bluuebunny/crossref_metadata_2025_split huggingface dataset:
Sight restoration after congenital blindness does not reinstate alpha oscillatory activity in humans
Authors: Bottari Davide , Troje Nikolaus F. , Ley Pia , Hense Marlene , Kekunnaya Ramesh , Röder Brigitte 
Published: April 2016

AbstractFunctional brain development is characterized by sensitive periods during which experience must be available to allow for the full development of neural circuits and associated behavior. Yet, only few neural markers of sensitive period plasticity in humans are known. Here we employed electroencephalographic recordings in a unique sample of twelve humans who had been blind from birth and regained sight through cataract surgery between four months and 16 years of age. Two additional control groups were tested: a group of visually impaired individuals without a history of total congenital blindness and a group of typically sighted individuals. The EEG was recorded while participants performed a visual discrimination task involving intact and scrambled biological motion stimuli. Posterior alpha and theta oscillations were evaluated. The three groups showed indistinguishable behavioral performance and in all groups evoked theta activity varied with biological motion processing. By contrast, alpha oscillatory activity was significantly reduced only in individuals with a history of congenital cataracts. These data document on the one hand brain mechanisms of functional recovery (related to theta oscillations) and on the other hand, for the first time, a sensitive period for the development of alpha oscillatory activity in humans.
Application of grounded metallic enclosing mesh for expanding rated voltage of dry‐type transformer
Authors: de Oliveira Luiz F. , Cabral Sérgio H.L. 
Published: April 2016

Thanks to the awareness of safety, dry‐type transformer has experienced a significant demand, lately. However, a limiting condition for an even more significant increase in its demand is that its maximum rated voltage is about 36 kV, in most of countries. Beyond this limit, dry‐type transformer becomes definitely uneconomical in comparison to oil‐filled transformer because of the expressive increase in dielectric clearance distances and consequent drawbacks. Thus, the aim of this work is to propose a way for overcoming this limit, based on shielding the electric field of the high‐voltage windings of the dry transformer with a grounded metallic mesh. The effectiveness of the proposition is shown whereas most of the undesirable of its consequences are also evaluated. Namely, losses and temperature rise concerns as well as items of standard dielectric tests, which are analysed through computer modelling and simulation. Due to its outstanding importance, analysis of distribution of lightning impulse voltage along the high‐voltage winding is also experimentally performed. The result is a set of key hints given by the authors and to be observed by transformer designers for making real the production of dry‐type transformer with a rated voltage higher than 36 kV.
Existe-t-il une interférence entre le système manducateur et le
système postural ?
Authors: Marignan Michel 
Published: April 2016

La posturologie est une compétence en physiologie théorique et clinique particulière
applicable à de nombreux domaines de la médecine et de ses disciplines annexes, dont
l’objet est l’étude de la station debout et ses dysfonctionnements. Elle propose une
panoplie multiprofessionnelle de moyens tant diagnostiques que thérapeutiques puissants
basés sur la neurophysiologie du positionnement et du mouvement humain dans la prise en
charge de nombreuses pathologies. C’est une approche médicale fonctionnelle. En tant que
médecin posturologue, si nous remarquons fréquemment une perturbation de la station debout
par une ou des dysfonctions manducatrices, il semble inversement indispensable de rappeler
pourquoi et comment un syndrome postural peut constituer une source d’échec thérapeutique
en orthopédie dento-faciale. Il nous appartient donc de proposer, sur la base des
connaissances actuelles, un schéma de prise en charge diagnostique et thérapeutique,
permettant d’éviter un échec en orthopédie dento-faciale au sens de la « non obtention du
résultat escompté ».
Échec dans la réhabilitation antérieure en cas d’agénésies des
incisives latérales maxillaires
Authors: Le Gall Michel , Philippart-Rochaix Martine , Philip-Alliez Camille 
Published: April 2016

L’agénésie des incisives latérales maxillaires pose des problèmes particuliers pour les
dentistes, les orthodontistes et les patients. Le traitement de ces agénésies fait encore
l’objet de nombreuses polémiques, tant sur le plan fonctionnel qu’esthétique. Sourire et
guidance antérieure du patient sont affectés. Ils doivent être rétablis. Le diagnostic est
facile et ne prête pas à confusion. La décision thérapeutique, quant à elle, est beaucoup
plus complexe. Même si cette décision ne repose que sur deux solutions parfaitement
distinctes : la fermeture de l’espace laissé par l’agénésie ou l’ouverture de cet espace
et le remplacement prothétique de la dent manquante. Ce choix se fera grâce à de multiples
facteurs...à l’origine des nombreuses erreurs d’appréciation. En effet, la recherche du
résultat optimal ne pourra se faire que s’il y a une excellente coordination entre
différents intervenants de plusieurs spécialités. Chaque clinicien aura un rôle spécifique
à jouer. Aussi, le patient et sa famille se trouvent au cœur de la décision, tant dans
leur consentement (durée du traitement, possibilités financières) que dans leur
motivation. C’est cette décision multifactorielle, pluridisciplinaire qui fait que le
traitement de l’agénésie de l’incisive latérale est un défi permanent pour le clinicien à
la recherche du meilleur résultat possible. Chaque cas est différent. Établir des règles
est impossible. Aucun facteur ne peut être négligé pour éviter « l’erreur ».
Implementing an Antibiotic Stewardship Program: Guidelines by the Infectious Diseases Society of America and the Society for Healthcare Epidemiology of America
Authors: Barlam Tamar F. , Cosgrove Sara E. , Abbo Lilian M. , MacDougall Conan , Schuetz Audrey N. , Septimus Edward J. , Srinivasan Arjun , Dellit Timothy H. , Falck-Ytter Yngve T. , Fishman Neil O. , Hamilton Cindy W. , Jenkins Timothy C. , Lipsett Pamela A. , Malani Preeti N. , May Larissa S. , Moran Gregory J. , Neuhauser Melinda M. , Newland Jason G. , Ohl Christopher A. , Samore Matthew H. , Seo Susan K. , Trivedi Kavita K. 
Published: April 2016

AbstractEvidence-based guidelines for implementation and measurement of antibiotic stewardship interventions in inpatient populations including long-term care were prepared by a multidisciplinary expert panel of the Infectious Diseases Society of America and the Society for Healthcare Epidemiology of America. The panel included clinicians and investigators representing internal medicine, emergency medicine, microbiology, critical care, surgery, epidemiology, pharmacy, and adult and pediatric infectious diseases specialties. These recommendations address the best approaches for antibiotic stewardship programs to influence the optimal use of antibiotics.
Formation of massive Population III galaxies through photoionization feedback: a possible explanation for CR 7
Authors: Visbal Eli , Haiman Zoltán , Bryan Greg L. 
Published: April 2016

Abstract
We explore the formation of massive high-redshift Population III (Pop III) galaxies through photoionization feedback. We consider dark matter haloes formed from progenitors that have undergone no star formation as a result of early reionization and photoevaporation caused by a nearby galaxy. Once such a halo reaches ≈109 M⊙, corresponding to the Jeans mass of the photoheated intergalactic medium at z ≈ 7, pristine gas is able to collapse into the halo, potentially producing a massive Pop III starburst. We suggest that this scenario may explain the recent observation of strong He ii 1640 Å line emission in CR 7, which is consistent with ∼107 M⊙ of young Pop III stars. Such a large mass of Pop III stars is unlikely without the photoionization feedback scenario, because star formation is expected to inject metals into haloes above the atomic cooling threshold (∼108 M⊙ at z ≈ 7). We use merger trees to analytically estimate the abundance of observable Pop III galaxies formed through this channel, and find a number density of ≈10−7 Mpc−3 at z = 6.6 (the redshift of CR 7). This is approximately a factor of 10 lower than the density of Ly α emitters as bright as CR 7.
Precision measurement and frequency metrology with ultracold atoms
Authors: Zhang Xibo , Ye Jun 
Published: April 2016

Abstract
Precision measurement and frequency metrology have pushed many scientific and technological frontiers in the field of atomic, molecular and optical physics. In this article, we provide a brief review on the recent development of optical atomic clocks, with an emphasis placed on the important inter-dependence between measurement precision and systematic effects. After presenting a general discussion on the motivation and techniques behind the development of optical lattice clocks, where the use of many atoms greatly enhances the measurement precision, we present the JILA strontium optical lattice clock as the leading system of frequency metrology with the lowest total uncertainty, and we describe other related research activities. We discuss key ingredients that have enabled the optical lattice clocks with ultracold atoms to reach the 18th digit in both precision and accuracy. Furthermore, we discuss extending the power of precision clock spectroscopy to study quantum many-body physics and to provide control for atomic quantum materials. In addition, we explore future research directions that have the potential to achieve even greater precision.
Network-based metabolite ratios for an improved functional characterization of genome-wide association study results
Authors: Krumsiek Jan , Stückler Ferdinand , Suhre Karsten , Gieger Christian , Spector Tim D. , Soranzo Nicole , Kastenmüller Gabi , Theis Fabian J. 
Published: April 2016

AbstractGenome-wide association studies (GWAS) with metabolite ratios as quantitative traits have successfully deepened our understanding of the complex relationship between genetic variants and metabolic phenotypes. Usually all ratio combinations are selected for association tests. However, with more metabolites being detectable, the quadratic increase of the ratio number becomes challenging from a statistical, computational and interpretational point-of-view. Therefore methods which select biologically meaningful ratios are required.We here present a network-based approach by selecting only closely connected metabolites in a given metabolic network. The feasibility of this approach was tested onin silicodata derived from simulated reaction networks. Especially for small effect sizes, network-based metabolite ratios (NBRs) improved the metabolite-based prediction accuracy of genetically-influenced reactions compared to the ‘all ratios’ approach. Evaluating the NBR approach on published GWAS association results, we compared reported ‘all ratio’-SNP hits with results obtained by selecting only NBRs as candidates for association tests. Input networks for NBR selection were derived from public pathway databases or reconstructed from metabolomics data. NBR-candidates covered more than 80% of all significant ratio-SNP associations and we could replicate 7 out of 10 new associations predicted by the NBR approach.In this study we evaluated a network-based approach to select biologically meaningful metabolite ratios as quantitative traits in GWAS. Taking metabolic network information into account facilitated the analysis and the biochemical interpretation of metabolite-gene association results. For upcoming studies, for instance with case-control design, large-scale metabolomics data and small sample numbers, the analysis of all possible metabolite ratios is not feasible due to the correction for multiple testing. Here our NBR approach increases the statistical power and lowers computational demands, allowing for a better understanding of the complex interplay between individual phenotypes, genetics and metabolic profiles.
An advanced immune based strategy to obtain an optimal feasible assembly sequence
Authors: Bahubalendruni M.V.A. Raju , Deepak B.B.V.L. , Biswal Bibhuti Bhusan 
Published: April 2016

Purpose
The purpose of this study is to develop an intelligent methodology to find out an optimal feasible assembly sequence while considering the assembly predicates.

Design/methodology/approach
This proposed study is carried out by using two artificial immune system-based models, namely, Bone Marrow Model and Negative Selection Algorithms, to achieve the following objectives: to obtain the possible number of assembly sequences; to obtain the feasible assembly sequences while considering different assembly predicates; and to obtain an optimal feasible assembly sequence.

Findings
Proposed bone-marrow model determines the possible assembly sequences to ease the intricacy of the problem formulation. Further evaluation has been carried out through negative-selection censoring and monitoring models. These developed models reduce the overall computational time to determine the optimal feasible assembly sequence.

Originality/value
In this paper, the novel and efficient strategies based on artificial immune system have been developed and proposed to obtain all valid assembly sequences and optimized assembly sequence for a given assembled product using assembly attributes. The introduced methodology has proven its effectiveness in achieving optimal assembly sequence with less computational time.
A new genetic algorithm approach to smooth path planning for mobile robots
Authors: Song Baoye , Wang Zidong , Sheng Li 
Published: April 2016

Purpose
The purpose of this paper is to consider the smooth path planning problem for a mobile robot based on the genetic algorithm (GA) and the Bezier curve.

Design/methodology/approach
The workspace of a mobile robot is described by a new grid-based representation that facilitates the operations of the adopted GA. The chromosome of the GA is composed of a sequence of binary numbered grids (i.e. control points of the Bezier curve). Ordinary genetic operators including crossover and mutation are used to search the optimum chromosome where the optimization criterion is the length of a piecewise collision-free Bezier curve path determined by the control points.

Findings
This paper has proposed a new smooth path planning for a mobile robot by resorting to the GA and the Bezier curve. A new grid-based representation of the workspace has been presented, which makes it convenient to perform operations in the GA. The GA has been used to search the optimum control points that determine the Bezier curve-based smooth path. The effectiveness of the proposed approach has been verified by a numerical experiment, and some performances of the obtained method have also been analyzed.

Research limitations/implications
There still remain many interesting topics, for example, how to solve the specific smooth path planning problem by using the GA and how to promote the computational efficiency in the more grids case. These issues deserve further research.

Originality/value
The purpose of this paper is to improve the existing results by making the following three distinctive contributions: a rigorous mathematical formulation of the path planning optimization problem is formulated; a general grid-based representation (2n × 2n) is proposed to describe the workspace of the mobile robots to facilitate the implementation of the GA where n is chosen according to the trade-off between the accuracy and the computational burden; and the control points of the Bezier curve are directly linked to the optimization criteria so that the generated paths are guaranteed to be optimal without any need for smoothing afterwards.
Bio-inspired approach to invariant recognition and classification of fabric weave patterns and yarn color
Authors: Khan Babar , Han Fang , Wang Zhijie , Masood Rana J. 
Published: April 2016

Purpose
This paper aims to propose a biologically inspired processing architecture to recognize and classify fabrics with respect to the weave pattern (fabric texture) and yarn color (fabric color).

Design/methodology/approach
By using the fabric weave patterns image identification system, this study analyzed the fabric image based on the Hierarchical-MAX (HMAX) model of computer vision, to extract feature values related to texture of fabric. Red Green Blue (RGB) color descriptor based on opponent color channels simulating the single opponent and double opponent neuronal function of the brain is incorporated in to the texture descriptor to extract yarn color feature values. Finally, support vector machine classifier is used to train and test the algorithm.

Findings
This two-stage processing architecture can be used to construct a system based on computer vision to recognize fabric texture and to increase the system reliability and accuracy. Using this method, the stability and fault tolerance (invariance) was improved.

Originality/value
Traditionally, fabric texture recognition is performed manually by visual inspection. Recent studies have proposed automatic fabric texture identification based on computer vision. In the identification process, the fabric weave patterns are recognized by the warp and weft floats. However, due to the optical environments and the appearance differences of fabric and yarn, the stability and fault tolerance (invariance) of the computer vision method are yet to be improved. By using our method, the stability and fault tolerance (invariance) was improved.
Bio-inspired neural network with application to license plate recognition: hysteretic ELM approach
Authors: Chen Liang , Cui Leitao , Huang Rong , Ren Zhengyun 
Published: April 2016

Purpose
This paper aims to present a bio-inspired neural network for improvement of information processing capability of the existing artificial neural networks.

Design/methodology/approach
In the network, the authors introduce a property often found in biological neural system – hysteresis – as the neuron activation function and a bionic algorithm – extreme learning machine (ELM) – as the learning scheme. The authors give the gradient descent procedure to optimize parameters of the hysteretic function and develop an algorithm to online select ELM parameters, including number of the hidden-layer nodes and hidden-layer parameters. The algorithm combines the idea of the cross validation and random assignment in original ELM. Finally, the authors demonstrate the advantages of the hysteretic ELM neural network by applying it to automatic license plate recognition.

Findings
Experiments on automatic license plate recognition show that the bio-inspired learning system has better classification accuracy and generalization capability with consideration to efficiency.

Originality/value
Comparing with the conventional sigmoid function, hysteresis as the activation function enables has two advantages: the neuron’s output not only depends on its input but also on derivative information, which provides the neuron with memory; the hysteretic function can switch between the two segments, thus avoiding the neuron falling into local minima and having a quicker learning rate. The improved ELM algorithm in some extent makes up for declining performance because of original ELM’s complete randomness with the cost of a litter slower than before.
A novel path planning method for biomimetic robot based on deep learning
Authors: Lu Yang , Yi Shujuan , Liu Yurong , Ji Yuling 
Published: April 2016

Purpose
This paper aims to design a multi-layer convolutional neural network (CNN) to solve biomimetic robot path planning problem.

Design/methodology/approach
At first, the convolution kernel with different scales can be obtained by using the sparse auto encoder training algorithm; the parameter of the hidden layer is a series of convolutional kernel, and the authors use these kernels to extract first-layer features. Then, the authors get the second-layer features through the max-pooling operators, which improve the invariance of the features. Finally, the authors use fully connected layers of neural networks to accomplish the path planning task.

Findings
The NAO biomimetic robot respond quickly and correctly to the dynamic environment. The simulation experiments show that the deep neural network outperforms in dynamic and static environment than the conventional method.

Originality/value
A new method of deep learning based biomimetic robot path planning is proposed. The authors designed a multi-layer CNN which includes max-pooling layer and convolutional kernel. Then, the first and second layers features can be extracted by these kernels. Finally, the authors use the sparse auto encoder training algorithm to train the CNN so as to accomplish the path planning task of NAO robot.
Improved GA and Pareto optimization-based facial expression recognition
Authors: Wang Fowei , Shen Bo , Sun Shaoyuan , Wang Zidong 
Published: April 2016

Purpose
The purpose of this paper is to improve the accuracy of the facial expression recognition by using genetic algorithm (GA) with an appropriate fitness evaluation function and Pareto optimization model with two new objective functions.

Design/methodology/approach
To achieve facial expression recognition with high accuracy, the Haar-like features representation approach and the bilateral filter are first used to preprocess the facial image. Second, the uniform local Gabor binary patterns are used to extract the facial feature so as to reduce the feature dimension. Third, an improved GA and Pareto optimization approach are used to select the optimal significant features. Fourth, the random forest classifier is chosen to achieve the feature classification. Subsequently, some comparative experiments are implemented. Finally, the conclusion is drawn and some future research topics are pointed out.

Findings
The experiment results show that the proposed facial expression recognition algorithm outperforms ones in the existing literature in terms of both the actuary and computational time.

Originality/value
The GA and Pareto optimization algorithm are combined to select the optimal significant feature. To improve the accuracy of the facial expression recognition, the GA is improved by adjusting an appropriate fitness evaluation function, and a new Pareto optimization model is proposed that contains two objective functions indicating the achievements in minimizing within-class variations and in maximizing between-class variations.