Aspects of Romanian Palaeozoic Palaeobotany and Palynology. Part III. The Late Carboniferous flora of Baia Nouă, Sirinia Basin

The Cucuiova Formation is a Pennsylvanian (late Carboniferous) coal-bearing unit in the intramontane Sirinia Basin, which was formed in the Danubian Units of the South Carpathians. The main coal seam in the Cucuiova Formation was worked at Baia Nouă (Nové Doly) and this locality has yielded a typical adpression coal flora. Previous studies have suggested that this flora was Moscovian (late Westphalian or even earliest Stephanian) in age. However, newly collected samples from Baia Nouă have included abundant Neuralethopteris, which clearly indicates a late Bashkirian (Langsettian) age. This suggests a possible link with the Svoge Basin in northern Bulgaria, which is another intramontane basin located on the Balkan Terrane with early Westphalian coal-bearing deposits.</p

Plataforma basada en redes neuronales para realizar pruebas de autenticación de usuarios mediante datos de ponibles

Durante esta última década la Inteligencia Artificial (IA) y más concretamente el aprendizaje profundo basado en redes neuronales se han convertido en un estándar en varios sectores que afectan diferentes campos de nuestra vida. Estos son capaces de resolver problemas complejos que requieren encontrar pa-trones ocultos en los datos que tratan. La identificación es la capacidad de identificar de forma exclusiva a un usuario de un sistema o una aplica-ción que se está ejecutando en el sistema. Estos modelos tienen la capacidad de identificar a los usuarios mediante los datos ponibles que recogen. Los datos ponibles en nuestro caso hacen referencia a los datos que recogen los relojes inteligentes y mediante los cuales se puede identificar al usuario según sus patro-nes. Debido a la amplia funcionalidad que ofrecen, es necesario probar ampliamente las distintas configu-raciones y capacidades que ofrecen. En este trabajo se propone una plataforma basada en redes neuronales capaz de realizar pruebas de autenticación de usuarios mediante datos de ponibles. En particular, se ha creado un framework o estructura que permite al usuario probar las diferentes funcionalidades que ofrece los modelos de aprendizaje profundo. En concreto, la plataforma permite la selección de dos tipos de mo-delos, un prototipo de Red Neuronal Artificial (ANN) como es el Perceptrón Multicapa (MLP) y un prototipo de Aprendizaje Profundo basado en Redes Neuronales Convolucionales (CNN).During this last decade, Artificial Intelligence (AI) and more specifically deep learning based on neural networks have become a standard in various sectors that affect different fields of our lives. These are ca-pable of solving complex problems that require finding hidden patterns in the data they deal with. Identification is the ability to uniquely identify a user of a system or an application running on the sys-tem. These models have the ability to identify users through the wearable data they collect. Wearable data refers to data that smart watches collect and through which the user can be identified based on their pat-terns. These models are capable of diagnosing cancer prematurely or proposing better eating habits. Due to the extensive functionality they offer, it is necessary to extensively test the various features and capabi-lities they offer. In this work, is proposed a platform based on neural networks capable of performing user authentication tests using wearable data. In particular, a has been created that allows the user to test the different functionalities offered by deep learning models. Specifically, the platform allows the selection of two types of models, an Artificial Neural Network (ANN) prototype such as the Multilayer Perceptron (MLP) and a Deep Learning prototype based on Convolutional Neural Networks (CNN).Departamento de Informática (Arquitectura y Tecnología de Computadores, Ciencias de la Computación e Inteligencia Artificial, Lenguajes y Sistemas Informáticos)Grado en Ingeniería Informátic

The use of geophysical methods in the study of tree roots in an urban environment

Near-surface geophysics has been increasingly applied to more and more environments, thanks to the development of both equipment and available software. As a result, non-destructive geophysical surveys in urban areas are increasingly used to solve a great deal of varied problems. Trees provide valuable and important environmental services and play an important role in the livelihoods of humans and animals alike. However, although trees have been researched extensively, roots remain an area that is notoriously difficult to understand. Hence, robust geophysical surveys might provide an array of useful information regarding the location, size, and overall structure of tree roots, with very few practical downsides. This thesis works at the junction of several disciplines, bringing them together in a cohesive and practical manner. The investigation focuses on two geophysical methods (GPR and geoelectrical surveying), presenting relevant surveys as well as forward models that aid survey design and data interpretation. The models also revealed why sometimes surveys are unsuccessful (or partly unsuccessful) and what can be done to maximize the odds of success. The results show that while this task is challenging and site-specific, it is possible to study tree roots in an urban context with geophysical methods

Economic stratification - The remedy and demise of humanity

The paper shows that the world economic stratification, as well as that of all natural, social and political systems is a natural law and a prerequisite for progress. Stratification itself may mean, however, both the remedy, but also the demise of systems, by exacerbating social inequalities. The database includes the evolution of gross domestic product per capita for different time frames at European level and worldwide. The main methods employed in processing database are the indices method and expectation values of position (quartile values) used to assess the structure of Europe and world countries according to the size of the gross domestic product. In Europe, for a century, stratification has increased visibly. If in 1913, the richest country in Europe achieved a GDP per capita of 3.94 times higher compared to the poorest country, in 2013 the ratio is 13.82 to one. The status of key statistical indicators that characterize the polarization of the world by size of gross domestic product, demonstrates that stratification is less pronounced inside continents, becoming however severe, worldwide. In this regard, it is alarming that in 1994, 75% of world countries were making only 7% of the GDP per capita in the richest country (Monaco). Given that information has now become increasingly more fluid, one can include among beneficiaries, the least developed countries. Circulation of information is, however, under the command of polarizing forces, belonging to the same great powers of the world. In this way, by means of more refined methods, the benefits of progress preserve world hierarchies

Clear cell urothelial carcinoma of the urinary bladder - a rare pathological entity. A case report and a systematic review of the literature

The most common histological type of urinary bladder cancer is urothelial carcinoma (UC). In contrast, the clear cell variant of urothelial carcinoma (CCUC) is quite a rare neoplasm. In this study, we report a case of an 81-year-old male, presenting with gross hematuria and acute urinary retention, which was subsequently diagnosed with CCUC at our pathology department. Furthermore, we provide a short systematic review of the literature (PubMed, Scopus, Science Citation Index) for this rare histopathological entity and a brief discussion about its morphological and immunohistochemical (IHC) characteristics

A quantitative approach for identifying plant ecogroups in the Romanian Early Jurassic terrestrial vegetation

Community level ecology is considered to support significantly the recognition of the ecological status of plant taxa and the identification of plant ecogroups, thus it generally provides extended data sets on the spatial and temporal changes of ecological factors. Since research based exclusively on plant structure and their supposed adaptation to the environment is now considered inadequate, statistical methods can be used. Assuming that co-occurrence of plant fossils on a single hand specimen in the case of autochthonous or parautochthonous floras is the result of their growth in the same phytocenosis, quantitative ecological analysis on Mesozoic materials would yield significant insights. In this paper, statistical and multivariate quantitative analyses of Early Jurassic plant fossil records from the Steierdorf Formation in Anina (South Carpathians, Romania) are presented. Four palaeoecological groups of taxa were distinguished by principal component analysis (PCA) and interpreted as plant assemblages of various palaeobiotopes associated with the sedimentary facies of the enclosing formation. A group of samples was analysed using the principal coordinate (PCO) method and the statistical significance (p {less than or equal to} 0.05) (p ≤ 0.05) of individual binary responses of taxa along the first two PCO ordination axes was tested by general linear model (GLM). They revealed putative palaeoecological gradients: axis 1 - disturbance caused by water level fluctuations, axis 2 - temperature, corresponding with the already assumed environmental and climatic change at the Hettangian/Sinemurian boundary. Multivariate analyses enabled the identification of palaeoecological groups and thus inferring palaeogeographical conditions based on Mesozoic materials. © 2016 Elsevier B.V