bluuebunny/crossref_metadata_2025 huggingface dataset:
Identification of inflammatory bowel disease-related proteins using a reverse k-nearest neighbor search
Authors: Suratanee Apichat , Plaimas Kitiporn
Published: July 2014

Inflammatory bowel disease (IBD) is a chronic disease whose incidence and prevalence increase every year; however, the pathogenesis of IBD is still unclear. Thus, identifying IBD-related proteins is important for understanding its complex disease mechanism. Here, we propose a new and simple network-based approach using a reverse k-nearest neighbor ( R k NN ) search to identify novel IBD-related proteins. Protein–protein interactions (PPI) and Genome-Wide Association Studies (GWAS) were used in this study. After constructing the PPI network, the R k NN search was applied to all of the proteins to identify sets of influenced proteins among their k-nearest neighbors ( R k NNs ). An observed protein whose influenced proteins were mostly known IBD-related proteins was statistically identified as a novel IBD-related protein. Our method outperformed a random aspect, k NN search, and centrality measures based on the network topology. A total of 39 proteins were identified as IBD-related proteins. Of these proteins, 71% were reported at least once in the literature as related to IBD. Additionally, these proteins were found over-represented in the IBD pathway and enriched in importantly functional pathways in IBD. In conclusion, the R k NN search with the statistical enrichment test is a great tool to identify IBD-related proteins to better understand its complex disease mechanism.
Exploiting Innovation in Dubai SMEs: The Effect of Strategic Orientation on Organizational Determinants
Authors: Al-Ansaari Yahya , Pervan Simon , Xu Jun
Published: July 2014

This study investigates the role of strategic orientations of small- and medium-sized enterprises (SMEs) in an emerging market, namely Dubai in the United Arab Emirates. It uses the business-level typology of Miles and Snow (prospector, analyzer, and defender) to examine the effect of strategic orientations on organizational determinants (organizational culture, technology orientation, alliance and cooperation, and market orientation) and their consequences in terms of innovation. Drawing upon data from 189 Dubai SMEs, the findings reveal that there are differences in the organizational determinants with prospector and defender orientations, with analyzer orientations falling in-between. Prospectors place more reliance than defenders on developing organizational culture, technology orientation, alliance and cooperation, and market orientation. Constant changes in the Dubai business and market environments seem to affect SMEs' strategic orientations and smaller SMEs are more likely to be analyzers than the SMEs employing over 100 staff. This study provides useful insights into the role of strategic orientations and organizational determinants of Dubai SMEs to accomplish successful innovation results.
A pelagic myodocopid ostracod from the Silurian of Arctic Russia
Authors: Perrier Vincent , Bogolepova Olga K. , Gubanov Alexander P. , Siveter David J. , Williams Mark
Published: July 2014

Abstract. The Silurian myodocope ostracod Richteria migrans is reported from Arctic Russia, from Kotel’ny Island (New Siberian Islands) and the Taimyr Peninsula in strata of Ludfordian (late Ludlow, Late Silurian) age. These occurrences extend the biogeographical range of R. migrans from tropical to mid latitudes of the Early Palaeozoic Rheic Ocean in the palaeo-Southern Hemisphere, into subtropical regions of the palaeo-Northern Hemisphere on, or adjacent to, the Siberia Palaeocontinent. The new records reinforce the idea that R. migrans had wide dispersal capacity and probably possessed a pelagic lifestyle. It also endorses the use of R. migrans as a biostratigraphical marker fossil for the Ludfordian Stage, Ludlow Series, Upper Silurian.
Computing Petaflops over Terabytes of Data
Authors: Fabregat-Traver Diego , Bientinesi Paolo
Published: July 2014

In many scientific and engineering applications, one has to solve not one but multiple instances of the same problem. Often times, these problems are linked in a way that allows intermediate results to be reused. A characteristic example for this class of applications is given by the Genome-Wide Association Studies (GWAS), a widely spread tool in computational biology. GWAS entails the solution of up to trillions (10
12
) of correlated generalized least-squares problems, posing a daunting challenge: the performance of petaflops (10
15
floating-point operations) over terabytes (10
12
bytes) of data.

In this article, we design an algorithm for performing GWAS on multicore architectures. This is accomplished in three steps. First, we show how to exploit the relation among successive problems, thus reducing the overall computational complexity. Then, through an analysis of the required data transfers, we identify how to eliminate any overhead due to input/output operations. Finally, we study how to decompose computation into tasks to be distributed among the available cores, to attain high performance and scalability. With our algorithm, a GWAS that currently requires the use of a supercomputer may now be performed in matter of hours on a single multicore node.

The discussion centers around the methodology to develop the algorithm rather than the specific application. We believe this article contributes valuable guidelines of general applicability for computational scientists on how to develop and optimize numerical algorithms.
Efficient Discovery of the Most Interesting Associations
Authors: Webb Geoffrey I. , Vreeken Jilles
Published: July 2014

Self-sufficient itemsets have been proposed as an effective approach to summarizing the key associations in data. However, their computation appears highly demanding, as assessing whether an itemset is self-sufficient requires consideration of all pairwise partitions of the itemset into pairs of subsets as well as consideration of all supersets. This article presents the first published algorithm for efficiently discovering self-sufficient itemsets. This branch-and-bound algorithm deploys two powerful pruning mechanisms based on upper bounds on itemset value and statistical significance level. It demonstrates that finding top-
k
productive and nonredundant itemsets, with postprocessing to identify those that are not independently productive, can efficiently identify small sets of key associations. We present extensive evaluation of the strengths and limitations of the technique, including comparisons with alternative approaches to finding the most interesting associations.
Algorithm 945
Authors: Belson Brandt A. , Tu Jonathan H. , Rowley Clarence W.
Published: July 2014

We describe a new parallelized Python library for model reduction, modal analysis, and system identification of large systems and datasets. Our library, called modred, handles a wide range of problems and any data format.

The modred library contains implementations of the Proper Orthogonal Decomposition (POD), balanced POD (BPOD) Petrov-Galerkin projection, and a more efficient variant of the Dynamic Mode Decomposition (DMD). The library contains two implementations of these algorithms, each with its own advantages. One is for smaller and simpler datasets, requires minimal knowledge to use, and follows a common matrix-based formulation. The second, for larger and more complicated datasets, preserves the abstraction of vectors as elements of a vector space and, as a result, allows the library to work with arbitrary data formats and eases distributed memory parallelization. We also include implementations of the Eigensystem Realization Algorithm (ERA), and Observer/Kalman Filter Identification (OKID). These methods are typically not computationally demanding and are not parallelized. The library is designed to be easy to use, with an object-oriented design, and includes comprehensive automated tests. In almost all cases, parallelization is done internally so that scripts that use the parallelized classes can be run in serial or in parallel without any modifications.
A Model-Based Approach for Crawling Rich Internet Applications
Authors: Dincturk Mustafa Emre , Jourdan Guy-Vincent , Bochmann Gregor V. , Onut Iosif Viorel
Published: July 2014

New Web technologies, like AJAX, result in more responsive and interactive Web applications, sometimes called Rich Internet Applications (RIAs). Crawling techniques developed for traditional Web applications are not sufficient for crawling RIAs. The inability to crawl RIAs is a problem that needs to be addressed for at least making RIAs searchable and testable. We present a new methodology, called “model-based crawling”, that can be used as a basis to design efficient crawling strategies for RIAs. We illustrate model-based crawling with a sample strategy, called the “hypercube strategy”. The performances of our model-based crawling strategies are compared against existing standard crawling strategies, including breadth-first, depth-first, and a greedy strategy. Experimental results show that our model-based crawling approach is significantly more efficient than these standard strategies.
Analyzing and Mining Comments and Comment Ratings on the Social Web
Authors: Siersdorfer Stefan , Chelaru Sergiu , Pedro Jose San , Altingovde Ismail Sengor , Nejdl Wolfgang
Published: July 2014

An analysis of the social video sharing platform YouTube and the news aggregator Yahoo! News reveals the presence of vast amounts of community feedback through comments for published videos and news stories, as well as through metaratings for these comments. This article presents an in-depth study of commenting and comment rating behavior on a sample of more than 10 million user comments on YouTube and Yahoo! News. In this study, comment ratings are considered first-class citizens. Their dependencies with textual content, thread structure of comments, and associated content (e.g., videos and their metadata) are analyzed to obtain a comprehensive understanding of the community commenting behavior. Furthermore, this article explores the applicability of machine learning and data mining to detect acceptance of comments by the community, comments likely to trigger discussions, controversial and polarizing content, and users exhibiting offensive commenting behavior. Results from this study have potential application in guiding the design of community-oriented online discussion platforms.
Design for Online Learning Using a Learner's Perspective Approach
Authors: Conceição Simone C. O.
Published: July 2014

A variety of instructional design models provide pathways for developing courses using different philosophical approaches. However, many design models tend to focus more on the teaching than on the learning portion of the process. Roderick Sims, in his book "Design Alchemy: Transforming the Way We Think About Learning and Teaching," provides an innovative approach to design online instruction that focuses primarily on the learning rather than the teacher or content. He uses the term "design alchemy" to explain how a designer can think about learning and teaching as a practical and effective means to creative online environments that maximize the educational experience. This approach allows for a more flexible and sustainable environment focused on the learner's growth and development.
Clustering high dimensional data
Authors: Kriegel Hans-Peter , Ntoutsi Eirini
Published: July 2014

The goal of this position paper is to contribute to a clear understanding of the commonalities and differences between subspace clustering and text clustering. Often text data is foisted as an ideal fit for subspace clustering due to its high dimensional nature and sparsity of the data. Indeed, the areas of subspace clustering and text clustering share similar challenges and the same goal, the simultaneous extraction of both clusters and the dimensions where these clusters are defined. However, there are fundamental differences between the two areas w.r.t object feature representation, dimension weighting and incorporation of these weights in the dissimilarity computation. We make an attempt to bridge these two domains in order to facilitate the exchange of ideas and best practices between them.
OpenML
Authors: Vanschoren Joaquin , van Rijn Jan N. , Bischl Bernd , Torgo Luis
Published: July 2014

Many sciences have made significant breakthroughs by adopting online tools that help organize, structure and mine information that is too detailed to be printed in journals. In this paper, we introduce OpenML, a place for machine learning researchers to share and organize data in fine detail, so that they can work more effectively, be more visible, and collaborate with others to tackle harder problems. We discuss how OpenML relates to other examples of networked science and what benefits it brings for machine learning research, individual scientists, as well as students and practitioners.
Disk arrays with multiple RAID levels
Authors: Thomasian Alexander
Published: July 2014

We propose Heterogeneous Disk Arrays (HDAs), which allow multiple RAID levels for database applications to coexist in a single disk array accommodating multiple RAID levels. Our main concern is to efficiently utilize disk bandwidth and capacity, while balancing disk loads in a cloud storage environment, however, a small number of disks is considered in this study for illustrative purposes. Individual RAID levels are adjusted to data availability requirements and workload demands. Adopting the most stringent availability requirements for all datasets would incur unnecessarily high bandwidth overhead for updating datasets, which do not have this requirement. Intermixing RAID levels is beneficial from the viewpoint of balancing disk loads, similarly to the striping paradigm in RAID5. The suitability of the RAID levels varies with database applications: RAID5 - reading/writing large datasets for data mining and warehousing, RAID1 -high performance OLTP applications. Several single pass data allocation methods are proposed in this paper and compared using synthetically generated allocation requests in associated papers.
Design and simulation of MAC unit using combinational circuit and adder
Authors: Maitra Subhashis , Sinha Amitabha
Published: July 2014

Hardware and timing complexities of MAC unit to perform arithmetic operation like addition or multiplication especially in the field of Digital Signal Processing (DSP) or Elliptic Curve Cryptography (ECC) are the major issues to the designer. The multiplication operation is essential and abundant in DSP Applications. In order to achieve maximum implementation efficiency and timing performance, designing a DSP systems is critical and frequently presents a significant challenge to hardware engineers. There are certain Multiplier that simplifies this challenge by abstracting away FPGA device specifics, while maintaining the required maximum performance and resource efficiency. These multipliers are able to perform parallel multiplication and hence constant coefficient multiplication, both with differing implementation styles. Again with the aid of instantaneous resource estimation, hardware engineers can rapidly select the optimal solution for their system. The latest additions to the IP provide fine control over the latency using the concept of pipelining of the multipliers that are purely combinatorial to be fully pipelined. Here a new compensation method that reduces both the hardware and timing complexities of the multiplier used for DSP application or ECC application has been proposed. The design of the MAC unit based on the proposed compensation method has been dealt here properly using Xilinx 13.2 and compared with array multiplier, Booth multiplier and Vedic multiplier to show its novelty over them. The hardware complexity is reduced to about 60% of the original multiplier. Design results show that the proposed architecture has lower hardware overhead, lower error and fast operating speed as compared with array, Booth and Vedic multiplier.
Efficient custom computing of fully-streamed lattice boltzmann method on tightly-coupled FPGA cluster
Authors: Sano Kentaro , Kono Yoshiaki , Suzuki Hayato , Chiba Ryotaro , Ito Ryo , Ueno Tomohiro , Koizumi Kyo , Yamamoto Satoru
Published: July 2014

This paper presents the detailed design of a custom computing machine for fully-streamed LBM computation on multiple FPGAs, and evaluates its efficiency with prototype implementation. We design a unit for completely streamed computation including boundary treatment with a newly introduced cell attribute. Experimental results demonstrate that the proposed machine achieves high utilization of PEs, 99 % of the peak performance, for one and two FPGAs computing a large lattice. This is due to our fully-streamed design to allow all arithmetic units to be efficienly utilized with a constant memory bandwidth, and the architecture to exploit a low-latency accelerator domain network (ADN) of a tightly-coupled FPGA cluster for scalable computation.
A hybrid CPU-FPGA system for high throughput (10Gb/s) streaming document classification
Authors: Vanderbauwhede Wim , Frolov Anton , Chalamalasetti Sai Rahul , Margala Martin
Published: July 2014

Processing large volumes of information in real time requires large amounts of computational power, which consumes a significant amount of energy. With the rise in the amount of data produced, energy-efficient high-performance information processing systems are becoming a necessity. We present a hybrid CPU-FPGA system for high-throughput classification of streams of textual documents (e.g. emails or web pages). The current system parses the document stream using a multicore CPU and performs classification on the parsed stream using Field-Programmable Gate Arrays (FPGAs). As an example, we demonstrate a Naive Bayes classifier on the TREC Aquaint dataset. Our current solution can classify 10Gb/s internet traffic in real time. Our aim is to increase the throughput to 100Gb/s by incorporating the parser into the FPGA design.
Customisable pipelined engine for intensity evaluation in multivariate hawkes point processes
Authors: Guo Ce , Luk Wayne , Vinkovskaya Ekaterina , Cont Rama
Published: July 2014

Hawkes processes are point processes that can be used to build probabilistic models to capture occurrence patterns of random events. They are widely used in high-frequency trading, seismic analysis and neuroscience. A critical calculation in Hawkes process models is intensity evaluation. The intensity of a point process represents the instantaneous rate of occurrence of events, but it is computationally expensive and challenging to calculate efficiently in order to make predictions using Hawkes process models. To accelerate the computation, we analyse data dependency in the intensity evaluation routine, and present a strategy to enable multiple intensities to be computed with a single pass through the data. We then design and optimise a pipelined hardware engine based on our strategy. In our experiments, an FPGA-based implementation of the proposed engine is evaluated by four case studies. This implementation achieves up to 94 times speedup over an optimised CPU implementation with one core, and 12 times speedup over a CPU with eight cores.
Reconfigurable and hardwired ORB engine on FPGA by Java-to-HDL synthesizer for realtime application
Authors: Ohkawa Takeshi , Uetake Daichi , Yokota Takashi , Ootsu Kanemitsu , Baba Takanobu
Published: July 2014

A platform for networked FPGA system design, which is named "ORB Engine", is proposed to add more controllability and design productivity on FPGA-based systems composed of software and hardwired IPs. A developer can define an object-oriented interface for the circuit IP in FPGA, and implement the control sequence part using Java. The circuit IP in FPGA can be handled through object-oriented interface from variety of programing languages like C++, Java, Python, Ruby and so on. Application specific and high-efficiency circuit for ORB (Object Request Broker) protocol processing is synthesized from easy-handling Java code using JavaRock Java-to-HDL synthesizer within the de-facto standard CORBA (Common Object Request Broker Architecture). The measurement result shows a very low latency as low as 200us of UDP/IP packet in/out and exhibits a fluctuation free delay performance, which is desirable for real-time applications.
Fixed-point trigonometric functions on FPGAs
Authors: de Dinechin Florent , Istoan Matei , Sergent Guillaume
Published: July 2014

Three approaches for computing sines and cosines on FPGAs are studied in this paper, with a focus of highthroughput pipelined architecture, and state-of-the-art implementation techniques. The first approach is the classical CORDIC iteration, for which we suggest a reduced iteration technique and fine optimizations in datapath width and latency. The second is an ad-hoc architecture specifically designed around trigonometric identities. The third uses a generic table- and DSP-based polynomial approximator. These three architectures are implemented and compared in the FloPoCo framework.
Performance evaluation of 3-D stacked 32-bit parallel multipliers
Authors: Tada Jubee
Published: July 2014

Conventional two-dimensional (2-D) implementation technologies face certain limitations; to overcome these limitations, three-dimensional (3-D) integration technologies have been developed. There has been a focus on circuit partitioning strategies because they play an important role in exploiting the potential of 3-D stacked circuits. The Middle-Grain circuit partitioning strategy has been proposed to exploit the potential of 3-D stacked circuits. The proposed strategy equalizes the area of each layer and avoids the critical paths across different layers as much as possible. In this study, 3-D stacked parallel multipliers are designed using various circuit partitioning strategies. Experimental results demonstrate that the 3-D stacked 32-bit parallel multiplier, designed using the proposed strategy, achieves a 27% delay reduction as compared to the 2-D implementation.
Customisable architectures for the set covering problem
Authors: Guo Liucheng , Thomas David B. , Luk Wayne
Published: July 2014

This paper proposes novel customisable streaming architectures for the NP-hard set covering problem. Our approach covers both exhaustive and genetic algorithms, supporting coarse-grain parallelism and deep pipelines while allowing trade-offs between performance and resource usage. Experiments targeting Maxeler systems show that our FPGA-based designs are more effective than the corresponding multicore software versions. The speed up of the exhaustive algorithm exceeds 250 times, and that of the genetic algorithm exceeds 60 times. Meanwhile, our implementations are more flexible than other FPGA solutions, allowing users to customise parameters at run time without recompilation.
Semi-automated text classification
Authors: Berardi Giacomo
Published: July 2014

There is currently a high demand for information systems that automatically analyze textual data, since many organizations, both private and public, need to process large amounts of such data as part of their daily routine, an activity that cannot be performed by means of human work only. One of the answers to this need is text classification (TC), the task of automatically labelling textual documents from a domain D with thematic categories from a predefined set C. Modern text classification systems have reached high efficiency standards, but cannot always guarantee the labelling accuracy that applications demand. When the level of accuracy that can be obtained is insufficient, one may revert to processes in which classification is performed via a combination of automated activity and human effort.

One such process is semi-automated text classification (SATC), which we define as the task of ranking a set D of automatically labelled textual documents in such a way that, if a human annotator validates (i.e., inspects and corrects where appropriate) the documents in a top-ranked portion of D with the goal of increasing the overall labelling accuracy of D, the expected such increase is maximized. An obvious strategy is to rank D so that the documents that the classifier has labelled with the lowest confidence are top-ranked. In this dissertation we show that this strategy is suboptimal. We develop new utility-theoretic ranking methods based on the notion of validation gain, defined as the improvement in classification efectiveness that would derive by validating a given automatically labelled document. We also propose new effectiveness measures for SATC-oriented ranking methods, based on the expected reduction in classification error brought about by partially validating a ranked list generated by a given ranking method. We report the results of experiments showing that, with respect to the baseline method above, and according to the proposed measures, our utility-theoretic ranking methods can achieve substantially higher expected reductions in classification error. We therefore explore the task of SATC and the potential of our methods, in multiple text classification contexts.

This dissertation is, to the best of our knowledge, the first to systematically address the task of semi-automated text classification.
Particle-Size Distribution Models for the Conversion of Chinese Data to FAO/USDA System
Authors: Shangguan Wei , Dai YongJiu , García-Gutiérrez Carlos , Yuan Hua
Published: July 2014

We investigated eleven particle-size distribution (PSD) models to determine the appropriate models for describing the PSDs of 16349 Chinese soil samples. These data are based on three soil texture classification schemes, including one ISSS (International Society of Soil Science) scheme with four data points and two Katschinski’s schemes with five and six data points, respectively. The adjusted coefficient of determinationr2, Akaike’s information criterion (AIC), and geometric mean error ratio (GMER) were used to evaluate the model performance. The soil data were converted to the USDA (United States Department of Agriculture) standard using PSD models and the fractal concept. The performance of PSD models was affected by soil texture and classification of fraction schemes. The performance of PSD models also varied with clay content of soils. The Anderson, Fredlund, modified logistic growth, Skaggs, and Weilbull models were the best.
Constraint Trajectory Surface-Hopping Molecular Dynamics Simulation of the Photoisomerization of Stilbene
Authors: Lei Yibo , Wu Shaomei , Zhu Chaoyuan , Wen Zhenyi , Lin Sheng-Hsien
Published: July 2014

Combining trajectory surface hopping (TSH) method with constraint molecular dynamics, we have extended TSH method from full to flexible dimensional potential energy surfaces. Classical trajectories are carried out in Cartesian coordinates with constraints in internal coordinates, while nonadiabatic switching probabilities are calculated separately in free internal coordinates by Landau-Zener and Zhu-Nakamura formulas along the seam. Two-dimensional potential energy surfaces of groundS0and excitedS1states are constructed analytically in terms of torsion angle and one dihedral angle around the central ethylenic C=C bond, and the other internal coordinates are all fixed at configuration of the conical intersection. At this conical intersection, the branching ratio from the present simulation is 48 : 52 (33 : 67) initially starting from trans(cis)-Stilbene in comparison with experimental value 50 : 50. Quantum yield for trans-to-cis isomerization is estimated as 49% in very good agreement with experimental value of 55%, while quantum yield for cis-to-trans isomerization is estimated as 47% in comparison with experimental value of 35%.
Prognostic Value of VEGF in Patients Submitted to Percutaneous Coronary Intervention
Authors: Ramos Catarina , Napoleão Patrícia , Selas Mafalda , Freixo Cláudia , Viegas Crespo Ana Maria , Mota Carmo Miguel , Cruz Ferreira Rui , Pinheiro Teresa
Published: July 2014

We examined the longitudinal changes of VEGF levels after percutaneous coronary intervention for predicting major adverse cardiac events (MACE) in coronary artery disease (CAD) patients. VEGF was measured in 94 CAD patients’ serum before revascularization, 1-month and 1-year after. Independently of clinical presentation, patients had lower VEGF concentration than a cohort of healthy subjects (median, IQ: 15.9, 9.0–264 pg/mL versus 419, 212–758 pg/mL;P<0.001) at baseline. VEGF increased to 1-month (median, IQ: 276, 167–498 pg/mL;P<0.001) and remained steady to 1-year (median, IQ: 320, 173–497 pg/mL;P<0.001) approaching control levels. Drug eluting stent apposition and previous medication intake produced a less steep VEGF evolution after intervention (P<0.05). Baseline VEGF concentration <40.8 pg/mL conveyed increased risk for MACE in a 5-year follow-up. Results reflect a positive role of VEGF in recovery and support its importance in CAD prognosis.
Gait Signal Analysis with Similarity Measure
Authors: Lee Sanghyuk , Shin Seungsoo
Published: July 2014

Human gait decision was carried out with the help of similarity measure design. Gait signal was selected through hardware implementation including all in one sensor, control unit, and notebook with connector. Each gait signal was considered as high dimensional data. Therefore, high dimensional data analysis was considered via heuristic technique such as the similarity measure. Each human pattern such as walking, sitting, standing, and stepping up was obtained through experiment. By the results of the analysis, we also identified the overlapped and nonoverlapped data relation, and similarity measure analysis was also illustrated, and comparison with conventional similarity measure was also carried out. Hence, nonoverlapped data similarity analysis provided the clue to solve the similarity of high dimensional data. Considered high dimensional data analysis was designed with consideration of neighborhood information. Proposed similarity measure was applied to identify the behavior patterns of different persons, and different behaviours of the same person. Obtained analysis can be extended to organize health monitoring system for specially elderly persons.
Stereotactic Body Radiotherapy for Small Lung Tumors in the University of Tokyo Hospital
Authors: Yamashita Hideomi , Takahashi Wataru , Haga Akihiro , Kida Satoshi , Saotome Naoya , Nakagawa Keiichi
Published: July 2014

Our work on stereotactic body radiation therapy (SBRT) for primary and metastatic lung tumors will be described. The eligibility criteria for SBRT, our previous SBRT method, the definition of target volume, heterogeneity correction, the position adjustment using four-dimensional cone-beam computed tomography (4D CBCT) immediately before SBRT, volumetric modulated arc therapy (VMAT) method for SBRT, verifying of tumor position within internal target volume (ITV) using in-treatment 4D-CBCT during VMAT-SBRT, shortening of treatment time using flattening-filter-free (FFF) techniques, delivery of 4D dose calculation for lung-VMAT patients using in-treatment CBCT and LINAC log data with agility multileaf collimator, and SBRT method for centrally located lung tumors in our institution will be shown. In our institution, these efforts have been made with the goal of raising the local control rate and decreasing adverse effects after SBRT.
Rapidly Destructive Inflammatory Arthritis of the Hip
Authors: Shu Jenny , Ross Ian , Wehrli Bret , McCalden Richard W. , Barra Lillian
Published: July 2014

Rapidly destructive coxarthrosis (RDC) is a rare syndrome that involves aggressive hip joint destruction within 6–12 months of symptom onset with no single diagnostic laboratory, pathological, or radiographic finding. We report an original case of RDC as an initial presentation of seronegative rheumatoid arthritis (RA) in a 57-year-old Caucasian woman presenting with 6 months of progressive right groin pain and no preceding trauma or chronic steroid use. Over 5 months, she was unable to ambulate and plain films showed complete resorption of the right femoral head and erosion of the acetabulum. There were inflammatory features seen on computed tomography (CT) and magnetic resonance imaging (MRI). She required a right total hip arthroplasty, but arthritis in other joints showed improvement with triple disease modifying antirheumatic drugs (DMARD) therapy and almost complete remission with the addition of adalimumab. We contrast our case of RDC as an initial presentation of RA to 8 RDC case reports of patients with established RA. Furthermore, this case highlights the importance of obtaining serial imaging to evaluate a patient with persistent hip symptoms and rapid functional deterioration.
The Role of Microclot Formation in an Acute Subarachnoid Hemorrhage Model in the Rabbit
Authors: Andereggen Lukas , Neuschmelting Volker , von Gunten Michael , Widmer Hans Rudolf , Fandino Javier , Marbacher Serge
Published: July 2014

Background.Microvascular dysfunction and microthrombi formation are believed to contribute to development of early brain injury (EBI) after aneurysmal subarachnoid hemorrhage (SAH).Objective.This study aimed to determine (i) extent of microthrombus formation and neuronal apoptosis in the brain parenchyma using a blood shunt SAH model in rabbits; (ii) correlation of structural changes in microvessels with EBI characteristics.Methods.Acute SAH was induced using a rabbit shunt cisterna magna model. Extent of microthrombosis was detected 24 h post-SAH (n=8) by fibrinogen immunostaining, compared to controls (n=4). We assessed apoptosis by terminal deoxynucleotidyl transferase nick end labeling (TUNEL) in cortex and hippocampus.Results.Our results showed significantly more TUNEL-positive cells (SAH: 115 ± 13; controls: 58 ± 10;P=0.016) and fibrinogen-positive microthromboemboli (SAH: 9 ± 2; controls: 2 ± 1;P=0.03) in the hippocampus after aneurysmal SAH.Conclusions.We found clear evidence of early microclot formation in a rabbit model of acute SAH. The extent of microthrombosis did not correlate with early apoptosis or CPP depletion after SAH; however, the total number of TUNEL positive cells in the cortex and the hippocampus significantly correlated with mean CPP reduction during the phase of maximum depletion after SAH induction. Both microthrombosis and neuronal apoptosis may contribute to EBI and subsequent DCI.
Least Absolute Deviation Support Vector Regression
Authors: Wang Kuaini , Zhang Jingjing , Chen Yanyan , Zhong Ping
Published: July 2014

Least squares support vector machine (LS‐SVM) is a powerful
tool for pattern classification and regression estimation. However, LS‐SVM is
sensitive to large noises and outliers since it employs the squared loss function.
To solve the problem, in this paper, we propose an absolute deviation loss
function to reduce the effects of outliers and derive a robust regression model
termed as least absolute deviation support vector regression (LAD‐SVR). The
proposed loss function is not differentiable. We approximate it by constructing
a smooth function and develop a Newton algorithm to solve the robust model.
Numerical experiments on both artificial datasets and benchmark datasets
demonstrate the robustness and effectiveness of the proposed method.
Intravitreal Bevacizumab Alone or Combined with Macular Laser Photocoagulation for Recurrent or Persistent Macular Edema Secondary to Branch Retinal Vein Occlusion
Authors: Hirashima Takafumi , Chihara Tomoyuki , Bun Toshitaka , Utsumi Takao , Hirose Miou , Oh Hideyasu
Published: July 2014

Background. To evaluate the efficacy of intravitreal bevacizumab (IVB) injection with or without macular laser photocoagulation (MLP) for recurrent or persistent macular edema (ME) secondary to branch retinal vein occlusion (BRVO).Methods. Thirty-four eyes underwent IVB injection for ME secondary to BRVO as a primary treatment. Twenty of the 34 eyes experienced recurrent or persistent ME after the first IVB. Nine of the 20 eyes (Group 1) were retreated with IVB combined with MLP. The remaining 11 eyes (Group 2) were retreated with IVB alone.Results. In Group 1, the postoperative best corrected visual acuity (BCVA) improved compared with the preoperative value at all follow-up visits, although no statistically significant improvement was observed at 6 months. In contrast, BCVA significantly improved from 0.53 to 0.40 at 6 months (P<0.05) in Group 2.Conclusion. Combined therapy tended to have a smaller effect on visual acuity compared with IVB monotherapy.
Mechatronic Feasibility of Minimally Invasive, Atraumatic Cochleostomy
Authors: Williamson Tom , Du Xinli , Bell Brett , Coulson Chris , Caversaccio Marco , Proops David , Brett Peter , Weber Stefan
Published: July 2014

Robotic assistance in the context of lateral skull base surgery, particularly during cochlear implantation procedures, has been the subject of considerable research over the last decade. The use of robotics during these procedures has the potential to provide significant benefits to the patient by reducing invasiveness when gaining access to the cochlea, as well as reducing intracochlear trauma when performing a cochleostomy. Presented herein is preliminary work on the combination of two robotic systems for reducing invasiveness and trauma in cochlear implantation procedures. A robotic system for minimally invasive inner ear access was combined with a smart drilling tool for robust and safe cochleostomy; evaluation was completed on a single human cadaver specimen. Access to the middle ear was successfully achieved through the facial recess without damage to surrounding anatomical structures; cochleostomy was completed at the planned position with the endosteum remaining intact after drilling as confirmed by microscope evaluation.
Some Interesting Bifurcations of Nonlinear Waves for the Generalized Drinfel’d-Sokolov System
Authors: Cai Huixian , Pan Chaohong , Liu Zhengrong
Published: July 2014

We study the bifurcations of nonlinear waves for the generalized Drinfel’d-Sokolov systemut+(vm)x=0,vt+a(vn)xxx+buxv+cuvx=0calledD(m,n)system. We reveal some interesting bifurcation phenomena as follows. (1) ForD(2,1)system, the fractional solitary waves can be bifurcated from the trigonometric periodic waves and the elliptic periodic waves, and the kink waves can be bifurcated from the solitary waves and the singular waves. (2) ForD(1,2)system, the compactons can be bifurcated from the solitary waves, and the peakons can be bifurcated from the solitary waves and the singular cusp waves. (3) ForD(2,2)system, the solitary waves can be bifurcated from the smooth periodic waves and the singular periodic waves.
Parameters of Drag Reducing Polymers and Drag Reduction Performance in Single-Phase Water Flow
Authors: Abubakar A. , Al-Hashmi A. R. , Al-Wahaibi T. , Al-Wahaibi Y. , Al-Ajmi A. , Eshrati M.
Published: July 2014

This study presents experimental investigation about the effect of polymer parameters on the performance of the drag reducing polymers in single-phase water flowing in a horizontal pipe of 30.6 mm ID. Master solutions (1000 ppm) of ten high-molecular weight polymers were injected at different flow rates to achieve polymer concentrations in the range of 2–40 ppm in the test section. The drag reduction increased with polymer concentration up to 10 ppm, above which it reached a plateau value. While the drag reduction at the plateau value increases with polymer molecular weight, the maximum drag reduction was not affected by the increase in polymer charge density up to 13%. For instance, the maximum drag reduction for anionic polymers with molecular weight 6–8 million Da. and charge density between 5 and 13% was around 60%, which decreased to around 38% for the polymer with charge density of 25%. Ionic polymers provided more drag reduction than nonionic ones. The overall conclusion is that drag reduction depends on polymer ability to form intermolecular associations and/or its flexibility, which can be enhanced by increasing molecular weight, decreasing charge density, and selecting smaller side groups in the main polymer backbone.
Does the Implant Surgical Technique Affect the Primary and/or Secondary Stability of Dental Implants? A Systematic Review
Authors: Shadid Rola Muhammed , Sadaqah Nasrin Rushdi , Othman Sahar Abdo
Published: July 2014

Background. A number of surgical techniques for implant site preparation have been advocated to enhance the implant of primary and secondary stability. However, there is insufficient scientific evidence to support the association between the surgical technique and implant stability.Purpose. This review aimed to investigate the influence of different surgical techniques including the undersized drilling, the osteotome, the piezosurgery, the flapless procedure, and the bone stimulation by low-level laser therapy on the primary and/or secondary stability of dental implants.Materials and methods. A search of PubMed, Cochrane Library, and grey literature was performed. The inclusion criteria comprised observational clinical studies and randomized controlled trials (RCTs) conducted in patients who received dental implants for rehabilitation, studies that evaluated the association between the surgical technique and the implant primary and/or secondary stability. The articles selected were carefully read and classified as low, moderate, and high methodological quality and data of interest were tabulated.Results. Eight clinical studies were included then they were classified as moderate or high methodological quality and control of bias.Conclusions. There is a weak evidence suggesting that any of previously mentioned surgical techniques could influence the primary and/or secondary implant stability.
Performance Analysis of Joint Base-Station Multiantenna Multibeam and Channel Assignment Scheme for Hierarchical Cellular System
Authors: Yang Peng , Liu Dou , Zhang Yan
Published: July 2014

Different from the traditional configuration of hierarchical cellular, we introduce the joint base-station multi-antenna multi-beam and channel assignment scheme for hierarchical cellular in this paper. The proposed scheme is based on multi-beam base-station antenna splitting in the elevation-radiating plane, and a dynamic channel allocation scheme by combining the adaptive antenna technologies. Simulation results show that the proposed configuration of the hierarchical cellular can enhance the spectral efficiency remarkably.
Implementing a Cooking and Dietary Management System Using RFID Technology
Authors: Chen Pai-Hsun , Liang Ying-Hsin , Lin Tsung-Chi
Published: July 2014

The establishment of a database of nutritional ingredients with electronic scales feature provides chefs with conducted cooking; as long as the food category is selected and weighed by order, the nutritional content of the dish will be known. By RFID electronic scales and electronic plate function, the meal intake of nutrients and measurement of food nutrients per meal can reach a daily diet control purpose. The so‐called RFID electronic plate is embedded into the chassis and aplate composed of a plurality of dishes to detect information in the chassis and the various subdishes through RFID reader. The chassis provides users with automatic identification such as physiological signals and doctor’s prescription as an individual dietary recommendation through dietary database. The dietary database, in addition to providing essential food nutrients, can be used to query using keywords and classification methods so as to quickly find the sum ingredients for cooking and ingredients. The chefs instantly know the meals nutrition during ingredients weighing by using RFID electronic scales. End users only need to place the allocated cooking dishes on electronic scales; they can easily know the total own meal intake nutrition.
Intelligent Inventory Control via Ruminative Reinforcement Learning
Authors: Katanyukul Tatpong , Chong Edwin K. P.
Published: July 2014

Inventory management is a sequential decision problem that can be solved with reinforcement learning (RL). Although RL in its conventional form does not require domain knowledge, exploiting such knowledge of problem structure, usually available in inventory management, can be beneficial to improving the learning quality and speed of RL. Ruminative reinforcement learning (RRL) has been introduced recently based on this approach. RRL is motivated by how humans contemplate the consequences of their actions in trying to learn how to make a better decision. This study further investigates the issues of RRL and proposes new RRL methods applied to inventory management. Our investigation provides insight into different RRL characteristics, and our experimental results show the viability of the new methods.
Labial Adhesion with Acute Urinary Retention Secondary to Vaginitis
Authors: Şentürk Şenol , Üstüner Pelin , Balık Gülşah , Kağıtcı Mehmet , Ural Ülkü Mete , Şahin Figen Kır
Published: July 2014

Labial adhesion occurs most often in infants and girls and is usually associated with low estrogen levels. Labial adhesion in the reproductive age group is extremely rare due to abundance of estrogen. Herein we present a case of almost complete labial adhesion with acute urinary retention in a 21-year-old virgin woman secondary to a probable untreated severe vaginitis.
Neural Network Observer‐Based Finite‐Time Formation Control of Mobile Robots
Authors: Zhang Caihong , Sun Tairen , Pan Yongping
Published: July 2014

This paper addresses the leader‐following formation problem of nonholonomic mobile robots. In the formation, only the pose (i.e., the position and direction angle) of the leader robot can be obtained by the follower. First, the leader‐following formation is transformed into special trajectory tracking. And then, a neural network (NN) finite‐time observer of the follower robot is designed to estimate the dynamics of the leader robot. Finally, finite‐time formation control laws are developed for the follower robot to track the leader robot in the desired separation and bearing in finite time. The effectiveness of the proposed NN finite‐time observer and the formation control laws are illustrated by both qualitative analysis and simulation results.
Compressed Sensing and Low‐Rank Matrix Decomposition in Multisource Images Fusion
Authors: Ren Kan , Xu Fuyuan , Gu Guohua
Published: July 2014

We propose a novel super‐resolution multisource images fusion scheme via compressive sensing and dictionary learning theory. Under the sparsity prior of images patches and the framework of the compressive sensing theory, the multisource images fusion is reduced to a signal recovery problem from the compressive measurements. Then, a set of multiscale dictionaries are learned from several groups of high‐resolution sample image’s patches via a nonlinear optimization algorithm. Moreover, a new linear weights fusion rule is proposed to obtain the high‐resolution image. Some experiments are taken to investigate the performance of our proposed method, and the results prove its superiority to its counterparts.
Regularization of DT-MRI Using 3D Median Filtering Methods
Authors: Kwon Soondong , Kim Dongyoun , Han Bongsoo , Kwon Kiwoon
Published: July 2014

DT-MRI (diffusion tensor magnetic resonance imaging) tractography is a method to determine the architecture of axonal fibers in the central nervous system by computing the direction of the principal eigenvectors obtained from tensor matrix, which is different from the conventional isotropic MRI. Tractography based on DT-MRI is known to need many computations and is highly sensitive to noise. Hence, adequate regularization methods, such as image processing techniques, are in demand. Among many regularization methods we are interested in the median filtering method. In this paper, we extended two-dimensional median filters already developed to three-dimensional median filters. We compared four median filtering methods which are two-dimensional simple median method (SM2D), two-dimensional successive Fermat method (SF2D), three-dimensional simple median method (SM3D), and three-dimensional successive Fermat method (SF3D). Three kinds of synthetic data with different altitude angles from axial slices and one kind of human data from MR scanner are considered for numerical implementation by the four filtering methods.