A Stochastic model for dynamics of FtsZ filaments and the formation of Z-ring

Understanding the mechanisms responsible for the formation and growth of FtsZ polymers and their subsequent formation of the $Z$-ring is important for gaining insight into the cell division in prokaryotic cells. In this work, we present a minimal stochastic model that qualitatively reproduces {\it in vitro} observations of polymerization, formation of dynamic contractile ring that is stable for a long time and depolymerization shown by FtsZ polymer filaments. In this stochastic model, we explore different mechanisms for ring breaking and hydrolysis. In addition to hydrolysis, which is known to regulate the dynamics of other tubulin polymers like microtubules, we find that the presence of the ring allows for an additional mechanism for regulating the dynamics of FtsZ polymers. Ring breaking dynamics in the presence of hydrolysis naturally induce rescue and catastrophe events in this model irrespective of the mechanism of hydrolysis.Comment: Replaced with published versio

DETERMINANTS OF PRIORITY SECTOR LENDING OF INDIAN PUBLIC SECTOR BANKS: AN ECONOMETRIC ANALYSIS

Compulsory sanctioning credit or priority sector lending (PSL) is part of the regulatory framework for commercial banks/ financial institutions in many countries, both developing and developed. However, compliance and lending effectiveness of such programs may be determined by a number of factors. This may be particularly so in developing countries, where availability of finance for the vulnerable sectors likes agriculture, small businesses, weaker sections, are scarce. The present paper aims at examining the patterns of priority sector lending by banks, with a view to identifying the factors which determine this lending The paper is based on an analysis of secondary data relating to priority sector lending (2006-07-2015-16) for the Public sector banks in India. The results indicate gaps in patterns of the sect oral target compliance by different bank groups, along with the lending preferences and challenges faced by banks in such lending. It also identifies bank-specific characteristics like the nature of ownership, size, performance, etc., which have a significant impact on the priority sector lending patterns. Based on its findings, the paper offers policy suggestions for improving the effectiveness of priority sector lending program

Recent advances in smart integrated membrane assisted liquid extraction technology

Novel processes based on SIMALE have been proposed as effective methods for the selective separation of different chemical species such as metal ions, organic/biologically important compounds and gas mixtures from different waste streams including nuclear waste. The industrial use of supported liquid membranes based on conventional liquids is limited by their relative instability and short lifetime. Under SIMALE techniques, the stability of the SLM is ensured by a modified SLM with pseudo emulsion based hollow fiber strip dispersion or non-dispersive solvent extraction techniques. In order to promote operational stability, SIMALE, using ionic liquids, as a liquid membrane phase could overcome these inconveniences due to their negligible vapour pressure and the possibility of minimizing their solubility in the surrounding phases. SIMALE studies on membrane-based dense gas extraction reported higher extraction efficiencies when the near critical or supercritical solvent is used. This review also discuss important applications including scale up, process intensification aspects, current status of the technology and future directions.Peer ReviewedPostprint (author's final draft

Application of IoT Framework for Prediction of Heart Disease using Machine Learning

Prognosis of illnesses is a difficult problem these days throughout the globe. Elder people of twenty years and over are taken into consideration to be laid low with this sickness now a days. For example, human beings having  HbA1c level more than 6.5% are diagnosed as infected with diabetic diseases. This paper uses IoT to evaluate threat factors which have been similar to heart diseases which are not treated properly. Diagnosis, prevention of heart disease may be done by use of machine learning (ML). There has been an extensive disconnect among Machine Learning architects, health care researchers, patients and physicians in their technology. This paper intends to perform an in-intensity evaluation on Machine Learning to make us of new advance technologies. Latest advances within the development of IoT implanted devices and other medicine delivery gadgets, disease diagnostic methods and other medical research have considerably helped human beings diagnosed heart diseases. New soft computing models can be helpful for remedy of various heart diseases. The Food and Drug Administration (FDA) employs several particularly creative thoughts to get their capsules to the client. Artificial Neural Community offers a first-rate chance to deal with heart diseases with advance IoT and cloud applications

Study of Wind Energy System with Induction Generators

Wind energy, as an alternative to fossil fuels, is plentiful, renewable, widely distributed, clean, and produces no greenhouse gas emissions during operation. The world has enormous resources of wind power. It has been estimated that even if 10% of raw wind potential could be put to use, all the electricity needs of the world would be met. A phased programme to develop wind energy in India started as early as 1985, and today the total installed capacity has reached 1650 MW, saving about 935,000 metric tonnes of coal. Wind electrical generation systems are the most cost-competitive of all the environmentally clean and safe renewable energy sources in the world. They are also competitive with fossil fuel generated power and much cheaper than nuclear power. Traditionally, wind generation systems used variable pitch constant speed wind turbines (horizontal or vertical axis) that were coupled to squirrel cage induction generators or wound-field synchronous generators and fed power to utility grids or autonomous loads. The recent evolution of power semiconductors and variable frequency drives technology has aided the acceptance of variable speed generation systems. Such systems can yield 20-30% more power than constant-speed generation systems

Migration/mobility and vulnerability to HIV among male migrant workers: Maharashtra 2007-08

HIV prevalence in Maharashtra is one of the highest among Indian states. The specific objectives of this study were: to understand the patterns and drivers of migration/mobility of men who migrate for the purpose of work in the state of Maharashtra; to describe the characteristics of vulnerable subpopulations among migrant men; and to examine the determinants of high-risk sexual behavior among the subpopulations of migrant men with particular emphasis on the role of mobility in determining the sexual risk behavior. The present study clearly demonstrates that these male migrants, married or otherwise, retain strong connectivity to their native villages, but also show high levels of sexual activity—including significant levels of high-risk sexual activity—making it imperative to study the situation in the sending districts regarding HIV prevalence and spread. The indication from this study is clear: in the context of high-risk sexual behavior (among both married and unmarried migrants) and the low levels of knowledge, condom use, and risk perception, the chances of sending households and districts becoming areas of high HIV prevalence are great. Further exploration of the sexual behavior pattern in sending areas is necessary to obtain additional insights into the possible routes of HIV transmission

Identification of mungbean lines with tolerance or resistance to yellow mosaic in fields in India where different begomovirus species and different Bemisia tabaci cryptic species predominate

Mungbean (Vigna radiata (L.) Wilczek) is an important pulse crop in India. A major constraint for improved productivity is the yield loss caused by mungbean yellow mosaic disease (MYMD). This disease is caused by several begomoviruses which are transmitted by the whitefly Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae). The objective of this study was to identify the predominant begomoviruses infecting mungbean and the major cryptic species of B. tabaci associated with this crop in India. The indigenous B. tabaci cryptic species Asia II 1 was found dominant in Northern India, whereas Asia II 8 was found predominant in Southern India. Repeated samplings over consecutive years indicate a stable situation with, Mungbean yellow mosaic virus strains genetically most similar to a strain from urdbean (MYMV-Urdbean) predominant in North India, strains most similar to MYMV-Vigna predominant in South India, and Mungbean yellow mosaic India virus (MYMIV) strains predominant in Eastern India. In field studies, mungbean line NM 94 showed a high level of tolerance to the disease in the Eastern state of Odisha where MYMIV was predominant and in the Southern state of Andhra Pradesh where MYMV-Vigna was predominant, but only a moderate level of tolerance in the Southern state of Tamil Nadu. However, in Northern parts of India where there was high inoculum pressure of MYMV-Urdbean during the Kharif season, NM 94 developed severe yellow mosaic symptoms. The identification of high level of tolerance in mungbean lines such as ML 1628 and of resistance in black gram and rice bean provides hope for tackling the disease through resistance breeding

Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021

Background: Future trends in disease burden and drivers of health are of great interest to policy makers and the public at large. This information can be used for policy and long-term health investment, planning, and prioritisation. We have expanded and improved upon previous forecasts produced as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) and provide a reference forecast (the most likely future), and alternative scenarios assessing disease burden trajectories if selected sets of risk factors were eliminated from current levels by 2050. Methods: Using forecasts of major drivers of health such as the Socio-demographic Index (SDI; a composite measure of lag-distributed income per capita, mean years of education, and total fertility under 25 years of age) and the full set of risk factor exposures captured by GBD, we provide cause-specific forecasts of mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) by age and sex from 2022 to 2050 for 204 countries and territories, 21 GBD regions, seven super-regions, and the world. All analyses were done at the cause-specific level so that only risk factors deemed causal by the GBD comparative risk assessment influenced future trajectories of mortality for each disease. Cause-specific mortality was modelled using mixed-effects models with SDI and time as the main covariates, and the combined impact of causal risk factors as an offset in the model. At the all-cause mortality level, we captured unexplained variation by modelling residuals with an autoregressive integrated moving average model with drift attenuation. These all-cause forecasts constrained the cause-specific forecasts at successively deeper levels of the GBD cause hierarchy using cascading mortality models, thus ensuring a robust estimate of cause-specific mortality. For non-fatal measures (eg, low back pain), incidence and prevalence were forecasted from mixed-effects models with SDI as the main covariate, and YLDs were computed from the resulting prevalence forecasts and average disability weights from GBD. Alternative future scenarios were constructed by replacing appropriate reference trajectories for risk factors with hypothetical trajectories of gradual elimination of risk factor exposure from current levels to 2050. The scenarios were constructed from various sets of risk factors: environmental risks (Safer Environment scenario), risks associated with communicable, maternal, neonatal, and nutritional diseases (CMNNs; Improved Childhood Nutrition and Vaccination scenario), risks associated with major non-communicable diseases (NCDs; Improved Behavioural and Metabolic Risks scenario), and the combined effects of these three scenarios. Using the Shared Socioeconomic Pathways climate scenarios SSP2-4.5 as reference and SSP1-1.9 as an optimistic alternative in the Safer Environment scenario, we accounted for climate change impact on health by using the most recent Intergovernmental Panel on Climate Change temperature forecasts and published trajectories of ambient air pollution for the same two scenarios. Life expectancy and healthy life expectancy were computed using standard methods. The forecasting framework includes computing the age-sex-specific future population for each location and separately for each scenario. 95% uncertainty intervals (UIs) for each individual future estimate were derived from the 2·5th and 97·5th percentiles of distributions generated from propagating 500 draws through the multistage computational pipeline. Findings: In the reference scenario forecast, global and super-regional life expectancy increased from 2022 to 2050, but improvement was at a slower pace than in the three decades preceding the COVID-19 pandemic (beginning in 2020). Gains in future life expectancy were forecasted to be greatest in super-regions with comparatively low life expectancies (such as sub-Saharan Africa) compared with super-regions with higher life expectancies (such as the high-income super-region), leading to a trend towards convergence in life expectancy across locations between now and 2050. At the super-region level, forecasted healthy life expectancy patterns were similar to those of life expectancies. Forecasts for the reference scenario found that health will improve in the coming decades, with all-cause age-standardised DALY rates decreasing in every GBD super-region. The total DALY burden measured in counts, however, will increase in every super-region, largely a function of population ageing and growth. We also forecasted that both DALY counts and age-standardised DALY rates will continue to shift from CMNNs to NCDs, with the most pronounced shifts occurring in sub-Saharan Africa (60·1% [95% UI 56·8–63·1] of DALYs were from CMNNs in 2022 compared with 35·8% [31·0–45·0] in 2050) and south Asia (31·7% [29·2–34·1] to 15·5% [13·7–17·5]). This shift is reflected in the leading global causes of DALYs, with the top four causes in 2050 being ischaemic heart disease, stroke, diabetes, and chronic obstructive pulmonary disease, compared with 2022, with ischaemic heart disease, neonatal disorders, stroke, and lower respiratory infections at the top. The global proportion of DALYs due to YLDs likewise increased from 33·8% (27·4–40·3) to 41·1% (33·9–48·1) from 2022 to 2050, demonstrating an important shift in overall disease burden towards morbidity and away from premature death. The largest shift of this kind was forecasted for sub-Saharan Africa, from 20·1% (15·6–25·3) of DALYs due to YLDs in 2022 to 35·6% (26·5–43·0) in 2050. In the assessment of alternative future scenarios, the combined effects of the scenarios (Safer Environment, Improved Childhood Nutrition and Vaccination, and Improved Behavioural and Metabolic Risks scenarios) demonstrated an important decrease in the global burden of DALYs in 2050 of 15·4% (13·5–17·5) compared with the reference scenario, with decreases across super-regions ranging from 10·4% (9·7–11·3) in the high-income super-region to 23·9% (20·7–27·3) in north Africa and the Middle East. The Safer Environment scenario had its largest decrease in sub-Saharan Africa (5·2% [3·5–6·8]), the Improved Behavioural and Metabolic Risks scenario in north Africa and the Middle East (23·2% [20·2–26·5]), and the Improved Nutrition and Vaccination scenario in sub-Saharan Africa (2·0% [–0·6 to 3·6]). Interpretation: Globally, life expectancy and age-standardised disease burden were forecasted to improve between 2022 and 2050, with the majority of the burden continuing to shift from CMNNs to NCDs. That said, continued progress on reducing the CMNN disease burden will be dependent on maintaining investment in and policy emphasis on CMNN disease prevention and treatment. Mostly due to growth and ageing of populations, the number of deaths and DALYs due to all causes combined will generally increase. By constructing alternative future scenarios wherein certain risk exposures are eliminated by 2050, we have shown that opportunities exist to substantially improve health outcomes in the future through concerted efforts to prevent exposure to well established risk factors and to expand access to key health interventions

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