Miracle-dz/UniFAR-FTUs huggingface dataset:
Research and implementation of the high-power three-phase sweep incentives source

This paper focuses on the high-power three-phase sweep incentives source, which mainly used digital switching power amplifier technology and combined three-phase topology. Synthesized control (repetitive control and PI control) and single polarity double frequency are used for reducing the output voltage waveform distortion. The optimal control strategies based on the characteristic of imbalance are used for improving the system dynamic response. Adaptive modulation algorithm is proposed for a wide range frequency adjustment. The implementation details based on DSP are also presented in this paper, and the experiments of the sweep incentives source working on 200-2000Hz are shown to prove that the output voltage waveform is excellent (the maximum distortion is less than 2%).
Online Consumers' Switching Behavior: A Buyer-Seller Relationship Perspective

Limited studies have investigated online consumer loyalty and retention from a relationship orientation in electronic commerce research. It is important to understand the differences in relationship orientations between people who have the propensity to stick to particular Web sites (â€œstayersâ€ ) and people who have the propensity to switch to alternative Web sites (â€œswitchersâ€ ). This study proposes a relationship-based classification schema consisting of five dimensions: that is, commitment, trust, satisfaction, comparison level of the alternatives, and nonretrievable investment. Data were collected from 299 college students who had experience with e-commerce Web sites. Using discriminating analysis, we found that stayers and switchers were significantly different along the five research dimensions. Satisfaction with the current Web site was the most important discriminant factor, followed by trust, commitment, comparison level of alternative Web sites, and nonretrievable investment in the current Web site. Implications of the findings for researchers and practitioners are discussed.
Learning to Perceive Transparency from the Statistics of Natural Scenes

Certain simple images are known to trigger a percept of transparency: the input image I is perceived as the sum of two images I(x,y) = I1(x,y) + I2(x,y). This percept is puzzling. First, why do we choose the "more complicated" description with two images rather than the "simpler" explanation I(x,y) = I1(x,y) + 0 ? Second, given the infinite number of ways to express I as a sum of two images, how do we compute the "best" decomposition? Here we suggest that transparency is the rational percept of a system that is adapted to the statistics of natural scenes. We present a probabilistic model of images based on the qualitative statistics of derivative filters and "corner detectors" in natural scenes and use this model to find the most probable decomposition of a novel image. The optimization is performed using loopy belief propagation. We show that our model computes perceptually "correct" decompositions on synthetic images and discuss its application to real images.
Automatic MeSH term assignment and quality assessment

For computational purposes documents or other objects are most often represented by a collection of individual attributes that may be strings or numbers. Such attributes are often called features and success in solving a given problem can depend critically on the nature of the features selected to represent documents. Feature selection has received considerable attention in the machine learning literature. In the area of document retrieval we refer to feature selection as indexing. Indexing has not traditionally been evaluated by the same methods used in machine learning feature selection. Here we show how indexing quality may be evaluated in a machine learning setting and apply this methodology to results of the Indexing Initiative at the National Library of Medicine.
Polymer/Graphite Nanocomposites: Physical Features, Fabrication and Current Relevance

Advancement from graphite to functional polymer/graphite nanocomposite is presented in this review article. These materials are comprised of graphite as filler, i.e., carbon-based thermodynamically stable, pseudo–-two-dimensional (2D), planar and layered solid material. Graphite and its modified forms propose unique properties to composites as high surface area, thermal and electrical conductivity as well as mechanical and barrier properties compared to neat polymers. Fine dispersion of graphitic fillers depends on selection of the appropriate fabrication technique including solution mixing; melt blending and in-situ polymerization. The corresponding significance of polymer/graphite-based nanomaterials, challenges, exploitation and future aspects of the materials is overviewed. GRAPHICAL ABSTRACT
Bayesian registration for anatomical landmark detection

In order to perform medical image registration, landmarks are used to settle correspondences between images. A landmark is a voxel in the image that corresponds to a well-defined point in the anatomy. Manual landmarking is a difficult, tedious and time-consuming procedure that would gain to be automated. We propose a Bayesian approach for automatic landmarking. Using training data, we learn the geometry through a probabilistic template. Landmarking consists then in estimating an affine transformation mapping the image onto the template. We use gradient ascent in the likelihood function to perform this task. Experiments validate the methodology for landmarking the temporal lobe in MR brain images
Dosage Determination of Ultrasmall Particles of Iron Oxide for the Delineation of Microvasculature in the Wistar Rat Brain

Purpose:This investigation sought to optimize ultrasmall particles of iron oxide (USPIO) contrast agent dosage for visualizing cerebral microvasculature on an 8.0-Tesla ultra high field magnetic resonance imaging system. Materials and Methods:USPIO contrast agent was intravenously administered to 3 groups of 4 rats at 1, 2, and 3 mg Fe/kg. Each animal was scanned before and after injection of USPIO using a high resolution T2*-weighted gradient recalled echo sequence with an in-plane resolution of 78 &mgr;m. The signal-to-noise ratio (SNR) and the number of microvessels visualized within the cortex and basal ganglia were calculated and compared before and after the administration of USPIO. Results:As the USPIO dose increased, microvascular conspicuity increased, and SNR decreased. A dosage of 2 mg Fe/kg improved microvascular visualization in both cortex and basal ganglion regions relative to 1 mg Fe/kg without significantly sacrificing SNR as was the case at 3 mg Fe/kg. Conclusion:Two mg Fe/kg USPIO is an optimal dose when imaging normal rat cerebral microvasculature using GRE T2*-weighted MR imaging at a field strength of 8 T.
Novel Strategy to Evaluate Infectious Salmon Anemia Virus Variants by High Resolution Melting

Genetic variability is a key problem in the prevention and therapy of RNA-based virus infections. Infectious Salmon Anemia virus (ISAv) is an RNA virus which aggressively attacks salmon producing farms worldwide and in particular in Chile. Just as with most of the Orthomyxovirus, ISAv displays high variability in its genome which is reflected by a wider infection potential, thus hampering management and prevention of the disease. Although a number of widely validated detection procedures exist, in this case there is a need of a more complex approach to the characterization of virus variability. We have adapted a procedure of High Resolution Melting (HRM) as a fine-tuning technique to fully differentiate viral variants detected in Chile and projected to other infective variants reported elsewhere. Out of the eight viral coding segments, the technique was adapted using natural Chilean variants for two of them, namely segments 5 and 6, recognized as virulence-associated factors. Our work demonstrates the versatility of the technique as well as its superior resolution capacity compared with standard techniques currently in use as key diagnostic tools.
CASA: a server for the critical assessment of protein sequence alignment accuracy

SUMMARY A public server for evaluating the accuracy of protein sequence alignment methods is presented. CASA is an implementation of the alignment accuracy benchmark presented by Sauder et al. (Proteins, 40, 6-22, 2000). The benchmark currently contains 39321 pairwise protein structure alignments produced with the CE program from SCOP domain definitions. The server produces graphical and tabular comparisons of the accuracy of a user's input sequence alignments with other commonly used programs, such as BLAST, PSI-BLAST, Clustal W, and SAM-T99. AVAILABILITY The server is located at http://capb.dbi. udel.edu/casa.
Centrality measures with a new index called E-User (Effective User) Index for determiningthe most effective user in Twitter Online Social Network

In this study, we considered the issue of determination of the most effective user in the twitter online social network. We worked on asocial network graph which have relationships (edges) between users who posteda tweet and other users who re-posted it. In other words, we assume that there is a relationship between User-X and User-Y when User-X posted a tweet and User-Y re-postedit. In Social Network Analysis (SNA), there are four fundamental centrality measures such as Degree Centrality, Closeness Centrality, Betweenness Centrality, and Eigenvector Centralities.We developed a new approach for determiningthe most effective user in Twitter online social network by using an index named E-User (Effective User) Index.Through this index, we think that we are able to obtain more realistic results in SNA for Twitter.We designed a small weighted and directed social network graph by using a simulated data and used it for determining the most effective user in this study. In our graph, weights indicate the number of retweets between a user and other user, and directions indicate which user did retweet to other user’s tweet. In the graph, directions can be bidirected. This means that both users did retweet their tweets to each other.
Fragmentation of Care and the Use of Head Computed Tomography in Patients With Ischemic Stroke

Background—Computed tomographic (CT) scans are central diagnostic tests for ischemic stroke. Their inefficient use is a negative quality measure tracked by the Centers for Medicare and Medicaid Services. Methods and Results—We performed a retrospective analysis of Medicare fee-for-service claims data for adults admitted for ischemic stroke from 2008 to 2009, with 1-year follow-up. The outcome measures were risk-adjusted rates of high-intensity CT use (≥4 head CT scans) and risk- and price-adjusted Medicare expenditures in the year after admission. The average number of head CT scans in the year after admission, for the 327 521 study patients, was 1.94, whereas 11.9% had ≥4. Risk-adjusted rates of high-intensity CT use ranged from 4.6% (Napa, CA) to 20.0% (East Long Island, NY). These rates were 2.6% higher for blacks than for whites (95% confidence interval, 2.1%–3.1%), with considerable regional variation. Higher fragmentation of care (number of different doctors seen) was associated with high-intensity CT use. Patients living in the top quintile regions of fragmentation experienced a 5.9% higher rate of high-intensity CT use, with the lowest quintile as reference; the corresponding odds ratio was 1.77 (95% confidence interval, 1.71–1.83). Similarly, 1-year risk- and price-adjusted expenditures exhibited considerable regional variation, ranging from $31 175 (Salem, MA) to $61 895 (McAllen, TX). Regional rates of high-intensity CT scans were positively associated with 1-year expenditures (r=0.56; P<0.01). Conclusions—Rates of high-intensity CT use for patients with ischemic stroke reflect wide practice patterns across regions and races. Medicare expenditures parallel these disparities. Fragmentation of care is associated with high-intensity CT use.
16 Terpenoids and Gibberellic Acids Interaction in Plants

Plants synthesize an astonishing diversity of isoprenoids, some of which play essential roles in photosynthesis, respiration, and the regulation of growth and development. In spite of economic significance of the terpenoids and their many essential functions, relatively little is known about terpenoid metabolism and its regulation in plants (Mansouri et al, 2009). However, two independent patheways for the biosynthesis of isoprenoid precursors coexist within the plant cell: the cytosolic mevalonic acid (MVA) pathway and the plastidial methyerythritol phosphate (MEP) pathway. Cannabis is a diecious species that is a source of fiber, food, oil and medicine. Cannabinoids represent a distinctive class of compounds belong to the chemical class of natural terpenophenols. Among others, Δ9-tetrahycannabinol (THC) and cannabidiol (CBD) are the most important of these compounds. The experiments with labeling patterns showed that the cannabinoids are derived entirely or predominantly (98%) from the deoxyxylulose pathway (Fellemeier et al., 2001). They are produced by glandular trichomes that occur on most aerial surfaces of the plant (Hilling 2004). Cannabis is used in modern medicine for the treatment of emesis in chemotherapy. As well as being useful anti-emetics, cannabinoids appear to have therapeutic value as antispasmodics, analgesics, and appetite stimulants and have potential in the treatment of epilepsy, glaucoma, and asthma (Agurell and Nilsson 1972; Guzman 2003; Howlett et al., 2004).
Cyclin D1 Expression in Breast Cancer Patients Receiving Adjuvant Tamoxifen-Based Therapy

Purpose: The objective of our study was to determine the clinical relevance of cyclin D1 expression in hormone receptor–positive breast cancer patients who were treated with tamoxifen-based therapy. Experimental Design: We assessed expression of cyclin D1 in surgical specimens of breast carcinoma by means of immunohistochemistry. Patients had been enrolled in either Austrian Breast and Colorectal Cancer Study Group (ABCSG) Trial 05 or ABCSG Trial 06 and received tamoxifen as part of their adjuvant treatment. Overall survival and relapse-free survival were analyzed with Cox models adjusted for clinical and pathologic factors. Results: Cyclin D1 was expressed in 140 of 253 (55%) tumors of ABCSG Trial 05 and in 569 of 948 (60%) tumors of ABCSG Trial 06. Expression of cyclin D1 was associated with poor outcome in both cohorts. Overall survival was significantly shorter in patients with cyclin D1–positive tumors compared with patients with cyclin D1–negative tumors [adjusted hazard ratio (HR) for death (ABCSG Trial 05), 2.47; 95% confidence interval (95% CI), 1.08-5.63; P = 0.03; adjusted HR for death (ABCSG Trial 06), 1.78; 95% CI, 1.36-2.34; P < 0.0001]. Relapse-free survival was also shorter in patients with cyclin D1–positive tumors than in patients with cyclin D1–negative tumors [adjusted HR for relapse (ABCSG Trial 05), 2.73; 95% CI, 1.50-4.96; P = 0.001; adjusted HR for relapse (ABCSG Trial 06), 1.52; 95% CI, 1.14-2.04; P = 0.005]. Conclusion: Cyclin D1 expression is an independent poor prognostic factor in women with early-stage, hormone receptor–positive breast cancer who received adjuvant tamoxifen-based therapy.
Ontological Specification of Performance Models for Multi-agent Systems

Large-scale multi-agent systems (MAS) utilize performance models for their optimization. These models could be queueing network models such as Jackson or BCMP networks that can capture the flow of tasks through the network of agents and estimate quantities such as response time and queue lengths. The selection of the model and subsequent analysis of the system is often done offline. We propose a generic ontological framework to capture the semantics of various performance models to facilitate online analysis of MAS with minimal human interaction. Through the framework, we illustrate the specification of queueing models used for MAS performance optimization.
Advanced SAT-Techniques for Bounded Model Checking of Blackbox Designs

In this paper we will present an optimized structural 01X-SAT-solver for bounded model checking of blackbox designs that exploits semantical knowledge regarding the node selection during SAT search. Experimental results show that exploiting the problem structure in this way speeds up the 01X-SAT-solver considerably. Additionally, we give a concise first-order formulation that is more expressive than using 01X-logic. This formulation leads to hard-to-solve QBF formulas for which experimental results from the QBF Evaluation 2006 are presented.
Integrated Collaborative Filtering for Implicit Feedback Incorporating Covisitation

Collaborative filtering with only implicit feedbacks has become a quite common scenario (e.g. purchase history, click-through log, and page visitation). This kind of feedback data only has a small portion of positive instances reflecting the user’s interaction. Such characteristics pose great challenges to dealing with implicit recommendation problems. In this letter, we take full advantage of matrix factorization and relative preference to make the recommendation model more scalable and flexible. In addition, we propose to take into consideration the concept of covisitation which captures the underlying relationships between items or users. To this end, we propose the algorithm Integrated Collaborative Filtering for Implicit Feedback incorporating Covisitation (ICFIF-C) to integrate matrix factorization and collaborative ranking incorporating the covisitation of users and items simultaneously to model recommendation with implicit feedback. The experimental results show that the proposed model outperforms state-of-the-art algorithms on three standard datasets. key words: collaborative filtering, implicit feedback, matrix factorization, covisitation, relative preference
Segmentation Based Interest Points and Evaluation of Unsupervised Image Segmentation Methods

This paper investigates segmentation based interest points for matching and recognition. We propose two simple methods for extracting features from the segmentation maps, which focus on the boundaries and centres of the gravity of the segments. In addition, this can be considered a novel approach for evaluating unsupervised image segmentation algorithms. Former evaluations aim at estimating segmentation quality by how well resulting segments adhere to the contours separating ground-truth foregrounds from backgrounds and therefore explicitly focus on particular objects of interest. In contrast, we propose to measure the robustness of segmentations by the repeatability of features extracted from segments on images related by various geometric and photometric transformations. Further, our evaluation provides a new insight into suitability of the segmentation methods for generating local features for image retrieval or recognition. Several segmentation methods are evaluated and compared to state-of-the art interest point detectors using the repeatability criteria as well as standard matching and recognition benchmarks.
Biller : Adaptive Bayesian Regression Splines in Semiparametric Generalized Linear Models

This paper presents a fully Bayesian approach to regression splines with automatic knot selection in generalized semiparametric models for fundamentally non Gaussian responses In a basis function representation of the regression spline we use a B spline basis The reversible jump Markov chain Monte Carlo method allows for simultaneous estimation both of the number of knots and the knot placement together with the unknown basis coe cients determining the shape of the spline Since the spline can be represented as design matrix times unknown basis coe cients it is straightforward to include additionally a vector of covariates with xed e ects yielding a semiparametric model The method is illustrated with data sets from the literature for curve estimation in generalized linear models the Tokyo rainfall data and the coal mining disaster data and by a credit scoring problem for generalized semiparametric models
Multillingual Corpora – Current Practice and Future Trends

In this paper I would like to give an overview of multilingual corpus building to date. In doing so, I will review two types of multilingual corpus, parallel and translation corpora. Following this, I will consider what tools are currently available which allow for the exploitation of such corpora in the context of machine/machine aided translation. Throughout I will give a fairly global view of work in this area, but will concentrate largely on work undertaken at Lancaster, a major centre of multilingual corpus construction and exploitation.
The MIT Press Journals

In this article we propose a strategy for the summarization of scientiﬁc articles that concentrates on the rhetorical status of statements in an article: Material for summaries is selected in such a way that summaries can highlight the new contribution of the source article and situate it with respect to earlier work. We provide a gold standard for summaries of this kind consisting of a substantial corpus of conference articles in computational linguistics annotated with human judgments of the rhetorical status and relevance of each sentence in the articles. We present several experiments measuring our judges’ agreement on these annotations. We also present an algorithm that, on the basis of the annotated training material, selects content from unseen articles and classiﬁes it into a ﬁxed set of seven rhetorical categories. The output of this extraction and classiﬁcation system can be viewed as a single-document summary in its own right; alternatively, it provides starting material for the generation of task-oriented and user-tailored summaries designed to give users an overview of a scientiﬁc ﬁeld.
Mutant Screen Distinguishes between Residues Necessary for Light-Signal Perception and Signal Transfer by Phytochrome B

The phytochromes (phyA to phyE) are a major plant photoreceptor family that regulate a diversity of developmental processes in response to light. The N-terminal 651–amino acid domain of phyB (N651), which binds an open tetrapyrrole chromophore, acts to perceive and transduce regulatory light signals in the cell nucleus. The N651 domain comprises several subdomains: the N-terminal extension, the Per/Arnt/Sim (PAS)-like subdomain (PLD), the cGMP phosphodiesterase/adenyl cyclase/FhlA (GAF) subdomain, and the phytochrome (PHY) subdomain. To define functional roles for these subdomains, we mutagenized an Arabidopsis thaliana line expressing N651 fused in tandem to green fluorescent protein, β-glucuronidase, and a nuclear localization signal. A large-scale screen for long hypocotyl mutants identified 14 novel intragenic missense mutations in the N651 moiety. These new mutations, along with eight previously identified mutations, were distributed throughout N651, indicating that each subdomain has an important function. In vitro analysis of the spectral properties of these mutants enabled them to be classified into two principal classes: light-signal perception mutants (those with defective spectral activity), and signaling mutants (those normal in light perception but defective in intracellular signal transfer). Most spectral mutants were found in the GAF and PHY subdomains. On the other hand, the signaling mutants tend to be located in the N-terminal extension and PLD. These observations indicate that the N-terminal extension and PLD are mainly involved in signal transfer, but that the C-terminal GAF and PHY subdomains are responsible for light perception. Among the signaling mutants, R110Q, G111D, G112D, and R325K were particularly interesting. Alignment with the recently described three-dimensional structure of the PAS-GAF domain of a bacterial phytochrome suggests that these four mutations reside in the vicinity of the phytochrome light-sensing knot.