Miracle-dz/UniFAR-FTUs huggingface dataset:
Dimensionality reduction of phone log-likelihood ratio features for spoken language recognition

In a previous work, we introduced the use of log-likelihood ratios of phone posterior probabilities, called Phone LogLikelihood Ratios (PLLR) as features for language recognition under an iVector-based approach, yielding high performance and promising results. However, the high dimensionality of the PLLR feature vectors (with regard to MFCC/SDC features) results in comparatively higher computational costs. In this work, several supervised and unsupervised dimensionality reduction techniques are studied, based on either fusions or selection of phone posteriors, finding that PLLR feature vectors can be reduced to almost a third of their original size attaining similar performance. Finally, Principal Component Analysis (PCA) is also applied to the original PLLR vector as a feature projection method for comparison purposes. Results show that PCA stands out among all the techniques studied, revealing that it does not only reduce computational costs, but also improves system performance significantly.
Cardiac development and physiology are modulated by FGF2 in an isoform- and sex-specific manner

The low‐molecular‐weight isoform (Lo) of fibroblast growth factor 2 (FGF2) has distinct functions from the high‐molecular‐weight isoforms (Hi) of FGF2 in the adult stressed heart. However, the specific roles of these isoforms in the unstressed heart were not examined. We investigated whether the FGF2 isoforms modulate cardiac development and physiology in isoform‐ and sex‐specific manners. Young adult male and female mice that were deficient in either Hi FGF2 (Hi KO) or Lo FGF2 (Lo KO) underwent echocardiographic analysis and were compared to their wild‐type (WT) counterparts. By comparison to WT cohorts, female Lo KO hearts display a 33% larger left ventricular (LV) volume and smaller LV mass and wall thickness. Mitral valve flow measurements from these hearts reveal that the early wave to atrial wave ratio (E/A) is higher, the deceleration time is 30% shorter and the mitral valve E‐A velocity–time integral is reduced by 20% which is consistent with a restrictive filling pattern. The female Hi KO hearts do not demonstrate any significant abnormality. In male Hi KO mice the cardiac output from the LV is 33% greater and the fractional shortening is 29% greater, indicating enhanced systolic function, while in male Lo KO hearts we observe a smaller E/A ratio and a prolonged isovolumic relaxation time, consistent with an impaired relaxation filling pattern. We conclude that the developmental and physiological functions of FGF2 isoforms in the unstressed heart are isoform specific and nonredundant and that these roles are modulated by sex.
Homogeneity-based feature extraction for classification of early-stage alzheimer's disease from functional magnetic resonance images

Alzheimer's disease is the most common form of age-related dementia. Early-stage diagnosis of Alzheimer is of major importance for the following reasons: Also easily curable conditions like depression, poor nutrition and drug side effects may cause symptoms like early-stage Alzheimer. Moreover, recently some medications have been developed which successfully attenuate the symptoms and delay the progression of Alzheimer, but to be effective, they need to be applied as soon as possible. However, early-stage diagnosis of Alzheimer is very difficult since the symptoms are very mild and can easily be confounded with effects of normal aging. In this paper, we introduce a bootstrapping-based feature extraction technique to identify early-stage Alzheimer's disease from resting-state functional resonance images. Our experiments demonstrate that subjects with early-stage Alzheimer's disease can be distinguished with an accuracy of 79% from age-matched healthy subjects using a support vector machine on the extracted features.
Effects of Spatial Frequencies on Word Identification by Fast and Slow Readers: Evidence from Eye Movements

Recent research has shown that differences in the effectiveness of spatial frequencies for fast and slow skilled adult readers may be an important component of differences in reading ability in the skilled adult reading population (Jordan et al., 2016a). But the precise nature of this influence on lexical processing during reading remains to be fully determined. Accordingly, to gain more insight into the use of spatial frequencies by skilled adult readers with fast and slow reading abilities, the present study looked at effects of spatial frequencies on the processing of specific target words in sentences. These target words were of either high or low lexical frequency and each sentence was displayed as normal or filtered to contain only very low, low, medium, high, or very high spatial frequencies. Eye movement behavior for target words was closest to normal for each reading ability when text was shown in medium or higher spatial frequency displays, although reading occurred for all spatial frequencies. Moreover, typical word frequency effects (the processing advantage for words with higher lexical frequencies) were observed for each reading ability across a broad range of spatial frequencies, indicating that many different spatial frequencies provide access to lexical representations during textual reading for both fast and slow skilled adult readers. Crucially, however, target word fixations were fewer and shorter for fast readers than for slow readers for all display types, and this advantage for fast readers appeared to be similar for normal, medium, high, and very high spatial frequencies but larger for low and very low spatial frequencies. Therefore, although fast and slow skilled adult readers can both use a broad range of spatial frequencies when reading, fast readers make more effective use of these spatial frequencies, and especially those that are lower, when processing the identities of words.
Hemolymph Proteins and Molting in Crustaceans and Insects

SYNOPSIS. The exoskeleton of crustaceans and insects is formed by cells of the hypodermis, but several hemolymph proteins contribute to the synthesis of the new exoskeleton. These hemolymph proteins share a surprising degree of sequence similarity and are members of the hemocyanin gene family. Copper-containing prophenoloxidases of crustaceans and insects are directly involved in cross-linking and hardening of the exoskeleton during molting and repair. Crustacean cryptocyanin and insect hexamerins lack copper and have probably evolved from a copper-free product of an early hemocyanin gene duplication. These proteins have been implicated in transport of hormones and phenols, and may be used directly as structural components of the new exoskeleton. They are synthesized elsewhere in the body, transported in the hemolymph, and probably taken up by the hypodermis via specific receptors. Hemocyanins have some residual phenoloxidase activity, in addition to their primary role of supplying oxygen to the metabolizing tissues. Thus multiple members of the hemocyanin gene family play vital roles during molting, and a molecular phytogeny of these proteins will contribute to our understanding of the evolution of form and function of these molecules from oxygen transport to molt-related activities. Further studies on the expression of prophenoloxidase, cryptocyanin, hexamerins and hemocyanin, potential marker proteins, may extend our understanding of the relationship between other molting animals in the proposed clade, Ecdysozoa.
Partial evaluation of functional logic programs

Languages that integrate functional and logic programming with a complete operational semantics are based on narrowing, a unification-based goal-solving mechanism which subsumes the reduction principle of functional languages and the resolution principle of logic languages. In this article, we present a partial evaluation scheme for functional logic languages based on an automatic unfolding algorithm which builds narrowing trees. The method is formalized within the theoretical framework established by Lloyd and Shepherdson for the partial deduction of logic programs, which we have generalized for dealing with functional computations. A generic specialization algorithm is proposed which does not depend on the eager or lazy nature of the narrower being used. To the best of our knowledge, this is the first generic algorithm for the specialization of functional logic programs. We also discuss the relation to work on partial evaluation in functional programming, term-rewriting systems, and logic programming. Finally, we present some experimental results with an implementation of the algorithm which show in practice that the narrowing-driven partial evaluator effectively combines the propagation of partial data structures (by means of logical variables and unification) with better opportunities for optimization (thanks to the functional dimension).
Antioxidant enzymes activity in subjects with Parkinson ’ s disease under L-DOPA therapy

1Elena C. Crăciun, 2Eleonora Dronca, 3Nicoleta V. Leach 1 Department of Pharmaceutical Biochemistry and Clinical Laboratory, Faculty of Pharmacy, “Iuliu Haţieganu” University of Medicine and Pharmacy, Cluj-Napoca, Romania; 2 Department of Molecular Sciences, Faculty of Medicine, “Iuliu Haţieganu” University of Medicine and Pharmacy, Cluj-Napoca, Romania; 4 Vth Department of Internal Medicine, “Iuliu Haţieganu” University of Medicine and Pharmacy, Cluj-Napoca, Romania.
Robust blind separation algorithms for heavy-tailed sources

The impulsive or heavy-tailed characteristics of sources signals can degrade severely the performances of existing blind source separation (BSS) methods. In this paper, we focus on the use of normalized statistics (NS) of heavy-tailed sources for the BSS problem. In M. Sahmoudi et al., (2003), the NS have been introduced for alpha-stable sources to justify for the use of algebraic-based separation algorithms (JADE, SOBI, etc) to achieve the BSS in the heavy-tailed case. In this work, we propose to use the NS to robustify the class of equivariant adaptive source separation algorithms EASI. Algorithm derivation, discussion and simulation results are provided to illustrate the usefulness of NS in that context. The new method has been compared with two of the most popular BSS algorithms; EASI and quasi maximum-likelihood algorithm.
Innovation with open data: Essential elements of open data ecosystems

Open data ecosystems are expected to bring many advantages, such as stimulating citizen participation and innovation. However, scant attention has been given to what constitutes an open data ecosystem. The objective of this paper is to provide an overview of essential elements of open data ecosystems for enabling easy publication and use of open data. To achieve this objective, the literature has been reviewed and a scenario about the publication and use of open data has been analyzed. It was found that various applications, tools and portals are available which together can form an ecosystem. The best functionalities of this ecosystem can be selected and utilized by open data providers and users. To create an open data ecosystem at least four key elements should be captured, namely, 1) releasing and publishing open data on the internet, 2) searching, finding, evaluating and viewing data and their related licenses, 3) cleansing, analyzing, enriching, combining, linking and visualizing data and 4) interpreting and discussing data and providing feedback to the data provider and other stakeholders. Furthermore, to integrate the ecosystem elements and to let them act as an integrated whole, there should be three additional elements 5) user pathways showing directions for how open data can be used, 6) a quality management system and 7) different types of metadata to be able to connect the elements.
THE HILBERT SCHEME OF DEGREE TWO CURVES AND CERTAIN ROPES

We study families of ropes of any codimension that are supported on lines. We construct suitable smooth parameter spaces and conclude that all ropes of fixed degree and genus lie in the same component of the corresponding Hilbert scheme. We show that this component is generically smooth if the genus is small enough unless the characteristic of the ground field is two and the curves under consideration have degree two. In this case the component is non-reduced.
Evaluation of Three Practical Methods for Estimating Daily Solar Radiation in Dry Climates

Three practical methods for estimating daily solar radiation in dry climates with air temperature and precipita- tion data as input were evaluated. The three equations only partially explained second order statistics such as variance and different correlations, so the interdependence with primary weather variables such as the daily maximum and minimum temperatures was not fully captured. The equations, however, may be useful for calculations that require solar radiation as input, such as the daily reference evapotranspiration according to Priestley-Taylor equation using the FAO guidelines ex- pert consultation.
Clustered Planarity Testing Revisited

The Hanani--Tutte theorem is a classical result proved for the first time in the 1930s that characterizes planar graphs as graphs that admit a drawing in the plane in which every pair of edges not sharing a vertex cross an even number of times. We generalize this result to clustered graphs with two disjoint clusters, and show that a straightforward extension to flat clustered graphs with three or more disjoint clusters is not possible. For general clustered graphs we show a variant of the Hanani--Tutte theorem in the case when each cluster induces a connected subgraph. Di Battista and Frati proved that clustered planarity of embedded clustered graphs whose every face is incident with at most five vertices can be tested in polynomial time. We give a new and short proof of this result, using the matroid intersection algorithm.
Using HIV Networks to Inform Real Time Prevention Interventions

Objective To reconstruct the local HIV-1 transmission network from 1996 to 2011 and use network data to evaluate and guide efforts to interrupt transmission. Design HIV-1 pol sequence data were analyzed to infer the local transmission network. Methods We analyzed HIV-1 pol sequence data to infer a partial local transmission network among 478 recently HIV-1 infected persons and 170 of their sexual and social contacts in San Diego, California. A transmission network score (TNS) was developed to estimate the risk of HIV transmission from a newly diagnosed individual to a new partner and target prevention interventions. Results HIV-1 pol sequences from 339 individuals (52.3%) were highly similar to sequences from at least one other participant (i.e., clustered). A high TNS (top 25%) was significantly correlated with baseline risk behaviors (number of unique sexual partners and insertive unprotected anal intercourse (p = 0.014 and p = 0.0455, respectively) and predicted risk of transmission (p<0.0001). Retrospective analysis of antiretroviral therapy (ART) use, and simulations of ART targeted to individuals with the highest TNS, showed significantly reduced network level HIV transmission (p<0.05). Conclusions Sequence data from an HIV-1 screening program focused on recently infected persons and their social and sexual contacts enabled the characterization of a highly connected transmission network. The network-based risk score (TNS) was highly correlated with transmission risk behaviors and outcomes, and can be used identify and target effective prevention interventions, like ART, to those at a greater risk for HIV-1 transmission.
Research statement 1 Research Statement

In the context of MRTA, I studied how to attain an optimum balance between coverage and sensing. I obtained optimal solutions under various cost schemes [1,2,5] that rely only on local information. Unlike previous results in the area, I consider both tasks that are of effectively different nature, and different realizations of the same task simultaneously. By looking at coordination problems, I improved the existing algorithms for two of the most common distributed robotic tasks: coverage and rendezvous. For coverage, I extended the approach from Cortés et. al. [10] to non-convex regions [4,6]. This generalization is highly relevant since most real world environments are non-convex. My result thus makes coverage algorithms practical for real world scenarios, including homeland security, environmental monitoring and ocean pollution control. Moreover, since the coverage problem can be shown to be equivalent to the quantization problem solved by Lloyd’s algorithm in signal processing, my extensions now allow its implementation in applications which are not restricted to a convex space. As for rendezvous, I solved the general problem by exhibiting it as a particular realization of consensus algorithms. My solution [3,8] describes how the rich literature on consensus protocols can be applied to analyze and solve the rendezvous problem, and also shows how most of the previous approaches to rendezvous are a particular realization of my solution. Although the relationship between rendezvous and coverage was not unnoticed in the literature, it was not until my paper [3] that an explicit description of the nature of this relationship was presented.
Remote sensing image fusion based on wavelet-based contourlet packet

In this paper, an algorithm based on wavelet-based contourlet transform is proposed for remote sensing image fusion. This method mainly involves three steps: The first stage provides subband decomposition, which in the case of the WBCT is a wavelet transform, in contrast to the Laplacian pyramid used in contourlets. The second stage of the WBCT is a directional filter bank (DFB), decomposition of the coefficients on wavelet-based contourlet packets (WBCP) and selection of proper fusion criterion in the contourlet subband. The main merit of the proposed method is that the contourlet transform can provide optimally sparse representation of objects with singularities along C2 edges and the wavelet-based contourlet packets (WBCP) can decompose the high frequency parts of the images which are not decomposed in discrete wavelet transform. This algorithm of fusing the images from different sensors can take advantage of the curves features of the source images more effectively. The experimental results demonstrate that this algorithm performs better than classical fusion methods both in visual effect and object evaluation.
Dynamic robot formations using directional visual perception

Recent research projects have demonstrated that it is possible to make robots move in formation. The approaches differ by the various assumptions about what can be perceived and communicated by the robots, the strategies used to make the robots move in formation, the ability to deal with obstacles and to switch formations. After suggesting criteria to characterize problems associated with robot formations, this paper presents a distributed approach based on directional visual perception and inter-robot communication. Using a pan camera head, sonar readings and wireless communication, we demonstrate that robots are not only able to move in formation, avoid obstacles and switch formations, but also initialize and determine by themselves their positions in the formation. Validation of our work is done in simulation and with Pioneer 2 robots.
Complex Decision-Making in Clinical Practice

Clinical Decision Support (CDS) Systems are considered crucial for diagnosis, treatment and care of patients. However, practical benefits of such systems have been far below expectations. This paper explores how the evolving interdependencies in organizational, clinical, political, and behavioral terms influence the design and implementation of CDS. The paper discusses how these interdependencies complicate clinical use of CDS where cross-departmental patient pathways increasingly dominate approaches to dealing with patients with complex conditions. Empirically, we report from an acute geriatric patient pathway project. The aim was to design and implement a decision-support form for triage of elderly patients in the emergency unit. The study emphasizes the intertwined collaborative nature of healthcare work, and the resulting need to consider the whole context when designing and implementing CDS tools. The contribution is to emphasize the “extended design” perspective to capture how workplace technologies and practices are shaped across multiple contexts and prolonged periods.
Miniature capacitive three-axis force sensor

Interest in low-cost force-torque sensors with high performance will continue to increase in the next years, as robot control needs to rely on more sensors to move into the human environment. Existing force-torque sensors still suffer from some shortcomings such as noise sensitivity, low resolution and high cost. This limits their use in some emerging applications. Through an advanced systematic design method based on a symbolic formulation of the wrench-displacement relationship, we designed compact and cost-effective three-axis capacitance-based force sensor. Despite its relative simplicity, our sensor exhibits a very good sensitivity thanks to the electronic components selected, but also to a special soft silicone layer filled with nanoparticles of ferroelectric ceramic. This composite we made has a relatively high dielectric constant. This paper presents the design process that led to the sensor including the structure, the capacitance measurement circuit and the fabrication of the soft dielectric. Characterization tests have also been carried out on a prototype of the sensor and the results show that it is sensitive and easy to fabricate.