Miracle-dz/UniFAR-FTUs huggingface dataset:
Electrocardiographic risk stratification in families with congenital long QT syndrome.

AIMS The QT interval in the surface ECG is one of the most often used risk stratifiers in families with congenital long QT syndrome (LQTS). The best ECG lead for clinical management of LQTS families remains unclear. METHODS AND RESULTS The predictive power of the QTc interval in all ECG leads was studied in 200 consecutive genotyped LQTS family members to identify mutation carriers (n = 103; age: 35+/-19 years) and high-risk LQTS patients (n = 16 with survived sudden cardiac arrest) using receiver operating curve (ROC) analysis (ROC = area under curve). Additionally, the risk for events (syncope and sudden cardiac arrest) was calculated for QTc decile in all individuals. The predictive power was highest in lead II and lead V5 for identifying carriers in LQTS families. These ECG leads were optimal for risk stratification (ROC range 0.83-0.87). In these leads, positive predictive value (PPV) and negative predictive value (NPV) were highest for suggested QTc cut-offs (440 and 500 ms) for identification of LQTS mutation carriers and high-risk patients (PPV between 78-81 and 73-80%, respectively). The risk for events in QTc deciles increased exponentially from 10 to 80% and was 40% for QTc > 500 ms. CONCLUSION On the basis of these data, QTc is the best diagnostic and prognostic ECG parameter in LQTS families. A single measurement should be obtained in lead II if measurable and then in left precordial leads (preferably V5) as a second choice.
A Relational Approach to Novelty Detection in Data Streams

A data stream is a sequence of time-stamped data elements which arrive on-line, at consecutive time points. In this work we propose a multi-relational approach to mine complex data streams in order to identify novelty patterns which target new or unknown situations in the stream. Multi-relational data mining is motivated by the existence of several real-world data stream applications where data elements are complex data scattered in several database relations of a relational database. In our proposal a stream is mined according to a data block model, that is, the stream is segmented in a sequence of data blocks where each data block consists of complex data elements arriving in a user define period (e.g., daily or monthly). A relational pattern base is mined each time a new data block arrives in the stream and a time window is used to filter out novelty patterns. An application of the proposed algorithm to the problem of detecting anomalies in network traffic is described
E-Cigarette: A New Tobacco Product for Schoolchildren in Paris

Objectives: To explore if the dramatic decrease in price of e-cigarette has transformed this new product into a product used for tobacco initiation among a teenage population. Methods: The authors added a question in 2012 on e-cigarette in the yearly survey on tobacco consumption in Paris schoolchildren. The study is conducted on a randomly selected sample from 2% of classes since 1991. Results: 277 (8.1%) of the 3409 schoolchildren studied (including 575 non responders to this question) reported having had an experience with e-cigarette. Experimentation rate is 6.4% among the 12 - 14-year-old, 11.8% among the 15 - 16-year-old and 9% among the 17-year-old schoolchildren. Among the 12 - 14- year-old schoolchildren, 64.4% of e-cigarette experimentation was by non-smokers. Of the 17-year-old teenagers who had used e-cigarettes, 12.4% were non-smokers. For the whole population, 33.2% of those having tried e-cigarette are non-smoker, 22.7% occasional smoker, 3.6% ex-smoker and 40.4% daily smoker. Those who experiment cannabis, shisha or binge-drinking are more frequently users of e-cigarette. In the smoker group, there is an inverse trend of relationship between the readiness to quit tobacco and the rate of use of e-cigarette. Conclusion: For teenager’s, e-cigarettes have become not a product to aid quit tobacco but a product for experimentation and initiation of cigarette use. Regulation is urgently needed to control the emergent use of this new tobacco product by children.
Designing Biomorphs with an Interactive Genetic Algorithm

We describe an interactive version of the Genetic Algorithm which can be used to evolve Fourier series based \biomorphs. " The user plays the role of a binary-valued objective function. The usual Genetic operators of Selection, Mutation, and Crossover are applied normally. We discuss the Inter-active Genetic Algorithm’s use as a teaching tool and in domains in which measures of utility are di(cid:14)cult or impossible to specify mathematically. We argue that the evolution of biomorphs can be considered an ergonomic design problem, and with the evolution of biomorphs as an example, we argue that a large class of design problems can be cast as \imprecise optimization" and \solved" with Interactive Genetic Algorithms. Thus IGAs can be used for applications that fall somewhere between AI, optimization, and CAD.
A hardware and software framework for automotive intelligent lighting

This paper describes the lately completed hardware and software framework in the field of automotive intelligent lighting. Furthermore a brief overview of currently announced concepts within this focus as well as a deducted tendency will be given. As marking spot lights will draw the driver's attention to hazardous objects in the future, the “Automotive Spot Light” as a novel approach on this will be announced. The combination of visual as well as thermal imager both with their advantages will help to decrease fatal injury on the road plus enables new safety light applications.
Testing for non-Gaussianity in the WMAP data: Minkowski functionals and the length of the skeleton

The three Minkowski functionals and the recently defined length of the skeleton are estimated for the co-added first-year WMAP data, and compared with 5000 Monte Carlo simulations, based on Gaussian fluctuations with the a-priori best-fit running-index power spectrum and WMAP -like beam and noise properties. A number of power spectrum dependent quantities, such as the number of stationary points, the total length of the skeleton, and a spectral parameter, γ, are also estimated. While the area and length Minkowski functionals and the length of the skeleton show no evidence for departures from the Gaussian hypothesis, the northern hemisphere genus has a χ that is large at the 95% level on all scales. For a smoothing scale of 8 FWHM it is larger than that found in 99.5% of the simulations. Also, the WMAP genus for negative thresholds in the northern hemisphere has an amplitude that is larger than in the simulations with a significance of more than 3σ. On scales smaller than 2, the number of extrema in the WMAP data is high at the 3σ level. However, this last result can probably be attributed to the effect of point sources. Also, the spectral parameter γ is high at the 99% level in the northern galactic hemisphere, while perfectly acceptable in the southern hemisphere, consistent with the previously reported power asymmetry between the two regions. Subject headings: cosmic microwave background – cosmology: observations – methods: statistical
Collection and analysis of referring expressions used in collaboration

In order to pursue research of referring expressions occurring in interaction between humans and agents, we first set up a data-collection experiment recording human-human interactions. Adopting a collaborationtask of solving the Tangram puzzle by a pair of participants, every utterancein interaction was recordedin synchronysationwith thepositionofeveryTangrampiece andtheoperationscarriedoutonthem by the participants. Referring expressionsin this data were annotatedwith their referentsto build a referring expression corpus. We provide preliminary results of the corpus analysis from various standpoints. Finally, we draw some preliminary conclusions and then discuss ideas on how to extend this research direction.
A pipe-based huge database object replication tool on heterogeneous database clusters

In rising ELT scenarios in data warehouse, for replicating many huge database objects(table/view) between heterogeneous database clusters, we propose a multi-way pipe-based replication architecture and put it into practice. To the best of our knowledge, there are few works on this aspects. Our contributions are from three aspects. The first is introducing a pipe-based architecture to avoid time spent in writing and reading data through an intermediate file, which is implemented on traditional file-based export or import tool. The second is automatically dividing a replication task into several sub-tasks, which will reduce time spent on task resuming when such a task encounters errors. At last, detailed experiments are made and the results show that such an architecture is effective in practical data warehouse projects.
OUT-OF-THE-MONEY: THE IMPACT OF UNDERWATER STOCK OPTIONS ON EXECUTIVE JOB SEARCH

The need for future leadership in organizations is widely recognized, and often addressed through leadership development, succession planning, and building a top talent pipeline among existing employees. Equally important is retaining talented executives. Executive retention has become a concern for organizations as plunging stock prices have led to vastly devalued stock options, perhaps causing executives to look elsewhere for more lucrative stock option portfolios. Yet, there has been little research on the relationship between stock option value and executive retention. In a cross-company, cross-industry sample of 610 U.S. executives, we explored the relationship between underwater stock options and job search. We found a positive association between the percentage of underwater stock options in executives' portfolios and job search. This relationship was moderated as predicted, by executives' perceptions of alternative employment and money inadequacy beliefs.
IITB-Sentiment-Analysts : Participation to Task # 2 Sentiment Analysis in Twitter

We propose a method for using discourse relations for polarity detection of tweets. We have focused on unstructured and noisy text like tweets on which linguistic tools like parsers and POS-taggers don’t work properly. We have showed how conjunctions, connectives, modals and conditionals affect the sentiments in tweets. We have also handled the commonly used abbreviations, slangs and collocations which are usually used in short text messages like tweets. This work focuses on a Web based application which produces results in real time. This approach is an extension of the previous work (Mukherjee et al. 2012).
Model Mental Fisika Siswa SMA dengan Experiential Learning

Abstract: This study aims to examine the effect of experiential learning model on mental model category of students. The method used mixed method design of embedded experimental model with quantitative and qualitative approach. The subject of class XI IPA-A (n = 30) in SMAN 3 Malang. The data collection using the instrument is 9 essay questions. The data were analyzed using effect size and N-gain. Obtained results with mental model category of surface, matching, and deep type. The result shows that the influence of experiential learning model on student's mental model is strong with the effect size value obtained 3.81. As for the mental model changes the students are moderate because the N-Gain value is 0.53. Abstrak: Penelitian ini bertujuan mempelajari pengaruh model pembelajaran experiential learning terhadap kategori model mental siswa. Metode yang digunakan mixed method desain embedded experimental model dengan pendekatan kuantitatif dan kualitatif . Subjek kelas XI IPA-A (n=30) di SMAN 3 Malang. Pengambilan data menggunakan instrumen berupa sembilan soal essay. Hasil data dianalisis menggunakan effect size dan N-gain . Diperoleh hasil dengan kategori model mental tipe surface , matching , dan deep . Hasil didapatkan besar pengaruh model experiential learning terhadap model mental siswa adalah kuat dengan nilai effect size yang didapatkan 3,81. Untuk perubahan model mental siswa adalah sedang karena nilai N-Gain 0,53.
SVM-based audio scene classification

Audio scene classification is very important in audio indexing, retrieval and video content analysis. In this paper we present our approach that uses support vector machine (SVM) for audio scene classification, which classifies audio clips into one of five classes: pure speech, non-pure speech, music, environment sound, and silence. Among them, non-pure speech may further be divided into speech with music and speech with noise. We also describe two methods to select effective and robust audio feature sets. Based on these feature sets, we have evaluated and compared the performance of two kinds of classification frameworks on a testing database that is composed of about 4-hour audio data. The experimental results have shown that the SVM-based method yields high accuracy with high processing speed.
Observations of O I and Ca II Emission Lines in Quasars: Implications for the Site of Fe II Line Emission

We present results of the near-infrared (IR) spectroscopy of six quasars whose redshifts range from 0.158 to 1.084. Combined with the satellite ultraviolet data, the relative line strengths of O I λ1304, O I λ8446, O I λ11287, and the near-IR Ca II triplet are given. In addition, the corresponding O I line strengths measured in normal Seyfert 1s and narrow-line Seyfert 1s are collected from the literature. These lines are thought to emerge from the same gas as do the Fe II lines, so they are good tracers of the Fe II emission region within a broad emission line region (BELR) in active galactic nuclei (AGNs). In order to reveal the physical condition within the relevant emission region, we performed photoionized model calculations and compared them to the observations. It suggests that a rather dense gas with density nH ~ 1011.5 cm-3 is present at an outer portion of the BELR, illuminated by the ionizing radiation corresponding to an ionization parameter U ~ 10-2.5 and is primarily responsible for the observed O I, Ca II, and Fe II lines, based on the resemblance of their profiles. The three O I lines are proven to be formed through Lyβ fluorescence and collisional excitation. We also show that the λ1304 bump typically observed in AGN spectra consists of the comparable contributions of O I and Si II multiplets, and we discuss the origin of such a strong Si II emission. The results are interpreted in the context of the locally optimally emitting cloud (LOC) scenario to find the plausible gas distribution within the BELR as a function of distance from the central source and density.
Semantic mapping with image segmentation using Conditional Random Fields

Most maps used in navigation by mobile robots represent only spatial information. By the other hand, semantic information, which could be thought of as the classification of spatial primitives in different classes, provides structure to spatial information, hence reducing any necessary computation over the final map. This article proposes a semantic mapping process that represents an association between obstacles in a grid-based map and the correspondent regions of interest (ROI) in images from a vision system. The implementation consists of clustering laser measurement points related to a single obstacle and projecting them in images to be segmented using a Conditional Random Field (CRF) model to obtain visual descriptions of the detected obstacles. Results with real data are provided.
Enhanced Empirical Mode Decomposition using a Novel Sifting-Based Interpolation Points Detection

Empirical mode decomposition (EMD) is a signal analysis method which has received much attention lately due its performance in a number of applications. The main disadvantage ntage of EMD is that it is lacking a theoretical foundation and therefore, our understanding of it have come through intuition and experimental validation. This drawback has significantly limited the potential for improvements to the method itself. In other words, the version of EMD currently used by most researchers is roughly the same as that proposed 9 years ago. In this paper, a novel version of EMD is proposed which exhibits significantly improved decomposition performance. This new development exploits the results of a study on EMD concerning the optimized configuration of EMD with respect to criteria for selection of interpolation points.
Bipartite consensus for multi-agent systems on directed signed networks

Collective dynamics is a complex emergence phenomenon yielded by local interactions within multi-agent systems. When agents cooperate or compete in the community, a collective behavior, such as consensus, polarization or diversity, may emerge. In this paper, we investigate a bipartite consensus process, in which all the agents converge to a final state characterized by identical modulus but opposite sign. Firstly, the interaction network of the agents is represented by a directed signed graph. A neighbor-based interaction rule is proposed for each agent with a single integrator dynamics. Then, we classify the signed network into heterogeneous networks and homogeneous networks according to the sign of edges. Under a weak connectivity assumption that the signed network has a spanning tree, some sufficient conditions are derived for bipartite consensus of multi-agent systems with the help of a structural balance theory. At the same time, signless Laplacian matrix and signed Laplacian matrix are introduced to analyze the bipartite consensus of multi-agent systems on homogeneous networks and heterogenous networks, respectively. Finally, simulation results are provided to demonstrate the bipartite consensus formation.
The Emerging Role of Exosomes in Epithelial–Mesenchymal-Transition in Cancer

Metastasis in cancer consists of multiple steps, including epithelial–mesenchymal-transition (EMT), which is characterized by the loss of epithelial-like characteristics and the gain of mesenchymal-like attributes including cell migration and invasion. It is clear that the tumor microenvironment can promote the metastatic cascade and that intercellular communication is necessary for this to occur. Exosomes are small membranous vesicles secreted by most cell types into the extracellular environment and they are important communicators in the tumor microenvironment. They promote angiogenesis, invasion, and proliferation in recipient cells to support tumor growth and a prometastatic phenotype. Although it is clear that exosomes contribute to cancer cell plasticity, experimental evidence to define exosome induced plasticity as EMT is only just coming to light. This review will discuss recent research on exosomal regulation of the EMT process in the tumor microenvironment.
Types and Records for Predication

This paper studies the use of records and dependent types in GF (Grammatical Framework) to build a grammar for predication with an unlimited number of subcategories, also covering extraction and coordination. The grammar is implemented for Chinese, English, Finnish, and Swedish, sharing the maximum of code to identify similarities and differences between the languages. Equipped with a probabilistic model and a large lexicon, the grammar has also been tested in widecoverage machine translation. The first evaluations show improvements in parsing speed, coverage, and robustness in comparison to earlier GF grammars. The study confirms that dependent types, records, and functors are useful in both engineering and theoretical perspectives.
Long‐term consistency in spatial patterns of primate seed dispersal

Abstract Seed dispersal is a key ecological process in tropical forests, with effects on various levels ranging from plant reproductive success to the carbon storage potential of tropical rainforests. On a local and landscape scale, spatial patterns of seed dispersal create the template for the recruitment process and thus influence the population dynamics of plant species. The strength of this influence will depend on the long‐term consistency of spatial patterns of seed dispersal. We examined the long‐term consistency of spatial patterns of seed dispersal with spatially explicit data on seed dispersal by two neotropical primate species, Leontocebus nigrifrons and Saguinus mystax (Callitrichidae), collected during four independent studies between 1994 and 2013. Using distributions of dispersal probability over distances independent of plant species, cumulative dispersal distances, and kernel density estimates, we show that spatial patterns of seed dispersal are highly consistent over time. For a specific plant species, the legume Parkia panurensis, the convergence of cumulative distributions at a distance of 300 m, and the high probability of dispersal within 100 m from source trees coincide with the dimension of the spatial–genetic structure on the embryo/juvenile (300 m) and adult stage (100 m), respectively, of this plant species. Our results are the first demonstration of long‐term consistency of spatial patterns of seed dispersal created by tropical frugivores. Such consistency may translate into idiosyncratic patterns of regeneration.
Software documentation and readability: a proposed process improvement

The paper is based on the premise that the productivity and quality of software development and maintenance, particularly in large and long term projects, is related to software readability. Software readability depends on such things as coding conventions and system overview documentation. Existing mechanisms to ensure readability --- for example, peer reviews --- are not sufficient. The paper proposes that software organizations or projects institute a readability/documentation group, similar to a test or usability group. This group would be composed of programmers and would produce overview documentation and ensure code and documentation readability. The features and functions of this group are described. Its benefits and possible objections to it are discussed.
Research on signal de-noising methods based on the convolution type of wavelet packet transformation

A multi-scale de-noising algorithm based on the con-volution type of wavelet packet transformation is presented. This algorithm overcomes the shortcoming that the length of sequences obtained always decreases with the decomposition scales increasing. The new algorithm improves noise variance estimation methods and keeps the main edges of signal well. A new thresholding function is employed, which is simple in expression and as continuous as the Donohopsilas soft-thresholding function. Moreover, this function overcomes the shortcoming that an invariable dispersion between the estimated wavelet coefficients and the decomposed wavelet coefficients in the soft-thresholding method. Simulation results indicate that this method suppresses the Pseudo-Gibbs phenomena effectively and achieves better SNR gains.