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PubMed Journals Articles About "BERNARD KRIEF SEARCH" - Page: 5 RSS

11:12 EDT 18th September 2018 | BioPortfolio

BERNARD KRIEF SEARCH PubMed articles on BioPortfolio. Our PubMed references draw on over 21 million records from the medical literature. Here you can see the latest BERNARD KRIEF SEARCH articles that have been published worldwide.

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Showing "BERNARD KRIEF SEARCH" PubMed Articles 101–125 of 1,800+

Label Consistent Matrix Factorization Hashing for Large-Scale Cross-Modal Similarity Search.

Multimodal hashing has attracted much interest for cross-modal similarity search on large-scale multimedia data sets because of its efficiency and effectiveness. Recently, supervised multimodal hashing, which tries to preserve the semantic information obtained from the labels of training data, has received considerable attention for its higher search accuracy compared with unsupervised multimodal hashing. Although these algorithms are promising, they are mainly designed to preserve pairwise similarities. Th...


Sliding of a single lac repressor protein along DNA is tuned by DNA sequence and molecular switching.

In any living cell, genome maintenance is carried out by DNA-binding proteins that recognize specific sequences among a vast amount of DNA. This includes fundamental processes such as DNA replication, DNA repair, and gene expression and regulation. Here, we study the mechanism of DNA target search by a single lac repressor protein (LacI) with ultrafast force-clamp spectroscopy, a sub-millisecond and few base-pair resolution technique based on laser tweezers. We measure 1D-diffusion of proteins on DNA at phy...

Working memory training and perceptual discrimination training impact overlapping and distinct neurocognitive processes: Evidence from event-related potentials and transfer of training gains.

There is emerging evidence that working memory (WM) can potentially be enhanced via targeted training protocols. However, the differential effects of targeted training of WM vs. training of general attentional processes on distinct neurocognitive mechanisms is not well understood. In the present study, we compared adaptive n-back WM training to an adaptive visual search training task that targeted perceptual discrimination, in the absence of demands on WM. The search task was closely matched to the n-back t...


NMR-based investigations into target DNA search processes of proteins.

To perform their function, transcription factors and DNA-repair/modifying enzymes must first locate their targets in the vast presence of nonspecific, but structurally similar sites on genomic DNA. Before reaching their targets, these proteins stochastically scan DNA and dynamically move from one site to another on DNA. Solution NMR spectroscopy provides unique atomic-level insights into the dynamic DNA-scanning processes, which are difficult to gain by any other experimental means. In this review, we provi...

Parsing a mental program: Fixation-related brain signatures of unitary operations and routines in natural visual search.

Visual search involves a sequence or routine of unitary operations (i.e. fixations) embedded in a larger mental global program. The process can indeed be seen as a program based on a while loop (while the target is not found), a conditional construct (whether the target is matched or not based on specific recognition algorithms) and a decision making step to determine the position of the next searched location based on existent evidence. Recent developments in our ability to co-register brain scalp potentia...

Bronchopulmonary Dysplasia: The Ongoing Search for One Definition to Rule Them All.

In Search of an Oncogene Driver for Squamous Lung Cancer.

Smallpox antiviral ends decades-long search.

Why Does Large Batch Training Result in Poor Generalization? A Comprehensive Explanation and a Better Strategy from the Viewpoint of Stochastic Optimization.

We present a comprehensive framework of search methods, such as simulated annealing and batch training, for solving nonconvex optimization problems. These methods search a wider range by gradually decreasing the randomness added to the standard gradient descent method. The formulation that we define on the basis of this framework can be directly applied to neural network training. This produces an effective approach that gradually increases batch size during training. We also explain why large batch trainin...

Ego-Surfing First-Person Videos.

We envision a future time when wearable cameras are worn by the masses and recording first-person point-of-view videos of everyday life. While these cameras can enable new assistive technologies and novel research challenges, they also raise serious privacy concerns. For example, first-person videos passively recorded by wearable cameras will necessarily include anyone who comes into the view of a camera -- with or without consent. Motivated by these benefits and risks, we developed a self-search technique ...

A Grid Weighted Sum Pareto Local Search for Combinatorial Multi and Many-Objective Optimization.

Combinatorial multiobjective optimization problems (CMOPs) are very popular due to their widespread applications in the real world. One common method for CMOPs is Pareto local search (PLS), a natural extension of single-objective local search (LS). However, classical PLS tends to reserve all of the nondominated solutions for LS, which causes the inefficient LS, as well as unbearable computational and space cost. Due to the aforementioned reasons, most PLS approaches can only handle CMOPs with no more than t...

Gestalt similarity groupings are not constructed in parallel.

Our visual system organizes spatially distinct areas with similar features into perceptual groups. To better understand the underlying mechanism of grouping, one route is to study its capacity and temporal progression. Intuitively, that capacity seems unlimited, and the temporal progression feels immediate. In contrast, here we show that in a visual search task that requires similarity grouping, search performance is consistent with serial processing of those groups. This was true across several experiments...

Object-based target templates guide attention during visual search.

During visual search, attention is believed to be controlled in a strictly feature-based fashion, without any guidance by object-based target representations. To challenge this received view, we measured electrophysiological markers of attentional selection (N2pc component) and working memory (sustained posterior contralateral negativity; SPCN) in search tasks where two possible targets were defined by feature conjunctions (e.g., blue circles and green squares). Critically, some search displays also contain...

Search for the X(5568) State Decaying into B_{s}^{0}π^{±} in Proton-Proton Collisions at sqrts=8  TeV.

A search for resonancelike structures in the B_{s}^{0}π^{±} invariant mass spectrum is performed using proton-proton collision data collected by the CMS experiment at the LHC at sqrt[s]=8  TeV, corresponding to an integrated luminosity of 19.7  fb^{-1}. The B_{s}^{0} mesons are reconstructed in the decay chain B_{s}^{0}→J/ψϕ, with J/ψ→μ^{+}μ^{-} and ϕ→K^{+}K^{-}. The B_{s}^{0}π^{±} invariant mass distribution shows no statistically significant peaks for different selection requiremen...

A novel method of using Deep Belief Networks and genetic perturbation data to search for yeast signaling pathways.

Perturbing a signaling system with a serial of single gene deletions and then observing corresponding expression changes in model organisms, such as yeast, is an important and widely used experimental technique for studying signaling pathways. People have developed different computational methods to analyze the perturbation data from gene deletion experiments for exploring the signaling pathways. The most popular methods/techniques include K-means clustering and hierarchical clustering techniques, or combin...

HTLV-1 and dendritic cells: a relation-ship in search of maturation.

The Search for Meaning.

Vasospasm following aneurysmal subarachnoid hemorrhage: The search for the elusive wonder-drug.

Systematic Review of the Effectiveness of Hypnosis for the Management of Headache.

Migraine is a complex neurological condition that causes a range of symptoms, the most common of which is a severe headache. The aim of this systematic review of the literature is to determine the efficacy of hypnosis in the treatment of migraine. A systematic search of 4 scientific databases was conducted using the primary search terms migraine, headache, hypnosis, and hypnotherapy. A total of 8 studies were identified that examined hypnotic techniques either alone or in combination with other nonpharmaceu...

Spatial remapping in visual search: Remapping cues are provided at attended and ignored locations.

We experience the world as stable and continuous, despite the fact that visual input is overwritten on the retina with each new ocular fixation. Spatial remapping is the process that integrates selected visual information into successive (continuous) representations of our spatial environment, thereby allowing us to keep track of objects, and experience the world as stable, despite frequent eye (re-)fixations. The present paper investigates spatial remapping in the context of visual pop-out search. Within s...

LOXL1 Polymorphisms: Genetic Biomarkers that Presage Environmental Determinants of Exfoliation Syndrome.

An agnostic high throughput search of the genome revealed a robust association between LOXL1 genetic polymorphisms and exfoliation syndrome (XFS), a discovery that likely would not have been possible with candidate or family-based gene search strategies. While questions remain regarding how LOXL1 gene variants contribute to XFS pathogenesis, it is clear that the frequencies of disease-related alleles do not track with the varying disease burden throughout the world, prompting a search for environmental risk...

COPD: Abandoning a Drunkard's Search.

The Search for High-Risk Coronary Plaque in Patients With Diabetes.

Computer-aided diagnosis of lung nodule using gradient tree boosting and Bayesian optimization.

We aimed to evaluate a computer-aided diagnosis (CADx) system for lung nodule classification focussing on (i) usefulness of the conventional CADx system (hand-crafted imaging feature + machine learning algorithm), (ii) comparison between support vector machine (SVM) and gradient tree boosting (XGBoost) as machine learning algorithms, and (iii) effectiveness of parameter optimization using Bayesian optimization and random search. Data on 99 lung nodules (62 lung cancers and 37 benign lung nodules) were inclu...

Injury rate and prevention in elite football: let us first search within our own hearts.


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