A Moderate Increase of Physiological CO2 in a Critical Range during Stable NREM Sleep Episode: A Potential Gateway to REM Sleep

Sleep is characterized as rapid eye movement (REM) and non-rapid eye movement (NREM) sleep. Studies suggest that wake-related neurons in the basal forebrain, posterior hypothalamus and brainstem, and NREM sleep-related neurons in the anterior-hypothalamic area inhibit each other, thus alternating sleep–wakefulness. Similarly, pontine REM-ON and REM-OFF neurons reciprocally inhibit each other for REM sleep modulation. It has been proposed that inhibition of locus coeruleus (LC) REM-OFF neurons is pre-requisite for REM sleep genesis, but it remains ambiguous how REM-OFF neurons are hyperpolarized at REM sleep onset. The frequency of breathing pattern remains high during wake, slows down during NREM sleep but further escalates during REM sleep. As a result, brain CO2 level increases during NREM sleep, which may alter REM sleep manifestation. It has been reported that hypocapnia decreases REM sleep while hypercapnia increases REM sleep periods. The groups of brainstem chemosensory neurons, including those present in LC, sense the alteration in CO2 level and respond accordingly. For example, one group of LC neurons depolarize while other hyperpolarize during hypercapnia. In another group, hypercapnia initially depolarizes but later hyperpolarizes LC neurons. Besides chemosensory functions, LC REM-OFF neurons are an integral part of REM sleep executive machinery. We reason that increased CO2 level during a stable NREM sleep period may hyperpolarize LC neurons including REM-OFF, which may help initiate REM sleep. We propose that REM sleep might act as a sentinel to help maintain normal CO2 level for unperturbed sleep

Simulation-Optimization for Conjunctive Water Resources Management and Optimal Crop Planning in Kushabhadra-Bhargavi River Delta of Eastern India

Water resources sustainability is a worldwide concern because of climate variability, growing population, and excessive groundwater exploitation in order to meet freshwater demand. Addressing these conflicting challenges sometimes can be aided by using both simulation and mathematical optimization tools. This study combines a groundwater-flow simulation model and two optimization models to develop optimal reconnaissance-level water management strategies. For a given set of hydrologic and management constraints, both of the optimization models are applied to part of the Mahanadi River basin groundwater system, which is an important source of water supply in Odisha State, India. The first optimization model employs a calibrated groundwater simulation model (MODFLOW-2005, the U.S. Geological Survey modular ground-water model) within the Simulation-Optimization MOdeling System (SOMOS) module number 1 (SOMO1) to estimate maximum permissible groundwater extraction, subject to suitable constraints that protect the aquifer from seawater intrusion. The second optimization model uses linear programming optimization to: (a) optimize conjunctive allocation of surface water and groundwater and (b) to determine a cropping pattern that maximizes net annual returns from crop yields, without causing seawater intrusion. Together, the optimization models consider the weather seasons, and the suitability and variability of existing cultivable land, crops, and the hydrogeologic system better than the models that do not employ the distributed maximum groundwater pumping rates that will not induce seawater intrusion. The optimization outcomes suggest that minimizing agricultural rice cultivation (especially during the non-monsoon season) and increasing crop diversification would improve farmers’ livelihoods and aid sustainable use of water resources

Understanding the evolution of catalytically active multi-metal sites in a bifunctional high-entropy alloy electrocatalyst for zinc–air battery application

Zinc–air batteries are known for high theoretical energy density and environmental friendliness. The successful commercial utilization of rechargeable zinc–air batteries is limited by unstable electrochemical interfaces and sluggish kinetics with poor round-trip efficiency. In this study, we report a nanocrystalline high entropy alloy (HEA) comprising Cu–Co–Mn–Ni–Fe (CCMNF) prepared by casting-cum-cryomilling method. This multi-component HEA embodies multiple catalytically active sites with diverse functionalities, thus enhancing the electrochemical redox reactions, e.g., oxygen reduction (ORR) and oxygen evolution reaction (OER). The bifunctional electrocatalytic performance of this HEA is comparable to that of standard catalysts, RuO2 and Pt/C, as evidenced by low overpotential requirements towards OER and ORR. The HEA was tested for use in the air electrode catalyst in the zinc–air battery, where it performed stable oxygen electrocatalysis that was durable over 1045 charging–discharging cycles for ∼90 hours of continuous operation. The microstructural analysis of HEA at different time scales (0, 24, 87 h) during the zinc–air battery operation suggested a dynamic participation of multiple metal active sites on the catalyst surface. Detailed studies revealed that despite leaching in harsh alkaline operation conditions, the synergistic electronic interactions between the component metal sites sustained good electrocatalytic performance and promoted oxygen electrocatalysis through the modification of electronic and chemical properties

Spatial and temporal variability of rainfall in the Gandaki River Basin of Nepal Himalaya

Landslides, floods, and droughts are recurring natural disasters in Nepal related to too much or too little water. The summer monsoon contributes more than 80% of annual rainfall, and rainfall spatial and inter-annual variation is very high. The Gandaki River, one of the three major rivers of Nepal and one of the major tributaries of the Ganges River, covers all agro-ecological zones in the central part of Nepal. Time series tests were applied for different agro-ecological zones of the Gandaki River Basin (GRB) for rainfall trends of four seasons (pre-monsoon, monsoon, post-monsoon and winter) from 1981 to 2012. The non-parametric Mann-Kendall and Sen’s methods were used to determine the trends. Decadal anomalies relative to the long-term average were analyzed using the APHRODITE precipitation product. Trends in number of rainy days and timing of the monsoon were also analyzed. We found that the post-monsoon, pre-monsoon and winter rainfalls are decreasing significantly in most of the zones but monsoon rainfall is increasing throughout the basin. In the hill region, the annual rainfall is increasing but the rainy days do not show any trend. There is a tendency toward later departure of monsoon from Nepal, indicating an increase in its duration. These seasonally and topographically variable trends may have significant impacts for the agriculture and livestock smallholders that form the majority of the population in the GRB

Mortality and pulmonary complications in patients undergoing surgery with perioperative SARS-CoV-2 infection: an international cohort study

Background: The impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on postoperative recovery needs to be understood to inform clinical decision making during and after the COVID-19 pandemic. This study reports 30-day mortality and pulmonary complication rates in patients with perioperative SARS-CoV-2 infection. Methods: This international, multicentre, cohort study at 235 hospitals in 24 countries included all patients undergoing surgery who had SARS-CoV-2 infection confirmed within 7 days before or 30 days after surgery. The primary outcome measure was 30-day postoperative mortality and was assessed in all enrolled patients. The main secondary outcome measure was pulmonary complications, defined as pneumonia, acute respiratory distress syndrome, or unexpected postoperative ventilation. Findings: This analysis includes 1128 patients who had surgery between Jan 1 and March 31, 2020, of whom 835 (74·0%) had emergency surgery and 280 (24·8%) had elective surgery. SARS-CoV-2 infection was confirmed preoperatively in 294 (26·1%) patients. 30-day mortality was 23·8% (268 of 1128). Pulmonary complications occurred in 577 (51·2%) of 1128 patients; 30-day mortality in these patients was 38·0% (219 of 577), accounting for 81·7% (219 of 268) of all deaths. In adjusted analyses, 30-day mortality was associated with male sex (odds ratio 1·75 [95% CI 1·28–2·40], p\textless0·0001), age 70 years or older versus younger than 70 years (2·30 [1·65–3·22], p\textless0·0001), American Society of Anesthesiologists grades 3–5 versus grades 1–2 (2·35 [1·57–3·53], p\textless0·0001), malignant versus benign or obstetric diagnosis (1·55 [1·01–2·39], p=0·046), emergency versus elective surgery (1·67 [1·06–2·63], p=0·026), and major versus minor surgery (1·52 [1·01–2·31], p=0·047). Interpretation: Postoperative pulmonary complications occur in half of patients with perioperative SARS-CoV-2 infection and are associated with high mortality. Thresholds for surgery during the COVID-19 pandemic should be higher than during normal practice, particularly in men aged 70 years and older. Consideration should be given for postponing non-urgent procedures and promoting non-operative treatment to delay or avoid the need for surgery. Funding: National Institute for Health Research (NIHR), Association of Coloproctology of Great Britain and Ireland, Bowel and Cancer Research, Bowel Disease Research Foundation, Association of Upper Gastrointestinal Surgeons, British Association of Surgical Oncology, British Gynaecological Cancer Society, European Society of Coloproctology, NIHR Academy, Sarcoma UK, Vascular Society for Great Britain and Ireland, and Yorkshire Cancer Research

Identifying sources of groundwater contamination in a hard-rock aquifer system using multivariate statistical analyses and GIS-based geostatistical modeling techniques

Study region: The study area is Udaipur district, which is situated in hard-rock hilly terrain of Rajasthan, India. Study focus: In this study, spatio-temporal variations of fifteen groundwater quality parameters are explored by box–whisker plots, trends are detected and quantified, and GIS-based groundwater quality index (GQI) is computed. For the first time, scores of principal component analysis (PCA) are combined with GIS-based geostatistical modeling by following a sound methodology in comprehensive manner to identify sources of groundwater contamination. New hydrological insights for the region: Box–whisker plots revealed linkages between rainfall and groundwater quality, which were further verified by GQI ranging from 69 to 76 in Cluster I and from 73 to 78 in Cluster II. Cluster analysis identified two clusters of sites based on groundwater contamination controlled by geology. Significantly increasing trends are indicated (p < 0.05) at most sites in fluoride, sodium, EC and TDS, but significantly decreasing trends in silica at 40% sites indicate a possibility of replacement of older groundwater with recent rainfall recharge. Spatial distribution of increasing trends is affected by anthropogenic processes. Sen's method indicated increasing rates for calcium, magnesium, sodium, iron, bicarbonate, sulphate, fluoride, TDS, hardness and EC. PCA results indicated occurrence of groundwater contamination in Cluster I by anthropogenic sources and presence of natural/geogenic processes in Cluster II. Significant PCs, viz. major ion and soil leaching pollution factors, govern overall evolution of geochemical processes

Assessing groundwater quality for drinking water supply using hybrid fuzzy-GIS-based water quality index

Groundwater is a vital source of freshwater in both urban and rural regions of the world. However, its injudicious abstraction and rapidly increasing contamination are posing a severe threat for sustainable water supply worldwide. Geographical Information System (GIS)-based groundwater quality evaluation using Groundwater Quality Index (GQI) has been proved to be a cost-effective tool for assessing groundwater quality and its variability at a larger scale. However, the conventional GQI approach is unable to deal with uncertainties involved in the assessment of environmental problems. To overcome this limitation, a novel hybrid framework integrating Fuzzy Logic with the GIS-based GQI is proposed in this study for assessing groundwater quality and its spatial variability. The proposed hybrid framework is demonstrated through a case study in a hard-rock terrain of Southern India using ten prominent groundwater-quality parameters measured during pre-monsoon and post-monsoon seasons. Two conventional GIS-based GQI models GQI-10 (using all the ten groundwater-quality parameters) and GQI-7 (using seven ‘concerned/critical’ groundwater-quality parameters) as well as hybrid Fuzzy-GIS-based GQI (FGQI) models (using seven critical parameters) were developed for the two seasons and the results were compared. The Trapezoidal membership functions classified the model input parameters into ‘desirable’, ‘acceptable’ and ‘unacceptable’ classes based on the experts’ knowledge and water quality standards for drinking purposes. The concentrations of Ca2+, Mg2+, and SO42− in groundwater were found within the WHO desirable limits for drinking water throughout the year, while the concentrations of seven parameters (TDS, NO3−-N, Na+, Cl−, K+, F− and Hardness) exceed their permissible limits during pre-monsoon and post-monsoon seasons. A comparative evaluation of GQI models revealed that the FGQI model predicts groundwater quality better than the conventional GQI-10 and GQI-7 models. GQI modeling results suggest that the groundwater of most of eastern and southern parts (∼60% in pre-monsoon season; ∼90% in post-monsoon season) of the study area is unsuitable for drinking. Further, the groundwater quality deteriorates during post-monsoon seasons compared to pre-monsoon seasons, which indicates an increased influx of contaminants from different industries, mining areas, waste disposal sites and agricultural fields during monsoon seasons. This finding calls for the strict enforcement of regulations for proper handling of effluents from various contamination sources in the study area. It is concluded that the fuzzy logic-based decision-making approach (FGQI) is more reliable and pragmatic for groundwater-quality assessment and analysis at a larger scale. It can serve as a useful tool for the water planners and decision makers in efficiently monitoring and managing groundwater quality at watershed or basin scales.ISSN:0043-1354ISSN:1879-244