Genetic distance estimated by RAPD markers and its relationship with hybrid performance in maize

The objective of this work was to evaluate the genetic diversity of 16 maize inbred lines, and to determine the correlation between genetic distance and hybrid performance, using random amplified polymorphic DNA (RAPD) molecular markers. Twenty-two different random primers were used, which resulted in the amplification of 265 fragments, 237 (84.44%) of them being polymorphic. A genetic similarity matrix was created from the RAPD data, using Jaccard coefficient, and a dendrogram was constructed. Hybrid analyses were carried out using random block design and Griffing method VI for diallel crossings. The genetic associations showed five distinct heterotic groups. Correlations between genetic divergences detected by RAPD, as well as the means observed in the diallel crossings were positive and significant for plant height, ear height, prolificacy, and grain weight. The correlation of genetic divergences, detected by RAPD, and the specific combining ability between heterotic group associations, showed significance in all characteristics under study, except prolificacy. A direct relationship between genetic divergence and productivity was found in 79.2% of the 120 hybrids confirming the hypothesis that genetic divergence is directly related to the performance of hybrids and is efficient in predicting it.

Estimated Traffic and Vehicle-Miles of Travel on Iowa's Proposed Interstate System 1956-1975

Data tables describing the length and vehicle-miles of travel on Iowa's 1975 proposed interstate system, broken down by interstate. No text is available.

Models of social networks based on social distance attachment

We propose a class of models of social network formation based on a mathematical abstraction of the concept of social distance. Social distance attachment is represented by the tendency of peers to establish acquaintances via a decreasing function of the relative distance in a representative social space. We derive analytical results (corroborated by extensive numerical simulations), showing that the model reproduces the main statistical characteristics of real social networks: large clustering coefficient, positive degree correlations, and the emergence of a hierarchy of communities. The model is confronted with the social network formed by people that shares confidential information using the Pretty Good Privacy (PGP) encryption algorithm, the so-called web of trust of PGP.

Marketing education, distance learning and hypermedia : teaching 'current issues in marketing' in a virtual campus

This article reports on a project at the Universitat Oberta de Catalunya (UOC: The Open University of Catalonia, Barcelona) to develop an innovative package of hypermedia-based learning materials for a new course entitled 'Current Issues in Marketing'. The UOC is a distance university entirely based on a virtual campus. The learning materials project was undertaken in order to benefit from the advantages which new communication technologies offer to the teaching of marketing in distance education. The article reviews the main issues involved in incorporating new technologies in learning materials, the development of the learning materials, and their functioning within the hypermedia based virtual campus of the UOC. An empirical study is then carried out in order to evaluate the attitudes of students to the project. Finally, suggestions for improving similar projects in the future are put forward.

Gliotransmitters Travel in Time and Space.

The identification of the presence of active signaling between astrocytes and neurons in a process termed gliotransmission has caused a paradigm shift in our thinking about brain function. However, we are still in the early days of the conceptualization of how astrocytes influence synapses, neurons, networks, and ultimately behavior. In this Perspective, our goal is to identify emerging principles governing gliotransmission and consider the specific properties of this process that endow the astrocyte with unique functions in brain signal integration. We develop and present hypotheses aimed at reconciling confounding reports and define open questions to provide a conceptual framework for future studies. We propose that astrocytes mainly signal through high-affinity slowly desensitizing receptors to modulate neurons and perform integration in spatiotemporal domains complementary to those of neurons.

Impact of quality and environmental investment on business competitiveness and profitability: The case of travel agencies

Few studies have examined the combined effect of implementing quality and environmental management within the service sector. This void is more evident if we focus on segments in which small businesses predominate and even more so if we look for highly competitive sectors that are very variable and that have high business mortality. After analysing 198 surveys of Spanish travel agency managers using structural equations, it can be concluded that practices of quality management have a significant direct impact on business competitiveness but not on this business's financial results, at least directly. However, there is a significant relationship between environmental management practices and economic benefits. This article suggests that commitment to quality and the environment can allow small businesses in the service sector to have a competitive advantage that will separate surviving and ceased operations, particularly in sectors that are rapidly evolving and highly competitive.

Forensic processing of false identity and travel documents to produce intelligence: a novel approach to assist in fighting organized crime

The production and use of false identity and travel documents in organized crime represent a serious and evolving threat. However, a case-by-case perspective, thus suffering from linkage blindness and a limited analysis capacity, essentially drives the present-day fight against this criminal problem. To assist in overcoming these limitations, a process model was developed using a forensic perspective. It guides the systematic analysis and management of seized false documents to generate forensic intelligence that supports strategic and tactical decision-making in an intelligence-led policing approach. The model is articulated on a three-level architecture that aims to assist in detecting and following-up on general trends, production methods and links between cases or series. Using analyses of a large dataset of counterfeit and forged identity and travel documents, it is possible to illustrate the model, its three levels and their contribution. Examples will point out how the proposed approach assists in detecting emerging trends, in evaluating the black market's degree of structure, in uncovering criminal networks, in monitoring the quality of false documents, and in identifying their weaknesses to orient the conception of more secured travel and identity documents. The process model proposed is thought to have a general application in forensic science and can readily be transposed to other fields of study.

Distance Transforms on Gray-Level Surfaces

This thesis studies gray-level distance transforms, particularly the Distance Transform on Curved Space (DTOCS). The transform is produced by calculating distances on a gray-level surface. The DTOCS is improved by definingmore accurate local distances, and developing a faster transformation algorithm. The Optimal DTOCS enhances the locally Euclidean Weighted DTOCS (WDTOCS) with local distance coefficients, which minimize the maximum error from the Euclideandistance in the image plane, and produce more accurate global distance values.Convergence properties of the traditional mask operation, or sequential localtransformation, and the ordered propagation approach are analyzed, and compared to the new efficient priority pixel queue algorithm. The Route DTOCS algorithmdeveloped in this work can be used to find and visualize shortest routes between two points, or two point sets, along a varying height surface. In a digital image, there can be several paths sharing the same minimal length, and the Route DTOCS visualizes them all. A single optimal path can be extracted from the route set using a simple backtracking algorithm. A new extension of the priority pixel queue algorithm produces the nearest neighbor transform, or Voronoi or Dirichlet tessellation, simultaneously with the distance map. The transformation divides the image into regions so that each pixel belongs to the region surrounding the reference point, which is nearest according to the distance definition used. Applications and application ideas for the DTOCS and its extensions are presented, including obstacle avoidance, image compression and surface roughness evaluation.