bluuebunny/crossref_metadata_2025 huggingface dataset:
A role for maternally derived myokines to optimize placental function and fetal growth across gestation
Authors: Dubé Chantal , Aguer Céline , Adamo Kristi , Bainbridge Shannon
Published: January 2017

Exercise during pregnancy is associated with improved health outcomes for both mother and baby, including a reduced risk of future obesity and susceptibility to chronic diseases. Overwhelming evidence demonstrates a protective effect of maternal exercise against fetal birth weight extremes, reducing the rates of both large- and small-for-gestational-age infants. It is speculated that this protective effect is mediated in part through exercise-induced regulation of maternal physiology and placental development and function. However, the specific mechanisms through which maternal exercise regulates these changes remain to be discovered. We hypothesize that myokines, a collection of peptides and cytokines secreted from contracting skeletal muscles during exercise, may be an important missing link in the story. Myokines are known to reduce inflammation, improve metabolism and enhance macronutrient transporter expression and activity in various tissues of nonpregnant individuals. Little research to date has focused on the specific roles of the myokine secretome in the context of pregnancy; however, it is likely that myokines secreted from exercising skeletal muscles may modulate the maternal milieu and directly impact the vital organ of pregnancy—the placenta. In the current review, data in strong support of this potential role of myokines will be presented, suggesting myokine secretion as a key mechanism through which maternal exercise optimizes fetal growth trajectories. It is clear that further research is warranted in this area, as knowledge of the biological roles of myokines in the context of pregnancy would better inform clinical recommendations for exercise during pregnancy and contribute to the development of important therapeutic interventions.
Population biology of infectious diseases shared by wild and farmed fish
Authors: Krkošek Martin
Published: January 2017

Global fisheries landings ceased increasing decades ago, causing an increasing shortfall in wild seafood supply and an expansion of aquaculture. The abundance of domesticated fishes now dwarfs related wild fishes in some coastal seas, changing the dynamics of their infectious diseases. Transport and trade of seafood, feed, eggs, and broodstock bring pathogens into new regions and into contact with naïve hosts. Density-dependent transmission creates threshold effects where disease can abruptly switch from endemic to epizootic dynamics. Hydrodynamics allow pathogens to disperse broadly, interconnecting farms into metapopulations of domesticated host fish in regions that also support related species of wild fish. Spillover and spillback dynamics of pathogen transmission between wild and farmed fish can create novel transmission pathways or bioamplify pathogen abundance, potentially depressing or endangering wild fish. Mortality from natural predator–prey interactions may be synergistic or compensatory with these increased infections. Domestic environments may favour the evolution of undesirable pathogen traits, such as virulence and drug resistance, leading to the emergence of strains that cause high mortality and (or) evade treatment. Overall, these changes to the dynamics of infectious disease in coastal seas impose new constraints on the sustainability of both wild and farmed fish.
Cloudiness regulates gross primary productivity of a poplar plantation under different environmental conditions
Authors: Xu Hang , Zhang Zhiqiang , Chen Jiquan , Zhu Mengxun , Kang Manchun
Published: January 2017

Cloud cover regulates the gross primary productivity (GPP) of forest ecosystems by changing the radiation component and other environmental factors. In this study, we used an open-path eddy covariance system and microclimate sensors installed over a poplar plantation in northern China to measure the carbon exchange and climate variables during the mid-growing seasons (June to August) in 2014 and 2015. The results indicated that the GPP of the plantation peaked when the clearness index (CI) was between 0.45 and 0.65, at which point diffuse photosynthetically active radiation (PARdif) had reached its maximum. Cloudy skies increased the maximum ecosystem photosynthetic capacity (Pmax) by 28% compared with clear skies. PARdif and soil moisture were the most and the least crucial drivers for photosynthetic productivity of the plantation under cloudy skies, respectively. The ecosystem photosynthetic potential was higher under lower vapor pressure deficit (VPD < 1.5 kPa), lower air temperature (Ta < 30 °C), and nonstressed conditions (REW > 0.4) for cloudy skies due to effects of Ta and VPD on stoma. Overall, our research highlighted the importance of cloud-induced radiation component change and environmental variation in quantifying the GPP of forest ecosystems.
Tree squirrel abundance and demography in managed coniferous forests of British Columbia are within the range of natural fluctuations of old-growth stands
Authors: Sullivan Thomas P. , Ransome Douglas B. , Sullivan Druscilla S. , Lindgren Pontus M.F. , Klenner Walt
Published: January 2017

The American red squirrel (Tamiasciurus hudsonicus Exrleben) and northern flying squirrel (Glaucomys sabrinus Shaw) are important mammal species in coniferous forests that are widely distributed across temperate and boreal ecological zones. Although T. hudsonicus and G. sabrinus apparently prefer late-successional forests, their population dynamics show no clear pattern in young second-growth and old-growth conifer forests. We used a compilation of study results that had standardized methodology and sampling effort to compare tree squirrel responses across a range of forest conditions. We tested the hypotheses (H) that abundance, reproduction, recruitment, and survival would be higher in (H1) old-growth than second-growth stands, (H2) unthinned than thinned second-growth stands, and (H3) lightly than heavily thinned stands. Tree squirrel populations in old-growth stands were considered the “standard” treatment to which other treatments in second-growth stands (unthinned and variously thinned) were compared. Thinned stands were grouped into low, medium, and high densities of trees. Datasets from seven published studies included 2804 Tamiasciurus and 837 G. sabrinus individuals, 25 study years, and 158 trapping periods. Mean abundance of Tamiasciurus was similar among treatment stands, ranging from 0.62 to 1.29·ha−1. Mean numbers of G. sabrinus were highest in old-growth stands at 0.65·ha−1, followed by the low- and medium-density stands at 0.50·ha−1, the high-density stands at 0.25·ha−1, and finally the unthinned second-growth stands at a low of 0.12·ha−1. In terms of effect size, mean proportional change in abundance, relative to that within old-growth stands, of both squirrel species in the three thinned stands were within the range of natural fluctuations in old-growth stands. Populations of Tamiasciurus in the unthinned stands were not within the range of fluctuations in the old-growth stands. Mean number of successful pregnancies and total recruits were similar among stands for Tamiasciurus, with variability in female breeding and winter survival. Mean number of recruits of G. sabrinus was highest in old-growth stands with no other differences in demographic attributes among stands. The biological significance of these differences in demographic variables was small in terms of effect sizes. Tamiasciurus and G. sabrinus seem to persist in a relatively broad range of young managed forest habitats, as well as in old-growth stands.
General theories of reflection and transmission scratch holograms
Authors: Li Bingjian , Kang Zi Yang , Lin Jiahuang , Yeo Ye , Tan Guoxian
Published: January 2017

Scratch holograms can be created easily and the associated interesting phenomena may be observed in daily life. In this paper, general and quantitative theories of scratch holograms were derived and presented. Both the reflection case where a scratch hologram reflects light, and the transmission case where it refracts and transmits light, were considered. A predictive model, which has not been presented in the literature, was developed. The model was able to solve for the position of the bright points along the scratches using a computational method. Extensive experimentation was carried out with scratch holograms of two designs to verify the model. Photographic evidence demonstrated extremely good fits with the theoretical predictions. The model was then used to theoretically simulate the 3D spatial positions of the hologram and also quantify distortion present in the images to illustrate novel real-life applications of the theories presented.
On the gradient flows on Finsler manifolds
Authors: Shojaee Neda , Rezaii Morteza Mirmohammad
Published: January 2017

The purpose of this paper is to provide a general overview of a curvature functional in Finsler geometry and use its information to introduce the gradient flow on Finsler manifolds. For this purpose, we first make some differentiable structures on a domain of Finslerian functionals. Then by means of the global inner product and the Berger–Ebin Theorem, we make some decomposition for the tangent space of the manifold of all Finslerian metrics. Next, we study Akbar–Zadeh curvature functional as a Finslerian functional and we find the critical points of this functional in the pointwise conformal metric direction. Through this way, we introduce a gradient flow on compact Finsler manifold. Finally, we compare this new flow with introducing Ricci flow in Finsler geometry.
The Stark effect with minimum length
Authors: Louzada H. L. C. , Belich H.
Published: January 2017

We will study the splitting in the energy spectrum of the hydrogen atom subjected to an uniform electric field (Stark effect) with the Heisenberg algebra deformed leading to the minimum length. We will use the perturbation theory for cases not degenerate (n[Formula: see text]=[Formula: see text]1) and degenerate (n[Formula: see text]=[Formula: see text]2), along with known results of corrections in these levels caused by the minimum length applied purely to the hydrogen atom, so that we may find and estimate the corrections of minimum length applied to the Stark effect.
Effect of weak disorder on the BCS–BEC crossover in a two-dimensional Fermi gas
Authors: Khan Ayan , Tanatar B.
Published: January 2017

In this paper, we study the two-dimensional (2D) ultracold Fermi gas with weak impurity in the framework of mean-field theory where the impurity is introduced through Gaussian fluctuations. We have investigated the role of the impurity by studying the experimentally accessible quantities such as condensate fraction and equation of state of the ultracold systems. Our analysis reveals that at the crossover, the disorder enhances superfluidity, which we attribute to the unique nature of the unitary region and to the dimensional effect.
Graph state-based quantum authentication scheme
Authors: Liao Longxia , Peng Xiaoqi , Shi Jinjing , Guo Ying
Published: January 2017

Inspired by the special properties of the graph state, a quantum authentication scheme is proposed in this paper, which is implemented with the utilization of the graph state. Two entities, a reliable party, Trent, as a verifier and Alice as prover are included. Trent is responsible for registering Alice in the beginning and confirming Alice in the end. The proposed scheme is simple in structure and convenient to realize in the realistic physical system due to the use of the graph state in a one-way quantum channel. In addition, the security of the scheme is extensively analyzed and accordingly can resist the general individual attack strategies.
Specific heat and thermal conductivity of nanomaterials
Authors: Bhatt Sandhya , Kumar Raghuvesh , Kumar Munish
Published: January 2017

A model is proposed to study the size and shape effects on specific heat and thermal conductivity of nanomaterials. The formulation developed for specific heat is based on the basic concept of cohesive energy and melting temperature. The specific heat of Ag and Au nanoparticles is reported and the effect of size and shape has been studied. We observed that specific heat increases with the reduction of particle size having maximum shape effect for spherical nanoparticle. To provide a more critical test, we extended our model to study the thermal conductivity and used it for the study of Si, diamond, Cu, Ni, Ar, ZrO2, BaTiO3 and SrTiO3 nanomaterials. A significant reduction is found in the thermal conductivity for nanomaterials by decreasing the size. The model predictions are consistent with the available experimental and simulation results. This demonstrates the suitability of the model proposed in this paper.
Extension of Canonical Adjacency Matrices for Frequent Approximate Subgraph Mining on Multi-Graph Collections
Authors: Acosta-Mendoza Niusvel , Gago-Alonso Andrés , Carrasco-Ochoa Jesús Ariel , Martínez-Trinidad José Fco. , Medina-Pagola José E.
Published: January 2017

Into the data mining field, frequent approximate subgraph (FAS) mining has become an important technique with a broad spectrum of real-life applications. This fact is because several real-life phenomena can be modeled by graphs. In the literature, several algorithms have been reported for mining frequent approximate patterns on simple-graph collections; however, there are applications where more complex data structures, as multi-graphs, are needed for modeling the problem. But to the best of our knowledge, there is no FAS mining algorithm designed for dealing with multi-graphs. Therefore, in this paper, a canonical form (CF) for simple-graphs is extended to allow representing multi-graphs and a state-of-the-art algorithm for FAS mining is also extended for processing multi-graph collections by using the extended CF. Our experiments over different synthetic and real-world multi-graph collections show that the proposed algorithm has a good performance in terms of runtime and scalability. Additionally, we show the usefulness of the patterns computed by our algorithm in an image classification problem where images are represented as multi-graphs.
Adaptive Hashing with Sparse Modification for Scalable Image Retrieval
Authors: Zhang Lifang , Shen Qi , Li Defang , Feng Guocan , Tang Xin , Wang Patrick S.
Published: January 2017

Approximate Nearest Neighbor (ANN) search is a challenging problem with the explosive high-dimensional large-scale data in recent years. The promising technique for ANN search include hashing methods which generate compact binary codes by designing effective hash functions. However, lack of an optimal regularization is the key limitation of most of the existing hash functions. To this end, a new method called Adaptive Hashing with Sparse Modification (AHSM) is proposed. In AHSM, codes consist of vertices on the hypercube and the projection matrix is divided into two separate matrices. Data is rotated through a orthogonal matrix first and modified by a sparse matrix. Here the sparse matrix needs to be learned as a regularization item of hash function which is used to avoid overfitting and reduce quantization distortion. Totally, AHSM has two advantages: improvement of the accuracy without any time cost increasement. Furthermore, we extend AHSM to a supervised version, called Supervised Adaptive Hashing with Sparse Modification (SAHSM), by introducing Canonical Correlation Analysis (CCA) to the original data. Experiments show that the AHSM method stably surpasses several state-of-the-art hashing methods on four data sets. And at the same time, we compare three unsupervised hashing methods with their corresponding supervised version (including SAHSM) on three data sets with labels known. Similarly, SAHSM outperforms other methods on most of the hash bits.
Dangerous Bifurcations Revisited
Authors: Avrutin Viktor , Zhusubaliyev Zhanybai T. , Saha Arindam , Banerjee Soumitro , Sushko Irina , Gardini Laura
Published: January 2017

A dangerous border collision bifurcation has been defined as the dynamical instability that occurs when the basins of attraction of stable fixed points shrink to a set of zero measure as the parameter approaches the bifurcation value from either side. This results in almost all trajectories diverging off to infinity at the bifurcation point, despite the eigenvalues of the fixed points before and after the bifurcation being within the unit circle. In this paper, we show that similar bifurcation phenomena also occur when the stable orbit in question is of a higher periodicity or is chaotic. Accordingly, we propose a generalized definition of dangerous bifurcation suitable for any kind of attracting sets. We report two types of dangerous border collision bifurcations and show that, in addition to the originally reported mechanism typically involving singleton saddle cycles, there exists one more situation where the basin boundary is formed by a repelling closed invariant curve.
A Numerical Scheme for Computing Stable and Unstable Manifolds in Nonautonomous Flows
Authors: Balasuriya Sanjeeva
Published: January 2017

There are many methods for computing stable and unstable manifolds in autonomous flows. When the flow is nonautonomous, however, difficulties arise since the hyperbolic trajectory to which these manifolds are anchored, and the local manifold emanation directions, are changing with time. This article utilizes recent results which approximate the time-variation of both these quantities to design a numerical algorithm which can obtain high resolution in global nonautonomous stable and unstable manifolds. In particular, good numerical approximation is possible locally near the anchor trajectory. Nonautonomous manifolds are computed for two examples: a Rossby wave situation which is highly chaotic, and a nonautonomus (time-aperiodic) Duffing oscillator model in which the manifold emanation directions are rapidly changing. The numerical method is validated and analyzed in these cases using finite-time Lyapunov exponent fields and exactly known nonautonomous manifolds.
On the Theory of Intermittency in 1D Maps
Authors: del Rio Ezequiel , Elaskar Sergio
Published: January 2017

The classical theory of intermittency developed for return maps assumes uniform density of points reinjected from the chaotic to laminar region. Recently, we reported how the reinjection probability density (RPD) can be generalized. Estimation of the universal RPD is based on fitting a linear function to experimental or numerical data. Here we present an analytical approach to estimate the RPD. After this, we can get an analytic evaluation of the characteristic exponent traditionally used to characterize the intermittency type. The proposed theoretical method is general and very simple to use. It is compared with numerical computation, showing a good agreement between both. Our analytical results are compared with some celebrated classical numerical results on intermittency theory.
Study of the Bifurcation of a Multiple Limit Cycle of the Second Kind by Means of a Dulac–Cherkas Function: A Case Study
Authors: Grin Alexander , Schneider Klaus R.
Published: January 2017

We consider a generalized pendulum equation depending on the scalar parameter [Formula: see text] having for [Formula: see text] a limit cycle [Formula: see text] of the second kind and of multiplicity three. We study the bifurcation behavior of [Formula: see text] for [Formula: see text] by means of a Dulac–Cherkas function.
Dynamics of a Delayed HIV-1 Infection Model with Saturation Incidence Rate and CTL Immune Response
Authors: Guo Ting , Liu Haihong , Xu Chenglin , Yan Fang
Published: January 2017

In this paper, we investigate the dynamics of a five-dimensional virus model incorporating saturation incidence rate, CTL immune response and three time delays which represent the latent period, virus production period and immune response delay, respectively. We begin this model by proving the positivity and boundedness of the solutions. Our model admits three possible equilibrium solutions, namely the infection-free equilibrium [Formula: see text], the infectious equilibrium without immune response [Formula: see text] and the infectious equilibrium with immune response [Formula: see text]. Moreover, by analyzing corresponding characteristic equations, the local stability of each of the feasible equilibria and the existence of Hopf bifurcation at the equilibrium point [Formula: see text] are established, respectively. Further, by using fluctuation lemma and suitable Lyapunov functionals, it is shown that [Formula: see text] is globally asymptotically stable when the basic reproductive numbers for viral infection [Formula: see text] is less than unity. When the basic reproductive numbers for immune response [Formula: see text] is less than unity and [Formula: see text] is greater than unity, the equilibrium point [Formula: see text] is globally asymptotically stable. Finally, some numerical simulations are carried out for illustrating the theoretical results.
A Note on Phase Coherence of Chaotic Sets
Authors: Yang Xiao-Song , Wu Tiantian
Published: January 2017

The phase coherence phenomenon of chaotic motion is unique to continuous time dynamical systems and of significance in many disciplines such as nonlinear physics and biology. In this paper, we present a geometric description of phase coherence of chaotic motion and show that chaotic sets near a homoclinic orbit or heteroclinic cycle are phase coherent in this geometric setting under a mild condition.
Regularity of Milne problem with geometric correction in 3D
Authors: Guo Yan , Wu Lei
Published: January 2017

Consider the Milne problem with geometric correction in a 3D convex domain. Via bootstrapping arguments, we establish [Formula: see text]-regularity for its solutions. Combined with a uniform [Formula: see text]-estimate, such regularity leads to the validity of diffusive expansion for the neutron transport equation with diffusive boundary conditions.
Pseudo knots and an obstruction to cosmetic crossings
Authors: Dye Heather A.
Published: January 2017

Pseudo links have two crossing types: classical crossings and indeterminate crossings. They were first introduced by Hanaki as a possible tool for analyzing images produced by electron microscopy of DNA. A normalized bracket polynomial is defined for pseudo links and then used to construct an obstruction to cosmetic crossings in classical links.
Semi-invariant ξ⊥-Riemannian submersions from almost contact metric manifolds
Authors: Akyol Mehmet Akif , Sarı Ramazan , Aksoy Elif
Published: January 2017

As a generalization of anti-invariant [Formula: see text]-Riemannian submersions, we introduce semi-invariant [Formula: see text]-Riemannian submersions from Sasakian manifolds onto Riemannian manifolds. We give examples, investigating the geometry of foliations which arise from the definition of a Riemannian submersion and proving a necessary and sufficient condition for a semi-invariant [Formula: see text]-Riemannian submersion to be totally geodesic. Moreover, we study semi-invariant [Formula: see text]-Riemannian submersions with totally umbilical fibers.
Tectonostratigraphic framework and depositional history of the Cretaceous–Danian succession of the Danish Central Graben (North Sea) – new light on a mature area
Authors: van Buchem F. S. P. , Smit F. W. H. , Buijs G. J. A. , Trudgill B. , Larsen P.-H.
Published: January 2017

An integrated tectonic and sequence stratigraphic analysis of the Cretaceous and Danian of the Danish Central Graben has led to significant new insights critical for our understanding of the chalk facies as a unique cool-water carbonate system, as well as for the evaluation of its potential remaining economic significance.

A major regional unconformity in the middle of the Upper Cretaceous chalk has been dated as being of early Campanian age. It separates two distinctly different basin types: a thermal contraction early post-rift basin (Valanginian–Santonian), which was succeeded by an inversion tectonics-affected basin (Campanian–Danian). The infill patterns for these two basin types are dramatically different as a result of the changing influence of the tectonic, palaeoceanographic and eustatic controlling factors.

Several new insights are reported for the Lower Cretaceous: a new depositional model for chalk deposition along the basin margins on shallow shelves, which impacts reservoir quality trends; recognition of a late Aptian long-lasting sea-level lowstand (which hosts lowstand sandstone reservoirs in other parts of the North Sea Basin); and, finally, the observation that Barremian–Aptian sequences can be correlated from the Boreal to the Tethyan domain. In contrast, the Late Cretaceous sedimentation patterns have a strong synsedimentary local tectonic overprint (inversion) that influenced palaeoceanography through the intensification of bottom currents and, as a result, the depositional facies. In this context, four different chalk depositional systems are distinguished in the Chalk Group, with specific palaeogeography, depositional features and sediment composition.

The first formalization of the lithostratigraphic subdivision of the Chalk Group in the Danish Central Graben is proposed, as well as an addition to the Cromer Knoll Group.
From a Formalized Parallel Action Language to Its Efficient Code Generation
Authors: Llopard Ivan , Fabre Christian , Cohen Albert
Published: January 2017

Modeling languages propose convenient abstractions and transformations to handle the complexity of today’s embedded systems. Based on the formalism of the Hierarchical State Machine, they enable the expression of hierarchical control parallelism. However, they face two important challenges when it comes to modeling data-intensive applications: no unified approach that also accounts for data-parallel actions and no effective code optimization and generation flows.

We propose a modeling language extended with parallel action semantics and hierarchical indexed-state machines suitable for computationally intensive applications. Together with its formal semantics, we present an optimizing model compiler aiming for the generation of efficient data-parallel implementations.
Learning
k
for kNN Classification
Authors: Zhang Shichao , Li Xuelong , Zong Ming , Zhu Xiaofeng , Cheng Debo
Published: January 2017

The
K
Nearest Neighbor (kNN) method has widely been used in the applications of data mining and machine learning due to its simple implementation and distinguished performance. However, setting all test data with the same
k
value in the previous kNN methods has been proven to make these methods impractical in real applications. This article proposes to learn a correlation matrix to reconstruct test data points by training data to assign different
k
values to different test data points, referred to as the Correlation Matrix kNN (CM-kNN for short) classification. Specifically, the least-squares loss function is employed to minimize the reconstruction error to reconstruct each test data point by all training data points. Then, a graph Laplacian regularizer is advocated to preserve the local structure of the data in the reconstruction process. Moreover, an ℓ
1
-norm regularizer and an ℓ
2, 1
-norm regularizer are applied to learn different
k
values for different test data and to result in low sparsity to remove the redundant/noisy feature from the reconstruction process, respectively. Besides for classification tasks, the kNN methods (including our proposed CM-kNN method) are further utilized to regression and missing data imputation. We conducted sets of experiments for illustrating the efficiency, and experimental results showed that the proposed method was more accurate and efficient than existing kNN methods in data-mining applications, such as classification, regression, and missing data imputation.
A Distribution Separation Method Using Irrelevance Feedback Data for Information Retrieval
Authors: Zhang Peng , Yu Qian , Hou Yuexian , Song Dawei , Li Jingfei , Hu Bin
Published: January 2017

In many research and application areas, such as information retrieval and machine learning, we often encounter dealing with a probability distribution that is mixed by one distribution that is relevant to our task in hand and the other that is irrelevant and that we want to get rid of. Thus, it is an essential problem to separate the irrelevant distribution from the mixture distribution. This article is focused on the application in Information Retrieval, where relevance feedback is a widely used technique to build a refined query model based on a set of feedback documents. However, in practice, the relevance feedback set, even provided by users explicitly or implicitly, is often a mixture of relevant and irrelevant documents. Consequently, the resultant query model (typically a term distribution) is often a mixture rather than a true relevance term distribution, leading to a negative impact on the retrieval performance. To tackle this problem, we recently proposed a Distribution Separation Method (DSM), which aims to approximate the true relevance distribution by separating a seed irrelevance distribution from the mixture one. While it achieved a promising performance in an empirical evaluation with simulated explicit irrelevance feedback data, it has not been deployed in the scenario where one should automatically obtain the irrelevance feedback data. In this article, we propose a substantial extension of the basic DSM from two perspectives: developing a further regularization framework and deploying DSM in the automatic irrelevance feedback scenario. Specifically, in order to avoid the output distribution of DSM drifting away from the true relevance distribution when the quality of seed irrelevant distribution (as the input to DSM) is not guaranteed, we propose a DSM regularization framework to constrain the estimation for the relevance distribution. This regularization framework includes three algorithms, each corresponding to a regularization strategy incorporated in the objective function of DSM. In addition, we exploit DSM in automatic (i.e., pseudo) irrelevance feedback, by automatically detecting the seed irrelevant documents via three different document reranking methods. We have carried out extensive experiments based on various TREC datasets, in order to systematically evaluate the proposed methods. The experimental results demonstrate the effectiveness of our proposed approaches in comparison with various strong baselines.
Colors -- Messengers of Concepts
Authors: Jahanian Ali , Keshvari Shaiyan , Vishwanathan S. V. N. , Allebach Jan P.
Published: January 2017

We study the concept of color semantics by modeling a dataset of magazine cover designs, evaluating the model via crowdsourcing, and demonstrating several prototypes that facilitate color-related design tasks. We investigate a probabilistic generative modeling framework that expresses semantic concepts as a combination of color and word distributions -- color-word topics. We adopt an extension to Latent Dirichlet Allocation (LDA) topic modeling, called LDA-dual, to infer a set of color-word topics over a corpus of 2,654 magazine covers spanning 71 distinct titles and 12 genres. Although LDA models text documents as distributions over word topics, we model magazine covers as distributions over color-word topics. The results of our crowdsourcing experiments confirm that the model is able to successfully discover the associations between colors and linguistic concepts. Finally, we demonstrate several prototype applications that use the learned model to enable more meaningful interactions in color palette recommendation, design example retrieval, pattern recoloring, image retrieval, and image color selection.
The Evolution of Android Malware and Android Analysis Techniques
Authors: Tam Kimberly , Feizollah Ali , Anuar Nor Badrul , Salleh Rosli , Cavallaro Lorenzo
Published: January 2017

With the integration of mobile devices into daily life, smartphones are privy to increasing amounts of sensitive information. Sophisticated mobile malware, particularly Android malware, acquire or utilize such data without user consent. It is therefore essential to devise effective techniques to analyze and detect these threats. This article presents a comprehensive survey on leading Android malware analysis and detection techniques, and their effectiveness against evolving malware. This article categorizes systems by methodology and date to evaluate progression and weaknesses. This article also discusses evaluations of industry solutions, malware statistics, and malware evasion techniques and concludes by supporting future research paths.
Accessible Touchscreen Technology for People with Visual Impairments
Authors: Grussenmeyer William , Folmer Eelke
Published: January 2017

Touchscreens have become a de facto standard of input for mobile devices as they most optimally use the limited input and output space that is imposed by their form factor. In recent years, people who are blind and visually impaired have been increasing their usage of smartphones and touchscreens. Although basic access is available, there are still many accessibility issues left to deal with in order to bring full inclusion to this population. Many of the accessibility problems are complex; in the past decade, various solutions have been explored. This article provides a review of the current state of the art of touchscreen accessibility for people with visual impairments and identifies new directions for research.
An FFT Circuit for a Spectrometer of a Radio Telescope using the Nested RNS including the Constant Division
Authors: Nakahara Hiroki , Nakanishi Hiroyuki , Iwai Kazumasa , Sasao Tsutomu
Published: January 2017

A radio telescope analyzes radio frequency (RF) received from celestial objects. It consists of an antenna, a receiver, and a spectrometer. The spectrometer converts the time domain into the frequency domain by an FFT operation. This paper applies an FFT circuit based on nested residue number system (NRNS), which recursively decompose the RNS. It can decompose the MAC unit into circuits with small sizes. In the FFT using the NRNS, a MAC unit is decomposed into 4-bit ones realized by look-up tables of the FPGA. Also, to realize the scaling (truncation) circuit, we propose a constant division algorithm on the FPGA. The truncation is realized by the division of a dynamic range for a subset of moduli. We implemented the proposed NRNS FFT on the Xilinx Inc. Virtex 6 FPGA. Compared with a Xilinx Inc. binary FFT library, although the number of block RAMs (BRAMs) was increased by 38%, in the RNS FFT, the number of LUTs was decreased by 42-45% and the maximum clock frequency was increased by 38-74%. With this technique, we successfully implemented an FFT that satisfied the required size and speed specifications on an available FPGA, since the excessive number of LUTs was the bottleneck of the binary FFT.
Neural Network Based Reinforcement Learning Acceleration on FPGA Platforms
Authors: Su Jiang , Liu Jianxiong , Thomas David B. , Cheung Peter Y.K.
Published: January 2017

Deep Q-learning (DQN) is a recently proposed reinforcement learning algorithm where a neural network is applied as a non-linear approximator to its value function. The exploitation-exploration mechanism allows the training and prediction of the NN to execute simultaneously in an agent during its interaction with the environment. Agents often act independently on battery power, so the training and prediction must occur within the agent and on a limited power budget. In this work, We propose an FPGA acceleration system design for Neural Network Q-learning (NNQL). Our proposed system has high flexibility due to the support to run-time network parameterization, which allows neuroevolution algorithms to dynamically restructure the network to achieve better learning results. Additionally, the power consumption of our proposed system is adaptive to the network size because of a new processing element design. Based on our test cases on networks with hidden layer size ranging from 32 to 16384, our proposed system achieves 7x to 346x speedup compared to GPU implementation and 22x to 77x speedup to hand-coded CPU counterpart.
Online Budgeted Truthful Matching
Authors: Vaze Rahul , Coupechoux Marceau
Published: January 2017

An online truthful budgeted matching problem is considered for a bipartite graph, where the right vertices are available ahead of time, and individual left vertices arrive sequentially. On arrival of a left vertex, its edge utilities (or weights) to all the right vertices and a corresponding cost (or bid) are revealed. If a left vertex is matched to any of the right vertices, then it has to be paid at least as much as its cost. The problem is to match each left vertex instantaneously and irrevocably to any one of the right vertices, if at all, to find the maximum weight matching that is truthful, under a payment budget constraint. Truthfulness condition requires that no left vertex has any incentive of misreporting its cost. Assuming that the vertices arrive in an uniformly random order (secretary model) with arbitrary utilities, a truthful algorithm is proposed that is 24ß- competitive (where ß is the ratio of the maximum and the minimum utility) and satisfies the payment budget constraint. Direct applications of this problem include crowdsourcing auctions, and matching wireless users to cooperative relays in device-to-device enabled cellular network.
Competitive Rumor Spread in Social Networks
Authors: Lim Yongwhan , Ozdaglar Asuman , Teytelboym Alexander
Published: January 2017

We consider a setting in which two firms compete to spread rumors in a social network. Firms seed their rumors simultaneously and rumors propagate according to the linear threshold model. Consumers have (randomly drawn) heterogeneous thresholds for each product. Using the concept of cascade centrality introduced by [6], we provide a sharp characterization of networks in which games admit purestrategy Nash equilibria (PSNE). We provide tight bounds for the efficiency of these equilibria and for the inequality in firms' equilibrium payoffs. When the network is a tree, the model is particularly tractable.
Timelines are Publisher-Driven Caches
Authors: Reiffers-Masson Alexandre , Hargreaves Eduardo , Altman Eitan , Caarls Wouter , Menasché Daniel S.
Published: January 2017

Cache networks are one of the building blocks of information centric networks (ICNs). Most of the recent work on cache networks has focused on networks of request driven caches, which are populated based on users requests for content generated by publishers. However, user generated content still poses the most pressing challenges. For such content timelines are the de facto sharing solution.

In this paper, we establish a connection between timelines and publisher-driven caches. We propose simple models and metrics to analyze publisher-driven caches, allowing for variable-sized objects. Then, we design two efficient algorithms for timeline workload shaping, leveraging admission and price control in order, for instance, to aid service providers to attain prescribed service level agreements.
Investigating a two headed monster
Authors: Carrillo Jesus Cano , Jimenez-Gomez Carlos E. , Falcone Francisco
Published: January 2017

This article discusses the intersection of information and communication technologies in the context of vast government enterprises. While e-government in practice is only recently a multi-sector discipline, current research demonstrates it is a two-headed monster: on the one hand requiring critical social and political expertise, and, on the other, requiring an excellent engineering infrastructure. As a result, e-government is becoming a paradigmatic crossroad with the citizen at the center, and technology as the tool enabling those citizens to contribute to the social and political component. Here we highlight the evolution from simple electronic support of normal government processes to the emerging digital revolution, where citizens collaborate with government to form a true e-government along with challenges in implementing this vision.
Route Design Model of Feeder Bus Service for Urban Rail Transit Stations
Authors: Zhu Zhenjun , Guo Xiucheng , Zeng Jun , Zhang Shengrui
Published: January 2017

As an important part of urban public transportation systems, the feeder bus fills a service gap left by rail transit, effectively extending the range of rail transit’s service and solving the problem of short‐distance travel and interchanges. By defining the potential demand of feeder bus services and considering its relationship with the traffic demands of corresponding staging areas, the distance between road and rail transit, and the repetition factor of road bus lines, this paper established a potential demand model of roads by opening feeder bus services and applying a logit model for passenger flow distribution. Based on a circular route model, a route starting and ending at urban rail transit stations was generated, and a genetic algorithm was then applied to solve it. The Wei‐Fang community of Shanghai was selected as the test area. Per the model and algorithm, the feeder route length was conformed to a functional orientation of short‐distance travel and the feeder service of a feeder bus; the route mostly covered where conventional bus lines were fewer, which is a finding that is in agreement with the actual situation; the feasibility of the model and algorithm was verified.
Exploiting Wireless Received Signal Strength Indicators to Detect Evil-Twin Attacks in Smart Homes
Authors: Tang Zhanyong , Zhao Yujie , Yang Lei , Qi Shengde , Fang Dingyi , Chen Xiaojiang , Gong Xiaoqing , Wang Zheng
Published: January 2017

Evil-Twin is becoming a common attack in smart home environments where an attacker can set up a fake AP to compromise the security of the connected devices. To identify the fake APs, The current approaches of detecting Evil-Twin attacks all rely on information such as SSIDs, the MAC address of the genuine AP, or network traffic patterns. However, such information can be faked by the attacker, often leading to low detection rates and weak protection. This paper presents a novel Evil-Twin attack detection method based on the received signal strength indicator (RSSI). Our approach considers the RSSI as a fingerprint of APs and uses the fingerprint of the genuine AP to identify fake ones. We provide two schemes to detect a fake AP in two different scenarios where the genuine AP can be located at either a single or multiple locations in the property, by exploiting the multipath effect of the Wi-Fi signal. As a departure from prior work, our approach does not rely on any professional measurement devices. Experimental results show that our approach can successfully detect 90% of the fake APs, at the cost of a one-off, modest connection delay.
Intelligent Vehicle Embedded Sensors Fault Detection and Isolation Using Analytical Redundancy and Nonlinear Transformations
Authors: Pous Nicolas , Gingras Denis , Gruyer Dominique
Published: January 2017

This work proposes a fault detection architecture for vehicle embedded sensors, allowing to deal with both system nonlinearity and environmental disturbances and degradations. The proposed method uses analytical redundancy and a nonlinear transformation to generate the residual value allowing the fault detection. A strategy dedicated to the optimization of the detection parameters choice is also developed.
Epidermal Growth Factor Signaling towards Proliferation: Modeling and Logic Inference Using Forward and Backward Search
Authors: Riesco Adrián , Santos-Buitrago Beatriz , De Las Rivas Javier , Knapp Merrill , Santos-García Gustavo , Talcott Carolyn
Published: January 2017

In biological systems, pathways define complex interaction networks where multiple molecular elements are involved in a series of controlled reactions producing responses to specific biomolecular signals. These biosystems are dynamic and there is a need for mathematical and computational methods able to analyze the symbolic elements and the interactions between them and produce adequate readouts of such systems. In this work, we use rewriting logic to analyze the cellular signaling of epidermal growth factor (EGF) and its cell surface receptor (EGFR) in order to induce cellular proliferation. Signaling is initiated by binding the ligand protein EGF to the membrane-bound receptor EGFR so as to trigger a reactions path which have several linked elements through the cell from the membrane till the nucleus. We present two different types of search for analyzing the EGF/proliferation system with the help of Pathway Logic tool, which provides a knowledge-based development environment to carry out the modeling of the signaling. The first one is a standard (forward) search. The second one is a novel approach based onnarrowing, which allows us to trace backwards the causes of a given final state. The analysis allows the identification of critical elements that have to be activated to provoke proliferation.
Ciprofloxacin Controlled-Solid Lipid Nanoparticles: Characterization, In Vitro Release, and Antibacterial Activity Assessment
Authors: Shazly Gamal A.
Published: January 2017

The objective of this research was to formulate ciprofloxacin (CIP) in solid lipid nanoparticles (SLNs) in an attempt to develop a controlled drug delivery system. An ultrasonic melt-emulsification method was used for preparing CIP-loaded SLNs. Key findings included that SLNs were successfully produced with average particle sizes ranging from 165 to 320 nm and polydispersity index in the range of 0.18–0.33. High entrapment efficiency values were reported in all formulations. The atomic force scanning microscopic images showed spherical shape with the size range closer to those found by the particle size analyzer. CIP release exhibited controlled-release behavior with various lipids. Ciprofloxacin solid lipid nanoparticles formula containing stearic acid (CIPSTE) displayed the strongest burst effect and the most rapid release rate. The release data revealed a better fit to the Higuchi diffusion model. After storing the CIPSTE formula at room temperature for 120 days, no significant difference in particle size and zeta potential was found. CIP-loaded SLNs exhibited superior antibacterial activity. Incorporation of CIP into SLNs leads to controlled release and a superior antibacterial effect of CIP.
A New Capacitor-Less Buck DC-DC Converter for LED Applications
Authors: Al-Absi Munir , Khalifa Zainulabideen , Hussein Alaa
Published: January 2017

In this paper, a new capacitor-less DC-DC converter is proposed to be used as a light emitting diode (LED) driver. The design is based on the utilization of the internal capacitance of the LED to replace the smoothing capacitor. LED lighting systems usually have many LEDs for better illumination that can reach multiple tens of LEDs. Such configuration can be utilized to enlarge the total internal capacitance and hence minimize the output ripple. Also, the switching frequency is selected such that a minimum ripple appears at the output. The functionality of the proposed design is confirmed experimentally and the efficiency of the driver is 85% at full load.
A New Iterative Numerical Continuation Technique for Approximating the Solutions of Scalar Nonlinear Equations
Authors: Antoni Grégory
Published: January 2017

The present study concerns the development of a new iterative method applied to a numerical continuation procedure for parameterized scalar nonlinear equations. Combining both a modified Newton’s technique and a stationary-type numerical procedure, the proposed method is able to provide suitable approximate solutions associated with scalar nonlinear equations. A numerical analysis of predictive capabilities of this new iterative algorithm is addressed, assessed, and discussed on some specific examples.