bluuebunny/crossref_metadata_2025 huggingface dataset:
Lattice study of the scalar and baryon spectra in many-flavor QCD
Authors: Aoki Yasumichi , Aoyama Tatsumi , Bennett Ed , Kurachi Masafumi , Maskawa Toshihide , Miura Kohtaroh , Nagai Kei-ichi , Ohki Hiroshi , Rinaldi Enrico , Shibata Akihiro , Yamawaki Koichi , Yamazaki Takeshi , LatKMI Collaboration
Published: December 2017

In the search for a composite Higgs boson in walking technicolor models, many flavor QCD, in particular with [Formula: see text], is an attractive candidate, and has been found to have a composite flavor-singlet scalar as light as the pion. Based on lattice simulations of this theory with the HISQ action, we will present our preliminary results on the scalar decay constant using the fermionic bilinear operator, and on the mass of the lightest baryon state which could be a dark matter candidate. Combining these two results, implications for dark matter direct detection are also discussed.
Competitive Author Profiling Using Compression-Based Strategies
Authors: Claude Francisco , Galaktionov Daniil , Konow Roberto , Ladra Susana , Pedreira Óscar
Published: December 2017

Author profiling consists in determining some demographic attributes — such as gender, age, nationality, language, religion, and others — of an author for a given document. This task, which has applications in fields such as forensics, security, or marketing, has been approached from different areas, especially from linguistics and natural language processing, by extracting different types of features from training documents, usually content — and style-based features.

In this paper we address the problem by using several compression-inspired strategies that generate different models without analyzing or extracting specific features from the textual content, making them style-oblivious approaches. We analyze the behavior of these techniques, combine them and compare them with other state-of-the-art methods. We show that they can be competitive in terms of accuracy, giving the best predictions for some domains, and they are efficient in time performance.
Towards an Ontological Model for Technological Systems Structure Representation
Authors: Reyes-Alvarez Liudmila , Fernández Jaime , Rodríguez-Muñiz Luis J. , Díaz Irene
Published: December 2017

More and more distribution companies need a model to efficiently retrieve physical technological systems. Building ontologies as knowledge representation models with respect to technological systems information is increasingly seen as a key to enable interoperability between software agents and people on the Web or through to network connections. This work presents a first step for the development of an ontological model for technological systems structure representation composed by physical artifacts. The goal of the work is twofold. First, the structure of these systems is described. Besides, a model to adapt the known Bill of Materials (BOM) to the needs of distribution companies focused not only on selling physical artifacts but also to correctly configure a technological system is presented. Finally, our approach proposes a mereotopological relationships set to model the interactions between the parts that make up the structure.
Are you Curious? Predicting the Human Curiosity from Facebook
Authors: Menk Alan , Sebastia Laura
Published: December 2017

Nowadays, social networks are daily used to share what people like, feel, where they travel to, etc. This huge amount of data can say a lot about their personality because it may reect their behaviour from the “real world” to the “virtual world”. Once obtained the access to this data, some authors have tried to infer the personality of the individual without the use of long questionnaires, only working with data in an implicit way, that is, transparently to the user. In this scenario, our work is focused on predicting one of the human personality traits, the Curiosity. In this paper, we analyse the information that can be extracted from the users’ profile on Facebook and the set of features that can be used to describe their degree of curiosity. Finally, we use these data to generate several prediction models. The best generated model is able to predict the degree of curiosity with an accuracy of 87%.
Stochastic Design Exploration with Rework of Flexible Manufacturing System Under Copula-Coverage Approach
Authors: Ram Mangey , Goyal Nupur
Published: December 2017

Manufacturing systems are increasingly becoming automated and complex in nature. Highly reliable and flexible manufacturing systems (FMSs) are the necessity of manufacturing industries to fulfill the increasing customized demands. Worldwide, FMSs are used in industries to attain high productivity in production environments with rapidly and continuously changing manufactured goods structures and demands. Reliability prediction plays a very significant role in system design in the manufacturing industry, and two crucial issues in the prediction of system reliability are failures of equipment and system configuration. This novel work presents a stochastic model to analyze the performance of an FMS through its reliability characteristics, in the concern of its equipment. To improve the reliability of FMS, determine the sensitivity of the reliability measures of FMS. FMS consists of many components such as machine tools like CNC, automatic handling and material storage, controller and robot for serving load. The designed system is studied by using the Markov process, supplementary variable technique, Laplace transformation, coverage factor and Gumbel–Hougaard family copula to obtain various reliability measures. For some realistic approach, particular cases and graphical illustrations are also obtained.
Dynamic Response Analysis and Structure Optimization of GDI Injector based on Mathematical Model
Authors: Yao Xigui , Zhang Zhendong , Kong Xiangdong , Yin Congbo
Published: December 2017

The purpose of this research is to prevent the abnormal injection process in Gasoline Direct Injection (GDI) injector, realize accurate control of the fuel injection quantity and improve the performance of gasoline engine. The mechanical characteristics of the needle valve in a porous GDI injector is analyzed, the needle dynamics model is established, and the needle oscillation process is simulated with a mechanic-electronic-hydraulic integration method with the help of AMEsim software. The validity of the model is verified. The factors that influence the dynamics of the needle valve are analyzed. The results show that the dynamics of needle movement in GDI injector are mainly affected by the seat cone angle and the moving mass of the needle valve. The comprehensively improved structure of GDI injector is proposed based on the needle oscillation analysis. The simulation results show that the dynamic characteristics in GDI injector’s needle valve can be significantly improved with the optimized new structure. The experimental results of fuel injection flow characteristic and penetration distance show that the reliability and safety of the injector has been enhanced after structure optimization.
Selective suppression and excitation of high resolution CARS spectra by tailoring femtosecond laser pulse
Authors: Huang Yunxia , Xu Shuwu , Zhang Shian
Published: December 2017

Femtosecond coherent anti-Stokes Raman scattering (CARS) spectra from close Raman levels are indistinguishable due to the large bandwidth of the femtosecond laser pulse. In this paper, we propose a scheme to realize high resolution CARS spectra and further the selective suppression and excitation of the Raman levels by phase shaped femtosecond laser pulse. We show that the CARS signals can be narrowed and differentiated by tailoring only the probe pulse. In addition, one or more of the spectra peaks can be suppressed to realize the selective excitation by further scanning the pump pulse with [Formula: see text] or double reverse [Formula: see text] spectral phase modulation.
Cohomology and deformation of 𝔞𝔣𝔣(1|1) acting on differential operators
Authors: Basdouri Khaled , Omri Salem
Published: December 2017

We consider the [Formula: see text]-module structure on the spaces of differential operators acting on the spaces of weighted densities. We compute the second differential cohomology of the Lie superalgebra [Formula: see text] with coefficients in differential operators acting on the spaces of weighted densities. We classify formal deformations of the [Formula: see text]-module structure on the superspaces of symbols of differential operators. We prove that any formal deformation of a given infinitesimal deformation of this structure is equivalent to its infinitesimal part. This work is the simplest superization of a result by Basdouri [Deformation of [Formula: see text]-modules of pseudo-differential operators and symbols, J. Pseudo-differ. Oper. Appl. 7(2) (2016) 157–179] and application of work by Basdouri et al. [First cohomology of [Formula: see text] and [Formula: see text] acting on linear differential operators, Int. J. Geom. Methods Mod. Phys. 13(1) (2016)].
Ultrasensitive SERS-Based Immunoassay of Tumor Marker in Serum Using Au–Ag Alloy Nanoparticles and Ag/AgBr Hybrid Nanostructure
Authors: Gao Yongfeng , Feng Yuanhui , Zhou Lu , Petti Lucia , Wang Zhe , Zhou Jun , Xie Shusen , Chen Jian , Qing Yanping
Published: December 2017

Ultrasensitive detection of alpha-fetoprotein (AFP) is critical for the early diagnosis of liver cancer. In this work, a novel surface-enhanced Raman scattering (SERS)-based immunoassay complex has been successfully developed for the detection of AFP by using the Au-Ag alloy nanoparticals and the Ag/AgBr hybrid nanostructure. As the typical bimetal or metal/semiconductor plasmonic materials, besides the strong SERS enhancement characteristics, the Au-Ag alloy nanoparticals exhibit excellent monodispersity and the Ag/AgBr hybrid nanostructure demonstrates good stability. The experimental results show that the SERS-based immunoassay of AFP presents a low limit of detection of 1.86[Formula: see text]fg/mL and a broad dynamic range from 2[Formula: see text]fg/mL to 0.8[Formula: see text][Formula: see text]g/mL. Furthermore, the clinical applicability of the proposed SERS-based immunoassay has been assessed by the detection of AFP in the human serum samples of cancer patient and healthy person. The test data are consistent well with that of chemiluminescence immunoassay (CLIA) in the relative errors of [Formula: see text]8.82–8.06% and show better detection sensitivity. It reveals that the proposed immunoassay protocol is significant for giving insight into the design of ultrasensitive biosensor and the point-of-care testing of cancers.
Direct growth of graphene nanowalls on quartz substrates as transparent conductive electrodes for perovskite solar cells
Authors: Lin Guanhua , Zhou Yaqing , Wang Yu , Yan Xin , Wu Baoshan , Huang Feifei , Fu Junchi , Cheng Qijin , Yun Daqin
Published: December 2017

An effective method to directly produce high-quality graphene nanowalls (GNWs) on quartz substrates was demonstrated using an advanced self-assembled ratio-frequency plasma-enhanced horizontal tube furnace deposition system under different growth times from 60[Formula: see text]s to 150[Formula: see text]s at a substrate temperature of 850[Formula: see text]C without using any catalyst. The synthesized well-connected three-dimensional GNWs feature outstanding electrical and optical performance: the sheet resistance varies from 1053 [Formula: see text]/[Formula: see text] to 342 [Formula: see text]/[Formula: see text], while the corresponding transmittance ranges from 90.4% to 67.8% at a wavelength of 550[Formula: see text]nm under different growth times. We have also demonstrated that GNWs can be used as transparent conductive electrodes for perovskite solar cells. The highest photovoltaic conversion efficiency of 6.93% can be obtained for the GNWs deposited at a growth time of 120[Formula: see text]s. Hence, our study paves a new way of using GNWs as transparent conductive electrodes in perovskite solar cells.
Evidence of the Poisson/Gaudin–Mehta phase transition for band matrices on global scales
Authors: Olver Sheehan , Swan Andrew
Published: December 2017

We prove that the Poisson/Gaudin–Mehta phase transition conjectured to occur when the bandwidth of an [Formula: see text] symmetric band matrix grows like [Formula: see text] is naturally observable in the rate of convergence of the level density to the Wigner semi-circle law. Specifically, we show for periodic and non-periodic band matrices the rate of convergence of the fourth moment of the level density is independent of the boundary conditions in the localized regime [Formula: see text] with a rate of [Formula: see text] for both cases, whereas in the delocalized regime [Formula: see text] where boundary effects become important, the rate of convergence for the two ensembles differs significantly, slowing to [Formula: see text] for non-periodic band matrices. Additionally, we examine the case of thick non-periodic band matrices [Formula: see text], showing that the fourth moment is maximally deviated from the Wigner semi-circle law when [Formula: see text], and provide numerical evidence that the eigenvector statistics also exhibit critical behavior at this point.
Personalized Air Travel Prediction
Authors: Liu Jie , Liu Bin , Liu Yanchi , Chen Huipeng , Feng Lina , Xiong Hui , Huang Yalou
Published: December 2017

Human mobility analysis is one of the most important research problems in the field of urban computing. Existing research mainly focuses on the intra-city ground travel behavior modeling, while the inter-city air travel behavior modeling has been largely ignored. Actually, the inter-city travel analysis can be of equivalent importance and complementary to the intra-city travel analysis. Understanding massive passenger-air-travel behavior delivers intelligence for airlines’ precision marketing and related socioeconomic activities, such as airport planning, emergency management, local transportation planning, and tourism-related businesses. Moreover, it provides opportunities to study the characteristics of cities and the mutual relationships between them. However, modeling and predicting air traveler behavior is challenging due to the complex factors of the market situation and individual characteristics of customers (e.g., airlines’ market share, customer membership, and travelers’ intrinsic interests on destinations). To this end, in this article, we present a systematic study on the personalized air travel prediction problem, namely
where
a customer will fly to and
which
airline carrier to fly with, by leveraging real-world anonymized Passenger Name Record (PNR) data. Specifically, we first propose a relational travel topic model, which combines the merits of latent factor model with a neighborhood-based method, to uncover the personal travel preferences of aviation customers and the latent travel topics of air routes and airline carriers simultaneously. Then we present a multi-factor travel prediction framework, which fuses complex factors of the market situation and individual characteristics of customers, to predict airline customers’ personalized travel demands. Experimental results on two real-world PNR datasets demonstrate the effectiveness of our approach on both travel topic discovery and customer travel prediction.
Performance and Cost Considerations for Providing Geo-Elasticity in Database Clouds
Authors: Guo Tian , Shenoy Prashant
Published: December 2017

Online applications that serve global workload have become a norm and those applications are experiencing not only temporal but also spatial workload variations. In addition, more applications are hosting their backend tiers separately for benefits such as ease of management. To provision for such applications, traditional elasticity approaches that only consider temporal workload dynamics and assume well-provisioned backends are insufficient. Instead, in this article, we propose a new type of provisioning mechanisms—geo-elasticity, by utilizing distributed clouds with different locations. Centered on this idea, we build a system called DBScale that tracks geographic variations in the workload to dynamically provision database replicas at different cloud locations across the globe. Our geo-elastic provisioning approach comprises a regression-based model that infers database query workload from spatially distributed front-end workload, a two-node open queueing network model that estimates the capacity of databases serving both CPU and I/O-intensive query workloads and greedy algorithms for selecting best cloud locations based on latency and cost. We implement a prototype of our DBScale system on Amazon EC2’s distributed cloud. Our experiments with our prototype show up to a 66% improvement in response time when compared to local elasticity approaches.
Characterizing Transactional Memory Consistency Conditions Using Observational Refinement
Authors: Attiya Hagit , Gotsman Alexey , Hans Sandeep , Rinetzky Noam
Published: December 2017

Transactional memory (TM) facilitates the development of concurrent applications by letting a programmer designate certain code blocks as atomic. The common approach to stating TM correctness is through a consistency condition that restricts the possible TM executions. Unfortunately, existing consistency conditions fall short of formalizing the intuitive semantics of atomic blocks through which programmers use a TM. To close this gap, we formalize programmer expectations as observational refinement between TM implementations. This states that properties of a program using a concrete TM implementation can be established by analyzing its behavior with an abstract TM, serving as a specification of the concrete one.

We show that a variant of Transactional Memory Specification (TMS), a TM consistency condition, is equivalent to observational refinement for a programming language where local variables are rolled back upon a transaction abort. We thereby establish that TMS is the weakest acceptable condition for this case. We then propose a new consistency condition, called
Strong Transactional Memory Specification (STMS)
, and show that it is equivalent to observational refinement for a language where local variables are not rolled back upon aborts. Finally, we show that under certain natural assumptions on TM implementations, STMS is equivalent to a variant of a well-known condition of opacity.

Our results suggest a new approach to evaluating TM consistency conditions and enable TM implementors and language designers to make better-informed decisions.
Remark on Algorithm 539
Authors: Hanson Richard J. , Hopkins Tim
Published: December 2017

We propose a set of new Fortran reference implementations, based on an algorithm proposed by Kahan, for the Level 1 BLAS routines
*NRM2
that compute the Euclidean norm of a real or complex input vector. The principal advantage of these routines over the current offerings is that, rather than losing accuracy as the length of the vector increases, they generate results that are accurate to almost machine precision for vectors of length
N
<
N

max

where
N

max

depends upon the precision of the floating point arithmetic being used. In addition, we make use of intrinsic modules, introduced in the latest Fortran standards, to detect occurrences of non-finite numbers in the input data and return suitable values as well as setting IEEE floating point status flags as appropriate. A set of C interface routines is also provided to allow simple, portable access to the new routines.

To improve execution speed, we advocate a hybrid algorithm; a simple loop is used first and, only if IEEE floating point exception flags signal, do we fall back on Kahan’s algorithm. Since most input vectors are “easy,” i.e., they do not require the sophistication of Kahan’s algorithm, the simple loop improves performance while the use of compensated summation ensures high accuracy.

We also report on a comprehensive suite of test problems that has been developed to test both our new implementation and existing codes for both accuracy and the appropriate settings of the IEEE arithmetic status flags.
Social Bridges in Urban Purchase Behavior
Authors: Dong Xiaowen , Suhara Yoshihiko , Bozkaya Burçin , Singh Vivek K. , Lepri Bruno , Pentland Alex ‘Sandy’
Published: December 2017

The understanding and modeling of human purchase behavior in city environment can have important implications in the study of urban economy and in the design and organization of cities. In this article, we study human purchase behavior at the community level and argue that people who live in different communities but work at close-by locations could act as “social bridges” between the respective communities and that they are correlated with similarity in community purchase behavior. We provide empirical evidence by studying millions of credit card transaction records for tens of thousands of individuals in a city environment during a period of three months. More specifically, we show that the number of social bridges between communities is a much stronger indicator of similarity in their purchase behavior than traditionally considered factors such as income and sociodemographic variables. Our findings also suggest that such an effect varies across different merchant categories, that the presence of female customers in social bridges is a stronger indicator compared to that of their male counterparts, and that there seems to be a geographical constraint for this effect, all of which may have implications in the studies of urban economy and data-driven urban planning.
Online Early-Late Fusion Based on Adaptive HMM for Sign Language Recognition
Authors: Guo Dan , Zhou Wengang , Li Houqiang , Wang Meng
Published: December 2017

In sign language recognition (SLR) with multimodal data, a sign word can be represented by multiply features, for which there exist an intrinsic property and a mutually complementary relationship among them. To fully explore those relationships, we propose an online early-late fusion method based on the adaptive Hidden Markov Model (HMM). In terms of the intrinsic property, we discover that inherent latent change states of each sign are related not only to the number of key gestures and body poses but also to their translation relationships. We propose an adaptive HMM method to obtain the hidden state number of each sign by affinity propagation clustering. For the complementary relationship, we propose an online early-late fusion scheme. The early fusion (feature fusion) is dedicated to preserving useful information to achieve a better complementary score, while the late fusion (score fusion) uncovers the significance of those features and aggregates them in a weighting manner. Different from classical fusion methods, the fusion is query adaptive. For different queries, after feature selection (including the combined feature), the fusion weight is inversely proportional to the area under the curve of the normalized query score list for each selected feature. The whole fusion process is effective and efficient. Experiments verify the effectiveness on the signer-independent SLR with large vocabulary. Compared either on different dataset sizes or to different SLR models, our method demonstrates consistent and promising performance.
Implementing Support for Pointers to Private Data in a General-Purpose Secure Multi-Party Compiler
Authors: Zhang Yihua , Blanton Marina , Almashaqbeh Ghada
Published: December 2017

Recent compilers allow a general-purpose program (written in a conventional programming language) that handles private data to be translated into a secure distributed implementation of the corresponding functionality. The resulting program is then guaranteed to provably protect private data using secure multi-party computation techniques. The goals of such compilers are generality, usability, and efficiency, but the complete set of features of a modern programming language has not been supported to date by the existing compilers. In particular, recent compilers PICCO and the two-party ANSI C compiler strive to translate any C program into its secure multi-party implementation, but they currently lack support for pointers and dynamic memory allocation, which are important components of many C programs. In this work, we mitigate the limitation and add support for pointers to private data and consequently dynamic memory allocation to the PICCO compiler, enabling it to handle a more diverse set of programs over private data. Because doing so opens up a new design space, we investigate the use of pointers to private data (with known as well as private locations stored in them) in programs and report our findings. Aside from dynamic memory allocation, we examine other important topics associated with common pointer use such as reference by pointer/address, casting, and building various data structures in the context of secure multi-party computation. This results in enabling the compiler to automatically translate a user program that uses pointers to private data into its distributed implementation that provably protects private data throughout the computation. We empirically evaluate the constructions and report on the performance of representative programs.
Sara Mauskopf Innovative thinking in the service of parents
Authors: Scoică Adrian
Published: December 2017

Sara Mauskopf lives in Silicon Valley, and is the CEO and co-founder of Winnie, an app with the mission to make parents' lives easier through technology.
Equality through digital technology
Authors: Kalantzis Vasileios
Published: December 2017

Dedicated to Alan Mathison Turing (1912--1954), a pioneer of computer science
Multidimensional Intratile Parallelization for Memory-Starved Stencil Computations
Authors: Malas Tareq M. , Hager Georg , Ltaief Hatem , Keyes David E.
Published: December 2017

Optimizing the performance of stencil algorithms has been the subject of intense research over the last two decades. Since many stencil schemes have low arithmetic intensity, most optimizations focus on increasing the temporal data access locality, thus reducing the data traffic through the main memory interface with the ultimate goal of decoupling from this bottleneck. There are, however, only a few approaches that explicitly leverage the shared cache feature of modern multicore chips. If every thread works on its private, separate cache block, the available cache space can become too small, and sufficient temporal locality may not be achieved. We propose a flexible multidimensional intratile parallelization method for stencil algorithms on multicore CPUs with a shared outer-level cache. This method leads to a significant reduction in the required cache space without adverse effects from hardware prefetching or TLB shortage. Our
Girih
framework includes an autotuner to select optimal parameter configurations on the target hardware. We conduct performance experiments on two contemporary Intel processors and compare with the state-of-the-art stencil frameworks Pluto and Pochoir, using four corner-case stencil schemes and a wide range of problem sizes.
Girih
shows substantial performance advantages and best arithmetic intensity at almost all problem sizes, especially on low-intensity stencils with variable coefficients. We study in detail the performance behavior at varying grid sizes using phenomenological performance modeling. Our analysis of energy consumption reveals that our method can save energy through reduced DRAM bandwidth usage even at a marginal performance gain. It is thus well suited for future architectures that will be strongly challenged by the cost of data movement, be it in terms of performance or energy consumption.
Verifying Reliability Properties Using the Hyperball Abstract Domain
Authors: Lidman Jacob , Mckee Sally A.
Published: December 2017

Modern systems are increasingly susceptible to soft errors that manifest themselves as bit flips and possibly alter the semantics of an application. We would like to measure the quality degradation on semantics due to such bit flips, and thus we introduce a Hyperball abstract domain that allows us to determine the worst-case distance between expected and actual results. Similar to intervals, hyperballs describe a connected and dense space. The semantics of low-level code in the presence of bit flips is hard to accurately describe in such a space. We therefore combine the Hyperball domain with an existing affine system abstract domain that we extend to handle bit flips, which are introduce as disjunctions. Bit-flips can reduce the precision of our analysis, and we therefor introduce the Scale domain as a disjunctive refinement to minimize precision loss. This domain bounds the number of disjunctive elements by quantifying the over-approximation of different partitions and uses submodular optimization to find a good partitioning (within a bound of optimal). We evaluate these domains to show benefits and potential problems. For the application we examine here, adding the Scale domain to the Hyperball abstraction improves accuracy by up to two orders of magnitude. Our initial results demonstrate the feasibility of this approach, although we would like to further improve execution efficiency.
HAShCache
Authors: Patil Adarsh , Govindarajan Ramaswamy
Published: December 2017

Integrated Heterogeneous System (IHS) processors pack throughput-oriented General-Purpose Graphics Pprocessing Units (GPGPUs) alongside latency-oriented Central Processing Units (CPUs) on the same die sharing certain resources, e.g., shared last-level cache, Network-on-Chip (NoC), and the main memory. The demands for memory accesses and other shared resources from GPU cores can exceed that of CPU cores by two to three orders of magnitude. This disparity poses significant problems in exploiting the full potential of these architectures.

In this article, we propose adding a large-capacity stacked DRAM, used as a shared last-level cache, for the IHS processors. However, adding the DRAMCache naively, leaves significant performance on the table due to the disparate demands from CPU and GPU cores for DRAMCache and memory accesses. In particular, the imbalance can significantly reduce the performance benefits that the CPU cores would have otherwise enjoyed with the introduction of the DRAMCache, necessitating a heterogeneity-aware management of this shared resource for improved performance.

In this article, we propose three simple techniques to enhance the performance of CPU application while ensuring very little to no performance impact to the GPU. Specifically, we propose (i)
PrIS
, a prioritization scheme for scheduling CPU requests at the DRAMCache controller; (ii)
ByE
, a selective and temporal bypassing scheme for CPU requests at the DRAMCache; and (iii)
Chaining
, an occupancy controlling mechanism for GPU lines in the DRAMCache through pseudo-associativity. The resulting cache, Heterogeneity-Aware Shared DRAMCache (HAShCache), is heterogeneity-aware and can adapt dynamically to address the inherent disparity of demands in an IHS architecture. Experimental evaluation of the proposed HAShCache results in an average system performance improvement of 41% over a naive DRAMCache and over 200% improvement over a baseline system with no stacked DRAMCache.
Data-Driven Concurrency for High Performance Computing
Authors: Matheou George , Evripidou Paraskevas
Published: December 2017

In this work, we utilize dynamic dataflow/data-driven techniques to improve the performance of high performance computing (HPC) systems. The proposed techniques are implemented and evaluated through an efficient, portable, and robust programming framework that enables data-driven concurrency on HPC systems. The proposed framework is based on data-driven multithreading (DDM), a hybrid control-flow/dataflow model that schedules threads based on data availability on sequential processors. The proposed framework was evaluated using several benchmarks, with different characteristics, on two different systems: a 4-node AMD system with a total of 128 cores and a 64-node Intel HPC system with a total of 768 cores. The performance evaluation shows that the proposed framework scales well and tolerates scheduling overheads and memory latencies effectively. We also compare our framework to MPI, DDM-VM, and OmpSs@Cluster. The comparison results show that the proposed framework obtains comparable or better performance.
Optimization of Triangular and Banded Matrix Operations Using 2d-Packed Layouts
Authors: Baroudi Toufik , Seghir Rachid , Loechner Vincent
Published: December 2017

Over the past few years, multicore systems have become increasingly powerful and thereby very useful in high-performance computing. However, many applications, such as some linear algebra algorithms, still cannot take full advantage of these systems. This is mainly due to the shortage of optimization techniques dealing with irregular control structures. In particular, the well-known polyhedral model fails to optimize loop nests whose bounds and/or array references are not affine functions. This is more likely to occur when handling sparse matrices in their packed formats. In this article, we propose using 2d-packed layouts and simple affine transformations to enable optimization of triangular and banded matrix operations. The benefit of our proposal is shown through an experimental study over a set of linear algebra benchmarks.
Acute and chronic resistance training downregulates select LINE-1 retrotransposon activity markers in human skeletal muscle
Authors: Romero Matthew A. , Mobley C. Brooks , Mumford Petey W. , Roberson Paul A. , Haun Cody T. , Kephart Wesley C. , Healy James C. , Beck Darren T. , Young Kaelin C. , Martin Jeffrey S. , Lockwood Christopher M. , Roberts Michael D.
Published: December 2017

Herein, we examined if acute or chronic resistance exercise affected markers of skeletal muscle long interspersed nuclear element-1 (LINE-1) retrotransposon activity. In study 1, 10 resistance-trained college-aged men performed three consecutive daily back squat sessions, and vastus lateralis biopsies were taken before (Pre), 2 h following session 1 (Post1), and 3 days following session 3 (Post2). In study 2, 13 untrained college-aged men performed a full-body resistance training program (3 days/wk), and vastus lateralis biopsies were taken before ( week 0) and ~72 h following training cessation ( week 12). In study 1, LINE-1 mRNA decreased 42–48% at Post1 and 2 ( P < 0.05), and reverse transcriptase (RT) activity trended downward at Post2 (−37%, P = 0.067). In study 2, LINE-1 mRNA trended downward at week 12 (−17%, P = 0.056) while LINE-1 promoter methylation increased (+142%, P = 0.041). Open reading frame (ORF)2p protein expression (−24%, P = 0.059) and RT activity (−26%, P = 0.063) also trended downward by week 12. Additionally, changes in RT activity versus satellite cell number were inversely associated ( r = −0.725, P = 0.008). Follow-up in vitro experiments demonstrated that 48-h treatments with lower doses (1 μM and 10 μM) of efavirenz and nevirapine (non-nucleoside RT inhibitors) increased myoblast proliferation ( P < 0.05). However, we observed a paradoxical decrease in myoblast proliferation with higher doses (50 μM) of efavirenz and delavirdine. This is the first report suggesting that resistance exercise downregulates markers of skeletal muscle LINE-1 activity. Given our discordant in vitro findings, future research is needed to thoroughly assess whether LINE-1-mediated RT activity enhances or blunts myoblast, or primary satellite cell, proliferative capacity.
Experimental Characterization of Dielectric Properties in Fluid Saturated Artificial Shales
Authors: Beloborodov Roman , Pervukhina Marina , Han Tongcheng , Josh Matthew
Published: December 2017

High dielectric contrast between water and hydrocarbons provides a useful method for distinguishing between producible layers of reservoir rocks and surrounding media. Dielectric response at high frequencies is related to the moisture content of rocks. Correlations between the dielectric permittivity and specific surface area can be used for the estimation of elastic and geomechanical properties of rocks. Knowledge of dielectric loss-factor and relaxation frequency in shales is critical for the design of techniques for effective hydrocarbon extraction and production from unconventional reservoirs. Although applicability of dielectric measurements is intriguing, the data interpretation is very challenging due to many factors influencing the dielectric response. For instance, dielectric permittivity is determined by mineralogical composition of solid fraction, volumetric content and composition of saturating fluid, rock microstructure and geometrical features of its solid components and pore space, temperature, and pressure. In this experimental study, we investigate the frequency dependent dielectric properties of artificial shale rocks prepared from silt-clay mixtures via mechanical compaction. Samples are prepared with various clay contents and pore fluids of different salinity and cation compositions. Measurements of dielectric properties are conducted in two orientations to investigate the dielectric anisotropy as the samples acquire strongly oriented microstructures during the compaction process.
Association between Genetic Polymorphism and Risk of von Willebrand Disease in Pakistan
Authors: Arshad Najma , Nawaz Syed Kashif , Iqbal Riffat , Arshad Muhammad , Musheer Farhana , Naz Amber , Mushtaq Iqra , Jaleel Sara
Published: December 2017

von Willebrand disease (VWD) is an inherited, genetically and clinically heterogeneous hemorrhagic disorder. The most common cause of this disease is mutation in the gene that encodes protein von Willebrand factor (VWF) which is responsible for blood clotting. The current study was designed to investigate the role of genetic polymorphisms with the onset of VWD in population of Pakistan. Three exonic variants (c.3445T>C; c.4975C>T; c.7603C>T) from VWF gene were used for the genotyping purpose. The current study employed a case-control association design involving 43 VWD patients and 100 healthy controls from Pakistani population. The genetic reason of VWD was investigated using the allele specific PCR. The significant (P<0.05) allelic association was found between all three exonic variants and VWD. The CT genotype of these variants was noticed to be associated with significantly higher risk of VWD [odds ratio (95% CI): 14.7 (4.546–47.98), 26.71 (7.281–97.98), and 21.5 (5.806–80.01) for c.3445T>C, c.4975C>T, and c.7603C>T, resp.] while genotypes CC (c.4975C>T) and TT (c.3445T>C and c.7603C>T) were having protective effect against the disease. However, replicated studies are needed for elaborating the role of these SNPs.
Image Regularity and Fidelity Measure with a Two‐Modality Potential Function
Authors: Wang Weiwei , Kong Shengjiang , Razi Amir , Feng Xiangchu
Published: December 2017

We define a strictly convex smooth potential function and use it to measure the data fidelity as well as the regularity for image denoising and cartoon‐texture decomposition. The new model has several advantages over the well‐known ROF or TV‐L2 and the TV‐L1 model. First, due to the two‐modality property of the new potential function, the new regularity has strong regularizing properties in all directions and thus encourages removing noise in smooth areas, while, near edges, it smoothes the edge mainly along the tangent direction and thus can well preserve the edges. Second, the new potential function is very close to the L1 norm; thus using it to measure the data fidelity makes the new model perform very well in removing impulse noise and preserving the contrast. Lastly, the proposed fidelity and regularization term is strictly convex and smooth and thus allows a unique global minimizer and it can be solved by using the steepest descent method. Numerical experiments show that the proposed model outperforms TV‐L2 and TV‐L1 in removing impulse noise and mixed noise. It also outperforms some state‐of‐the‐art methods specially designed for impulse noise. Tests on cartoon‐texture decomposition show that our method is effective and performs better than TV‐L1.
Radical Scavenger Capacity of Jabuticaba Fruit (Myrciaria cauliflora) and Its Biological Effects in Hypertensive Rats
Authors: de Souza Camila Gabriela , de Andrade Daniela Medeiros Lobo , Jordão Juliana Bahia Reis , de Ávila Renato Ivan , Borges Leonardo Luiz , Vaz Boniek Gontijo , Valadares Marize Campos , de Souza Gil Eric , da Conceição Edemilson Cardoso , Rocha Matheus Lavorenti
Published: December 2017

Jabuticaba is an exotic fruit native to Brazil that has been arousing medicinal interest. Using chemical (HPLC‐PDA, resonance mass spectra, and NMR), electroanalytical (differential pulse voltammetry, radical scavenging assay), and pharmacological (in vivo and in vitro) approaches, we have identified its bioactive compounds and hypotensive effects on hypertensive rats. The hydroalcoholic extract of jabuticaba (HEJ) presents a great quantity of phenolic compounds, and several molecules with hydroxyl groups present high efficiency as an antioxidant. The treatment with HEJ (100 and 300 mg/kg/day, for four weeks) presented hypotensive effects on L‐NAME‐induced hypertensive rats, possibly improving the nitric oxide bioavailability because of its high antioxidant potential. Furthermore, renal and cardiac hypertrophies were also attenuated after the HEJ treatment. Moreover, the vascular responses to contractile and dilating agonists were improved with the HEJ treatment, which is also able to induce nitric oxide production in endothelial cells.
Development of ANN Model for Wind Speed Prediction as a Support for Early Warning System
Authors: Marović Ivan , Sušanj Ivana , Ožanić Nevenka
Published: December 2017

The impact of natural disasters increases every year with more casualties and damage to property and the environment. Therefore, it is important to prevent consequences by implementation of the early warning system (EWS) in order to announce the possibility of the harmful phenomena occurrence. In this paper, focus is placed on the implementation of the EWS on the micro location in order to announce possible harmful phenomena occurrence caused by wind. In order to predict such phenomena (wind speed), an artificial neural network (ANN) prediction model is developed. The model is developed on the basis of the input data obtained by local meteorological station on the University of Rijeka campus area in the Republic of Croatia. The prediction model is validated and evaluated by visual and common calculation approaches, after which it was found that it is possible to perform very good wind speed prediction for time steps Δt=1 h, Δt=3 h, and Δt=8 h. The developed model is implemented in the EWS as a decision support for improvement of the existing “procedure plan in a case of the emergency caused by stormy wind or hurricane, snow and occurrence of the ice on the University of Rijeka campus.”
Periprosthetic Joint Infection of Shoulder Arthroplasties: Diagnostic and Treatment Options
Authors: Fink Bernd , Sevelda Florian
Published: December 2017

Periprosthetic joint infection (PJI) is one of the most frequent reasons for painful shoulder arthroplasties and revision surgery of shoulder arthroplasties. Cutibacterium acnes (Propionibacterium acnes) is one of the microorganisms that most often causes the infection. However, this slow growing microorganism is difficult to detect. This paper presents an overview of different diagnostic test to detect a periprosthetic shoulder infection. This includes nonspecific diagnostic tests and specific tests (with identifying the responsible microorganism). The aspiration can combine different specific and nonspecific tests. In dry aspiration and suspected joint infection, we recommend a biopsy. Several therapeutic options exist for the treatment of PJI of shoulder arthroplasties. In acute infections, the options include leaving the implant in place with open debridement, septic irrigation with antibacterial fluids like octenidine or polyhexanide solution, and exchange of all removable components. In late infections (more than four weeks after implantation) the therapeutic options are a permanent spacer, single-stage revision, and two-stage revision with a temporary spacer. The functional results are best after single-stage revisions with a success rate similar to two-stage revisions. For single-stage revisions, the microorganism should be known preoperatively so that specific antibiotics can be mixed into the cement for implantation of the new prosthesis and specific systemic antibiotic therapy can be applied to support the surgery.
The Origin of Chern-Simons Modified Gravity from an 11 + 3-Dimensional Manifold
Authors: Helayël-Neto J. A. , Sepehri Alireza , Ghaffary Tooraj
Published: December 2017

It is our aim to show that the Chern-Simons terms of modified gravity can be understood as generated by the addition of a 3-dimensional algebraic manifold to an initial 11-dimensional space-time manifold; this builds up an 11+3-dimensional space-time. In this system, firstly, some fields living in the bulk join the fields that live on the 11-dimensional manifold, so that the rank of the gauge fields exceeds the dimension of the algebra; consequently, there emerges an anomaly. To solve this problem, another 11-dimensional manifold is included in the 11+3-dimensional space-time, and it interacts with the initial manifold by exchanging Chern-Simon fields. This mechanism is able to remove the anomaly. Chern-Simons terms actually produce an extra manifold in the pair of 11-dimensional manifolds of the 11+3-space-time. Summing up the topology of both the 11-dimensional manifolds and the topology of the exchanged Chern-Simons manifold in the bulk, we conclude that the total topology shrinks to one, which is in agreement with the main idea of the Big Bang theory.
HPV Status and Its Correlation with BCL2, p21, p53, Rb, and Survivin Expression in Breast Cancer in a Chinese Population
Authors: Wang Ya-Wen , Zhang Kai , Zhao Song , Lv Yanrong , Zhu Jiang , Liu Huantao , Feng Jinbo , Liang Weili , Ma Rong , Wang Jianli
Published: December 2017

Despite recent evidence, the role of human papillomavirus (HPV) in breast carcinogenesis is controversial. The correlations of HPV infection with the clinicopathological features of breast cancer and the expression of cell cycle/apoptosis-associated proteins have not been well elucidated. In this study, we sought to determine the prevalence of high-risk HPVs (HR-HPVs) infection and BCL2, p21, p53, Rb, and survivin expression in breast cancer patients and to investigate the relationship of HPV with these cancer-related proteins, in an attempt to clarify the potential mechanism of HPV in breast cancer pathogenesis. HPV presence in 81 fresh breast cancer tissues was determined by hybrid capture 2 (HC2) assay, and expression of BCL2, p21, p53, Rb, and survivin was detected by immunohistochemistry. Here we showed that fourteen (17.3%) patients were HR-HPV positive. HPV infection demonstrated no significant correlation with the clinicopathological characteristics of breast cancer. HPV-positive tumors showed significantly higher BCL2 and lower p53 expression than HPV-negative tumors. Expression of p21, Rb, and survivin was not associated with HPV status. Our results suggest a possible role of HR-HPV in breast cancer carcinogenesis, in which BCL2 and p53 may be involved.