Analyzing Performance for Generating Power with Renewable Energy Source using Rice Husk as an Alternate Fuel

Energy demand is increasing continuously due to sharp growth in population and industrial development. The development and installation of energy sources are not keeping pace with spiraling demand of energy. Although energy production has increased manifold but still there is big gap between production and demand. The major energy demand is met by conventional energy sources like coal, petroleum, diesel, and natural gas etc. This causes depletion of fossil fuel reserve and environmental pollution. The use of fossil fuel not only causes environmental impact but also energy security problem. Energy from biomass is renewable energy, being looked at as an alternative of fossil fuel. One of the biomass energy sources is rice husk, which is a very promising renewable energy source as it is indigenous and has environmental benefits. However, the environmental and financial profiles of the electricity generation from biomass must be assessed to ensure reduction in greenhouse gas emission and positive cash flow. Environmental impact potential from rice husk is generally lesser than fossil fuel plants. A dual fuel diesel engine-generation of 800 kW, using rice husk gasifier, is considered for the analysis purpose. Keywords: Renewable energy, Rice husk, Gasification, Dual fuel generation, Energy model, GHG (Green House Gas) emission

Reversible single-crystal to single-crystal transformations in a Hg(II) derivative. 1D-polymeric chain ⇋ 2D-networking as a function of temperature

Reactions of HgX2 (X = Cl-, Br-, l-) with the ligand hep-H (hep-H = 2-(2-hydroxyethyl)pyridine) in methanol at 298 K result in 1D-polymeric chains of [(X)Hg(μ-X)2(hep-H)]∞, 1-3, respectively, where hep-H binds to the Hg(II) ions in a monodentate fashion exclusively with the pyridine nitrogen donor and the suitably ortho-positioned -(CH2)2OH group of hep-H remains pendant. The packing diagrams of 1-3 exhibit extensive intramolecular and intermolecular hydrogen bonding interactions leading to hydrogen bonded 2D network arrangement in each case. Though the single crystal of either 2 (X = Br) or 3 (X = I) loses crystallinity upon heating, the single crystal of 1 selectively transforms to a 2D-polymeric network, 4 on heating at 383 K for 1.5 h. The polymeric 4 consists of central dimeric [Hg(μ3-Cl)(hep-H)Cl]2 units, which are covalently linked with the upper and lower layers of [-(μ-Cl)2-Hg-(μ-Cl)2-Hg(μ-Cl)2-]n. The packing diagram of 4 reveals the presence of O-H-Cl and C-H-Cl hydrogen bonding interactions which in effect yields hydrogen bonded 3D-network. Remarkably, the single crystals of 4 convert back to the single crystals of parent 1 on standing at 298 K for three days

Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980-2017: a systematic analysis for the Global Burden of Disease Study 2017.

BACKGROUND: Global development goals increasingly rely on country-specific estimates for benchmarking a nation's progress. To meet this need, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 estimated global, regional, national, and, for selected locations, subnational cause-specific mortality beginning in the year 1980. Here we report an update to that study, making use of newly available data and improved methods. GBD 2017 provides a comprehensive assessment of cause-specific mortality for 282 causes in 195 countries and territories from 1980 to 2017. METHODS: The causes of death database is composed of vital registration (VR), verbal autopsy (VA), registry, survey, police, and surveillance data. GBD 2017 added ten VA studies, 127 country-years of VR data, 502 cancer-registry country-years, and an additional surveillance country-year. Expansions of the GBD cause of death hierarchy resulted in 18 additional causes estimated for GBD 2017. Newly available data led to subnational estimates for five additional countries-Ethiopia, Iran, New Zealand, Norway, and Russia. Deaths assigned International Classification of Diseases (ICD) codes for non-specific, implausible, or intermediate causes of death were reassigned to underlying causes by redistribution algorithms that were incorporated into uncertainty estimation. We used statistical modelling tools developed for GBD, including the Cause of Death Ensemble model (CODEm), to generate cause fractions and cause-specific death rates for each location, year, age, and sex. Instead of using UN estimates as in previous versions, GBD 2017 independently estimated population size and fertility rate for all locations. Years of life lost (YLLs) were then calculated as the sum of each death multiplied by the standard life expectancy at each age. All rates reported here are age-standardised

Abstract 10932: Prediction of 30-Day Hospital Readmission in High-Risk Atherosclerotic Cardiovascular Disease Patients Using Machine Learning Methods on Electronic Health Record Data from Medical Information Mart for Intensive Care-3 Database

Introduction: Despite significant therapeutic advancements, Atherosclerotic Cardiovascular Disease (ASCVD) patients require frequent hospitalization. Machine learning (ML) algorithms present an opportunity to develop improved and more generalizable prediction models for 30-day hospital readmission due to ASCVD. Objectives: The current study aims to leverage electronic health record (EHR) data to predict 30-day hospital readmission in high-risk ASCVD patients. Methods: This study utilized the MIMIC III database (a publicly available large, single-centre critical care database of 46,520 patients) comprising of deidentified ~60,000 ICU admissions. Adult patients with the first admission due to ASCVD event and whose length of stay (LOS) in the ICU was >48 hours were included. To develop a prediction model, features representing groups of diagnosis data along with demographics and length of stay in the hospital were used. The performance of ML models was evaluated using the area under the receiver operating characteristic curves (AUCs). Results: Our cohort consisted of 22,666 admissions (mean age 70.1 years) due to an ASCVD event. Out of the 9022 readmissions within 180 days, 60.5% were observed within 30 days of discharge. Among the 17 prospective predictors age, LOS and first hospitalization due to coronary atherosclerosis, heart failure, and haemorrhage issues were the most important factors to predict readmission within 30 days (Fig A). Random Forest was the best performing model with an AUC of 0.66 (Fig B). Conclusions: This model can be helpful in predicting the readmission of high-risk patients after the first ASCVD event which might address the huge unmet need of aiding healthcare resource planning, better patient care, and prevention of rehospitalization and death by intensifying treatment interventions in those patients and taking appropriate decisions to discharge patients based on their age, LOS and ASCVD events resulting in first hopitalization

Varying structural motifs in oxyanions (NO<SUB>3</SUB><SUP>−</SUP>, CO<SUB>3</SUB><SUP>2−</SUP>) and phenoxyacetate (PhOAc<SUP>−</SUP>) bridged coordination polymers derived from alkoxo-bridged dicopper building blocks with {Cu<SUB>2</SUB>O<SUB>2</SUB>} core

The oxyanions (NO3−, CO32−) and phenoxyacetate (PhOAc−) bridged three 1D-coordination polymeric chains, {[Cu2(μ-hep)2(μ-NO3)]2}n (1), {[Cu2(μ-hep)2(H2O)2]·2H2O(μ-CO3)}n (3) and {[Cu2(μ-hep)2(μ-PhOAc−)]2}n (2) (hep-H = 2-(2-hydroxyethyl)pyridine) have been synthesized. In 1-3 the alkoxide bridged dicopper building units, [Cu(μ-hep)]2 with Cu2O2 core, are linked via the respective anions. Detailed structural analysis reveals that in 1 or 2, two units of NO3− (1) or PhOAc− (2), respectively, bind with the four copper ions in two adjacent alkoxide bridged dimeric units in head-to-head and tail-to-tail fashion and the same binding mode continues along the polymeric chain. This in effect yields a 12-membered metallacyclic ring in between two dimeric core units. However, in 3 only one CO32− group bridges the two copper centres associated with the two neighbouring alkoxide bridged dimeric units in head-to-tail mode which in turn forms a zig-zag polymeric chain. Two coordinated and two lattice water molecules from two adjacent polymeric layers in the structure of 3 form water tetramers. Furthermore, the interaction of water tetramer with the uncoordinated -C=O group of the bridging CO32− develops an additional zig-zag chain which is being trapped between the two outer zig-zag coordination polymeric chains in 3. The polymeric chains in 1-3 further develop a 2D-network pattern via an extensive non-covalent hydrogen bonding as well as C-H···π and π···π interactions

Continuous, Automated Breathing Rate and Body Motion Monitoring of Rats With Paraquat-Induced Progressive Lung Injury

Assessments of respiratory response and animal activity are useful endpoints in drug pharmacology and safety research. We investigated whether continuous, direct monitoring of breathing rate and body motion in animals in the home cage using the Vum Digital Smart House can complement standard measurements in enabling more granular detection of the onset and severity of physiologic events related to lung injury in a well-established rodent model of paraquat (PQ) toxicity. In rats administered PQ, breathing rate was significantly elevated while body motion was significantly reduced following dosing and extending throughout the 14-day study duration for breathing rate and at least 5 days for both nighttime and daytime body motion. Time course differences in these endpoints in response to the potential ameliorative test article bardoxolone were also readily detected. More complete than standard in-life measurements, breathing rate and body motion tracked injury progression continuously over the full study time period and aligned with, and informed on interval changes in clinical pathology. In addition, breathing rates correlated with terminal pathology measurements, such as normalized lung weights and histologic alveolar damage and edema. This study is a preliminary evaluation of the technology; our results demonstrate that continuously measured breathing rate and body motion served as physiologically relevant readouts to assess lung injury progression and drug response in a respiratory injury animal model