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The purpose of the present study is to examine the impact of parental socioeconomic status on pupils' achievement in secondary school Mathematics. The population of the study consists of class nine students studying in different secondary and higher secondary schools of Karbi Anglong district of Assam state in India. 900 students of 30 different schools and their parents participated in the survey and responded to the questionnaires. Stepwise Multiple Regression Analysis technique is adopted to analyze collected data. The main objective of the study is to determine the relationship between parents' socioeconomic status and its impact on the scholastic attainment of secondary school students in mathematics. The result of the analysis reveals that parents' socioeconomic status has significant relationship with school learners' academic achievement in mathematics.

Introduction. Trauma is the leading cause of non-obstetric maternal mortality and affects up to 8% of all pregnancies. Pregnant patients with traumatic brain injury (TBI) are a vulnerable population and management is complex with multiple special considerations. Recommendations proposed for the management of TBI patients are non-applicable to pregnant women as often have been excluded from these major trials. Evidence on TBI management in pregnant women is limited and mostly based on clinical experience. Aim and objective. This study is to share our experiences in the management of TBI during pregnancy at a tertiary trauma centre in north India to formulate a stepwise approach consisting of different tiers of treatment. Methods. Case records of thirty pregnant patients with traumatic brain injury admitted at the tertiary apex trauma centre of northern India during the period of January 2015 to June 2022 were retrospectively analyzed. Results. Road traffic accidents (specifically two-wheelers) were the most common cause of TBI in pregnancy (80%). 60% suffered from moderate to severe TBI. Operative neurosurgical intervention was required in 30% of cases. During hospital stay, 27 patients (90%) had continuation of pregnancy. Nine patients (30%) who expired, belonged to moderate to severe TBI. Conclusion. Moderate or severe TBI in pregnancy is associated with unfavourable maternal and fetal outcomes. The complex physiological modifications occurring in pregnancy have a crucial role in the management and require a stepwise approach. Fetal concerns and the paucity of high-quality evidence further complicate the issue and more studies including this group specifically are required. [ABSTRACT FROM AUTHOR]

Medical education in India is confronting a charismatic transformation from traditional curriculum to competency-based medical education (CBME). It is more clinically oriented; skill-based and claims to produce competent Indian medical graduates. CBME has divided subjects into competencies and related topics are scattered over different competencies. The intention behind teaching should not be merely students' learning, but contemplation should be towards concept building, imagination, creativity, self-motivated thinking, and the rightful application of knowledge in day-to-day life. Hence a well-formulated, organized, effective, and practically assessable design and an efficient approach are essential not only to link these spread-over pieces of the topic but to teach that topic in a certain flow and rhythm to a medical student also. Therefore, a stepwise approach has been proposed to teach a CBME-driven curriculum to medical students. [ABSTRACT FROM AUTHOR]

Restricted access to healthcare during COVID-19 pandemic warranted an urgent adaptation of telemedicine practice. We describe a synchronous, stepwise (telephonic, video, and in-person consultation) direct-care model. From 18th May to 31st August 2020, 128 new and 198 follow-up patients received consultation. Eighty-nine percent of new patients required video-consultation. Sixty-eight percent of follow-up cases were managed by telephonic consultation. A third of new and a fifth of the follow-up patients had to be called for physical consultation. Limited access to and understanding of the technologies, potential breach in privacy, and restrictions imposed on online prescription of medications posed significant challenges., (Copyright © 2021. Published by Elsevier B.V.)

When and how the TP underwent uplift and deformation are still under heated debate. We present paleomagnetic evidence for the NB in the northeastern central TP to help decipher the potential plateau deformation mechanism. Magnetostratigraphy with zircon U‐Pb age of volcanic rock demonstrates that the NB basin deposited during 52.5–35.0 Ma. Paleomagnetic declinations indicate that the basin experienced counterclockwise rotation of 25.9 ± 7.2° during 52–46 Ma and clockwise rotation of 24.4 ± 9.7° during 41–35 Ma, which coexisted with the intrusion and explosion of volcanic rocks at 51–46 and 39–35 Ma. We proposed a stepwise compression and extrusion model to interpret the basin deposition, rotation, and volcanism by northward compression and eastward extrusion of the eastern Lhasa and Qiangtang Blocks (Proto‐TP) in relation to the Sichuan Basin as early response to the India‐Asia collision. Plain Language Summary: How the Tibetan Plateau (TP) adjusted its inner crustal thickening and tectonic deformation during the India‐Asia collision is still in hot debate, for example, through lateral extrusion or continuous distribution. The Nangqian Basin (NB) is located in the bending (transitional) part from an east‐west tectonic area in the central TP to a north‐south tectonic area in the eastern and southeastern TP. It is an ideal location to provide abundant tectonic evidences for the plateau deformation and uplift models. We report a detailed paleomagnetic dating of the Paleogene sedimentary sequence from the NB with a complete paleomagnetic rotation analysis. Radiometric and magnetostratigraphic dating suggested that the NB commenced its deposition at 52.5 Ma and ended at 35.0 Ma. Paleomagnetic declination data reveal a change of rotation sense of the NB, from a counterclockwise rotation of 25.9° at 52–46 Ma to a clockwise rotation of 24.4° at 41–35 Ma. Integrated with other lines of geological evidence, we believe that the Eocene deformation, rotation, and uplift of the south and east central TP in response to the early India‐Asia collision can be explained by stepwise compressions and eastward extrusions. Key Points: Magnetostratigraphic results demonstrate that the Early Cenozoic sedimentary sequence of the Nangqian Basin yields ages of 52.5–35.0 MaDeclination data indicate change of rotation in the Nangqian Basin from counterclockwise during 52–46 Ma to clockwise during 41–35 MaThe Eocene deformation, rotation, and uplift of the east central Tibetan Plateau favor the compression and extrusion model [ABSTRACT FROM AUTHOR]

Importance: A stepwise approach that includes screening and lifestyle modification followed by the addition of metformin for individuals with high risk of diabetes is recommended to delay progression to diabetes; however, there is scant evidence regarding whether this approach is cost-effective., Objective: To estimate the cost-effectiveness of a stepwise approach in the Diabetes Community Lifestyle Improvement Program., Design, Setting, and Participants: This economic evaluation study included 578 adults with impaired glucose tolerance, impaired fasting glucose, or both. Participants were enrolled in the Diabetes Community Lifestyle Improvement Program, a randomized clinical trial with 3-year follow-up conducted at a diabetes care and research center in Chennai, India., Interventions: The intervention group underwent a 6-month lifestyle modification curriculum plus stepwise addition of metformin; the control group received standard lifestyle advice., Main Outcomes and Measures: Cost, health benefits, and incremental cost-effectiveness ratios (ICERs) were estimated from multipayer (including direct medical costs) and societal (including direct medical and nonmedical costs) perspectives. Costs and ICERs were reported in 2019 Indian rupees (INR) and purchasing power parity-adjusted international dollars (INT $)., Results: The mean (SD) age of the 578 participants was 44.4 (9.3) years, and 364 (63.2%) were men. Mean (SD) body mass index was 27.9 (3.7), and the mean (SD) glycated hemoglobin level was 6.0% (0.5). Implementing lifestyle modification and metformin was associated with INR 10 549 (95% CI, INR 10 134-10 964) (INT $803 [95% CI, INT $771-834]) higher direct costs; INR 5194 (95% CI, INR 3187-INR 7201) (INT $395; 95% CI, INT $65-147) higher direct nonmedical costs, an absolute diabetes risk reduction of 10.2% (95% CI, 1.9% to 18.5%), and an incremental gain of 0.099 (95% CI, 0.018 to 0.179) quality-adjusted life-years per participant. From a multipayer perspective (including screening costs), mean ICERs were INR 1912 (INT $145) per 1 percentage point diabetes risk reduction, INR 191 090 (INT $14 539) per diabetes case prevented and/or delayed, and INR 196 960 (INT $14 986) per quality-adjusted life-year gained. In the scenario of a 50% increase or decrease in screening and intervention costs, the mean ICERs varied from INR 855 (INT $65) to INR 2968 (INT $226) per 1 percentage point diabetes risk reduction, from INR 85 495 (INT $6505) to INR 296 681 (INT $22 574) per diabetes case prevented, and from INR 88 121 (INT $6705) to INR 305 798 (INT $23 267) per quality-adjusted life-year gained., Conclusions and Relevance: The findings of this study suggest that a stepwise approach for diabetes prevention is likely to be cost-effective, even if screening costs for identifying high-risk individuals are added.

Objectives: Most World Health Organisation (WHO) STEPS surveys use cluster sampling to assess the prevalence of risk factors for non-communicable diseases (NCDs) for which design effects need to be estimated using intracluster correlation (ICCs) coefficients, for sample size calculation. Although there are many reports of risk factor surveys reported from developing countries, there are very few reports of ICCs for risk factors for NCDs, which can inform planning the appropriate sample size needed for such surveys. This study reports the ICCs for NCD risk factors, obtained from a WHO STEPS survey conducted in Vellore district, in the state of Tamil Nadu, South India., Study Design: Cross-sectional study., Methods: A cross-sectional study was carried out in 48 urban clusters (wards) and nine rural clusters (villages) between 2011 and 2012, using the WHO STEPS methodology for assessing behavioural, anthropometric, physical and biochemical risk factors. The ICC estimates for various risk factors were obtained using loneway and xtmelogit commands using STATA to study clustering of risk factors., Results: The number of respondents was 6196 adults aged 30-64 years. The median ICC of cardiovascular risk factors in the urban area was 0.046, while it was 0.064 in the rural area. Clustering was higher for behavioural risk factors such as physical activity (ICC: 0.179 rural, 0.049 urban) and fruit and vegetable intake (ICC: 0.105 rural, 0.091 urban) as compared with physical risk factors (ICCs for hypertension: 0.044 rural, 0.006 urban; body mass index: 0.046 rural, 0.041 urban) and biochemical outcomes such as fasting plasma glucose (ICC: 0.017 rural, 0.027 urban)., Conclusions: This study provides estimates of ICCs for cardiovascular risk factors from Vellore, South India, as such data have not been reported from WHO STEPS surveys in India or neighbouring countries. Such estimates of ICCs if reported from various WHO STEPS being carried out across the country can contribute to better planning of epidemiological surveys. Clustering of behavioural risk factors at village/ward level as seen in this study points to the need for community-based interventions for health promotion, as spatial clustering influences behaviour, which in turn affects chronic disease outcomes., (Copyright © 2018 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.)

Objective: This study tests the effectiveness of expert guidelines for diabetes prevention: lifestyle intervention with addition of metformin, when required, among people with prediabetes., Research Design and Methods: The Diabetes Community Lifestyle Improvement Program (D-CLIP) is a randomized, controlled, translation trial of 578 overweight/obese Asian Indian adults with isolated impaired glucose tolerance (iIGT), isolated impaired fasting glucose (iIFG), or IFG+IGT in Chennai, India. Eligible individuals were identified through community-based recruitment and randomized to standard lifestyle advice (control) or a 6-month, culturally tailored, U.S. Diabetes Prevention Program-based lifestyle curriculum plus stepwise addition of metformin (500 mg, twice daily) for participants at highest risk of conversion to diabetes at ≥4 months of follow-up. The primary outcome, diabetes incidence, was assessed biannually and compared across study arms using an intention-to-treat analysis., Results: During 3 years of follow-up, 34.9% of control and 25.7% of intervention participants developed diabetes (P = 0.014); the relative risk reduction (RRR) was 32% (95% CI 7-50), and the number needed to treat to prevent one case of diabetes was 9.8. The RRR varied by prediabetes type (IFG+IGT, 36%; iIGT, 31%; iIFG, 12%; P = 0.77) and was stronger in participants 50 years or older, male, or obese. Most participants (72.0%) required metformin in addition to lifestyle, although there was variability by prediabetes type (iIFG, 76.5%; IFG+IGT, 83.0%; iIGT, 51.3%)., Conclusions: Stepwise diabetes prevention in people with prediabetes can effectively reduce diabetes incidence by a third in community settings; however, people with iIFG may require different interventions., (© 2016 by the American Diabetes Association.)

India has the highest number of retinoblastoma (RB) patients among the developing countries owing to its increasing population. Of the patients with RB, about 40% have the heritable form of the disease, making genetic analysis of the RB1 gene an integral part of disease management. However, given the large size of the RB1 gene with its widely dispersed exons and no reported hotspots, genetic testing can be cumbersome. To overcome this problem, we have developed a rapid screening strategy by prioritizing the order of exons to be analyzed, based on the frequency of nonsense mutations, deletions and duplications reported in the RB1-Leiden Open Variation Database and published literature on Indian patients. Using this strategy for genetic analysis, mutations were identified in 76% of patients in half the actual time and one third of the cost. This reduction in time and cost will allow for better risk prediction for siblings and offspring, thereby facilitating genetic counseling for families, especially in developing countries.

This study gives insight into the spatiotemporal variability of respirable PM concentrations around typically highly mechanized opencast coal mines in India and its influence on ambient air quality, which at present is scant in the literature. The results suggest that at a distance of 500 m from the pit boundary, the respirable PM concentrations were found higher than the background concentration (1.52, 1.80 and 1.89 times for PM10, PM2.5 and PM1 at Mine 1 and 1.4, 1.35 and 1.35 times for PM10, PM2.5 and PM1 at Mine 2) which suggests that residents up to and beyond 500 m from the mine are exposed to the PM emitted from mining activities. For PM2.5 and PM1 concentrations, RH was the most important determinant (PM2.5: 24.8%; PM1: 30.1%). Pit boundary PM concentration was the weakest determinant (7%) for the PM2.5 concentration in mine surroundings, and wind speed was found as the weakest determinant (6.6%) for PM1 concentration. Conversely, distance (20.8%) was the important determinant of PM10 concentrations. All the four predictors (RH, wind speed, distance and Pit boundary PM concentration) could explain 46–54% variability in the PM concentrations. Inclusion of pit boundary PM concentration as a predictor increased the prediction capability of the models (all the developed models have R2 > 0.40 at significance level p < 0.05). PM prediction models can be used by the mining and regulatory authorities to assess the respirable PM level in mine surroundings. [ABSTRACT FROM AUTHOR]

The curve geometry influences the driver's speed choice behavior when passing through a horizontal curve. Hence, speed prediction models are essential to ensure highway safety, particularly under heterogeneous traffc conditions prevailing in India, where various classes of vehicles occupy the roadway space. Toward this, the present study aims to develop an operating speed increment and decrement model to identify the influence of the highway geometry variables on the drivers' speed choice behavior. The National Highway NH-953 is located on hilly terrain, from which 15 curves with various geometric characteristics were selected. The speed data were collected using the radar gun for three dominant vehicle types: motorized two-wheelers (2Ws), cars, and heavy commercial vehicles (HCVs) at three curve points. After that, the two types of speed differences are calculated: the differential of 85th percentile speed (ΔV85) and 85th percentile speed differential (Δ85V). The backward stepwise regression (BSR) technique was used on the collected speed data to develop the operating speed increment and decrement models. The results revealed that the curve geometric variables like curve radius, deflection angle, curve length, and tangent length significantly influence the drivers' speed choice behavior passing through the horizontal curves. Besides, for all three vehicle types, speed increments and decrement models ΔV85 underestimated Δ85V by 3 to 13 km=h [ABSTRACT FROM AUTHOR]

Anthropological research relies on skeletal and dental remains for the identification of species. Sexual dimorphism is the systematic difference in form between males and females of the same species. This study is designed to compute a new formula for sex determination using discriminant function analysis in the deciduous crown dimensions of a paediatric population of South Indian origin and to check its accuracy. The sample consisted of 93 females and 90 males of South Indian origin aged between 5 and 13 years. Alginate impressions of the upper dental arch were made and casts were poured immediately. A digital vernier calliper was used to obtain measurements. Teeth considered for measurement were deciduous maxillary canines and molars. Our study is a maiden attempt in considering diagonal measurements along with mesiodistal (MD) and buccolingual (BL) dimensions as predictor variables for sex determination. Statistical analysis was performed using the Statistical Package for the Social Science version 17.0 software. By using the Student t-test, the different predictor variables of teeth selected between male and females were found to be significant (p < 0.05). Highly significant sexual dimorphism was found in the mean MD dimension of maxillary right canine and right and left first molar, BL dimension of right first molar, distobuccal-mesiolingual of right and left first molar and right second molar and mesiobuccal-distolingual of right second molar. The percentage of sexual dimorphism in MD dimensions revealed that the right upper first molar was the most dimorphic tooth and the upper first molar of the left side was the least dimorphic of the six teeth studied. The present study found the level of sexual dimorphism in the deciduous crown dimensions of a selected group of South Indian population, which is sufficiently large to determine sex with an accuracy of 87.2-88% by discriminant function analysis. Hence the formula derived from the present study could be of some value in sex determination of paediatric populations of South Indian origin., (Copyright © 2013 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.)

Host genetics has an important role in leprosy, and variants in the shared promoter region of PARK2 and PACRG were the first major susceptibility factors identified by positional cloning. Here we report the linkage disequilibrium mapping of the second linkage peak of our previous genome-wide scan, located close to the HLA complex. In both a Vietnamese familial sample and an Indian case-control sample, the low-producing lymphotoxin-alpha (LTA)+80 A allele was significantly associated with an increase in leprosy risk (P = 0.007 and P = 0.01, respectively). Analysis of an additional case-control sample from Brazil and an additional familial sample from Vietnam showed that the LTA+80 effect was much stronger in young individuals. In the combined sample of 298 Vietnamese familial trios, the odds ratio of leprosy for LTA+80 AA/AC versus CC subjects was 2.11 (P = 0.000024), which increased to 5.63 (P = 0.0000004) in the subsample of 121 trios of affected individuals diagnosed before 16 years of age. In addition to identifying LTA as a major gene associated with early-onset leprosy, our study highlights the critical role of case- and population-specific factors in the dissection of susceptibility variants in complex diseases.

Sorghum is an important dual-purpose crop of India grown for food and fodder. Prevailing weather conditions during the crop growth period determine the yield of sorghum. Hence, the crop yield forecasting models based on weather parameters will be an appropriate option for policymakers and researchers to develop sustainable cropping strategies. In the present study, six multivariate weather-based models viz., least absolute shrinkage and selection operator (LASSO), elastic net (ENET), principal component analysis (PCA) in combination with stepwise multiple linear regression (SMLR), artificial neural network (ANN) alone and in combination with PCA and ridge regression model are examined by fixing 90% of the data for calibration and remaining dataset for validation to forecast rabi sorghum yield for different districts of Karnataka. The R2 and root mean square error (RMSE) during calibration ranged between 0.42 to 0.98 and 30.48 to 304.17 kg ha−1, respectively, without actual evapotranspiration (AET) whereas, these evaluation parameters varied from 0.38 to 0.99 and 19.84 to 308.79 kg ha−1, respectively with AET inclusion. During validation, the RMSE and nRMSE (normalized root mean square error) varied between 88.99 to 1265.03 kg ha−1 and 4.49 to 96.84%, respectively without AET and including AET as one of the weather variable RMSE and nRMSE were 63.48 to 1172.01 kg ha−1 and 4.16 to 92.56%, respectively. The performance of six multivariate models revealed that LASSO was the best model followed by ENET compared to PCA_SMLR, ANN, PCA_ANN and ridge regression models because of reduced overfitting through penalisation of regression coefficient. Thus, it can be concluded that LASSO and ENET weather-based models can be effectively utilized for the district level forecast of sorghum yield. [ABSTRACT FROM AUTHOR]

Background: Garden pea is a cool season vegetable crop cultivated extensively throughout the world. Besides nutritional quality it also boosts soils through the fixation of atmospheric nitrogen. The most important task of pea breeding is to develop varieties with high and stable production, different maturity types and resistance against biotic and abiotic stresses. To fulfil these objectives, analysis of genetic diversity is the prerequisite to choose genetically diverse parents for a successful hybridization program and to know the source of genes for a particular trait within the available germplasm. Methods: A study was conducted at ICAR-Indian Institute of Vegetable Research (IIVR), Varanasi during 2015, using principle component analysis, correlation analysis and stepwise regression analysis approaches to assess the genetic diversity present in 160 pea genotypes for the identification of diverse parents for use in crop improvement. Result: Based on the phenotypic data, three superior genotypes VRPD-2, VRPR-15 and VRP-292 were identified on the basis of pod yield, number of pods per plant, ten pod weight, pod length and number of seeds per pod whereas three other genotypes VRPE-45-1, VRPE-55 and VRPE-36 were found early flowering. Principle Component Analysis revealed that first four principle components contributed to 85% of the total variation so these four were given due importance for further explanation. Stepwise multiple regression analysis revealed that number of pods per plant, ten pod weight and number of internode for first pod were the best predictors of pod yield per plant. [ABSTRACT FROM AUTHOR]

A comparison of induction of labour (IOL) using three doses of 25 µg vaginal misoprostol inserted at intervals of 4 h or more with a stepwise oral regime starting with 50 µg followed by two doses of 100 µg was studied in a double-blind placebo-controlled trial in a tertiary centre in South India. Primary outcome was vaginal delivery in 24 h. Significantly more women in the first group required oxytocin augmentation and a third dose of the drug than women in the second group. Uterine tachysystole and other maternal and neonatal complications were similar. Thus it is concluded that women induced with oral, as compared to vaginal misoprostol are more likely to labour without oxytocin. [ABSTRACT FROM AUTHOR]

This study aims to develop predictive models for rice yield by applying multivariate techniques. It utilizes stepwise multiple regression, discriminant function analysis and logistic regression techniques to forecast crop yield in specific districts of Haryana. The time series data on rice crop have been divided into two and three classes based on crop yield. The yearly time series data of rice yield from 1980–81 to 2020–21 have been taken from various issues of Statistical Abstracts of Haryana. The study also utilized fortnightly meteorological data sourced from the Agrometeorology Department of CCS HAU, India. For comparing various predictive models' performance, evaluation of measures like Root Mean Square Error, Predicted Error Sum of Squares, Mean Absolute Deviation and Mean Absolute Percentage Error have been used. Results of the study indicated that discriminant function analysis emerged as the most effective to predict the rice yield accurately as compared to logistic regression. Importantly, the research highlighted that the optimum time for forecasting the rice yield is 1 month prior to the crops harvesting, offering valuable insight for agricultural planning and decision-making. This approach demonstrates the fusion of weather data and advanced statistical techniques, showcasing the potential for more precise and informed agricultural practices. [ABSTRACT FROM AUTHOR]

Objectives: The present study aims to assess the prevalence and predictors of smartphone addiction and insomnia among nurses working in the outpatient department (OPD) after the second wave of the coronavirus disease 2019 (COVID-19) pandemic. Materials and Methods: A descriptive, cross-sectional study was carried out among 117 OPD nurses between October and December 2021 using a purposive sampling technique. Two self-reported standardized scales, the Smartphone Addiction Scale-Short Version and Insomnia Severity Index were used. Kolmogorov–Smirnov test, Mann–Whitney U, and Kruskal–Wallis H test were used. Pearson's correlation and Scatter plot were used to determine the relationship between the study variables. A stepwise multiple linear regression analysis was also performed. Results: The majority of participants had slight smartphone addiction (78.6%) and suffered from sub-threshold to severe forms of insomnia (73.5%). A significant mild positive correlation was found between smartphone addiction and insomnia (r = 0.195, P < 0.05). Stepwise multivariate logistic regression analysis predicted factors such as female gender and exposure to smartphones for more than 5 years influencing smartphone addiction. A strong influence of exposure to the smartphone for more than 5 years was found on insomnia severity. Conclusion: Smartphone addiction and insomnia were identified problems among nurses working in the OPD after the second wave of the COVID-19 pandemic, requiring an urgent need to identify and manage various factors responsible for smartphone addiction and insomnia such as female gender and years of exposure to smartphones. [ABSTRACT FROM AUTHOR]

present study aims to develop vehicle type-wise operating-speed prediction (OSP) models for heterogeneous traffic on twolane rural highways in Indian hilly terrains. For the present study, 27 curves with varying geometric characteristics located along the National Highway (NH-953) connecting Netrang and Rajpipla in the western state of Gujarat, India, were selected. Speed data were collected using radar guns at three curve locations (entry point, midpoint, and exit point) in each travel direction for three dominant types of vehicles: motorized two-wheelers (2W), cars, and heavy commercial vehicles (HCVs). OSP models were developed for different vehicle types at three curve points using the backward elimination stepwise regression (BSR) technique. The results revealed that the preceding curve point's operating speed, curve length, and tangent length positively affected operating speed. In contrast, deflection angle, curve sharpness, and grade had adverse effects. The curve geometric characteristics had the most negligible impact on the operating speed of 2Wand a significant effect on HCV. Among all the curve-related aspects, curve length was the most significant variable and affected the speed of all three vehicle types, followed by curve sharpness. Further, the developed OSP models were applied to the other hilly terrain to check the transferability of the model. As an important outcome, the developed OSP models were used to evaluate geometric design consistency. This highlights the need for geometric and traffic-calming measures to improve highway operating-speed consistency and driver safety. [ABSTRACT FROM AUTHOR]

Background: Lifestyle modifications (LM) are crucial in managing comorbid Tuberculosis (TB) and Diabetes Mellitus (DM) patients, significantly impacting treatment outcomes and overall health. In view of this, a study was conducted to clarify sociocultural features associated with LM among TB–diabetes comorbid patients. Methods: A cross-sectional descriptive study among randomly selected 180 adult TB–diabetes-comorbid-patients was conducted using a semi-structured interview schedule. Mann–Whitney-U-test was used to examine differences in means between patterns of distress (PDs) and perceived causes (PCs) regarding TB and Diabetes for two identified LM strategies among comorbid patients. Stepwise logistic regression was used to study factors associated with these LM strategies. Results: TB–diabetes-comorbid-patients reporting physical symptoms as PDs preferred to follow the LM-1 strategy for TB and LM-2 for Diabetes. In contrast, patients reporting health-illness-injury-related causes follow LM-2 for TB and LM-1 for Diabetes. Further patients reporting hypertension for Diabetes (AOR = 2.916, 95% CI 0.9262–9.1788) and concerns-about-the-course-of-TB-illness (AOR = 3.746, 95% CI 1.4683–9.5593) as PDs were 3–4 times more likely to follow LM-1. While those reporting prior illnesses (AOR = 4.255, 95% CI 1.3941–12.9837) and sanitation (AOR = 5.242, 95% CI 1.2028–22.8446) as PCs for TB were 4–5 times follow LM-2. Patients who perceived consumption of alcohol as PCs of Diabetes were 10 times more likely to stop addictions (AOR = 9.680, 95% CI 2.5555–36.6639) and follow the LM-2 strategy. Conclusion: Given significant associations of sociocultural features with LM strategies, consideration of sociocultural features vis-à-vis these strategies is indispensable for managing TBDM comorbidity, emphasizing the need for developing comprehensive, patient-centred self-management interventions to enhance adherence and improve health outcomes. [ABSTRACT FROM AUTHOR]

Body volume and 35 anthropometric measurements were obtained from 88 active soldiers using standard techniques. These anthropometric measurements were examined for their possible relationships to body volume using stepwise linear regression analysis. Four measurements (Body weight, anterior thigh skinfold thickness, subscapular skinfold thickness and suprailiac skinfold thickness) accounted for 99.7% of the variation in body volume and the introduction of each of these measurements in the equation was significant. The regression equation for predicting body volume from these 4 anthropometric measurements had a multiple correlation coefficient of 0.9987 (P less than 0.001). Body weight alone was correlated with body volume to the extent of 0.9966. An attempt has therefore been made to develop a multiple linear regression equation without incorporation of body weight in the regression analysis. Nine measurements were selected by stepwise linear regression analysis for predicting body volume. These nine measurements accounted for 97.1% of the variation in body volume. These equations have been validated on another small sample of 22 soldiers. The analysis has also revealed that a direct regression of body density from the anthropometric variables gives more accurate results than when estimated body volumes are utilized for calculating body density.

Nodulation and shoot nitrogen of two varieties of soybean (Glycine max) were studied with twenty strains of Rhizobium japonicum. A number of cultural characteristics of the strains in isolation to the symbiotic system were also studied. A stepwise selection method was employed for detecting efficient cultures through the cultural characteristics which showed association with the steps in the symbiotic system. Nodulation of one variety was found to be associated with the dehydrogenase activity and the growth of microbes in the medium containing soil extract, whereas the nodulation of another variety showed association with the growth in the media containing asparagine and tryptophane. The shoot nitrogen of one nodulated cultivar correlated with the microbial growth in Elkan's medium in the medium containing serine and glucose, whereas the shoot nitrogen of the other nodulating variety correlated with the growth of the cultures in the medium containing aspartic acid. The validity of this approach to the problem for detecting efficient strains through cultural characteristics was discussed.

Remote sensing was used as a potential solution for monitoring the surface water quality parameters as an alternative to the traditional in situ measurements which are time consuming and labour-intensive. While most of the studies are restricted in just analysing the optical water quality parameters, only few studies have attempted the estimation of non-optical water quality parameters. In this paper, a correlation was developed between various optical and non-optical water quality parameters, thereby establishing an indirect relationship between non-optical parameters and reflectance data based on which the predictive models were developed. The water body chosen for this present study is the Ukkadam Lake situated in Coimbatore, Tamilnadu, India (10.9917° North, 76.9722° East). The correlation between reflectance data obtained from Sentinel-2 and Unmanned aerial vehicle images along with in situ measured data were analysed using stepwise regression method. Algorithms were developed for assessing the water quality parameters like turbidity, Total suspended solids, Total organic carbon, Chemical oxygen demand, Biological oxygen demand and Dissolved oxygen that were based on Sentinel-2 with high coefficient of determination (R2). Unmanned aerial vehicle-based Stepwise regression models were employed for assessing Total suspended solids, Total organic carbon and Chemical oxygen demand. The developed models were validated with 25% of sample data acquired, and the algorithms showed that multispectral data from Sentinel-2 and RGB data from Unmanned aerial vehicles can be effectively used to estimate the concentration of various water quality parameters with reasonable accuracy in case of large water bodies, including the one chosen for this study. [ABSTRACT FROM AUTHOR]

The emergence of lumpy skin disease (LSD) among cattle in India is concerning. District-level data on LSD cases in Uttar Pradesh between 2021 and 2022 were analyzed. A stepwise spatial analytical approach was followed by first constructing yearly and monthly disease maps for LSD incidence rates (IRs), then spatially interpolating the LSD IRs, followed by evaluating the global and local clustering of LSD IRs and finally conducting spatial regression modeling. Overall, 5784 LSD cases from 6 districts and 112,226 cases from 33 districts were detected in 2021 and 2022, respectively. In the incremental spatial autocorrelation analysis, the highest global clustering of LSD IRs for the 2022 outbreak was detected at 196.49 km. For the 2021 LSD outbreak, one district with high-low and nine districts with low-high LSD IRs were identified in the eastern region of the state. For the 2022 LSD outbreak, 13 districts with high-high and 7 districts with low-high LSD IRs were identified in the western part of the state. A geographically weighted regression model identified the impact of climate (temperature and humidity) and land cover (pasture, fallow, and non-agricultural land) on LSD IRs. The study results can aid animal health authorities in developing LSD prevention and control programs. [ABSTRACT FROM AUTHOR]

Objective: Though airway ultrasonography (USG) is used to assess difficult laryngoscopy (DL), there is still ambiguity about approach followed and parameters assessed. There is need of a simple, stepwise sonographic assessment with clearly defined parameters for DL prediction. The primary objective of this study was to find diagnostic accuracy of sonographic parameters measured by a stepwise Airway- USG in DL prediction (DLP). Methods: This prospective, observational cohort study was done in 217 elective surgical adult patients administered general anaesthesia with tracheal intubation using conventional laryngoscopy from 1st May 2019 to 31st July 2020, after ethical approval. A sagittal Airway- USG was done using 2-6 Hz transducer in three steps specifying probe placement and head position. Demographic, clinical and Airway- USG measurements were noted. Correlation of the clinical/sonographic parameters was made with Cormack-Lehane score on DL. After receiver operating characteristic curve plotting, the sensitivity, specificity, positive predictive value, negative predictive value (NPV) of DL was calculated for each parameter using open-epi software. Results: DL was observed in 19/217 patients. Airway-USG parameters of skin to epiglottis distance >2.45 cm, hyomental distance with head extension <5.13 cm, head neutral <4.5 cm, their ratio <1.18, maximum tongue thickness >3.93 cm and maximum skin to tongue distance >5.45 cm were statistically significant in predicting DL. DLP score with presence of >3 positive parameters showed 98% specificity, 98% NPV and 96% diagnostic accuracy to predict DL. Conclusion: DLP score derived from Airway-USG may be used as a screening and diagnostic tool for DL. [ABSTRACT FROM AUTHOR]

Background: Several observational studies have reported the prevalence of cerebral microbleeds (CMBs) and their risk factors in an elderly population. Any information in this regard is currently lacking from India. Aim of this study was to estimate the prevalence, risk factors of CMBs, and association with cognition in an Indian urban population aged 50 years and above. Methods: Household surveys were conducted as part of ongoing Longitudinal Cognition and Aging Research on Population of the National Capital Region (LoCARPoN) study in areas of urban Delhi. Magnetic resonance imaging of the brain was performed in 2599 participants. Using standard neuropsychological battery, mean Z-scores for each domain (memory, executive, information) were derived. Binary and stepwise logistic regression models were used to determine associated risk factors for the presence of CMB and its association with cognitive domains. Results: The prevalence of CMBs was 14.42% (95% confidence interval [CI]: 13.06-15.73). Of these, 203 (7.81%) participants had single CMBs and 172 (6.61%) had multiple microbleeds (≥2). Higher prevalence was observed in older age (6070 years: odds ratio [OR]: 1.25 [95% CI: 0.93-1.67]; 70-80 years: OR: 2.05 [95% CI: 1.48-2.84]; ≥80 years: OR: 3.27 [95% CI: 1.97-5.44]) compared to individuals in the age group 50-60 years. History of stroke (OR: 2.97 [95% CI: 1.56-5.66]), hypertension (OR: 1.36 [95% CI: 1.05-1.75]), and smoking (OR: 1.43 [95% CI: 1.11-1.85]) was associated with at least one CMB. Multiple CMBs were associated with worse scores in memory and executive domains. Conclusion: Older age, hypertension, history of stroke, and history of smoking emerged as important risk factors for the presence of multiple CMBs. Follow-up study is required to determine implications of CMBs. [ABSTRACT FROM AUTHOR]

Sugarcane is one of the leading commercial crops grown in India. The prevailing weather during the various crop-growth stages significantly impacts sugarcane productivity and the quality of its juice. The objective of this study was to predict the yield of sugarcane during different growth periods using machine learning techniques viz., random forest (RF), support vector machine (SVM), stepwise multiple linear regression (SMLR) and artificial neural networks (ANN). The performance of different yield forecasting models was assessed based on the coefficient of determination (R2), root mean square error (RMSE), normalized root mean square error (nRMSE) and model efficiency (EF). Among the models, ANN model was able to predict the yield at different growth stages with higher R2 and lower nRMSE during both calibration and validation. The performance of models across the forecasts was ranked based on the model efficiency as ANN > RF > SVM > SMLR. This study demonstrated that the ANN model can be used for reliable yield forecasting of sugarcane at different growth stages. [ABSTRACT FROM AUTHOR]

Background: Adolescence is the most complex stage of development that causes the greatest difficulties in their life because of frequent physical and emotional issues including deviated character and behavioral disorders. Aim: This descriptive comparative study was intended to compare self-esteem between heinous and non-heinous male delinquent adolescents residing in observation homes. Materials and Methods: A quantitative research approach with a non-experimental descriptive comparative design was adopted. One hundred and seventy-nine male delinquent adolescents (Heinous = 74, Non-Heinous = 105) residing in two observation homes were selected by convenience sampling technique based on the type of crime committed. The standardized Rosenberg's self-esteem scale was used to collect the data. Results: We analyzed the data with Chi-square for homogeneity of sample characteristics, an independent t test for comparison of self-esteem between groups, an independent t test, one-way ANOVA for the association, and stepwise regression for predictors. There was a statistically significant difference in self-esteem between groups, a significant association of self-esteem with age and duration of stay in the heinous group and with the father's education in the non-heinous group, and the father's education, mother's occupation, substance use, and order of birth had predicted the self-esteem in non-heinous group. Conclusion: The study concluded that self-esteem significantly varied between heinous and non-heinous group delinquents. This study is the first of its kind and provided initial evidence by filling the gap in the literature to understand the difference in the level of self-esteem among delinquent adolescents according to the type of crime committed. [ABSTRACT FROM AUTHOR]

Reinforced concrete structures are an inherent part of the construction sector. Every in situ reinforced concrete structure cardinally involves rebar-fixing works, which entails activities like transporting, marking, laying, and tying the rebar for the components under construction. Rebar-fixing absorbs a significant number of man-hours during the operation. Therefore, productivity of rebar fixers is a critical concern in construction. Several attributes influence rebar-fixing productivity. Former studies have investigated the impact of the attributes separately and predominantly using qualitative data. A few studies have assessed rebar productivity quantitatively but ignored the effects of some crucial parameters, such as congestion, crew composition, and construction delays. Moreover, studies are limited to account for all time proportions like productive, semiproductive, and nonproductive while assessing rebar productivity. Therefore, this study addresses the aforementioned research gaps by assessing the impact of diverse attributes using direct measures of rebar-fixing productivity and its attributes. Initially, hypotheses were developed to determine the influence of eight attributes identified in this study on rebar-fixing productivity. Next, the data were recorded from one large construction project in Gujarat, India. The work sampling approach was adopted for the productivity assessment of rebar fixers at the project site to evaluate each time proportion. Furthermore, the stepwise regression analysis was performed on the data set to examine the hypotheses. Results indicate that attributes such as quantity of reinforcement, characteristic rebar diameter, and congestion have a significant positive impact on rebar-fixing productivity, whereas work duration has a significant negative impact on it. The outcomes of this research can aid the site management, structural engineers, and construction planners in decision-making to enhance the productivity of rebar fixers, thereby adhering to the budget and schedule constraints of the project. Reinforcement fixing is a major activity that significantly controls the revenue and duration of any construction project. Labor is an indispensable part of this activity. Therefore, it is crucial to guard the output of the rebar fixers. This study is a guiding light for the construction stakeholders to manage the productivity of rebar fixers. The various identified attributes are practically examined to know their impact on the productivity of rebar fixers. The results can be helpful in decision-making and process improvement at the site management level. During the designing stage of a structure, it can support the design backed up with evidence to improve the rebar-fixing productivity significantly. [ABSTRACT FROM AUTHOR]

Food is an integral part of a tourist's travel experience. Tourists have acquired a multidimensional approach to augment their food experiences. For tourists, various dimensions that determine overall satisfaction through food experiences are local gastronomic offerings, dining atmosphere, food quality and price, with food quality being the most significant element. The present study aims to examine the impact of attributes of Indian cuisine on overall satisfaction of the foreign tourists visiting India. A total of 432 foreign tourists who visited India responded to a self-administered questionnaire. To test the research hypothesis, the methodology of stepwise multiple regression models was used. The findings of the study reveal that fast and efficient food service of the restaurants, sufficient portion size of food items and value for money are the attributes that facilitate memorable culinary experience. Apart from this aroma, taste and flavor of traditional food items also creates a memorable positive food experience. The study also concludes that all these attributes significantly contribute towards achieving overall satisfaction based on the culinary experience of foreign tourists. [ABSTRACT FROM AUTHOR]

Background: Improvement of number of low birth weight (LBW) baby-mother dyad practicing KMC in postnatal ward in a tertiary care hospital of eastern India and to increase number of babies weighing between 1.8-2.5kg receiving KMC from 11.5% to at least 60% in postnatal ward with increment of total duration from 1.9 to minimum 8hours a day. Methods: QI team was formed. The potential barriers for initiation of KMC among this group of dyads were evaluated using fish bone analysis. Stepwise measures (initiation of early skin-to-skin contact immediately after birth), KMC as an integral part of treatment, counseling of mothers, allotting dedicated nursing staff in each shift to monitor KMC, introduction of bedside KMC Sheet with KMC register, provision of separate beds for "KMC corner") were introduced and subsequently tested by multiple Plan-do-study-act (PDSA) cycles. Data on duration of KMC per day was measured by bedside nurses on daily basis. Results: Total 510 neonates were enrolled in the study (110 in baseline phase, 116 in implementation phase and 293 in post intervention phase). Demographic characteristics including birth weight and gestational age were comparable among baseline and post intervention cohorts. During implementation phase, KMC of any duration was received by 40.5%, 67%, 82.5% and 95% neonates following PDSA I, PDSA 2, PDSA 3 and PDSA 4, respectively against 11.5% of baseline phase. In comparison to baseline phase, mean duration of KMC increased from 1.9 hours to 8.6 hours during post implementation phase. Conclusions: Stepwise implementation of PDSA cycles significantly increased the percentage of LBW newborns of weight 1.8-2.5kg receiving KMC for >6 hours a day in Postnatal Ward, thereby resulting in earlier discharge. [ABSTRACT FROM AUTHOR]

Mustard is the second most important edible oilseed after groundnut for India. Adverse weather drastically reduces the mustard yield. Weather variables affect the crop differently during different stages of development. Weather influence on crop yield depends not only on the magnitude of weather variables but also on weather distribution pattern over the crop growing period. Hence, developing models using weather variables for accurate and timely crop yield prediction is foremost important for crop management and planning decisions regarding storage, import, export, etc. Machine learning plays a significant role as it has a decision support tool for crop yield prediction. The models for mustard yield prediction was developed using long-term weather data during the crop growing period along with mustard yield data. Techniques used for developing the model were variable selection using stepwise multiple linear regression (SMLR) and artificial neural network (SMLR-ANN), variable selection using SMLR and support vector machine (SMLR-SVM), variable selection using SMLR and random forest (SMLR-RF), variable extraction using principal component analysis (PCA) and ANN (PCA-ANN), variable extraction using PCA and SVM (PCA-SVM), and variable extraction using PCA and RF (PCA-RF). Optimal combinations of the developed models were done for improving the accuracy of mustard yield prediction. Results showed that, on the basis of model accuracy parameters nRMSE, RMSE, and RPD, the PCA-SVM model performed best among all the six models developed for mustard yield prediction of study areas. Performance of mustard yield prediction done by optimum combinations of the models was better than the individual model. [ABSTRACT FROM AUTHOR]

Biosimilar insulin analogues are increasing market access for diabetic patients globally. Scientific establishment of biosimilarity is cornerstone of this key change in the medical landscape. BGL-ASP is a biosimilar insulin aspart developed by BioGenomics Limited, India. BioGenomics has considered a stepwise approach in generating the totality of evidence required to establish similarity with reference product. Insulin aspart is a recombinant rapid-acting human insulin analogue utilised in the treatment of type-1 and type-2 diabetes mellitus. The single amino acid substitution at position B28 where proline is replaced with aspartic acid results in a decreased propensity to form hexamers, thus increasing the absorption rate on subcutaneous administration compared to native insulin. In order to establish the safety and efficacy of BGL-ASP, the critical quality attributes (CQAs) of BGL-ASP are identified based on the impact created on biological activity, pharmacokinetic/pharmacodynamic (PK/PD), immunogenicity and safety. The CQAs of insulin aspart are related to product structure, purity and functionality and are characterised using a series of state-of-the-art orthogonal analytical tools. The primary protein sequence, the secondary, tertiary and quaternary structure are found to be highly similar for BGL-ASP and reference product. The product related impurities of insulin aspart and the assay content are determined using high performance liquid chromatography (HPLC) based analysis and is similar for BGL-ASP and reference insulin aspart sourced from United States of America (US), Europe Union (EU) and India. The safety, efficacy and immunogenicity of BGL-ASP is also found to be comparable with reference product and is confirmed through the clinical trials conducted as recommended by International Council for Harmonisation of Technical Requirements of Pharmaceuticals for Human Use (ICH) and European Medicines Agency (EMA) guidelines. The data encompassed in this study demonstrates that reference insulin aspart and BGL-ASP are highly similar in terms of structural, physicochemical, and biological properties, thus confirming its safety and efficacy for usage as potential alternative economical medicinal treatment for diabetes mellitus. [ABSTRACT FROM AUTHOR]

Context: Economic burden imposed by sexually transmitted infections (STIs) is substantial in low‑middle‑income countries like India, in spite of the fact that national programs for controlling STIs are operational. Aims: The aim of this study was to estimate the out‑of‑pocket expenses and catastrophic health expenditure (CHE) incurred by patients of STIs and analyze expenditure pattern in relation to various clinical and sociodemographic characteristics. Settings and Design: This was a hospital‑based cross‑sectional study among patients attending Suraksha Clinic. Subject and Methods: The study was conducted among patients aged ≥18 years. Data were collected regarding various direct and indirect expenses incurred, after adjusting any reimbursement or waive off. Total costs exceeding 10% of annual household income were considered catastrophic. Stepwise regression analysis was used to analyze predictors, and P < 0.05 was considered statistically significant. Results: Out of 157 patients, most were suffering from herpetic ulcers (27.4%). The median and interquartile range (IQR) for total OOPE of STI management was `1950 (IQR 1035–5725). Direct expenditure constituted major expenses with a median of `1850 (IQR 787.50–5385.0). The cost of STI management was catastrophic in 15.2% of cases. Lower socioeconomic status, longer traveling distance, overnight stay as a part of seeking treatment at Suraksha Clinic, previous history of other than allopathic treatment, and quack consultation were found to be independent predictors of CHE. Conclusions: Despite free diagnostic and treatment services to STI patients under the National AIDS Control Programme, many incurred considerable costs and catastrophic expenditure toward STI care. Better outreach of health services is required to maximize STI control and lower financial morbidity. [ABSTRACT FROM AUTHOR]

Pollutant emissions at toll stations are expected to be different than at a normal free flowing traffic environment because of stop and go movement of the vehicles at toll stations. This study therefore aimed at investigating the personal exposure of workers at a toll station on a busy national highway. Results showed that toll workers inside the toll collection cabins were exposed to higher DPM (Diesel particulate matter) concentrations (79.6 ± 27.24 µg m−3) than kerbside workers (73.52 ± 40.9 µg m−3). The in-cabin and kerbside PM2.5 (particles with aerodynamic diameter ≤ 2.5 µm) concentrations were 86.1 ± 45.4 µg m−3 and 79.20 ± 48 µg m−3, respectively. For PM10 (particles with aerodynamic diameter ≤ 10 µm) it was 169.56 ± 58.83 µg m−3 in-cabin and 156.41 ± 80.72 µg m−3 at the kerbside. DPM and PM (PM2.5 and PM10) evening concentrations were ~ 2 times higher than the morning concentrations, primarily due to increased traffic and lesser atmospheric dispersion of pollutants. Stepwise regression models showed that temperature, relative humidity and wind speed significantly influenced the DPM and PM concentration. The General Linear Model analysis showed that the predictors could explain 53% (DPM concentrations), 71% (PM2.5 concentration) and 55% (PM10 concentration) variability. Worker's respiratory deposition dose of pollutants was higher (~ 2–3 times) inside the toll cabin than at kerbside; higher in the evening (~ 2 times) than morning and higher (~ 1.5 times) on weekdays than on weekends. The present study demonstrates the need to focus on different policies to control the pollution concentration in workplaces, especially at places having proximity to traffic. [ABSTRACT FROM AUTHOR]

Background: Social and community participation are major indicators to assess the adequacy of treatment and rehabilitation in patients with spinal cord injury (SCI). This study examined the relationship between functional independence, level of disability, and social and community participation among people with SCI in India. Materials and Method: In this cross sectional study, 110 persons with SCI, aged 18 years and above participated in a community setting, in Karnataka, India. Spinal Cord Independence Measure Version III-self-reporting (SCIM III-SR), Craig Handicap Assessment and Reporting Technique (CHART), and WHO Disability Assessment Schedule 2.0 (WHODAS) were the clinical outcome measures. Spearman's correlation and stepwise multiple linear regression were done to determine association and identify the factors determining the community participation of people with SCI. Results: CHART physical independence had a positive correlation with SCIM self-care (R = 0.446) and SCIM mobility (r = 0.434). CHART cognitive independence (R = -0.38) and CHART mobility (R = -0.396) had a weak correlation with WHODAS. SCIM self-care and SCIM mobility (R² = 0.34) were determinants of CHART cognitive independence. SCIM respiratory and sphincter management and SCIM self-care (R² = 0.327) were determinants of CHART mobility. Conclusion: Self-care and mobility of people with SCI determine their ability to successfully reintegrate into the community, warranting a comprehensive community rehabilitation program. [ABSTRACT FROM AUTHOR]

As a next step to better understand the role of cultural tightness-looseness (CTL), this study aimed to examine whether CTL is associated with COVID-19 vaccination behavior among university students, taking into consideration sociocultural perceptions of vaccination across countries. A global online survey was conducted. University students from Japan, the US, and India participated. The average CTL score, three sociocultural perceptions related to COVID-19 vaccination, side effects, infection experience of themselves and family members, and other demographic variables were used to identify the model and to explain the second vaccination status using stepwise logistic regression methods with Akaike Information Criterion (AIC) scores which was for both the total, with the country as a variable, and for each country. Analyses of data from 1289 respondents who received the first vaccine revealed the essential role of CTL in individuals getting the second vaccine, while also revealing differences between countries. Regardless of the limitations, this study adds knowledge about CTL's roles in the COVID-19 vaccination behavior among young generations and provides insights into public health communication practices for issues like COVID-19. [ABSTRACT FROM AUTHOR]

The onset of the Asian summer monsoon (ASM) starts the rainy season in one of the most world populous regions. The present study found that the stepwise ASM onset process (ASMOP) in the Bay of Bengal, South China Sea (SCS), and India exhibits three distinct interannual modes induced by different sea surface temperature anomalies (SSTAs). The first mode features are in‐phase variation of ASMOP in southern Asia, which originates from the ENSO‐related SSTAs and anomalous circulations in the tropical Indo‐Pacific Ocean. The second mode indicates the anomalous ASMOP in India and depends on the southwestern Indian SSTAs that alter the low‐level cross‐equatorial flow over the Arabian Sea. In the third mode, the western North Pacific SSTAs and their resultant circulation anomalies regulate ASMOP in the northern SCS. These extra‐equatorial SSTAs and their associated air‐sea interaction serve as an additional source of seasonal predictability for ASMOP besides El Niño–Southern Oscillation events. Plain Language Summary: The onset of the Asian summer monsoon (ASM) begins the rainy season in South and East Asia, one of the world's most populous regions. In general, the ASM onset process (ASMOP) follows a stepwise progression over the Bay of Bengal (BOB), South China Sea (SCS), and India, in turn. The year‐by‐year relationship between the monsoon onset dates over these areas helps to predict the arrival of the monsoon in Asian countries. However, there is no consensus on the year‐by‐year relationship of ASMOP among these areas. The present study used a unified definition to revisit the distinct modes of interannual variation in ASMOP. The El Niño–Southern Oscillation (ENSO)–associated tropical sea surface temperature anomalies (SSTAs) in the Indian and Pacific oceans can modify ASMOP over BOB, the southern SCS, and India simultaneously. Besides the influence of ENSO, the SSTAs in the southwestern Indian Ocean can regulate ASMOP in India. At the same time, the SSTAs modulate ASMOP in the northern SCS in the western North Pacific. Results from numerical experiments verified that air–sea interaction is critical for the effect of extra‐equatorial SSTAs on ASMOP, which provides an additional source of seasonal predictability of ASMOP besides ENSO factors. Key Points: The Asian summer monsoon onset process (ASMOP) shows distinct interannual modes in the tropicsEl Niño–Southern Oscillation determines the interannual variability in ASMOP over India, the Bay of Bengal, and the southern South China Sea (SCS)The southwestern Indian and western Pacific sea surface temperature anomalies modulate ASMOP over India and the northern SCS via air–sea interaction, respectively [ABSTRACT FROM AUTHOR]

Pigeon pea is the second most important grain legume in India, primarily grown under rainfed conditions. Any changes in agro-climatic conditions will have a profound influence on the productivity of pigeon pea (Cajanus cajan) yield and, as a result, the total pulse production of the country. In this context, weather-based crop yield prediction will enable farmers, decision-makers, and administrators in dealing with hardships. The current study examines the application of the stepwise linear regression method, supervised machine learning algorithms (support vector machines (SVM) and random forest (RF)), shrinkage regression approaches (least absolute shrinkage and selection operator (LASSO) or elastic net (ENET)), and artificial neural network (ANN) model for pigeon pea yield prediction using long-term weather data. Among the approaches, ANN resulted in a higher coefficient of determination (R2 = 0.88–0.99), model efficiency (0.88–1.00) with subsequent lower normalised root mean square error (nRMSE) during calibration (1.13–12.55%), and validation (0.33–21.20%) over others. The temperature alone or its interaction with other weather parameters was identified as the most influencing variables in the study area. The Pearson correlation coefficients were also determined for the observed and predicted yield. Those values also showed ANN as the best model with correlation values ranging from 0.939 to 0.999 followed by RF (0.955–0.982) and LASSO (0.880–0.982). However, all the approaches adopted in the study were outperformed the statistical method, i.e. stepwise linear regression with lower error values and higher model efficiency. Thus, these approaches can be effectively used for precise yield prediction of pigeon pea over different districts of Karnataka in India. [ABSTRACT FROM AUTHOR]

This study investigates the impact of El Niño–Southern Oscillation (ENSO) on the seasonal evolution of the Asian–Pacific summer monsoon. The results show that during the summers when the SSTs in the equatorial eastern Pacific are above normal (i.e., during developing El Niño), the seasonal march of the Asian–Pacific summer monsoon is delayed. Specifically, the stepwise northeastward extension of the western North Pacific monsoon and the northward migration of East Asian and Indian monsoon are all delayed, resulting in rainfall deficiency in the western North Pacific and India, and more rainfall in the Yangtze River valley but less rainfall in North China due to the delayed northward migration and resultant prolonged rainy season in the Yangtze River valley. In addition, the seasonal march of the Asian upper-tropospheric westerly jet, which is mainly characterized by the northward migration during the monsoon development, is also delayed, concurrent with the delayed march of monsoonal rainfall. During La Niña summers, however, the seasonal march of the monsoon and Asian jet does not exhibit clear variations, suggesting asymmetrical impacts between El Niño and La Niña. Furthermore, we explain these variations in the seasonal evolution of rainfall and jet and the asymmetrical impacts between El Niño and La Niña through the variations in tropical tropospheric temperatures and the resultant changes in meridional temperature gradient. Significance Statement: The seasonal march of the Asian–Pacific summer monsoon exhibits large spatial and temporal variations, but shows some regular features such as stepwise northward migrations. The impacts of ENSO on the seasonal evolution of the components of Asian–Pacific summer monsoon have been shown in previous studies. However, there have been remarkable uncertainties in the previous results, and more emphasis has been put on the impacts of preceding ENSO. This study starts from El Niño and La Niña summers to reduce uncertainty caused by defining the seasonal march of the monsoon, and includes the variations in circulations that correspond well to monsoonal rainfall, making the conclusions more reliable. [ABSTRACT FROM AUTHOR]

Vitamin D deficiency is a serious issue in developing nations, including India. This study investigates the determinants of vitamin D deficiency among Indian adolescents and assesses their relative importance using dominance analysis. Data from the Comprehensive National Nutrition Survey (CNNS) conducted between 2016 and 2018 were utilized in this study. Vitamin D levels were assessed based on serum 25-hydroxyvitamin D concentration, with a sample size encompassing 13,065 adolescents aged between 10 and 19 years. Backward stepwise multivariate logistic regression was used to identify the correlates of vitamin D deficiency, and the relative importance of these factors was assessed using dominance analysis. The study identified nine predictors that were significantly associated with vitamin D deficiency at a 1% level of significance (α = 0.001). Among these factors, sex was found to be the most significant predictor, with female adolescents being 2.66 (95% CI: 95% CI: 2.39–2.96) times more likely to be vitamin D deficient compared to male adolescents. Lifestyle and behavioral factors, such as "sex," "wealth index," and "place of residence," were more dominant in predicting vitamin D deficiency than biological indicators like "BMI" and "serum creatinine." This underscores the vital role of sunlight exposure in maintaining sufficient vitamin D levels. In summary, this study sheds light on the multifaceted factors contributing to vitamin D deficiency among Indian adolescents, emphasizing the significance of targeted interventions and public health awareness campaigns to mitigate this pressing issue. [ABSTRACT FROM AUTHOR]

Ethical workplace climate has been extensively researched in the for‐profit context but neglected in nonprofits. Perhaps because nonprofits promote shared values, engage with people, and implement development interventions creating public good, they are considered implicitly ethical. This assumption has been questioned in recent studies. We attempted to develop a psychometrically valid scale measuring ethical workplace climate following a sequential research design to fill this gap. We interviewed 74 employees from 30 nonprofit organizations using the critical incident technique to generate statements on ethical workplace climate. The statements generated were categorized with expert judges' help, followed by a survey of 507 nonprofit employees across India. The exploratory factor analysis (EFA) and subsequent confirmatory factor analysis (CFA) resulted in a 43‐item scale, further reduced to 26 items using stepwise regression. Results of subsequent application of EFA and CFA confirmed a four‐factor solution: self‐interest, collegiality, internal legitimacy, and stewardship. A follow‐up study of 243 members of nonprofit organizations confirmed the hypothesized relationships that ethical work climate has a significant effect on affective commitment and job engagement. Finally, we discussed our findings along theoretical contributions, implications, limitations, and future direction. [ABSTRACT FROM AUTHOR]

The study proposes an efficient method to evaluate the suspended sediment concentration (SSC) relative to the traditional sediment rating curves (SRC) for gauged stations and subsequently to predict the SSC in ungauged stations of a major river basin. Multiple environmental control parameters were collected from 16 stations along the Mahanadi River basin (MRB) during the monsoon season. The hysteresis behaviour of SSC is assessed and therefore considered for modelling SSC using linear mixed-effects modelling (LMM). A basin-scale rating model is proposed using principal component analysis and stepwise multiple linear regression for estimating the unmeasured SSC. The findings show that the MRB acts differently in terms of hysteresis, with distinct dilution and flushing regimes in SRC. LMM outscored SRC by nearly doubling the mean covariance and notably reducing the percent bias between observed and predicted data across stations. However, unlike LMM, SRC could not correctly estimate low and high SSCs of ≤ 0.05 g/l and ≥ 1.5 g/l, respectively. The error metrics of the proposed rating model are within acceptable limits for all ungauged stations. Nevertheless, its efficiency varies due to smaller catchment areas, non-linearity in sediment transport with respect to catchment area, and other sampling issues. As a result, compared to other known models applied on the MRB, this model has the lowest error and seems to be the best in predicting monthly SSC. [ABSTRACT FROM AUTHOR]

Background: Mild cognitive impairment (MCI) is a transitional state between normal cognition and clinical dementia. MCI is associated with an increased risk of dementia and mortality. Progression of MCI to dementia can be prevented by cognitive and lifestyle interventions. There is limited evidence on the burden and risk factors associated with MCI in India. To estimate the prevalence of MCI among elderly persons, and to study the factors associated with MCI. Materials and Methods: This community-based cross-sectional study was carried out among 365 persons aged 60 years or older, residing in an urban resettlement colony of Delhi. Participants with dementia (score <23 on the Hindi version of the Mini-Mental State Examination) were excluded. Objective cognitive impairment and functional disability were assessed by the Montreal Cognitive Impairment-Basic (MoCA-B) tool and Barthel's Activities of Daily Living, respectively. The prevalence of MCI was estimated by Petersen's criteria, i.e., subjective memory impairment, objective cognitive impairment (MoCA score 19-25), functional independence, and absence of dementia. Univariate analysis was performed, followed by stepwise multivariate logistic regression. The association of socio-demographic and other health conditions with MCI was assessed. Results: The prevalence of MCI was 9.3% [95% confidence interval (CI) 6.7-12.7], 13.3% (95% CI 8.8-19.7) among men, and 6.5% (95% CI 3.9-10.6) among women. The risk of MCI was higher among current smokers. Conclusions: MCI was common among the elderly. Early detection of MCI may be included in health programs for elderly persons. [ABSTRACT FROM AUTHOR]

Purpose: To assess the oral hygiene and periodontal status and analyse the influence of age, education, institutionalization, type of visit and oral health behaviour on oral hygiene and periodontal status among detainees in juvenile detention center in Udaipur city, Rajasthan, India. Materials and Methods: The total sample comprised 223 subjects (67.7% male and 32.3% female) aged 6 to 18 years. Clinical examination included assessment of oral hygiene and periodontal status using OHI-S (Oral Hygiene Index-Simplified) and CPI (Community Periodontal Index), respectively. Analysis of variance (ANOVA), chi-square, Student t-test and stepwise multiple linear and multiple logistic regression analysis were carried out to find the relation between oral hygiene/periodontal status and different independent variables. Results: The results showed that the oral hygiene status of detainees was poor, with only 28.1% of the subjects having good oral hygiene. Mean OHI-S scores were significantly associated with all independent variables. Overall periodontal disease prevalence was 80.2% with bleeding and calculus contributing a major part (71.9%). Stepwise multiple linear and logistic regression analysis revealed that oral hygiene practice and type of visit in the detention center were the best predictors for the oral hygiene index, and for periodontal disease it was oral hygiene practice alone. Conclusion: The findings confirmed that detainees in the juvenile detention center have poor oral hygiene and an increased prevalence of periodontal disease compared to that of similarly ages in the general population. [ABSTRACT FROM AUTHOR]

The lower course of the Damodar River in West Bengal is one of the most polluted stretches in the Ganga River basin. There is a lack of research along the whole course of the Damodar, and parameter level analysis receives little attention. Eleven monitoring sites were chosen based on the potential sources of pollution for 6 years (2014–2019). Multivariate statistical techniques (factor analysis (FA), cluster analysis (CA), and discriminate analysis (DA)) evaluate the spatial and temporal variation of Damodar River water quality by considering 24 parameters. Factor analysis extracts the most influential seasonal parameters, and stepwise DA extracts ammonia, DO, potassium, temperature, total coliform, TFS, and turbidity, which are the most responsible parameters for seasonal variation of the water quality. CA classify sampling stations into three groups helping to identify the spatial variation of water quality. Ammonia, BOD, calcium, chloride, conductivity, DO, sodium, sulfate, temperature, Alkalinity, TDS, hardness, TSS, and turbidity are the most influential variables for spatial variation extracted through stepwise DA. Monsoon season shows a higher pollution level due to the contribution from both point and non-point sources. Due to high-density urban areas and large-scale industries, the middle course is more polluted. The Canadian Council of Ministers of the Environment (CCME) water quality index (WQI) accesses the water quality in temporal and spatial scales. The resultant water quality pattern is matched with the derived result from multivariate analysis. Poor water quality is regular at all sample sites in all seasons. [ABSTRACT FROM AUTHOR]

Background: The number of people experiencing functional limitations due to health conditions (capacity) is expected to increase in low and middle-income countries as populations age and rates of non-communicable disease rise. This trend could raise the prevalence and levels of disability worldwide. Understanding the demographic and environmental factors associated with disability can inform the design of policy interventions to make societies more accessible and inclusive for all.Methods: Approximately 2,500-3,000 participants in each of India, Laos, and Tajikistan responded to the Gallup World Poll and the World Health Organization's Brief Model Disability Survey through face-to-face interviews. For each country, random forest regression was performed to explore the associations of demographic and environmental factors with disability while controlling for capacity. Using the variable importance measures generated by the random forest models, linear regression models were built in a stepwise manner for each country to predict disability level based on these contextual factors.Results: Capacity was strongly associated with disability in all three countries. Most of the variance in disability was explained by minimally adjusted linear models that included only capacity, sex, and age. Inclusion of additional demographic factors and environmental factors explained slightly more of the variance in disability score. Across all three countries, the level of basic infrastructure, public services, and financial stability were moderately associated with disability. Age, sex, employment status, the use of assistive technologies, and other factors had associations with disability that were highly variable across countries.Conclusion: While capacity was the main determinant of disability, individual demographic and environmental factors were associated with disability in a country-specific manner while controlling for the effects of capacity. [ABSTRACT FROM AUTHOR]

We studied the impact of weather parameters on the population build-up of Brevicoryne brassicae (L.) (Cabbage aphid), Lipaphis erysimi (Kalt.) (Mustard aphid), Myzus persicae (Sulzer) (Green peach aphid) and their biocontrol agents (coccinellids, syrphids, and a parasitoid, Diaeretiella rapae M'Intosh) on oilseed brassicas in Himachal Pradesh, India, during winters from 2016–2017 to 2018–2019. The temperature and sunshine resulted in the build-up of B. brassicae and their biocontrol agents' population, while rainfall and relative humidity caused a negative influence at surveyed locations. The L. erysimi and M. persicae populations showed an inverse correlation with the density-independent factors at most locations. Correlation coefficients indicated a negative correlation of the coccinellids population with the build-up of L. erysimi and M. persicae , while the predator population was positively related to the B. brassicae population at maximum locations. Parasitization by D. rapae showed a negative relationship with the aphid population. Stepwise regression analysis showed that minimum temperature and rainfall had a significant effect on the variability in the population of aphids. The predictive model could interpret more than 90% variation by minimum temperature in the coccinellid population at the surveyed locations. Further, regression analysis with temperature could explain up to 94% variability in parasitization by D. rapae. This study will contribute to predicting the changes that may occur in a population of aphids concerning the weather. [ABSTRACT FROM AUTHOR]

In vitro oral bioaccessibility assay (simple bioaccessibility extraction test) was used to assess bioaccessible PTEs (As, Cd, Co, Cu, Fe, Mn, Ni, Pb, Sn, and Zn) in 16 playground soils of Khagra, which is a medieval bell metal industrial town at Murshidabad district, West Bengal, India. The aim was also to establish levels of potentially toxic elements (PTEs) in soil, their origin, and human health risk, particularly on children. The average pseudo-total PTEs content in playground soil samples was in the decreasing order of Fe (18,988 mg kg−1) > Zn (1229 mg kg−1) > Cu (999 mg kg−1) > Mn (343 mg kg−1) > Pb (181 mg kg−1) > Sn (132 mg kg−1) > Co (8.63 mg kg−1) > As (5.21 mg kg−1) > Cd (0.88 mg kg−1). The pollution indices indicate significant enrichment of Cd, Cu, Pb, Zn, and Sn in the playground. The bioaccessible percentage of PTEs in the 16 playground soils ranged from 0 to 80.25%, where the range of percentage of bioaccessibility was 13.24–62.50, 0–61.46, 16.82–28.79, 5.05–73.06, 0.96–6.14, 2.28–38, and 0–80 for As, Cd, Co, Cu, Fe, Ni, and Zn, respectively. The order of percentage of bioaccessibility was As > Mn > Zn > Sn > Cu > Co > Pb > Cd > Ni > Fe. PCA extracted two major factors indicating the anthropogenic (Cd, Cu, Ni, Pb, Zn, and Sn) and geogenic (Co, Fe, and Mn) source. Stepwise multiple regression analysis exhibited that the oral bioaccessibility of PTEs did not correlate with physicochemical parameters like pH, EC. In contrast, Sn had a significant correlation with that of organic matter. The health risk for pseudo-total as well as bioavailable fraction in playground soil depicted that children were more vulnerable to ingestion of soil contaminated with PTEs, particularly for Cu and Pb. A risk management plan with the bioaccessible data involving detailed site-specific exposure factors to indicate the importance of the study in terms of child health safety is required. [ABSTRACT FROM AUTHOR]

The aim of this study is to examine the influence of antenatal factors such as anxiety, depression, perceived stress, marital satisfaction, maternal antenatal attachment, and social support on postnatal maternal attachment and competence in women who received assisted reproductive treatment. A prospective longitudinal cohort design was adopted with two groups—50 women who received assisted reproductive treatment and 50 women who had natural conception. Both the groups were assessed using self-report measures over three time points: T1, 7th month of pregnancy; T2, 2 weeks postpartum; and T3, 3 months postpartum. A final sample of 44 women who had assisted conception and 47 women who had natural conception completed assessments across all three time points. Descriptive, bivariate analyses, and stepwise multiple linear regression analyses were carried out. In the assisted conception group, maternal antenatal attachment, depression, and marital satisfaction significantly predicted postnatal maternal-infant attachment. Perceived social support, depression, and duration of marriage significantly predicted postnatal maternal competence. In the naturally conceived group, maternal antenatal attachment and social support significantly predicted postnatal maternal-infant attachment; perceived stress significantly predicted postnatal maternal competence. Antenatal depressive symptoms and relational factors significantly influenced postnatal maternal attachment and competence highlighting the need for screening and targeted psychological interventions during pregnancy. [ABSTRACT FROM AUTHOR]