The Method for Determining Time-Generation Range

Karashchuk, Oksana; Mayorova, Elena; Nikishin, Alexander Fedorovich; Kornilova, Olena V.

doi:10.1177/2158244020968082

Cited by 12 publications

(7 citation statements)

References 14 publications

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“…In general, the ranges of years for each generation have differences among countries. For example, Karashchuk et al ( 2020 ) explained that the range of years for each generation has specific differences between Russia and America. Accordingly, in the case of the Baby Boomer generation, the Baby Boomer birth period varies from country to country (Sudbury-Riley et al, 2015 ).…”

Section: Introductionmentioning

confidence: 99%

Segmentation of Older Adults in the Acceptance of Social Networking Sites Using Machine Learning

et al. 2021

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This study analyzes the most important predictors of acceptance of social network sites in a sample of Chilean elder people (over 60). We employ a novelty procedure to explore this phenomenon. This procedure performs apriori segmentation based on gender and generation. It then applies the deep learning technique to identify the predictors (performance expectancy, effort expectancy, altruism, telepresence, social identity, facilitating conditions, hedonic motivation, perceived physical condition, social norms, habit, and trust) by segments. The predictor variables were taken from the literature on the use of social network sites, and an empirical study was carried out by quota sampling with a sample size of 395 older people. The results show different predictors of social network sites considering all the samples, baby boomer (born between 1947 and 1966) males and females, silent (born between 1927 and 1946) males and females. The high heterogeneity among older people is confirmed; this means that dealing with older adults as a uniform set of users of social network sites is a mistake. This study demonstrates that the four segments behave differently, and many diverse variables influence the acceptance of social network sites.

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Section: Introductionmentioning

confidence: 99%

Segmentation of Older Adults in the Acceptance of Social Networking Sites Using Machine Learning

et al. 2021

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“…The theory of group generation or cohort generation is defined as everyone who comes into being at the same historical moment, that is, everyone belonging to the same group [19][20][21]. On the other hand, cohort generation does not have a direct relationship with genealogy or lineage.…”

Section: Resultsmentioning

confidence: 99%

Key Role of Millennial Generation in Rural Agricultural Development In Indonesia: Cohort Generation Theory Approach

Kifli¹,

Slameto

Kilmanun³

et al. 2021

E3S Web Conf.

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Agricultural development actors in Indonesia are currently dominated by elderly farmers and a small proportion of young farmers. Another condition is that the farming system in Indonesia is generally subsistence. Several good potentials in the context of agricultural development in Indonesia today, firstly, the productive working age group is dominated by youth, especially the millennial generation, and secondly, the growing rapidly used internet networks. The condition of subsistence farming and the lack of young actors in agriculture, but on the other hand there is the potential of the millennial generation and availability of internet networks access. This study employed a quantitative research method. The purpose of this research is to see the current condition of agricultural development in Indonesia concerning its current potential. Another objective is to design the appropriate strategy for exploiting this potential to accelerate agricultural development in Indonesia. The results obtained from this research are the high level of accessibility of rural communities as initial capital for agricultural development in Indonesia for now. The millennial generation who dominates the working age in Indonesia can maximize their role in the agricultural sector in rural areas through developing entrepreneurship based on the use of internet networks.

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“…We determined also the levels of the proinflammatory cytokines IL-1 and IL-6 (ELISA, analyzer "RT-2100C", reagents from "Vector-Best"); products of lipid peroxidation: diene conjugates (spectrophotometry of heptane phase of lipids extract) [10] and malondialdehyde (test with tiobarbiture acid) [1], the activity of antioxidant enzymes: katalase serum (by the speed of decomposition hydrogen peroxide) [18] and superoxide dismutase erythrocytes (by the degree of inhibition of nitroblue tetrazolium recovery in the presence of N-methylphenazone metasulfate and NADH) [7,19]; routine biochemical parameters: glucose (glucose-oxidase method), creatinine (by Jaffe's color reaction by Popper's method), urea (urease method by reaction with phenolhypochlorite), uric acid (uricase method), bilirubin (by diazoreaction using the Jedrashik-Kleghorn-Grof method), asparagine and alanine transaminase as well as γ-glutamiltranspeptidase according to instructions [11] with the use of analyzers "Reflotron" (BRD) and "Pointe-180" (USA) and corresponding sets of reagents. By default, a general blood test was performed.…”

Section: Materials and Research Methodsmentioning

confidence: 99%

Metabolic accompaniment of plasma lipoproteins profile in persons with maladaptation

Tsymbryla,

Barylyak,

Żukow

et al. 2023

J Educ Health Sport

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Background. During the implementation of the project "The relationship between the lipoprotein profile of the blood plasma and the parameters of the neuroendocrine-immune complex, and the influence of the factors of the Truskavets’ spa on them", we first divided observed cohort into 5 homogeneous groups that differed from each other by 6 discriminant variables. The purpose of this study is to identify the metabolic accompaniment of plasma lipoprotein profile in the same persons. Material and research methods. The object of observation were 41 volunteers: 20 women aged 30-76 years and 21 men aged 24-69 years without clinical diagnose but with dysfunction of neuroendocrine-immune complex and dysmetabolism. We estimated lipoprotein profile of plasma, determined the levels of the proinflammatory cytokines, parameters of lipid peroxidation as well as routine biochemical and paraclinical parameters. Results. The patients with increased, normal and decreased levels of Dobiásová’s&Frohlich’s Atherogenic Index of Plasma (D&FAIP) are characterized, together with levels of Triglycerides and HDLP Cholesterol by definition, by specific constellations of levels of IL-6, IL-1, Diene conjugates, Malondialdehyde, Katalase, Glucose, and Alanine aminotransferase (classification accuracy is 98.8%). A close canonical correlation was found between the parameters of the plasma lipoprotein profile, on the one hand, and metabolism and erythroon, on the other (R=0.920). Conclusion. Atherogenic, normal and anti-atherogenic blood plasma is characterized by specific levels of markers of inflammation, lipid peroxidation, cytolysis and erythroon.

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The Method for Determining Time-Generation Range

Cited by 12 publications

References 14 publications

Segmentation of Older Adults in the Acceptance of Social Networking Sites Using Machine Learning

Segmentation of Older Adults in the Acceptance of Social Networking Sites Using Machine Learning

Key Role of Millennial Generation in Rural Agricultural Development In Indonesia: Cohort Generation Theory Approach

Metabolic accompaniment of plasma lipoproteins profile in persons with maladaptation

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