Miracle-dz/UniFAR-FTUs huggingface dataset:
Robust voice activity detection using higher-order statistics in the LPC residual domain

This paper presents a robust algorithm for voice activity detection (VAD) based on newly established properties of the higher order statistics (HOS) of speech. Analytical expressions for the third and fourth-order cumulants of the LPC residual of short-term speech are derived assuming a sinusoidal model. The flat spectral feature of this residual results in distinct characteristics for these cumulants in terms of phase, periodicity and harmonic content and yields closed-form expressions for the skewness and kurtosis. Important properties about these cumulants and their similarity with the autocorrelation function are revealed from this exploratory part. They show that the HOS of speech are sufficiently distinct from those of Gaussian noise and can be used as a basis for speech detection. Their immunity to Gaussian noise makes them particularly useful in algorithms designed for low SNR environments. The proposed VAD algorithm combines HOS metrics with second-order measures, such as SNR and LPC prediction error, to classify speech and noise frames. The variance of the HOS estimators is quantified and used to yield a likelihood measure for noise frames. Moreover, a voicing condition for speech frames is derived based on the relation between the skewness and kurtosis of voiced speech. The performance of the algorithm is compared to the ITU-T G.729B VAD in various noise conditions, and quantified using the probability of correct and false classifications. The results show that the proposed algorithm has an overall better performance than G.729B, with noticeable improvement in Gaussian-like noises, such as street and parking garage, and moderate to low SNR.
Effects of Fertilizer and Low Rates of Imidacloprid on Adelges tsugae (Hemiptera: Adelgidae)

ABSTRACT Healthy hemlock trees, Tsuga canadensis (L.) Carrière, and hemlock woolly adelgid, Adelges tsugae Annand (Hemiptera: Adelgidae), populations should favor retention and population growth of adelgid predators such as Laricobius nigrinus Fender (Coleoptera: Derodontidae) and Sasajiscymnus tsugae (Sasaji & McClure) (Coleoptera: Coccinellidae). Eastern hemlock trees between 15 and 38 cm diameter at breast height (dbh) were treated with 0, 10, or 25% of 1.5 g imidacloprid (Merit 75 WP) per 2.5 cm dbh and were either fertilized or not, in a 3 by 2 factorial design. After 2 yr, imidacloprid reduced the numbers of ovisacs and eggs found on trees in a dosage-dependent manner, while enhancing tree growth parameters such as new shoots or needles and the length of new shoots. Fertilized trees had greater adelgid fecundity, which was positively correlated with total foliar N in both winter generations. In February 2009 (27 mo after imidacloprid treatment), higher imidacloprid dosages to unfertilized trees resulted in reduced adelgid fecundity. Concentrations of N, P, and K were higher in the foliage of trees treated with insecticide, whereas foliar aluminum concentrations were consistently lower in trees with higher insecticide dosages. Trees treated with low rates of imidacloprid were healthier than untreated trees, but only trees treated with the 0.1 × dosage had sufficient adelgids to possibly sustain predators over extended periods.
The Lactic Acid Bacterium Pediococcus acidilactici Suppresses Autoimmune Encephalomyelitis by Inducing IL-10-Producing Regulatory T Cells

Background Certain intestinal microflora are thought to regulate the systemic immune response. Lactic acid bacteria are one of the most studied bacteria in terms of their beneficial effects on health and autoimmune diseases; one of which is Multiple sclerosis (MS) which affects the central nervous system. We investigated whether the lactic acid bacterium Pediococcus acidilactici, which comprises human commensal bacteria, has beneficial effects on experimental autoimmune encephalomyelitis (EAE), an animal model of MS. Methodology/Principal Findings P. acidilactici R037 was orally administered to EAE mice to investigate the effects of R037. R037 treatment suppressed clinical EAE severity as prophylaxis and therapy. The antigen-specific production of inflammatory cytokines was inhibited in R037-treated mice. A significant increase in the number of CD4+ Interleukin (IL)-10-producing cells was observed in the mesenteric lymph nodes (MLNs) and spleens isolated from R037-treated naive mice, while no increase was observed in the number of these cells in the lamina propria. Because only a slight increase in the CD4+Foxp3+ cells was observed in MLNs, R037 may primarily induce Foxp3− IL10-producing T regulatory type 1 (Tr1) cells in MLNs, which contribute to the beneficial effect of R037 on EAE. Conclusions/Significance An orally administered single strain of P. acidilactici R037 ameliorates EAE by inducing IL10-producing Tr1 cells. Our findings indicate the therapeutic potential of the oral administration of R037 for treating multiple sclerosis.
On the optimal ordering of maps and selections under factorization

The query optimizer of a database system is confronted with two aspects when handling user-defined functions (UDFs) in query predicates: the vast differences in evaluation costs between UDFs (and other functions) and multiple calls of the same (expensive) UDF The former is dealt with by ordering the evaluation of the predicates optimally, the latter by identifying common subexpressions and thereby avoiding costly recomputation. Current approaches order n predicates optimally (neglecting factorization) in O(nlogn). Their result may deviate significantly from the optimal solution under factorization. We formalize the problem of finding optimal orderings under factorization and prove that it is NP-hard. Furthermore, we show how to improve on the run time of the brute-force algorithm (which computes all possible orderings) by presenting different enhanced algorithms. Although in the worst case these algorithms obviously still behave exponentially, our experiments demonstrate that for real-life examples their performance is much better.
Regulation of 3β-Hydroxysteroid Dehydrogenase/Δ5-Δ4 Isomerase: A Review

This review focuses on the expression and regulation of 3β-hydroxysteroid dehydrogenase/Δ5-Δ4 isomerase (3β-HSD), with emphasis on the porcine version. 3β-HSD is often associated with steroidogenesis, but its function in the metabolism of both steroids and xenobiotics is more obscure. Based on currently available literature covering humans, rodents and pigs, this review provides an overview of the present knowledge concerning the regulatory mechanisms for 3β-HSD at all omic levels. The HSD isoenzymes are essential in steroid hormone metabolism, both in the synthesis and degradation of steroids. They display tissue-specific expression and factors influencing their activity, which therefore indicates their tissue-specific responses. 3β-HSD is involved in the synthesis of a number of natural steroid hormones, including progesterone and testosterone, and the hepatic degradation of the pheromone androstenone. In general, a number of signaling and regulatory pathways have been demonstrated to influence 3β-HSD transcription and activity, e.g., JAK-STAT, LH/hCG, ERα, AR, SF-1 and PPARα. The expression and enzymic activity of 3β-HSD are also influenced by external factors, such as dietary composition. Much of the research conducted on porcine 3β-HSD is motivated by its importance for the occurrence of the boar taint phenomenon that results from high concentrations of steroids such as androstenone. This topic is also examined in this review.
Physiologic frailty and fragility fracture in HIV-infected male veterans.

BACKGROUND The Veterans Aging Cohort Study (VACS) Index is associated with all-cause mortality in individuals infected with human immunodeficiency virus (HIV). It is also associated with markers of inflammation and may thus reflect physiologic frailty. This analysis explores the association between physiologic frailty, as assessed by the VACS Index, and fragility fracture. METHODS HIV-infected men from VACS were included. We identified hip, vertebral, and upper arm fractures using ICD-9-CM codes. We used Cox regression models to assess fragility fracture risk factors including the VACS Index, its components (age, hepatitis C status, FIB-4 score, estimated glomerular filtration rate, hemoglobin, HIV RNA, CD4 count), and previously identified risk factors for fragility fractures. RESULTS We included 40 115 HIV-infected male Veterans. They experienced 588 first fragility fractures over 6.0 ± 3.9 years. The VACS Index score (hazard ratio [HR], 1.15; 95% confidence interval [CI], 1.11-1.19), white race (HR, 1.92; 95% CI, 1.63-2.28), body mass index (HR, 0.94; 95% CI, .92-.96), alcohol-related diagnoses (HR, 1.65; 95% CI, 1.26-2.17), cerebrovascular disease (HR, 1.95; 95% CI, 1.14-3.33), proton pump inhibitor use (HR, 1.87; 95% CI, 1.54-2.27), and protease inhibitor use (HR, 1.25; 95% CI, 1.04-1.50) were associated with fracture risk. Components of the VACS Index score most strongly associated with fracture risk were age (HR, 1.40; 95% CI, 1.27-1.54), log HIV RNA (HR, 0.91; 95% CI, .88-.94), and hemoglobin level (HR, 0.82; 95% CI, .78-.86). CONCLUSIONS Frailty, as measured by the VACS Index, is an important predictor of fragility fractures among HIV-infected male Veterans.
The Effect of Combine Hopfield Neural Network and Fuzzy Ranking on E-Learning system Performance

In recent years, more and more teachers and learners have used e-learning system as the site to teach and study. Therefore, how to improve the efficiency in e-learning system has become a very important topic. This research combines Hopfield-Tank Neural Network and fuzzy ranking theories to analyze the learning efficiency and the useful nodes in learning path. After that, the researcher can improve the learning material according to the results and therefore make the students who study the same course of the e-learning system get better proficiency.
AnimSkin: Fabricating Epidermis with Interactive, Functional and Aesthetic Color Animation

Human epidermis, as the largest organ on body, has become a new design platform for wearable computing. The availability of miniature electronics makes more possibilities for on-skin designs. In this paper, we present AnimSkin, a thin-film interface, which will emit dynamic color animations directly on skin. This is done by using thermochromic material embedded with transparent electrode acting as a capacitive sensor. Moreover, an accessible and low-cost fabrication method is introduced. Individuals could also customize aesthetic graphic designs by following the detailed fabrication process to achieve personalized patterns. We propose four different dynamic types of color animation by applying certain voltage to the heating circuitry. With two examples, Email Reminder and Light Control System, we demonstrate how AnimSkin can be integrated into everyday life, and specifically, we show how AnimSkin can benefit areas such as on-skin design, thin-film interface and beauty technology.
A Stabilized Finite Element Method for Darcy-Stokes Problems

A stabilized finite element methods for the singularly perturbed Stokes problem is proposed in this paper. This model is approximately a linear Stokes problem when the perturbation parameter is large, while it degenerates to a mixed formulation of Poisson's equation as the perturbation parameter tends to zero. The stabilized formula is uniformly stable for a traditional stable and uniformly-consistent Stokes element. The corresponding discretization error estimates are derived. Finally some 2Dnumerical experiments are carried out to verify the theoretical results.
The periodic magnetic Schr\"odinger operators: spectral gaps and tunneling effect

A periodic Schr\"odinger operator on a noncompact Riemannian manifold $M$ such that $H^1(M, \mathbb R)=0$ endowed with a properly discontinuous cocompact isometric action of a discrete group is considered. Under some additional conditions on the magnetic field existence of an arbitrary large number of gaps in the spectrum of such an operator in the semiclassical limit is established. The proofs are based on the study of the tunneling effect in the corresponding quantum system.
Functional Specialization of the Plant miR396 Regulatory Network through Distinct MicroRNA–Target Interactions

MicroRNAs (miRNAs) are ∼21 nt small RNAs that regulate gene expression in animals and plants. They can be grouped into families comprising different genes encoding similar or identical mature miRNAs. Several miRNA families are deeply conserved in plant lineages and regulate key aspects of plant development, hormone signaling, and stress response. The ancient miRNA miR396 regulates conserved targets belonging to the GROWTH-REGULATING FACTOR (GRF) family of transcription factors, which are known to control cell proliferation in Arabidopsis leaves. In this work, we characterized the regulation of an additional target for miR396, the transcription factor bHLH74, that is necessary for Arabidopsis normal development. bHLH74 homologs with a miR396 target site could only be detected in the sister families Brassicaceae and Cleomaceae. Still, bHLH74 repression by miR396 is required for margin and vein pattern formation of Arabidopsis leaves. MiR396 contributes to the spatio-temporal regulation of GRF and bHLH74 expression during leaf development. Furthermore, a survey of miR396 sequences in different species showed variations in the 5′ portion of the miRNA, a region known to be important for miRNA activity. Analysis of different miR396 variants in Arabidopsis thaliana revealed that they have an enhanced activity toward GRF transcription factors. The interaction between the GRF target site and miR396 has a bulge between positions 7 and 8 of the miRNA. Our data indicate that such bulge modulates the strength of the miR396-mediated repression and that this modulation is essential to shape the precise spatio-temporal pattern of GRF2 expression. The results show that ancient miRNAs can regulate conserved targets with varied efficiency in different species, and we further propose that they could acquire new targets whose control might also be biologically relevant.
Neural Representations of Observed Actions Generalize across Static and Dynamic Visual Input

People interact with entities in the environment in distinct and categorizable ways (e.g., kicking is making contact with foot). We can recognize these action categories across variations in actors, objects, and settings; moreover, we can recognize them from both dynamic and static visual input. However, the neural systems that support action recognition across these perceptual differences are unclear. Here, we used multivoxel pattern analysis of fMRI data to identify brain regions that support visual action categorization in a format-independent way. Human participants were scanned while viewing eight categories of interactions (e.g., pulling) depicted in two visual formats: (1) visually controlled videos of two interacting actors and (2) visually varied photographs selected from the internet involving different actors, objects, and settings. Action category was decodable across visual formats in bilateral inferior parietal, bilateral occipitotemporal, left premotor, and left middle frontal cortex. In most of these regions, the representational similarity of action categories was consistent across subjects and visual formats, a property that can contribute to a common understanding of actions among individuals. These results suggest that the identified brain regions support action category codes that are important for action recognition and action understanding. SIGNIFICANCE STATEMENT Humans tend to interpret the observed actions of others in terms of categories that are invariant to incidental features: whether a girl pushes a boy or a button and whether we see it in real-time or in a single snapshot, it is still pushing. Here, we investigated the brain systems that facilitate the visual recognition of these action categories across such differences. Using fMRI, we identified several areas of parietal, occipitotemporal, and frontal cortex that exhibit action category codes that are similar across viewing of dynamic videos and still photographs. Our results provide strong evidence for the involvement of these brain regions in recognizing the way that people interact physically with objects and other people.
Adaptive Jacobian tracking control of robots with uncertainties in kinematic, dynamic and actuator models

Most research so far on robot trajectory control has assumed that the kinematics of the robot is known exactly. However, when a robot picks up tools of uncertain lengths, orientations, or gripping points, the overall kinematics becomes uncertain and changes according to different tasks. Recently, we derived a new adaptive Jacobian tracking controller for robots with uncertain kinematics and dynamics. This note extends the results to include redundant robots and adaptation to actuator parameters. Experimental results are presented to illustrate the performance of the proposed controller.
Probabilistic Graphlet Cut: Exploiting Spatial Structure Cue for Weakly Supervised Image Segmentation

Weakly supervised image segmentation is a challenging problem in computer vision field. In this paper, we present a new weakly supervised image segmentation algorithm by learning the distribution of spatially structured super pixel sets from image-level labels. Specifically, we first extract graph lets from each image where a graph let is a small-sized graph consisting of super pixels as its nodes and it encapsulates the spatial structure of those super pixels. Then, a manifold embedding algorithm is proposed to transform graph lets of different sizes into equal-length feature vectors. Thereafter, we use GMM to learn the distribution of the post-embedding graph lets. Finally, we propose a novel image segmentation algorithm, called graph let cut, that leverages the learned graph let distribution in measuring the homogeneity of a set of spatially structured super pixels. Experimental results show that the proposed approach outperforms state-of-the-art weakly supervised image segmentation methods, and its performance is comparable to those of the fully supervised segmentation models.
Microglia are crucial regulators of neuro-immunity during central nervous system tuberculosis

Mycobacterium tuberculosis (M. tuberculosis) infection of the central nervous system (CNS) is the most devastating manifestation of tuberculosis (TB), with both high mortality and morbidity. Although research has been fueled by the potential therapeutic target microglia offer against neurodegenerative inflammation, their part in TB infection of the CNS has not been fully evaluated nor elucidated. Yet, as both the preferential targets of M. tuberculosis and the immune-effector cells of the CNS, microglia are likely to be key determinants of disease severity and clinical outcomes. Following pathogen recognition, bacilli are internalized and capable of replicating within microglia. Cellular activation ensues, utilizing signaling molecules that may be neurotoxic. Central to initiating, orchestrating and modulating the tuberculous immune response is microglial secretion of cytokines and chemokines. However, the neurological environment is unique in that inflammatory signals, which appear to be damaging in the periphery, could be beneficial by governing neuronal survival, regeneration and differentiation. Furthermore, microglia are important in the recruitment of peripheral immune cells and central to defining the pro-inflammatory milieu of which neurotoxicity may result from many of the participating local or recruited cell types. Microglia are capable of both presenting antigen to infiltrating CD4+ T-lymphocytes and inducing their differentiation—a possible correlate of protection against M. tuberculosis infection. Clarifying the nature of the immune effector molecules secreted by microglia, and the means by which other CNS-specific cell types govern microglial activation or modulate their responses is critical if improved diagnostic and therapeutic strategies are to be attained. Therefore, this review evaluates the diverse roles microglia play in the neuro-immunity to M. tuberculosis infection of the CNS.
Conditional Discrimination and Stimulus Equivalence: Effects of Suppressing Derived Symmetrical Responses on the Emergence of Transitivity.

Symmetry suppression was conducted for five subjects who demonstrated a tendency to derive equivalence relations based on conditional discrimination training in a match-to-sample procedure. Symmetry suppression was applied in three consecutive sessions in which symmetrical responses were suppressed for one stimulus class in the first condition, two stimulus classes in the second condition, and all three stimulus classes in the final condition. Symmetry suppression slowed the emergence of transitivity for two subjects and prevented it for the other three. Results indicated that unplanned features of stimulus configurations emerged as discriminative variables that controlled selection responses and altered the function of consequent stimuli. Disruption of cognitive development by conflicting contingencies in natural learning environments is discussed.
Dutch Cooking with xAPI Recipes: The Good, the Bad, and the Consistent

This short paper presents the experiences of several Dutch projects in their application of the xAPI standard and different design patterns including the deployment of Learning Record Stores. In this paper we share insights and argue for the formation of an international Special Interest Group on interoperability issues to contribute to the Open Analytics Framework as envisioned by SoLAR and enacted by the Apereo Learning Analytics Initiative. Therefore, we provide an overview of the advantages and disadvantages of implementing the current xAPI standard by presenting projects that applied xAPI in very different ways followed by the lessons learned.
Age Dependence of Immunity Induced by a Candidate Universal Influenza Vaccine in Mice

Influenza has a major impact on the elderly due to increased susceptibility to infection with age and poor response to current vaccines. We have studied universal influenza vaccine candidates based on influenza A nucleoprotein and matrix 2 (A/NP+M2). Long-lasting protection against influenza virus strains of divergent subtypes is induced, especially with mucosal immunization. Here, we tested universal vaccination in BALB/c mice of different ages. Vaccination used intramuscular DNA priming to A/NP+M2 followed by intranasal (i.n.) boosting with recombinant adenoviruses (rAd) expressing the same antigens, or only A/NP+M2-rAd given i.n. Antigen-specific systemic antibody responses were induced in young, middle-aged, and elderly mice (2, 11–17, and 20 months old, respectively), but decreased with age. Antibody responses in bronchoalveolar lavage (BAL) were detected only in young mice. Antigen-specific T cell responses were seen in young and middle-aged but not elderly mice. A/NP+M2 vaccination by the two regimens above protected against stringent challenge in young and middle-aged mice, but not in elderly mice. However, mice vaccinated with A/NP-rAd or A/M2-rAd during their youth were partially protected against challenge 16 months later when they were elderly. In addition, a regimen of two doses of A/NP+M2-rAd given i.n. one month apart beginning in old age protected elderly mice against stringent challenge. This study highlights the potential benefit of cross-protective vaccines through middle age, and suggests that their performance might be enhanced in elderly individuals who had been exposed to influenza antigens early in life, as most humans have been, or by a two-dose rAd regimen given later in life.