Electromagnetic interference shielding effectiveness of copper plated fabrics

Electroless plating of copper on cotton and polyester fabrics has been done with varying CuSO4 concentration (8, 12, 16 and 20 g/L) and temperature (30°, 40°, 50° & 60° C) for 30min at all levels. The plating depositions are characterized by scanning electron microscope and X-ray diffraction respectively. The physical properties, such as tensile strength, tear strength, abrasion resistance and electromagnetic interference shielding performances have also been investigated. It is found that the tensile and tear strength of cotton and polyester fabrics decrease with the increase in CuSO4 concentration. The abrasion resistance of copper plated cotton fabric decreases more than that of polyester fabric. The surface resistance of the copper plated polyester fabric shows poor electrical resistance and the electromagnetic interference shielding effectiveness, but has high shielding effectiveness up to 30dB than cotton fabrics

Characterization of Calcium Phosphate Chitosan Nanocomposite as Plant Growth Promoter

In this study, calcium phosphate-chitosan nanocomposite (CaP-CS NC) was prepared by a convenient and affordable co-precipitation method, and the prepared NC was tested for agriculture application.  Physico-chemicals analyses of the CaP-CS NC were conducted by X-ray diffraction (XRD), scanning electron microscope with energy dispersive X-ray spectroscopy (SEM-EDS), Fourier transform infrared spectroscopy (FTIR), and ultraviolet-visible spectroscopy (UV-Vis) instruments to determine the structural characteristics, surface topology, chemical composition, function group, and optical properties. The XRD pattern of CaP-CS NC revealed that the average crystallite size was 43 nm. The SEM images showed agglomeration of the CaP-CS NC with a rod-like shape. The EDS spectrum of the CaP-CS NC indicated the presence of Ca, P, O, and N elements. FTIR displayed vibrational peaks for the active functional group such as carboxylic (C=O), amines (N-H), hydroxyl (O-H), and alkyne (C-H). Furthermore, the spectrum of CaP-CS NC showed the bending mode of phosphates at 588.37 cm-1 and 508.45 cm-1. The UV-Vis-NIR spectrum of the prepared nanocomposite indicates the anti-reflection properties, which might be useful in solar cell applications to increase the efficiency of the solar cell. In addition, the prepared CaP-CS NC was tested for the plant growth stimulator properties at the lab scale level, wherein it exhibited substantial growth. Accordingly, the current study suggests that the prepared CaP-CS NC could be used as a plant growth promoter

Solar Power Prediction Using Machine Learning

This paper presents a machine learning-based approach for predicting solar power generation with high accuracy using a 99% AUC (Area Under the Curve) metric. The approach includes data collection, pre-processing, feature selection, model selection, training, evaluation, and deployment. High-quality data from multiple sources, including weather data, solar irradiance data, and historical solar power generation data, are collected and pre-processed to remove outliers, handle missing values, and normalize the data. Relevant features such as temperature, humidity, wind speed, and solar irradiance are selected for model training. Support Vector Machines (SVM), Random Forest, and Gradient Boosting are used as machine learning algorithms to produce accurate predictions. The models are trained on a large dataset of historical solar power generation data and other relevant features. The performance of the models is evaluated using AUC and other metrics such as precision, recall, and F1-score. The trained machine learning models are then deployed in a production environment, where they can be used to make real-time predictions about solar power generation. The results show that the proposed approach achieves a 99% AUC for solar power generation prediction, which can help energy companies better manage their solar power systems, reduce costs, and improve energy efficiency.Comment: 7 page

Review of Hybrid Wind-Solar PV Technology in the Generation of Electricity

Achieving sustainability by utilizing alternative energy sources viable technological possibilities for creating sustainable energy, the sun, biomass, wind, geothermal resources, hydropower, and ocean resources are considered. Despite the fact that the total amount of energy produced by PV cells and wind turbines is still far less than that of fossil fuels, their ability to generate electricity has significantly expanded in recent years. This article provides an overview of the Solar-Wind hybrid power system, which generates electricity by combining the Sun and Wind, two renewable energy sources. Microcontrollers are widely used in the field of system management. We can maximize the utilization of those resources by employing this strategy, which takes into account the distinct production processes of each resource. Furthermore, it increases dependability and decreases reliance on any single input. This hybrid solar-wind power generation system is suitable for both industrial and residential applications

A multi-dimensional study to estimate the behaviour of the general public during COVID-19 pandemic

Background: The COVID-19 pandemic has had a significant impact on societies all over the world, leading to significant shifts in individual behavior as well as societal norms. The goal of this study was to provide an in-depth look at the many different aspects of public behavior during the COVID-19 pandemic. Methods: Demographic information, COVID-19 knowledge and awareness, prevention adherence, vaccination attitudes, and psychological well-being as a whole were all be gathered through the quantitative survey. The subjective meetings will give further bits of knowledge into the hidden inspirations, discernments, and difficulties faced by people in following general wellbeing rules. Results: To find patterns and correlations among the various variables, statistical methods like regression analysis, factor analysis, and clustering algorithms were used in the data analysis. The subjective information was investigated specifically, separating key topics and accounts that shed light on the subtleties of the public’s way of behaving during the pandemic. Conclusions: In the end, the goal of this multidimensional study was to help make decisions based on evidence and come up with plans to improve public health and lessen the impact of infectious disease outbreaks like COVID-19

Maternal antecedents of adiposity and studying the transgenerational role of hyperglycemia and insulin (MAASTHI): a prospective cohort study : Protocol of birth cohort at Bangalore, India.

BACKGROUND: India is experiencing an epidemic of obesity-hyperglycaemia, which coincides with child bearing age for women. The epidemic can be sustained and augmented through transgenerational transmission of adiposity and glucose intolerance in women. This presents an opportunity for exploring a clear strategy for the control of this epidemic in India. We conducted a study between November 2013 and May 2015 to inform the design of a large pregnancy cohort study. Based on the findings of this pilot, we developed the protocol for the proposed birth cohort of 5000 women, the recruitment for which will start in April 2016. The protocol of the study documents the processes which aim at advancing the available knowledge, linking several steps in the evolution of obesity led hyperglycemia. METHODS: Maternal Antecedents of Adiposity and Studying the Transgenerational role of Hyperglycemia and Insulin (MAASTHI) is a cohort study in the public health facilities in Bangalore, India. The objective of MAASTHI is to prospectively assess the effects of glucose levels in pregnancy on the risk of adverse infant outcomes, especially in predicting the possible risk markers of later chronic diseases. The primary objective of the proposed study is to investigate the effect of glucose levels in pregnancy on skinfold thickness (adiposity) in infancy as a marker of future obesity and diabetes in offspring. The secondary objective is to assess the association between psychosocial environment of mothers and adverse neonatal outcomes including adiposity. The study aims to recruit 5000 pregnant women and follow them and their offspring for a period of 4 years. The institutional review board at The Indian Institute of Public Health (IIPH)-H, Bangalore, Public Health Foundation of India has approved the protocol. All participants are required to provide written informed consent. DISCUSSION: The findings from this study may help to address important questions on screening and management of high blood sugar in pregnancy. It may provide critical information on the specific determinants driving the underweight-obesity-T2DM epidemic in India. The study can inform the policy regarding the potential impact of screening and management protocols in public healthcare facilities. The public health implications include prioritising issues of maternal glycemic control and weight management and better understanding of the lifecourse determinants in the development of T2DM

OCT using spectrally resolved bandwidth

An apparatus is disclosed for studying an object based on at least one of polarization, space, position or angle of light that has reflected from the object. An optical tomographic instrumentation of the apparatus includes a light source coupled to a source path, a sample path, a reference path, and a detection path, wherein the light source generates a spectrally resolved bandwidth. The spectrally resolved bandwidth includes a plurality of spectrally resolved cells and a detector in the detection path for analyzing light reflected from an object in the sample path and the light reflected in the reference path based upon at least one of the polarization, spatial relationship, position or angle domains.Board of Regents, University of Texas Syste

Plant Growth Promoting Bacteria Improve Growth and Phytostabilization Potential of Zea Mays under Chromium and Drought Stress by Altering Photosynthetic and Antioxidant Responses

Drought in heavy metal polluted arid and semiarid regions severely inhibits the plant growth and phytoremediation potential by affecting photosynthesis, antioxidant defense mechanism, and other biochemical processes. In the present study, we explored the role of plant growth-promoting bacteria (PGPB) on Zea mays growth and phytoremediation efficiency in Chromium (Cr) contaminated soils under drought stress by assessing plant stress tolerance, photosynthetic gas exchange activities, chlorophyll fluorescence, and Cr accumulation. Two efficient Cr and drought resistant PGPB with the potential to reduce Cr(VI) to Cr(III) and produce plant growth-promoting metabolites even under Cr, drought, or Cr+drought stress conditions were isolated and identified as Providencia sp. (TCR05) and Proteus mirabilis (TCR20). In pot experiments, the inoculation of TCR05 and TCR20 increased the plant growth, pigments, protein, phenolics, and relative water content and decreased the lipid peroxidation, proline, and superoxide dismutase activity under Cr, drought, or Cr+drought conditions. Irrespective of stress treatment, TCR05 and TCR20 also improved plant photosynthetic efficiency by increasing the CO2 assimilation rate, stomatal conductance to water vapor, transpiration rate, maximum quantum efficiency of PSII, actual quantum efficiency of PSII, electron transport rate, photochemical quenching, reducing the internal CO2 concentration and non-photochemical quenching. Besides, the PGPB decreased the translocation of Cr through immobilization of Cr in root. These results denoted that strains TCR05 and TCR20 could be a capable bio-inoculant for improving plant growth and phytostabilization practices in Cr contaminated sites even under water-limited conditions. © 2021 The Authors.North Carolina Central University, NCCU; Department of Science and Technology, Ministry of Science and Technology, India, डीएसटी: INT/RUS/RFBR/363; Science and Engineering Research Board, SERB; Russian Foundation for Basic Research, РФФИ: L.B.B thankful to the Science and Engineering Research Board (SERB), India for providing National Post-Doctoral Fellowship (Grant No. PDF/2017/001074 ). A.K., T, and M.R. are grateful for the “ Department of Science and Technology (DST), India (Project No. INT/RUS/RFBR/363 ) and Russian Foundation for Basic Research, Russia (Project No. 19-516-45006) bilateral research grant”. A.K. acknowledge the work support by Russian Science Foundation (Project No. 21-76-00011). Many thanks to Benedict Analin from the Department of Life Sciences, Central University of Tamil Nadu for helping to analyze photosynthetic parameters in the laboratory. The manuscript was written through the contributions of all authors