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The increased reach of health programs in India, during the past few decades, has significantly contributed to declining in postnatal mortality including the infant, child & other mortality. However, reduction in neonatal mortality remained negligible. About 70% neonatal deaths take place within a week after birth. The prime objective of this study is to explore the death clustering of the neonates and its determinants in India. 3rd round of National Family Health Survey (NFHS-3), India, 2005-06 data was used for this study. Bivariate analysis followed by multivariate analysis (Binary logistic regression) was performed to identify the determinants of neonatal mortality. Moran’s I & Univariate LISA cluster map was used to explore the spatial clusters of neonatal deaths in India. Univariate Moran’s I (Moran’s I=0.215) was significant i.e. spatial dependence exists for neonatal deaths in Indian states. The Univariate LISA cluster map explored significant hotspots of neonatal deaths which were Bihar, Chhattisgarh, Jharkhand, MP, Odisha, Rajasthan, UP and WB. The estimated odds of neonatal death was 2.75 times higher (OR=2.75; 95% CI: 2.21-3.43) among smaller size neonates than the average & larger size neonates. The odds of neonatal death was found 2.39 times, 2.73 times & 1.84 times higher among those mothers who had an illiterate, primary & secondary level of education as compared to mothers who had higher education. The risk of neonatal death among 1st (OR=1.43) and more than 4th (OR=1.35) order births was positively higher than 2nd to 3rd order births. Based on the findings, the study proposes various approaches to address the increasing contribution of neonatal deaths in India. The findings suggest that raising mother education & providing a healthy diet to pregnant women, can bring a quick substantial reduction of neonatal mortality and the target fixed can be achieved. So, it is necessary to encourage & support women for higher education. This study proposes to provide the combination of the continuum care for maternal, neonatal, and child health by integrating a family-community based service delivery approach with the existing health care system especially to the death clusters in India.

Triphenylphosphine [TPP] used in synthesis of organic and organo metallic compounds is investigated for its fundamental reactive properties by density functional theory [DFT] calculations. Natural bond orbital (NBO) analysis enables in comprehending the stability and charge delocalization in the title molecule. Hirshfeld surface analysis for visually analyzing intermolecular interactions in crystal structures employing surface contours and 2D fingerprint plots has been used to scrutinize molecular shapes. Besides NLO, Frontier molecular orbitals and global reactivity descriptors values are calculated. Molecular electrostatic potential map, Fukui Function, Mulliken atomic charges, natural population analysis, Atomic Polar tensors and Thermodynamic analysis were performed. The solvent effects were investigated for obtained molecular energies, hardness and atomic charge distributions were studied for the title compound at TD-DFT method. The binding activity of the molecule with biological targets was examined by docking analysis.

Over 70% of the photovoltaic (PV) systems are designed with transformers which are galvanic isolations. However, such inverters are big, heavy and expensive with low efficiency. In this work, a transformer-less PV system is introduced. It is smaller, lighter, and cheaper with higher efficiency as compared to the transformer of the same rating. The proposed inverter employs push pull circuit, an H bridge circuit, the oscillating circuit, an automatic changeover dual battery bank and an RF remote control circuit unit. The switching technique of the proposed inverter consists of a pulse width modulation system along with grid synchronization condition. As the suggested method is entirely transformer-less, there is a reduction in transformer loss which tremendously reduces the total harmonic distortion (THD) to even less than1% with an assumption of; inductor is ideal without any internal resistance, the switches and diodes are ideal with the dead line between the switches are neglected. A filtering capacitor provides a nearly constant output current which stabilizes the system rapidly and reduces harmonics generated by the switching circuit. Overall performance of the proposed inverter was simulated with PROTEUS and validated with MATLAB which produced a pure sinusoidal waveform as the output voltage. The proposed inverter minimizes size and increases the inverter efficiency to 90% which can be used in our homes, offices and schools for lightening and charging.

The study aimed at designing an efficient low cost poultry feather plucker with the main objective of ensuring that the machine improves the hygiene, food safety and defeathering processes in poultry meat production. The machine is made up of four main parts viz: the frame, prime mover, plucker drum, and plucker fingers. The study reveals that for the aim to be realized, an electric motor of 0.5hp with 2300rpm is needed to transmit a torque of 1226.25Nmm through a mild steel shaft of 10mm diameter to a plucker drum of mass 2.5kg which has 24 polypropylene plucker fingers mounted on it. The study estimated the cost of producing the machine to be $98 and considers the design safe since the FoS of the drum has a minimum value of 8 and a maximum value of 56; shear strength of the drum falls below the shear stress of Aluminum

With the increase in the number of mobile applications in the day to day life, essential thing is to keep track as to which ones are safe and which ones aren’t. One can’t judge how safe and true each application is based only on the reviews that are mentioned for each application. Hence it is a need to keep track and develop a system to make sure the applications present are genuine or not. The objective is to develop a system in detecting fraud applications before the user downloads by using machine learning. Sentimental analysis is to help in determining the emotional tones behind words which are expressed in online. This method is useful in monitoring social media and helps to get a brief idea of the public’s opinion on certain issues. The user cannot always get correct or true reviews about the product on the internet. We can check for user’s sentimental comments on multiple application. The reviews may be fake or genuine. Analyzing the rating and reviews together involving both user and admins comments, we can determine whether the application is genuine or not. Using machine learning, the machine is able to learn and analyze the sentiments, emotions about reviews and other texts. The manipulation of review is the key aspects of Application ranking fraud. By using Machine Learning, analyzing reviews and comments can help to determine the correct application for both Android and iOS platforms.

A profitable banking sector is better able to withstand negative shocks and contribute to the stability of the financial system. The importance of bank profitability can be appraised at the micro and macro levels of the economy. At the micro level, profit is determined by bank’s management decisions and policy objectives, while the macroeconomic determinants look at variables that reflect the economic and legal environment where the credit institution operates. Bank profitability, typically measured by the return on assets (ROA) and/or the return on equity (ROE), and/or net interest margin (NIM) is usually expressed as a function of internal and external determinants. These issues engaged the minds of the authors in this paper. Industry related dataset that covers a 10year period of time was used. The regression results indicate that bank-specific characteristics and macroeconomic variables explain up to 97.4% variations in bank profitability when NIM was used as a dependent variable. Summarily, profitability was found to be associated with well-capitalised banks as capital ratio has a positive significant relationship with NIM; bank size has a negative but significant relationship with NIM; Asset composition has a positive but an insignificant relationship with NIM; Liquidity has a negative and insignificant relationship with NIM; all the macroeconomic variables apart from inflation have a negative and insignificant relationship with NIM. Therefore, the study recommends that regulatory authorities should promote policies that will bring about low inflation and stable economic output growth, whereas, bank managements should concentrate more on cost and non-performing loans reduction and asset composition diversification.

Malnutrition in under five is a major concern in developing countries including Somalia. More than 1 billion people are malnourished and malnutrition contributes to more than 30% of all deaths in children below five years. This study will investigate determinants of malnutrition in children under five years old in Mogadishu-Somalia at Banadir and S0S Hospitals. The specific objectives are: to identify how income level of household influences determines malnutrition in children under five years old; how health education determines malnutrition in children under five years old and finally to find out how dietary intake determines malnutrition in children under five years old. The study involves a design for the collection, measurement and analysis of data. The population in study is 450, and its sample size is 212 and main data collection tool is a semi structured administered questionnaire. Qualitative data were analyzed on content matter of the responses. Quantitative data were coded and entered into Statistical Package for social Scientist (SPSS Version 22) using multiple Regression tool for analyzing the data. The result was presented in the form of summaries, such as statistical tables and discussions and illustrations. The study findings are useful for the health workers as reference in the determinants of malnutrition for children under five old and the community at large. The study findings showed that 77% of the respondents agreed that the income level of household affects child nutrition while 23% of the respondents disagreed. The study findings indicated that 21% of respondents had gone to the nutritionist 'once', 9% of them had gone to the nutritionist 'twice', 11% of them visited the nutritionist '3 times' while 4% of them had gone to nutritionist 'above 3 times' while 55% of them had 'never gone to a nutritionist. Education training on nutrition plays a very significant role in reducing malnutrition. Study findings indicated that 2% of the mothers with malnourished children breast-fed their children to provide their children balanced diet because breast milk for first six months is balanced diet. 85% of the them breast fed their children to protect them diseases. 13% of them breast-fed their children to take part their proper growth. The researcher is recommending that Income growth alone will not reduce rates of malnutrition, and so direct interventions to tackle malnutrition is needed. Things such as vitamin, mineral and micronutrient supplementation; kangaroo mother care, early initiation of breastfeeding, promotion of dietary diversity; community-based nutrition education, and school feeding programmes. Education may change women's preferences about the quantity versus the quality of children, with educated women choosing fewer children but of better "quality". Mother’s education has a greater impact on the educational attainment and school achievement of children than father's education.

Anaemia is a nutritional problem affecting all segments of the population in general and children, woman & pregnant woman in particular. In the latter groups, prevalence of anaemia may be as high as 60 – 70 per cent. Anaemia in our country is essentially due to iron deficiency although in children, woman & pregnant woman, folate deficiency also plays a part. Although our diets contain fairly good amount of iron, its absorption is very poor (2- 3 per cent).9 Micronutrient malnutrition commonly referred as “Hidden Hunger”, causes learning disabilities, impaired work capacity, illness & ultimately death. Forty per cent of the world suffers from iron deficiency.

A methodology based on flame atomic absorption spectrometry (FAAS) was developed and validated to quantify lithium in spodumene mineral sample. Validation parameters, including linearity and range, precision, accuracy, limit of detection (LOD) and limit of quantification (LOQ), were evaluated. The method is linear over 1.0 – 9.0 µg mL-1, with a coefficient of correlation (r) > 0.999. The LOD and LOQ were 0.2 ?g mL-1 and 0.7 ?g mL-1. This method is very precise; intraday precision measurements had a relative standard deviation (RSD) value of 4.00 %. This RSD value was lower than that required by Horwitz. The mean recovery percentage was 99.06 %, indicating that this method could accurately quantify the lithium in the studied mineral. The percentage of lithium oxide in the spodumene mineral sample was 0.33 –0.39%.

Altogether 272 species and infraspecific taxa of algae and cyanobacteria were identified in the Enguri River habitats during 1974-1977, and 2014 field trips. Total list of algal flora including our findings and reference lists is represented by 339 taxa (excluding diatoms) and most of them were bio-indicators. Charophyta, Cyanobacteria and Chlorophyta species were dominated in communities. Altitude play the major role in distribution patterns of algal diversity and ecological groups of water quality indicators.