Non-performing assets also known as Bad Loans have played havoc with financials of Scheduled Commercial Banks (SCBs) in India from 2015 to 2022. The NPAs started piling up after an abnormal growth in advances of these banks in the developmental phase unleashed by the Government of India after the 2008 Global crises. The period witnessed a rise in manufacturing and infrastructure project financing imbued with over optimism of promoters for success and profitabilty. Banks vied with one another to share a piece of pie for opportunities in sectors like Iron and Steel, Mining, Aviation and Road Construction. The spurt in advances of banks also witnessed a simultaneous rise in their bad loans. NPAs have impacted negatively the financial performance of various Indian banks over the years (Sharma & Dhiman 2023). Though Non-Performing Assets cannot be wiped off completely from the advances portfolio of the banks yet it is important to control this critical parameter of financial performance of the banking sector. Management of NPAs is significant for bank profitability and growth of the economy. Bad debts or NPAs are not always created due to the fault of a bank. Though managements of different banks try their best to reduce NPAs but due to various macroeconomic, borrower related and at times bank related specific factors it is not possible to eliminate these altogether from the banking book. However prudent board policies, proper pre-sanction appraisal of borrowers and post sanction forensic audit of disbursements to large borrowers by the banks can go a long way in curbing the menace of bad loans.
{"title":"Non-Performing Assets - Content Analysis and Suggestions for Resolution","authors":"Dr. Parmod Kumar Sharma, Dr. Babli Dhiman","doi":"10.32628/ijsrst24254411","DOIUrl":"https://doi.org/10.32628/ijsrst24254411","url":null,"abstract":"Non-performing assets also known as Bad Loans have played havoc with financials of Scheduled Commercial Banks (SCBs) in India from 2015 to 2022. The NPAs started piling up after an abnormal growth in advances of these banks in the developmental phase unleashed by the Government of India after the 2008 Global crises. The period witnessed a rise in manufacturing and infrastructure project financing imbued with over optimism of promoters for success and profitabilty. Banks vied with one another to share a piece of pie for opportunities in sectors like Iron and Steel, Mining, Aviation and Road Construction. The spurt in advances of banks also witnessed a simultaneous rise in their bad loans. NPAs have impacted negatively the financial performance of various Indian banks over the years (Sharma & Dhiman 2023). Though Non-Performing Assets cannot be wiped off completely from the advances portfolio of the banks yet it is important to control this critical parameter of financial performance of the banking sector. Management of NPAs is significant for bank profitability and growth of the economy. Bad debts or NPAs are not always created due to the fault of a bank. Though managements of different banks try their best to reduce NPAs but due to various macroeconomic, borrower related and at times bank related specific factors it is not possible to eliminate these altogether from the banking book. However prudent board policies, proper pre-sanction appraisal of borrowers and post sanction forensic audit of disbursements to large borrowers by the banks can go a long way in curbing the menace of bad loans.","PeriodicalId":14387,"journal":{"name":"International Journal of Scientific Research in Science and Technology","volume":"13 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140462187","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Particulate matter (PM) has widely been recognized as the primary factor responsible for air pollution, posing significant health hazards, particularly cardiovascular and respiratory diseases. Major sources of particulate matter include construction sites, power plants, industries and automobiles, landfills and agriculture, wildfires and brush/waste burning, industrial sources, wind-blown dust from open lands, pollen, and fragments of bacteria. Even though various studies have been carried out to predict particulate matter concentration, there are only a handful of papers that focus on the data scaling pre-processing aspect and how it affects the prediction. For the study, Gandhinagar Smart City Development Limited, Gandhinagar, Gujarat has provided Air Quality data from 26-1-2022 to 16-01-2023. The provided data has several challenges such as missing data, inconsistent data, and mixed data (numerical and categorical). Data pre-processing is an essential step in machine learning regression problems. Data pre-processing techniques include missing value handling, data scaling, outlier detection, feature selection/engineering, and imputation. So, this paper aims to identify the effect of the data scaling pre-processing technique to predict the concentration of Particulate Matter (PM10) for Gandhinagar, Gujarat. Data scaling will be performed based on whether data are normally distributed or not. Four data scaling techniques such as Normalizer, Robust Scaler, Min-Max Scaler, and Standard Scaler in combination with six machine learning algorithms such as Multiple Linear Regressor, Support Vector Regressor, K-Nearest Neighbour regressor, Decision Tree Regressor, Random Forest Regressor, and XGBoost Regressor were compared to identify best prediction model for Particulate Matter (PM10) concentration.
{"title":"Effect of Feature Scaling Pre-processing Techniques on Machine Learning Algorithms to Predict Particulate Matter Concentration for Gandhinagar, Gujarat, India","authors":"Zalak L. Thakker, Sanjay H. Buch","doi":"10.32628/ijsrst52411150","DOIUrl":"https://doi.org/10.32628/ijsrst52411150","url":null,"abstract":"Particulate matter (PM) has widely been recognized as the primary factor responsible for air pollution, posing significant health hazards, particularly cardiovascular and respiratory diseases. Major sources of particulate matter include construction sites, power plants, industries and automobiles, landfills and agriculture, wildfires and brush/waste burning, industrial sources, wind-blown dust from open lands, pollen, and fragments of bacteria. Even though various studies have been carried out to predict particulate matter concentration, there are only a handful of papers that focus on the data scaling pre-processing aspect and how it affects the prediction. For the study, Gandhinagar Smart City Development Limited, Gandhinagar, Gujarat has provided Air Quality data from 26-1-2022 to 16-01-2023. The provided data has several challenges such as missing data, inconsistent data, and mixed data (numerical and categorical). Data pre-processing is an essential step in machine learning regression problems. Data pre-processing techniques include missing value handling, data scaling, outlier detection, feature selection/engineering, and imputation. So, this paper aims to identify the effect of the data scaling pre-processing technique to predict the concentration of Particulate Matter (PM10) for Gandhinagar, Gujarat. Data scaling will be performed based on whether data are normally distributed or not. Four data scaling techniques such as Normalizer, Robust Scaler, Min-Max Scaler, and Standard Scaler in combination with six machine learning algorithms such as Multiple Linear Regressor, Support Vector Regressor, K-Nearest Neighbour regressor, Decision Tree Regressor, Random Forest Regressor, and XGBoost Regressor were compared to identify best prediction model for Particulate Matter (PM10) concentration.","PeriodicalId":14387,"journal":{"name":"International Journal of Scientific Research in Science and Technology","volume":"501 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139820670","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A set of five novel Schiff’s bases (5a-e) incorporating coumarin-1, 3, 4-oxadiazole derivative were synthesized through condensation reaction of 3-acetyl-4-hydroxy-2H-chromen-2-one with 2-aminooxadiazole derivatives as heterocyclic aromatic amines. The novel structures of these compounds were confirmed based on their elemental analysis and spectral data. All these investigated derivatives were tested against bacterial species S. aurous, E. coli, S. typhi, B. substilis using the Agar cup method, and against fungal species A. niger, P. chrysogenum, F. moneliforme and A. flavus using poison plate method. Schiff bases incorporating coumarin and 1,3,4-oxadiazole moieties have shown notable efficacy against both bacterial and fungal strains.
{"title":"The Synthesis, Characterization, and Biological Activities of Some Novel Schiff Bases Derived From 3-Acetyl-4-Hydroxy-2H-Chromen-2-One And 2-Aminooxadiazole Derivatives Have Been Investigated","authors":"Jadhav Rajpal L., Ubale Sanjay B.","doi":"10.32628/ijsrst52411174","DOIUrl":"https://doi.org/10.32628/ijsrst52411174","url":null,"abstract":"A set of five novel Schiff’s bases (5a-e) incorporating coumarin-1, 3, 4-oxadiazole derivative were synthesized through condensation reaction of 3-acetyl-4-hydroxy-2H-chromen-2-one with 2-aminooxadiazole derivatives as heterocyclic aromatic amines. The novel structures of these compounds were confirmed based on their elemental analysis and spectral data. All these investigated derivatives were tested against bacterial species S. aurous, E. coli, S. typhi, B. substilis using the Agar cup method, and against fungal species A. niger, P. chrysogenum, F. moneliforme and A. flavus using poison plate method. Schiff bases incorporating coumarin and 1,3,4-oxadiazole moieties have shown notable efficacy against both bacterial and fungal strains.","PeriodicalId":14387,"journal":{"name":"International Journal of Scientific Research in Science and Technology","volume":"1359 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140466979","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The purpose of this research is to look into the solution technique for obtaining MHD velocity and temperature profiles. In the presence of a changing heat flux, the unsteady laminar boundary layer flow and heat transfer of a viscous incompressible fluid across a stretching sheet are numerically investigated. The unsteadiness is thought to be generated by a sudden increase in the surface temperature and a time-dependent stretching velocity. The flow and heat transfer partial differential equations were numerically solved using an implicit finite difference scheme and a quasi-linearization technique. Both velocity and temperature rise with time and magnetic field, according to the findings. The computed results are compared to previous work that has been published. Variable heat flux (VHF) conditions have also been taken into account.
{"title":"The Effect of Variable Heat Flux on Unsteady Laminar MHD Boundary Layer Flow and Heat Transfer Due to a Stretching Sheet","authors":"Ajaykumar M, A. H. Srinivasa","doi":"10.32628/ijsrst52411161","DOIUrl":"https://doi.org/10.32628/ijsrst52411161","url":null,"abstract":"The purpose of this research is to look into the solution technique for obtaining MHD velocity and temperature profiles. In the presence of a changing heat flux, the unsteady laminar boundary layer flow and heat transfer of a viscous incompressible fluid across a stretching sheet are numerically investigated. The unsteadiness is thought to be generated by a sudden increase in the surface temperature and a time-dependent stretching velocity. The flow and heat transfer partial differential equations were numerically solved using an implicit finite difference scheme and a quasi-linearization technique. Both velocity and temperature rise with time and magnetic field, according to the findings. The computed results are compared to previous work that has been published. Variable heat flux (VHF) conditions have also been taken into account.","PeriodicalId":14387,"journal":{"name":"International Journal of Scientific Research in Science and Technology","volume":"159 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140464049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ranjana N, Haripriya S, Mahalakshmi Sundarapandian
This comprehensive literature review on pomegranate plants thoroughly examines the various aspects, including traditional uses, nutritional composition, bioactive compounds present in each part of the plant, and their potential activity on human health. The chemical composition of the pomegranate peel and the toxicology of the plant are also discussed. This review also contributes to the understanding of the various pharmacological actions of the pomegranate plant parts. The pharmacological actions of pomegranate include antibacterial activity, antiviral activity, anticancer activity, antioxidant properties, antimicrobial activity, anti-diabetic activity, dermatological activity, and furthermore.
{"title":"Pomegranate Powerhouse : A Synthesis of Scientific Insights into Its Nutraceutical Marvels and Biomedical Applications","authors":"Ranjana N, Haripriya S, Mahalakshmi Sundarapandian","doi":"10.32628/ijsrst52411170","DOIUrl":"https://doi.org/10.32628/ijsrst52411170","url":null,"abstract":"This comprehensive literature review on pomegranate plants thoroughly examines the various aspects, including traditional uses, nutritional composition, bioactive compounds present in each part of the plant, and their potential activity on human health. The chemical composition of the pomegranate peel and the toxicology of the plant are also discussed. This review also contributes to the understanding of the various pharmacological actions of the pomegranate plant parts. The pharmacological actions of pomegranate include antibacterial activity, antiviral activity, anticancer activity, antioxidant properties, antimicrobial activity, anti-diabetic activity, dermatological activity, and furthermore.","PeriodicalId":14387,"journal":{"name":"International Journal of Scientific Research in Science and Technology","volume":"45 43","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140464604","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Particulate matter (PM) has widely been recognized as the primary factor responsible for air pollution, posing significant health hazards, particularly cardiovascular and respiratory diseases. Major sources of particulate matter include construction sites, power plants, industries and automobiles, landfills and agriculture, wildfires and brush/waste burning, industrial sources, wind-blown dust from open lands, pollen, and fragments of bacteria. Even though various studies have been carried out to predict particulate matter concentration, there are only a handful of papers that focus on the data scaling pre-processing aspect and how it affects the prediction. For the study, Gandhinagar Smart City Development Limited, Gandhinagar, Gujarat has provided Air Quality data from 26-1-2022 to 16-01-2023. The provided data has several challenges such as missing data, inconsistent data, and mixed data (numerical and categorical). Data pre-processing is an essential step in machine learning regression problems. Data pre-processing techniques include missing value handling, data scaling, outlier detection, feature selection/engineering, and imputation. So, this paper aims to identify the effect of the data scaling pre-processing technique to predict the concentration of Particulate Matter (PM10) for Gandhinagar, Gujarat. Data scaling will be performed based on whether data are normally distributed or not. Four data scaling techniques such as Normalizer, Robust Scaler, Min-Max Scaler, and Standard Scaler in combination with six machine learning algorithms such as Multiple Linear Regressor, Support Vector Regressor, K-Nearest Neighbour regressor, Decision Tree Regressor, Random Forest Regressor, and XGBoost Regressor were compared to identify best prediction model for Particulate Matter (PM10) concentration.
{"title":"Effect of Feature Scaling Pre-processing Techniques on Machine Learning Algorithms to Predict Particulate Matter Concentration for Gandhinagar, Gujarat, India","authors":"Zalak L. Thakker, Sanjay H. Buch","doi":"10.32628/ijsrst52411150","DOIUrl":"https://doi.org/10.32628/ijsrst52411150","url":null,"abstract":"Particulate matter (PM) has widely been recognized as the primary factor responsible for air pollution, posing significant health hazards, particularly cardiovascular and respiratory diseases. Major sources of particulate matter include construction sites, power plants, industries and automobiles, landfills and agriculture, wildfires and brush/waste burning, industrial sources, wind-blown dust from open lands, pollen, and fragments of bacteria. Even though various studies have been carried out to predict particulate matter concentration, there are only a handful of papers that focus on the data scaling pre-processing aspect and how it affects the prediction. For the study, Gandhinagar Smart City Development Limited, Gandhinagar, Gujarat has provided Air Quality data from 26-1-2022 to 16-01-2023. The provided data has several challenges such as missing data, inconsistent data, and mixed data (numerical and categorical). Data pre-processing is an essential step in machine learning regression problems. Data pre-processing techniques include missing value handling, data scaling, outlier detection, feature selection/engineering, and imputation. So, this paper aims to identify the effect of the data scaling pre-processing technique to predict the concentration of Particulate Matter (PM10) for Gandhinagar, Gujarat. Data scaling will be performed based on whether data are normally distributed or not. Four data scaling techniques such as Normalizer, Robust Scaler, Min-Max Scaler, and Standard Scaler in combination with six machine learning algorithms such as Multiple Linear Regressor, Support Vector Regressor, K-Nearest Neighbour regressor, Decision Tree Regressor, Random Forest Regressor, and XGBoost Regressor were compared to identify best prediction model for Particulate Matter (PM10) concentration.","PeriodicalId":14387,"journal":{"name":"International Journal of Scientific Research in Science and Technology","volume":"20 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139880613","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A common excellent replacement for GC and HPLC is High-Performance Thin Layer Chromatography (HPTLC), an improved and automated technique of thin-layer chromatography (TLC) that provides better separation performance and detection limits. Applications of HPTLC include the study of biological materials and phytochemicals, the measurement of herbal medications and active components, formulation fingerprinting, and the identification of adulterants in formulations. Using HPTLC, chemicals of forensic importance can be located. It is more sensitive and feasible to run many samples in a little period of time by using a small volume of solvent. It is one of the more intricate instrumental procedures, utilizing every feature available in thin-layer chromatography.
{"title":"A Review on High Performance Thin Layer Chromatography","authors":"Miss. Payal Badhe, Dr. Vijaya Barge","doi":"10.32628/ijsrst52411163","DOIUrl":"https://doi.org/10.32628/ijsrst52411163","url":null,"abstract":"A common excellent replacement for GC and HPLC is High-Performance Thin Layer Chromatography (HPTLC), an improved and automated technique of thin-layer chromatography (TLC) that provides better separation performance and detection limits. Applications of HPTLC include the study of biological materials and phytochemicals, the measurement of herbal medications and active components, formulation fingerprinting, and the identification of adulterants in formulations. Using HPTLC, chemicals of forensic importance can be located. It is more sensitive and feasible to run many samples in a little period of time by using a small volume of solvent. It is one of the more intricate instrumental procedures, utilizing every feature available in thin-layer chromatography.","PeriodicalId":14387,"journal":{"name":"International Journal of Scientific Research in Science and Technology","volume":"40 14","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140465146","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The city of Pune experiences poor air quality, leading to research of various air constituents in order to assess the overall quality of the air. Significant pollutants such as PM2.5, PM10 (RSPM), NO2, O3, SO2, and CO are addressed in this analysis, along with their causes and consequences. Exceeding WHO standards, levels of PM2.5 constitute a severe problem; NO2 and O3 levels constitute grounds for concern. In order to mitigate such pollutants and obtain cleaner air in Pune City, the research stresses the necessity for more difficult emission control measures, the promotion of public transportation and electric vehicles, and the supervision of industrial and construction activity. The objective of this research is to evaluate Pune City's air quality and offer insights by thoroughly examining various air quality elements. An extensive tracking strategy is analyzed for three years (2022, 2023, and 2024), considering air quality components like RSPM (PM10), PM-2.5,NO2, O3, etc. Various graphs are analyzed for the above-mentioned years and observe the growth in air quality index for Pune city. In the last three years, data has been collected from government websites on a monthly basis, and various graphs have been plotted by considering their average value. All the graphs show an increase in the air quality index. The study's findings provide valuable new information on the present state of the air quality in Pune City and emphasize the urgent need for effective air quality management measures. To mitigate air pollution, maintain public health, and maintain environmental sustainability, initiatives must concentrate on emissions control, planning for cities, enhancing public transportation, and creating green infrastructure in Pune City.
{"title":"The Examination of different Air Constituents to Ascertain Pune City's Air Quality","authors":"Dr. Nidhi Mishra","doi":"10.32628/ijsrst52411164","DOIUrl":"https://doi.org/10.32628/ijsrst52411164","url":null,"abstract":"The city of Pune experiences poor air quality, leading to research of various air constituents in order to assess the overall quality of the air. Significant pollutants such as PM2.5, PM10 (RSPM), NO2, O3, SO2, and CO are addressed in this analysis, along with their causes and consequences. Exceeding WHO standards, levels of PM2.5 constitute a severe problem; NO2 and O3 levels constitute grounds for concern. In order to mitigate such pollutants and obtain cleaner air in Pune City, the research stresses the necessity for more difficult emission control measures, the promotion of public transportation and electric vehicles, and the supervision of industrial and construction activity.\u0000The objective of this research is to evaluate Pune City's air quality and offer insights by thoroughly examining various air quality elements. An extensive tracking strategy is analyzed for three years (2022, 2023, and 2024), considering air quality components like RSPM (PM10), PM-2.5,NO2, O3, etc. Various graphs are analyzed for the above-mentioned years and observe the growth in air quality index for Pune city. In the last three years, data has been collected from government websites on a monthly basis, and various graphs have been plotted by considering their average value. All the graphs show an increase in the air quality index. The study's findings provide valuable new information on the present state of the air quality in Pune City and emphasize the urgent need for effective air quality management measures. To mitigate air pollution, maintain public health, and maintain environmental sustainability, initiatives must concentrate on emissions control, planning for cities, enhancing public transportation, and creating green infrastructure in Pune City.","PeriodicalId":14387,"journal":{"name":"International Journal of Scientific Research in Science and Technology","volume":"82 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140467873","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Stunting is a developmental disorder in toddlers characterized by H/A index z-score of less than -2SD. Based on the results of SSGI 2022, the prevalence of stunting among toddlers in Bogor Regency reached 24.9 percent. This study aimed to determine the relationship between family income, birth length, and energy intake with the incidence of stunting among toddlers in Cibungbulang District. The sample was 151 toddlers aged 24 – 59 months who were selected by systematic random sampling. Intake data were collected with 24-hour food recall, stunting by measuring heights, and other data were collected by interview using questionnaires. Most of the toddlers were male (57.6%) with fathers aged >35 year (58.3%) and graduated from senior high school (34,4%) and mothers aged 21 – 35 years (70.2%) with high school diploma or its equivalent (34.4%). Most of the children-under-five had families with income below the regional minimum wage (88.1%), normal birth length (80.8%), adequate and excessive energy intake (53.6%). A total of 41.7 percent of toddlers were stunted. There were significant relationships between family income (p=0.022), birth length (p=0.040), and energy intake (p=0.040) with the incidence of stunting in toddlers (p<0.05). It can be concluded that family income, birth length, and energy intake are related to the incidence of stunting in toddlers aged 24 – 59 months in Cibungbulang District. Maternal nutrition intake needs to be monitored carefully during pregnancy and home food gardening program should be promoted to increase food availability and income thus ensuring optimal children development.
{"title":"The Association of Family Income, Birth Length, and Energy Intake with The Incidence of Stunting in Cibungbulang Sub-District","authors":"Rina Efiyanna, Meilinasari, Fairuz Dhia Rabbani","doi":"10.32628/ijsrst52411143","DOIUrl":"https://doi.org/10.32628/ijsrst52411143","url":null,"abstract":"Stunting is a developmental disorder in toddlers characterized by H/A index z-score of less than -2SD. Based on the results of SSGI 2022, the prevalence of stunting among toddlers in Bogor Regency reached 24.9 percent. This study aimed to determine the relationship between family income, birth length, and energy intake with the incidence of stunting among toddlers in Cibungbulang District. The sample was 151 toddlers aged 24 – 59 months who were selected by systematic random sampling. Intake data were collected with 24-hour food recall, stunting by measuring heights, and other data were collected by interview using questionnaires. Most of the toddlers were male (57.6%) with fathers aged >35 year (58.3%) and graduated from senior high school (34,4%) and mothers aged 21 – 35 years (70.2%) with high school diploma or its equivalent (34.4%). Most of the children-under-five had families with income below the regional minimum wage (88.1%), normal birth length (80.8%), adequate and excessive energy intake (53.6%). A total of 41.7 percent of toddlers were stunted. There were significant relationships between family income (p=0.022), birth length (p=0.040), and energy intake (p=0.040) with the incidence of stunting in toddlers (p<0.05). It can be concluded that family income, birth length, and energy intake are related to the incidence of stunting in toddlers aged 24 – 59 months in Cibungbulang District. Maternal nutrition intake needs to be monitored carefully during pregnancy and home food gardening program should be promoted to increase food availability and income thus ensuring optimal children development.","PeriodicalId":14387,"journal":{"name":"International Journal of Scientific Research in Science and Technology","volume":"768 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140467960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study focused on synthesising MnFe2O4 (Manganese Ferrite) nanoparticles using the sol-gel method. We then applied these nanoparticles as a catalyst for synthesising dihydropyrano[2,3-c]pyrazole derivatives at a specific temperature. The significant advantage of this process is that it requires only short reaction times and no solvents. Additionally, the crude pyranopyrazole derivatives can be purified through a simple recrystallization process. The catalyst is reusable, magnetically separable and maintains its activity even after five uses. The chemical integrity of the catalyst was confirmed through FT-IR, 1H NMR, and 13C NMR techniques.
{"title":"MnFe2O4 nanoparticle as a new and magnetically separable nanocatalyst for solvent-free synthesis of dihydropyrano [2,3-c]pyrazole derivatives","authors":"Santosh B. Gaikwad, Kishore Puri","doi":"10.32628/ijsrst173876","DOIUrl":"https://doi.org/10.32628/ijsrst173876","url":null,"abstract":"This study focused on synthesising MnFe2O4 (Manganese Ferrite) nanoparticles using the sol-gel method. We then applied these nanoparticles as a catalyst for synthesising dihydropyrano[2,3-c]pyrazole derivatives at a specific temperature. The significant advantage of this process is that it requires only short reaction times and no solvents. Additionally, the crude pyranopyrazole derivatives can be purified through a simple recrystallization process. The catalyst is reusable, magnetically separable and maintains its activity even after five uses. The chemical integrity of the catalyst was confirmed through FT-IR, 1H NMR, and 13C NMR techniques.","PeriodicalId":14387,"journal":{"name":"International Journal of Scientific Research in Science and Technology","volume":"39 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140500421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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