Miracle-dz/UniFAR-FTUs huggingface dataset:
A Fast and Scalable Multiobjective Genetic Fuzzy System for Linguistic Fuzzy Modeling in High-Dimensional Regression Problems

Linguistic fuzzy modeling in high-dimensional regression problems poses the challenge of exponential-rule explosion when the number of variables and/or instances becomes high. One way to address this problem is by determining the used variables, the linguistic partitioning and the rule set together, in order to only evolve very simple, but still accurate models. However, evolving these components together is a difficult task, which involves a complex search space. In this study, we propose an effective multiobjective evolutionary algorithm that, based on embedded genetic database (DB) learning (involved variables, granularities, and slight fuzzy-partition displacements), allows the fast learning of simple and quite-accurate linguistic models. Some efficient mechanisms have been designed to ensure a very fast, but not premature, convergence in problems with a high number of variables. Further, since additional problems could arise for datasets with a large number of instances, we also propose a general mechanism for the estimation of the model error when using evolutionary algorithms, by only considering a reduced subset of the examples. By doing so, we can also apply a fast postprocessing stage for further refining the learned solutions. We tested our approach on 17 real-world datasets with different numbers of variables and instances. Three well-known methods based on embedded genetic DB learning have been executed as references. We compared the different approaches by applying nonparametric statistical tests for multiple comparisons. The results confirm the effectiveness of the proposed method not only in terms of scalability but in terms of the simplicity and generalizability of the obtained models as well.
Are Abell Clusters Correlated with Gamma-Ray Bursts?

A recent study has presented marginal statistical evidence that gamma-ray burst (GRB) sources are correlated with Abell clusters, based on analyses of bursts in the BATSE 3B catalog. Using precise localization information from the Third Interplanetary Network, we have reanalyzed this possible correlation. We find that most of the Abell clusters that are in the relatively large 3B error circles are not in the much smaller IPN/BATSE error regions. We believe that this argues strongly against an Abell cluster-GRB correlation.
Semantic enterprise application integration standards

This paper investigates the potential of the Semantic Web technologies to support a semantic-based Enterprise Application Integration (EAI) standards architecture. We give detailed information of the support that these technologies and the underlying Description Logics (DL) formalism provide for the integration task. Our main aim is to assess the potential impact of these emerging technologies on industrial interoperability efforts. In addition to that effect, we plan to use this advanced EAI standards architecture as an experimental framework in which the Semantic Web technologies are evaluated on realistic enterprise integration problems. We illustrate novel capabilities beyond the existing syntactic integration approaches when managing multiple enterprise ontologies derived from a common ontology.
Infestation by triatomine bugs in indigenous communities of Valledupar, Colombia.

OBJECTIVE To calculate triatomine infestation indices in indigenous communities in Colombia. METHODS A descriptive study was carried out in 19 communities in Valledupar Municipality, Cesar Department, Colombia. During June to December, 2007, triatromine bugs were collected from their resting places in households. Taxonomic identification was made according to the keys by Lent & Wygodzinsky. An infection process in animal model and isozyme analysis of triatomine feces were performed. RESULTS Rhodnius prolixus showed a density index of 154.7%, for Triatoma dimidiata was 102.45%, T. maculata 109.25% and Panstrogylus geniculatus 0.3%. The mean infestation index was 40.54%, and mean Trypanosoma infection index was 9.4%. Of five hemocultures positive for T. cruzi, three were enzimatically identified as T. cruzi group I. Biopsies revealed few pathologic characteristics of infective process with these strains isolated from domiciliary triatomine bugs. CONCLUSIONS The high triatomine infestation indices in households and the T. cruzi infection index are evidence of active transmission of Chagas disease. The situation merits a vector control program and serological survey of the population at risk. The genetic characterization of T. cruzi strains as group I agrees with other findings on strains in this region of Colombia.
INCIDENCE AND POPULATION FLUCTUATION OF SPITTLEBUGS ON THREE PERENNIAL GRASSES: ON-FARM ASSESSMENTS

Significant population outbreaks of spittlebugs (Hemiptera: Cercopidae) have been observed in perennial grasses (Poaceae) established in farms in South of Brazil. This situation is worrying local producers in relation to the continuous supply of forage due to the significant damage caused by this pest species complex. Thus, this study aimed to evaluated the incidence and populational fluctuation of spittlebugs (Hemiptera: Cercopidae) in three perennial grasses [ Cynodon dactylon cv. Jiggs, C. dactylon cv. Tifton 85, and Axonopus catharinensis cv. SCS 315 Catarina Gigante (Poales: Poaceae)] in an experimental farm under semi-intensive milk production system. For this purpose, weekly counts of the foam produced by the spittlebugs nymphs were carried out in 10 points of 0.25 m 2 (0.5 x 0.5 m) each, totalizing 35 assessments from the beginning of September 2015 to the end of April 2016. The incidence of spittlebugs was significantly different among the three perennial grasses. Lower incidence of spittlebugs was observed on A. catharinensis cv. SCS 315 Catarina Gigante (4.91 nymphs foam m -2 week -1 in average), which is a natural species from South Brazil, followed by C. dactylon cv. Jiggs (6.51 nymphs foam m -2 week -1 in average) and by C. dactylon cv. Tifton 85 (7.58 nymphs foam m -2 week -1 in average). Moreover, three characteristic population peaks of spittlebugs was observed: the first in the end of September, the second in the middle of December, and the third in February early. However, the number of nymphs foam of spittlebugs was not significant correlated with the climatic parameters (precipitation, average temperature, and relative humidity) of periods (week) prior to the weekly sampling times. In light of these findings, A. catharinensis cv. SCS 315 Catarina Gigante constitutes an interesting option for establishing new pasture areas.
Unsupervised training of acoustic models for large vocabulary continuous speech recognition

For large vocabulary continuous speech recognition systems, the amount of acoustic training data is of crucial importance. In the past, large amounts of speech were thus recorded from various sources and had to be transcribed manually. It is thus desirable to train a recognizer with as little manually transcribed acoustic data as possible. Since untranscribed speech is available in various forms nowadays, the unsupervised training of a speech recognizer on recognized transcriptions is studied in this paper. A low-cost recognizer trained with between one and six h of manually transcribed speech is used to recognize 72 h of untranscribed acoustic data. These transcriptions are then used in combination with a confidence measure to train an improved recognizer. The effect of the confidence measure which is used to detect possible recognition errors is studied systematically. Finally, the unsupervised training is applied iteratively. Starting with only one h of transcribed acoustic data, a recognition system is trained fully automatically. With this iterative training procedure, the word error rates are reduced from 71.3% to 38.3% on the Broadcast News'96 evaluation test set and from 65.6% to 29.3% on the Broadcast News'98 evaluation test set. In comparison with an optimized system trained with the manually generated transcriptions of the complete 72 h training corpus, the word error rates increase by 14.3% relative and 18.6% relative, respectively.
Sense Meets Nonsense - Sense Meets Nonsense - a dual-layer Danish speech corpus for perception studies

In this paper, we present the newly established Danish speech corpus PiTu. The corpus consists of recordings of 28 native Danish talkers (14 female and 14 male) each reproducing (i) a series of nonsense syllables, and (ii) a set of authentic natural language sentences. The speech corpus is tailored for investigating the relationship between early stages of the speech perceptual process and later stages. We present our considerations involved in preparing the experimental set-up, producing the anechoic recordings, compiling the data, and exploring the materials in linguistic research. We report on a small pilot experiment demonstrating how PiTu and similar speech corpora can be used in studies of prosody as a function of semantic content. The experiment addresses the issue of whether the governing principles of Danish prosody assignment is mainly talker-specific or mainly content-typical (under the specific experimental conditions). The corpus is available in its entirety for download at http://amtoolbox.sourceforge. net/pitu/.
Reproducibility of Functional Connectivity and Graph Measures Based on the Phase Lag Index (PLI) and Weighted Phase Lag Index (wPLI) Derived from High Resolution EEG

Functional connectivity (FC) and graph measures provide powerful means to analyze complex networks. The current study determines the inter-subject-variability using the coefficient of variation (CoV) and long-term test-retest-reliability (TRT) using the intra-class correlation coefficient (ICC) in 44 healthy subjects with 35 having a follow-up at years 1 and 2. FC was estimated from 256-channel-EEG by the phase-lag-index (PLI) and weighted PLI (wPLI) during an eyes-closed resting state condition. PLI quantifies the asymmetry of the distribution of instantaneous phase differences of two time-series and signifies, whether a consistent non-zero phase lag exists. WPLI extends the PLI by additionally accounting for the magnitude of the phase difference. Signal-space global and regional PLI/wPLI and weighted first-order graph measures, i.e. normalized clustering coefficient (gamma), normalized average path length (lambda), and the small-world-index (SWI) were calculated for theta-, alpha1-, alpha2- and beta-frequency bands. Inter-subject variability of global PLI was low to moderate over frequency bands (0.12<CoV<0.28), higher for wPLI (0.25<CoV<0.55) and very low for gamma, lambda and SWI (CoV<0.048). TRT was good to excellent for global PLI/wPLI (0.68<ICC<0.80), regional PLI/wPLI (0.58<ICC<0.77), and fair to good for graph measures (0.32<ICC<0.73) except wPLI-based lambda in alpha1 (ICC = 0.12). Inter-electrode distance correlated very weakly with inter-electrode PLI (−0.06<rho<0) and weakly with inter-electrode wPLI (−0.22<rho<−0.18). Global PLI/wPLI and topographic connectivity patterns differed between frequency bands, and all individual networks showed a small-world-configuration. PLI/wPLI based network characterization derived from high-resolution EEG has apparently good reliability, which is one important requirement for longitudinal studies exploring the effects of chronic brain diseases over several years.
Hybrid ISMA/FDMA protocol for wireless packet transmission

The paper proposes a novel multiple access scheme, which is a combination of inhibit sense multiple access (ISMA) and frequency division multiple access (FDMA). Two types of the proposed protocol are considered. They are based on FDD and TDD modes. The performance of each hybrid protocol is evaluated in terms of throughput; the comparison of the proposed schemes with the pure ISMA scheme is discussed. Two examples are constructed to show the main property of the ISMA/FDMA scheme.
Bridging the Gap between Software Variability and System Variant Management: Experiences from an Industrial Machinery Product Line

Companies that develop complex systems often do so in the form of product lines, where each product variant can be configured to a certain degree to fit a customer's specific requirements. Features cannot be combined arbitrarily in a product line. The knowledge which features require or exclude each other is represented in form of variability models. Unfortunately, in practice, such variability models do not exist or they are oriented towards the needs and viewpoints of specific organizational units, e.g. Sales, manufacturing, hardware engineering, or software development. In this paper we present our experiences in building a variability model for the highly configurable software part of a complex mechatronic system produced by one of our industrial partner companies. The company already had support and processes for product variant management in place for sales and hardware manufacturing. However, the corresponding variability model was at the level of the overall system and excluded the variability of the software part. The paper discusses the resulting problems and challenges and describes the approach we selected to bridge the gap that existed between product variants and software configurations. The goal and driving motivation for our work was the improvement of the software development process and specifically the testing of software variants. The paper also shows how software configuration and testing activities can benefit from an appropriate variability model.
Book Review: Handbook of European Social Policy and The Routledge International Handbook to Welfare State Systems

Book reviews of: - Handbook of European social policy / edited by Patricia Kennett and Noemi Lendvai-Bainton (Cheltenham : Edward Elgar, 2017), 458 pages, £160 (hardback), ISBN: 9781783476459 - The Routledge international handbook to welfare state systems / edited by Christian Aspalter (London : Routledge, 2017), 498 pages, £175 (hardback), ISBN: 9781472449306
Software Deployment Extending Configuration Management Support into the Field

Traditionally, configuration management has only addressed the needs of the software development process. Once a software system leaves the development environment and enters the field, however, there still is a signifi- cant role for configuration management. Activities such as release, installation, activation, update, adaptation, deactivation, and de-release constitute the "deployment lifecycle"; these activities need careful coordination and planning in their own right. This article discusses the dimensions of software deployment, argues why current solutions are not sufficient, and presents two research systems that specifically address software deployment.
UM-Corpus: A Large English-Chinese Parallel Corpus for Statistical Machine Translation

Parallel corpus is a valuable resource for cross-language information retrieval and data-driven natural language processing systems, especially for Statistical Machine Translation (SMT). However, most existing parallel corpora to Chinese are subject to in-house use, while others are domain specific and limited in size. To a certain degree, this limits the SMT research. This paper describes the acquisition of a large scale and high quality parallel corpora for English and Chinese. The corpora constructed in this paper contain about 15 million English-Chinese (E-C) parallel sentences, and more than 2 million training data and 5,000 testing sentences are made publicly available. Different from previous work, the corpus is designed to embrace eight different domains. Some of them are further categorized into different topics. The corpus will be released to the research community, which is available at the NLP2CT website.
The outcome and prognostic factors of 248 elderly patients with acute myeloid leukemia treated with standard-dose or low-intensity induction therapy

AbstractThe prognosis of elderly patients with acute myeloid leukemia (AML) is poor, and the recommendation of standard-dose or low-intensity induction regimen for these patients remains controversial. We retrospectively analyzed treatment outcome and prognostic factors of elderly AML patients who had received either standard-dose or low-intensity induction regimens.Two hundred forty-eight elderly AML patients with good Eastern Cooperative Oncology Group performance status (ECOG PS ⩽ 2) received one of three regimens for induction in this study: standard-dose cytarabine plus idarubicin (IA; n = 144) or daunorubicin (DA; n = 42); low-intensity cytarabine, aclarubicin, and granulocyte colony-stimulating factor (G-CSF) (CAG; n = 62). After first induction treatment cycle, the overall complete remission (CR) rate was 42.7%. Patients in IA group had a higher CR rate than in DA or CAG group (49.3%, 35.7%, and 32.3%, respectively; P = 0.046). The 1-year, 3-year, and 5-year overall survival (OS) rates were 42.2%, 18.9%, and 13.5% for these 248 patients, with median survival of 9.2 months. Long-term survival of IA group was better than DA or CAG group. The 1-year, 3-year, and 5-year OS rates of IA group were 45.9%, 23.5%, and 19.4%, respectively, as compared to 39.8%, 8.3%, and estimated 2.4% in DA group, and 34.9%, 15.9%, and 6.3% in CAG group, respectively. Early induction mortality and 2-year relapse rates showed no difference among 3 groups. Univariate analysis and multivariate analysis identified lactic dehydrogenase (LDH) more than two times of upper normal limit at diagnosis and nonremission after first induction cycle as adverse prognostic factors for OS. A simple and valid scoring model was constructed for risk stratification and prediction of long-term survival of elderly AML patients.Standard-dose IA regimen could improve the prognosis of elderly AML patients with good performance status compared with standard-dose DA or low-intensity CAG regimen. All prognostic factors and risk assessment should be considered to ensure that each patient receives the suitable individualized treatment.
Modeling of Junction Temperature and Current Flow in High Power InGaN/GaN Light Emission Diodes Using Finite Element Methods

InGaN/GaN LEDs offer important lighting devices for human livings. These devices have high efficiency and lifetimes at low injection power but so far show degradation under high injection conditions. Current spreading and heat dissipation are key reasons for degradation under high power operation. In this paper, we have developed a three-dimensional (3-D) finite element method (FEM) to examine the heat generation and dissipation and a two-dimensional (2D) Finite element Poisson and drift-diffusion solver for the analysis of current spreading. As we know, the junction temperature plays an important role to the performance of the LED, and it will influence the optical performance. Therefore, the discussion of different surface current density and sapphire width will be considered in this paper. We examine how current flow can be altered by careful design of the LEDs. Results for a conventional LED and an LED with ion-implantation to improve current flow are presented. Our simulations show that improved device design based on modifying current flow paths can improve the device operation.
Evasion of Early Antiviral Responses by Herpes Simplex Viruses

Besides overcoming physical constraints, such as extreme temperatures, reduced humidity, elevated pressure, and natural predators, human pathogens further need to overcome an arsenal of antimicrobial components evolved by the host to limit infection, replication and optimally, reinfection. Herpes simplex virus-1 (HSV-1) and herpes simplex virus-2 (HSV-2) infect humans at a high frequency and persist within the host for life by establishing latency in neurons. To gain access to these cells, herpes simplex viruses (HSVs) must replicate and block immediate host antiviral responses elicited by epithelial cells and innate immune components early after infection. During these processes, infected and noninfected neighboring cells, as well as tissue-resident and patrolling immune cells, will sense viral components and cell-associated danger signals and secrete soluble mediators. While type-I interferons aim at limiting virus spread, cytokines and chemokines will modulate resident and incoming immune cells. In this paper, we discuss recent findings relative to the early steps taking place during HSV infection and replication. Further, we discuss how HSVs evade detection by host cells and the molecular mechanisms evolved by these viruses to circumvent early antiviral mechanisms, ultimately leading to neuron infection and the establishment of latency.
Graphic simulation for camera calibration in visual-servoing applications

Hyperredundant robots produce changes of configuration using a continuous backbone made of sections which bend. The lack of no discrete joints is a serious and difficult issue in the determination of the robot's shape. Next development of such application is the vision based control of the robot, kinematics and dynamics. Camera calibration is the essential procedure for all such applications: positioning and orienting the cameras in order to support the accuracy of the image features extraction. The calibration for a pan/tilt/zoom camera orientation is achieved by means of an engineered environment and a simulation graphic module. The paper presents experimental details showing the effectiveness of the technique used with the hyperredundant manipulator.
Determining the fittest frontal view face AdaBoost classifier for adoption in personage detector

A big challenge in many face detection applications is how well faces can be reliably detected. An increasing number of algorithms have been published and many such face detectors have been made publicly available in the form of open source applications, such as the OpenCV classifiers. In this work, we attempt to compare four frontal face OpenCV classifiers and determine the most fit for adoption in personage detector. We focus on frontal view following the expert's rule of thumb when looking for any person of interest in an image. We chose AdaBoost classifiers because AdaBoost algorithm often results in improved performance. We measured the detectors' performance on the accuracy in terms of recall, precision and harmonic mean. We performed testing over four heterogeneous datasets to obtain a reasonably accurate estimation of the performance of the classifiers that will help us in identifying the most suitable classifier meeting our needs.
Detecting copyright infringement on YouTube videos using YouTube metadata

YouTube is one of the largest video sharing website on the Internet. Several music and record companies, artists and bands have official channels on YouTube (part of the music ecosystem of YouTube) to promote and monetize their music videos. YouTube consists of the huge amount of copyright violated content including music videos (the focus of the work presented in this paper) despite the fact that they have defined several policies and implemented measures to combat copyright violations of content. We present a method to automatically detect copyright violated videos by mining video as well as older meta-data. We propose a multi-step approach consisting of computing textual similarity between query video title and video search results, detecting useful linguistic markers (based on a pre-defined lexicon) in title, mining user profile data, analyzing the popularity of the Uploader and the video to predict the category (original or copyright-violated) of the video. Our proposed solution approach is based on a rule-based classification framework. We validate our hypothesis by conducting a series of experiments on evaluation dataset acquired from YouTube. The empirical results indicate that the proposed approach is effective