Explore the vast range of titles available.

Placement in prestigious research institutions for STEM (science, technology, engineering, and mathematics) PhD recipients is generally considered to be optimal. Yet some doctoral recipients are not interested in intensive research careers and instead seek alternative careers, outside but also within academe (for example teaching positions in Liberal Arts Schools). Recent attention to non-academic pathways has expanded our understanding of alternative PhD careers. However, career preferences and placements are also nuanced along the academic pathway. Existing research on academic careers (mostly research-centric) has found that certain factors have a significant impact on the prestige of both the institutional placement and the salary of PhD recipients. We understand less, however, about the functioning of career preferences and related placements outside of the top academic research institutions. Our work builds on prior studies of academic career placement to explore the impact that prestige of PhD-granting institution, advisor involvement, and cultural capital have on the extent to which STEM PhDs are placed in their preferred academic institution types. What determines whether an individual with a preference for research oriented institutions works at a Research Extensive university? Or whether an individual with a preference for teaching works at a Liberal Arts college? Using survey data from a nationally representative sample of faculty in biology, biochemistry, civil engineering and mathematics at four different Carnegie Classified institution types (Research Extensive, Research Intensive, Master's I & II, and Liberal Arts Colleges), we examine the relative weight of different individual and institutional characteristics on institutional type placement. We find that doctoral institutional prestige plays a significant role in matching individuals with their preferred institutional type, but that advisor involvement only has an impact on those with a preference for research oriented institutions. Gender effects are also observed, particularly in the role of the advisor in affecting preferred career placement.

Background In the pursuit of a better understanding of biodiversity, evolutionary biologists rely on the study of phylogenetic relationships to illustrate the course of evolution. The relationships among natural organisms, depicted in the shape of phylogenetic trees, not only help to understand evolutionary history but also have a wide range of additional applications in science. One of the most challenging problems that arise when building phylogenetic trees is the presence of missing biological data. More specifically, the possibility of inferring wrong phylogenetic trees increases proportionally to the amount of missing values in the input data. Although there are methods proposed to deal with this issue, their applicability and accuracy is often restricted by different constraints. Results We propose a framework, called PhyloMissForest, to impute missing entries in phylogenetic distance matrices and infer accurate evolutionary relationships. PhyloMissForest is built upon a random forest structure that infers the missing entries of the input data, based on the known parts of it. PhyloMissForest contributes with a robust and configurable framework that incorporates multiple search strategies and machine learning, complemented by phylogenetic techniques, to provide a more accurate inference of lost phylogenetic distances. We evaluate our framework by examining three real-world datasets, two DNA-based sequence alignments and one containing amino acid data, and two additional instances with simulated DNA data. Moreover, we follow a design of experiments methodology to define the hyperparameter values of our algorithm, which is a concise method, preferable in comparison to the well-known exhaustive parameters search. By varying the percentages of missing data from 5% to 60%, we generally outperform the state-of-the-art alternative imputation techniques in the tests conducted on real DNA data. In addition, significant improvements in execution time are observed for the amino acid instance. The results observed on simulated data also denote the attainment of improved imputations when dealing with large percentages of missing data. Conclusions By merging multiple search strategies, machine learning, and phylogenetic techniques, PhyloMissForest provides a highly customizable and robust framework for phylogenetic missing data imputation, with significant topological accuracy and effective speedups over the state of the art.

The objective of this paper is to understand what sovereign and country risk ratings actually measure. These ratings were created by key financial agencies to serve as a way of guiding a significant part of investment in developing nations. Theoretically, this project deals with one of the key debates in the social sciences: Are markets rational and efficient, or does uncertainty lead to the adoption of certain measures and policies because they are culturally and politically legitimate? To answer this question, this paper employs quantitative analyses, looking at both the factors that lead a country to be rated and what drives the ratings themselves. More specifically, I use different statistical techniques to show that the risk ratings are not driven solely by market factors but rather measure compliance with the existing neoliberal paradigm, such as financial deregulation and privatization. They are measures of compliance with the existing policy paradigm and fail to adequately capture investment risk. As such, they play a key role in the adoption of neoliberal policies even in the face of financial crises worldwide, especially in the Global South, as is the case with Latin America studied here.

The objective of this work was to evaluate the kinetics and mineralization fraction of organic matter from sewage sludge mixed with the soil under controlled laboratory conditions. For this, organic material samples accumulated in layers 0–5 cm, 5–10 cm and 10–15 cm in relation to the surface of a vertical flow constructed wetland system (VF-CW) used for treatment of septic tank sludge, in addition to samples of dewatered sludge from a septic tank and a UASB reactor and non-dewatered sludge from an anaerobic digester were mixed with material collected from the surface layer of a Red Yellow Argisol at rates equivalent to the applications, via organic residues, of 300 and 600 kg ha −1  year −1 of total nitrogen. It was found that the two-phase kinetic equation fit better to the mineralization data of labile and recalcitrant organic carbon. For the lowest nitrogen application rate in the mixtures, the mineralization fractions of the total organic carbon were higher than 73%, while at the highest dose there was a reduction in the mineralization of organic matter by 17% and 63%, respectively in samples collected in layer 10–15 cm from the VF-CW and in the septic tank sludge dewatered in the drying bed.

Ever since Anderson’s seminal work [1], the study of localization properties in quantum systems has been recognized to be best performed through a statistical analysis of local physical quantities. The Local Density of States (LDoS) is a perfect candidate for it is one of the simplest observable one can build and, furthermore, it can be measured experimentally with Scanning Tunneling Microscope (STM) techniques [2]. In 1D and quasi1D/2D systems, earlier analytical studies have been conducted by Altshuler et. al. [3] and Mirlin et. al. [4], respectively. In general, it was widely shown that the distribution of the LDoS follows a Log-Normal when disorder is present. At the Anderson transition from Metal-to-Anderson Insulator, the distribution undergoes a distinct change from Normal to a Log-Normal. On the numerical side, Schubert et. al. [5] performed calculations of this distribution with the Kernel Polynomial Method (KPM) technique [6] and also sees the emergence of this change of the distributions on the Anderson transition and that it can be used to identify the presence of extended/localized regimes.This thesis is devoted to the investigation of the role of disorder and Anderson localization in the statistical properties of the local density of states of lattice systems. In order to perform this study, a new set of numerical methods are introduced allowing the evaluation of the LDoS with an efficiency hitherto unseen in the literature. The Kernel Polynomial Method is a numerical method with linear complexity in the size of the system, i.e O (L). The study of these distributions requires the accumulation of many LDoS points throughout the lattice, and thus, the effective computational complexity of the numerical method is elevated to O (L2). Given this, we present a new method to circumvent this problem inspired by the ideas behind the stochastic computation of traces of operators []. We effectively create a novel method to compute the LDoS across the entire lattice in linear time, O(L).Moreover, recent advance in the use of Graphics Processing Units (GPUs) with the Kernel Polynomial Method [7] have drawn our attention. We revisit this topic and develop a brand new and original software programmed in CUDA that can take best advantage of the most recent Nvidia GPUs. With this we are able to personalize it to maximize the performance, resulting in a software capable of running the KPM hundreds of times faster than a CPU-based implementation.By combining our new linear-scaling method for computing LDoS across the lattice with GPU-accelerated software, we are able to obtain the statistics of the LDoS in unprecedented scale. With this, we examined the one-dimensional systems and employing the findings of Altshuler et al. [3] as a benchmark for a comprehensive study. Additionally, we explored the interplay among the parameters governing the simulation of the onedimensional system and established the presence of an effective length and a crucial parameter for ensuring the robust convergence of the LDoS statistics.This breakthroughs not only advances the field but also has promising implications for future research. With the ease of obtaining LDoS statistics, we could study other special systems, such as the Weyl Semimetals where the transition from Semimetal-to-Metal is an open problem and begs the use of LDoS distributions to properly comprehend it.

RESUMO No presente artigo, focalizamos um tipo específico de repetição saliente nos discursos políticos de campanha de Fernando Collor de Mello quando das eleições presidenciais de 1989: os paralelismos sintáticos. A partir de um olhar qualitativo e interpretativo para esse fenômeno, e apoiados pela Teoria da Mesclagem Conceptual (FAUCONNIER; TURNER, 2002), investigamos as funções des s a estratégia em um corpus constituído pelos três primeiros programas eleitorais levados ao ar pelo então candidato. Nossa análise sugere que os paralelismos sintáticos desempenham duas funções argumentativas importantes: de um lado, acionam um processo de recategorização de entidades conceptuais/discursivas; de outro, permitem apresentar o resultado desse processo como informação pressuposta, minimizando as chances de refutação e invisibilizando a perspectiva ideológica do que é dito. Essa lente cognitiva para os processos de construção de sentido nos permite mostrar os modos como a performance do ex-presidente atualiza certos lemas da comunicação de massa, aproximando os campos da política e do entretenimento. ABSTRACT FAUCONNIER; TURNER, 2002

This thesis, developed in collaboration with Tekever, a leading Portuguese company in unmanned aerial systems (UAS), focuses on the structural design and optimization of the tail and boom components of the ARX, Tekever’s future UAV, with a focus on versatile missions, including ISAR operations and cargo transportation, with an expected launch in 2025. The main objective of this research is to design a lightweight and structurally robust tail and boom system, in compliance with ASTM F3116-18 standards, while simultaneously optimizing operational efficiency and performance using heuristic optimization tools. Additionally, the project aims to validate and improve in terms of computational efficiency a heuristic algorithm optimization tool initiated in the 2022/2023 academic year to predict the minimum number of layers and the optimal fiber orientations for the composite material used in the critical points of the Tail boom structure developed for the ARX seeking better performance and structural optimization. The tool is based on a unique evolutionary algorithm to explore the search space, with limits based on Hashin matrix and fiber failure indices. To accommodate these limitations, a surrogate model was developed, combining the Abaqus finite element program and Python, building the training data for the surrogate model using the Latin hypercube sampling technique and a Gaussian regression model. As a final phase, it was possible to obtain an approximate 73% computational efficiency over the initial tool, through the fine-tuning of the genetic algorithm and Gaussian regression, greater flexibility in applying the tool to complex cases after direct implementation of .Cae files and an improved condition of the failure criterion and studying the application of LAr05 and Hashin criteria, culminating in an ARX tail boom structure 14% lighter than the initial reference. Overall, this research not only advances the structural design of Tekever’s ARX but also contributes to the broader field of UAV development by demonstrating effective methodologies for lightweight, high-performance aerostructure optimization.

As Terras Pretas Arqueológicas (TPA) são solos que podem concentrar até seis vezes mais carbono orgânico que solos adjacentes sem horizonte A antrópico, presumindo-se, dessa forma, maior efluxo de CO2 nesses solos. O objetivo deste estudo foi investigar a distribuição espacial do efluxo de CO2, temperatura e umidade do solo em área de Terra Preta Arqueológica sob cultivo de cacau e café no município de Apuí, AM, Brasil. Foram construídas malhas amostrais nas dimensões 42 x 80 m, com espaço entre os pontos de 8 x 10 m e 6 x 10 m para as áreas de cacau e café, respectivamente. Após a etapa de coleta dos dados do efluxo de CO2, temperatura e umidade do solo, procedeu-se a análise estatística descritiva e geoestatística. Os resultados mostraram que os parâmetros avaliados apresentam dependência espacial, com alcance variando de 25 a 40 m para o efluxo de CO2 da área TPA com cacau. O efluxo de CO2 na área de cacau foi superior, com valor médio de 5,49 µmol m 2 s-1, comparado ao 3,99 µmol m-2 s-1 de CO2 da área com café.

This article focuses on a specific type of repetition that turns out to be particularly frequent in the political speeches delivered by Fernando Collor de Mello during the 1989 presidential campaign in Brazil: syntactic parallelisms. By adopting a qualitative and interpretive perspective on the phenomenon, we use the framework of Conceptual Blending Theory (FAUCONNIER; TURNER, 2002) to investigate the functions of this strategy in a corpus constituted by the first three electoral programs aired by the candidate. Our analysis suggests that syntactic parallelisms play two important argumentative roles: on the one hand, they trigger a process of recategorization of conceptual/discursive entities; on the other hand, they allow the speaker to present the result of this process as backgrounded information, thus reducing the likelihood of rebuttal and making underlying ideology invisible. By using such cognitive lens to look into meaning-making processes, we show how the former president's performances manifest certain premises of mass communication, bringing closer together the fields of politics and entertainment.KEYWORDS: Political Discourse. Syntatic Parallelism. Conceptual Blending. Mass Media. Fernando Collor.No presente artigo, focalizamos um tipo especifico de repeticao saliente nos discursos politicos de campanha de Fernando Collor de Mello quando das eleicoes presidenciais de 1989: os paralelismos sintaticos. A partir de um olhar qualitativo e interpretativo para esse fenomeno, e apoiados pela Teoria da Mesclagem Conceptual (FAUCONNIER; TURNER, 2002), investigamos as funcoes dessa estrategia em um corpus constituido pelos tres primeiros programas eleitorais levados ao ar pelo entao candidato. Nossa analise sugere que os paralelismos sintaticos desempenham duas funcoes argumentativas importantes: de um lado, acionam um processo de recategorizacao de entidades conceptuais/discursivas; de outro, permitem apresentar o resultado desse processo como informacao pressuposta, minimizando as chances de refutacao e invisibilizando a perspectiva ideologica do que e dito. Essa lente cognitiva para os processos de construcao de sentido nos permite mostrar os modos como a performance do ex-presidente atualiza certos lemas da comunicacao de massa, aproximando os campos da politica e do entretenimento.PALAVRAS-CHAVE: Discurso Politico. Paralelismo Sintatico. Mesclagem Conceptual. Comunicacao de Massa. Fernando Collor.

This article focuses on a specific type of repetition that turns out to be particularly frequent in the political speeches delivered by Fernando Collor de Mello during the 1989 presidential campaign in Brazil: syntactic parallelisms. By adopting a qualitative and interpretive perspective on the phenomenon, we use the framework of Conceptual Blending Theory (FAUCONNIER; TURNER, 2002) to investigate the functions of this strategy in a corpus constituted by the first three electoral programs aired by the candidate. Our analysis suggests that syntactic parallelisms play two important argumentative roles: on the one hand, they trigger a process of recategorization of conceptual/discursive entities; on the other hand, they allow the speaker to present the result of this process as backgrounded information, thus reducing the likelihood of rebuttal and making underlying ideology invisible. By using such cognitive lens to look into meaning-making processes, we show how the former president's performances manifest certain premises of mass communication, bringing closer together the fields of politics and entertainment.