer lesions. The levels of compartmentalized expression of survivin and STAT3/pSTAT3 correlated in precancerous and adenocarcinoma lesions. Although overexpression of these proteins was found associated with the tobacco use and alcohol consumption, their expression invariably and strongly correlated with concurrent Helicobacter pylori infection. Receiver operating characteristic analysis of nuclear survivin, STAT3, and pSTAT3 in different study groups showed acceptable positive and negative predictive values with area under the curve above 0.8 (P < .001).ConclusionOverall, our results suggest that overall increase in survivin and STAT3 and their subcellular localization are key determinants of gastric cancer progression, which can be collectively used as potential disease biomarkers and therapeutic targets for gastric cancer.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/144680/1/cnr21004-Supplementary_Methods_20180313.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/144680/2/cnr21004-sup-0001-F1.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/144680/3/cnr21004_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/144680/4/cnr21004.pd

Production of He-4 and (4) in Pb-Pb collisions at root(NN)-N-S=2.76 TeV at the LHC

Results on the production of He-4 and (4) nuclei in Pb-Pb collisions at root(NN)-N-S = 2.76 TeV in the rapidity range vertical bar y vertical bar <1, using the ALICE detector, are presented in this paper. The rapidity densities corresponding to 0-10% central events are found to be dN/dy4(He) = (0.8 +/- 0.4 (stat) +/- 0.3 (syst)) x 10(-6) and dN/dy4 = (1.1 +/- 0.4 (stat) +/- 0.2 (syst)) x 10(-6), respectively. This is in agreement with the statistical thermal model expectation assuming the same chemical freeze-out temperature (T-chem = 156 MeV) as for light hadrons. The measured ratio of (4)/He-4 is 1.4 +/- 0.8 (stat) +/- 0.5 (syst). (C) 2018 Published by Elsevier B.V.Peer reviewe

Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods: The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk–outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. Findings: Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7–9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4–9·2]), smoking (5·7% [4·7–6·8]), low birthweight and short gestation (5·6% [4·8–6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8–6·0]). For younger demographics (ie, those aged 0–4 years and 5–14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9–27·7]) and environmental and occupational risks (decrease of 22·0% [15·5–28·8]), coupled with a 49·4% (42·3–56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9–21·7] for high BMI and 7·9% [3·3–12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6–1·9) for high BMI and 1·3% (1·1–1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4–78·8) for child growth failure and 66·3% (60·2–72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). Interpretation: Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions

ANALYZING SEISMIC ACTIVITIES DURING 1900 TO 2015 TO ASSESS URBAN RISK IN NEPAL HIMALAYAS USING GEOINFORMATICS

A high magnitude ( Mw = 7.8) earthquake caused a geological disaster recently on April-May 2015 in Nepal Himalayas and resulted in severe devastation in Nepal as well as neighboring states in India. Looking into its recurrent occurrence with varied intensity, in the present study, the earthquake pattern in Nepal Himalayas was analyzed during the period 1900 to 2015 using United States Geological Survey (USGS) data sources in GIS environment. The result exhibits that the intensity of earthquake events are increased in recent decade in Nepal Himalayas as compared to previous century (1900-2014). The information pertaining to earthquake epicenter, magnitude, depth to hypocenter, demography etc . was also analyzed in geospatial environment to deduce its relation with geotectonic settings and possible risk in the vicinity. The earthquake events were also observed at deeper location (more than 40 kms) during 1900-2014 (414 events; 53.9%) as compared to the recent events (2015), where majority of eathquake events (146 events; 85.3%) recorded at below 10 km depth (Janakpur and Bagmati provinces in Nepal). The result exhibits high number of recent events with greater magnitudes in central Nepal during April-May 2015 affecting a very large population above and around their vicinity with varied intensity. The cities located in central Nepal are highly prone to frequent earthquake hazard and induced risk on population of 2 923 621 persons followed by north-western Nepal

Contrasting behaviour of temporal glacier changes and long term estimation of glacier mass balance across Himalayan–Karakoram range

Glacier dynamics and mass balance observations in Himalayan–Karakoram (H–K) region are important to monitor the effect of climatic perturbations over the highest cryospheric region of the world. Such studies can be accomplished by employing satellite based remote sensing technique as field measurements are difficult to obtain in these inaccessible region. In the present study, an attempt was made to investigate the retreat/advancement along with their mass fluctuations of 13 select glaciers from different sectors of H–K region over a continuous period from year 1996 to 2020 using satellite images. Variation in areal and snout fluctuations shown different patterns pertaining to gain/advancement and loss/retreat of each select glaciers. Mass loss for glaciers in Karakoram Range (–0.217 ± 0.017 m w e) was marginal when compared with Western (–0.26 ± 0.08 m w e), Central (–0.56 ± 0.067 m w e) and Eastern Himalayas (–0.625 ± 0.13 m w e). Contrasting relationship between glacier dynamics and mass balance has been obtained in the present study. Validation of results with existing field observations depicted the utility of satellite-based observation

Satellite Based Temporal Analysis of Local Weather Elements along N–S Transect across Jharkhand, Bihar and Eastern Nepal

The study shows the variation in the most important climatic variables i.e., Net Surface Radiation (Rn), Temperature, Rainfall, Evapotranspiration (ET), etc. during 2000–2016 along the North–South transect across Jharkhand, Bihar and Eastern Nepal. The Tropical Rainfall Measuring Mission (TRMM) monthly average precipitation (0.25° × 0.25°), Moderate Resolution Imaging Spectroradiometer (MODIS) 8 day average Land Surface Temperature (LST) product (1 km × 1 km), Modern-Era Retrospective analysis for Research and Applications, Version-2 (MERRA-2) radiation (0.5° × 0.625°) and Global Land Data Assimilation System (GLDAS) reanalysis model data (0.25° × 0.25°) have been used to study and analysed the spatial variability and distribution of rainfall, surface temperature, energy fluxes and evapotranspiration, respectively. The results have shown that the overall annual average rainfall has a gradual decreasing trend. Results have suggested that the regions with low rainfall (&lt;1000 mm) have to witness warmer temperature conditions (&gt;43 °C). The east–west central line of the Bihar, along the river Ganga is found to be the line of division for the comparatively higher (towards south) and lower (towards north) temperature zones. The results for Rn have shown an overall increasing trend over the period of time. Nepal has a wider stretch of Rn concluded by its mountain topography followed by the Jharkhand (plateau) and Bihar (plain). ET values have also shown an increasing trend and the results are noticeable for western Bihar-Jharkhand. There is an upward latitudinal shifting of the low rainfall bands in both the pre-monsoon and monsoon conditions. Due to the lack of availability of ground truth data, we have to restrict with the remotely sensed dataset only

Long-term precipitation monitoring and its linkage with flood scenario in changing climate conditions in Kashmir valley

The flood in Kashmir valley has a long history and is considered as recurrent phenomena, though the flood occurred in 2014 was extremely severe due to its extent, intensity and impact on mankind. To understand the variation of this precarious climatic condition, the long-term variability of precipitation over Kashmir valley was analysed over a period of 1901–2018 on an annual, seasonal, monthly and weekly basis to investigate the pattern of precipitation and its linkage to flooding. The mean annual precipitation analysis exhibits only few (06) severe incidences (>1226mm). Sen’s slope estimation exhibited a statistically positive trend during winter season (0.458 mm year−1) as compared to rainy season (-0.661 mm year−1) at the 5% level of significance. The major deficit (> −99%) in precipitation anomaly was recorded forming the September month as anomalous. September 2014 exceptionally confronted one incidence of sudden but continuous weekly high precipitation (>130 mm) with intensity of 22.82 mm day−1 during 15 years

Long-term estimation of glacier mass balance using geospatial techniques in Western Himalayas, Ladakh, India

All glaciers are subject to mass fluctuations in the current context of climate change. For daily requirements like food, drink, irrigation, and the generation of hydroelectric power, these glaciers provide water to important basins including the Indus, Ganga, and Brahmaputra. Changes in glacier patterns are a blatant sign of local climate variability. Monitoring of glaciers requires long-term studies on glacier dynamics. Himalayan glaciers, because of their disposition in a complex topographic setting and inaccessible terrain render difficulty in the glacier observations in a continuous mode. Glacier mass fluctuations can be associated with glacier area shrinkage or expansion and concomitant snout shift. In the current study, two adjoining glaciers of different sizes, Pensilungpa and Drang Drung glaciers in the Zanskar Valley, Ladakh, India are selected. The period of the study was taken between the years 2000–2022. Earlier studies used a single day per year Accumulation Area Ratio (AAR) method to compute mass balance, which had limitations due to snow cover variability. The present study calculated and averaged all the AAR values for cloud-free images per year during the peak ablation period (mid-July to early September). Digital Elevation Model (DEM) difference technique was also employed for computing the mass budget between 2000 and 2021 b y utilizing two-time period DEMs. It was revealed that in the case of the AAR method, the Pensilungpa glacier showed 7 years of positive and 16 years of negative mass balance. The years 2003–2005 and 2011 to 2016 were depicted with negative mass balance with the highest value up to −0.752-m water equivalent (m.w.e.) for the year 2015. It has negligible areal fluctuations ranging from 0.01 to 0.6 km2. Drang Drung Glacier has shown 12 years of positive and 11 years of negative mass balance. The years 2002–2004 and 2009 to 2012 were depicted with positive mass balance with the highest value up to 0.305 m. w.e. Except, for the year 2009–2012 (areal increment ∼ 2.65 km2), years 2013–2015 showed a negative mass balance with negligible areal fluctuations. Mass balance estimation using DEM differencing method revealed an average estimated mass balance of −0.03 m. w.e. For Pensilungpa glacier though, it is 0.08 m. w.e. For Drang Drung glacier which shows good matches with the mass balance estimated using AAR method in m. w.e. Such contrasting behavior of mass balance suggests higher sensitivity of smaller glaciers to climate change

Google Earth Engine for Large-Scale Flood Mapping Using SAR Data and Impact Assessment on Agriculture and Population of Ganga-Brahmaputra Basin

The Ganga-Brahmaputra basin is highly sensitive to the impacts of climate change and experiences recurrent flooding, which affects large agricultural areas and poses a high risk to the population. The present study is focused on the recent flood disaster in the Ganga-Brahmaputra basin, which mainly affected the regions of Bihar, West Bengal, and Assam in India and neighboring Bangladesh during July, August, and September 2020. Using the Sentinel-1A Synthetic Aperture Radar (SAR) data, the flood extent was derived in the Google Earth Engine (GEE) platform. The composite area under flood inundation for July&ndash;September was estimated to be 25,889.1 km2 for Bangladesh, followed by Bihar (20,837 km2), West Bengal (17,307.1 km2), and Assam (13,460.1 km2). The Copernicus Global Land Cover dataset was used to extract the affected agricultural area and flood-affected settlement. Floods have caused adverse impacts on agricultural lands and settlements, affecting 23.68&ndash;28.47% and 5.66&ndash;9.15% of these areas, respectively. The Gridded Population of the World (GPW) population density and Global Human Settlement Layer (GHSL) population dataset were also employed to evaluate flood impacts, which revealed that 23.29 million of the population was affected by floods in the Ganga-Brahmaputra basin. The highest impacts of floods can be seen from the Bihar state, as people reside in the lower valley and near to the riverbank due to their dependency on river water. Similarly, the highest impact was from Bangladesh because of the high population density as well as the settlement density. The study provided a holistic spatial assessment of flood inundation in the region due to the combined impact of the Ganga-Brahmaputra River basin. The identification of highly flood-prone areas with an estimated impact on cropland and build-up will provide necessary information to decision-makers for flood risk reduction, mitigation activities, and management