Miracle-dz/UniFAR-FTUs huggingface dataset:
Feature selection in high-dimensional EEG data by parallel multi-objective optimization

Feature selection is required in many applications that involve high dimensional model building or classification problems. Many bioinformatics applications belong to this type. Recently, some approaches for supervised and unsupervised feature selection as a multi-objective optimization problem have been proposed. As the performance of unsupervised classification is evaluated through the quality of the obtained groups or clusters in the data set to be classified, it is difficult to define a suitable objective function that drives the selection of the features. Thus, several evaluation measures, and thus multi-objective clustering characterization, could provide a suitable set of features for unsupervised classification. In this paper, we consider the parallel implementation of a multi-objective feature selection that makes it possible to apply it to complex classification problems such as those having many features to select, and specifically high-dimensional data sets with much more features than data items. In this paper, we propose master-worker implementations of two different parallel evolutionary models, the parallel computation of the cost functions for the individuals in the population, and the parallel execution of evolutionary multi-objective procedures on subpopulations. The experiments accomplished on different benchmarks, including some related with feature selection in classification of EEG (Electroencephalogram) signals for BCI (Brain Computer Interface) applications, show the benefits of parallel processing not only for decreasing the running time, but also for improving the solution quality.
Multi-modal pedestrian detection on the move

This paper presents an on-the-move pedestrian detection system that utilizes multiple sensor modalities to improve detection rates at deployable computational loads. The system was developed for a vehicle moving up to 40 kph that can detect moving pedestrians up to a distance of 50m, with support for both day and night operations. In the day, 3D pointclouds obtained from an 8-layer LIDAR sensor are processed to produce a labeling of the scene distinguishing ground, large structures, and potential pedestrians to produce reliable detections in the short range (up to 30m), while a stereo-based detection and classification system is used for ranges between 30-50m+. We describe the algorithms in detail and show that the combined system allows for reliable detection at faster frame-rates than when using each sensor or component individually. A second method for fusing two IR cameras with the LIDAR sensor is proposed for night operations, where LIDAR is used to produce multi-scale masks that define the search space for a HOG-based pedestrian classifier.
Digital Curves in 3D Space and a Linear-Time Length Estimation Algorithm

We consider simple digital curves in a 3D orthogonal grid as special polyhedrally bounded sets. These digital curves model digitized curves or arcs in three-dimensional Euclidean space. The length of such a simple digital curve is defined to be the length of the minimum-length polygonal curve fully contained and complete in the tube of this digital curve. So far, no algorithm was known for the calculation of such a shortest polygonal curve. The paper provides an iterative algorithmic solution for approximating the minimum-length polygon of a given simple digital space-curve. The theoretical foundations of this algorithm are presented as well as experimental results.
Cumulative Inequalities over the Life-Course: Life-long Learning and Social Mobility in Britain

Abstract This paper examines the possibility that life-long learning promotes intergenerational class mobility. The following two research questions are asked. Is it the case that further education provides individuals coming from less advantaged origins with a second chance to improve on their educational attainment? Is it the case that the returns to further qualifications, in terms of chances of upward class career mobility, are greater for children from less advantaged backgrounds than for children from more advantaged backgrounds? The analyses – that are based on the complete educational and class histories of men and women in a British birth cohort – mainly produce negative findings. Children coming from managerial and professional backgrounds seem to benefit most from further education. More specifically, further education appears to be an effective means of career advancement for individuals of managerial and professional origins who start out in their working lives in relatively low-level class positions. Via further education they can increase or update their qualifications, and in turn enhance their chances of being counter-mobile back to their class of origin. Overall, based on the findings of this paper, we can conclude that qualifications attained through life-long learning primarily serve to maintain, rather than to narrow, inequalities attached to social origins in Britain.
Molecular Approach to the Identification of Fish in the South China Sea

Background DNA barcoding is one means of establishing a rapid, accurate, and cost-effective system for the identification of species. It involves the use of short, standard gene targets to create sequence profiles of known species against sequences of unknowns that can be matched and subsequently identified. The Fish Barcode of Life (FISH-BOL) campaign has the primary goal of gathering DNA barcode records for all the world's fish species. As a contribution to FISH-BOL, we examined the degree to which DNA barcoding can discriminate marine fishes from the South China Sea. Methodology/Principal Findings DNA barcodes of cytochrome oxidase subunit I (COI) were characterized using 1336 specimens that belong to 242 species fishes from the South China Sea. All specimen provenance data (including digital specimen images and geospatial coordinates of collection localities) and collateral sequence information were assembled using Barcode of Life Data System (BOLD; www.barcodinglife.org). Small intraspecific and large interspecific differences create distinct genetic boundaries among most species. In addition, the efficiency of two mitochondrial genes, 16S rRNA (16S) and cytochrome b (cytb), and one nuclear ribosomal gene, 18S rRNA (18S), was also evaluated for a few select groups of species. Conclusions/Significance The present study provides evidence for the effectiveness of DNA barcoding as a tool for monitoring marine biodiversity. Open access data of fishes from the South China Sea can benefit relative applications in ecology and taxonomy.
Features in Identification Approaches for MicroRNA Precursors Based on Machine Learning

MicroRNAs (miRNAs) are a group of non-coding small RNA of ~ 22 nucleotides in length. They play important roles in gene regulation in animals and plants. The machine learning approach has become an important way to discover miRNAs, which is complement to experimental approaches. Feature selection is the key step of machine learning approaches to discover miRNA precursors. The performance and generalization ability of classifier is affected by the feature set. Features of miRNA precursors used in machine learning approaches were summarized in this review. According to the properties of features to distinguish the miRNA precursors and the non-miRNA precursors, features were categorized into three classes: sequence features, structure features, structure sequence features.
Locally optimum detection for spectrum sensing in cognitive radio

Spectrum sensing is a key feature in cognitive radio networks. We propose a locally optimum (LO) detector, which is known to be optimum at low SNR. This is desirable in cognitive radio since the primary user's signal may exhibit a very low power at the cognitive user's transmitter. We focus here on linear modulation in the presence of an unknown phase shift and additive white Gaussian noise. In the case of BPSK modulation, the sufficient statistic of the LO detector is shown to be the sum of the absolute second-order moment (i.e., energy) and second-order moment (pseudo-energy) estimates. For higher size constellation, it is proven that the energy detector is locally optimum. The paper also addresses the issue of noise power uncertainty, to which the energy detector is very sensitive. Although the proposed LO detector is shown to be less sensitive than the energy detector, its performance does deteriorate at high noise power mismatch values. To overcome this problem, we also propose a detector whose probability of false alarm is independent of the noise power. Simulation results show that the proposed detectors in the case of BPSK significantly outperform the energy detector. Further, the complexity of the proposed detectors is only slightly higher than that of the energy detector.
MAC-RANSAC: a robust algorithm for the recognition of multiple objects

This paper addresses the problem of recognizing multiple rigid objects that are common to two images. We propose a generic algorithm that allows to simultaneously decide if one or several objects are common to the two images and to estimate the corresponding geometric transformations. The considered transformations include similarities, homographies and epipolar geometry. We first propose a generalization of an "a contrario" formulation of the RANSAC algorithm proposed in [Moisan and Stival 04]. We then introduce an algorithm for the detection of multiple transformations between images and show its efficiency on various experiments.
Assessing mobility support in mesh networks

We address the joint problem of traffic routing and mobility support in wireless mesh networks that are built by many fixed nodes and few mobile nodes. We focus on a vehicular setting, where buses or streetcars connect to different fixed mesh nodes as they move in a urban environment. First, through simulation we identify the best candidate for routing traffic in such a scenario and we find that our improved version of the BATMAN protocol, named smart window BATMAN, outperforms other reactive and proactive approaches. Then, we develop a testbed which includes both roadside mesh nodes and vehicular mesh nodes. There, we implement the selected routing solution, along with a handover scheme that allows vehicles to connect to the different mesh nodes in a seamless manner. Our testbed and performance assessment show that mobility can be efficiently supported in mesh networks, and that our modified version of the BATMAN protocol is a good candidate for sustaining the handover of UDP streams in a seamless manner.
Implementation of the KNGR Class Library Based on the GPM and Semantic Networks for Co-design

AbstractWith the competition between companies becomes fiercer, it is necessary that several designers who are usually geometrically distributed, need cooperative work in design for an efficient design. In particular, a nuclear power plant is so complex, and these co-design environments were positively required. In this paper, to support co-design common data model, which has geometry and non-geometry data model, was developed based on semantic networks. That is the Korean Next Generation Reactor (KNGR) class library. The subject of data model is the Reactor Coolant System (RCS) in the KNGR. The KNGR class library was completed using XML through an analysis of the KNGR Information Management System (IMS) – Engineering Database (EDB) and the Generic Product Model (GPM) class library. When the KNGR class library was made, we considered a structural representation of plant and differences between the Pressurized-Water Reactor (PWR) and the Boiling-Water Reactor (BWR).
High Power Factor Interleaved Boost ACDC Converter with ZVS for Charging Battery Operated Vehicles

Abstract: The aim of the project is to develop a high power factor and efficient AC-DC converter suitable for charging batteries that are used in electric vehicles. The energy conversion during the battery charging is performed by an ac/dc converter. Boost converters are generally used to realize input PFC and ac/dc conversion. In high power applications, interleaving continuous current mode PFC boost stages are used. A novel, yet simple zero-voltage switching (ZVS) interleaved boost power factor correction (PFC) ac/dc converter used to charge the traction battery of an electric vehicle from the utility mains is proposed here. The proposed converter implements soft switching through a simple passive auxiliary circuit placed in between the two phases of the interleaved boost converter. This auxiliary circuit provides reactive current during the transition times of the MOSFETs to charge and discharge the output capacitors of the MOSFETs. In addition, the control system effectively optimizes the amount of reactive current required to achieve ZVS for the power MOSFETs. This optimization is crucial in this application since the converter may work at very light loads for a long period of time. The proposed converter maintains ZVS for the universal input voltage, which includes a very wide range of duty ratios.
A Neurologist's Guide to TNF Biology and to the Principles behind the Therapeutic Removal of Excess TNF in Disease

Tumor necrosis factor (TNF) is an ancient and widespread cytokine required in small amounts for much physiological function. Higher concentrations are central to innate immunity, but if unchecked this cytokine orchestrates much chronic and acute disease, both infectious and noninfectious. While being a major proinflammatory cytokine, it also controls homeostasis and plasticity in physiological circumstances. For the last decade or so these principles have been shown to apply to the central nervous system as well as the rest of the body. Nevertheless, whereas this approach has been a major success in treating noncerebral disease, its investigation and potential widespread adoption in chronic neurological conditions has inexplicably stalled since the first open trial almost a decade ago. While neuroscience is closely involved with this approach, clinical neurology appears to be reticent in engaging with what it offers patients. Unfortunately, the basic biology of TNF and its relevance to disease is largely outside the traditions of neurology. The purpose of this review is to facilitate lowering communication barriers between the traditional anatomically based medical specialties through recognition of shared disease mechanisms and thus advance the prospects of a large group of patients with neurodegenerative conditions for whom at present little can be done.
Mobile Use of IT

The emergence of worldwide computing networks is often said to make us all inhabitants of a “global village”. It will not matter where you are in the world, you can still communicate with everybody else. You will be able to access relevant information regardless. This has not made us less mobile, however. On the contrary, we are more mobile than ever. It may sound like a paradox, but an impressive set of statistics supports our claim:  25% of computer systems sold are for mobile use.  Europe has 55 million cellular telephone (GSM) subscribers.  USA had 2,24 million users of wireless internet-access in 1997. There could be 10 million by the end of 2000.  300 000 people are, at any time, airborne above USA.  300 000 people travel by car and train into London every morning. The global village is indeed a mobile one. Mobile Informatics is the field concerned with equipping the mobile society with innovative and useful services and applications. The purpose of this paper to explore the core concepts of Mobile Informatics, i.e., mobility and mobile IT use, and outline current problems and possibilities of IT use in mobile situations.
The chemistry of compact planetary nebulae

We report high-sensitivity millimetre observations of several molecular species ( 13 CO, HCN, HNC, CN, HCO + and N2H + ) in a sample of compact planetary nebulae. Some species such as HCO + and CN are particularly abundant compared to envelopes around AGB stars or even interstellar clouds. We have estimated the following average values for the column densities ratios: CN/HCN ∼ 2.6, HCO + /HCN ∼ 0.5, and HNC/HCN ∼ 0.4. Thus, the chemical composition of the molecular envelopes in these compact PNe appears somewhat intermediate between the composition of proto-PNe (such as CRL2688 or CRL618) and well evolved PNe (such as the Ring, M4-9, or the Helix). From observations of the CO isotopomers, we have estimated that the 12 C/ 13 C ratio is in the range 10 < 12 C/ 13 C < 40. These values are below those expected from standard asymptotic giant branch models and suggest non-standard mixing processes. The observed molecular abundances are compared to very recent modelling work, and we conclude that the observations are well explained, in general terms, by time-dependent gas-phase chemical models in which the ionization rate is enhanced by several orders of magnitude with respect to the average interstellar value. Thus, our observations confirm that the chemistry in the neutral shells of PNe is essentially governed by the high energy radiation from the hot central stars. The complexity of the chemical processes is increased by numerous factors linked to the properties of the central star and the geometry and degree of clumpiness of the envelope. Several aspects of the PN chemistry that remains to be understood are discussed within the frame of the available chemical models.
Supervised Coreference Resolution with SUCRE

In this paper we present SUCRE (Kobdani and Schutze, 2010) that is a modular coreference resolution system participating in the CoNLL-2011 Shared Task: Modeling Unrestricted Coreference in OntoNote (Pradhan et al., 2011). The SUCRE's modular architecture provides a clean separation between data storage, feature engineering and machine learning algorithms.
Girsanov Based Direct Policy Gradient Methods

Despite the plethora of reinforcement learning algorithms in machine learning and control, the majority of the work in this area relies on discrete time formulations of stochastic dynamics. In this work we present a new policy gradient algorithm for reinforcement learning in continuous state action spaces and continuous time. The derivation is based on successive application of Girsanov’s theorem and the use of the Radon Nikodým derivative as formulated for markov diffusion processes. The resulting policy gradient is reward weighted with the reward taking the form of a path integral. We apply the resulting algorithm in two simple examples for learning attractor landscapes in rhythmic and discrete movements.
A Point Mutation in a Herpesvirus Polymerase Determines Neuropathogenicity

Infection with equid herpesvirus type 1 (EHV-1) leads to respiratory disease, abortion, and neurologic disorders in horses. Molecular epidemiology studies have demonstrated that a single nucleotide polymorphism resulting in an amino acid variation of the EHV-1 DNA polymerase (N752/D752) is significantly associated with the neuropathogenic potential of naturally occurring strains. To test the hypothesis that this single amino acid exchange by itself influences neuropathogenicity, we generated recombinant viruses with differing polymerase sequences. Here we show that the N752 mutant virus caused no neurologic signs in the natural host, while the D752 virus was able to cause inflammation of the central nervous system and ataxia. Neurologic disease induced by the D752 virus was concomitant with significantly increased levels of viremia (p = 0.01), but the magnitude of virus shedding from the nasal mucosa was similar between the N752 and D752 viruses. Both viruses replicated with similar kinetics in fibroblasts and epithelial cells, but exhibited differences in leukocyte tropism. Last, we observed a significant increase (p < 0.001) in sensitivity of the N752 mutant to aphidicolin, a drug targeting the viral polymerase. Our results demonstrate that a single amino acid variation in a herpesvirus enzyme can influence neuropathogenic potential without having a major effect on virus shedding from infected animals, which is important for horizontal spread in a population. This observation is very interesting from an evolutionary standpoint and is consistent with data indicating that the N752 DNA pol genotype is predominant in the EHV-1 population, suggesting that decreased viral pathogenicity in the natural host might not be at the expense of less efficient inter-individual transmission.
Medical Management of Osteoarthritis

OBJECTIVES After participating in the CME activity, primary care physicians should be able to: 1. List the most commonly involved joints in osteoarthritis (OA) and some risk factors for developing the disease. 2. Understand the appropriate use of and potential adverse events associated with the currently available therapies for OA. 3. Appreciate the role of physical modalities in the management of OA. 4. Formulate an appropriate workup and differential diagnosis in a patient presenting with a joint effusion.
Vesicles Insect Midgut Brush Border Membrane Cry 1 Aa Toxin in Bacillus thuringiensis Affect the Rate of Pore Formation by the Mutations in Domain I Interhelical Loops

Published Ahead of Print 17 April 2009. 10.1128/AEM.02924-08. 2009, 75(12):3842. DOI: Appl. Environ. Microbiol. and Jean-Louis Schwartz Geneviève Larouche, Charles Vincent, Raynald Laprade Frédéric Girard, Luke Masson, Marc Juteau, Aliou Bah, Geneviève Lebel, Vincent Vachon, Gabrielle Préfontaine, Vesicles Insect Midgut Brush Border Membrane Cry1Aa Toxin in Bacillus thuringiensis Affect the Rate of Pore Formation by the Mutations in Domain I Interhelical Loops
Management of Locally Advanced Renal Cell Carcinoma with Invasion of the Duodenum

Renal cell carcinoma (RCC) is rare but aggressive, with greater than 20% of patients presenting with stage III or IV, disease. Surgical resection of the primary tumor regardless of stage is the treatment of choice, and en bloc resection of involved organs provides the only potential chance for cure. This case report describes a patient with metastatic right-sided RCC with invasion of the inferior vena cava and duodenum managed by en block resection and pancreaticoduodenectomy. This report will review the workup and treatment of locally advanced RCC, as well as the role of cytoreductive nephrectomy in the setting of metastatic disease.