Geotechnical evaluation of rocks and soils in Catoca kimberlitic mining complex (Angola)

Landslides and rock sliding occur very frequently in the mining area of Catoca, located in Angola. Therefore, a physical/mechanical and geotechnical characterization of the massif and the rock matrix was carried out adopting the landslide classifications as proposed by Hutchinson and Varnes. The safety factor was applied based on the structural weakness coefficient (λ); resulting in 0.70 in surface rocks, sandstones and intraformational sands; 0.58 in oversaturated eluvial gneiss; 0.50 in cracked gneiss and 0.47 in the ore compound of weathered, moist kimberlitic porphyric and weathered porphyric kimberlite. These results indicate the low strength of the massif and the need to reformulate the activities in the mine and the construction of more stable slopes. It could also be observed that deformation of rocks in the slopes and the cuts in the Catoca mine is conditioned by the movement of underground water within the rock massif itself

Os diplomados em Ciências da Documentação e Informação da Faculdade de Letras da Universidade de Lisboa: Empregabilidade 2008-2017

Objetivo: O objectivo do presente trabalho é analisar a empregabilidade dos diplomados do Mestrado em Ciências da Documentação e Informação da Universidade de Lisboa. Metodología: O presente estudo, como qualquer estudo de índole científica, assenta numa metodologia de investigação que nos permite apresentar resultados válidos e legitima o próprio trabalho. Neste sentido, o trabalho foi realizado completando as seguintes fases (Quivy & Campenhoudt, 1992): Elaboração da Pergunta de partida; Revisão da Literatura; Problematização; Instrumento de Análise; Recolha de Dados; e Análise dos Dados. É, ainda, um estudo exploratório de natureza qualitativa e quantitativa, suportado, sobretudo na revisão da literatura, pelo método de pesquisa documental (Saint-Georges, 1997:15). Resultados: Em termos absolutos, os valores da empregabilidade apresentados nos três momentos que foram inquiridos – à data de candidatura, à data de conclusão e atualmente, são de, respetivamente, 83%, 82% e 87%. Estes valores são ainda firmados pelo facto de 65% dos adjetivos utilizados sobre a formação do Mestrado ser: boa, abrangente, interessante, pertinente, atual, excelente, relevante, diversificada, prática, útil, enriquecedora, científica, eficiente, fundamental e rigorosa. Em suma, o presente estudo evidencia uma elevada empregabilidade dos diplomados em Ciências da Documentação e Informação pela Faculdade de Letras da Universidade de Lisboa, entre 2008 e 2017.info:eu-repo/semantics/draf

A empregabilidade como fator da sustentabilidade: os diplomados em Ciências da Documentação e Informação pela Faculdade de Letras da Universidade de Lisboa

O objetivo do presente trabalho é analisar a empregabilidade dos diplomados do Mestrado em Ciências da Documentação e Informação da Universidade de Lisboa. O presente estudo, como qualquer estudo de índole científica, assenta numa metodologia de investigação que nos permite apresentar resultados válidos e legitima o próprio trabalho. Neste sentido, o trabalho foi realizado completando as seguintes fases (Quivy & Campenhoudt, 1992): Elaboração da Pergunta de partida; Revisão da Literatura; Problematização; Instrumento de Análise; Recolha de Dados; e Análise dos Dados. É, ainda, um estudo exploratório de natureza qualitativa e quantitativa, suportado, sobretudo na revisão da literatura, pelo método de pesquisa documental (Saint-Georges, 1997:15).Objective: The objective of this work is to analyze the employability of graduates of the Master in Documentation and Information Sciences at the University of Lisbon. Methodology: The present study, like any study of a scientific nature, is based on a research methodology that allows us to present valid results and legitimizes the work itself. In this sense, the work was carried out completing the following phases (Quivy & Campenhoudt, 1992): Elaboration of the starting question; Literature revision; Problematization; Analysis Instrument; Data collection; and Data Analysis. It is also an exploratory study of a qualitative and quantitative nature, supported, above all, in the literature review, by the documentary research method (Saint-Georges, 1997:15).info:eu-repo/semantics/publishedVersio

In situ readout of DNA barcodes and single base edits facilitated by in vitro transcription

Molecular barcoding technologies that uniquely identify single cells are hampered by limitations in barcode measurement. Readout by sequencing does not preserve the spatial organization of cells in tissues, whereas imaging methods preserve spatial structure but are less sensitive to barcode sequence. Here we introduce a system for image-based readout of short (20-base-pair) DNA barcodes. In this system, called Zombie, phage RNA polymerases transcribe engineered barcodes in fixed cells. The resulting RNA is subsequently detected by fluorescent in situ hybridization. Using competing match and mismatch probes, Zombie can accurately discriminate single-nucleotide differences in the barcodes. This method allows in situ readout of dense combinatorial barcode libraries and single-base mutations produced by CRISPR base editors without requiring barcode expression in live cells. Zombie functions across diverse contexts, including cell culture, chick embryos and adult mouse brain tissue. The ability to sensitively read out compact and diverse DNA barcodes by imaging will facilitate a broad range of barcoding and genomic recording strategies

Subdiffusion and heat transport in a tilted 2D Fermi-Hubbard system

Using quantum gas microscopy we study the late-time effective hydrodynamics of an isolated cold-atom Fermi-Hubbard system subject to an external linear potential (a "tilt"). The tilt is along one of the principal directions of the two-dimensional (2D) square lattice and couples mass transport to local heating through energy conservation. We study transport and thermalization in our system by observing the decay of prepared initial density waves as a function of wavelength $\lambda$ and tilt strength and find that the associated decay time $\tau$ crosses over as the tilt strength is increased from characteristically diffusive to subdiffusive with $\tau\propto\lambda^4$. In order to explain the underlying physics we develop a hydrodynamic model that exhibits this crossover. For strong tilts, the subdiffusive transport rate is set by a thermal diffusivity, which we are thus able to measure as a function of tilt in this regime. We further support our understanding by probing the local inverse temperature of the system at strong tilts, finding good agreement with our theoretical predictions. Finally, we discuss the relation of the strongly tilted limit of our system to recently studied 1D models which may exhibit nonergodic dynamics.Comment: 7 pages with 5 figures in main text, 5 pages with 3 figures in Supplemental Materia

Visualizing Strange Metallic Correlations in the 2D Fermi-Hubbard Model with AI

Strongly correlated phases of matter are often described in terms of straightforward electronic patterns. This has so far been the basis for studying the Fermi-Hubbard model realized with ultracold atoms. Here, we show that artificial intelligence (AI) can provide an unbiased alternative to this paradigm for phases with subtle, or even unknown, patterns. Long- and short-range spin correlations spontaneously emerge in filters of a convolutional neural network trained on snapshots of single atomic species. In the less well-understood strange metallic phase of the model, we find that a more complex network trained on snapshots of local moments produces an effective order parameter for the non-Fermi-liquid behavior. Our technique can be employed to characterize correlations unique to other phases with no obvious order parameters or signatures in projective measurements, and has implications for science discovery through AI beyond strongly correlated systems.Comment: 12 pages, 9 figures; updated in accord with the published versio

Visualizing strange metallic correlations in the two-dimensional Fermi-Hubbard model with artificial intelligence

Strongly correlated phases of matter are often described in terms of straightforward electronic patterns. This has so far been the basis for studying the Fermi-Hubbard model realized with ultracold atoms. Here, we show that artificial intelligence (AI) can provide an unbiased alternative to this paradigm for phases with subtle, or even unknown, patterns. Long- A nd short-range spin correlations spontaneously emerge in filters of a convolutional neural network trained on snapshots of single atomic species. In the less well-understood strange metallic phase of the model, we find that a more complex network trained on snapshots of local moments produces an effective order parameter for the non-Fermi-liquid behavior. Our technique can be employed to characterize correlations unique to other phases with no obvious order parameters or signatures in projective measurements, and has implications for science discovery through AI beyond strongly correlated systems