Miracle-dz/UniFAR-FTUs huggingface dataset:
TopicSketch: Real-Time Bursty Topic Detection from Twitter

Twitter has become one of the largest platforms for users around the world to share anything happening around them with friends and beyond. A bursty topic in Twitter is one that triggers a surge of relevant tweets within a short time, which often reflects important events of mass interest. How to leverage Twitter for early detection of bursty topics has therefore become an important research problem with immense practical value. Despite the wealth of research work on topic modeling and analysis in Twitter, it remains a huge challenge to detect bursty topics in real-time. As existing methods can hardly scale to handle the task with the tweet stream in real-time, we propose in this paper Topic Sketch, a novel sketch-based topic model together with a set of techniques to achieve real-time detection. We evaluate our solution on a tweet stream with over 30 million tweets. Our experiment results show both efficiency and effectiveness of our approach. Especially it is also demonstrated that Topic Sketch can potentially handle hundreds of millions tweets per day which is close to the total number of daily tweets in Twitter and present bursty event in finer-granularity.
Feminist NGOs and the European Union: Contracting Opportunities and Strategic Response

European women's organizations were among the first social movements to recognize the European Union (EU) as an important context for claim-making. From the mid-1990s, feminist groups had secured a representation to this transnational opportunity structure in the form of the European Women's Lobby (EWL), which receives EU funding, has access to policy setting, and is credited with a role in the construction and consolidation of EU gender equality policy. More recently, the EWL has experienced a contraction in the EU political opportunity context, a function of Eurocrisis dynamics that deem gender equality too costly at a time of austerity. EU progress on gender equality has stalled, with most policy advanced through non-binding or soft law mechanisms. This work assesses the implications of these shifts for the strategies and patterns of mobilization employed by the EWL as it works to exploit soft law opportunities and develop collaborative strategies with other EU non-governmental organizations (NGOs) and in other intergovernmental fora to promote a gendered analysis of the economic crises. Though this latter strategy is a relatively late and weak engagement on austerity, it marks a departure in strategic terms. The organization has also adopted strategies aimed at compensating for declining resources including seeking out new resource streams and cohering closely to topics where EU funding opportunities remain. Analysis of the EWL's response to this challenging political opportunity structure allows for an assessment of how feminist NGOs deal with austerity-based reductions in the political space and financial support for feminist mobilization and gender equality measures across Europe.
Generalized Data Naming and Scalable State Announcements for Reliable

Traditional ARQ-based reliable protocols for unicast (e.g., TCP) as well as multicast (e.g., Horus, RMTP etc.) use sequential numbering of data units and detect losses from discontinuities in the sequence of received packets. The Application Level Framing (ALF) model encourages application control over loss-detection and recovery. With sequence numbers, the application must express its reliability requirements using sub-sequences of the sequence space. This is both cumbersome and restrictive for applications that have no a priori knowledge of the data stream. Distributed whiteboard applications, webcast, and file system multicasting are some examples of applications where data is continuously generated and receivers cannot predict which sub-sequences must be received reliably.
Vacuum electrical breakdown characteristics and surface condition of Ti electrodes with oxidation conditions

Outgassing from an electrode surface is regarded as a major factor leading to electrical breakdowns in vacuum. Recently oxidation treatment at 200/spl deg/C was reported as an effective means of reducing Ti outgassing. In this paper, we report our measurement and comparison of the electrical breakdown characteristics of Ti electrodes with different oxidation conditions (without oxidation, oxidation at 200/spl deg/C, oxidation at 450/spl deg/C). In addition, we analyzed electrode surfaces before and after breakdown experiments in situ with X-ray photoelectron spectroscopy (XPS). Before oxidation, we machined the electrode's surfaces to the roughness of 0.8 /spl mu/m Rmax with diamond turning. Breakdown experiments demonstrated that the breakdown field is highest at the first application of voltage to electrodes with oxidized at 200/spl deg/C. Before breakdown experiment, surface analysis revealed that all the sample electrodes had a large amount of carbon originating from the hydrocarbons of contaminants, and after the experiments, they revealed that the carbons had disappeared. To obtain breakdown characteristics of electrodes with smoother surfaces, we conducted experiments on electrodes with a surface roughness of 0.05 /spl mu/m Ra. For these electrodes, the breakdown field was higher at first breakdown; the repetitions required to achieve saturated breakdown fields were significantly fewer, and the amount of carbon on electrode surfaces before breakdown was less.
An inference system for detecting firewall filtering rules anomalies

Firewalls are crucial equipments for protecting private networks. However by only deploying firewalls, administrators are far from securing their enterprises networks. Bad configurations may cause serious security breaches and network vulnerabilities. In particular, conflicting filtering rules lead to block legitimate traffic or to accept unwanted packets. We present in this paper a new classification method to detect overlaps between packet filters within one firewall. Our method processes a set of filtering rules that have a variable number of fields. A field has a range of values, represented by an interval or a variable length bit string, that may intersect with the corresponding field ranges of other rules. In order to detect overlaps we organize the conditions of each filtering rule in such a way that we can quickly separate non overlapping rules. This strategy allows us to avoid considering the entire rule header in many cases.
One gene, two diseases and three conformations: Molecular dynamics simulations of mutants of human prion protein at room temperature and elevated temperatures

Fatal familial insomnia (FFI) and Creutzfeldt‐Jakob disease (CJD) are associated to the same mutation at codon 178 but differentiate into clinicopathologically distinct diseases determined by this mutation and a naturally occurring methionine–valine polymorphism at codon 129 of the prion protein gene. It has been suggested that the clinical and pathological difference between FFI and CJD is caused by different conformations of the prion protein. Using molecular dynamics (MD), we investigated the effect of the mutation at codon 178 and the polymorphism at codon 129 on prion protein dynamics and conformation at normal and elevated temperatures. Four model structures were examined with a focus on their dynamics and conformational changes. The results showed differences in stability and dynamics between polymorphic variants. Methionine variants demonstrated a higher stability than valine variants. Elongation of existing β‐sheets and formation of new β‐sheets was found to occur more readily in valine polymorphic variants. We also discovered the inhibitory effect of proline residue on existing β‐sheet elongation. Proteins 2005. © 2005 Wiley‐Liss, Inc.
What Has Research Told Us about the Beginning Music Teacher?

JMTE Recent educational research has suggested that beginning teacher induction and mentor programs are valuable and necessary for the future of teacher education (FeinmanNemser, 2000; Feinman-Nemser, Schwille, Carver, & Yusko, 1999; Griffin, 1999; Huling-Austin, 1994; Scherer, 1999). However, little research has focused on the induction of music teachers (DeLorenzo, 1992; Jones, 1978; Krueger, 1999; Thompson, 1988). As we are currently experiencing a music teacher shortage (Asmus, 1999) and research has continued to suggest that education often loses the “best and the brightest” from the field (Gonzales & Sosa, 1993; National Commission on Teaching and America’s Future, 1996; Schlechty & Vance, 1981, 1983), it is important that music teachers are properly brought into the profession. The National Standards for Arts Education (MENC, 1994) recommends new content emphases for music teachers. New high-stakes accountability programs (Salzman, 2000) in many states will require all teachers to be accountable to a variety of state and national standards. Many music teacher education programs are working to prepare preservice teachers to teach this content. However, research has shown that without proper induction into the field, new teachers will teach only as they were taught and will not further the aims of the profession (Feinman-Nemser, 1983, 2000; Lortie, 1975; Moran, 1990; Reinhartz, 1989). Over the past two decades, school change experts and educational researchers have encouraged teacher educators to address induction and mentoring (Feiman-Nemser, 1983, 2000; Feiman-Nemser, et al., 1999; Fullan, 1991; Gordon, 1991; HulingAustin, 1990, 1992, 1994; HulingAustin, Odell, Ishler, Kay & Edelfelt, 1989; Sarason, 1996; Zeichner, 1983; Zeichner & Gore, 1990). Yet the music education research community has not yet explored this area in depth. There is a need for strong music teachWhat Has Research Told Us about the Beginning Music Teacher?
Preserving Modes and Messages via Diverse Particle Selection

In applications of graphical models arising in domains such as computer vision and signal processing, we often seek the most likely configurations of high-dimensional, continuous variables. We develop a particle-based max-product algorithm which maintains a diverse set of posterior mode hypotheses, and is robust to initialization. At each iteration, the set of hypotheses at each node is augmented via stochastic proposals, and then reduced via an efficient selection algorithm. The integer program underlying our optimization-based particle selection minimizes errors in subsequent max-product message updates. This objective automatically encourages diversity in the maintained hypotheses, without requiring tuning of application-specific distances among hypotheses. By avoiding the stochastic resampling steps underlying particle sum-product algorithms, we also avoid common degeneracies where particles collapse onto a single hypothesis. Our approach significantly outperforms previous particle-based algorithms in experiments focusing on the estimation of human pose from single images.
Chapter II: The Curriculum in the Social Studies1

A CLEAR PICTURE of the development of the social studies curriculum from 1937 through 1940 cannot be obtained by summarizing only the research that would meet the approval of a graduate committee. Numerous reports of successful practice are extremely significant even though they have not been carefully evaluated by objective measures. Materials summarized in this chapter are selected from three sources: (a) a few articles written from such a rich background of experience that their significance cannot be questioned, (b) a number of articles reporting successful practices, and (c) articles that are strictly research.
Extreme-Ultraviolet Images of the Clusters of Galaxies A2199 and A1795: Clear Evidence for a Separate and Luminous Emission Component

Since all of the five clusters of galaxies observed by the Extreme-Ultraviolet Explorer deep survey telescope are found to possess a diffuse EUV-emitting component that is unrelated to the hot intracluster medium (ICM) at X-ray temperatures, the question concerning the nature of this new component has been a subject of controversy. Here we present results of an EUV and soft X-ray spatial analysis of the rich clusters Abell 2199 and 1795. The EUV emission does not resemble the X-ray morphology of clusters: at the cluster core, the EUV contours are organized; at larger radii, they are anisotropic and therefore are unrelated to the hot ICM. The ratio of EUV to soft X-ray intensity rises with respect to cluster radius, to reach values ~10 times higher than that expected from the hot ICM. The strong EUV excess that exists in the absence of soft X-ray excess poses formidable problems for the nonthermal (inverse Compton) scenario but may readily be explained as being due to emission lines from a shocked underionized gas.
Influence, originality and similarity in directed acyclic graphs

We introduce a framework for network analysis based on random walks on directed acyclic graphs where the probability of passing through a given node is the key ingredient. We illustrate its use in evaluating the mutual influence of nodes and discovering seminal papers in a citation network. We further introduce a new similarity metric and test it in a simple personalized recommendation process. This metric's performance is comparable to that of classical similarity metrics, thus further supporting the validity of our framework.
Performance Optimization of Data Mining Application Using Radial Basis Function Classifier

Text data mining is a process of exploratory data analysis. Classification maps data into predefined groups or classes. It is often referred to as supervised learning because the classes are determined before examining the data. This paper describes proposed radial basis function Classifier that performs comparative crossvalidation for existing radial basis function Classifier. The feasibility and the benefits of the proposed approach are demonstrated by means of data mining problem: direct Marketing. Direct marketing has become an important application field of data mining. Comparative Cross-validation involves estimation of accuracy by either stratified k-fold cross-validation or equivalent repeated random subsampling. While the proposed method may have high bias; its performance (accuracy estimation in our case) may be poor due to high variance. Thus the accuracy with proposed radial basis function Classifier was less than with the existing radial basis function Classifier. However there is smaller the improvement in runtime and larger improvement in precision and recall. In the proposed method Classification accuracy and prediction accuracy are determined where the prediction accuracy is comparatively high. Keywords—Text Data Mining, Comparative Cross-validation, Radial Basis Function, runtime, accuracy.
A Structural Bioinformatics Approach to the Analysis of nonsynonymous Single nucleotide polymorphisms (nsSNPS) and their Relation to Disease

The prediction of the effects of nonsynonymous single nucleotide polymorphisms (nsSNPs) on function depends critically on exploiting all information available on the three-dimensional structures of proteins. We describe software and databases for the analysis of nsSNPs that allow a user to move from SNP to sequence to structure to function. In both structure prediction and the analysis of the effects of nsSNPs, we exploit information about protein evolution, in particular, that derived from investigations on the relation of sequence to structure gained from the study of amino acid substitutions in divergent evolution. The techniques developed in our laboratory have allowed fast and automated sequence-structure homology recognition to identify templates and to perform comparative modeling; as well as simple, robust, and generally applicable algorithms to assess the likely impact of amino acid substitutions on structure and interactions. We describe our strategy for approaching the relationship between SNPs and disease, and the results of benchmarking our approach -- human proteins of known structure and recognized mutation.
Examining how preferences for employer branding attributes differ from entry to exit and how they relate to commitment, satisfaction, and retention

Purpose – The aim of this paper is to address three broad questions: Are preferences for branding attributes similar for entry and for retention? Are there generational and career stage differences in one's entry and exit priorities? How is current satisfaction with brand image attributes related to overall commitment, satisfaction and retention? Design/methodology/approach – This paper reports on the results of a survey of 144 workers employed at 37 day care centers in a medium sized Canadian city. Findings – Although the level of respondents' priorities for entry and exit differed, most priorities remained in the same order. However, their perspectives were more disaggregated for entry than for exit, where branding attributes were more strongly correlated. Consistent with the exploration stage of career development, younger people planned to stay a shorter length of time with a particular center. Research limitations/implications – This study includes only child care workers in a small geographic region.
Effective and extensible feature extraction method using genetic algorithm-based frequency-domain feature search for epileptic EEG multiclassification

Abstract In this paper, genetic algorithm-based frequency-domain feature search (GAFDS) method is proposed for the electroencephalogram (EEG) analysis of epilepsy. In this method, frequency-domain features are first searched and then combined with nonlinear features. Subsequently, these features are selected and optimized to classify EEG signals. The extracted features are analyzed experimentally. The features extracted by GAFDS show remarkable independence, and they are superior to the nonlinear features in terms of the ratio of interclass distance and intraclass distance. Moreover, the proposed feature search method can search for features of instantaneous frequency in a signal after Hilbert transformation. The classification results achieved using these features are reasonable; thus, GAFDS exhibits good extensibility. Multiple classical classifiers (i.e., k-nearest neighbor, linear discriminant analysis, decision tree, AdaBoost, multilayer perceptron, and Naïve Bayes) achieve satisfactory classification accuracies by using the features generated by the GAFDS method and the optimized feature selection. The accuracies for 2-classification and 3-classification problems may reach up to 99% and 97%, respectively. Results of several cross-validation experiments illustrate that GAFDS is effective in the extraction of effective features for EEG classification. Therefore, the proposed feature selection and optimization model can improve classification accuracy.
Design and fabrication of the Bosma stripline circulator in LTCC technology

Low temperature co-fired ceramics (LTCC) have shown to be one of the most admirable materials in high-frequency components design ([1], [2]). Low dielectric losses and the applicability of highly conductive materials are making them desirable in production of high quality passive components, most often capacitors and inductors. These are the reasons that made this technology attractive for the circulator fabrication, and present the core of this paper. Bosma type of the circulator with Y-junction configuration is the topic of this work and is intended to use at the 5 GHz. Field analysis and the design of the circulator was adopted from Bosma in [3] and Wu in [4]. Theoretical analysis from these works predicts the values of geometrical parameters and the COMSOL simulation was made to confirm its validity. The fabrication process included standard LTCC production procedure consisting of dielectric and ferrite tape preparation, laser cutting, photolithographic screen stencil preparation, screen printing, lamination and, finally, co-firing. Fabricated samples were magnetically polarized and characterized. To maintain magnetic polarization of the produced circulator, small disk shaped neodymium magnets were placed on top and bottom of the ferrite discs. Measurements and characterization were performed on vector network analyzer in range of 4.5 - 8 GHz.
Developmental expression and distinctive tyrosine phosphorylation of the Eph-related receptor tyrosine kinase Cek9

Cek9 is a receptor tyrosine kinase of the Eph subfamily for which only a partial cDNA sequence was known (Sajjadi, F.G., and E.B. Pasquale. 1993. Oncogene. 8:1807-1813). We have obtained the entire cDNA sequence and identified a variant form of Cek9 that lacks a signal peptide. We subsequently examined the spatio-temporal expression and tyrosine phosphorylation of Cek9 in the chicken embryo by using specific antibodies. At embryonic day 2, Cek9 immunoreactivity is concentrated in the eye, the brain, the posterior region of the neural tube, and the most recently formed somites. Later in development, Cek9 expression is widespread but particularly prominent in neural tissues. In the developing visual system, Cek9 is highly concentrated in areas containing retinal ganglion cell axons, suggesting a role in regulating their outgrowth to the optic tectum. Unlike other Eph-related receptors, Cek9 is substantially phosphorylated on tyrosine in many tissues at various developmental stages. Since autophosphorylation of receptor protein-tyrosine kinases typically correlates with increased enzymatic activity, this suggests that Cek9 plays an active role in embryonic signal transduction pathways.
Stanford I2V: a news video dataset for query-by-image experiments

Reproducible research in the area of visual search depends on the availability of large annotated datasets. In this paper, we address the problem of querying a video database by images that might share some contents with one or more video clips. We present a new large dataset, called Stanford I2V. We have collected more than 3; 800 hours of newscast videos and annotated more than 200 ground-truth queries. In the following, the dataset is described in detail, the collection methodology is outlined and retrieval performance for a benchmark algorithm is presented. These results may serve as a baseline for future research and provide an example of the intended use of the Stanford I2V dataset. The dataset can be downloaded at http://purl.stanford. edu/zx935qw7203.
Architectural Support for Thread-Level Data Speculation

Thread-Level Data Speculation (TLDS) is a technique which enables the optimistic parallelization of applications despite uncertainty as to whether data dependences exist between the resulting threads which would normally make them unsafe to execute in parallel. The basic idea is to speculate that dependences do not exist, and to then recover and restart whenever dependences do occur dynamically. TLDS can accelerate performance when the gain from increased thread-level paral-lelism outweighs the overhead of failed speculation. The bulk of the support for TLDS is managed by software, but hardware provides two key pieces of functionality through an extension to invalidation-based cache coherence: (i) detecting dependence violations, and (ii) buuering speculative side-eeects until they can be safely committed to memory. This paper explores a number of issues regarding architectural support for TLDS, including the software interface to our new hardware mechanisms (which includes extensions to the instruction set), the cache coherence protocol, and further details on how this scheme might be implemented within a modern memory hierarchy. We note that this document is a snapshot of our work in progress in this area, and we expect to reene our scheme in the future as we conduct further experiments as part of the STAMPede project.