Evolution of network structure in polymer-stabilised liquid crystals

Experiments were performed to investigate the evolution of structure and morphology of the network in polymer-stabilised liquid crystals. In situ optical microscopy revealed that the morphology was significantly altered by extraction of the LC host, while scanning electron microscopy showed that the network morphology was also dependent on the polymerisation conditions and closely related to the depletion of monomer, as monitored by high performance liquid chromatography. Transmission electron microscopy allowed observation of internal structure, resolving microstructure on the order of 0. 1 μm.

Genetic diversity and population structure of pumas (Puma concolor) in southeastern Brazil: implications for conservation in a human-dominated landscape

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Genetic diversity and population structure of the New World screwworm fly from the Amazon region of Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Genetic diversity and population structure of Musa accessions in ex situ conservation

Abstract Background Banana cultivars are mostly derived from hybridization between wild diploid subspecies of Musa acuminata (A genome) and M. balbisiana (B genome), and they exhibit various levels of ploidy and genomic constitution. The Embrapa ex situ Musa collection contains over 220 accessions, of which only a few have been genetically characterized. Knowledge regarding the genetic relationships and diversity between modern cultivars and wild relatives would assist in conservation and breeding strategies. Our objectives were to determine the genomic constitution based on Internal Transcribed Spacer (ITS) regions polymorphism and the ploidy of all accessions by flow cytometry and to investigate the population structure of the collection using Simple Sequence Repeat (SSR) loci as co-dominant markers based on Structure software, not previously performed in Musa. Results From the 221 accessions analyzed by flow cytometry, the correct ploidy was confirmed or established for 212 (95.9%), whereas digestion of the ITS region confirmed the genomic constitution of 209 (94.6%). Neighbor-joining clustering analysis derived from SSR binary data allowed the detection of two major groups, essentially distinguished by the presence or absence of the B genome, while subgroups were formed according to the genomic composition and commercial classification. The co-dominant nature of SSR was explored to analyze the structure of the population based on a Bayesian approach, detecting 21 subpopulations. Most of the subpopulations were in agreement with the clustering analysis. Conclusions The data generated by flow cytometry, ITS and SSR supported the hypothesis about the occurrence of homeologue recombination between A and B genomes, leading to discrepancies in the number of sets or portions from each parental genome. These phenomenons have been largely disregarded in the evolution of banana, as the “single-step domestication” hypothesis had long predominated. These findings will have an impact in future breeding approaches. Structure analysis enabled the efficient detection of ancestry of recently developed tetraploid hybrids by breeding programs, and for some triploids. However, for the main commercial subgroups, Structure appeared to be less efficient to detect the ancestry in diploid groups, possibly due to sampling restrictions. The possibility of inferring the membership among accessions to correct the effects of genetic structure opens possibilities for its use in marker-assisted selection by association mapping.

Diversity and genetic structure in natural populations of Hancornia speciosa var. speciosa Gomes in northeastern Brazil

Hancornia speciosa Gomes is a fruit tree native from Brazil that belongs to Apocinaceae family, and is popularly known as Mangabeira. Its fruits are widely consumed raw or processed as fruit jam, juices and ice creams, which have made it a target of intense exploitation. The extractive activities and intense human activity on the environment of natural occurrence of H. speciosa has caused genetic erosion in the species and little is known about the ecology or genetic structure of natural populations. The objective of this research was the evaluation of the genetic diversity and genetic structure of H. speciosa var. speciosa. The genetic variability was assessed using 11 allozyme loci with a sample of 164 individuals distributed in six natural populations located in the States of Pernambuco and Alagoas, Northeastern Brazil. The results showed a high level of genetic diversity within the species (e= 0.36) seeing that the most of the genetic variability of H. speciosa var. speciosa is within its natural populations with low difference among populations ( or = 0.081). The inbreeding values within ( = -0.555) and among populations ( =-0.428) were low showing lacking of endogamy and a surplus of heterozygotes. The estimated gene flow ( m ) was high, ranging from 2.20 to 13.18, indicating to be enough to prevent the effects of genetic drift and genetic differentiation among populations. The multivariate analyses indicated that there is a relationship between genetic and geographical distances, which was confirmed by a spatial pattern analysis using Mantel test (r = 0.3598; p = 0.0920) with 1000 random permutations. The high genetic diversity index in these populations indicates potential for in situ genetic conservation.

Diversity and Genetic structure of the Spanish collection of durum wheat (Triticum turgidum L) landraces

The objectives of this study were to assess diversity and genetic structure of a collection of Spanish durum wheat (Triticum turgidum L) landraces, using SSRs, DArTs and gliadin-markers, and to correlate the distribution of diversity with geographic and climatic features, as well as agro-morphological traits. A high level of diversity was detected in the genotypes analyzed, which were separated into nine populations with a moderate to great genetic divergence among them. The three subspecies taxa, dicoccon, turgidum and durum, present in the collection, largely determined the clustering of the populations. Genotype variation was lower in dicoccon (one major population) and turgidum (two major populations) than in durum (five major populations). Genetic differentiation by the agro-ecological zone of origin was greater in dicoccon and turgidum than in durum. DArT markers revealed two geographic substructures, east-west for dicoccon and northeast-southwest for turgidum. The ssp. durum had a more complex structure, consisting of seven populations with high intra-population variation. DArT markers allowed the detection of subgroups within some populations, with agro-morphological and gliadin differences, and distinct agro-ecological zones of origin. Two different phylogenetic groups were detected; revealing that some durum populations were more related to ssp. turgidum from northern Spain, while others seem to be more related to durum wheats from North Africa

Self-organizing cultured neural networks: Image analysis techniques for longitudinal tracking and modeling of the underlying network structure

Esta tesis estudia la evolución estructural de conjuntos de neuronas como la capacidad de auto-organización desde conjuntos de neuronas separadas hasta que forman una red (clusterizada) compleja. Esta tesis contribuye con el diseño e implementación de un algoritmo no supervisado de segmentación basado en grafos con un coste computacional muy bajo. Este algoritmo proporciona de forma automática la estructura completa de la red a partir de imágenes de cultivos neuronales tomadas con microscopios de fase con una resolución muy alta. La estructura de la red es representada mediante un objeto matemático (matriz) cuyos nodos representan a las neuronas o grupos de neuronas y los enlaces son las conexiones reconstruidas entre ellos. Este algoritmo extrae también otras medidas morfológicas importantes que caracterizan a las neuronas y a las neuritas. A diferencia de otros algoritmos hasta el momento, que necesitan de fluorescencia y técnicas inmunocitoquímicas, el algoritmo propuesto permite el estudio longitudinal de forma no invasiva posibilitando el estudio durante la formación de un cultivo. Además, esta tesis, estudia de forma sistemática un grupo de variables topológicas que garantizan la posibilidad de cuantificar e investigar la progresión de las características principales durante el proceso de auto-organización del cultivo. Nuestros resultados muestran la existencia de un estado concreto correspondiente a redes con configuracin small-world y la emergencia de propiedades a micro- y meso-escala de la estructura de la red. Finalmente, identificamos los procesos físicos principales que guían las transformaciones morfológicas de los cultivos y proponemos un modelo de crecimiento de red que reproduce el comportamiento cuantitativamente de las observaciones experimentales. ABSTRACT The thesis analyzes the morphological evolution of assemblies of living neurons, as they self-organize from collections of separated cells into elaborated, clustered, networks. In particular, it contributes with the design and implementation of a graph-based unsupervised segmentation algorithm, having an associated very low computational cost. The processing automatically retrieves the whole network structure from large scale phase-contrast images taken at high resolution throughout the entire life of a cultured neuronal network. The network structure is represented by a mathematical object (a matrix) in which nodes are identified neurons or neurons clusters, and links are the reconstructed connections between them. The algorithm is also able to extract any other relevant morphological information characterizing neurons and neurites. More importantly, and at variance with other segmentation methods that require fluorescence imaging from immunocyto- chemistry techniques, our measures are non invasive and entitle us to carry out a fully longitudinal analysis during the maturation of a single culture. In turn, a systematic statistical analysis of a group of topological observables grants us the possibility of quantifying and tracking the progression of the main networks characteristics during the self-organization process of the culture. Our results point to the existence of a particular state corresponding to a small-world network configuration, in which several relevant graphs micro- and meso-scale properties emerge. Finally, we identify the main physical processes taking place during the cultures morphological transformations, and embed them into a simplified growth model that quantitatively reproduces the overall set of experimental observations.

Self-organizing cultured neural networks: Image analysis techniques for longitudinal tracking and modeling of the underlying network structure (versión actualizada)

Esta tesis estudia la evolución estructural de conjuntos de neuronas como la capacidad de auto-organización desde conjuntos de neuronas separadas hasta que forman una red (clusterizada) compleja. Esta tesis contribuye con el diseño e implementación de un algoritmo no supervisado de segmentación basado en grafos con un coste computacional muy bajo. Este algoritmo proporciona de forma automática la estructura completa de la red a partir de imágenes de cultivos neuronales tomadas con microscopios de fase con una resolución muy alta. La estructura de la red es representada mediante un objeto matemático (matriz) cuyos nodos representan a las neuronas o grupos de neuronas y los enlaces son las conexiones reconstruidas entre ellos. Este algoritmo extrae también otras medidas morfológicas importantes que caracterizan a las neuronas y a las neuritas. A diferencia de otros algoritmos hasta el momento, que necesitan de fluorescencia y técnicas inmunocitoquímicas, el algoritmo propuesto permite el estudio longitudinal de forma no invasiva posibilitando el estudio durante la formación de un cultivo. Además, esta tesis, estudia de forma sistemática un grupo de variables topológicas que garantizan la posibilidad de cuantificar e investigar la progresión de las características principales durante el proceso de auto-organización del cultivo. Nuestros resultados muestran la existencia de un estado concreto correspondiente a redes con configuracin small-world y la emergencia de propiedades a micro- y meso-escala de la estructura de la red. Finalmente, identificamos los procesos físicos principales que guían las transformaciones morfológicas de los cultivos y proponemos un modelo de crecimiento de red que reproduce el comportamiento cuantitativamente de las observaciones experimentales. ABSTRACT The thesis analyzes the morphological evolution of assemblies of living neurons, as they self-organize from collections of separated cells into elaborated, clustered, networks. In particular, it contributes with the design and implementation of a graph-based unsupervised segmentation algorithm, having an associated very low computational cost. The processing automatically retrieves the whole network structure from large scale phase-contrast images taken at high resolution throughout the entire life of a cultured neuronal network. The network structure is represented by a mathematical object (a matrix) in which nodes are identified neurons or neurons clusters, and links are the reconstructed connections between them. The algorithm is also able to extract any other relevant morphological information characterizing neurons and neurites. More importantly, and at variance with other segmentation methods that require fluorescence imaging from immunocyto- chemistry techniques, our measures are non invasive and entitle us to carry out a fully longitudinal analysis during the maturation of a single culture. In turn, a systematic statistical analysis of a group of topological observables grants us the possibility of quantifying and tracking the progression of the main networks characteristics during the self-organization process of the culture. Our results point to the existence of a particular state corresponding to a small-world network configuration, in which several relevant graphs micro- and meso-scale properties emerge. Finally, we identify the main physical processes taking place during the cultures morphological transformations, and embed them into a simplified growth model that quantitatively reproduces the overall set of experimental observations.

Genetic diversity and population structure of Tasmanian devils, the largest marsupial carnivore

Genetic diversity and population structure were investigated across the core range of Tasmanian devils (Sarcophilus laniarius; Dasyuridae), a wide-ranging marsupial carnivore restricted to the island of Tasmania. Heterozygosity (0.386-0.467) and allelic diversity (2.7-3.3) were low in all subpopulations and allelic size ranges were small and almost continuous, consistent with a founder effect. Island effects and repeated periods of low population density may also have contributed to the low variation. Within continuous habitat, gene flow appears extensive up to 50 km (high assignment rates to source or close neighbour populations; nonsignificant values of pairwise F-ST), in agreement with movement data. At larger scales (150-250 km), gene flow is reduced (significant pairwise F-ST) but there is no evidence for isolation by distance. The most substantial genetic structuring was observed for comparisons spanning unsuitable habitat, implying limited dispersal of devils between the well-connected, eastern populations and a smaller northwestern population. The genetic distinctiveness of the northwestern population was reflected in all analyses: unique alleles; multivariate analyses of gene frequency (multidimensional scaling, minimum spanning tree, nearest neighbour); high self-assignment (95%); two distinct populations for Tasmania were detected in isolation by distance and in Bayesian model-based clustering analyses. Marsupial carnivores appear to have stronger population subdivisions than their placental counterparts.

The network structure of a regional tourism organization: Application of he social network theory in one region of Queensland

Regional tourism organizations (RTOs) plays a central role in planning, coordinating and marketing tourism in many areas, including Queensland, Australia. RTOs rely on interaction with a network of other organizations for their efficient functioning. This paper describes an exploratory case study that develops a method for use of social network analysis techniques to analyse the inter-organizational network in one RTO region in Queensland. Results indicate that differences exist in the structure of inter-organizational links between commercial tourism organizations and planning organizations, between tourism organizations and other sectoral clusters, and between organizations at local, regional and state levels. The results highlight areas or improvement in the role and responsibilities of RTOs in Queensland.

University-industry-relations - their role in technological innovation:the case of biotechnology in the UK

Biotechnology is one of a series of new `generic technologies' that have been identified by western governments as possessing stategic economic opportunities. In this thesis I examine the characteristics of the technology and the government policies that have been developed to both promote and exploit the underpinning scientific research for biotechnology. The approach I have taken involves an in-depth analysis of the role of university-industry research relations in the development of biotechnology. To this end I carried out a detailed survey of biotechnology companies in the UK on the nature of their interactions and objectives. Through individual case studies of the SERC and DTI club mechanisms in biotechnology, I provide a contemporary appraisal of the development of new mechanisms involving co-ordination and cooperation between industry, government and academia, established to couple state funded science and national economic development. The public policy implications of the club funding systems for science in the UK are examined.

Network effects, network structure and consumer interaction in mobile telecommunications in Europe and Asia

This paper estimates the importance of (tariff-mediated) network effects and the impact of a consumer's social network on her choice of mobile phone provider. The study uses network data obtained from surveys of students in several European and Asian countries. We use the Quadratic Assignment Procedure, a non-parametric permutation test, to adjust for the particular error structure of network data. We find that respondents strongly coordinate their choice of mobile phone providers, but only if their provider induces network effects. This suggests that this coordination depends on network effects rather than on information contagion or pressure to conform to the social environment.

The network structure of Hungarian business clusters

This article investigates the attitudes to inter-firm co-operation in Hungary by analysing a special group of business networks: the business clusters. Following an overview of cluster policy, a wide range of selfproclaimed business clusters are identified. A small elite of these business networks evolves into successful, sustainable innovative business clusters. However, in the majority of cases, these consortia of interfirm co-operation are not based on a mutually satisfactory model, and as a consequence, many clusters do not survive in the longer term. The paper uses the concepts and models of social network theory in order to explain, why and under what circumstances inter-firm co-operation in clusters enhances the competitiveness of the network as a whole, or alternatively, under what circumstances the cluster remains dependent on Government subsidies. The empirical basis of the study is a thorough internet research about the Hungarian cluster movement; a questionnaire based expert survey among managers of clusters and member companies and a set of in-depth interviews among managers of self-proclaimed clusters. The last chapter analyises the applicability of social network theory in the analysis of business networks and a model involving the value chain is recommended.