bluuebunny/crossref_metadata_2025 huggingface dataset:
Referral facility CT perfusion prior to inter-facility transfer in patients undergoing mechanical thrombectomy
Authors: Aghaebrahim Amin , Sauvageau Eric , Aguilar-Salinas Pedro , Cortez Gustavo , Santos Roberta , Hanel Ricardo A
Published: December 2017

Background and purpose

The use of CT perfusion (CTP) imaging at a referring hospital is feasible and may shorten the door to puncture time for patients with acute ischemic stroke.

Methods

We conducted a single center retrospective review of a prospectively maintained database of consecutive ischemic stroke patients transferred to our center for consideration of endovascular therapy. Patients were divided into two groups. Group 1 consisted of patients transferred from facilities where CTP (using automated RAPID software) was routinely performed and group 2 consisted of patients transferred from facilities that did not perform perfusion imaging.

Results

We identified a total of 132 patients, all of whom were transferred to our center, from April 2014 to April 2017. There were no differences in baseline characteristics between the two groups. A total of 34 patients were transferred from a facility after CTP (group 1) and 98 were transferred from a facility with no CTP (group 2). Door to puncture time was significantly shorter for patients in group 1 compared with those in group 2 (median 12 (IQR 8–16) min and 48.5 (32.8–71.8) min, respectively; P<0.001). Despite obtaining additional pre-transfer imaging in group 1, there was no difference in door in and door out times at the referring facilities compared with group 2.

Conclusions

We found that triaging from a primary stroke center after CTP RAPID was feasible and significantly reduced the door to puncture time without any significant delay in the transfer process.
Dietary supplementation with Allium hirtifolium and/or Astragalus hamosus improved memory and reduced neuro-inflammation in the rat model of Alzheimer’s disease
Authors: Bahaeddin Zahra , Yans Asal , Khodagholi Fariba , Sahranavard Shamim
Published: December 2017

Allium hirtifolium Boiss and Astragalus hamosus L. are mentioned in Iranian traditional medicine documentation as therapy for a kind of dementia with the features and symptoms similar to those of Alzheimer’s disease (AD). In the present study, the effects of these herbs on neuro-inflammation and memory have been evaluated as new therapies in amyloid beta (Aβ)-induced memory impairment model. Separate groups of rats were fed with A. hirtifolium or A. hamosus extract (both 100 mg/(kg·day)−1) started 1 week before stereotaxic surgery to 24 h before behavioral testing (totally, for 16 successive days). The effects of oral administration of mentioned extracts on the memory and neuro-inflammation were assessed in the Aβ-injected rats. The results of this study showed that oral administration of both A. hirtifolium and A. hamosus improved the memory, examined by using Y-maze test and shuttle box apparatus. Also, Western blotting analysis of cyclooxygenase-2, interleukin-1β, and tumor necrosis factor-α showed that these herbs have ameliorating effects against the neuro-inflammation caused by Aβ. These findings suggest that the use of A. hirtifolium and A. hamosus as herbal therapy may be suitable for decreasing AD-related symptoms and treatment of other neurodegenerative disorders.
Lateral compression response of overlapping jet-grout columns with geometric imperfections in radius and position
Authors: Liu Yong , Pan Yutao , Sun Miaomiao , Hu Jun , Yao Kai
Published: December 2017

Spatial variability in the radius of a jet-grout column is commonly encountered in practice. Although various prediction models for the column radius are available, they have been generally used to predict a nominal radius. The radius variation within a column has been seldom considered. In this study, the intracolumn radius variation was simulated as a lognormal stochastic process. This was done based on the existing prediction models where the column radius can be correlated with the undrained shear strength of in situ soils. A slab consisting of overlapping jet-grout columns was considered. The slab serves as an earth-retaining stabilizing structure in a deep excavation. The effects of radius variation on the mass performance of the slab were examined with the finite-element method. In addition, the positioning errors in jet-grout columns were also investigated. Owing to the random nature of the radius variation, Monte-Carlo simulations were performed to estimate the statistical characteristics of the mass performance of the slab. A strength reduction factor was introduced and tabulated to account for the effects of geometric imperfections in the column radius and column position. With the strength reduction factor, practitioners could quantitatively evaluate the effects of these geometric imperfections in design considerations. Practical recommendations on the column length and column spacing were also proposed.
Mechanisms by which basal branches suppress axillary bud outgrowth in pea (Pisum sativum)
Authors: Thomas R.G. , Hay M.J.M.
Published: December 2017

This study examined whether the strong inhibitory influences of basal branches on axillary bud outgrowth seen in Trifolium repens L. similarly occur in Pisum sativum L. Mechanisms by which basal branches in P. sativum suppress bud outgrowth were assessed using treatment combinations of main stem decapitation and excision, girdling, and (or) disbudding of basal branches. The combination of decapitation with basal branch excision provided a new avenue for the investigation of correlative suppression of bud outgrowth. The results revealed a dual suppressive action of basal branch buds: girdling of basal branches confirmed they act via export of an inhibitory influence, but also demonstrated, for the first time in P. sativum, their role as competitive sinks for bud outgrowth stimulus. Although all of the axillary buds on the main stem had similar intrinsic potential for outgrowth, sensitivity to these suppressive influences varied with position on the stem. This suppressive influence of basal branches was, like apical dominance, a major influence on the regulation of bud outgrowth. The finding in P. sativum that basal branches suppress bud outgrowth via their action as competitive sinks for an outgrowth stimulus, as they do in nodally rooting clonal herbs, suggests further investigation of this process is warranted.
Discrimination between a group of three-parameter distributions for hydro-meteorological frequency modeling
Authors: Ba Ismaila , Ashkar Fahim
Published: December 2017

We recommend methods of discrimination between some three-parameter distributions used in hydro-meteorological frequency modeling. Discriminations are between model pairs belonging to the group (generalized extreme value (GEV), Pearson Type III (P3), generalized logistic (GLO)). To assess the fit of these distributions to data, the Akaike information criterion, Bayesian information criterion, and (or) goodness-of-fit measures are commonly employed. However, it is difficult to estimate the discrimination power and bias of these methods when used with three-parameter distributions. Consequently, we propose two alternative tools and assess their performance. Both tools are based on a sample transformation to normality followed by applying a powerful statistic for testing normality, such as the Shapiro-Wilk or the probability plot correlation coefficient statistic. While arriving at recommendations for discriminating between the (GEV, GLO) and (P3, GLO) pairs of models, we show that the discrimination power between the P3 and GEV distributions can be rather low.
Habitat suitability modeling based on a spatiotemporal model: an example for cusk in the Gulf of Maine
Authors: Runnebaum Jocelyn , Guan Lisha , Cao Jie , O’Brien Loretta , Chen Yong
Published: December 2017

Habitat use and distribution is a critical aspect in the management and conservation of a species, particularly for those in decline. Habitat suitability indices (HSI) are a common method of habitat mapping dependent on empirical data that can easily lead to misunderstanding the spatiotemporal dynamics of marine species experiencing population decline and density-dependent catchability within surveys. This is especially true when only a single monitoring program with limited spatiotemporal coverage is used. A delta-generalized linear mixed model was used to combine trawl and longline surveys to predict density estimates for cusk (Brosme brosme) in unsampled locations for use in HSIs. Catchability was estimated for longline and trawl gear without having an estimate of area fished for the longline survey. HSIs performed better using model-based density estimates from multiple surveys compared with sample-based abundance indices from a single survey. The increased spatial resolution can better inform the HSIs by providing information where the survey programs did not sample. This study provides a novel approach for integrating data from different monitoring programs for habitat modeling.
A real-time method to predict social media popularity
Authors: Chen Xiao , Lu Zhe-Ming
Published: December 2017

How to predict the future popularity of a message or video on online social media (OSM) has long been an attractive problem for researchers. Although many difficulties are still ahead, recent studies suggest that temporal and topological features of early adopters generally play a very important role. However, with the increase of the adopters, the feature space will grow explosively. How to select the most effective features is still an open issue. In this work, we investigate several feature extraction methods over the Twitter platform and find that most predictive power concentrates on the second half of the propagation period, and that not only a model trained on one platform generalizes well to others as previous works observed, but also a model trained on one dataset performs well on predicting the popularity for other datasets with different number of observed early adopters. According to these findings, at least for the best features by far, the data used to extract features can be halved without loss of evident accuracy and we provide a way to roughly predict the growth trend of a social-media item in real-time.
Multiphoton annihilation of monopolium
Authors: Fanchiotti H. , García Canal C. A. , Vento V.
Published: December 2017

We show that due to the large coupling constant of the monopole–photon interaction the annihilation of monopole–antimonopole and monopolium into many photons must be considered experimentally. For monopole–antimonopole annihilation and lightly bound monopolium, even in the less favorable scenario, multiphoton events (four and more photons in the final state) are dominant, while for strongly bound monopolium, although two photon events are important, four- and six-photon events are also sizable.
A model to study finite-size and magnetic effects on the phase transition of a fermion interacting system
Authors: Corrêa Emerson B. S. , Linhares César A. , Malbouisson Adolfo P. C.
Published: December 2017

We present a model to study the effects from external magnetic field, chemical potential and finite size on the phase structures of a massive four- and six-fermion interacting systems. These effects are introduced by a method of compactification of coordinates, a generalization of the standard Matsubara prescription. Through the compactification of the z-coordinate and of imaginary time, we describe a heated system with the shape of a film of thickness L, at temperature [Formula: see text] undergoing first- or second-order phase transition. We have found a strong dependence of the temperature transition on the coupling constants [Formula: see text] and [Formula: see text]. Besides inverse magnetic catalysis and symmetry breaking for both kinds of transition, we have found an inverse symmetry breaking phenomenon with respect to first-order phase transition.
Psychological Features for Automatic Text Summarization
Authors: Losada David E. , Parapar Javier
Published: December 2017

Automatically summarizing a document requires conveying the important points of a large document in only a few sentences. Extractive strategies for summarization are based on selecting the most important sentences from the input document(s). We claim here that standard features for estimating sentence importance can be effectively combined with innovative features that encode psychological aspects of communication. We employ Quantitative Text analysis tools for estimating psychological features and we inject them into state-of-the-art extractive summarizers. Our experiments demonstrate that this novel set of features is a good guidance for selecting salient sentences. Our empirical study concludes that psychological features are best suited for hard summarization cases. This motivated us to formally define and study the problem of predicting the difficulty of summarization. We propose a number of predictors to model the difficulty of every summarization problem and we evaluate several learning methods to perform this prediction task.
Detecting Deceptive Opinions: Intra and Cross-Domain Classification Using an Efficient Representation
Authors: Cagnina Leticia C. , Rosso Paolo
Published: December 2017

Online opinions play an important role for customers and companies because of the increasing use they do to make purchase and business decisions. A consequence of that is the growing tendency to post fake reviews in order to change purchase decisions and opinions about products and services. Therefore, it is really important to filter out deceptive comments from the retrieved opinions. In this paper we propose the character n-grams in tokens, an efficient and effective variant of the traditional character n-grams model, which we use to obtain a low dimensionality representation of opinions. A Support Vector Machines classifier was used to evaluate our proposal on available corpora with reviews of hotels, doctors and restaurants. In order to study the performance of our model, we make experiments with intra and cross-domain cases. The aim of the latter experiment is to evaluate our approach in a realistic cross-domain scenario where deceptive opinions are available in a domain but not in another one. After comparing our method with state-of-the-art ones we may conclude that using character n-grams in tokens allows to obtain competitive results with a low dimensionality representation.
Short Messages Spam Filtering Combining Personality Recognition and Sentiment Analysis
Authors: Ezpeleta Enaitz , Garitano Iñaki , Zurutuza Urko , Hidalgo José María Gómez
Published: December 2017

Currently, short communication channels are growing up due to the huge increase in the number of smartphones and online social networks users. This growth attracts malicious campaigns, such as spam campaigns, that are a direct threat to the security and privacy of the users. While most researches are focused on automatic text classification, in this work we demonstrate the possibility of improving current short messages spam detection systems using a novel method. We combine personality recognition and sentiment analysis techniques to analyze Short Message Services (SMS) texts. We enrich a publicly available dataset adding these features, first separately and after in combination, of each message to the dataset, creating new datasets. We apply several combinations of the best SMS spam classifiers and filters to each dataset in order to compare the results of each one. Taking into account the experimental results we analyze the real inuence of each feature and the combination of both. At the end, the best results are improved in terms of accuracy, reaching to a 99.01% and the number of false positive is reduced.
Markovian Software Reliability Modeling with Change-Point
Authors: Inoue Shinji , Yamada Shigeru
Published: December 2017

We discuss a Markovian modeling approach for software reliability assessment with the effects of change-point and imperfect debugging environment. Testing-time when the characteristic of the software failure-occurrence or fault-detection phenomenon changes notably is called change-point. Taking into account the effect at change-point in software reliability growth modeling is important to improve the accuracy of software reliability assessment. Our modeling approach describes a software reliability growth process with not only the effect of change-point but also the imperfect debugging activities based on a semi-Markov process for reflecting actual situation of debugging activities. Finally, we show numerical examples of our model for software reliability analysis and check the performance of our model with an existing Markovian software reliability growth model by using actual data.
Reliability Inference Based on the Three-Parameter Burr Type XII Distribution with Type II Censoring
Authors: Xin Hua , Zhu Jianping , Sun Junge , Zheng Chenlu , Tsai Tzong-Ru
Published: December 2017

The three-parameter Burr type XII distribution (3pBXIID) is quite flexible and contains a wide range of distribution shapes for fitting lifetime data. However, it is difficult to obtain reliable estimates of the 3pBXIID quantiles from censored samples for evaluating the reliability of lifetime data. In this work, a Metropolis–Hastings Markov chain Monte Carlo (M-H MCMC) procedure is proposed to obtain reliable maximum likelihood estimates (MLEs) of the 3pBXIID quantiles from a type II censored sample. Moreover, the parametric bootstrap percentile procedure is used to obtain the confidence interval of the quantile of the 3pBXIID. The performance of the proposed M-H MCMC method is evaluated in view of Monte Carlo simulations. Two examples, regarding the survival lifetimes of breast cancer patients and the reliability inference on the lifetimes of oil-well pumps for sucker-rod oil pumping systems, are applied to illustrate the applications of the proposed M-H MCMC method and bootstrap procedure.
Multi-Dimensional Software Tool for OSS Project Management Considering Cloud with Big Data
Authors: Tamura Yoshinobu , Yamada Shigeru
Published: December 2017

We discuss a method of software dependability assessment based on stochastic differential equation modeling in order to consider the interesting factors of the numbers of components, cloud applications and users. Then, we consider the determination of an optimum software maintenance time, minimizing the total expected software cost. In particular, we develop the three-dimensional AIR application for reliability and cost optimization analyses based on the proposed method. Moreover, the three-dimensional application based on NW.js, known as the latest technology, is developed in this paper. Furthermore, we show several numerical examples of the developed application software to evaluate the performance of software optimization and reliability assessment tools for the big data on cloud computing.
HIGH PRECISION SIMULATION ON SURFACE POTENTIAL OF CELLULAR ELECTRETS BY CHARGE SIMULATION METHOD
Authors: ZHANG J. W. , CHEN X. , ZHAO Y. S. , SU Z. Y. , LIU R. T.
Published: December 2017

Surface potential is one of the key properties of charge retain ability and energy storage performance of cellular electrets. Based on charge simulation method (CSM), a high precision simulation algorithm of surface potential of functional dielectrics is proposed in this paper, which can be applied to the simulations of cellular polypropylene after high-voltage corona discharge. In order to validate the modeling, the surface potential of insulating polymer after corona discharge is measured by an electrostatic measurement system and compared with simulation results based on CSM and finite element method (FEM). The result shows that the numerical simulation based on CSM is well consistent with the experimental data, which indicates that the modeling based on CSM can be used in the calculation and analysis of charge storage ability of capacitor and electrostatic generator based on functional electrets. Moreover, as simulation based on CSM has higher precision than FEM, investigation of surface charge storage ability and prediction of electrostatic hazards of insulating dielectrics could be realized by using CSM.
HOFFA’S FRACTURE WITH IRREDUCIBLE PATELLAR DISLOCATION: APPROACH TO AVOID COMPLICATIONS IN A RARE INJURY
Authors: Salunke Abhijeet Ashok , Savale Abhijeet , Dwivedi Chirayu , Pathak Subodh , Ughareja Prahald , Akbari Keyur , Jain Shantanu , Bhalodiya Parth , Mishra Shubham , Chen Yongsheng
Published: December 2017

Hoffa’s fracture is coronal oriented fracture of distal femur with the fracture line extending through the femoral condyles. Hoffa’s fracture is rarely associated with ipsilateral femur and tibia fractures. Proper clinical examination and radiographic evaluation is necessary to diagnose associated injuries around the knee joint with Hoffa’s fracture. Closed reduction of dislocated patella in emergency room and field triage should be avoided to prevent patellar tendon incarcenation, patellar tendon rupture and osteochondral damage. We report a rare case of Hoffa’s fracture with irreducible patellar dislocation and tibial intercondylar eminence fracture following road traffic accident.
The Generation of 3D Trimmed Elements for NURBS-Based Isogeometric Analysis
Authors: Im Chan-Kyung , Youn Sung-Kie
Published: December 2017

In conventional 3D NURBS-based isogeometric analysis (IGA), it is required to generate a discretized 3D model from the imported CAD model. Since a CAD file only contains surface information of the 3D object, generation of 3D mesh and trivariate basis functions are required for the IGA. In CAD system, the Boolean difference operation, so-called “trimming” is frequently employed for creating complex objects. To directly utilize the trimming information into analysis, trimmed elements need to be defined and their integration schemes are also needed. In this paper, trimmed elements searching, classification, decomposition and integration rules are presented. In the process, seven types of generalized trimmed elements are defined. Since covering all possible 3D geometries is not possible, three out of seven types of trimmed elements formed by extrusion are treated. The decomposition rule of trimmed elements is introduced and curved tetrahedral cells are adopted to integrate the trimmed elements. For numerical integration of curved tetrahedral cells, 3D NEFEM-like integration scheme has been developed. For the demonstration of the usage of the developed elements, two numerical examples of trimmed volume are treated.
Loop quantum cosmology scalar field models
Authors: Kleidis K. , Oikonomou V. K.
Published: December 2017

In this work, we use the Loop Quantum Cosmology (LQC) modified scalar–tensor reconstruction techniques in order to investigate how bouncing and inflationary cosmologies can be realized. With regard to the inflationary cosmologies, we shall be interested in realizing the intermediate inflation and the Type IV singular inflation, while with regard to bouncing cosmologies, we shall realize the superbounce and the symmetric bounce. In all the cases, we shall find the kinetic term of the LQC holonomy corrected scalar–tensor theory and the corresponding scalar potential. In addition, we shall include a study of the effective Equation of State (EoS), emphasizing at the early- and late-time eras. As we demonstrate, in some cases it is possible to have a nearly de Sitter EoS at the late-time era, a result that could be interpreted as the description of a late-time acceleration era. Also, in all cases we shall examine the dynamical stability of the LQC holonomy corrected scalar-tensor theory, and we shall confront the results with those coming from the corresponding classical dynamical stability theory. The most appealing cosmological scenario is that of a Type IV singular inflationary scenario, in which the singularity may occur at the late-time era. As we demonstrate, for this model, during the dark energy era, a transition from non-phantom to a phantom dark energy era occurs.
On rigidity and scalar curvature of Einstein-type manifolds
Authors: Mirshafeazadeh Mir Ahmad , Bidabad Behroz
Published: December 2017

Here, the scalar curvature of an Einstein-type manifold or equivalently an almost Yamabe quasi-soliton is explicitly determined in terms of its soliton function and some rigidity theorems are obtained. Among the others its shown; if the soliton function is negative, then every compact conformal Yamabe quasi-soliton is isometric to the standard Euclidean sphere.
A Novel Capacitive Negative Electrode Material of Fe3N
Authors: Zhao Zhi-Yun , Zhang Wei-Bin , Ma Xue-Jing , Li Kai , Zhao Yue , Gao Jian-Fei , Kang Long , Kong Ling-Bin
Published: December 2017

A capacitive negative electrode material of Fe3N has been synthesized via a simple precursor ammoniation treatment. Electrochemical measure shows that the electrode exhibits a specific capacitance of 270[Formula: see text]F[Formula: see text]g[Formula: see text] at a current density of 0.5[Formula: see text]A[Formula: see text]g[Formula: see text] in 6[Formula: see text]M KOH, 66% of the initial value remains at a specific current density of 5[Formula: see text]A[Formula: see text]g[Formula: see text]. Capacitance retention after 5000 cycles is about 61.5% of the initial capacitance. The electrochemical performance is relatively great in comparison with the literature reports of some Fe-based compounds. Because of the low cost and simple preparation method of Fe3N, the material is promising in electrochemical capacitive energy storage applications.
k-step adaptive cluster sampling with Horvitz–Thompson estimator
Authors: Zhu Guangyu , Fu Liyong
Published: December 2017

Adaptive cluster sampling (ACS) has been widely used for data collection of environment and natural resources. However, the randomness of its final sample size often impedes the use of this method. To control the final sample sizes, in this study, a [Formula: see text]-step ACS based on Horvitz–Thompson (HT) estimator was developed and an unbiased estimator was derived. The [Formula: see text]-step ACS-HT was assessed first using a simulated example and then using a real survey for numbers of plants for three species that were characterized by clustered and patchily spatial distributions. The effectiveness of this sampling design method was assessed in comparison with ACS Hansen–Hurwitz (ACS-HH) and ACS-HT estimators, and [Formula: see text]-step ACS-HT estimator. The effectiveness of using different [Formula: see text]-step sizes was also compared. The results showed that [Formula: see text]-step ACS-HT estimator was most effective and ACS-HH was the least. Moreover, stable sample mean and variance estimates could be obtained after a certain number of steps, but depending on plant species. [Formula: see text]-step ACS without replacement was slightly more effective than that with replacement. In [Formula: see text]-step ACS, the variance estimate of one-step ACS is much larger than other [Formula: see text]-step ACS ([Formula: see text]), but it is smaller than ACS. This implies that [Formula: see text]-step ACS is more effective than traditional ACS, besides, the final sample size can be controlled easily in population with big clusters.
Delay-Aware Quality Optimization in Cloud-Assisted Video Streaming System
Authors: Wu Jiyan , Cheng Bo , Yang Yuan , Wang Ming , Chen Junliang
Published: December 2017

Cloud-assisted video streaming has emerged as a new paradigm to optimize multimedia content distribution over the Internet. This article investigates the problem of streaming cloud-assisted real-time video to multiple destinations (e.g., cloud video conferencing, multi-player cloud gaming, etc.) over lossy communication networks. The user diversity and network dynamics result in the delay differences among multiple destinations. This research proposes Differentiated cloud-Assisted VIdeo Streaming (DAVIS) framework, which proactively leverages such delay differences in video coding and transmission optimization. First, we analytically formulate the optimization problem of joint coding and transmission to maximize received video quality. Second, we develop a quality optimization framework that integrates the video representation selection and FEC (Forward Error Correction) packet interleaving. The proposed DAVIS is able to effectively perform
differentiated
quality optimization for multiple destinations by taking advantage of the delay differences in cloud-assisted video streaming system. We conduct the performance evaluation through extensive experiments with the Amazon EC2 instances and Exata emulation platform. Evaluation results show that DAVIS outperforms the reference cloud-assisted streaming solutions in video quality and delay performance.
DeepSearch
Authors: Wang Peisong , Hu Qinghao , Fang Zhiwei , Zhao Chaoyang , Cheng Jian
Published: December 2017

Content-based image retrieval (CBIR) is one of the most important applications of computer vision. In recent years, there have been many important advances in the development of CBIR systems, especially Convolutional Neural Networks (CNNs) and other deep-learning techniques. On the other hand, current CNN-based CBIR systems suffer from high computational complexity of CNNs. This problem becomes more severe as mobile applications become more and more popular. The current practice is to deploy the entire CBIR systems on the server side while the client side only serves as an image provider. This architecture can increase the computational burden on the server side, which needs to process thousands of requests per second. Moreover, sending images have the potential of personal information leakage. As the need of mobile search expands, concerns about privacy are growing. In this article, we propose a fast image search framework, named DeepSearch, which makes complex image search based on CNNs feasible on mobile phones. To implement the huge computation of CNN models, we present a tensor Block Term Decomposition (BTD) approach as well as a nonlinear response reconstruction method to accelerate the CNNs involving in object detection and feature extraction. The extensive experiments on the ImageNet dataset and Alibaba Large-scale Image Search Challenge dataset show that the proposed accelerating approach BTD can significantly speed up the CNN models and further makes CNN-based image search practical on common smart phones.
Egocentric Hand Detection Via Dynamic Region Growing
Authors: Huang Shao , Wang Weiqiang , He Shengfeng , Lau Rynson W. H.
Published: December 2017

Egocentric videos, which mainly record the activities carried out by the users of wearable cameras, have drawn much research attention in recent years. Due to its lengthy content, a large number of ego-related applications have been developed to abstract the captured videos. As the users are accustomed to interacting with the target objects using their own hands, while their hands usually appear within their visual fields during the interaction, an egocentric hand detection step is involved in tasks like gesture recognition, action recognition, and social interaction understanding. In this work, we propose a dynamic region-growing approach for hand region detection in egocentric videos, by jointly considering hand-related motion and egocentric cues. We first determine seed regions that most likely belong to the hand, by analyzing the motion patterns across successive frames. The hand regions can then be located by extending from the seed regions, according to the scores computed for the adjacent superpixels. These scores are derived from four egocentric cues: contrast, location, position consistency, and appearance continuity. We discuss how to apply the proposed method in real-life scenarios, where multiple hands irregularly appear and disappear from the videos. Experimental results on public datasets show that the proposed method achieves superior performance compared with the state-of-the-art methods, especially in complicated scenarios.
A Factor-Based Bayesian Framework for Risk Analysis in Stochastic Simulations
Authors: Xie Wei , Li Cheng , Zhang Pu
Published: December 2017

Simulation is commonly used to study the random behaviors of large-scale stochastic systems with correlated inputs. Since the input correlation is often induced by latent common factors in many situations, to facilitate system diagnostics and risk management, we introduce a factor-based Bayesian framework that can improve both computational and statistical efficiency and provide insights for system risk analysis. Specifically, we develop a flexible Gaussian copula-based multivariate input model that can capture important properties in the real-world data. A nonparametric Bayesian approach is used to model marginal distributions, and it can capture the properties, including multi-modality and skewness. We explore the factor structure of the underlying generative processes for the dependence. Both input and simulation estimation uncertainty are characterized by the posterior distributions. In addition, we interpret the latent factors and estimate their effects on the system performance, which could be used to support diagnostics and decision making for large-scale stochastic systems. Our approach is supported by both asymptotic theory and empirical study.
Can we build the cyborg future we all deserve?
Authors: Schlesinger Ari
Published: December 2017

Knowing who we represent in HCI helps us understand what is at stake. Intersectionality can help us do better.
Digital and physical barriers to changing identities
Authors: Haimson Oliver L.
Published: December 2017

Social media sites often erect barriers to changing identities online, which can be similar to physical world barriers faced by marginalized groups. How can social media be designed to enable rather than constrain life changes?
Disability-disclosure preferences and practices in online dating communities
Authors: Bennett Cynthia L.
Published: December 2017

Based on a cooperative research project, this article explores the experience of dating online with a disability, contextualized with an overview of the historical connection between disability and asexuality. It concludes with ideas for decoupling this inaccurate association through online dating platforms.
Primal Dual Gives Almost Optimal Energy-Efficient Online Algorithms
Authors: Devanur Nikhil R. , Huang Zhiyi
Published: December 2017

We consider the problem of online scheduling of jobs on unrelated machines with dynamic speed scaling to minimize the sum of energy and weighted flow-time. We give an algorithm with an almost optimal competitive ratio for arbitrary power functions. (No earlier results handled arbitrary power functions for unrelated machines.) For power functions of the form
f
(
s
) =
s
α
for some constant α > 1, we get a competitive ratio of
O
(α / log α), improving upon a previous competitive ratio of
O
(α
2
) by Anand et al. (2012), along with a matching lower bound of Ω(α / log α). Further, in the resource augmentation model, with a 1+ ϵ speed up, we give a 2(1/ϵ + 1) competitive algorithm, with essentially the same techniques, improving the bound of 1 +
O
(1/ϵ
2
) by Gupta et al. (2010) and matching the bound of Anand et al. (2012) for the special case of fixed speed unrelated machines. Unlike the previous results most of which used an amortized local competitiveness argument or dual fitting methods, we use a primal-dual method, which is useful not only to analyze the algorithms but also to design the algorithm itself.
SCALO
Authors: Georgakoudis Giorgis , Vandierendonck Hans , Thoman Peter , Supinski Bronis R. De , Fahringer Thomas , Nikolopoulos Dimitrios S.
Published: December 2017

Shared memory machines continue to increase in scale by adding more parallelism through additional cores and complex memory hierarchies. Often, executing multiple applications concurrently, dividing among them hardware threads, provides greater efficiency rather than executing a single application with large thread counts. However, contention for shared resources can limit the improvement of concurrent application execution: orchestrating the number of threads used by each application and is essential.

In this article, we contribute SCALO, a solution to orchestrate concurrent application execution to increase throughput. SCALO monitors co-executing applications at runtime to evaluate their scalability. Its optimizing thread allocator analyzes these scalability estimates to adapt the parallelism of each program. Unlike previous approaches, SCALO differs by including dynamic contention effects on scalability and by controlling the parallelism during the execution of parallel regions. Thus, it improves throughput when other state-of-the-art approaches fail and outperforms them by up to 40% when they succeed.
Optical and Excitonic Properties of Atomically Thin Transition-Metal Dichalcogenides
Authors: Berkelbach Timothy C. , Reichman David R.
Published: December 2017

Starting with the isolation of a single sheet of graphene, the study of layered materials has been one of the most active areas of condensed matter physics, chemistry, and materials science. Single-layer transition-metal dichalcogenides are direct-gap semiconducting analogs of graphene that exhibit novel electronic and optical properties. These features provide exciting opportunities for the discovery of both new fundamental physical phenomena as well as innovative device platforms. Here, we review the progress associated with the creation and use of a simple microscopic framework for describing the optical and excitonic behavior of few-layer transition-metal dichalcogenides, which is based on symmetry, band structure, and the effective interactions between charge carriers in these materials. This approach provides an often quantitative account of experiments that probe the physics associated with strong electron–hole interactions in these quasi two-dimensional systems and has been successfully employed by many groups to both describe and predict emergent excitonic behavior in these layered semiconducting systems.
Spacetime from Entanglement
Authors: Swingle Brian
Published: December 2017

This is an idiosyncratic colloquium-style review of the idea that spacetime and gravity can emerge from entanglement. Drawing inspiration from the conjectured duality between quantum gravity in anti de Sitter space and certain conformal field theories, we argue that tensor networks can be used to define a discrete geometry that encodes entanglement geometrically. With the additional assumption that a continuum limit can be taken, the resulting geometry necessarily obeys Einstein's equations. The discussion takes the point of view that the emergence of spacetime and gravity is a mysterious phenomenon of quantum many-body physics that we would like to understand. We also briefly discuss possible experiments to detect emergent gravity in highly entangled quantum systems.
Maxwell Lattices and Topological Mechanics
Authors: Mao Xiaoming , Lubensky Tom C.
Published: December 2017

This is a review on the emergent field of topological mechanics, where concepts from electronic topological states of matter are applied to mechanics. We focus on the subcategory of topological mechanics of Maxwell lattices, which are mechanical frames having average coordination numbers equal to twice their spatial dimension, 〈z〉=2d, leaving them on the verge of mechanical instability. We start by introducing examples of Maxwell lattices, describing their elastic properties, and discussing their general classification. We then focus on topological phonon modes of these lattices by reviewing recent theoretical progress on one-dimensional chains and two-dimensional lattices that exhibit topologically protected zero-frequency phonon modes on edges and domain walls. We also propose metamaterials based on Maxwell lattices with unusual topologically protected mechanical properties.
Postnatal tendon growth and remodeling require platelet-derived growth factor receptor signaling
Authors: Sugg Kristoffer B. , Markworth James F. , Disser Nathaniel P. , Rizzi Andrew M. , Talarek Jeffrey R. , Sarver Dylan C. , Brooks Susan V. , Mendias Christopher L.
Published: December 2017

Platelet-derived growth factor receptor (PDGFR) signaling plays an important role in the fundamental biological activities of many cells that compose musculoskeletal tissues. However, little is known about the role of PDGFR signaling during tendon growth and remodeling in adult animals. Using the hindlimb synergist ablation model of tendon growth, our objectives were to determine the role of PDGFR signaling in the adaptation of tendons subjected to a mechanical growth stimulus, as well as to investigate the biological mechanisms behind this response. We demonstrate that both PDGFRs, PDGFRα and PDGFRβ, are expressed in tendon fibroblasts and that the inhibition of PDGFR signaling suppresses the normal growth of tendon tissue in response to mechanical growth cues due to defects in fibroblast proliferation and migration. We also identify membrane type-1 matrix metalloproteinase (MT1-MMP) as an essential proteinase for the migration of tendon fibroblasts through their extracellular matrix. Furthermore, we report that MT1-MMP translation is regulated by phosphoinositide 3-kinase/Akt signaling, while ERK1/2 controls posttranslational trafficking of MT1-MMP to the plasma membrane of tendon fibroblasts. Taken together, these findings demonstrate that PDGFR signaling is necessary for postnatal tendon growth and remodeling and that MT1-MMP is a critical mediator of tendon fibroblast migration and a potential target for the treatment of tendon injuries and diseases.
Zinc regulates vascular endothelial cell activity through zinc-sensing receptor ZnR/GPR39
Authors: Zhu Donghui , Su Yingchao , Zheng Yufeng , Fu Bingmei , Tang Liping , Qin Yi-Xian
Published: December 2017

Zn2+ is an essential element for cell survival/growth, and its deficiency is linked to many disorders. Extracellular Zn2+ concentration changes participate in modulating fundamental cellular processes such as proliferation, secretion, ion transport, and cell signal transduction in a mechanism that is not well understood. Here, we hypothesize that the Zn2+-sensing receptor ZnR/G protein-coupled receptor 39 (GPR39), found in tissues where dynamic Zn2+ homeostasis takes place, enables extracellular Zn2+ to trigger intracellular signaling pathways regulating key cell functions in vascular cells. Thus, we investigated how extracellular Zn2+ regulates cell viability, proliferation, motility, angiogenesis, vascular tone, and inflammation through ZnR/GPR39 in endothelial cells. Knockdown of GPR39 through siRNA largely abolished Zn2+-triggered cellular activity changes, Ca2+ responses, as well as the downstream activation of Gαq-PLC pathways. Extracellular Zn2+ promoted vascular cell survival/growth through activation of cAMP and Akt as well as overexpressing of platelet-derived growth factor-α receptor and vascular endothelial growth factor A. It also enhanced cell adhesion and mobility, endothelial tubule formation, and cytoskeletal reorganization. Such effects from extracellular Zn2+ were not observed in GPR39−/− endothelial cells. Zn2+ also regulated inflammation-related key molecules such as heme oxygenase-1, selectin L, IL-10, and platelet endothelial cell adhesion molecule 1, as well as vascular tone-related prostaglandin I2 synthase and nitric oxide synthase-3. In sum, extracellular Zn2+ regulates endothelial cell activity in a ZnR/GPR39-dependent manner and through the downstream Gαq-PLC pathways. Thus, ZnR/GPR39 may be a therapeutic target for regulating endothelial activity.
Solute-excluded volumes near the Novikoff cell surface
Authors: Polefka T. G. , Garrick R. A. , Redwood W. R. , Swislocki N. I. , Chinard F. P.
Published: December 2017

A differential centrifugation technique, in which all extracellular water except that intimately associated with the cell (pericellular domain) is removed, has been applied to isolated Novikoff hepatoma cells. The pericellular volumes accessible to albumin, inulin, raffinose, and sucrose were inversely related to the molecular weights of the test solutes. This phenomenon was not detectable in erythrocytes or in fat cells. Selective removal of cell surface components by enzymatic treatment produced proportional changes in the relative volumes of distribution accessible to the solutes. This discrimination in the volume accessible to each of the solutes is analogous to that obtained in gel chromatographic separation and represents, in effect, excluded volumes which are inversely related to solute size. This exclusion is associated with components of the Novikoff cell surface, including the surface coat and the microvilli that cover the Novikoff cell. These structures provide an additional level of discrimination for the Novikoff cell not seen in certain other cell types.
Increased angiotensin II receptors in neuronal cultures from hypertensive rat brain
Authors: Raizada M. K. , Muther T. F. , Sumners C.
Published: December 2017

Binding of 125I-angiotensin II (ANG II) to neuronal cultures made from the brains of 1-day-old normotensive (Wistar-Kyoto, WKY) and spontaneously hypertensive (SH) rats was time dependent, saturable, reversible, and 90-95% specific. Neuronal cultures from SH rats bound 50-70% more 125I-ANG II compared with their WKY controls. Scatchard analysis revealed that the increase in the specific binding of ANG II to SH rat neuronal cultures was due to an increase in the number of binding sites per cell rather than change in the affinity of receptors for ANG II. Light-microscopic autoradiographic analysis showed that ANG II specific binding sites were located on neuronal cell bodies and neurites. Treatment of neuronal cultures from both strains of rats with alpha-methyl-p-tyrosine caused a 50-60% decrease in the endogenous levels of norepinephrine (NE) and dopamine (DA). This decrease was associated with increases in the specific binding of 125I-ANG II in neuronal cultures from WKY rat brain. In contrast, ANG II binding in neuronal cultures from SH rat brain failed to respond to changes in NE and DA levels. These observations suggest that ANG II specific receptors are increased and that they are not under a negative-feedback control by catecholamines in SH rat brain neuronal cultures.
Osmotic tolerance of human granulocytes
Authors: Armitage W. J. , Mazur P.
Published: December 2017

Human granulocytes are injured when returned to isotonic conditions after exposure at 0 degree C to hyperosmotic solutions of NaCl or sucrose with osmolalities above 0.6 osmolal. The damage was expressed as a loss of membrane integrity [fluorescein diacetate (FDA) assay] only after 60-90 min incubation at 37 degrees C. Survival after exposure to a 1.4-osmolal solution at 0 degree C was dependent on the extent of subsequent dilution. Dilution to below 0.6 osmolal was damaging, but cells could be returned to near-osmotic conditions provided that the solute concentration was increased again to 0.64 osmolal before the cells were incubated at 37 degrees C. Granulocyte cell volumes were measured under various osmotic conditions by computer-assisted micrometry. The cells did not display a minimum volume but behaved as osmometers over the observed range of 0.2-1.4 osmolal. Granulocyte volume at a given osmolality was independent of whether the cells had first been exposed to a strongly hyperosmotic medium, indicating that no solute loading occurred in hyperosmotic sucrose solutions. Even though the cells did not survive sequential exposure to greater than 0.6 osmolal solutions, subsequent return to isotonicity, and incubation at 37 degrees C, neither cell lysis nor loss in FDA-positive cells occurred after the first two steps. This finding is not consistent with the critical-surface area-increment theory of freezing injury. The mechanism of cell injury in hyperosmotic solutions is thus not known. However, the results show that osmotic stress is potentially a major damaging factor both in the equilibration of cells with protective additives and during freezing and thawing.