Miracle-dz/UniFAR-FTUs huggingface dataset:
Variable Selection for Support Vector Machines in High Dimensions

The support vector machine (SVM) is a powerful binary classification tool with high accuracy and great flexibility. It has achieved great success, but its performance can be seriously impaired if many redundant covariates are included. Some efforts have been devoted to studying variable selection for SVMs, but asymptotic properties, such as variable selection consistency, are largely unknown when the number of predictors diverges to infinity. In this work, we establish a unified theory for a general class of nonconvex penalized SVMs in the high-dimensional setting. We prove that there exists a local minimizer of the nonconvex penalized SVM objective function possessing the oracle property even when the number of predictors grows exponentially with the sample size. Furthermore, we give sufficient conditions under which the proposed algorithm identifies the oracle solution among potentially multiple local minimizers. Numerical examples provide supportive evidence.
In Vitro Evaluation of Dimensional Stability of Alginate Impressions after Disinfection by Spray and Immersion Methods

Background and aims The most common method for alginate impression disinfection is spraying it with disinfecting agents, but some studies have shown that these impressions can be immersed, too. The aim of this study was to evaluate the dimensional stability of alginate impressions following disinfecting by spray and immersion methods. Materials and methods Four common disinfecting agents (Sodium Hypochlorite, Micro 10, Glutaraldehyde and De-conex) were selected and the impressions (n=108) were divided into four groups (n=24) and eight subgroups (n=12) for disinfecting by any of the four above-mentioned agents by spray or immersion methods. The control group (n=12) was not disinfected. Then the impressions were poured by type III Dental Stone Plaster in a standard method. The results were ana-lyzed by descriptive methods (mean and standard deviation), t-test, two-way analysis of variance (ANOVA) and Duncan test, using SPSS 14.0 software for windows. Results The mean changes of length and height were significant between the various groups and disinfecting methods. Regarding the length, the greatest and the least amounts were related to Deconex and Micro 10 in the immersion method, respectively. Regarding height, the greatest and the least amounts were related to Glutaraldehyde and Deconex in the im-mersion method, respectively. Conclusion Disinfecting alginate impressions by Sodium Hypochlorite, Deconex and Glutaraldehyde by immersion method is not recommended and it is better to disinfect alginate impressions by spraying of Micro 10, Sodium Hypochlorite, Glutaraldehyde and immersion in Micro 10.
On Hopping Strategies for Autonomous Wireless Networks

The transmission capacity (TmC) of an ad hoc network measures the area spectral efficiency (in bits/sec×Hz×m2) of successful transmissions as a function of the required transmission rate in single-hop links τ, under the assumption that the average density of active links λat in the network is given [1]. In reality, however, the probability that a node wishing to transmit becomes active is conditioned on the availability of a receiving peer. Consequently, λat is not a given parameter but rather a function of topological parameters. In this paper, we employ stochastic-geometric tools to obtain an expression of λat as a function of the transmission range d and network density λ, and apply the result to evaluate the transmission capacity of autonomous interference-limited networks. We then use the TmC to study the impact of closest-neighbor, furthest-neighbor and random-neighbor hopping strategies on the performance of such networks. It is shown that amongst these alternatives, the closest-neighbor strategy always achieves the highest transmission capacity. Furthermore, it is found that the advantage of closest-neighbor hopping is more significant in networks with high densities, large transmission ranges and/or higher required rates, where interference is the dominant limiting factor. In noninterference-limited networks, however, the three strategies are equivalent.
Low Abdominal NIRS Values and Elevated Plasma Intestinal Fatty Acid-Binding Protein in a Premature Piglet Model of Necrotizing Enterocolitis

To identify early markers of necrotizing enterocolitis (NEC), we hypothesized that continuous abdominal near-infrared spectroscopy (A-NIRS) measurement of splanchnic tissue oxygen saturation and intermittent plasma intestinal fatty-acid binding protein (pI-FABP) measured every 6 hours can detect NEC prior to onset of clinical symptoms. Premature piglets received parenteral nutrition for 48-hours after delivery, followed by enteral feeds every three hours until death or euthanasia at 96-hours. Continuous A-NIRS, systemic oxygen saturation (SpO2), and heart rate were measured while monitoring for clinical signs of NEC. Blood samples obtained at 6-hour intervals were used to determine pI-FABP levels by ELISA. Piglets were classified as fulminant-NEC (f-NEC), non-fulminant-NEC (nf-NEC) and No-NEC according to severity of clinical and histologic features. Of 38 piglets, 37% (n=14) developed nf-NEC, 18% (n=7) developed f-NEC and 45% (n=17) had No-NEC. There were significant differences in baseline heart rate (p=0.008), SpO2 (p<0.001) and A-NIRS (p<0.001) among the three groups. A-NIRS values of NEC piglets remained lower throughout the study with mean for f-NEC of 69±3.8%, 71.9±4.04% for nf-NEC, and 78.4±1.8% for No-NEC piglets (p<0.001). A-NIRS <75% predicted NEC with 97% sensitivity and 97% specificity. NEC piglets demonstrated greater variability from baseline in A-NIRS than healthy piglets (10.1% vs. 6.3%; p=0.04). Mean pI-FABP levels were higher in animals that developed NEC compared to No-NEC piglets (0.66 vs. 0.09 ng/mL;p<0.001). In f-NEC piglets, pI-FABP increased precipitously after feeds (0.04 to 1.87 ng/mL;p<0.001). pI-FABP levels increased in parallel with disease progression and a value >0.25ng/mL identified animals with NEC (68% sensitivity and 90% specificity). NIRS is a real-time, non-invasive tool that can serve as a diagnostic modality for NEC. In premature piglets, low A-NIRS in the early neonatal period and increased variability during initial feeds are highly predictive of NEC, which is then confirmed by rising plasma I-FABP levels. These modalities may help identify neonates with NEC prior to clinical manifestations of disease.
A CMOS focal-plane array for heterodyne terahertz imaging

In this paper we present a focal-plane array (FPA) for heterodyne imaging at 0.65-THz in a low-cost 0.25-µm CMOS process technology. The 3×5 pixel array is fully integrated on chip and consists of differential patch antennas, NMOS square-law mixers, and 43-dB low-IF amplifiers. The NMOS square-law mixers are based on distributed resistive self-mixing and facilitate mixing well beyond the cutoff frequency of the technology. First 0.65-THz heterodyne imaging results are presented.
N281 Implicit Category Learning 1 Running Head: (N281) THE CASE FOR IMPLICIT CATEGORY LEARNING The Case for Implicit Category Learning

This paper evaluates the evidence regarding the claim that people can learn a novel category implicitly, i.e., by an implicit memory system that is qualitatively different from an explicit system. The evidence considered is based on the prototype-extraction task, in which participants are first exposed to a set of category exemplars under incidental learning instructions, and are then required to categorize novel test items. Knowlton and Squire (1993) first reported that memory-impaired patients performed normally on the prototype-extraction task while being impaired on a comparable recognition task. Several studies have replicated these results, but other articles have criticized the evidence for implicit category learning on both methodological and theoretical grounds. In this paper, we consider five of these criticisms – e.g., that the normal performance of the patients is due to intact working-memory mechanisms (e.g., Palmeri & Flannery, 1999), or to the lesser cognitive demands of prototype-extraction than recognition (e.g., Nosofsky & Zaki, 1998). For each of the five criticisms, we offer counterevidence that supports implicit category learning. N281 Implicit Category Learning 3
Nanodisk-Associated Amphotericin B Clears Leishmania major Cutaneous Infection in Susceptible BALB/c Mice

ABSTRACT Nanometer-scale, apolipoprotein-stabilized phospholipid bilayer disk complexes (nanodisks [ND]) harboring the toxic and poorly soluble antileishmanial agent amphotericin B (AMB) were examined for efficacy in treatment of Leishmania major-infected BALB/c mice (Mus musculus). L. major-infected mice were intraperitoneally (i.p.) treated with AMB-ND in 0-, 1-, and 5-mg/kg doses at 24 h, 48 h, and 4, 7, 14, and 21 days postinfection in two experiments. L. major-infected mice were i.p. treated with phosphate-buffered saline, 5 mg/kg AMB-ND, or 5 mg/kg lipid-associated amphotericin B (liposomal amphotericin B, AmBisome) at 24 h, 48 h, and 10, 20, 30, and 40 days postinfection in one experiment. Parasite numbers, footpad lesion size progression, and development of cytokine responses were assayed at days 7, 15, 30, 50, 140, and 250 or at days 14, 30, 50, 95, and 140 postinfection. Mice administered AMB-ND in 1- or 5-mg/kg doses were significantly protected from L. major, displaying decreases in lesion size and parasite burden, particularly at the 5-mg/kg dosage level. In contrast to the i.p. treated AmBisome group, BALB/c mice treated with i.p. AMB-ND completely cleared an L. major infection by 140 to 250 days postinfection, with no lesions remaining and no parasites isolated from infected animals. Restimulated mixed lymphocyte culture cytokine responses (interleukin-4 [IL-4], IL-12, IL-10, NO, and gamma interferon) were unchanged by AMB-ND administration compared to controls. The marked clearance of Leishmania parasites from a susceptible strain of mice without an appreciable change in the cytokine response suggests that AMB-ND represent a potentially useful formulation for treatment of intrahistiocytic organisms.
Entropy and climate. I - ERBE observations of the entropy production of the earth

SUMMARY This paper introduces an approximate method for estimating the global distributions of the entropy fluxes Howing through the upper boundary of the climate system, and provides an estimate of the entropy exchange between the earth and space and the entropy production of the planet. The entropy fluxes are those associated with the exchange of radiation between the earth and space and a specific method is described to derive these entropy fluxes from available measurements of the earth's radiation budget. The distribution of these entropy fluxes and the entropy production derived from these fluxes differ in significant ways from those reported previously. The major source of these differences arises from the incorrect estimate of entropy exchange associated with reflected solar radiation in these earlier studies. This problem is overcome by the application of a simple physical model for the entropy exchange. Radiative-transfer simulations of the entropy exchange demonstrate that this model reasonably approximates the entropy exchange associated with reflected solar radiation, and that the long-wave fluxes of cntropy arc closely approximated by the equivalent black-body entropy flux, Entropy fluxes calculated from the Earth Radiation Budget Experiment measurements show how the long-wave entropy flux densities dominate the total entropy fluxes at all latitudes compared with the entropy Hux densities associated with reHected sunlight, although the short-wave flux densities are important in the context of clear sky-cloudy sky net entropy flux differences. It appears from the analysis presented in this paper that the entropy production of the planet is both constant for the 36 months of data considered and very near its maximum possible value. The mean value of this production is 0.68 X I0"W K-' and the amplitude of the annual cycle is approximately 1 to 2% of this value, which is within the uncertainty of our estimate. Climatic fluctuations ol entropy production are shown to be less than about 2% of the total production and therefore cannot be detected using the method describcd in this paper. The production of global entropy is dominated entirely by radiative processes. It remains a considerable challenge to detect these climatic fluctuations above such a large background of entropy production.
International Journal of Innovative Research in Computer and Communication Engineering Efficient Multi-dimensional Fuzzy Search for Personal Information Management Systems

With the explosion in the amount of semi-structured data users access and store in personal information management systems, there is a critical need for powerful search tools to retrieve often very heterogeneous data in a simple and efficient way. Existing tools typically support some IR-style ranking on the textual part of the query, but only consider structure (e.g., file directory) and metadata (e.g., date, file type) as filtering conditions. We propose a novel multi-dimensional search approach that allows users to perform fuzzy searches for structure and metadata conditions in addition to keyword conditions. Our techniques individually score each dimension and integrate the three dimension scores into a meaningful unified score. We also design indexes and algorithms to efficiently identify the most relevant files that match multi-dimensional queries. We perform a thorough experimental evaluation of our approach and show that our relaxation and scoring framework for fuzzy query conditions in non content dimensions can significantly improve ranking accuracy. We also show that our query processing strategies perform and scale well, making our fuzzy search approach practical for every day usage.
AN ADAPTIVE FAILURE DETECTION APPROACH FOR REAL-TIME DISTRIBUTED CONTROL SYSTEMS OVER SHARED ETHERNET

Integration among sub-systems, easy interconnection amon g devices, reliability, and reduction of operational cost are some of the requirements demanded by modern control systems. Thus, the automation and control industry has used off-the-shelf components such as the Ethernet to re duce costs and increase interoperability. However, the non-determinism nature of such networks brings difficultie s for time-critical control applications, especially when faulttolerant mechanisms (such as failure detectors) are employ ed to guarantee continuous operation. Following this conte xt, and considering a distributed control system built over an E thernet network, this paper presents an implementation of an adaptive failure detector based on Artificial Neural Netw orks. By means of simulation it is shown that the presented approach performs well compared with conventional existin g solutions. Additionally, this paper gives evidences that e overhead caused for the use of such detectors does not interf ere with the performance of conventional control algorithm s, such as PID, in a dedicated network.
QDroid: Mobile Application Quality Analyzer for App Market Curators

Low quality mobile applications have damaged the user experience. However, in light of the number of applications, quality analysis is a daunting task. For that reason, QDroid is proposed, an automated quality analyzer that detects the presence of crashes, excessive resource usage, and compatibility problems, without source codes and human involvement. QDroid was applied to 67 applications for evaluation and discovered 78% more crashes and attained 23% higher Activity coverage than Monkey testing. For detecting excessive resource usage and compatibility problems, QDroid reduced the number of applications that required manual review by up to 96% and 69%, respectively.
Distributed, complete, multi-robot coverage of initially unknown environments using repartitioning

We consider the problem of coverage path planning by multiple robots in an environment where the location and geometry of obstacles are initially unknown to the robots. We propose a novel algorithm where the robots initially partition the environment using Voronoi partitioning. Each robot then uses an auction-based algorithm to reallocate inaccessible portions of its initial Voronoi cell to robots in neighboring Voronoi cells so that each robot is responsible for covering a set of contiguous connected regions. We have verified the performance of our algorithm on e-puck robots within the Webots simulator in different environments with different obstacle geometries and shown that it performs complete, non-overlapping coverage.
Testing distributional models for the Irish equity market

This study outlines distributional properties and tests the applicability of different models for the ISEQ index and its major constituents. A Stability under Additions procedure is applied to raw, filtered and rescaled returns. The filtering process uses GARCHd, 1) and GARCH-M(1, 1) specifications, removing the influence of temporal anomalies and non-synchronous trading effects. Rescaling involves the standardising of returns using the time varying models estimates of conditional variance. Results support the ordinary stable and mixtures of stables distributions. The lack of normality is affected by first and second moment dependence.
Multi-Engine Approach for Named Entity Recognition in Bengali

This paper reports about a multi-engine approach for the development of a NER system in Bengali by combining the classifiers such as Maximum Entropy (ME), Conditional Random Field (CRF) and Support Vector Machine (SVM) with the help of weighted voting approach. The training set consists of approximately 272K wordforms, out of which 150K wordforms have been manually annotated with the four major named entity (NE) tags such as Person, Location, Organization and Miscellaneous tags. An appropriate tag conversion routine has been defined in order to convert the 122K wordforms of the IJCNLP-08 NER shared task, into the desired forms. The classifiers make use of the different contextual information of the words along with the variety of features that are helpful in predicting the various NE classes. Lexical context patterns, which are generated from an unlabeled corpus of 3 million wordforms in a semi-automatic way, have been used as the features of the classifiers in order to improve their performance. In addition, we have developed a number of techniques to post-process the output of each of the classifiers in order to reduce the errors and to improve the performance. Finally, we have applied weighted voting approach to combine the systems. Results show the effectiveness of the proposed approach with the overall average recall, precision, and f-score values of 93.98%, 90.63%, and 92.28%, respectively, which shows an improvement of 14.92% in f-score over the best performing baseline SVM based system and an improvement of 18.36% in f-score over the least performing baseline ME based system. The proposed system also outperforms the other existing Bengali NER system.
Automatic Transcription of Melody, Bass Line, and Chords in Polyphonic Music

This article proposes a method for the automatic transcription of the melody, bass line, and chords in polyphonic pop music. The method uses a frame-wise pitch-salience estimator as a feature extraction front-end. For the melody and bass-line transcription, this is followed by acoustic modeling of note events and musicological modeling of note transitions. The acoustic models include a model for the target notes (i.e., melody or bass notes) and a background model. The musicological model involves key estimation and note bigrams that determine probabilities for transitions between target notes. A transcription of the melody or the bass line is obtained using Viterbi search via the target and the background note models. The performance of the melody and the bass-line transcription is evaluated using approximately 8.5 hours of realistic polyphonic music. The chord transcription maps the pitch salience estimates to a pitch-class representation and uses trained chord models and chord-transition probabilities to produce a transcription consisting of major and minor triads. For chords, the evaluation material consists of the first eight Beatles albums. The method is computationally efficient and allows causal implementation, so it can process streaming audio. Transcription of music refers to the analysis of an acoustic music signal for producing a parametric representation of the signal. The representation may be a music score with a meticulous arrangement for each instrument or an approximate description of melody and chords in the piece, for example. The latter type of transcription is commonly used in commercial songbooks of pop music and is usually sufficient for musicians or music hobbyists to play the piece. On the other hand, more detailed transcriptions are often employed in classical music to preserve the exact arrangement of the composer. � 2008 Massachusetts Institute of Technology. We propose a method for the automatic transcription of the melody, bass line, and chords in pop-music recordings. Conventionally, these tasks have been carried out by trained musicians who listen to a piece of music and write down notes or chords by hand, which is time-consuming and requires musical training. A machine transcriber enables several applications. First, it provides an easy way of obtaining a description of a music recording, allowing musicians to play it. Second, the produced transcriptions may be used in music analysis, music information retrieval (MIR) from large music databases, content-based audio processing, and interactive music systems, for example.
Speech acts meet tagging: NiceTag ontology

Current tag models do not fully take into account the rich and diverse nature of tags. Each model makes different partial assumptions as to the definition and attributes a tag should receive. In this paper we propose an ontology, NiceTag, whose primitives are "tag actions" modeled with RDF named graphs. This mechanism allows us to type, describe and thus ensure the traceability of each single act of tagging. Our named graphs contain at least a resource linked to a "sign", which can be any resource reachable on the Web (an ontology concept, an image, etc.). The resource, the sign and the link between them are the three components of the acts of tagging that we want to explicitly represent as social actions, akin to speech acts. The purpose of our model is threefold. First, to be able to describe acts of tagging in a very precise and general manner, consistent with the principles behind the architecture of the Web. To reconcile and bridge existing tag models (Newman ontology, Tagont, ES, SCOT, SIOC, CommonTag, MOAT, NAO). And finally, to propose a viable way to reify and represent the intention behind an act of tagging and leverage its semantics.