A relational approach to the geography of innovation: a typology of regions

The aim of this study was to devise a method for computing a composite indicator that measures the regional degree of exposure to external knowledge sources. On the basis of this indicator, we propose a typology of regions according to their potential capacity to access extra-local items of knowledge, which might help them to recombine complementary elements of such an asset to produce a higher number of new ideas. Building on various research streams that have been relatively independent to date, we summarize a non-exhaustive instrumental list of recent studies that motivates our approach and the construction of our complex indicator, which can be used to appraise the extent to which each region is in an optimal position to access external innovative resources.

An integrative computational analysis provides evidence for FBN1-associated network deregulation in trisomy 21

Although approximately 50% of Down Syndrome (DS) patients have heart abnormalities, they exhibit an overprotection against cardiac abnormalities related with the connective tissue, for example a lower risk of coronary artery disease. A recent study reported a case of a person affected by DS who carried mutations in FBN1, the gene causative for a connective tissue disorder called Marfan Syndrome (MFS). The fact that the person did not have any cardiac alterations suggested compensation effects due to DS. This observation is supported by a previous DS meta-analysis at the molecular level where we have found an overall upregulation of FBN1 (which is usually downregulated in MFS). Additionally, that result was cross-validated with independent expression data from DS heart tissue. The aim of this work is to elucidate the role of FBN1 in DS and to establish a molecular link to MFS and MFS-related syndromes using a computational approach. To reach that, we conducted different analytical approaches over two DS studies (our previous meta-analysis and independent expression data from DS heart tissue) and revealed expression alterations in the FBN1 interaction network, in FBN1 co-expressed genes and FBN1-related pathways. After merging the significant results from different datasets with a Bayesian approach, we prioritized 85 genes that were able to distinguish control from DS cases. We further found evidence for several of these genes (47%), such as FBN1, DCN, and COL1A2, being dysregulated in MFS and MFS-related diseases. Consequently, we further encourage the scientific community to take into account FBN1 and its related network for the study of DS cardiovascular characteristics.

Study of tergal glands morphogenesis through an integrative analysis of genomic data

About 50% of living species are holometabolan insects. Therefore, unraveling the ori- gin of insect metamorphosis from the hemimetabolan (gradual metamorphosis) to the holometabolan (sudden metamorphosis at the end of the life cycle) mode is equivalent to explaining how all this biodiversity originated. One of the problems with studying the evolution from hemimetaboly to holometaboly is that most information is available only in holometabolan species. Within the hemimetabolan group, our model, the cock- roach Blattella germanica, is the most studied species. However, given that the study of adult morphogenesis at organismic level is still complex, we focused on the study of the tergal gland (TG) as a minimal model of metamorphosis. The TG is formed in tergites 7 and 8 (T7-8) in the last days of the last nymphal instar (nymph 6). The comparative study of four T7-T8 transcriptomes provided us with crucial keys of TG formation, but also essential information about the mechanisms and circuitry that allows the shift from nymphal to adult morphogenesis.

Accelerated Microstructure Imaging via Convex Optimisation for regions with multiple fibres (AMICOx)

This paper reviews and extends our previous work to enable fast axonal diameter mapping from diffusion MRI data in the presence of multiple fibre populations within a voxel. Most of the existing mi-crostructure imaging techniques use non-linear algorithms to fit their data models and consequently, they are computationally expensive and usually slow. Moreover, most of them assume a single axon orientation while numerous regions of the brain actually present more complex configurations, e.g. fiber crossing. We present a flexible framework, based on convex optimisation, that enables fast and accurate reconstructions of the microstructure organisation, not limited to areas where the white matter is coherently oriented. We show through numerical simulations the ability of our method to correctly estimate the microstructure features (mean axon diameter and intra-cellular volume fraction) in crossing regions.

Accuracy of cognitive MRI-targeted biopsy in hitting prostate cancer-positive regions of interest.

PURPOSE: Prostate cancer (PCa) diagnosis relies on clinical suspicion leading to systematic transrectal ultrasound-guided biopsy (TRUSGB). Multiparametric magnetic resonance imaging (mpMRI) allows for targeted biopsy of suspicious areas of the prostate instead of random 12-core biopsy. This method has been shown to be more accurate in detecting significant PCa. However, the precise spatial accuracy of cognitive targeting is unknown. METHODS: Consecutive patients undergoing mpMRI-targeted TRUSGB with cognitive registration (MRTB-COG) followed by robot-assisted radical prostatectomy were included in the present analysis. The regions of interest (ROIs) involved by the index lesion reported on mpMRI were subsequently targeted by two experienced urologists using the cognitive approach. The 27 ROIs were used as spatial reference. Mapping on radical prostatectomy specimen was used as reference to determine true-positive mpMRI findings. Per core correlation analysis was performed. RESULTS: Forty patients were included. Overall, 40 index lesions involving 137 ROIs (mean ROIs per index lesion 3.43) were identified on MRI. After correlating these findings with final pathology, 117 ROIs (85 %) were considered as true-positive lesions. A total of 102 biopsy cores directed toward such true-positive ROIs were available for final analysis. Cognitive targeted biopsy hit the target in 82 % of the cases (84/102). The only identified risk factor for missing the target was an anterior situated ROI (p = 0.01). CONCLUSION: In experienced hands, cognitive MRTB-COG allows for an accuracy of 82 % in hitting the correct target, given that it is a true-positive lesion. Anterior tumors are less likely to be successfully targeted.

Analysis of space-time environmental data in complex regions

This thesis develops a comprehensive and a flexible statistical framework for the analysis and detection of space, time and space-time clusters of environmental point data. The developed clustering methods were applied in both simulated datasets and real-world environmental phenomena; however, only the cases of forest fires in Canton of Ticino (Switzerland) and in Portugal are expounded in this document. Normally, environmental phenomena can be modelled as stochastic point processes where each event, e.g. the forest fire ignition point, is characterised by its spatial location and occurrence in time. Additionally, information such as burned area, ignition causes, landuse, topographic, climatic and meteorological features, etc., can also be used to characterise the studied phenomenon. Thereby, the space-time pattern characterisa- tion represents a powerful tool to understand the distribution and behaviour of the events and their correlation with underlying processes, for instance, socio-economic, environmental and meteorological factors. Consequently, we propose a methodology based on the adaptation and application of statistical and fractal point process measures for both global (e.g. the Morisita Index, the Box-counting fractal method, the multifractal formalism and the Ripley's K-function) and local (e.g. Scan Statistics) analysis. Many measures describing the space-time distribution of environmental phenomena have been proposed in a wide variety of disciplines; nevertheless, most of these measures are of global character and do not consider complex spatial constraints, high variability and multivariate nature of the events. Therefore, we proposed an statistical framework that takes into account the complexities of the geographical space, where phenomena take place, by introducing the Validity Domain concept and carrying out clustering analyses in data with different constrained geographical spaces, hence, assessing the relative degree of clustering of the real distribution. Moreover, exclusively to the forest fire case, this research proposes two new methodologies to defining and mapping both the Wildland-Urban Interface (WUI) described as the interaction zone between burnable vegetation and anthropogenic infrastructures, and the prediction of fire ignition susceptibility. In this regard, the main objective of this Thesis was to carry out a basic statistical/- geospatial research with a strong application part to analyse and to describe complex phenomena as well as to overcome unsolved methodological problems in the characterisation of space-time patterns, in particular, the forest fire occurrences. Thus, this Thesis provides a response to the increasing demand for both environmental monitoring and management tools for the assessment of natural and anthropogenic hazards and risks, sustainable development, retrospective success analysis, etc. The major contributions of this work were presented at national and international conferences and published in 5 scientific journals. National and international collaborations were also established and successfully accomplished. -- Cette thèse développe une méthodologie statistique complète et flexible pour l'analyse et la détection des structures spatiales, temporelles et spatio-temporelles de données environnementales représentées comme de semis de points. Les méthodes ici développées ont été appliquées aux jeux de données simulées autant qu'A des phénomènes environnementaux réels; nonobstant, seulement le cas des feux forestiers dans le Canton du Tessin (la Suisse) et celui de Portugal sont expliqués dans ce document. Normalement, les phénomènes environnementaux peuvent être modélisés comme des processus ponctuels stochastiques ou chaque événement, par ex. les point d'ignition des feux forestiers, est déterminé par son emplacement spatial et son occurrence dans le temps. De plus, des informations tels que la surface bru^lée, les causes d'ignition, l'utilisation du sol, les caractéristiques topographiques, climatiques et météorologiques, etc., peuvent aussi être utilisées pour caractériser le phénomène étudié. Par conséquent, la définition de la structure spatio-temporelle représente un outil puissant pour compren- dre la distribution du phénomène et sa corrélation avec des processus sous-jacents tels que les facteurs socio-économiques, environnementaux et météorologiques. De ce fait, nous proposons une méthodologie basée sur l'adaptation et l'application de mesures statistiques et fractales des processus ponctuels d'analyse global (par ex. l'indice de Morisita, la dimension fractale par comptage de boîtes, le formalisme multifractal et la fonction K de Ripley) et local (par ex. la statistique de scan). Des nombreuses mesures décrivant les structures spatio-temporelles de phénomènes environnementaux peuvent être trouvées dans la littérature. Néanmoins, la plupart de ces mesures sont de caractère global et ne considèrent pas de contraintes spatiales com- plexes, ainsi que la haute variabilité et la nature multivariée des événements. A cet effet, la méthodologie ici proposée prend en compte les complexités de l'espace géographique ou le phénomène a lieu, à travers de l'introduction du concept de Domaine de Validité et l'application des mesures d'analyse spatiale dans des données en présentant différentes contraintes géographiques. Cela permet l'évaluation du degré relatif d'agrégation spatiale/temporelle des structures du phénomène observé. En plus, exclusif au cas de feux forestiers, cette recherche propose aussi deux nouvelles méthodologies pour la définition et la cartographie des zones périurbaines, décrites comme des espaces anthropogéniques à proximité de la végétation sauvage ou de la forêt, et de la prédiction de la susceptibilité à l'ignition de feu. A cet égard, l'objectif principal de cette Thèse a été d'effectuer une recherche statistique/géospatiale avec une forte application dans des cas réels, pour analyser et décrire des phénomènes environnementaux complexes aussi bien que surmonter des problèmes méthodologiques non résolus relatifs à la caractérisation des structures spatio-temporelles, particulièrement, celles des occurrences de feux forestières. Ainsi, cette Thèse fournit une réponse à la demande croissante de la gestion et du monitoring environnemental pour le déploiement d'outils d'évaluation des risques et des dangers naturels et anthro- pogéniques. Les majeures contributions de ce travail ont été présentées aux conférences nationales et internationales, et ont été aussi publiées dans 5 revues internationales avec comité de lecture. Des collaborations nationales et internationales ont été aussi établies et accomplies avec succès.

Vulnerability of stream biota to climate change in mediterranean climate regions: a synthesis of ecological responses and conservation challenges

Freshwater species worldwide are experiencing dramatic declines partly attributable to ongoing climate change. It is expected that the future effects of climate change could be particularly severe in mediterranean climate (med-) regions, which host many endemic species already under great stress from the high level of human development. In this article, we review the climate and climate-induced changes in streams of med-regions and the responses of stream biota, focusing on both observed and anticipated ecological responses. We also discuss current knowledge gaps and conservation challenges. Expected climate alterations have already been observed in the last decades, and include: increased annual average air temperatures; decreased annual average precipitation; hydrologic alterations; and an increase in frequency, intensity and duration of extreme events, such as floods, droughts and fires. Recent observations, which are concordant with forecasts built, show stream biota of med-regions when facing climate changes tend to be displaced towards higher elevations and upper latitudes, communities tend to change their composition and homogenize, while some life-history traits seem to provide biota with resilience and resistance to adapt to the new conditions (as being short-lived, small, and resistant to low streamflow and desiccation). Nevertheless, such responses may be insufficient to cope with current and future environmental changes. Accurate forecasts of biotic changes and possible adaptations are difficult to obtain in med-regions mainly because of the difficulty of distinguishing disturbances due to natural variability from the effects of climate change, particularly regarding hydrology. Long-term studies are needed to disentangle such variability and improve knowledge regarding the ecological responses and the detection of early warning signals to climate change. Investments should focus on taxa beyond fish and macroinvertebrates, and in covering the less studied regions of Chile and South Africa. Scientists, policy makers and water managers must be involved in the climate change dialogue because the freshwater conservation concerns are huge.

Active regions for colour texture segmentation integrating region and boundary information

In this paper a colour texture segmentation method, which unifies region and boundary information, is proposed. The algorithm uses a coarse detection of the perceptual (colour and texture) edges of the image to adequately place and initialise a set of active regions. Colour texture of regions is modelled by the conjunction of non-parametric techniques of kernel density estimation (which allow to estimate the colour behaviour) and classical co-occurrence matrix based texture features. Therefore, region information is defined and accurate boundary information can be extracted to guide the segmentation process. Regions concurrently compete for the image pixels in order to segment the whole image taking both information sources into account. Furthermore, experimental results are shown which prove the performance of the proposed method

Unsupervised active regions for multiresolution image segmentation

An unsupervised approach to image segmentation which fuses region and boundary information is presented. The proposed approach takes advantage of the combined use of 3 different strategies: the guidance of seed placement, the control of decision criterion, and the boundary refinement. The new algorithm uses the boundary information to initialize a set of active regions which compete for the pixels in order to segment the whole image. The method is implemented on a multiresolution representation which ensures noise robustness as well as computation efficiency. The accuracy of the segmentation results has been proven through an objective comparative evaluation of the method

Does social capital reinforce technological inputs in the creation of knowledge? Evidence from the Spanish regions

In this paper we seek to verify the hypothesis that trust and cooperation between individuals, and between them and public institutions, can encourage technological innovation and the adoption of knowledge. Additionally, we test the extent to which the interaction of social capital with human capital and R&D expenditures improve their effect on a region’s ability to innovate. Our empirical evidence is taken from the Spanish regions and employs a knowledge production function and longitudinal count data models. Our results suggest that social capital correlates positively with innovation. Further, our analysis reveals a powerful interaction between human and social capital in the production of knowledge, whilst the complementarity with R&D efforts would seem less clear.

Panel Data Stochastic Convergence Analysis of the Mexican Regions

The stochastic convergence amongst Mexican Federal entities is analyzed in panel data framework. The joint consideration of cross-section dependence and multiple structural breaks is required to ensure that the statistical inference is based on statistics with good statistical properties. Once these features are accounted for, evidence in favour of stochastic convergence is found. Since stochastic convergence is a necessary, yet insufficient condition for convergence as predicted by economic growth models, the paper also investigates whether-convergence process has taken place. We found that the Mexican states have followed either heterogeneous convergence patterns or divergence process throughout the analyzed period.

Avantatges i inconvenients de la metodologia INE per a elaborar indicadors de la producció industrial per a les regions espanyoles

Conèixer l'evolució conjuntural del sector industrial, tant a nivell nacional com regional, és de gran importància. En aquest sentit, el retard en la publicació de les xifres de les Comptabilitats Nacionals/Regionals, fa necessària l'elaboració d'indicadors que permetin dur a terme un seguiment a curt termini de l'activitat industrial. Així, l'INE elabora un IPI mensual obtingut pel mètode directe pel conjunt de l'Estat. D'altra banda, al llarg dels darrers anys, a algunes comunitats autònomes espanyoles, s'han engegat projectes centrats en l'elaboració d'indicadors de l'activitat industrial regional, tot i que a partir de metodologies no homogènies. Per corregir aquesta situació, d'un temps ençà, a diferents fòrums s'ha proposat emprar la metodologia emprada per l'IDESCAT per elaborar l'indicador de la comunitat catalana com a alternativa per construir indicadors de l'activitat industrial regional, atès el seu bon comportament per Catalunya. Així, l'INE recentment ha publicat uns IPIs per les CA espanyoles d'acord amb dita metodologia. A aquest treball s'estudia la idoneïtat d'estendre l'esmentada metodologia a totes les regions espanyoles. Per això, es duu a terme una anàlisi comparativa centrada en (tres de) les quatre regions que disposen d'un IPI elaborat pel mètode directe: Andalusia, Astúries i el País Basc.