Rapid method for determination of antimicrobial susceptibilities pattern of urinary bacteria

Method determines bacterial sensitivity to antimicrobial agents by measuring level of adenosine triphosphate remaining in the bacteria. Light emitted during reaction of sample with a mixture of luciferase and luciferin is measured

Backbone of complex networks of corporations: The flow of control

We present a methodology to extract the backbone of complex networks based on the weight and direction of links, as well as on nontopological properties of nodes. We show how the methodology can be applied in general to networks in which mass or energy is flowing along the links. In particular, the procedure enables us to address important questions in economics, namely, how control and wealth are structured and concentrated across national markets. We report on the first cross-country investigation of ownership networks, focusing on the stock markets of 48 countries around the world. On the one hand, our analysis confirms results expected on the basis of the literature on corporate control, namely, that in Anglo-Saxon countries control tends to be dispersed among numerous shareholders. On the other hand, it also reveals that in the same countries, control is found to be highly concentrated at the global level, namely, lying in the hands of very few important shareholders. Interestingly, the exact opposite is observed for European countries. These results have previously not been reported as they are not observable without the kind of network analysis developed here.Comment: 24 pages, 12 figures, 2nd version (text made more concise and readable, results unchanged

Optimal treatment allocations in space and time for on-line control of an emerging infectious disease

A key component in controlling the spread of an epidemic is deciding where, whenand to whom to apply an intervention.We develop a framework for using data to informthese decisionsin realtime.We formalize a treatment allocation strategy as a sequence of functions, oneper treatment period, that map up-to-date information on the spread of an infectious diseaseto a subset of locations where treatment should be allocated. An optimal allocation strategyoptimizes some cumulative outcome, e.g. the number of uninfected locations, the geographicfootprint of the disease or the cost of the epidemic. Estimation of an optimal allocation strategyfor an emerging infectious disease is challenging because spatial proximity induces interferencebetween locations, the number of possible allocations is exponential in the number oflocations, and because disease dynamics and intervention effectiveness are unknown at outbreak.We derive a Bayesian on-line estimator of the optimal allocation strategy that combinessimulation–optimization with Thompson sampling.The estimator proposed performs favourablyin simulation experiments. This work is motivated by and illustrated using data on the spread ofwhite nose syndrome, which is a highly fatal infectious disease devastating bat populations inNorth America

Fragment Flow and the Nuclear Equation of State

We use the Boltzmann-Uehling-Uhlenbeck model with a momentum-dependent nuclear mean field to simulate the dynamical evolution of heavy ion collisions. We re-examine the azimuthal anisotropy observable, proposed as sensitive to the equation of state of nuclear matter. We obtain that this sensitivity is maximal when the azimuthal anisotropy is calculated for nuclear composite fragments, in agreement with some previous calculations. As a test case we concentrate on semi-central $^{197}{\rm Au}\ +\ ^{197}{\rm Au}$ collisions at 400 $A$ MeV.Comment: 12 pages, ReVTeX 3.0. 12 Postscript figures, uuencoded and appende

Achieving Generalizable Robustness of Deep Neural Networks by Stability Training

We study the recently introduced stability training as a general-purpose method to increase the robustness of deep neural networks against input perturbations. In particular, we explore its use as an alternative to data augmentation and validate its performance against a number of distortion types and transformations including adversarial examples. In our image classification experiments using ImageNet data stability training performs on a par or even outperforms data augmentation for specific transformations, while consistently offering improved robustness against a broader range of distortion strengths and types unseen during training, a considerably smaller hyperparameter dependence and less potentially negative side effects compared to data augmentation.Comment: 18 pages, 25 figures; Camera-ready versio

Light depolarization effects in tip enhanced Raman spectroscopy of silicon (001) and gallium arsenide (001)

We report on the effects of light depolarization induced by sharp metallic tips in Tip-Enhanced Raman Spectroscopy (TERS). Experiments on Si(001) and GaAs(001) crystals show that the excitation field depolarization induces a selective enhancement of specific Raman modes, depending on their Raman tensor symmetry. A complete polarization analysis of the light backscattered from the tip confirms the TERS findings. The spatial confinement of the depolarization field is studied and its dependence on the excitation wavelength and power are explored

Combining active learning and semi-supervised learning techniques to extract protein interaction sentences

Background: Protein-protein interaction (PPI) extraction has been a focal point of many biomedical research and database curation tools. Both Active Learning and Semi-supervised SVMs have recently been applied to extract PPI automatically. In this paper, we explore combining the AL with the SSL to improve the performance of the PPI task. Methods: We propose a novel PPI extraction technique called PPISpotter by combining Deterministic Annealing-based SSL and an AL technique to extract protein-protein interaction. In addition, we extract a comprehensive set of features from MEDLINE records by Natural Language Processing (NLP) techniques, which further improve the SVM classifiers. In our feature selection technique, syntactic, semantic, and lexical properties of text are incorporated into feature selection that boosts the system performance significantly. Results: By conducting experiments with three different PPI corpuses, we show that PPISpotter is superior to the other techniques incorporated into semi-supervised SVMs such as Random Sampling, Clustering, and Transductive SVMs by precision, recall, and F-measure. Conclusions: Our system is a novel, state-of-the-art technique for efficiently extracting protein-protein interaction pairs.X116sciescopu

(Total) Vector Domination for Graphs with Bounded Branchwidth

Given a graph $G=(V,E)$ of order $n$ and an $n$-dimensional non-negative vector $d=(d(1),d(2),\ldots,d(n))$, called demand vector, the vector domination (resp., total vector domination) is the problem of finding a minimum $S\subseteq V$ such that every vertex $v$ in $V\setminus S$ (resp., in $V$) has at least $d(v)$ neighbors in $S$. The (total) vector domination is a generalization of many dominating set type problems, e.g., the dominating set problem, the $k$-tuple dominating set problem (this $k$ is different from the solution size), and so on, and its approximability and inapproximability have been studied under this general framework. In this paper, we show that a (total) vector domination of graphs with bounded branchwidth can be solved in polynomial time. This implies that the problem is polynomially solvable also for graphs with bounded treewidth. Consequently, the (total) vector domination problem for a planar graph is subexponential fixed-parameter tractable with respectto $k$, where $k$ is the size of solution.Comment: 16 page

Long-term mortality after Histoplasma infection in people with HIV

Histoplasmosis is a common opportunistic infection in people with HIV (PWH); however, no study has looked at factors associated with the long-term mortality of histoplasmosis in PWH. We conducted a single-center retrospective study on the long-term mortality of PWH diagnosed with histoplasmosis between 2002 and 2017. Patients were categorized into three groups based on length of survival after diagnosis: early mortality (death \u3c 90 days), late mortality (death ≥ 90 days), and long-term survivors. Patients diagnosed during or after 2008 were considered part of the modern antiretroviral therapy (ART) era. Insurance type (private vs. public) was a surrogate indicator of socioeconomic status. Out of 54 PWH infected with histoplasmosis, overall mortality was 37%; 14.8% early mortality and 22.2% late mortality. There was no statistically significant difference in survival based on the availability of modern ART