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Black box

David C Whitcomb
No abstract text is available yet for this article.
November 2016: Pancreas
Irene Sturm, Sebastian Lapuschkin, Wojciech Samek, Klaus-Robert Müller
BACKGROUND: In cognitive neuroscience the potential of Deep Neural Networks (DNNs) for solving complex classification tasks is yet to be fully exploited. The most limiting factor is that DNNs as notorious 'black boxes' do not provide insight into neurophysiological phenomena underlying a decision. Layer-wise Relevance Propagation (LRP) has been introduced as a novel method to explain individual network decisions. NEW METHOD: We propose the application of DNNs with LRP for the first time for EEG data analysis...
October 13, 2016: Journal of Neuroscience Methods
Dara Mohammadi
No abstract text is available yet for this article.
October 10, 2016: Lancet Respiratory Medicine
Jannis Erhard, Patrick Bleiziffer, Andreas Görling
A power series approximation for the correlation kernel of time-dependent density-functional theory is presented. Using this approximation in the adiabatic-connection fluctuation-dissipation (ACFD) theorem leads to a new family of Kohn-Sham methods. The new methods yield reaction energies and barriers of unprecedented accuracy and enable a treatment of static (strong) correlation with an accuracy of high-level multireference configuration interaction methods but are single-reference methods allowing for a black-box-like handling of static correlation...
September 30, 2016: Physical Review Letters
James J Malone, Ric Lovell, Matthew C Varley, Aaron J Coutts
Athlete tracking devices that include global positioning system (GPS) and micro electrical mechanical system (MEMS) components are now commonplace in sport research and practice. These devices provide large amounts of data that are used to inform decision-making on athlete training and performance. However, the data obtained from these devices are often provided without clear explanation of how these metrics are obtained. At present, there is no clear consensus regarding how these data should be handled and reported in a sport context...
October 13, 2016: International Journal of Sports Physiology and Performance
Ramon Farré, Daniel Navajas, Josep M Montserrat
Current devices for providing noninvasive respiratory support contain sensors and built-in intelligence for automatically modifying ventilation according to the patient's needs. These devices, including automatic continuous positive airway pressure devices and noninvasive ventilators, are technologically complex and offer a considerable number of different modes of ventilation and setting options, the details of which are sometimes difficult to capture by the user. Therefore, better predicting and interpreting the actual performance of these ventilation devices in clinical application requires understanding their functioning principles and assessing their performance under well controlled bench test conditions with simulated patients...
January 2016: ERJ Open Research
Vanya Van Belle, Ben Van Calster, Sabine Van Huffel, Johan A K Suykens, Paulo Lisboa
PROBLEM SETTING: Support vector machines (SVMs) are very popular tools for classification, regression and other problems. Due to the large choice of kernels they can be applied with, a large variety of data can be analysed using these tools. Machine learning thanks its popularity to the good performance of the resulting models. However, interpreting the models is far from obvious, especially when non-linear kernels are used. Hence, the methods are used as black boxes. As a consequence, the use of SVMs is less supported in areas where interpretability is important and where people are held responsible for the decisions made by models...
2016: PloS One
David Moher, Philippe Ravaud
Biomedical journals continue to be the single most important conduit for disseminating biomedical knowledge. Unlike clinical medicine, where evidence is considered fundamental to practice, journals still operate largely in a 'black box' mode without sufficient evidence to drive their practice. We believe there is an immediate need to substantially increase the amount and quality of research by journals to ensure their practice is as evidence based as possible. To achieve this goal, we are proposing the development of an international 'best practice journal research network'...
October 10, 2016: BMC Medicine
Thomas Dresselhaus, Steffen Eusterwiemann, David R Matuschek, Constantin G Daniliuc, Oliver Janka, Rainer Pöttgen, Armido Studer, Johannes Neugebauer
In all but the simplest crystal structures, the identification of all relevant interactions between magnetic sites as well as the setup of magnetic model spaces, which are necessary for modeling macroscopic magnetism, are tedious and error-prone tasks. Here, we present a procedure to generate magnetic susceptibility versus temperature curves using only a crystal structure as input. The procedure, which is based on the first-principles bottom-up approach [Deumal et al., J. Phys. Chem. A, 2002, 106, 1299], is designed in a way to require as little user interference as possible...
October 12, 2016: Physical Chemistry Chemical Physics: PCCP
Davide Castelvecchi
No abstract text is available yet for this article.
October 5, 2016: Nature
Alejandro J Garza, Gustavo E Scuseria
We compare the ability of four popular hybrid density functionals (B3LYP, B3PW91, HSE, and PBE0) for predicting band gaps of semiconductors and insulators over a large benchmark set using a consistent methodology. We observe no significant statistical difference in their overall performance although the screened hybrid HSE is more accurate for typical semiconductors. HSE can improve its accuracy for large large band gap materials --without affecting that of semiconductors-- by including a larger portion of Hartree--Fock exchange in its short range...
October 5, 2016: Journal of Physical Chemistry Letters
Sweta Vangaveti, Srivathsan V Ranganathan, Alan A Chen
Molecular simulations have become an essential tool for biochemical research. When they work properly, they are able to provide invaluable interpretations of experimental results and ultimately provide novel, experimentally testable predictions. Unfortunately, not all simulation models are created equal, and with inaccurate models it becomes unclear what is a bona fide prediction versus a simulation artifact. RNA models are still in their infancy compared to the many robust protein models that are widely in use, and for that reason the number of RNA force field revisions in recent years has been rapidly increasing...
October 4, 2016: Wiley Interdisciplinary Reviews. RNA
Oleg V Krokhin, Vic Spicer
The emergence of data independent quantitative LC-MS/MS analysis protocols further highlights the importance of high quality reproducible chromatographic procedures. Knowing, controlling and being able to predict the effect of multiple factors that alter peptide RP-HPLC separation selectivity is critical to successful data collection for the construction of ion libraries. Proteomic researchers have often regarded RP-HPLC as a "black box", while vast amounts of research on peptide separation is readily available...
October 4, 2016: Proteomics
Carola Doerr, Johannes Lengler
Black-box complexity theory provides lower bounds for the runtime of black-box optimizers like evolutionary algorithms and other search heuristics and serves as an inspiration for the design of new genetic algorithms. Several black-box models covering different classes of algorithms exist, each highlighting a different aspect of the algorithms under considerations. In this work we add to the existing black-box notions a new elitist black-box model, in which algorithms are required to base all decisions solely on (the relative performance of) a fixed number of the best search points sampled so far...
October 4, 2016: Evolutionary Computation
Mario A Muñoz, Kate A Smith-Miles
This paper presents a method for the objective assessment of an algorithm's strengths and weaknesses. Instead of examining only the performance of one or more algorithms on a benchmark set, or generating custom problems that maximize the performance difference between two algorithms, our method quantifies both the nature of the test instances and the algorithm performance. Our aim is to gather information about possible phase transitions in performance, i.e., the points in which a small change in problem structure produces algorithm failure...
September 30, 2016: Evolutionary Computation
Fabio Daolio, Arnaud Liefooghe, Sébastien Verel, Hernán Aguirre, Kiyoshi Tanaka
In this paper, we attempt to understand and to contrast the impact of problem features on the performance of randomized search heuristics for black-box multi-objective combinatorial optimization problems. At first, we measure the performance of two conventional dominance-based approaches with unbounded archive on a benchmark of enumerable binary optimization problems with tunable ruggedness, objective space dimension, and objective correlation (ρMNK-landscapes). Precisely, we investigate the expected runtime required by a global evolutionary optimization algorithm with an ergodic variation operator (GSEMO) and by a neighborhood-based local search heuristic (PLS), to identify a [Formula: see text]-approximation of the Pareto set...
September 30, 2016: Evolutionary Computation
Franck A Atienzar, Eric A Blomme, Minjun Chen, Philip Hewitt, J Gerry Kenna, Gilles Labbe, Frederic Moulin, Francois Pognan, Adrian B Roth, Laura Suter-Dick, Okechukwu Ukairo, Richard J Weaver, Yvonne Will, Donna M Dambach
Drug-induced liver injury (DILI) is a major cause of late-stage clinical drug attrition, market withdrawal, black-box warnings, and acute liver failure. Consequently, it has been an area of focus for toxicologists and clinicians for several decades. In spite of considerable efforts, limited improvements in DILI prediction have been made and efforts to improve existing preclinical models or develop new test systems remain a high priority. While prediction of intrinsic DILI has improved, identifying compounds with a risk for idiosyncratic DILI (iDILI) remains extremely challenging because of the lack of a clear mechanistic understanding and the multifactorial pathogenesis of idiosyncratic drug reactions...
2016: BioMed Research International
Emily S Spivak, Sara E Cosgrove, Arjun Srinivasan
Indiscriminate antimicrobial use has plagued medicine since antibiotics were first introduced into clinical practice more than seventy years ago. Infectious diseases physicians and public health officials have advocated for preservation of these life-saving drugs for many years. With rising burden of antimicrobial resistant organisms and Clostridium difficile infections, halting unnecessary antimicrobial use has become one of the largest public health concerns of our time. Inappropriate antimicrobial use has been quantified in various settings using numerous definitions; however, no established reference standard exists...
September 28, 2016: Clinical Infectious Diseases: An Official Publication of the Infectious Diseases Society of America
Wilma C Hazeleger, Wilma F Jacobs-Reitsma, Heidy M W den Besten
Campylobacter is well recognized as the leading cause of bacterial foodborne diarrheal disease worldwide, and is routinely found in meat originating from poultry, sheep, pigs, and cattle. Effective monitoring of Campylobacter contamination is dependent on the availability of reliable detection methods. The method of the International Organization for Standardization for the detection of Campylobacter spp. in food (ISO 10272-1:2006) recommends the use of Bolton broth (BB) as selective enrichment medium, including a pre-enrichment step of 4-6 h at 37°C to revive sublethally damaged cells prior to incubation for 2 days at 41...
2016: Frontiers in Microbiology
Eric T Lofgren
Mathematical modeling is an important tool in biological research, allowing for the synthesis of results from many studies into an understanding of a system. Despite this, the need for extensive subject matter knowledge and complex mathematics often leaves modeling as an esoteric subspecialty. A 2-fold approach can be used to make modeling more approachable for students and those interested in obtaining a functional knowledge of modeling. The first is the use of a popular culture disease system-a zombie epidemic-to allow for exploration of the concepts of modeling using a flexible framework...
October 2016: FEMS Microbiology Letters
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