724 resultados para Non-government organization


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Based on the consolidated statements data of the universal/commercial banks (UKbank) and non-bank financial institutions with quasi-banking licenses, this paper presents a keen necessity of obtaining data in detail on both sides (assets and liabilities) of their financial conditions and further analyses. Those would bring more adequate assessments on the Philippine financial system, especially with regard to each financial subsector's financing/lending preferences and behavior. The paper also presents a possibility that the skewed locational and operational distribution exists in the non-UKbank financial subsectors. It suggests there may be a significant deviation from the authorities' (the BSP, SEC and others) intended/anticipated financial system in the banking/non-bank financial institutions' real operations.

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At present, many countries allow citizens or entities to interact with the government outside the telematic environment through a legal representative who is granted powers of representation. However, if the interaction takes place through the Internet, only primitive mechanisms of representation are available, and these are mainly based on non-dynamic offline processes that do not enable quick and easy identity delegation. This paper proposes a system of dynamic delegation of identity between two generic entities that can solve the problem of delegated access to the telematic services provided by public authorities. The solution herein is based on the generation of a delegation token created from a proxy certificate that allows the delegating entity to delegate identity to another on the basis of a subset of its attributes as delegator, while also establishing in the delegation token itself restrictions on the services accessible to the delegated entity and the validity period of delegation. Further, the paper presents the mechanisms needed to either revoke a delegation token or to check whether a delegation token has been revoked. Implications for theory and practice and suggestions for future research are discussed.

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Cuando una colectividad de sistemas dinámicos acoplados mediante una estructura irregular de interacciones evoluciona, se observan dinámicas de gran complejidad y fenómenos emergentes imposibles de predecir a partir de las propiedades de los sistemas individuales. El objetivo principal de esta tesis es precisamente avanzar en nuestra comprensión de la relación existente entre la topología de interacciones y las dinámicas colectivas que una red compleja es capaz de mantener. Siendo este un tema amplio que se puede abordar desde distintos puntos de vista, en esta tesis se han estudiado tres problemas importantes dentro del mismo que están relacionados entre sí. Por un lado, en numerosos sistemas naturales y artificiales que se pueden describir mediante una red compleja la topología no es estática, sino que depende de la dinámica que se desarrolla en la red: un ejemplo son las redes de neuronas del cerebro. En estas redes adaptativas la propia topología emerge como consecuencia de una autoorganización del sistema. Para conocer mejor cómo pueden emerger espontáneamente las propiedades comúnmente observadas en redes reales, hemos estudiado el comportamiento de sistemas que evolucionan según reglas adaptativas locales con base empírica. Nuestros resultados numéricos y analíticos muestran que la autoorganización del sistema da lugar a dos de las propiedades más universales de las redes complejas: a escala mesoscópica, la aparición de una estructura de comunidades, y, a escala macroscópica, la existencia de una ley de potencias en la distribución de las interacciones en la red. El hecho de que estas propiedades aparecen en dos modelos con leyes de evolución cuantitativamente distintas que siguen unos mismos principios adaptativos sugiere que estamos ante un fenómeno que puede ser muy general, y estar en el origen de estas propiedades en sistemas reales. En segundo lugar, proponemos una medida que permite clasificar los elementos de una red compleja en función de su relevancia para el mantenimiento de dinámicas colectivas. En concreto, estudiamos la vulnerabilidad de los distintos elementos de una red frente a perturbaciones o grandes fluctuaciones, entendida como una medida del impacto que estos acontecimientos externos tienen en la interrupción de una dinámica colectiva. Los resultados que se obtienen indican que la vulnerabilidad dinámica es sobre todo dependiente de propiedades locales, por tanto nuestras conclusiones abarcan diferentes topologías, y muestran la existencia de una dependencia no trivial entre la vulnerabilidad y la conectividad de los elementos de una red. Finalmente, proponemos una estrategia de imposición de una dinámica objetivo genérica en una red dada e investigamos su validez en redes con diversas topologías que mantienen regímenes dinámicos turbulentos. Se obtiene como resultado que las redes heterogéneas (y la amplia mayora de las redes reales estudiadas lo son) son las más adecuadas para nuestra estrategia de targeting de dinámicas deseadas, siendo la estrategia muy efectiva incluso en caso de disponer de un conocimiento muy imperfecto de la topología de la red. Aparte de la relevancia teórica para la comprensión de fenómenos colectivos en sistemas complejos, los métodos y resultados propuestos podrán dar lugar a aplicaciones en sistemas experimentales y tecnológicos, como por ejemplo los sistemas neuronales in vitro, el sistema nervioso central (en el estudio de actividades síncronas de carácter patológico), las redes eléctricas o los sistemas de comunicaciones. ABSTRACT The time evolution of an ensemble of dynamical systems coupled through an irregular interaction scheme gives rise to dynamics of great of complexity and emergent phenomena that cannot be predicted from the properties of the individual systems. The main objective of this thesis is precisely to increase our understanding of the interplay between the interaction topology and the collective dynamics that a complex network can support. This is a very broad subject, so in this thesis we will limit ourselves to the study of three relevant problems that have strong connections among them. First, it is a well-known fact that in many natural and manmade systems that can be represented as complex networks the topology is not static; rather, it depends on the dynamics taking place on the network (as it happens, for instance, in the neuronal networks in the brain). In these adaptive networks the topology itself emerges from the self-organization in the system. To better understand how the properties that are commonly observed in real networks spontaneously emerge, we have studied the behavior of systems that evolve according to local adaptive rules that are empirically motivated. Our numerical and analytical results show that self-organization brings about two of the most universally found properties in complex networks: at the mesoscopic scale, the appearance of a community structure, and, at the macroscopic scale, the existence of a power law in the weight distribution of the network interactions. The fact that these properties show up in two models with quantitatively different mechanisms that follow the same general adaptive principles suggests that our results may be generalized to other systems as well, and they may be behind the origin of these properties in some real systems. We also propose a new measure that provides a ranking of the elements in a network in terms of their relevance for the maintenance of collective dynamics. Specifically, we study the vulnerability of the elements under perturbations or large fluctuations, interpreted as a measure of the impact these external events have on the disruption of collective motion. Our results suggest that the dynamic vulnerability measure depends largely on local properties (our conclusions thus being valid for different topologies) and they show a non-trivial dependence of the vulnerability on the connectivity of the network elements. Finally, we propose a strategy for the imposition of generic goal dynamics on a given network, and we explore its performance in networks with different topologies that support turbulent dynamical regimes. It turns out that heterogeneous networks (and most real networks that have been studied belong in this category) are the most suitable for our strategy for the targeting of desired dynamics, the strategy being very effective even when the knowledge on the network topology is far from accurate. Aside from their theoretical relevance for the understanding of collective phenomena in complex systems, the methods and results here discussed might lead to applications in experimental and technological systems, such as in vitro neuronal systems, the central nervous system (where pathological synchronous activity sometimes occurs), communication systems or power grids.

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This exploratory study presents a comparison between two samples of microenterprises. One sample is formed by companies involved in product innovation during the current economic crisis and the other is formed by companies not involved in product innovation during the same period. The comparison analyzes which internal factors, supported by the literature as the influential factors of small business innovation, are significant when explaining the main differences between innovative microenterprise and non-innovative ones. The results suggest that the factors related to the organization and activity of the company are the factors which explain the differences between these two types of firms, rather than those factors related to micro-entrepreneurs own profile.

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Apples can be considered as having a complex system formed by several structures at different organization levels: macroscale (mayor que100 ?m) and microscale (menor que100 ?m). This work implements 2D T1/T2 global and localized relaxometry sequences on whole apples to be able to perform an intensive non-destructive and non-invasive microstructure study. The 2D T1/T2 cross-correlation spectroscopy allows the extraction of quantitative information about the water compartmentation in different subcellular organelles. A clear difference is found as sound apples show neat peaks for water in different subcellular compartments, such as vacuolar, cytoplasmatic and extracellular water, while in watercore-affected tissues such compartments appear merged. Localized relaxometry allows for the predefinition of slices in order to understand the microstructure of a particular region of the fruit, providing information that cannot be derived from global 2D T1/T2 relaxometry.

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Apples can be considered as having a complex system formed by several structures at different organization levels: macroscale (>100 μm) and microscale (<100 μm). This work implements 2D T1/T2 global and localized relaxometry sequences on whole apples to be able to perform an intensive non-destructive and non-invasive microstructure study. The 2D T1/T2 cross-correlation spectroscopy allows the extraction of quantitative information about the water compartmentation in different subcellular organelles. A clear difference is found as sound apples show neat peaks for water in different subcellular compartments, such as vacuolar, cytoplasmatic and extracellular water, while in watercore-affected tissues such compartments appear merged. Localized relaxometry allows for the predefinition of slices in order to understand the microstructure of a particular region of the fruit, providing information that cannot be derived from global 2D T1/T2 relaxometry.

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Dehydroepiandrosterone (DHEA) and its sulfate derivative (DHEAS) are the most abundant steroids produced by the human adrenal, but no receptors have been identified for these steroids, and no function for them has been established, other than as precursors for sex steroid synthesis. DHEA and DHEAS are found in brains from many species, and we have shown that enzymes crucial for their synthesis, especially P450c17 (17α-hydroxylase/c17,20 lyase), are expressed in a developmentally regulated, region-specific fashion in the developing rodent brain. One region of embryonic expression of P450c17, the neocortical subplate, has been postulated to play a role in guiding cortical projections to their appropriate targets. We therefore determined if products of P450c17 activity, DHEA and DHEAS, regulated the motility and/or growth of neocortical neurons. In primary cultures of mouse embryonic neocortical neurons, DHEA increased the length of neurites containing the axonal marker Tau-1, and the incidence of varicosities and basket-like process formations in a dose-dependent fashion. These effects could be seen at concentrations normally found in the brain. By contrast, DHEAS had no effect on Tau-1 axonal neurites but increased the length of neurites containing the dendritic marker microtubule-associated protein-2. DHEA rapidly increased free intracellular calcium via activation of N-methyl-d-aspartate (NMDA) receptors. These studies provide evidence of mechanisms by which DHEA and DHEAS exert biological actions, show that they have specific functions other than as sex steroid precursors, mediate their effects via non-classic steroid hormone receptors, and suggest that their developmentally regulated synthesis in vivo may play crucial and different roles in organizing the neocortex.

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The conserved organization of the Hox genes throughout the animal kingdom has become one of the major paradigms of evolutionary developmental biology. We have examined the organization of the Hox genes of the grasshopper, Schistocerca gregaria. We find that the grasshopper Hox cluster is over 700 kb long, and is not split into equivalents of the Antennapedia complex and the bithorax complex of Drosophila melanogaster. SgDax and probably also Sgzen, the grasshopper homologues of fushi-tarazu (ftz) and Zerknüllt (zen), respectively, are also in the cluster, showing that the non-homeotic Antp-class genes, “accessory genes,” are an ancient feature of insect Hox clusters.

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The segregation of thalamocortical inputs into eye-specific stripes in the developing cat or monkey visual cortex is prevented by manipulations that perturb or abolish neural activity in the visual pathway. Such findings show that proper development of the functional organization of visual cortex is dependent on normal patterns of neural activity. The generalisation of this conclusion to other sensory cortices has been questioned by findings that the segregation of thalamocortical afferents into a somatotopic barrel pattern in developing rodent primary somatosensory cortex (S1) is not prevented by activity blockade. We show that a temporary block of N-methyl-D-aspartate (NMDA) and non-NMDA glutamate receptors in rat S1 during the critical period for barrel development disrupts the topographic refinement of thalamocortical connectivity and columnar organization. These effects are evident well after the blockade is ineffective and thus may be permanent. Our findings show that neural activity and specifically the activation of postsynaptic cortical neurons has a prominent role in establishing the primary sensory map in S1, as well as the topographic organization of higher order synaptic connections.

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beta 2-Microglobulin is an essential subunit of major histocompatibility complex (Mhc) class I molecules, which present antigenic peptides to T lymphocytes. We sequenced a number of cDNAs and two genomic clones corresponding to chicken beta 2-microglobulin. The chicken beta 2-microglobulin gene has a similar genomic organization but smaller introns and higher G+C content than mammalian beta 2-microglobulin genes. The promoter region is particularly G+C-rich and contains, in addition to interferon regulatory elements, potential S/W, X, and Y boxes that were originally described for mammalian class II but not class I alpha or beta 2-microglobulin genes. There is a single chicken beta 2-microglobulin gene that has little polymorphism in the coding region. Restriction fragment length polymorphisms from Mhc homozygous lines, Mhc congenic lines, and backcross families, as well as in situ hybridization, show that the beta 2-microglobulin gene is located on a microchromosome different from the one that contains the chicken Mhc. We propose that the structural similarities between the beta 2-microglobulin and Mhc genes in the chicken are due to their presence on microchromosomes and suggest that these features and the microchromosomes appeared by deletion of DNA in the lineage leading to the birds.

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Non-suicidal self-injury (NSSI), such as cutting and burning, is a widespread social problem among lesbian, gay, bisexual, transgender, queer, and questioning (LGBTQ) youth. Extant research indicates that this population is more than twice as likely to engage in NSSI than heterosexual and cisgender (non-transgender) youth. Despite the scope of this social problem, it remains relatively unexamined in the literature. Research on other risk behaviors among LGBTQ youth indicates that experiencing homophobia and transphobia in key social contexts such as families, schools, and peer relationships contributes to health disparities among this group. Consequently, the aims of this study were to examine: (1) the relationship between LGBTQ youth's social environments and their NSSI behavior, and (2) whether/how specific aspects of the social environment contribute to an understanding of NSSI among LGBTQ youth. This study was conducted using an exploratory, sequential mixed methods design with two phases. The first phase of the study involved analysis of transcripts from interviews conducted with 44 LGBTQ youth recruited from a community-based organization. In this phase, five qualitative themes were identified: (1) Violence; (2) Misconceptions, Stigma, and Shame; (3) Negotiating LGBTQ Identity; (4) Invisibility and Isolation; and (5) Peer Relationships. Results from the qualitative phase were used to identify key variables and specify statistical models in the second, quantitative, phase of the study, using secondary data from a survey of 252 LGBTQ youth. The qualitative phase revealed how LGBTQ youth, themselves, described the role of the social environment in their NSSI behavior, while the quantitative phase was used to determine whether the qualitative findings could be used to predict engagement in NSSI among a larger sample of LGBTQ youth. The quantitative analyses found that certain social-environmental factors such as experiencing physical abuse at home, feeling unsafe at school, and greater openness about sexual orientation significantly predicted the likelihood of engaging in NSSI among LGBTQ youth. Furthermore, depression partially mediated the relationships between family physical abuse and NSSI and feeling unsafe at school and NSSI. The qualitative and quantitative results were compared in the interpretation phase to explore areas of convergence and incongruence. Overall, this study's findings indicate that social-environmental factors are salient to understanding NSSI among LGBTQ youth. The particular social contexts in which LGBTQ youth live significantly influence their engagement in this risk behavior. These findings can inform the development of culturally relevant NSSI interventions that address the social realities of LGBTQ youth's lives.

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Conceptual frameworks of dryland degradation commonly include ecohydrological feedbacks between landscape spatial organization and resource loss, so that decreasing cover and size of vegetation patches result in higher water and soil losses, which lead to further vegetation loss. However, the impacts of these feedbacks on dryland dynamics in response to external stress have barely been tested. Using a spatially-explicit model, we represented feedbacks between vegetation pattern and landscape resource loss by establishing a negative dependence of plant establishment on the connectivity of runoff-source areas (e.g., bare soils). We assessed the impact of various feedback strengths on the response of dryland ecosystems to changing external conditions. In general, for a given external pressure, these connectivity-mediated feedbacks decrease vegetation cover at equilibrium, which indicates a decrease in ecosystem resistance. Along a gradient of gradual increase of environmental pressure (e.g., aridity), the connectivity-mediated feedbacks decrease the amount of pressure required to cause a critical shift to a degraded state (ecosystem resilience). If environmental conditions improve, these feedbacks increase the pressure release needed to achieve the ecosystem recovery (restoration potential). The impact of these feedbacks on dryland response to external stress is markedly non-linear, which relies on the non-linear negative relationship between bare-soil connectivity and vegetation cover. Modelling studies on dryland vegetation dynamics not accounting for the connectivity-mediated feedbacks studied here may overestimate the resistance, resilience and restoration potential of drylands in response to environmental and human pressures. Our results also suggest that changes in vegetation pattern and associated hydrological connectivity may be more informative early-warning indicators of dryland degradation than changes in vegetation cover.

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This experimental work aims at probing current-induced forces at the atomic scale. Specifically it addresses predictions in recent work regarding the appearance of run-away modes as a result of a combined effect of the non-conservative wind force and a ‘Berry force’. The systems we consider here are atomic chains of Au and Pt atoms, for which we investigate the distribution of break down voltage values. We observe two distinct modes of breaking for Au atomic chains. The breaking at high voltage appears to behave as expected for regular break down by thermal excitation due to Joule heating. However, there is a low-voltage breaking mode that has characteristics expected for the mechanism of current-induced forces. Although a full comparison would require more detailed information on the individual atomic configurations, the systems we consider are very similar to those considered in recent model calculations and the comparison between experiment and theory is very encouraging for the interpretation we propose.

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Sensing techniques are important for solving problems of uncertainty inherent to intelligent grasping tasks. The main goal here is to present a visual sensing system based on range imaging technology for robot manipulation of non-rigid objects. Our proposal provides a suitable visual perception system of complex grasping tasks to support a robot controller when other sensor systems, such as tactile and force, are not able to obtain useful data relevant to the grasping manipulation task. In particular, a new visual approach based on RGBD data was implemented to help a robot controller carry out intelligent manipulation tasks with flexible objects. The proposed method supervises the interaction between the grasped object and the robot hand in order to avoid poor contact between the fingertips and an object when there is neither force nor pressure data. This new approach is also used to measure changes to the shape of an object’s surfaces and so allows us to find deformations caused by inappropriate pressure being applied by the hand’s fingers. Test was carried out for grasping tasks involving several flexible household objects with a multi-fingered robot hand working in real time. Our approach generates pulses from the deformation detection method and sends an event message to the robot controller when surface deformation is detected. In comparison with other methods, the obtained results reveal that our visual pipeline does not use deformations models of objects and materials, as well as the approach works well both planar and 3D household objects in real time. In addition, our method does not depend on the pose of the robot hand because the location of the reference system is computed from a recognition process of a pattern located place at the robot forearm. The presented experiments demonstrate that the proposed method accomplishes a good monitoring of grasping task with several objects and different grasping configurations in indoor environments.

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Since the beginning of 3D computer vision problems, the use of techniques to reduce the data to make it treatable preserving the important aspects of the scene has been necessary. Currently, with the new low-cost RGB-D sensors, which provide a stream of color and 3D data of approximately 30 frames per second, this is getting more relevance. Many applications make use of these sensors and need a preprocessing to downsample the data in order to either reduce the processing time or improve the data (e.g., reducing noise or enhancing the important features). In this paper, we present a comparison of different downsampling techniques which are based on different principles. Concretely, five different downsampling methods are included: a bilinear-based method, a normal-based, a color-based, a combination of the normal and color-based samplings, and a growing neural gas (GNG)-based approach. For the comparison, two different models have been used acquired with the Blensor software. Moreover, to evaluate the effect of the downsampling in a real application, a 3D non-rigid registration is performed with the data sampled. From the experimentation we can conclude that depending on the purpose of the application some kernels of the sampling methods can improve drastically the results. Bilinear- and GNG-based methods provide homogeneous point clouds, but color-based and normal-based provide datasets with higher density of points in areas with specific features. In the non-rigid application, if a color-based sampled point cloud is used, it is possible to properly register two datasets for cases where intensity data are relevant in the model and outperform the results if only a homogeneous sampling is used.