The envirome and the connectome: exploring the structural noise in the human brain associated with socioeconomic deprivation

Complex cognitive functions are widely recognized to be the result of a number of brain regions working together as large-scale networks. Recently, complex network analysis has been used to characterize various structural properties of the large scale network organization of the brain. For example, the human brain has been found to have a modular architecture i.e. regions within the network form communities (modules) with more connections between regions within the community compared to regions outside it. The aim of this study was to examine the modular and overlapping modular architecture of the brain networks using complex network analysis. We also examined the association between neighborhood level deprivation and brain network structure – modularity and grey nodes. We compared network structure derived from anatomical MRI scans of 42 middle-aged neurologically healthy men from the least (LD) and the most deprived (MD) neighborhoods of Glasgow with their corresponding random networks. Cortical morphological covariance networks were constructed from the cortical thickness derived from the MRI scans of the brain. For a given modularity threshold, networks derived from the MD group showed similar number of modules compared to their corresponding random networks, while networks derived from the LD group had more modules compared to their corresponding random networks. The MD group also had fewer grey nodes – a measure of overlapping modular structure. These results suggest that apparent structural difference in brain networks may be driven by differences in cortical thicknesses between groups. This demonstrates a structural organization that is consistent with a system that is less robust and less efficient in information processing. These findings provide some evidence of the relationship between socioeconomic deprivation and brain network topology

Dense urban elevation models from stereo images by an affine region merging approach

The main subject of this thesis is the computation of Dense Disparity Maps from a pair of satelite or aerial stereo images from an urban scene, taken from two different viewpoints. Several steps are needed to obtain the ?nal disparity map from the pair of images. We focus here on one of these steps: how to match the points in one image with the points in the other one. This matching process is closely related to the computation of the altitudes of the objects present in the scene. Indeed, the precision we can obtain in these altitude values is directly proportional to the precision in the matching process. This precision in the altitude is also inversely proportional to the distance between both viewpoints where the images are taken(baseline). The matching process is a widely studied ?eld in the Computer Vision Community and several methods and algorithms have been developed so far ([31, 27, 49]). Most of them consider a big base- line con?guration, which increases the performance in the altitude and also simpli?es the matching process. However, this assumption presents a major drawback with objects that are occluded in one image but appear in the other one. The bigger the baseline is, the more objects are occluded in one image and are not occluded in the other one. Recently, a different approach in which the images are taken with a very small baseline started to be analyzed ([19, 20]). This approach has the advantage of eliminating most of the ambiguities presented when one object occluded in one image is not occluded in the other one. Indeed, if we consider that we have a very small baseline, the occlusions presented in both images are almost the same. Now, this con?guration obviously decreases the precision in the ?nal altitude. In order to continue obtaining highly accurate altitude values, the precision in the matching process must be im- proved. The methods developed so far which consider the small baseline approach, compute altitude values with a high precision at some points, but leave the rest of them with no altitude values at all, generating a non-dense disparity map. Based on the fact that piecewise-a?ne models are reasonable for the elevation in urban areas, we propose a new method to interpolate and denoise those non-dense disparity maps. Under lambertian illumination hypothesis 1 , it is reasonable to assume that homogeneous regions in the graylevel image, correspond to the same a?ne elevation model. In other words, the borders between the piecewise a?ne elevation model are included to a large extent within contrasted graylevel borders. Hence, it is reasonable to look for an piecewise a?ne ?t to the elevation model where the borders between regions are taken from a graylevel segmenation of the image We present a region-merging algorithm that starts with an over-segmentation of the gray-level im- age. The disparity values at each region are approximated by an a?ne model, and a meaningfulness measure of the ?t is assigned to each of them. Using this meaningfulness as a merging order, the method iterates until no new merge is possible, according to a merging criterion which is also based on the meaningfulness of each pair of neighboring regions. In the last step, the algorithm performs a validation of the ?nal regions using again the meaningfulness of the ?t. The regions validated in this last step are those for which the a?ne model is a good approximation. The region-merging algorithm presented in this work can be seen as an attempt to incorporate a semantical meaning to real scenes: we have developed a validation method to determine whether the data within a region is well approximated by an a?ne model or not. Hence, we could analyze more complex models, de?ning a suitable validation criterion for each of them. In this way, we can search for the model that best explains a given data set in terms of its meaningfulness

Leadership Styles among Genders of Retail Managers

Themes that affect leadership have long aroused the interest of the academic community, especially regarding the categorization of the diverse forms of exercising this position and the impacts of these differences on the organizational environment. In this perspective, the interfering elements in the formation of the leader's style profile are also relevant, as the workforce is increasingly heterogeneous in terms of race, ethnicity, gender and other culturally diverse groups. However, segmentation of leadership styles is still observed exclusively by gender, which may give rise to spaces for the practice of prejudices and discrimination. In view of this, this work aims to identify the significant differences of styles of leadership between genders in the retail trade. To do so, a quantitative approach was carried out with a sample of 100 managers, male and female, self-reported by the participants, using the MLQ questionnaire from Bass, corroborated widely in several countries and populations. Data were treated using descriptive frequency statistics, as well as the Cronbach Alpha tests for reliability analysis, Confirmatory Factor Analysis for validity, and the T-Test for independent samples. The results indicate that the female gender has greater presence of the transformational leadership trait and the additional factors (extra effort, efficacy and satisfaction); and the transactional leadership styles and Laissez-Faire did not present significant difference of presence between the genders. Finally, this research demonstrates that there is evidence that scale is appropriate for different organizational cultures

Rooted America: Immobility and Segregation of the Inter-county Migration Networks

Despite the popular narrative that the United States is a "land of mobility," the country may have become a ``rooted America'' after a decades-long decline in migration rates. This paper interrogates the lingering question about the social forces that limit migration, with the empirical focus on the internal migration in the United States. We propose a systemic, network model of migration flows, combining demographic, economic, political, geographical factors and network dependence structures that reflect the internal dynamics of migration systems. Using valued temporal exponential-family random graph models, we model the network of inter-county migration flows during the 2011-2015 period. Our analysis reveals a pattern of "segmented immobility," where fewer people migrate between counties with dissimilar political contexts, levels of urbanization, and racial compositions. Probing our model using "knockout experiments" suggests that one would have observed approximately 4.6 million (27%) more inter-county migrants each year were the segmented immobility mechanisms inoperative. The paper offers a systemic view of internal migration and reveals the social and political cleavages that underlie geographical immobility in America

The Digitalization of Seniors: Analyzing the Multiple Confluence of Social and Spatial Divides

The lower digitization among seniors must be understood in the context of the coming together of multiple digital divides. In addition to the obvious generation divide (age is one of the factors most determining digital uses), others also have an influence, such as a lower education or income level, which is characteristic of this group and also strongly correlated with lower use of new technologies. We also find gender differences in the digital uses of seniors (more pronounced than in the population as a whole) and a significant geospatial inequality in several variables. The latter is important due to both the rapid aging of the rural population, greater than that seen in the urban population, and the fact that the geographical areas with a lower income level, where the aging population tends to be concentrated to a greater extent, are also the areas where digitization reaches the least, in terms of both infrastructures and uses. This article addresses the multiconfluence of the aforementioned “digital divides in older people” (or “seniors”), trying to determine the effects and degree of importance of each, identify the main groups at risk of digital exclusion, and to characterize the technological uses of seniors and their main segments. To do this, we have used the microdata from the “Survey on Equipment and Use of Information and Communication Technologies in homes”, produced by the Spanish Statistical Office (INE) for the year 2020.Fac. de Ciencias Políticas y SociologíaTRUEpu

Novel pattern recognition methods for classification and detection in remote sensing and power generation applications

Novel pattern recognition methods for classification and detection in remote sensing and power generation application

Analysis of Lisbon visitors’ internet access behavior: behavior analysis through the identification of clusters

Project Work presented as the partial requirement for obtaining a Master's degree in Data Driven Marketing, specialization in Marketing IntelligenceThis master's thesis focuses on clustering the internet access behavior of urban visitors in the Lisbon urban area. To promote smart city development, the study aims to provide insights into visitors' behaviors while accessing the internet in Lisbon, enabling improved decision-making processes for city management, and enhancing the overall online and offline experience for visitors. The over-tourism phenomenon has put a strain on infrastructure, public transportation, and cultural heritage sites. Therefore, innovative methods are needed for effective smart city management, particularly in urban mobility. The increasing availability of Wi-Fi networks during travel has generated valuable data that can be used to develop groundbreaking approaches to understanding visitors’ behaviors and mobility patterns in urban areas. This knowledge enables the analysis and clustering of urban visitors' behavior, contributing to improved decision-making processes in smart city management