bluuebunny/crossref_metadata_2025 huggingface dataset:
Analyzing Influenza Virus Sequences using Binary Encoding Approach
Authors: Lam Ham Ching , Sreevatsan Srinand , Boley Daniel
Published: January 2015

Capturing mutation patterns of each individual influenza virus sequence is often challenging; in this paper, we demonstrated that using a binary encoding scheme coupled with dimension reduction technique, we were able to capture the intrinsic mutation pattern of the virus. Our approach looks at the variance between sequences instead of the commonly used p-distance or Hamming distance. We first convert the influenza genetic sequences to a binary strings and form a binary sequence alignment matrix and then apply Principal Component Analysis (PCA) to this matrix. PCA also provides identification power to identify reassortant virus by using data projection technique. Due to the sparsity of the binary string, we were able to analyze large volume of influenza sequence data in a very short time. For protein sequences, our scheme also allows the incorporation of biophysical properties of each amino acid. Here, we present various encouraging results from analyzing influenza nucleotide, protein and genome sequences using the proposed approach.
PyTrilinos: Recent Advances in the Python Interface to Trilinos
Authors: Spotz William F.
Published: January 2015

PyTrilinos is a set of Python interfaces to compiled Trilinos packages. This collection supports serial and parallel dense linear algebra, serial and parallel sparse linear algebra, direct and iterative linear solution techniques, algebraic and multilevel preconditioners, nonlinear solvers and continuation algorithms, eigensolvers and partitioning algorithms. Also included are a variety of related utility functions and classes, including distributed I/O, coloring algorithms and matrix generation. PyTrilinos vector objects are compatible with the popular NumPy Python package. As a Python front end to compiled libraries, PyTrilinos takes advantage of the flexibility and ease of use of Python, and the efficiency of the underlying C++, C and Fortran numerical kernels. This paper covers recent, previously unpublished advances in the PyTrilinos package.
Karyometric Comparison of Splenic and Gastric Marginal Zone Lymphomas
Authors: Styczeń Magdalena , Szpor Joanna , Demczuk Sergiusz , Okoń Krzysztof
Published: January 2015

Background: Marginal zone lymphomas are indolent B-cell lymphomas associated with autoimmunity and chronic inflammation. The two most frequent variants are mucosa associated lymphoid tissues marginal zone lymphomas and splenic marginal zone lymphomas. The aim of the study was to determine if it is possible to classify splenic and gastric lymphomas according to karyometric features.

Methods: The material consisted of 16 splenic and 14 gastric lymphomas. The measurements were done with the AnalySIS image analysis system. In each case at least 100 nuclei were selected, and 19 different geometric parameters were measured.

Results: On statistical analysis, the nuclei of splenic and gastric lymphomas showed differences in most parameters, but significant overlap of the values was present. Neural networks were trained and used for classification of the data. By this method, the nuclei were properly classified with a sensitivity of 0.75 and specificity of 0.71. In addition, in all the cases the majority of the nuclei were properly classified, thus allowing correct classification of all the cases into “splenic” or “gastric”.

Conclusion: These results support the view that mucosa-associated lymphoid tissue lymphomas and splenic marginal-zone lymphomas are separate entities.
BECSI: Bandwidth Efficient Certificate Status Information Distribution Mechanism for VANETs
Authors: Gañán Carlos , Muñoz Jose L. , Esparza Oscar , Loo Jonathan , Mata-Díaz Jorge , Alins Juanjo
Published: January 2015

Certificate revocation is a challenging task, especiallyin mobile network environments such as vehicular ad Hoc networks (VANETs).According to the IEEE 1609.2 security standard for VANETs, public keyinfrastructure (PKI) will provide this functionality by means of certificate revocation lists (CRLs).When a certificate authority (CA)needs to revoke a certificate, itglobally distributes CRLs.Transmitting these lists pose a problem as they require high update frequencies and a lot of bandwidth. In this article, we propose BECSI, aBandwidth Efficient Certificate Status Informationmechanism to efficiently distributecertificate status information (CSI) in VANETs.By means of Merkle hash trees (MHT), BECSI allowsto retrieve authenticated CSI not onlyfrom the infrastructure but also from vehicles actingas mobile repositories.Since these MHTs are significantly smaller than the CRLs, BECSIreduces the load on the CSI repositories and improves the response time for the vehicles.Additionally, BECSI improves the freshness of the CSIby combining the use of delta-CRLs with MHTs.Thus, vehicles that have cached the most current CRLcan download delta-CRLs to have a complete list of revoked certificates.Once a vehicle has the whole list of revoked certificates, it can act as mobile repository.
Simultaneous Dual-Color Fluorescence Microscope: A Characterization Study
Authors: Li Zheng , Chen Xiaodong , Ren Liqiang , Song Jie , Li Yuhua , Zheng Bin , Liu Hong
Published: January 2015

Background: High spatial resolution and geometric accuracy is crucial for chromosomal analysis of clinical cytogenetic applications. High resolution and rapid simultaneous acquisition of multiple fluorescent wavelengths can be achieved by utilizing concurrent imaging with multiple detectors. However, such class of microscopic systems functions differently from traditional fluorescence microscopes.

Objective: To develop a practical characterization framework to assess and optimize the performance of a high resolution and dual-color fluorescence microscope designed for clinical chromosomal analysis.

Methods: A dual-band microscopic imaging system utilizes a dichroic mirror, two sets of specially selected optical filters, and two detectors to simultaneously acquire two fluorescent wavelengths. The system’s geometric distortion, linearity, the modulation transfer function, and the dual detectors’ alignment were characterized.

Results: Experiment results show that the geometric distortion at lens periphery is less than 1%. Both fluorescent channels show linear signal responses, but there exists discrepancy between the two due to the detectors’ non-uniform response ratio to different wavelengths. In terms of the spatial resolution, the two contrast transfer function curves trend agreeably with the spatial frequency. The alignment measurement allows quantitatively assessing the cameras' alignment. A result image of adjusted alignment is demonstrated to show the reduced discrepancy by using the alignment measurement method.

Conclusions: In this paper, we present a system characterization study and its methods for a specially designed imaging system for clinical cytogenetic applications. The presented characterization methods are not only unique to this dual-color imaging system but also applicable to evaluation and optimization of other similar multi-color microscopic image systems for improving their clinical utilities for future cytogenetic applications.
Compiler-Directed File Layout Optimization for Hierarchical Storage Systems
Authors: Ding Wei , Zhang Yuanrui , Kandemir Mahmut , Son Seung Woo
Published: January 2015

File layout of array data is a critical factor that effects the behavior of storage caches, and has so far taken not much attention in the context of hierarchical storage systems. The main contribution of this paper is a compiler-driven file layout optimization scheme for hierarchical storage caches. This approach, fully automated within an optimizing compiler, analyzes a multi-threaded application code and determines a file layout for each disk-resident array referenced by the code, such that the performance of the target storage cache hierarchy is maximized. We tested our approach using 16 I/O intensive application programs and compared its performance against two previously proposed approaches under different cache space management schemes. Our experimental results show that the proposed approach improves the execution time of these parallel applications by 23.7% on average.
From Physics Model to Results: An Optimizing Framework for Cross-Architecture Code Generation
Authors: Blazewicz Marek , Hinder Ian , Koppelman David M. , Brandt Steven R. , Ciznicki Milosz , Kierzynka Michal , Löffler Frank , Schnetter Erik , Tao Jian
Published: January 2015

Starting from a high-level problem description in terms of partial differential equations using abstract tensor notation, theChemoraframework discretizes, optimizes, and generates complete high performance codes for a wide range of compute architectures. Chemora extends the capabilities of Cactus, facilitating the usage of large-scale CPU/GPU systems in an efficient manner for complex applications, without low-level code tuning. Chemora achieves parallelism through MPI and multi-threading, combining OpenMP and CUDA. Optimizations include high-level code transformations, efficient loop traversal strategies, dynamically selected data and instruction cache usage strategies, and JIT compilation of GPU code tailored to the problem characteristics. The discretization is based on higher-order finite differences on multi-block domains. Chemora's capabilities are demonstrated by simulations of black hole collisions. This problem provides an acid test of the framework, as the Einstein equations contain hundreds of variables and thousands of terms.
Urothelial Differentiation of Human Umbilical Cord-Derived Mesenchymal Stromal CellsIn Vitro
Authors: Wu Shuai , Cheng Zhongliang , Liu Guohua , Zhao Xinfeng , Zhong Liang , Zhu Yingjian , Zhu Jiang
Published: January 2015

Human umbilical cord-derived mesenchymal stromal cells (hUCMSCs) are the most primitive of those isolated from other post-natal tissue source. The hUCMSCs possess the capability of differentiating along multi-lineage. This study aimed to investigate whether hUCMSCs can differentiate into urothelium-like cells. The hUCMSCs were isolated from fresh human umbilical cord postpartum and expanded at least to passage 3in vitro. Subsequently, they were cultured with conditioned medium from urothelial cells (UC-CM) supplemented with 20 ng/ml exogenous epidermal growth factor (EGF). Urothelial cell specific marker uroplakin II (UPII) and cytokeratins were evaluated by reverse transcriptase-polymerase chain reaction (RT-PCR) and immunofluorescence technology. During culture, hUCMSCs started to express UPII and cytokeratins weakly at 7 days and were significantly up-regulated at 2 weeks post-induction. Additionally, morphology of hUCMSCs changed from spindle-shape to a polygonal epithelial-shape similar to that of urothelial cells after 7 days. The study results indicated that hUCMSCs can differentiate into urothelium-like cells in a defined micro-environmentin vitroconstituted by UC-CM and exogenous EGF.
Modelling Spatio-Temporal Relevancy in Urban Context-Aware Pervasive Systems Using Voronoi Continuous Range Query and Multi-Interval Algebra
Authors: Samany Najmeh Neysani , Delavar Mahmoud Reza , Chrisman Nicholas , Malek Mohammad Reza
Published: January 2015

Space and time are two dominant factors in context-aware pervasive systems which determine whether an entity is related to the moving user or not. This paper specifically addresses the use of spatio-temporal relations for detecting spatio-temporally relevant contexts to the user. The main contribution of this work is that the proposed model is sensitive to the velocity and direction of the user and applies customized Multi Interval Algebra (MIA) with Voronoi Continuous Range Query (VCRQ) to introduce spatio-temporally relevant contexts according to their arrangement in space. In this implementation the Spatio-Temporal Relevancy Model for Context-Aware Systems (STRMCAS) helps the tourist to find his/her preferred areas that are spatio-temporally relevant. The experimental results in a scenario of tourist navigation are evaluated with respect to the accuracy of the model, performance time and satisfaction of users in 30 iterations of the algorithm. The evaluation process demonstrated the efficiency of the model in real-world applications.
Smartphone-Based Indoor Pedestrian Tracking Using Geo-Magnetic Observations
Authors: Lee Sungnam , Chon Yohan , Cha Hojung
Published: January 2015

With the widespread use of smartphones, the use of location-based services (LBS) with smartphones has become an active research issue. The accurate measurement of user location is necessary to provide LBS. While outdoor locations are easily obtained with GPS, indoor location information is difficult to acquire. Previous work on indoor location tracking systems often relied on infrastructures that are influenced by environmental changes and temporal differences. Several studies have proposed infrastructure-less systems that are independent of the surroundings, but these works generally required non-trivial computation time or energy costs. In this paper, we propose an infrastructure-less pedestrian tracking system in indoor environments. The system uses accelerometers and magnetic sensors in smartphones without pre-installed infrastructure. We reduced the cumulative error of location tracking by geo-magnetic observations at corners and spots with magnetic fluctuations. In addition, we developed a robust estimation model that is tolerant to false positives, as well as a mobility model that reflects the characteristics of multiple sensors. Extensive evaluation in a real environment indicates that our system is accurate and cost-effective.
MPI Runtime Error Detection with MUST: Advances in Deadlock Detection
Authors: Hilbrich Tobias , Protze Joachim , Schulz Martin , de Supinski Bronis R. , Müller Matthias S.
Published: January 2015

The widely used Message Passing Interface (MPI) is complex and rich. As a result, application developers require automated tools to avoid and to detect MPI programming errors. We present the Marmot Umpire Scalable Tool (MUST) that detects such errors with significantly increased scalability. We present improvements to our graph-based deadlock detection approach for MPI, which cover future MPI extensions. Our enhancements also check complex MPI constructs that no previous graph-based detection approach handled correctly. Finally, we present optimizations for the processing of MPI operations that reduce runtime deadlock detection overheads. Existing approaches often require 𝒪(p) analysis time per MPI operation, forpprocesses. We empirically observe that our improvements lead to sub-linear or better analysis time per operation for a wide range of real world applications.
McrEngine: A Scalable Checkpointing System Using Data-Aware Aggregation and Compression
Authors: Islam Tanzima Zerin , Mohror Kathryn , Bagchi Saurabh , Moody Adam , de Supinski Bronis R. , Eigenmann Rudolf
Published: January 2015

High performance computing (HPC) systems use checkpoint-restart to tolerate failures. Typically, applications store their states in checkpoints on a parallel file system (PFS). As applications scale up, checkpoint-restart incurs high overheads due to contention for PFS resources. The high overheads force large-scale applications to reduce checkpoint frequency, which means more compute time is lost in the event of failure. We alleviate this problem through a scalable checkpoint-restart system, mcrEngine. McrEngine aggregates checkpoints from multiple application processes with knowledge of the data semantics available through widely-used I/O libraries, e.g., HDF5 and netCDF, and compresses them. Our novel scheme improves compressibility of checkpoints up to 115% over simple concatenation and compression. Our evaluation with large-scale application checkpoints show that mcrEngine reduces checkpointing overhead by up to 87% and restart overhead by up to 62% over a baseline with no aggregation or compression.
Automated Quantification of DNA Aneuploidy by Image Cytometry as an Adjunct for the Cytologic Diagnosis of Malignant Effusion
Authors: Meng Zhilan , Shi Jie , Zhu Chenyan , Gu Jiangang , Zhou Chen
Published: January 2015

DNA aneuploidy is a cancer biomarker, which may have a potential diagnostic value in body effusion specimen. DNA aneuploidy is determined by measuring the DNA content of tested cells and comparing them with diploid cells (2c). In order to assess the value of automated DNA image cytometry (DNA-ICM) in the cytologic diagnosis of effusion, we measured DNA ploidy using an automated DNA-ICM analysis system in 126 consecutive effusion specimens and followed the cases for histologic diagnosis. Half of each effusion specimen was used to prepare cytologic smears for conventional cytologic diagnosis, while the other half was used to prepare a monolayer slide stained by Feulgen stain for automated ICM. By using Youden index, we found that 4 cells exceeding 2.5c is the optimal cut off value for aneuploidy, which has a sensitivity of 88.3% and specificity of 100% for diagnosis of malignant effusion. We also found that the DNA aneuploidy thresholds used for other types of cytologic specimens cannot be used in the diagnosis of effusion specimens. Our study demonstrated that automated DNA image cytometry is a simple, practical and cost-effective method for adjunct diagnosis of malignant effusion.
Data Gathering Using Mobile Agents for Reducing Traffic in Dense Mobile Wireless Sensor Networks
Authors: Goto Keisuke , Sasaki Yuya , Hara Takahiro , Nishio Shojiro
Published: January 2015

Recently, there has been increasing interest in Mobile Wireless Sensor Networks (MWSNs) that are constructed by mobile sensor nodes held by ordinary people, and it has led to a new concept called urban sensing. In such MWSNs, mobile sensor nodes densely exist, and thus, there are basically many sensor nodes that can sense a geographical point in the entire sensing area. To reduce the communication cost for gathering sensor data, it is desirable to gather the sensor data from the minimum number of mobile sensor nodes which are necessary to guarantee the sensing coverage or the quality of services. In this paper, to achieve this, we propose a data gathering method using mobile agents in dense MWSNs. The proposed method guarantees the sensing coverage of the entire area using mobile agents that autonomously perform sensing operations, transmit sensor data, and move between sensor nodes. By gathering only sensor data generated by sensor nodes where mobile agents are running, our proposed method can achieve efficient gathering of sensor data.
A Multi-Hop Advertising Discovery and Delivering Protocol for Multi Administrative Domain MANET
Authors: Mari Federico , Melatti Igor , Tronci Enrico , Finzi Alberto
Published: January 2015

A Mobile Ad-hoc NETwork (MANET) is Multi Administrative Domain (MAD) if each network node belongs to an independent authority, that is each node owns its resources and there is no central authority owning all network nodes. One of the main obstructions in designing Service Advertising, Discovery and Delivery (SADD) protocol for MAD MANETs is the fact that, in an attempt to increase their own visibility, network nodes tend to flood the network with their advertisements. In this paper, we present a SADD protocol for MAD MANET, based on Bloom filters, that effectively prevents advertising floods due to such misbehaving nodes. Our results with the ns-2 simulator show that our SADD protocol is effective in counteracting advertising floods, it keeps low the collision rate as well as the energy consumption while ensuring that each peer receives all messages broadcasted by other peers.
A Parallel Ghosting Algorithm for The Flexible Distributed Mesh Database
Authors: Mubarak Misbah , Seol Seegyoung , Lu Qiukai , Shephard Mark S.
Published: January 2015

Critical to the scalability of parallel adaptive simulations are parallel control functions including load balancing, reduced inter-process communication and optimal data decomposition. In distributed meshes, many mesh-based applications frequently access neighborhood information for computational purposes which must be transmitted efficiently to avoid parallel performance degradation when the neighbors are on different processors. This article presents a parallel algorithm of creating and deleting data copies, referred to as ghost copies, which localize neighborhood data for computation purposes while minimizing inter-process communication. The key characteristics of the algorithm are: (1) It can create ghost copies of any permissible topological order in a 1D, 2D or 3D mesh based on selected adjacencies. (2) It exploits neighborhood communication patterns during the ghost creation process thus eliminating all-to-all communication. (3) For applications that need neighbors of neighbors, the algorithm can creatennumber of ghost layers up to a point where the whole partitioned mesh can be ghosted. Strong and weak scaling results are presented for the IBM BG/P and Cray XE6 architectures up to a core count of 32,768 processors. The algorithm also leads to scalable results when used in a parallel super-convergent patch recovery error estimator, an application that frequently accesses neighborhood data to carry out computation.
A Framework for Low-Communication 1-D FFT
Authors: Tang Ping Tak Peter , Park Jongsoo , Kim Daehyun , Petrov Vladimir
Published: January 2015

In high-performance computing on distributed-memory systems, communication often represents a significant part of the overall execution time. The relative cost of communication will certainly continue to rise as compute-density growth follows the current technology and industry trends. Design of lower-communication alternatives to fundamental computational algorithms has become an important field of research. For distributed 1-D FFT, communication cost has hitherto remained high as all industry-standard implementations perform three all-to-all internode data exchanges (also called global transposes). These communication steps indeed dominate execution time. In this paper, we present a mathematical framework from which many single-all-to-all and easy-to-implement 1-D FFT algorithms can be derived. For large-scale problems, our implementation can be twice as fast as leading FFT libraries on state-of-the-art computer clusters. Moreover, our framework allows tradeoff between accuracy and performance, further boosting performance if reduced accuracy is acceptable.
A Divide and Conquer Strategy for Scaling Weather Simulations with Multiple Regions of Interest
Authors: Malakar Preeti , George Thomas , Kumar Sameer , Mittal Rashmi , Natarajan Vijay , Sabharwal Yogish , Saxena Vaibhav , Vadhiyar Sathish S.
Published: January 2015

Accurate and timely prediction of weather phenomena, such as hurricanes and flash floods, require high-fidelity compute intensive simulations of multiple finer regions of interest within a coarse simulation domain. Current weather applications execute these nested simulations sequentially using all the available processors, which is sub-optimal due to their sub-linear scalability. In this work, we present a strategy for parallel execution of multiple nested domain simulations based on partitioning the 2-D processor grid into disjoint rectangular regions associated with each domain. We propose a novel combination of performance prediction, processor allocation methods and topology-aware mapping of the regions on torus interconnects. Experiments on IBM Blue Gene systems using WRF show that the proposed strategies result in performance improvement of up to 33% with topology-oblivious mapping and up to additional 7% with topology-aware mapping over the default sequential strategy.
Sharing with Caution: Managing Parking Spaces in Vehicular Networks
Authors: Delot Thierry , Ilarri Sergio , Lecomte Sylvain , Cenerario Nicolas
Published: January 2015

By exchanging events in a vehicular ad hoc network (VANET), drivers can receive interesting information while driving. For example, they can be informed of available parking spaces in their vicinity. A suitable protocol is needed to disseminate the events efficiently within the area where they are relevant. Moreover, in such a competitive context where each vehicle may be interested in a resource, it is crucial not to communicate that resource to each driver in the vicinity. Otherwise, those drivers would waste time trying to reach a parking space and only one of them would be fulfilled, which would lead to a poor satisfaction in the system.
Efficient and Reliable Network Tomography in Heterogeneous Networks Using Bittorrent Broadcasts and Clustering Algorithms
Authors: Dichev Kiril , Reid Fergal , Lastovetsky Alexey
Published: January 2015

In the area of network performance and discovery, network tomography focuses on reconstructing network properties using only end-to-end measurements at the application layer. One challenging problem in network tomography is reconstructing available bandwidth along all links during multiple source/multiple destination transmissions. The traditional measurement procedures used for bandwidth tomography are extremely time consuming. We propose a novel solution to this problem. Our method counts the fragments exchanged during a BitTorrent broadcast. While this measurement has a high level of randomness, it can be obtained very efficiently, and aggregated into a reliable metric. This data is then analyzed with state-of-the-art algorithms, which correctly reconstruct logical clusters of nodes interconnected by high bandwidth, as well as bottlenecks between these logical clusters. Our experiments demonstrate that the proposed two-phase approach efficiently solves the presented problem for a number of settings on a complex grid infrastructure.
Energy Conservation in Mobile Devices and Applications: A Case for Context Parsing, Processing and Distribution in Clouds
Authors: Kiani Saad Liaquat , Anjum Ashiq , Bessis Nik , Hill Richard , Knappmeyer Michael
Published: January 2015

Context information consumed and produced by the applications on mobile devices needs to be represented, disseminated, processed and consumed by numerous components in a context-aware system. Significant amounts of context consumption, production and processing takes place on mobile devices and there is limited or no support for collaborative modelling, persistence and processing between device-Cloud ecosystems. In this paper we propose an environment for context processing in a Cloud-based distributed infrastructure that offloads complex context processing from the applications on mobile devices. An experimental analysis of complexity based context-processing categories has been carried out to establish the processing-load boundary. The results demonstrate that the proposed collaborative infrastructure provides significant performance and energy conservation benefits for mobile devices and applications.
Cartilage Oligomeric Matrix Protein (COMP)-Mediated Cell Differentiation to Proteolysis Mechanism Networks from Human Normal Adjacent Tissues to Lung Adenocarcinoma
Authors: Wang Lin , Huang Juxiang , Jiang Minghu , Diao Haizhen , Zhou Huilei , Li Xiaohe , Chen Qingchun , Jiang Zhenfu , Feng Haitao , Wolfl Stefan
Published: January 2015

Background: To understand cartilage oligomeric matrix protein (COMP) mechanism network from human normal adjacent tissues to lung adenocarcinoma.

Methods:COMPcomplete different activated (all no positive correlation, Pearson CC< 0.25) and uncomplete (partly no positive correlation exceptCOMP, Pearson CC< 0.25) network were identified in higher lung adenocarcinoma compared with lower human normal adjacent tissues from the correspondingCOMP-stimulated (≥0.25) or inhibited (Pearson CC≤−0.25) overlapping molecules of Pearson correlation coefficient (CC) and GRNInfer, respectively.COMPcomplete different activated and inhibited (all no positive correlation, Pearson CC< 0.25) mechanisms networks of higher lung adenocarcinoma and lower human normal adjacent tissues were constructed by integration of Pearson CC, GRNInfer and GO. As visualized by integration of GO, KEGG, GenMAPP, BioCarta and Disease, we deduced COMP complete different activated and inhibited network in higher lung adenocarcinoma and lower human normal adjacent tissues.

Results: As visualized by GO, KEGG, GenMAPP, BioCarta and disease database integration, we proposed mainly that the mechanism and function ofCOMPcomplete different activated network in higher lung adenocarcinoma was involved inCOMPactivation with matrix-localized insulin-like factor coupling carboxypeptidase to metallopeptidase-induced proteolysis, whereas the corresponding inhibited network in lower human normal adjacent tissues participated inCOMPinhibition with nucleus-localized vasculogenesis, B and T cell differentiation and neural endocrine factors coupling pyrophosphatase-mediated proteolysis. However,COMPcomplete different inhibited network in higher lung adenocarcinoma includedCOMPinhibition with nucleus-localized chromatin maintenance, licensing and assembly factors coupling phosphatase-inhibitor to cytokinesis regulators-mediated cell differentiation, whereas the corresponding activated network in lower human normal adjacent tissues containedCOMPactivation with cytolplasm-localized translation elongation factor coupling fucosyltransferase to ubiquitinprotein ligase-induced cell differentiation.

Conclusion:COMPdifferent networks were verified not only by complete and uncompleteCOMPactivated or inhibited networks within human normal adjacent tissues or lung adenocarcinoma, but also byCOMPactivated and inhibited network between human normal adjacent tissues and lung adenocarcinoma.
Expression of WW Domain-Containing Oxidoreductase WOX1 in Human Nervous System Tumors
Authors: Chiang Ming-Fu , Chen Shur-Tzu , Lo Chen-Peng , Sze Chun-I , Chang Nan-Shan , Chen Yu-Jen
Published: January 2015

Background and ObjectiveS: We aimed to evaluate the expression levels of the tumor suppressor WOX1 in nervous system tumors and its co-expression with p53 and neurofibromatosis type 2/merlin (NF2) tumor suppressor gene products.

Methods: Immunohistochemistry, western blotting andin situhybridization were used for WOX1 protein and WWOX mRNA expression. Immunofluorescence and electron microscopical immunohistochemistry were performed for colocalization of gene products.

Results: WOX1 expression is low in normal cortical neurons, mainly on the axon fibers, whereas there is moderate to high immunoreactivity in the cytosol and nuclei of certain tumor cells. In the microcystic (WHO grade I) and malignant (WHO grade III) meningiomas, WOX1 expression is intense, but various in transitional (WHO grade I) and atypical (WHO grade II) subtypes. WOX1 levels are moderate to high in the menigiotheliomatous area, but relatively low in the fibroblastic area. WOX1 and NF2/merlin, but not p53, colocalized in certain tumor cells, primarily at the borders of nuclei. Schwannoma and astrocytoma specimens stained moderately to strongly positive for the WOX1 protein. Interestingly, the expression of WOX1, NF2/merlin and mutant p53 is intense in high grade glioblastoma, but WOX1 expression is low in metastatic carcinoma or adenocarcinoma.

Conclusions: The expression of WOX1 on different types of nervous system tumors, including primary and metastatic tumors, is differential.
Parameter Estimation for Propagation along Random Rough Surface by Using Line of Sight Data
Authors: Uchida Kazunori , Takematsu Masafumi , Lee Jun-Hyuck , Honda Junichi
Published: January 2015

This paper is concerned with a numerical procedure to estimate two parameters, amplitude modification factor α and propagation order of distance β, for electromagnetic (EM) propagation in complicated natural environments such as random rough surface (RRS). These two parameters are key parameters when we simulate field distributions along various types of RRS based on 1-ray model. We assume that the former parameter α can be evaluated by the visual planar angles of illuminated lines in case of 1D RRS and by the visual solid angles of illuminated planes in case of 2D RRS. We also assume that the latter parameter β can be estimated not only by base station (BS) antenna height, similar to Okumura-Hata model simulating EM propagation in urban and suburban areas, but also by mobile station (MS) antenna height. In order to demonstrate validity of the proposed parameter estimation, we compare the numerical field distributions obtained by the 1-ray model using estimated two parameters with those computed by discrete ray tracing method (DRTM) which is an effective EM field solver. It is shown that both numerical results are in good agreement.
Special Issue on Automatic Application Tuning for HPC Architectures
Authors: Benkner Siegfried , Franchetti Franz , Gerndt Hans Michael , Hollingsworth Jeffrey K.
Published: January 2015

High Performance Computing architectures have become incredibly complex and exploiting their full potential is becoming more and more challenging. As a consequence, automatic performance tuning (autotuning) of HPC applications is of growing interest and many research groups around the world are currently involved. Autotuning is still a rapidly evolving research field with many different approaches being taken. This special issue features selected papers presented at the Dagstuhl seminar on “Automatic Application Tuning for HPC Architectures” in October 2013, which brought together researchers from the areas of autotuning and performance analysis in order to exchange ideas and steer future collaborations.
Coordinated Energy Management in Heterogeneous Processors
Authors: Paul Indrani , Ravi Vignesh , Manne Srilatha , Arora Manish , Yalamanchili Sudhakar
Published: January 2015

This paper examines energy management in a heterogeneous processor consisting of an integrated CPU–GPU for high-performance computing (HPC) applications. Energy management for HPC applications is challenged by their uncompromising performance requirements and complicated by the need for coordinating energy management across distinct core types – a new and less understood problem. We examine the intra-node CPU–GPU frequency sensitivity of HPC applications on tightly coupled CPU–GPU architectures as the first step in understanding power and performance optimization for a heterogeneous multi-node HPC system. The insights from this analysis form the basis of a coordinated energy management scheme, called DynaCo, for integrated CPU–GPU architectures. We implement DynaCo on a modern heterogeneous processor and compare its performance to a state-of-the-art power- and performance-management algorithm. DynaCo improves measured average energy-delay squared (ED2) product by up to 30% with less than 2% average performance loss across several exascale and other HPC workloads.
Scalable Domain Decomposition Preconditioners for Heterogeneous Elliptic Problems
Authors: Jolivet Pierre , Hecht Frédéric , Nataf Frédéric , Prud'homme Christophe
Published: January 2015

Domain decomposition methods are, alongside multigrid methods, one of the dominant paradigms in contemporary large-scale partial differential equation simulation. In this paper, a lightweight implementation of a theoretically and numerically scalable preconditioner is presented in the context of overlapping methods. The performance of this work is assessed by numerical simulations executed on thousands of cores, for solving various highly heterogeneous elliptic problems in both 2D and 3D with billions of degrees of freedom. Such problems arise in computational science and engineering, in solid and fluid mechanics. While focusing on overlapping domain decomposition methods might seem too restrictive, it will be shown how this work can be applied to a variety of other methods, such as non-overlapping methods and abstract deflation based preconditioners. It is also presented how multilevel preconditioners can be used to avoid communication during an iterative process such as a Krylov method.
Ubiquitous Monitoring Solution for Wireless Sensor Networks with Push Notifications and End-to-End Connectivity
Authors: Oliveira Luis M. L. , Rodrigues Joel J. P. C. , Elias André G. F. , Zarpelão Bruno B.
Published: January 2015

Wireless Sensor Networks (WSNs) belongs to a new trend in technology in which tiny and resource constrained devices are wirelessly interconnected and are able to interact with the surrounding environment by collecting data such as temperature and humidity. Recently, due to the huge growth in the use of mobile devices with Internet connection, smartphones are becoming the center of future ubiquitous wireless networks. Interconnecting WSNs with smartphones and the Internet is a big challenge and new architectures are required due to the heterogeneity of these devices. Taking into account that people are using smartphones with Internet connection, there is a good opportunity to propose a new architecture for wireless sensors monitoring using push notifications and smartphones. Then, this paper proposes a ubiquitous approach for WSN monitoring based on a REST Web Service, a relational database, and an Android mobile application. Real-time data sensed by WSNs are sent directly to a smartphone or stored in a database and requested by the mobile application using a well-defined RESTful interface. A push notification system was created in order to alert mobile users when a sensor parameter overcomes a given threshold. The proposed architecture and mobile application were evaluated and validated using a laboratory WSN testbed and are ready for use.
Implementation of D-Spline-Based Incremental Performance Parameter Estimation Method with ppOpen-AT
Authors: Tanaka Teruo , Otsuka Ryo , Fujii Akihiro , Katagiri Takahiro , Imamura Toshiyuki
Published: January 2015

In automatic performance tuning (AT), a primary aim is to optimize performance parameters that are suitable for certain computational environments in ordinary mathematical libraries. For AT, an important issue is to reduce the estimation time required for optimizing performance parameters. To reduce the estimation time, we previously proposed the Incremental Performance Parameter Estimation method (IPPE method). This method estimates optimal performance parameters by inserting suitable sampling points that are based on computational results for a fitting function. As the fitting function, we introduced d-Spline, which is highly adaptable and requires little estimation time. In this paper, we report the implementation of the IPPE method with ppOpen-AT, which is a scripting language (set of directives) with features that reduce the workload of the developers of mathematical libraries that have AT features. To confirm the effectiveness of the IPPE method for the runtime phase AT, we applied the method to sparse matrix–vector multiplication (SpMV), in which the block size of the sparse matrix structure blocked compressed row storage (BCRS) was used for the performance parameter. The results from the experiment show that the cost was negligibly small for AT using the IPPE method in the runtime phase. Moreover, using the obtained optimal value, the execution time for the mathematical library SpMV was reduced by 44% on comparing the compressed row storage and BCRS (block size 8).
Cytologic-Radiologic Correlation Using Transthoracic CT-Guided FNA for Lung and Mediastinal Masses: Our Experience
Authors: Piplani Sanjay , Mannan Rahul , Lalit Monika , Manjari Mridu , Bhasin Tejinder S. , Bawa Jasmin
Published: January 2015

Background and Objectives.Thoracic lesions account for various benign and malignant conditions. Of these lung carcinoma (mainly primary) is the most common carcinoma in the world. The present study was undertaken to know the pathological spectrum of thoracic lesions and to correlate cytoradiological findings.Materials and Methods.The present study was conducted in a tertiary care center of North India on 74 patients over an 18-month period. CT guided transthoracic FNAC (TTFNA) was carried out, and aspirates were drawn, examined, and compared with radiological diagnoses.Results.The diagnostic accuracy for FNA in the present study was calculated to be 95.94% (using cytology as the gold standard). The predominant lesion was malignancy (85.1%), followed by suspicions of malignancy and inflammatory pathology (5.40% each). By cytology, the most common malignant lesion was adenocarcinoma (48%) followed by squamous cell carcinoma (40%), small cell carcinoma (8%), and undifferentiated carcinoma (4%). Cytoradiological correlation was found to be 89.2% in the present study.Conclusion.Present study thus concludes that TT FNA of thoracic lesions is a simple, safe, economically prudent technique associated with low morbidity and leading to quick and early diagnosis.
ELASTIC: A Large Scale Dynamic Tuning Environment
Authors: Martínez Andrea , Sikora Anna , César Eduardo , Sorribes Joan
Published: January 2015

The spectacular growth in the number of cores in current supercomputers poses design challenges for the development of performance analysis and tuning tools. To be effective, such analysis and tuning tools must be scalable and be able to manage the dynamic behaviour of parallel applications. In this work, we present ELASTIC, an environment for dynamic tuning of large-scale parallel applications. To be scalable, the architecture of ELASTIC takes the form of a hierarchical tuning network of nodes that perform a distributed analysis and tuning process. Moreover, the tuning network topology can be configured to adapt itself to the size of the parallel application. To guide the dynamic tuning process, ELASTIC supports a plugin architecture. These plugins, called ELASTIC packages, allow the integration of different tuning strategies into ELASTIC. We also present experimental tests conducted using ELASTIC, showing its effectiveness to improve the performance of large-scale parallel applications.
Design Patterns for Sparse-Matrix Computations on Hybrid CPU/GPU Platforms
Authors: Cardellini Valeria , Filippone Salvatore , Rouson Damian W.I.
Published: January 2015

We apply object-oriented software design patterns to develop code for scientific software involving sparse matrices. Design patterns arise when multiple independent developments produce similar designs which converge onto a generic solution. We demonstrate how to use design patterns to implement an interface for sparse matrix computations on NVIDIA GPUs starting from PSBLAS, an existing sparse matrix library, and from existing sets of GPU kernels for sparse matrices. We also compare the throughput of the PSBLAS sparse matrix–vector multiplication on two platforms exploiting the GPU with that obtained by a CPU-only PSBLAS implementation. Our experiments exhibit encouraging results regarding the comparison between CPU and GPU executions in double precision, obtaining a speedup of up to 35.35 on NVIDIA GTX 285 with respect to AMD Athlon 7750, and up to 10.15 on NVIDIA Tesla C2050 with respect to Intel Xeon X5650.
Delay Tolerant Networking with Data Triage Method based on Emergent User Policies for Disaster Information Network System
Authors: Uchida Noriki , Kawamura Norihiro , Sato Goshi , Shibata Yoshitaka
Published: January 2015

When Disaster Information Network System is considered in local areas that were heavy damaged by the East Japan Great Earthquake in 2011, the resiliency of the network system is one of significant subjects for the restoration of the areas. DTN (Delay Tolerant Network) has been focused for the effective methods for such inoperable network circumstances. However, when DTN is applied for the local areas, there are some problems such as message delivery rate and latency because there are fewer roads, cars, and pedestrians than in urban areas. In this paper, we propose the Enhanced Media Coordinate System for its architecture, and Data Triage method by emergent user policies is introduced to improve the QoS in Disaster Information Network System in local areas. In the proposed method, every message is tagged with the priority levels by data types with considering emergent user policies, and the high priority messages are firstly duplicated to transmittable nodes. Then, the experimental results by the GIS map of a Japanese coastal town and the future studies are discussed.
Nonalcoholic Fatty Liver Disease: Different Classifications Concordance and Relationship between Degrees of Morphological Features and Spectrum of the Disease
Authors: Monteiro Juliana Maya , Monteiro Geysa Maya , Caroli-Bottino Adriana , Pannain Vera Lucia
Published: January 2015

The morphological features of nonalcoholic fatty liver disease (NAFLD) range from steatosis to nonalcoholic steatohepatitis (NASH) and cirrhosis. Liver biopsy remains the main tool for NASH diagnosis and many histological systems to diagnose and grade NAFLD were proposed. We evaluated the relationship among NAFLD activity score (NAS), histological diagnoses (non-NASH, possible NASH, and definite NASH), and histological algorithm proposed by Bedossa et al.; additionally the degrees of morphological features were semiquantified and correlated with non-NASH and NASH. Seventy-one liver biopsies were studied. The agreement among the three systems considering NASH and non-NASH was excellent (Κ=0.96). Among the 22 biopsies with NAS 3-4, 72.7% showed to be NASH according to Bedossa’s algorithm. The degree of steatosis, ballooning, lobular inflammation, and fibrosis stage were correlated with NASH (P<0.001). Fibrosis stage 1 was also found in non-NASH. Over the spectrum of NAFLD, no association was observed between intensity of steatosis and fibrosis grade. The degrees of lobular inflammation showed association with fibrosis stage (P<0.0001). In conclusion, there is agreement among different NAFLD classifications and NAS > 4 may be a better cutoff from which to consider NASH diagnosis; besides the highest degrees of steatosis, ballooning, inflammation, and fibrosis are associated with NASH.
Feature Selection for the Automated Detection of Metaphase Chromosomes: Performance Comparison Using a Receiver Operating Characteristic Method
Authors: Qiu Yuchen , Song Jie , Lu Xianglan , Li Yuhua , Zheng Bin , Li Shibo , Liu Hong
Published: January 2015

Background. The purpose of this study is to identify a set of features for optimizing the performance of metaphase chromosome detection under high throughput scanning microscopy. In the development of computer-aided detection (CAD) scheme, feature selection is critically important, as it directly determines the accuracy of the scheme. Although many features have been examined previously, selecting optimal features is often application oriented.Methods. In this experiment, 200 bone marrow cells were first acquired by a high throughput scanning microscope. Then 9 different features were applied individually to group captured images into the clinically analyzable and unanalyzable classes. The performance of these different methods was assessed by a receiving operating characteristic (ROC) method.Results. The results show that using the number of labeled regions on each acquired image is suitable for the first on-line CAD scheme. For the second off-line CAD scheme, it would be suggested to combine four feature extraction methods including the number of labeled regions, average regions area, average region pixel value, and the standard deviation of either region distance or circularity.Conclusion. This study demonstrates an effective method of feature selection and comparison to facilitate the optimization of the CAD schemes for high throughput scanning microscope in the future.
MATLAB-Like Scripting of Java Scientific Libraries in ScalaLab
Authors: Papadimitriou Stergios , Mavroudi Seferina , Theofilatos Kostas , Likothanasis Spiridon
Published: January 2015

Although there are a lot of robust and effective scientific libraries in Java, the utilization of these libraries in pure Java is difficult and cumbersome, especially for the average scientist that does not expertise in software development. We illustrate that ScalaLab presents an easier and productive MATLAB like front end. Also, the main strengths and weaknesses of the core Java libraries of ScalaLab are elaborated. Since performance is of paramount importance for scientific computation, the article discusses extensively performance aspects of the ScalaLab environment. Also, Java bytecode performance is compared to native code.