Entropy bounds for uncollapsed matter

In any static spacetime the quasilocal Tolman mass contained within a volume can be reduced to a Gauss-like surface integral involving the flux of a suitably defined generalized surface gravity. By introducing some basic thermodynamics, and invoking the Unruh effect, one can then develop elementary bounds on the quasilocal entropy that are very similar in spirit to the holographic bound, and closely related to entanglement entropy.Comment: 4 pages. Prepared for the proceedings of the Spanish Relativity meeting (ERE2010), Granada, Spain, 6-10 Sep 201

The quantum interest conjecture in (3+1)-dimensional Minkowski space

The quantum inequalities, and the closely related quantum interest conjecture, impose restrictions on the distribution of the energy density measured by any time-like observer, potentially preventing the existence of exotic phenomena such as Alcubierre warp-drives or traversable wormholes. It has already been proved that both assertions can be reduced to statements concerning the existence or non-existence of bound states of a certain 1-dimensional quantum mechanical Hamiltonian. Using this approach, we will informally review a simple variational proof of one version of the Quantum Interest conjecture in (3+1)-dimensional Minkowski space.Comment: 3 pages. Prepared for the proceedings of the 12th Marcel Grossmann conference. (Paris, July 2009.

Automatic offensive language detection from Twitter data using machine learning and feature selection of metadata

The popularity of social networks has only increased in recent years. In theory, the use of social media was proposed so we could share our views online, keep in contact with loved ones or share good moments of life. However, the reality is not so perfect, so you have people sharing hate speech-related messages, or using it to bully specific individuals, for instance, or even creating robots where their only goal is to target specific situations or people. Identifying who wrote such text is not easy and there are several possible ways of doing it, such as using natural language processing or machine learning algorithms that can investigate and perform predictions using the metadata associated with it. In this work, we present an initial investigation of which are the best machine learning techniques to detect offensive language in tweets. After an analysis of the current trend in the literature about the recent text classification techniques, we have selected Linear SVM and Naive Bayes algorithms for our initial tests. For the preprocessing of data, we have used different techniques for attribute selection that will be justified in the literature section. After our experiments, we have obtained 92% of accuracy and 95% of recall to detect offensive language with Naive Bayes and 90% of accuracy and 92% of recall with Linear SVM. From our understanding, these results overcome our related literature and are a good indicative of the importance of the data description approach we have used

Quantum Interest in (3+1) dimensional Minkowski space

The so-called "Quantum Inequalities", and the "Quantum Interest Conjecture", use quantum field theory to impose significant restrictions on the temporal distribution of the energy density measured by a time-like observer, potentially preventing the existence of exotic phenomena such as "Alcubierre warp-drives" or "traversable wormholes". Both the quantum inequalities and the quantum interest conjecture can be reduced to statements concerning the existence or non-existence of bound states for a certain one-dimensional quantum mechanical pseudo-Hamiltonian. Using this approach, we shall provide a simple proof of one version of the Quantum Interest Conjecture in (3+1) dimensional Minkowski space.Comment: V1: 8 pages, revtex4; V2: 10 pages, some technical changes in details of the argument, no change in physics conclusions, this version essentially identical to published versio

High-Dimensional Graphical Model Search with the gRapHD R Package

This paper presents the R package gRapHD for efficient selection of high-dimensional undirected graphical models. The package provides tools for selecting trees, forests, and decomposable models minimizing information criteria such as AIC or BIC, and for displaying the independence graphs of the models. It has also some useful tools for analysing graphical structures. It supports the use of discrete, continuous, or both types of variables.

Devising adjuvant therapeutic strategies toward severe lower respiratory infections

Dissertação de mestrado em BiotechnologyAs infecções das vias respiratórias inferiores (IVRI) são uma causa comum de mortalidade/morbilidade em todo o mundo. As IVRI são frequentemente governadas por biofilmes, tipicamente polimicrobianos e na sua maioria dominadas por espécies bacterianas Pseudomonas aeruginosa, Staphylococcus aureus, Acinetobacter baumannii, Klebsiella pneumoniae), mas também por fungos (por exemplo, Candida albicans). Os biofilmes contribuem significativamente para o aparecimento de resistência antimicrobiana (RAM), o que é de grande preocupação clínica. A ineficácia dos antibióticos e a falta de novos antibióticos exige fortemente estratégias alternativas que possam restabelecer a acção dos antibióticos existentes contra os agentes patogénicos. O principal objectivo deste trabalho foi o de encontrar estratégias combinatórias eficazes de antibiótico-adjuvante capazes de atenuar os traços de RAM nos agentes patogénicos associados ao IVRI, isolados e em co-infecção. Em primeiro lugar, a susceptibilidade das populações microbianas foi avaliada em relação a um painel de compostos, incluindo antibióticos e potenciais compostos adjuvantes (PCAs). Os antibióticos ineficazes foram testados em combinação com todos os PCAs e verificados quanto à sinergia através de um checkboard assay. As combinações antibiótico-adjuvante mais promissoras foram então empregadas contra biofilmes pré-estabelecidos 24 h de uma única espécie, de dupla (P. aeruginosa/S. aureus) e tripla espécie (P. aeruginosa/S. aureus/K. pneumoniae) para avaliar a sua eficácia. A maioria das populações microbianas mostrou resistência à maioria dos antibióticos (12 em 25). Não foi encontrada actividade antimicrobiana para os 4 AAE testados (EDTA, SucA, FAR, LIN). Foram encontradas combinações sinergéticas contra S. aureus, K. pneumoniae e A. baumannii, conforme determinado pelo índice FIC. EDTA e LIN mostraram os melhores resultados ao interagirem com sucesso com todos os antibióticos que anteriormente tinham sido considerados ineficazes. As combinações antibiótico-adjuvante de PIP+EDTA, PIP+COL, COL+EDTA, e COL+LIN foram testadas contra biofilmes de uma e várias espécies. Todas as combinações testadas levaram a reduções significativas na biomassa do biofilme de P. aeruginosa e S. aureus; reduções igualmente visíveis no número de células foram também obtidas nos biofilmes formados por cada espécie. No entanto, não foi observada qualquer redução significativa na massa do biofilme de K. pneumoniae e A. baumannii, mas houve uma diminuição nas células cultiváveis. As combinações antibiótico-adjuvantes contra biofilmes de dupla espécie resultaram em reduções significativas na biomassa do biofilme e nas células cultiváveis de P. aeruginosa. Quanto aos biofilmes tri-espécies, a única redução significativa na massa dos biofilmes foi encontrada quando foram utilizadas combinações de COL. Contudo, nenhuma combinação foi capaz de erradicar completamente as populações de biofilmes.Lower respiratory tract infections (LRTIs) are a common cause of mortality/morbidity worldwide. Biofilms often govern LRTIs, typically polymicrobial and dominated mainly by bacterial species Pseudomonas aeruginosa, Staphylococcus aureus, Acinetobacter baumannii, Klebsiella pneumoniae), but also fungi (e.g., Candida albicans). Biofilms contribute significantly to the emergence of antimicrobial resistance (AMR), which is of great clinical concern. The antibiotic ineffectiveness and the lack of new antibiotics strongly demand alternative strategies that may restore the action of existing antibiotics against pathogens. The main goal of this work was to find effective antibiotic-adjuvant combinatorial strategies able to attenuate AMR traits in LRTI-associated pathogens, isolated and in co-infection. Firstly, the susceptibility of the microbial populations was evaluated against a panel of compounds, including antibiotics and potential adjuvant compounds (AAEs). Ineffective antibiotics were tested in combination with all the AAEs and checked for synergy through a checkerboard assay. The most promising antibiotic-adjuvant combinations were then employed against 24 h pre-established biofilms of single species and of dual (P. aeruginosa/S. aureus) and triple-species (P. aeruginosa/S. aureus/K. pneumoniae) to evaluate their effectiveness. Most microbial populations showed resistance to most antibiotics (12 out of 25). No antimicrobial activity was found for the 4 tested AAEs (EDTA, SucA, FAR, LIN). Synergistic combinations were found against S. aureus, K. pneumoniae, and A. baumannii, as determined by the FIC index. EDTA and LIN showed the best outcomes by successfully interacting with all antibiotics previously found ineffective. Antibiotic adjuvant combinations of PIP+EDTA, PIP+COL, COL+EDTA, and COL+LIN were tested against single and multi-species biofilms. All tested combinations led to significant reductions in the biofilm biomass of P. aeruginosa and S. aureus; similarly visible reductions in the number of cells were also obtained in the biofilms formed by each species. However, no significant reduction in the biofilm mass of K. pneumoniae and A. baumannii were observed, but there was a decrease in cultivable cells. The antibiotic-adjuvants combinations against dual-species biofilms resulted in significant reductions in biofilm biomass and cultivable cells of P. aeruginosa. As for triple-species biofilms, the only significant reduction in biofilm mass was found when COL combinations were employed. However, no combination was able to eradicate biofilm populations