The Institutional Care of Children. United Nations Department of Economic and Social Affairs

The ability of microorganisms to withstand long periods with extremely low energy input has gained increasing scientific attention in recent years. Starvation experiments in the laboratory have shown that a phylogenetically wide range of microorganisms evolve fitness-enhancing genetic traits within weeks of incubation under low-energy stress. Studies on natural environments that are cut off from new energy supplies over geologic time scales, such as deeply buried sediments, suggest that similar adaptations might mediate survival under energy limitation in the environment. Yet, the extent to which laboratory-based evidence of starvation survival in pure or mixed cultures can be extrapolated to sustained microbial ecosystems in nature remains unclear. In this review, we discuss past investigations on microbial energy requirements and adaptations to energy limitation, identify gaps in our current knowledge, and outline possible future foci of research on life under extreme energy limitation.

Life under extreme energy limitation: a synthesis of laboratory- and field-based investigations.

Human health implications, risk assessment and remediation of As-contaminated water: A critical review.

This study determined the total and speciated arsenic (As) concentrations and other health-related water quality parameters for unraveling the health risk of As from drinking water to humans. Groundwater samples (n = 62) were collected from three previously unexplored rural areas (Chichawatni, Vehari, Rahim Yar Khan) of Punjab in Pakistan. The mean and median As concentrations in groundwater were 37.9 and 12.7 µg·L−1 (range = 1.5–201 µg·L−1). Fifty three percent groundwater samples showed higher As value than WHO safe limit of 10 µg·L−1. Speciation of As in groundwater samples (n = 13) showed the presence of inorganic As only; arsenite (As(III)) constituted 13%–67% of total As and arsenate (As(V)) ranged from 33% to 100%. For As health risk assessment, the hazard quotient and cancer risk values were 11–18 and 46–600 times higher than the recommended values of US-EPA (i.e., 1.00 and 10−6, respectively). In addition to As, various water quality parameters (e.g., electrical conductivity, Na, Ca, Cl−, NO3−, SO42−, Fe, Mn, Pb) also enhanced the health risk. The results show that consumption of As-contaminated groundwater poses an emerging health threat to the communities in the study area, and hence needs urgent remedial and management measures.

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Unraveling Health Risk and Speciation of Arsenic from Groundwater in Rural Areas of Punjab, Pakistan.

Ensemble machine learning paradigms in hydrology: A review

Stubble burning has been reckoned among the major contributors of air pollution especially in South Asia. It is a significant source of gaseous pollutants such as, carbon dioxide (CO2), carbon monoxide (CO), nitrogen oxides (NOx), sulfur oxides (SOx), and methane (CH4) as well as particulate matters (PM10 and PM2.5) causing serious damage to human health and the environment. It was reported that the burning of 63 Mt of crop stubble releases 3.4 Mt of CO, 0.1 Mt of NOx, 91 Mt of CO2, 0.6 Mt of CH4 and 1.2 Mt of PM into the atmosphere. The situation is more austere in India due to the intensive rice-wheat rotation system which generates large amount of stubble. It was estimated that about 352 Mt of stubble is generated each year in India out of which 22% and 34% are contributed by wheat and rice stubble respectively. About 84 Mt (23.86%) of the stubble is burnt on-field each year immediately after harvest. The disastrous haze observed over India during the winter season has been linked to stubble burning as it coincides with the burning periods (October-November). During this time, most Indian cities, especially within the National Capital Region (NCR) experience harsh pollution often reaching the severe levels of the air quality index (AQI). In November 2019, Delhi recorded a peak AQI of 487, Ghaziabad reported an AQI as high as 493, and Greater Noida recorded 480. The health effects of air pollution ranges from skin and eyes irritation to severe neurological, cardiovascular and respiratory diseases, asthma, chronic obstructive pulmonary disease (COPD), bronchitis, lung capacity loss, emphysema, cancer, etc. It also leads to an increase in mortality rates due to the prolonged exposure to high pollution. The Energy and Resources Institute (2019) reported that in 2012, air pollution had led to about 5 million deaths in South Asia which is around 22% of the total deaths in the region. In addition to its effects on air quality, stubble burning also affects soil fertility (through the destruction of its nutrients), economic development and climate. The crop stubbles (if managed properly) could provide immense economic benefits to the farmers and protect the environment from the severe pollution. Some of the alternative management practices include the incorporation of the stubble into the soil, use of stubble as fuel in power plants, use as raw material for pulp and paper industries, or as biomass for biofuel production. It can also be used to generate compost and biochar, or as blend for the production of cement and bricks. Most of the farmers in North India are not aware of the prolific alternatives for managing stubble and, therefore, consider burning as the best option. This necessitates the need for immense awareness programs to enlighten the farmers about the availability of economically feasible options and the composite effects of stubble burning.

Stubble burning: Effects on health & environment, regulations and management practices

In recent decades, various conventional techniques have been formulated around the world to evaluate the overall water quality (WQ) at particular locations. In the present study, back propagation neural network (BPNN) and adaptive neuro-fuzzy inference system (ANFIS), support vector regression (SVR), and one multilinear regression (MLR) are considered for the prediction of water quality index (WQI) at three stations, namely Nizamuddin, Palla, and Udi (Chambal), across the Yamuna River, India. The nonlinear ensemble technique was proposed using the neural network ensemble (NNE) approach to improve the performance accuracy of the single models. The observed WQ parameters were provided by the Central Pollution Control Board (CPCB) including dissolved oxygen (DO), pH, biological oxygen demand (BOD), ammonia (NH3), temperature (T), and WQI. The performance of the models was evaluated by various statistical indices. The obtained results indicated the feasibility of the developed data intelligence models for predicting the WQI at the three stations with the superior modelling results of the NNE. The results also showed that the minimum values for root mean square (RMS) varied between 0.1213 and 0.4107, 0.003 and 0.0367, and 0.002 and 0.0272 for Nizamuddin, Palla, and Udi (Chambal), respectively. ANFIS-M3, BPNN-M4, and BPNN-M3 improved the performance with regard to an absolute error by 41%, 4%, and 3%, over other models for Nizamuddin, Palla, and Udi (Chambal) stations, respectively. The predictive comparison demonstrated that NNE proved to be effective and can therefore serve as a reliable prediction approach. The inferences of this paper would be of interest to policymakers in terms of WQ for establishing sustainable management strategies of water resources.

Implementation of data intelligence models coupled with ensemble machine learning for prediction of water quality index

Industrial effluents are a menace to the environment and the fact that their characteristics vary from industry-to-industry only adds to the complex challenge they offer to the engineers and scientists. Resource-efficient and environment-friendly solutions to this hazard are a call of the hour. Coagulation, by synthetic chemicals, has been used as a cost-effective and efficient method for managing the effluents generated by a large number of industries. However, the synthetic chemicals themselves are a cause of concern due to their non-native nature, non-degradability, and health conditions associated with their left-over residues. Natural coagulants offer a cost-effective, environment-friendly, and sustainable alternative to the application of synthetic chemicals. Such natural coagulants, despite their demonstrated effectiveness in treating the industrial wastewaters, have their own limitations and are yet to be investigated for large-scale applications. The current work presents a state-of-the-art review of the natural coagulants' application in treating industrial wastewaters and their relative advantages and disadvantages as compared to the chemical coagulants. Future research areas have also been identified that may ultimately lead to the large-scale commercial application of natural coagulants and will result in an environment-friendly and sustainable solution to the problems created by industrial effluents and synthetic chemical coagulants.

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Use of natural coagulants for industrial wastewater treatment.

For the most recent CMOS feature sizes (e.g., 90 nm and 65 nm), leakage power dissipation has become an overriding concern for VLSI circuit designers. ITRS reports that leakage power dissipation may come to dominate total power consumption [1]. We are doing comparable analysis of different low power, leakage current reduction techniques like SLEEP approach, STACK, ZIGZAG & some new techniques like, SLEEPY-STACK, LEAKAGE FEEDBACK approach and SLEEPY KEEPER techniques and, after that to combine the advantages of above written techniques, we propose two novel approaches from simulation study, named "Leakage Feedback with Stack (LFS)" & "Sleep Stack with Keeper (SSK)" which reduces leakage current while saving exact logic state. But based on simulations result with a full adder circuit, "Sleep-Stack with keeper approach" achieves up to 76–80 % less power consumption.

New low-power techniques: Leakage Feedback with Stack & Sleep Stack with Keeper

In this work an attempt has been made to analyze the scaling limits of Double Gate (DG) underlap and Triple Gate (TG) overlap FinFET structure using 2D and 3D computer simulations respectively. To analyze the scaling limits of FinFET structure, simulations are performed using three variables: finthickness, fin-height and gate-length. From 2D simulation of DG FinFET, it is found that the gate-length (L) and fin-thickness (T fin ) ratio plays a key role while deciding the performance of the device. Drain Induced Barrier Lowering (DIBL) and Subthreshold Swing (SS) increase abruptly when (L/T fin ) ratio goes below 1.5. So, there will be a trade-off in between SCEs and on- current of the device since on-off current ratio is found to be high at small dimensions. From 3D simulation study on TG FinFET, It is found that both fin-thickness (T fin ) and fin-height (H fin ) can control the SCEs. However, T fin is found to be more dominant parameter than H fin while deciding the SCEs. DIBL and SS increase as (L eff /T fin ) ratio decreases. The (L eff /T fin ) ratio can be reduced below 1.5 unlike DG FinFET for the same SCEs. However, as this ratio approaches to 1, the SCEs can go beyond acceptable limits for TG FinFET structure. The relative ratio of H fin and T fin should be maximum at a given T fin and L eff to get maximum on-current per unit width. However, increasing H fin degrades the fin stability and degrades SCEs.

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Gaurav Saini

Papers

Stubble burning: Effects on health & environment, regulations and management practices

Implementation of data intelligence models coupled with ensemble machine learning for prediction of water quality index

Use of natural coagulants for industrial wastewater treatment.

New low-power techniques: Leakage Feedback with Stack & Sleep Stack with Keeper

Physical Scaling Limits of FinFET Structure: A Simulation Study