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A considerable increase in life expectancy since the mid-fifties has slightly shifted the age structure of the population to the older age group as compared to earlier in India. Consequently, there is a growing demand for projections of the distribution of household types, sizes, and living arrangements of the older adults for socioeconomic planning, environment, development, business and market research, and policy and scholarly analysis in the country. This study attempts to highlight the prospective living arrangement patterns of the older adults in the country at the national and sub-national levels. The purpose of this study was to apply the net transition probability Markov chain simulation model and the Monte Carlo simulation model to project the different living arrangements of the Indian older adults from the year 2025 to 2050. The findings show a substantial increase in the proportion of the older adults living with a spouse only; the proportion of the older adults living alone would also rise substantially in the future years. In contrast, the proportion of the older adults living in three-generation households is projected to experience a steady decline from 2025 to 2050. Demographically advanced states like Tamil Nadu and Telangana are projected to have the highest proportion of older adults living alone. Among the northeastern states, Arunachal Pradesh and Sikkim are projected to take the lead in this regard. Meghalaya, also a northeastern state, is projected to have the highest proportion of the older adults living with spouses only, whereas in Assam, the number of the older adults living in two-generation and three-generation households are projected to undergo the highest decline in the near future. From a methodological perspective, this study shows that the net transition probability Monte Carlo simulation model gives better estimates than the Markov chain simulation model. Given the ongoing transformation of India's demographic landscape, it is imperative for policymakers, researchers, and institutions to adapt their strategies to ensure the well-being and quality of life of the older adults. The insights and projections presented in this study serve as a valuable resource for guiding future initiatives and interventions in this context. [ABSTRACT FROM AUTHOR]

Familial composition has always occupied the center stage in sociological research and is linked with different socio-economic and demographic transitions. This study examines the change in the pattern of one-person (OP) and one-couple-only (OC) households in India for the period 1993–2050. Household-level data was obtained from three rounds of the National Family Health Survey and closely matched with the estimates of the Census. We adopted the spline method for age smoothing, the ordinary least squares regression method for examining the factors affecting OP and OC households, and the logistic curve for making projections. The findings show that during 2015–16, 4% of the households in India were OP households, which figure is expected to become 5.5% (4.9%-5.6%) by 2030 and 6.7% (5%-7%) by 2050. The percentage of OC households was 8% in 2015–16, which will increase to 10.4% (9.2%-10.8%) by 2030 and 12.6% (9.8%-14.2%) by 2050. In 2015–16, the proportion of OP households ranged between 1.54 in Jammu & Kashmir and 8% in Arunachal Pradesh. while that of OC households ranged from 3.3% in Meghalaya to 14.4% in Andhra Pradesh. The demographically advanced state of Kerala is projected to have the highest proportion of OC households in the coming years. One-man households were concentrated in the younger ages, while one-woman households dominated in the older ages. The share of OP households was higher among older persons from rural areas than those from urban areas. The increasing share of OP and OC households among the elderly may accelerate the already-underway processes of feminisation and ruralisation of ageing. The ongoing increase in urbanisation and decline in the Total Fertility Rate (TFR) would lead to an increase in the share of both OP and OC households in India in the future. [ABSTRACT FROM AUTHOR]

A mathematical model is a mathematical connection that describes some real-life scenario. To handle real-world problems securely and effectively, simulation modelling is required. In this article, the author investigates the stochastic regression model scenario in which the dependent and independent variables in a linear regression model follow a distribution. We assume that the dependent and independent variables both exhibit Type I Extreme Value Distribution. The estimators are then derived using the Modified Maximum Likelihood (MML) estimation method. In accordance with this, a hypothesis testing technique is developed. [ABSTRACT FROM AUTHOR]

The objective of the study is to determine the impact of land use and land cover (LULC) change on land surface temperature (LST) and thermal stress at Jorhat from 2009 to 2021. The experiment used Landsat TM (Thematic Mapper) for 2009 and OLI (Operational Land Imager)/TIRS (Thermal Infrared Sensor) for 2021 from earth.explorer.usgs.gov. Landsat data were employed to calculate the LST and LULC changes. Utilizing UTFVI (urban thermal field variance index), thermal stress over the ground surface has been computed. Thermal discomfort is computed simultaneously using the relative strain index (RSI) and net effective temperature (NET) index. Jorhat evidenced significant rise in built-up land to 281.25 hectares with reduced vegetation cover of 480.96 hectares from 2009 to 2021. These modifications caused significant rises in LST of 4.28 °C, 2.33 °C and 3.01 °C in September, October and December from 2009 to 2021. According to UTFVI from 2009 to 2021, Jorhat experienced declining ecologically excellent area with a rising proportion of ecologically worse land. In September and October 2009, the Jorhat city had just 10 days of bioclimatic discomfort and 19 days of bioclimatic comfort, as opposed to 24 and 10 days in 2021, respectively. Similarly, NET estimated 21 very hot days in October 2021, as opposed to just 9 days in 2009. Compared to 2009, there are now 6 and 4 days in December 2021 that are classified as warm or slightly hot, respectively. This leads to the conclusion that Jorhat's thermal condition is significantly impacted by changes in land use and land cover. [ABSTRACT FROM AUTHOR]

Crime is an unavoidable social phenomenon prevailing more or less in every social structure. The incidences of crime either can be minimized or controlled, however, it is difficult to eradicate it completely. To observe crime pattern of a particular place, trend analysis plays vital role in examining shape and structure of the data. In crime study, it provides help in solving issues like crime mapping, policy-prescription, prediction, etc. Trend analysis in crime data provides comprehensive as well as extensive observations of the statistics, because of which behavioral study of the same becomes trouble-free. In this paper, an attempt has been made to analyze crime data of India for last two decades. To study the trend, Dynamic Time Warping (DTW) technique has been exercised. Hierarchical clustering of all the states and UTs has been performed as well based on crime rates to figure out places with similar pattern. Moreover, simple statistical analysis has also been carried out for better understanding of the scenario. [ABSTRACT FROM AUTHOR]

The study analyzed the pattern of building wall temperature (BWT) and road surface temperature (RST) in both urban and suburban area and its relation to traffic volume at Jorhat municipal area. The surface temperature pattern is assessed using the FLIR TG-165 spot thermal imaging camera and HTC MT-4 IR thermometer, while traffic volume is investigated through schedule survey and video recording over the selected urban roads. The study revealed a positive correlation between traffic volumes with BWT and RST, though the correlation is quite stronger with RST. The higher positive relationship between traffic volume and RST has been noticed mostly in the shadowing part of the surface, whereas on the other hand, the relationship pattern of BWT with traffic volume is also found noticeably higher at the shadowed part of the surface. In both analyses, the relationship between traffic with RST and BWT is identified as remarkably stronger at midday and afternoon period. The urban areas with maximum traffic congestion are identified as accountable for the higher BWT and RST. [ABSTRACT FROM AUTHOR]

Personal network characteristics have an important role in assessing the hard-to-reach population. The purpose of the study was to assess the network characteristic, recruitment pattern and the association between personal networks with other cofactors of female sex workers (FSWs) in Nagaland, India. Four hundred and seventeen FSWs were recruited through Respondent Driven Sampling in Dimapur, Nagaland using seven seeds. Transition probability matrices and homophily indices were used to describe the network characteristics and network pattern of FSWs. Respondent Driven Sampling weighted logistic regression model was performed to observed the association. Mean personal network size of FSWs was 6.8. Heterophily was present for age at first sexual debut, duration of sex work, client volume per weeks, and personal network size. Being >30 years of age, having ≥10 years of engagement in sex work, being hotel/lodge entertainer, having more client were found significantly associated with an increased likelihood of personal network size. Higher personal network size was also found significantly associated with ever illicit drug used practices. The personal network sized and the existence of the affiliation between recruiters and recruitees may help to spread peer-driven intervention among FSWs in the region. Further, research is required on the social networks of FSWs for a better understanding of their personal network, network pattern, and high-risk behaviors in all aspects to build a better foundation for behavioral intervention. [ABSTRACT FROM AUTHOR]

Frailty model in survival analysis is a special kind of random effect model, which can also deal with heterogeneity, caused by unmeasured covariates, where the random effect (the frailty) has a multiplicative effect on the baseline hazard function. With recent advances in computing technology, Bayesian approaches to frailty models are now computationally feasible and several researchers have been developing Bayesian methodologies to analyse survival data with different frailty models. In this paper, an attempt has been made to develop two new multivariate Accelerated Failure Time Frailty models under Bayesian approach with different baseline hazard functions. For making a comparative analysis, we consider the same two Accelerated Failure Time (AFT) models without the frailty term. To illustrate the models a real life survival data set of Diabetic Retinopathy Study is used and posterior inferences are drawn using Markov Chain Monte Carlo (MCMC) simulation methods and model comparison tools like deviance information criteria (DIC) and the log pseudo marginal likelihood (LPML) are also calculated and to check the fit of the model Cox-Snell residual plot is employed. [ABSTRACT FROM AUTHOR]

Regression models form the core of the discipline of econometrics. One of the basic assumptions of classical linear regression model is that the values of the explanatory variables are fixed in repeated sampling. However, in most of the real life cases, particularly in economics the assumption of fixed regressors is not always tenable. Under a non-experimental or uncontrolled environment, the dependent variable is often under the influence of explanatory variables that are stochastic in nature. There is a huge literature related to stochastic regressors in various aspects. In this paper, a historical perspective on some of the works related to stochastic regressor is being tried to pen down based on literature search. [ABSTRACT FROM AUTHOR]

In this paper, an attempt has been made to study the performance of Cricket Players using Factor Analysis technique. For this , the dataset of 85 batsmen, 85 bowlers; and 95 batsmen, 95 bowlers have been considered from IPL9, 2016 (20 overs) and ICC World Cup, 2015 (50 overs) respectively, and the findings of this study reveals that batting capability dominates over bowling capability which is in conformity with an earlier study on same kind of game. [ABSTRACT FROM AUTHOR]

This article studies the situation of health awareness among the inhabitants of Chars (river islands) of Nalbari, Borpeta and Jorhat districts of Assam. The health awareness is measured by health expenditure. The findings reveal that all the variables—caste-residence compound status, educational attainment, economic consideration of the family, family structure and primary occupation of the families have desirable impact on health awareness. In particular, the inhabitants of Char areas of Nalbari and Borpeta districts are seen to be least health aware. Thus on the basis of the findings of this study, it can be stated that in spite of launching several schemes for the upliftment of Chars (like forming Char area development authority, forming a separate state ministry for Char development, and so forth), the people living in these Chars are still far more backward than the people living in other parts of Assam. [ABSTRACT FROM PUBLISHER]

The study has been conducted using IR (infrared) thermometer over 16 sites at Jorhat town for a period of 5 months. The study area constitutes urban, suburban, and peripheral rural locations. The study focuses on depicting the diurnal, monthly, and seasonal dynamics of ST condition of Jorhat town. The diurnal pattern revealed the peak ST at midday for all months, while the lowest ST is in the morning during July, September, and October, and conversely in the afternoon period during the months of November to December. The month of October displayed a maximum ST at 38.30 °C. Though, the maximum range of ST has been identified in the month of November (9.48 °C). Seasonally, the overall monsoon depicts a higher ST than post-monsoon and winter. But remarkably, the maximum intensity of ST was investigated in the post-monsoonal period. Interestingly, the RST and BWT displayed a dissimilar pattern showing the peak ST in the month of July and October while the lowest is during in the month of December respectively. The concentration of built environment with less vegetation cover is considered as a causative factor for the development of the peak ST all throughout the study period in the central part of the town. [ABSTRACT FROM AUTHOR]