Miracle-dz/UniFAR-FTUs huggingface dataset:
M-DWARF RAPID ROTATORS AND THE DETECTION OF RELATIVELY YOUNG MULTIPLE M-STAR SYSTEMS

We have searched the Kepler light curves of ∼3900 M-star targets for evidence of periodicities that indicate, by means of the effects of starspots, rapid stellar rotation. Several analysis techniques, including Fourier transforms, inspection of folded light curves, “sonograms,” and phase tracking of individual modulation cycles, were applied in order to distinguish the periodicities due to rapid rotation from those due to stellar pulsations, eclipsing binaries, or transiting planets. We find 178 Kepler M-star targets with rotation periods, Prot, of <2 days, and 110 with Prot < 1 day. Some 30 of the 178 systems exhibit two or more independent short periods within the same Kepler photometric aperture, while several have 3 or more short periods. Adaptive optics imaging and modeling of the Kepler pixel response function for a subset of our sample support the conclusion that the targets with multiple periods are highly likely to be relatively young physical binary, triple, and even quadruple M star systems. We explore in detail the one object with four incommensurate periods all less than 1.2 days, and show that two of the periods arise from one of a close pair of stars, while the other two arise from the second star, which itself is probably a visual binary. If most of these M-star systems with multiple periods turn out to be bound M stars, this could prove a valuable way discovering young hierarchical M-star systems; the same approach may also be applicable to G and K stars. The ∼5% occurrence rate of rapid rotation among the ∼3900 M star targets is consistent with spin evolution models that include an initial contraction phase followed by magnetic braking, wherein a typical M star can spend several hundred Myr before spinning down to periods longer than 2 days.
Effects of post activation potentiation on eccentric loading: Is it possible to do more repetitions after supra-maximal loading?

The aim of this study is to investigate the effects of Post Activation Potentiation (PAP) on muscular endurance performance. 42 physically active male participants (PAP Group n=32, Control Group n=10) who have at least 1 year of resistance training experience and exercise min. times/week, participated in this study. First testing session were the same for both Control and PAP group. On the first session, 1 Repetition Maximum (1RM) of subjects was found. 65% of the 1 RM was calculated to find the weight that was going to be used for the muscular endurance test. Subjects completed maximal number of repetitions with 65 % of their 1 RM. On the second test session which was done 48 hours after the first session, PAP group did eccentric loading with Bench Press with their 120 % of 1 RM than rest 8 minutes to elicit the effects of PAP. After the resting period, muscular endurance test with 65% of 1 RM and time under tension were recorded. No statistical difference was found between the number of repetitions that were done in the first and the second test session for control group (p>0.05). Whereas significant increase was found for the PAP group (p 0.05). As a result of this study, supra-maximal eccentric loading was found to be an effective method to elicit the effects of PAP on muscular endurance. Therefore, PAP protocols in resistance training sessions might be considered to be used for athletes who want to improve their muscular endurance performance.
REGULARIZABLE CYCLES ASSOCIATED WITH A SELBERG TYPE INTEGRAL UNDER SOME RESONANCE CONDITION

Twisted homology groups attached to a Selberg type integral are studied under some resonance condition. We study the kernel of the map from the homology of compact cycles to the homology of locally finite cycles. As a result, the dimension of the image, the space of the regularizable cycles, is expressed as a special value of the generalized hypergeometric series 3F2.
dOSEK: A Dependable RTOS for Automotive Applications

Recent automotive systems exhibit an increased susceptibility against transient hardware faults. As a consequence, dependability measures are mandatory to provide appropriate fault detection or masking properties fulfilling the required safety standards. On the other and, production costs are still a crucial factor in this domain, which leads to hardware consolidation and therefore mixed-criticality systems. An existing dependability approach, supporting such systems, combines triple modular redundancy with encoded operations, but still leaves the operating system as single point of failure. We intend to close this gap by extending the encoded operations throughout the kernel execution, and additionally integrate the analyzed system behavior into the code.
Plagiarism Detection Considering Frequent Senses Using Graph Based Research Document Clustering

A new, graph based research document clustering technique (GRD-Clust) is introduced based on frequent senses rather than frequent keywords as per the traditional document clustering techniques.GRDClust presents text documents as hierarchal document-graphs and utilizes an Apriori paradigm to find the frequent sub graphs, which reflect frequent senses based on support and confidence. We highlight the different types of plagiarism and address the issues of plagiarism of text, plagiarism of ideas, mosaic plagiarism, self-plagiarism, and duplicate publication. Different documents eschewed of plagiarism by identifying the alleged terms are considered. An act of plagiarism can have several repercussions when an article does not score high on clarity or lacks conciseness, the deficiency is typically unintentional.
Investigating the use of readability metrics to detect differences in written productions of learners : a corpus-based study

This paper deals with the use of readability metrics as indices of learmers' linguistic features in a written corpus of Spanish learners of English L2. Seventeen measures of readability are presented and computed for 200 samples of written argumentative essays extracted from the corpus NOCE (Diaz-Negrillo, 2007). Support Vector Machines (SVM) are used in order to detect which are the metrics that perform better at detecting differences in learners’ productions belonging to students enrolled in the first or in the second year of an English major. Metrics based on sentence length, number of sentences, and number of polysyllabic words are reported to be the most accurate ones for the classification of learners' linguistic features.
Improving performances of a distributed NFSP implementation ?

Our NFS implementation, NFSP aims at providing some transparent way to aggregate unused disk space by means of dividing a usually centralized NFS server into smaller entities: a meta-server and I/O servers. This paper illustrates what are the issues related to increasing the performances of such an implementation by using two different approaches: distributing the load across several servers or implementing the server in a more efficient and intrusive way. Performances of the different versions are given and compared to the first implementation.
Semantic Web in Comparison to Web 2.0

The Semantic Web is not a separate Web but an extension of the current one, in which information is given well-defined meaning, better enabling computers and people to work in cooperation. It is also referred to as Web 3.0 and is an upcoming technology. The Semantic Web is a web of data. The Semantic Web is about two things: it is about common formats for integration and combination of data drawn from diverse sources and about how the data relates to real world objects. Semantic Web can be considered a part of artificial intelligence as it puts into use Model theory, Web effect. Oracle, IBM, Adobe, Software AG, Mozilla and Yahoo! are some of the large corporations that have picked up this technology. This paper presents a comparison of Semantic Web and Web2.0 as well also discusses on the features and capabilities of Semantic Web.
Prior environmental contamination increases the risk of acquisition of vancomycin-resistant enterococci.

BACKGROUND Patients colonized with vancomycin-resistant enterococci (VRE) frequently contaminate their environment, but the environmental role of VRE transmission remains controversial. METHODS During a 14-month study in 2 intensive care units, weekly environmental and twice-weekly patient surveillance cultures were obtained. VRE acquisition was defined as a positive culture result >48 h after admission. To determine risk factors for VRE acquisition, Cox proportional hazards models using time-dependent covariates for colonization pressure and antibiotic exposure were examined. RESULTS Of 1330 intensive care unit admissions, 638 patients were at risk for acquisition, and 50 patients (8%) acquired VRE. Factors associated with VRE acquisition included average colonization pressure (hazard ratio [HR], 1.4 per 10% increase; 95% confidence interval [CI], 1.2-1.8), mean number of antibiotics (HR, 1.7 per additional antibiotic; 95% CI, 1.2-2.5), leukemia (HR, 3.1; 95% CI, 1.2-7.8), a VRE-colonized prior room occupant (HR, 3.1; 95% CI, 1.6-5.8), any VRE-colonized room occupants within the previous 2 weeks (HR, 2.5; 95% CI, 1.3-4.8), and previous positive room culture results (HR, 3.4; 95% CI, 1.2-9.6). In separate multivariable analyses, a VRE-colonized prior room occupant (HR, 3.8; 95% CI, 2.0-7.4), any VRE-colonized room occupants within the previous 2 weeks (HR, 2.7; 95% CI, 1.4-5.3), and previous positive room culture results (HR, 4.4; 95% CI, 1.5-12.8) remained independent predictors of VRE acquisition, adjusted for colonization pressure and antibiotic exposure. CONCLUSIONS We found that prior room contamination, whether measured via environmental cultures or prior room occupancy by VRE-colonized patients, was highly predictive of VRE acquisition. Increased attention to environmental disinfection is warranted.
Dynamic hand gesture recognition system using moment invariants

We have developed a dynamic hand gesture recognition system that can simplify the way humans interact with computers and many other non-critical consumer electronic equipment. The proposed system is based on the well-known “Wave Controller” technology developed at the University of Wollongong [1–3] and will revolutionize video gaming and consumer electronics control interfaces. Currently, computer interfacing mainly involves keyboard, mouse, joystick or gaming wheels and occasionally voice recognition for user input. These modes of interaction have restrained the artistic ability of many users, as they are required to respond to the computer through pressing buttons or moving other apparatus. Voice recognition is seen as unreliable and impractical in areas where more than one user is present. All these drawbacks can be tackled by using a reliable hand gesture recognition system that facilitates interaction between users and computers and other consumer electronic equipment in real time. This will further enhance the user experience as users no longer have any physical connection to the equipment being controlled. This system can also be extended to a sign language system for the benefit of the disabled including those with speech disabilities.
Learning Compliant Locomotion on a Quadruped Robot

Over the last decades, compliant locomotion and manipulation have become a very active field of research, due to the versatility that robots with such capabilities would offer in many applications. With very few exceptions, generally, robotic applications and experiments take place in controlled environments. One of the reasons of this limited use is that in real world scenarios, robots need to interact with an unknown environment. In order to have a safe interaction with the environment while successfully performing some meaningful task, robots need to be compliant, such as humans and animals are. In this paper, a framework for optimizing stereotypical trotting gait of a quadruped robot by the use of variable impedance control is proposed. The framework uses the Policy Improvements with Path Integrals algorithm (PI) to optimize a parametrized gait generator and the robot’s impedance during locomotion. As result, it achieves an energetically efficient and robust trotting gait for different speeds while respecting the joints and actuators limits. The resulting controllers have been tested in a physics based simulator.
An Improved Ambiguity Measure Feature Selection for Text Categorization

The high dimensionality of the text categorization raises big hurdles in applying many sophisticated learning algorithms to the text categorization. Feature selection, which reduces the number of features that represent documents, is an absolute requirement in text categorization. In this paper, we proposed a feature selection method, which improved the performance of the Ambiguity Measure feature selection. We compare the proposed method with four feature selections (Information Gain, Ambiguity Measure, Odd Ratios and Mutual Information) using two classification algorithms (Naïve Bayes and Support Vector Machines) on three datasets (20-newgroups, Reuters-21578 and WebKB). The experiments show that the proposed method is significantly better than AM and MI, and achieves comparable performance with IG and OR.
MapCG: Writing parallel program portable between CPU and GPU

Graphics Processing Units (GPU) have been playing an important role in the general purpose computing market recently. The common approach to program GPU today is to write GPU specific code with low level GPU APIs such as CUDA. Although this approach can achieve very good performance, it raises serious portability issues: programmers are required to write a specific version of code for each potential target architecture. It results in high development and maintenance cost.
Modeling the mashup space

We introduce a formal model for capturing the notion of mashup in its globality. The basic component in our model is the mashlet. A mashlet may query data sources, import other mashlets, use external Web services, and specify complex interaction patterns between its components. A mashlet state is modeled by a set of relations and its logic specified by datalog-style active rules. We are primarily concerned with changes in a mashlet state relations and rules. The interactions with users and other applications, as well as the consequent effects on the mashlets composition and behavior, are captured by streams of changes. The model facilitates dynamic mashlets composition, interaction and reuse, and captures the fundamental behavioral aspects of mashups.
Phrasal Transfer Model for Vietnamese-english Machine Translation

Morphological diierences between Viet-namese and English not only aaect to translation process in morphological level but also strongly change the structure of translated sentence. Actually, in bilingual dictionary many Vietnamese word entries do not have any equivalent English word and must be translated to English phrases. In this paper we present our analysis of Vietnamese morphology and describe a phrasal transfer model for Vietnamese to English Machine Translation. The phrasal transfer model is discussed as an approach to solving of lexical gap between two languages. The model, which based on conventional three-step transfer model, allows the system to map a word in source language to a phrase in target language , and control restructuring to generate target sentences.
Context-enhanced information fusion for tracking applications

Over the last decade, context has become a key source of information for tracking problems. Context inference allows refining sensor modeling and target dynamics as well as the creation of motion constraints according to the physical and operational conditions of the scenario. This work presents two example applications: indoor and inland waterway navigation where the context information is employed to reduce the uncertainty of the tracking and enhance the navigation solution. For indoor positioning a cascaded Extended Kalman Filter (EKF) and Particle Filter (PF) architecture is proposed. The system uses stance phase detection and the available floor map to construct the measurement models for the KF and motion constraints for the PF respectively. For navigating in inland waterways it is shown how to benefit from context information fusion by inferring the operating condition of the Global Navigation Satellite System (GNSS). In this scenario, context based criteria are derived for the selection of the best position estimation amongst several positioning solvers running in parallel. This work presents the basics for context fusion in tracking applications, illustrating the theory with two application examples. The preliminary results already demonstrate a performance improvement compared to state-of-the-art approaches.
INTEGRATED APPROACH FOR DEFECT DETECTION IN CERAMIC TILES

Quality control is an important issue in the ceramic tile industry. Price of ceramic tiles also depends on purity of texture, accuracy of color, shape etc. Considering this criteria, an integrated defect detection and classification technique has been proposed which plays an important role in ceramic tiles industries to detect the defects and to control the quality of ceramic tiles.GLCM extracts the texture features and these features together with color features are used for analysis in classifiers such as SVM, KNN and Bayesian. Experimental results illustrated that every classifier gives highest accuracy with HSV.
Energy management system for control of hybrid AC/DC microgrids

Hybrid AC/DC microgrid is getting popularized due to the higher penetration of DC-compatible loads, energy sources and storages. To maintain system power balance in both AC and DC sub-grids, the bidirectional interlinking converter (BIC) is used. Distributed control of hybrid AC/DC microgrid is normally implemented to enhance system reliability. DC bus voltage and AC frequency are used for indication of system active power balance. BIC power flow is determined based on local information to equalize the normalized deviations of DC voltage and AC frequency. However, deviations of AC frequency and DC bus voltage degrade system power quality, which deteriorate the lifetime operation of system units. Multi-level energy management system (EMS) is thus proposed in this paper to enhance control accuracy while retaining system reliability. Distributed control of hybrid AC/DC microgrid is scheduled as the primary control. Restorations of AC frequency and DC bus voltage are implemented in secondary control. In tertiary control, the power references of system units are generated based on the comparison of marginal costs. Power sharing compensation is applied to minimize power tracking errors. MATLAB/Simulink model for hybrid AC/DC microgrid is developed for the verification of the proposed multi-level EMS.
The New Keynesian Phillips Curve with Non Zero Steady State Inflation and Entry of Firms

Over the last years, a few authors have assumed a non zero steady state inflation in the derivationof the new Keynesian Phillips curve (NKPC) based on Calvo price setting with staggered prices. This hasled to the theoretical result that the slope of the NKPC decreases with trend inflation, in contrast withstylized facts showing its decline since the 1980s.In this paper, we develop an enlarged NKPC allowing for endogenous entry of firms withpreviously assumed non zero steady state inflation. Pricing complementarities are introduced on thedemand side. This NKPC exhibits the following properties: 1) its slope, though decreasing with the trend ofinflation, also decreases with the trend of the number of varieties; therefore, this NKPC reconciles theorywith stylized facts in an environment of low inflation and globalization; 2) in the long run, real averagemarginal cost and real activity not only decrease with inflation, but also increase with the number ofvarieties; 3) disinflation and deregulation in the product market (a lowering of the entry costs for firms)have complementary effects in the long run: disinflation implies more growth for lower levels of productmarket regulation.
Effect and Mechanism of Survivin on Hypoxia-Induced Multidrug Resistance of Human Laryngeal Carcinoma Cells

This study aimed at clarifying the mechanism and role of survivin in hypoxia-induced multidrug resistance (MDR) of laryngeal carcinoma cells. Human laryngeal cancer cells were incubated under hypoxia or normoxia. The expression of survivin was silenced by performing RNA interference. Additionally, by Western blot and real-time quantitative RT-PCR, survivin expression was detected. The sensitivity of human laryngeal carcinoma cells to multiple drugs was measured by CCK-8 assay. Meanwhile, the apoptosis of cells induced by cisplatin or paclitaxel was assessed by Annexin-V/propidium iodide staining analysis. Under hypoxic conditions, the upregulation of survivin was abolished by RNA interference. Then, CCK-8 analysis demonstrated that the sensitivity to multiple agents of laryngeal carcinoma cells could be increased by inhibiting survivin expression (P < 0.05). Moreover, Annexin-V/propidium iodide staining analysis revealed that decreased expression of survivin could evidently increase the apoptosis rate of laryngeal carcinoma cells that were induced by cisplatin or paclitaxel evidently (P < 0.05). Our data suggests that hypoxia-elicited survivin may exert a pivotal role in regulating hypoxia-induced MDR of laryngeal cancer cells by preventing the apoptosis of cells induced by chemotherapeutic drug. Thus, blocking survivin expression in human laryngeal carcinoma cells may provide an avenue for gene therapy.
Developing Distributed Representations of structured sequences by

1 Introduction In spite of the growing research on connectionist Natural Language Processing (NLP), there are still a number of challenges to be solved, for example, the development of proper linguistic representations. Natural language is a dynamic system with underlying hierarchical structure and sequential external appearance. Therefore, NLP systems need an adequate hierarchical system of linguistic representations. What we roughly distinguish as letters, words, sentences, etc., need to be encoded in a proper and systematic manner, permitting direct, " holistic " operations over the resultant abstract representations rather than over external sequential forms (Chalmers 1990; Blank 1992; Hammerton 1998). Those representations should be static, unique characterization of the original objects, which is necessary for reproducing them back into their sequential form. They should allow holistic transformations and associations to representations from other modalities – visual, effectual, etc. Natural language is not the only structured process, where static representations at different levels are necessary for modeling: consider composite actions, dynamic visual processes and so on. We find other examples also outside of cognitive modeling, such as modeling economic processes, physical phenomena, etc.
Patterns of sympathetic neuron activity associated with Mayer waves.

PREISS, GEORGE, AND CANIO POLOSA. Patterns of sympathetic neuron activity associated with Mayer xqaues. Am. J. Physiol. 226(3) : 724-730. 1974. -In Nembutal-anesthetized or decerebrate cats Mayer waves were evoked by bleeding and common carotid artery occlusion. The temporal patterns of sympathetic preganglionic neuron activity associated with the waves were essentially similar to those observed in the control conditions but were modulated at the Mayer wave repetition rate. This periodic modulation of the neuron firing patterns persisted when the systemic arterial pressure oscillation was abolished by means of a pressure-stabilizing apparatus or by means of the alpha-adrenergicblocking drug, phentolamine. These procedures also abolished the periodicity in baroreceptor afferent inflow. These observations suggest that the rhythmic modulation of sympathetic neuron activity, underlying Mayer waves, is the result of the activity of a central oscillator.