Space curves on surfaces with ordinary singularities

We show that smooth curves in the same biliaison class on a hypersurface in $\mathbf{P}^3$ with ordinary singularities are linearly equivalent. We compute the invariants $h^0(\mathscr{I}_C(d))$, $h^1(\mathscr{I}_C(d))$ and $h^1(\mathscr{O}_C(d))$ of a curve $C$ on such a surface $X$ in terms of the cohomologies of divisors on the normalization of $X$. We then study general projections in $\mathbf{P}^3$ of curves lying on the rational normal scroll $S(a,b)\subset\mathbf{P}^{a+b+1}$. If we vary the curves in a linear system on $S(a,b)$ as well as the projections, we obtain a family of curves in $\mathbf{P}^3$. We compute the dimension of the space of deformations of these curves in $\mathbf{P}^3$ as well as the dimension of the family. We show that the difference is a linear function in $a$ and $b$ which does not depend on the linear system. Finally, we classify maximal rank curves on ruled cubic surfaces in $\mathbf{P}^3$. We prove that the general projections of all but finitely many classes of projectively normal curves on $S(1,2)\subset\mathbf{P}^4$ fail to have maximal rank in $\mathbf{P}^3$. These give infinitely many classes of counter-examples to a question of Hartshorne.Comment: 22 page

The analysis of organizational work environment factors affecting training transfer: a questionnaire survey in chinese enterprises

This study aims to find out which work environment factors may have the most significant influence on affecting training transfer from the perceptions of trainees, in the Chinese organizational context. Additionally, this study aims to find, whenever it is possible, different perceptions about work environment factors and training transfer, based on some socio-demographic characteristics, as well as company type where the respondent works. To gather data, it was used a self-administered questionnaire delivered on the Internet, for two weeks in March 2015. Means, standard deviations, correlations, and coefficient alpha internal consistency reliabilities are computed. T-tests and one-way ANOVA are used to investigate differences between groups. Next, the multiple linear regression analysis is conducted for to investigate the relationship between employee perceptions of work environment factors and training evaluation variables. The main results show that work environment factors significantly influence training transfer. Findings also support the idea that there are significant differences on perceptions about work environment factors and training transfer by socio-demographic variables. On the light of the study findings, the researcher managed to provide some recommendations and suggestions for managers of companies in China.Este estudo tem por objective conhecer os factores ambientais de trabalho que afectam a transferência de conhecimentos adquiridos em formação no contexto organizacional, a partir das percepções dos formandos, na China. Adicionalmente, este estudo procura identificar, caso existam, diferentes percepções sobre os factores ambientais de trabalho e a transferência de conhecimentos quando são analisados as características sócio-demográficas, bem como o tipo de organização onde o participante trabalha. A recolha dos dados empíricos foi realizada com um questionário de auto-preenchimento disponibilizado na internet, por um período de duas semanas, em Março de 2015. Foram calculados médias, desvios-padrões, correlações e o alfa de Cronbach para identificar o grau de consistência interna das escalas. O teste t e a análise ANOVA foram usadas para investigar diferenças entre grupos. A análise de regressão linear múltipla é executada para investigar a relação entre as percepções dos empregados sobre os factores ambientais de trabalho e as variáveis de avaliação da formação. Os principais resultados mostram que os factores ambientais de trabalho influenciam significativamente a transferência do conhecimento. Os resultados também suportam a ideia de que existem diferenças significativas nas percepções sobre os factores ambientais de trabalho e a transferência de conhecimentos quando são analisadas variáveis sócio-demográficas. À luz dos resultados obtidos, o investigador fornece algumas recomendações e sugestões aos gestores de empresas na China

Empirical study of freeway interchange crash characteristics and influence areas

Factors that affect drivers at interchanges are various and include changing lanes, changes in speed limits, and lengths of speed-change lanes. State Departments of Transportation (DOTs), local authorities, and transportation researchers use reported crash locations for analysis, neglecting the functionality of speed-change lanes. This may lead to the inaccurate prediction of the number of crashes and non-optimum geometric designs. This study used a newly proposed method for locating crashes by the functionality of speed-change lanes instead of exact crash location for safety analysis. Missouri crash reports were reviewed to determine how police officers located crashes. In addition, the functional and physical classification methods were compared. Crash distributions were presented for different types of facilities, such as freeway segments, speed-change lane segments, and ramp segments, in order to better understand the safety of different interchange-related facilities. In addition, on the basis of crash data, the safety influence areas were estimated using empirical data. By using functional classification, more crashes were assigned to speed-change lanes than ramps or freeways that had been assigned through the use of physical classification. Mainline freeway segments still generated the most crashes in interchanges under functional classification (62.09%), with speed-change lanes second (21.21%). The interchange influence area determined in this research was 2000 ft., which is longer than the 1500 ft. discussed in previous studies