Miracle-dz/UniFAR-FTUs huggingface dataset:
Speech kurtosis estimation from observed noisy signal based on generalized Gaussian distribution prior and additivity of cumulants

In this paper, we propose a new method for stable estimation of the kurtosis of a speech power spectrum. Speech kurtosis can be used for the prediction of speech recognition accuracy as reported in recent studies. However, the conventional estimation method is very unstable owing to the high sensitivity of higher-order statistics. To overcome this problem, we introduce the generalized Gaussian distribution prior in order to avoid the calculation of higher-order statistics, and construct a kurtosis table that directly represents the relationship among the kurtosis of speech, noise, and their mixture in the power spectrum domain. Speech kurtosis can be estimated stably from observable data by looking up values in the table. An experimental evaluation confirms the efficacy of the proposed method.
Corporate Governance, Performance and Risk-Taking in the U.S. Banking Industry

vi Chapter 1 1 Literature Review and Hypotheses 4 Data and Methodology 9 Results 12 Conclusion 14 Tables 17 Appendix 29 Chapter 2 34 Literature Review and Hypotheses 36 Data and Methodology 41 Results 44 Conclusion 48 Tables 50 Appendix 66 References 73 Vita 78
Prenatal Exposure to Residential Air Pollution and Infant Mental Development: Modulation by Antioxidants and Detoxification Factors

Background: Air pollution effects on children’s neurodevelopment have recently been suggested to occur most likely through the oxidative stress pathway. Objective: We aimed to assess whether prenatal exposure to residential air pollution is associated with impaired infant mental development, and whether antioxidant/detoxification factors modulate this association. Methods: In the Spanish INfancia y Medio Ambiente (INMA; Environment and Childhood) Project, 2,644 pregnant women were recruited during their first trimester. Nitrogen dioxide (NO2) and benzene were measured with passive samplers covering the study areas. Land use regression models were developed for each pollutant to predict average outdoor air pollution levels for the entire pregnancy at each residential address. Maternal diet was obtained at first trimester through a validated food frequency questionnaire. Around 14 months, infant mental development was assessed using Bayley Scales of Infant Development. Results: Among the 1,889 children included in the analysis, mean exposure during pregnancy was 29.0 μg/m3 for NO2 and 1.5 μg/m3 for benzene. Exposure to NO2 and benzene showed an inverse association with mental development, although not statistically significant, after adjusting for potential confounders [β (95% confidence interval) = –0.95 (–3.90, 1.89) and –1.57 (–3.69, 0.56), respectively, for a doubling of each compound]. Stronger inverse associations were estimated for both pollutants among infants whose mothers reported low intakes of fruits/vegetables during pregnancy [–4.13 (–7.06, –1.21) and –4.37 (–6.89, –1.86) for NO2 and benzene, respectively], with little evidence of associations in the high-intake group (interaction p-values of 0.073 and 0.047). Inverse associations were also stronger in non-breast-fed infants and infants with low maternal vitamin D, but effect estimates and interactions were not significant. Conclusions: Our findings suggest that prenatal exposure to residential air pollutants may adversely affect infant mental development, but potential effects may be limited to infants whose mothers report low antioxidant intakes.
Closed-Form Direction Finding Using Collocated but Orthogonally Oriented Higher Order Acoustic Sensors

This paper introduces new closed-form formulas to estimate an incident source's azimuth-elevation angle-of-arrival, for various combinations of higher order directional acoustic sensors, that are orthogonally oriented in a collocated triad. Also identified are the validity regions for un ambiguous estimation of the azimuth-elevation arrival-angle. These new direction-finding formulas may be used in the open literature's eigen-structure-based direction-finding algorithms, originally designed for (first-order) acoustic particle-velocity sensors.
Evidence for ice particles in the tropical stratosphere from in-situ measurements

In-situ ice crystal size distribution measurements are presented within the tropical troposphere and lower stratosphere. The measurements were performed using a combination of a Forward Scattering Spectrometer Probe (FSSP-100) and a Cloud Imaging Probe (CIP), which were installed on the Russian high altitude research aircraft M55 "Geophysica" during the SCOUT-O3 campaign in Darwin, Australia. One of the objectives of the campaign was to characterise the Hector convective system, which appears on an almost daily basis during the pre-monsoon season over the Tiwi Islands, north of Darwin. In total 90 encounters with ice clouds, between 10 and 19 km altitude were selected from the dataset and were analysed. Six of these encoun- ters were observed in the lower stratosphere, up to 1.4 km above the local tropopause. Concurrent lidar measurements on board "Geophysica" indicate that these ice clouds were a result of overshooting convection. Large ice crystals, with a maximum dimension up to 400µm, were observed in the stratosphere. The stratospheric ice clouds included an ice water content ranging from 7.7◊10 5 to 8.5◊10 4 g m 3 and were observed at ambient relative humidities (with re- spect to ice) between 75 and 157%. Three modal lognormal size distributions were fitted to the average size distributions for different potential temperature intervals, showing that the
Automatic SAR Target Recognition Based on Two-Dimensional Locality-Preserved Maximum Information Projection

Synthetic Aperture Radar (SAR) has been widely used in military and civil domains, while SAR Automatic Target Recognition (SAR ATR) poses a great challenge for researchers to meet real application demands. It is widely agreed that the lack of effective features is the bottleneck in advance of SAR ATR. In this paper, Locality-Preserved Maximum Information Projection (LPMIP) is used to extract features from the SAR images for ATR, where LPMIP is improved in three ways. 1) It is extended from one-dimensional version to two-dimensional one so that the structure information of SAR images can be better preserved. 2) The labels of samples are taken into account which makes the feature extraction method a supervised learning process. 3) To better balance the global and local structures, a two-stage framework is adopted, the presented 2D-LPMIP is executed following 2D-PCA to extract features of SAR images. ATR experiments on MSTAR databases achieved recognition accuracy of 97.44% with 698 training samples and 1662 testing samples. Experiment results testify the effectiveness of the proposed SAR image feature extraction method.
Bioinformatics Original Paper Predicting Transcription Factor Affinities to Dna from a Biophysical Model

Motivation: Theoretical efforts to understand the regulation of gene expression are traditionally centered around the identification of transcription factor binding sites at specific DNA positions. More recently these efforts have been supplemented by experimental data for relative binding affinities of proteins to longer intergenic sequences. The question arises to what extent these two approaches converge. In this paper, we adopt a physical binding model to predict the relative binding affinity of a transcription factor for a given sequence. Results: We find that a significant fraction of genome-wide binding data in yeast can be accounted for by simple count matrices and a physical model with only two parameters. We demonstrate that our approach is both conceptually and practically more powerful than traditional methods, which require selection of a cutoff. Our analysis yields biologically meaningful parameters, suitable for predicting relative binding affinities in the absence of experimental binding data. Availability: The C source code for our TRAP program is freely available for non-commercial use at
An algorithm for speech segregation of co-channel speech

This paper introduces an algorithm to separate speech streams from a single-channel speech mixture. Most current speech segregation algorithms allocate speech regions to participating speakers depending on which speaker dominates in which spectro-temporal region. The proposed method is a different approach to speech segregation, in that it separates the participating speaker streams rather than decide in the favor of the dominating speaker. The algorithm depends on a Lease-Squares fitting approach to model the speech mixture as a sum of complex exponentials. The algorithm gives results that are better than an existent algorithm when tested on the same task. The performance on a different database yielded good segregation results, even for Target-to-Masker ratios as low as −15 dB. The algorithm has immense promise for improvement and practical implementation.
Glycated hemoglobin, diabetes, and cardiovascular risk in nondiabetic adults.

BACKGROUND Fasting glucose is the standard measure used to diagnose diabetes in the United States. Recently, glycated hemoglobin was also recommended for this purpose. METHODS We compared the prognostic value of glycated hemoglobin and fasting glucose for identifying adults at risk for diabetes or cardiovascular disease. We measured glycated hemoglobin in whole-blood samples from 11,092 black or white adults who did not have a history of diabetes or cardiovascular disease and who attended the second visit (occurring in the 1990-1992 period) of the Atherosclerosis Risk in Communities (ARIC) study. RESULTS The glycated hemoglobin value at baseline was associated with newly diagnosed diabetes and cardiovascular outcomes. For glycated hemoglobin values of less than 5.0%, 5.0 to less than 5.5%, 5.5 to less than 6.0%, 6.0 to less than 6.5%, and 6.5% or greater, the multivariable-adjusted hazard ratios (with 95% confidence intervals) for diagnosed diabetes were 0.52 (0.40 to 0.69), 1.00 (reference), 1.86 (1.67 to 2.08), 4.48 (3.92 to 5.13), and 16.47 (14.22 to 19.08), respectively. For coronary heart disease, the hazard ratios were 0.96 (0.74 to 1.24), 1.00 (reference), 1.23 (1.07 to 1.41), 1.78 (1.48 to 2.15), and 1.95 (1.53 to 2.48), respectively. The hazard ratios for stroke were similar. In contrast, glycated hemoglobin and death from any cause were found to have a J-shaped association curve. All these associations remained significant after adjustment for the baseline fasting glucose level. The association between the fasting glucose levels and the risk of cardiovascular disease or death from any cause was not significant in models with adjustment for all covariates as well as glycated hemoglobin. For coronary heart disease, measures of risk discrimination showed significant improvement when glycated hemoglobin was added to models including fasting glucose. CONCLUSIONS In this community-based population of nondiabetic adults, glycated hemoglobin was similarly associated with a risk of diabetes and more strongly associated with risks of cardiovascular disease and death from any cause as compared with fasting glucose. These data add to the evidence supporting the use of glycated hemoglobin as a diagnostic test for diabetes.
Simulating Large Networks - How Big is Big Enough?

Simulation has become the evaluation method of choice for many areas of computer networking research. However, most existing network simulation packages have severe limitations on the size and complexity of the network being modeled. Simulated networks of just a few thousand network elements and a few thousand data ows will quickly exhaust the computing resources in any reasonably sized computer workstation. Thus the researcher is faced with the dilemma of proving concepts designed to work eÆciently on networks of tens of millions of elements, using a simulation of only a few thousand elements. The grand challenge we discuss in this paper is that of using simulation to reach credible conclusions about Internet{scale network performance. We present data that demonstrates that simulation of Internet{scale networks is not presently feasible, nor is it likely to be feasible in the near future. We present a summary of current research in the eld of large scale network simulations. These recent advances, while not enabling Internet{scale simulations, do o er the tools with which one can begin to tackle the problem. We sketch one possible approach and describe the issues that need to be resolved in order to realize it.
Influence of Co and B12 on the growth and nitrogen fixation of Trichodesmium

We investigated the influence of varying cobalt (Co) and B12 concentrations to growth and nitrogen fixation of Trichodesmium, a major diazotroph in the tropical and subtropical oligotrophic ocean. Here we show that sufficient inorganic Co, 20 pmol L-1, sustains the growth of Trichodesmium either with or without an additional B12 supply. We also found that in these culture conditions, nitrogen levels fixed by Trichodesmium were higher in treatments with insufficient B12 than in treatments with higher B12 availability. Under limited inorganic Co availability, ranging from 0.2 to 2 pmol L-1, Trichodesmium growth was significantly compromised in cultures without B12. In these low Co concentrations, addition of 400 pmol L-1 of B12 supported phytoplankton growth indicating that B12 supply augmented for the low Co concentrations. Our study demonstrates that Trichodesmium has an absolute Co requirement, which is not replaceable with Zn, and that B12 supply alleviates stress in cases where Co is limiting. These results show that the interlocking availabilities of Co and B12 may influence the growth and nitrogen fixation of Trichodesmium in the ocean.
Biomarkers of Chronic Inflammatory State in Uremia and Cardiovascular Disease

Cardiovascular disease is the leading cause of death in the general population; traditional risk factors seem inadequate to explain completely the remarkable prevalence of cardiovascular mortality and morbidity observed in the uremic population. A role for chronic inflammation has been well established in the development of atherosclerotic disease, and, on the basis of these observations, atherosclerosis might be considered an inflammatory disease. Inflammation has been implicated in the etiology of coronary artery disease in the general population, and traditional inflammatory biomarkers such as C-reactive protein (CRP) and interleukin-6 (IL-6) have been shown to predict cardiovascular events in both symptomatic and asymptomatic individuals as well as those in the uremic population. Later on, new nontraditional markers were related to the risk of cardiovascular morbidity and mortality in general and in uremic population. As a consequence of the expanding research base and availability of assays, the number of inflammatory marker tests ordered by clinicians for cardiovascular disease (CVD) risk prediction has grown rapidly and several commercial assays have become available. So, up to now we can consider that several new nontraditional markers as CD40-CD40 ligand system and pentraxin-3 seem to be significant features of cardiovascular disease in general and in ESRD population.
An X-Ray-Selected Galaxy Cluster at z = 1.11 in the ROSAT Deep Cluster Survey

We report the discovery of an X-ray–luminous galaxy cluster at z = 1.11. RDCS J0910+5422 was selected as an X-ray cluster candidate in the ROSAT Deep Cluster Survey on the basis of its spatial extent in a ROSAT Position Sensitive Proportional Counter image. Deep optical and near-IR imaging reveal a red galaxy overdensity around the peak of the X-ray emission, with a significant excess of objects with J-K and I-K colors typical of elliptical galaxies at z ∼ 1. Spectroscopic observations at the Keck II telescope secured nine galaxy redshifts in the range 1.095 < z < 1.120, yielding a mean cluster redshift of ⟨z⟩ = 1.106. Eight of these galaxies lie within a 30″ radius around the peak X-ray emission. A deep Chandra ACIS exposure on this field shows extended X-ray morphology and allows the X-ray spectrum of the intracluster medium to be measured. The cluster has bolometric luminosity Lx = 2.48 × 1044 ergs s-1, temperature kT = 7.2 keV, and mass within r = 1 Mpc of 7.0 × 1014 M⊙ (H0 = 65 km s-1 Mpc-1, Ωm = 0.3, and ΩΛ = 0.7). The spatial distribution of the cluster members is elongated, which is not due to an observational selection effect, and followed by the X-ray morphology. The X-ray surface brightness profile and the spectrophotometric properties of the cluster members suggest that this is an example of a massive cluster in an advanced stage of formation with a hot intracluster medium and an old galaxy population already in place at z > 1.
Developing adaptive exergames for adolescent children

Thanks to progression in ubiquitous technologies, exergames have emerged with the potential to motivate and facilitate exercise within an enjoyable context. While early research has shown the potential of the genre, little work has been done on systems that specifically target adolescent children, with their unique requirements and needs. In order to develop well suited exergames, capable of adapting to the situation of the player, work must me done to better understand the exergame experience. In this research we investigate how different demographics (gender, gaming backgrounds, exercise backgrounds) of adolescent children react to an exergame in order to begin understanding what contributes to an affective exergame experience, and how this differs between users. This work forms the first steps in modelling children within exergames with the goal of developing systems capable of adapting to the unique needs of the player.
A Daily-level Purchasing Model at an E-commerce Site

Recently, the e-commerce sites market in Japan is growing. Many companies in e-commerce sites compete for customers each other. Therefore, e-commerce managers need to find good customers who may benefit before these customers purchase at rivals. Some preceding studies discuss which visits lead to purchase. However, it is unclear when a customer visits. In our approach, we predict the day a customer will purchase. As a result, we found some customers who tend to purchase on the day after they viewed many product pages. We also found that product page viewing before purchasing may be one of good predictors. DOI: http://dx.doi. org/10.11591/ijece.v2i6. 1816
Extracting and depicting the 3D shape of specular surfaces

Many materials including water, plastic and metal have specular surface characteristics. Specular reflections have commonly been considered a nuisance for the recovery of object shape. However, the way that reflections are distorted across the surface depends crucially on 3D curvature, suggesting that they could in fact be a useful source of information. Indeed, observers can have a vivid impression of 3D shape when an object is perfectly mirrored (i.e. the image contains nothing but specular reflections). This leads to the question what are the underlying mechanisms of our visual system to extract this 3D shape information from a perfectly mirrored object. In this paper we propose a biologically motivated recurrent model for the extraction of visual features relevant for the perception of 3D shape information from images of mirrored objects. We analyze qualitatively and quantitatively the results of computational model simulations and show that bidirectional recurrent information processing leads to better results then pure feedforward processing. Furthermore we utilize the model output to create a rough non-photorealistic sketch representation of a mirrored object, which emphasizes image features that are mandatory for 3D shape perception (e.g. occluding contour, regions of high curvature). Moreover, this sketch illustrates that the model generates a representation of object features independent of the surrounding scene reflected in the mirrored object.
Numerical Simulation of the Taylor-Green Vortex at Re = 1600 with the Discontinuous Galerkin Spectral Element Method

In the following work, we present the results of selected simulations of the classical Taylor-Green vortex problem with a variant of the Discontinuous Galerkin method (DG) labeled the “Discontinuous Galerkin Spectral Element Method” (DGSEM). In the classical DGSEM formulation, the non-linear fluxes are colocated on the solution grid, leading to a highly efficient scheme but possible aliasing errors. Polynomial de-aliasing techniques proposed by Kirby and Karniadakis [5] avoid these errors, but incur a higher computational cost. We show results for the co-location and fully de-aliased versions of DGSEM, along with results for a locally adaptive de-aliasing approach. Taylor-Green Vortex flow The Taylor-Green vortex flow problem constitutes the simplest flow for which a turbulent energy cascade can be observed numerically. Starting from an initial analytical solution containing only a single length scale, the flow field undergoes a rapid build-up of a fully turbulent dissipative spectrum because of non-linear interactions of the developing eddies (Fig. 1). The resulting flow field exhibits the features of an isotropic, homogeneous turbulence and is often used in code validation or evaluation of numerical approaches to subgrid scale modeling [2], [3], [4]. All our computations were run on a structured Cartesian grid of hexahedral elements, covering a tripleperiodic box of size [−π, π]. The physical time frame from 0s to 20s was covered according to the problem description, starting from the initial analytical solution with given velocity and pressure fields, a constant temperature and an essentially incompressible flow field with a Mach number of Ma = 0.1. Figure 1: Taylor-Green Vortex (Re = 5000). Isocontours of vorticity magnitude, colored by helicity at t = 0.5s, 1.9s and 9.0s
Specificity of Afferent Synapses onto Plane-Polarized Hair Cells in the Posterior Lateral Line of the Zebrafish

The proper wiring of the vertebrate brain represents an extraordinary developmental challenge, requiring billions of neurons to select their appropriate synaptic targets. In view of this complexity, simple vertebrate systems provide necessary models for understanding how synaptic specificity arises. The posterior lateral-line organ of larval zebrafish consists of polarized hair cells organized in discrete clusters known as neuromasts. Here we show that each afferent neuron of the posterior lateral line establishes specific contacts with hair cells of the same hair-bundle polarity. We quantify this specificity by modeling the neuron as a biased selector of hair-cell polarity and find evidence for bias from as early as 2.5 d after fertilization. More than half of the neurons form contacts on multiple neuromasts, but the innervated organs are spatially consecutive and the polarity preference is consistent. Using a novel reagent for correlative electron microscopy, HRP-mCherry, we show that these contacts are indeed afferent synapses bearing vesicle-loaded synaptic ribbons. Moreover, afferent neurons reassume their biased innervation pattern after hair-cell ablation and regeneration. By documenting specificity in the pattern of neuronal connectivity during development and in the context of organ regeneration, these results establish the posterior lateral-line organ as a vertebrate system for the in vivo study of synaptic target selection.