Speed Control of DC Motor using Pid Controller Based on Matlab

This paper is to design PID controller to supervise and control the speed response of the DC motor and MATLAB program is used for calculation and simulation PID controllers are widely used in a industrial plants because of their simplicity and robustness. Industrial processes are subjected to variation in parameters and parameter perturbations. We are choosing PID parameters and discussed Key words: DC motor, PID controller, MATLAB representatio

Solid–liquid coexistence of neon, argon, krypton, and xenon studied by simulations

The noble elements constitute the simplest group of atoms. At low temperatures or high pressures they freeze into the face-centered cubic (fcc) crystal structure (except helium). We perform molecular dynamics using the recently proposed simplified ab initio atomic (SAAP) potential [Deiters and Sadus, J. Chem. Phys. 150, 134504 (2019)] . This potential is parameterized using data from accurate ab initio quantum mechanical calculations by the coupled-cluster approach on the CCSD(T) level. We compute the fcc freezing lines for Argon and find a great agreement with the experimental values. At low pressures, this agreement is further enhanced by using many-body corrections. Hidden scale invariance of the potential energy function is validated by computing lines of constant excess entropy (configurational adiabats) and shows that mean square displacement and the static structure factor are invariant. These lines (isomorphs) can be generated from simulations at a single state-point by having knowledge of the pair potential. The isomorph theory for the solid-liquid transition is used to accurately predict the shape of the freezing line in the pressure-temperature plane, the shape in the density-temperature plane, the entropy of melting and the Lindemann parameters along the melting line. We finally predict that the body-centered cubic (bcc) crystal is stable at high pressures

PROTECTION OF SINGLE PHASE INDUCTION MOTOR AND MONITORING

In this project we give a special idea of industrial automation, and fault monitoring. Induction motors are the nerves of many industries. Hence industrial automation is required for precise and accurate operation. The project Arduino based parameter monitoring system for induction motor proposes a control and monitoring system for induction motor based on Arduino communication protocol for safe and economic data communication in industrial fields. Current, voltage, and temperature of the induction motors are very important parameters for its control system. The performance of an induction motor is directly affected by these fundamental quantities. However, during continuous operation it is difficult to control the machines. Arduino system is used for collecting and storing data and generate control signal to start or stop the induction machine. We measure the different type of fault such as Over Voltage, Over Current and Over Temperature

A robust pest identification system using morphological analysis in neural networks

Timely detection of pests play a major role in agriculture. There exist many pest identification systems, but almost all of them suffer from the misclassification due to lighting, background clutter, heterogeneous capturing devices as well as the pest being partially visible or in the different orientation. This misclassification may cause tremendous yield loss. To mitigate this situation, we proposed an architecture to provide high classification accuracy under the aforementioned conditions using morphology and skeletonization along with neural networks as classifiers. We have considered the crop rice as a use case as it is the staple food grain of almost the entire population of India. The amount of pesticides used is highest in rice as compared to all other food grains. This paper offers a robust technique to identify the pests in rice crops. The performance of the proposed architecture is tested with an image dataset, and the experimental results reveal that our proposed approach provides better classification accuracy than the existing pest detection approaches in the literature. Furthermore, the experimental results also provide the performance comparison among the popular classifiers

GPS TEC Scintillations and TEC depletion as seen from Hetauda and NAST, Nepal for 2016

We analyzed Global positing System Total Electron Content (GPS-TEC) data of stations Hetauda (27.414 0N and 85.051 0E) and NAST (27.656 0N and 85.327 0E), Nepal which are a part of UNAVCO.We obtained the variation of rate of TEC index (ROTI) and S4 index throughout the year 2016 for the two stations involved for the 32 all the Pseudo-Random Noise (PRN) numbers barring PRN number 4 which was inactive throughout the year. We chooses two stations data which are almost 40 km in distance and correlated the value of ROTI index with ROTI index and S4 index with S4 index and found that the ROTI index of Hetauda is well correlated with ROTI index of NAST with the highest being 94% for PRN 10 and the lowest being -13% for PRN 1. An extremely low correlation between S4 index of Hetauda and S4 index of NAST was observed with the highest correlation being 8% in PRN 3, 32 and the lowest correlation of -15% in PRN 12. BIBECHANA 18 (2) (2021) 87-9

GPS TEC Scintillations and TEC depletion as seen from Hetauda and NAST, Nepal for 2016

We analyzed Global positing System Total Electron Content (GPS-TEC) data of stations Hetauda (27.414 0N and 85.051 0E) and NAST (27.656 0N and 85.327 0E), Nepal which are a part of UNAVCO.We obtained the variation of rate of TEC index (ROTI) and S4 index throughout the year 2016 for the two stations involved for the 32 all the Pseudo-Random Noise (PRN) numbers barring PRN number 4 which was inactive throughout the year. We chooses two stations data which are almost 40 km in distance and correlated the value of ROTI index with ROTI index and S4 index with S4 index and found that the ROTI index of Hetauda is well correlated with ROTI index of NAST with the highest being 94% for PRN 10 and the lowest being -13% for PRN 1. An extremely low correlation between S4 index of Hetauda and S4 index of NAST was observed with the highest correlation being 8% in PRN 3, 32 and the lowest correlation of -15% in PRN 12. BIBECHANA 18 (2) (2021) 87-9

Nanoparticulate RNA delivery systems in cancer

Background: Drug delivery system is a common practice in cancer treatment. RNA interference-mediated post-transcriptional gene silencing holds promise as an approach to knockdown in the expression of target genes responsible for cancer cell growth and metastasis. RNA interference (RNAi) can be achieved by delivering small interfering RNA (siRNA) and short hairpin RNA (shRNA) to target cells. Since neither interfering RNAs can be delivered in naked form due to poor stability, an efficient delivery system is required that protects, guides, and delivers the siRNA and shRNA to target cells as part of cancer therapy (chemotherapy). Recent findings: In this review, a discussion is presented about the different types of drug delivery system used to deliver siRNA and shRNA, together with an overview of the potential benefits associated with this sophisticated biomolecular therapy. Improved understanding of the different approaches used in nanoparticle (NP) fabrication, along with an enhanced appreciation of the biochemical properties of siRNA/shRNA, will assist in developing improved drug delivery strategies in basic and clinical research. Conclusion: These novel delivery techniques are able to solve the problems that form an inevitable part of delivering genes in more efficient manner and as part of more effective treatment protocols. The present review concludes that the nanoparticulate RNA delivery system has great possibility for cancer treatment along with several other proposed methods. Several NPs or nanocarriers are already in use, but the methods proposed here could fulfill the missing gap in cancer research. It is the future technology, which unravels the mystery of resolving genomic diseases that is, especially genomic instability and its signaling cascades

Mapping development and health effects of cooking with solid fuels in low-income and middle-income countries, 2000-18 : a geospatial modelling study

Background More than 3 billion people do not have access to clean energy and primarily use solid fuels to cook. Use of solid fuels generates household air pollution, which was associated with more than 2 million deaths in 2019. Although local patterns in cooking vary systematically, subnational trends in use of solid fuels have yet to be comprehensively analysed. We estimated the prevalence of solid-fuel use with high spatial resolution to explore subnational inequalities, assess local progress, and assess the effects on health in low-income and middle-income countries (LMICs) without universal access to clean fuels.Methods We did a geospatial modelling study to map the prevalence of solid-fuel use for cooking at a 5 km x 5 km resolution in 98 LMICs based on 2.1 million household observations of the primary cooking fuel used from 663 population-based household surveys over the years 2000 to 2018. We use observed temporal patterns to forecast household air pollution in 2030 and to assess the probability of attaining the Sustainable Development Goal (SDG) target indicator for clean cooking. We aligned our estimates of household air pollution to geospatial estimates of ambient air pollution to establish the risk transition occurring in LMICs. Finally, we quantified the effect of residual primary solid-fuel use for cooking on child health by doing a counterfactual risk assessment to estimate the proportion of deaths from lower respiratory tract infections in children younger than 5 years that could be associated with household air pollution.Findings Although primary reliance on solid-fuel use for cooking has declined globally, it remains widespread. 593 million people live in districts where the prevalence of solid-fuel use for cooking exceeds 95%. 66% of people in LMICs live in districts that are not on track to meet the SDG target for universal access to clean energy by 2030. Household air pollution continues to be a major contributor to particulate exposure in LMICs, and rising ambient air pollution is undermining potential gains from reductions in the prevalence of solid-fuel use for cooking in many countries. We estimated that, in 2018, 205000 (95% uncertainty interval 147000-257000) children younger than 5 years died from lower respiratory tract infections that could be attributed to household air pollution.Interpretation Efforts to accelerate the adoption of clean cooking fuels need to be substantially increased and recalibrated to account for subnational inequalities, because there are substantial opportunities to improve air quality and avert child mortality associated with household air pollution. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd.Peer reviewe

Population and fertility by age and sex for 195 countries and territories, 1950–2017: a systematic analysis for the Global Burden of Disease Study 2017

Background: Population estimates underpin demographic and epidemiological research and are used to track progress on numerous international indicators of health and development. To date, internationally available estimates of population and fertility, although useful, have not been produced with transparent and replicable methods and do not use standardised estimates of mortality. We present single-calendar year and single-year of age estimates of fertility and population by sex with standardised and replicable methods. Methods: We estimated population in 195 locations by single year of age and single calendar year from 1950 to 2017 with standardised and replicable methods. We based the estimates on the demographic balancing equation, with inputs of fertility, mortality, population, and migration data. Fertility data came from 7817 location-years of vital registration data, 429 surveys reporting complete birth histories, and 977 surveys and censuses reporting summary birth histories. We estimated age-specific fertility rates (ASFRs; the annual number of livebirths to women of a specified age group per 1000 women in that age group) by use of spatiotemporal Gaussian process regression and used the ASFRs to estimate total fertility rates (TFRs; the average number of children a woman would bear if she survived through the end of the reproductive age span [age 10–54 years] and experienced at each age a particular set of ASFRs observed in the year of interest). Because of sparse data, fertility at ages 10–14 years and 50–54 years was estimated from data on fertility in women aged 15–19 years and 45–49 years, through use of linear regression. Age-specific mortality data came from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 estimates. Data on population came from 1257 censuses and 761 population registry location-years and were adjusted for underenumeration and age misreporting with standard demographic methods. Migration was estimated with the GBD Bayesian demographic balancing model, after incorporating information about refugee migration into the model prior. Final population estimates used the cohort-component method of population projection, with inputs of fertility, mortality, and migration data. Population uncertainty was estimated by use of out-of-sample predictive validity testing. With these data, we estimated the trends in population by age and sex and in fertility by age between 1950 and 2017 in 195 countries and territories. Findings: From 1950 to 2017, TFRs decreased by 49·4% (95% uncertainty interval [UI] 46·4–52·0). The TFR decreased from 4·7 livebirths (4·5–4·9) to 2·4 livebirths (2·2–2·5), and the ASFR of mothers aged 10–19 years decreased from 37 livebirths (34–40) to 22 livebirths (19–24) per 1000 women. Despite reductions in the TFR, the global population has been increasing by an average of 83·8 million people per year since 1985. The global population increased by 197·2% (193·3–200·8) since 1950, from 2·6 billion (2·5–2·6) to 7·6 billion (7·4–7·9) people in 2017; much of this increase was in the proportion of the global population in south Asia and sub-Saharan Africa. The global annual rate of population growth increased between 1950 and 1964, when it peaked at 2·0%; this rate then remained nearly constant until 1970 and then decreased to 1·1% in 2017. Population growth rates in the southeast Asia, east Asia, and Oceania GBD super-region decreased from 2·5% in 1963 to 0·7% in 2017, whereas in sub-Saharan Africa, population growth rates were almost at the highest reported levels ever in 2017, when they were at 2·7%. The global average age increased from 26·6 years in 1950 to 32·1 years in 2017, and the proportion of the population that is of working age (age 15–64 years) increased from 59·9% to 65·3%. At the national level, the TFR decreased in all countries and territories between 1950 and 2017; in 2017, TFRs ranged from a low of 1·0 livebirths (95% UI 0·9–1·2) in Cyprus to a high of 7·1 livebirths (6·8–7·4) in Niger. The TFR under age 25 years (TFU25; number of livebirths expected by age 25 years for a hypothetical woman who survived the age group and was exposed to current ASFRs) in 2017 ranged from 0·08 livebirths (0·07–0·09) in South Korea to 2·4 livebirths (2·2–2·6) in Niger, and the TFR over age 30 years (TFO30; number of livebirths expected for a hypothetical woman ageing from 30 to 54 years who survived the age group and was exposed to current ASFRs) ranged from a low of 0·3 livebirths (0·3–0·4) in Puerto Rico to a high of 3·1 livebirths (3·0–3·2) in Niger. TFO30 was higher than TFU25 in 145 countries and territories in 2017. 33 countries had a negative population growth rate from 2010 to 2017, most of which were located in central, eastern, and western Europe, whereas population growth rates of more than 2·0% were seen in 33 of 46 countries in sub-Saharan Africa. In 2017, less than 65% of the national population was of working age in 12 of 34 high-income countries, and less than 50% of the national population was of working age in Mali, Chad, and Niger. Interpretation: Population trends create demographic dividends and headwinds (ie, economic benefits and detriments) that affect national economies and determine national planning needs. Although TFRs are decreasing, the global population continues to grow as mortality declines, with diverse patterns at the national level and across age groups. To our knowledge, this is the first study to provide transparent and replicable estimates of population and fertility, which can be used to inform decision making and to monitor progress

Measuring progress from 1990 to 2017 and projecting attainment to 2030 of the health-related Sustainable Development Goals for 195 countries and territories: a systematic analysis for the Global Burden of Disease Study 2017

Background: Efforts to establish the 2015 baseline and monitor early implementation of the UN Sustainable Development Goals (SDGs) highlight both great potential for and threats to improving health by 2030. To fully deliver on the SDG aim of “leaving no one behind”, it is increasingly important to examine the health-related SDGs beyond national-level estimates. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017), we measured progress on 41 of 52 health-related SDG indicators and estimated the health-related SDG index for 195 countries and territories for the period 1990–2017, projected indicators to 2030, and analysed global attainment. Methods: We measured progress on 41 health-related SDG indicators from 1990 to 2017, an increase of four indicators since GBD 2016 (new indicators were health worker density, sexual violence by non-intimate partners, population census status, and prevalence of physical and sexual violence [reported separately]). We also improved the measurement of several previously reported indicators. We constructed national-level estimates and, for a subset of health-related SDGs, examined indicator-level differences by sex and Socio-demographic Index (SDI) quintile. We also did subnational assessments of performance for selected countries. To construct the health-related SDG index, we transformed the value for each indicator on a scale of 0–100, with 0 as the 2\ub75th percentile and 100 as the 97\ub75th percentile of 1000 draws calculated from 1990 to 2030, and took the geometric mean of the scaled indicators by target. To generate projections through 2030, we used a forecasting framework that drew estimates from the broader GBD study and used weighted averages of indicator-specific and country-specific annualised rates of change from 1990 to 2017 to inform future estimates. We assessed attainment of indicators with defined targets in two ways: first, using mean values projected for 2030, and then using the probability of attainment in 2030 calculated from 1000 draws. We also did a global attainment analysis of the feasibility of attaining SDG targets on the basis of past trends. Using 2015 global averages of indicators with defined SDG targets, we calculated the global annualised rates of change required from 2015 to 2030 to meet these targets, and then identified in what percentiles the required global annualised rates of change fell in the distribution of country-level rates of change from 1990 to 2015. We took the mean of these global percentile values across indicators and applied the past rate of change at this mean global percentile to all health-related SDG indicators, irrespective of target definition, to estimate the equivalent 2030 global average value and percentage change from 2015 to 2030 for each indicator. Findings: The global median health-related SDG index in 2017 was 59\ub74 (IQR 35\ub74–67\ub73), ranging from a low of 11\ub76 (95% uncertainty interval 9\ub76–14\ub70) to a high of 84\ub79 (83\ub71–86\ub77). SDG index values in countries assessed at the subnational level varied substantially, particularly in China and India, although scores in Japan and the UK were more homogeneous. Indicators also varied by SDI quintile and sex, with males having worse outcomes than females for non-communicable disease (NCD) mortality, alcohol use, and smoking, among others. Most countries were projected to have a higher health-related SDG index in 2030 than in 2017, while country-level probabilities of attainment by 2030 varied widely by indicator. Under-5 mortality, neonatal mortality, maternal mortality ratio, and malaria indicators had the most countries with at least 95% probability of target attainment. Other indicators, including NCD mortality and suicide mortality, had no countries projected to meet corresponding SDG targets on the basis of projected mean values for 2030 but showed some probability of attainment by 2030. For some indicators, including child malnutrition, several infectious diseases, and most violence measures, the annualised rates of change required to meet SDG targets far exceeded the pace of progress achieved by any country in the recent past. We found that applying the mean global annualised rate of change to indicators without defined targets would equate to about 19% and 22% reductions in global smoking and alcohol consumption, respectively; a 47% decline in adolescent birth rates; and a more than 85% increase in health worker density per 1000 population by 2030. Interpretation: The GBD study offers a unique, robust platform for monitoring the health-related SDGs across demographic and geographic dimensions. Our findings underscore the importance of increased collection and analysis of disaggregated data and highlight where more deliberate design or targeting of interventions could accelerate progress in attaining the SDGs. Current projections show that many health-related SDG indicators, NCDs, NCD-related risks, and violence-related indicators will require a concerted shift away from what might have driven past gains—curative interventions in the case of NCDs—towards multisectoral, prevention-oriented policy action and investments to achieve SDG aims. Notably, several targets, if they are to be met by 2030, demand a pace of progress that no country has achieved in the recent past. The future is fundamentally uncertain, and no model can fully predict what breakthroughs or events might alter the course of the SDGs. What is clear is that our actions—or inaction—today will ultimately dictate how close the world, collectively, can get to leaving no one behind by 2030