Depressive Symptoms, Alcohol Beliefs and Heavy Episodic Drinking in Adolescents

Adolescents who engage in heavy episodic drinking (HED—i.e., 5+ drinks on a single occasion) increase risks for psychopathology, alcohol dependence, and similar negative consequences in adulthood. We explored associations among depressive symptoms, positive alcohol beliefs, and progression of heavy episodic drinking (HED) in 3021 German adolescents (M(SD) age at baseline = 12.4 (1.0)) followed for 30 months in 4 waves, using a conditional parallel process linear growth model, with full information maximum likelihood estimation. By wave 4, 40.3% of participants had engaged in HED more than once; 16.4% had done so ≥5 times. Depressive symptoms were indirectly related to baseline values of HED (through positive beliefs and wave 1 drinking frequency and quantity) and to the rate of growth in HED (through positive beliefs and wave 1 quantity). Adolescents with higher levels of depressive symptoms and positive alcohol beliefs drink more frequently and at greater quantities, which is associated with initiating HED at a higher level and escalating HED more rapidly than peers with similar depressive symptoms who lack those beliefs. This suggests that, to the extent that positive alcohol beliefs can be tempered through public health campaigns, education and/or counseling, HED among depressed adolescents might be reduced.

Modelling the growth of rearing cattle

Scientific growth literature often uses the models of Brody, Gompertz, Verhulst, and von Bertalanffy. The versatile five-parameter Bertalanffy-Pütter (BP) model generalizes them. Using the least-squares method, we fitted the BP model to mass-at-age data of 161 calves, cows, bulls, and oxen of cattle breeds that are common in Austria and Southern Germany. We used three measures to assess the goodness of fit: R-squared, normalized root-mean squared error, and the Akaike information criterion together with a correction for sample size. Although the BP model improved the fit of the linear growth model considerably in terms of R-squared, the better fit did not, in general, justify the use of its additional parameters, because most of the data had a non-sigmoidal character. In terms of the Akaike criterion, we could identify only a small core of data (15%) where sigmoidal models were indispensable.

Growth rates of the chokka squid Loligo reynaudii d’Orbigny, 1845 (Cephalopoda: Myopsida: Loliginidae) off South Africa, investigated over two years

Growth of adult chokka squid Loligo reynaudii d’Orbigny was modelled using mantle length and age data derived from samples collected over two years (2003 and 2004) from a single, large cohort of mature and spawning squid. A total of 588 statoliths were examined (310 males, 278 females) from individuals of 71–425 mm mantle length (ML). The maximum size of chokka squid was 425 mm ML for males and 263 mm ML for females. The Francis Growth Model and Linear Growth model were selected for further analysis from six models considered. Males and females attain similar ages, although mantle length-based daily growth rates ranged from 0.75 to 1.02 (0.88 quantile _50) mm/day for males and 0.32–0.45 (0.38 quantile _50) mm/day for females, explaining the sexual dimorphism apparent in the sizes of individuals of this species.

Small saving in India with special reference to Saving pattern of weavers in Handloom sector of Bodoland Territorial Area Districts(BTAD), Assam, India

Small saving scheme is one of the key investment avenues for individual investor. It encourages small-income investors to invest and earn high returns and to save on income tax as well. In this paper the growth of small saving from 2001-02 to2017-18 has been analyzed by adopting non linear growth model. The paper also examined factors leading to saving differential of weavers in the handloom sectors of BTAD areas. The study is based on both primary and secondary data. To determine the relationship between various variables multiple regressions has been used. It is found that saving of weaver is positively determined by their monthly wages and negatively by family size and they are found significant at 1 percent level. Again the saving of weavers is found to be negatively determined by dependent children. Saving differences among gender and community is found insignificant, that mean we cannot say whether saving is greater (smaller) for male than female and for STs than non ST. So we cannot find a differences in saving behaviour among gender and community although there's found a significant difference in saving among marital status and types of weaver.

An Empirical Analysis on India’s Food Grain Cultivation, Production and Yield in Pre & Post Globalisation

Globalization is, directly and indirectly, contributing to its effect in all sectors of an economy. The agricultural sector is not exempted from the effect of change due to globalization as a component of the primary sector and a prime sector for human survival needs. The status of self-sufficient in the production of food grain will lead a nation to make a walk of pride among the other member globally. India is an agro-economy. In other words, agriculture is the backbone of the Indian economy. So the production of food grain and its cultivation and yield should be normally high to meet out the demand of a growing population. Also, with the implementation of a policy of globalization, there might be some change in cultivation, production, and yield of food grains in India. In this paper, an attempt was made to examine/ identify the change in area under cultivation, yield, and production by using the secondary sources of data from 1970 to 2017. The selected breakeven point of time was 1991-1992. The annual growth rate pictured the change in a particular point of time; the linear and quadratic model gave the growth over the period selected for the study, and dummy used regression model presented the difference in structural change. AGR results dominated by the negative growth rate; the linear growth model for production depicts that 3.6 percentage of tons of production will be move when a year moves upward. The area under cultivation is deteriorating in AGR, and other models used gave a weakness in explanatory level concerning time for the area under cultivation of food grain. Regarding the obtained results for yield reflect that a positive change exists after globalization, even though a reduction in area under cultivation.

How is China’s Health Development During 2012 to 2017? A Longitudinal Study Based on Comprehensive Evaluation and Linear Growth Model

Background: Since 2012, China has come into a new period of health development. This paper comprehensively described China’s health development and explored associated influencing factors during the last 6 years (2012-2017).Methods: Data for this study came from statistics yearbook and analysis unit were provincial regions. Comprehensive evaluation (principal component analysis and entropy weight method) was employed to calculate the comprehensive health index to evaluate the health. Then linear growth model was applied to explore factors that influenced the development.Results: Results showed that, since 2012, China’s health had a sustainable growth but inequities among provincial regions were still existing and becoming larger. For influencing factors, time was always a significant positive predictor ( ) and it was affected by geographical distributions ( ) and distance to Beijing ( ), which indicated that regions in central or far from Beijing had a lower growth. Among socioeconomics variables, urbanization level was the final factor ( ) that promoted China’s health development and caused development inequalities. Besides, health level was also influenced by the distance to Beijing ( ), regions near to Beijing had a higher health level.Conclusion: Time effect was the results of policy, during 2012 to 2017, China’s sustainable health development was brought by the policy effect and growth of urbanization level.Thus, it is crucial for one country to introduce suitable health policies and narrow the urban-rural gaps to improve its health. Distance to Beijing represented the potential political influence on health of one country’s capital due to the policy execution level which means that supervisions need to be strengthened for regions far from the capital. Besides, supports and supervisions also need to be enhanced in central regions. They were one of the reasons that caused development inequalities.

Predicting Parcel-Scale Redevelopment Using Linear and Logistic Regression—the Berkeley Neighborhood Denver, Colorado Case Study

Many watershed challenges can be associated with the increased impervious cover that accompanies urban development. This study establishes a methodology of evaluating the spatial and temporal distribution of infill re-development on a parcel scale, using publicly available urban planning data. This was achieved through a combination of linear and logistic regression. First, a “business as usual” linear growth scenario was developed based on available building coverage data. Then, a logistic regression model of historic redevelopment, as a function of various parcel attributes, was used to predict each parcel’s probability of future redevelopment. Finally, the linear growth model forecasts were applied to the parcels with the greatest probability of future redevelopment. Results indicate that building cover change within the study site, from 2004–2014, followed a linear pattern (R2 = 0.98). During this period the total building cover increased by 17%, or 1.7% per year on average. Applying the linear regression model to the 2014 building coverage data resulted in an increase of 820,498 sq. ft. (18.8 acres) in building coverage over a ten-year period, translating to a 14% overall increase in impervious neighborhoods. The parcel and building variables selected for inclusion in the logistic regression model during the model calibration phase were total value, year built, percent difference between current and max building cover, and the current use classifications—rowhome and apartment. The calibrated model was applied to a validation dataset, which predicted redevelopment accuracy at 81%. This method will provide municipalities experiencing infill redevelopment a tool that can be implemented to enhance watershed planning, management, and policy development.