Miracle-dz/UniFAR-FTUs huggingface dataset:
Combination of acoustic and lexical speaker adaptation for disordered speech recognition

This paper presents an approach to provide of lexical adaptation in Automatic Speech Recognition (ASR) of the disordered speech from a group of young impaired speakers. The outcome of an Acoustic Phonetic Decoder (APD) is used to learn new lexical variants of the 57-word vocabulary and add them to a lexicon personalized to each user. The possibilities of combination of this lexical adaptation with acoustic adaptation achieved through traditional Maximum A Posteriori (MAP) approaches are furtherer explored, and the results show the importance of matching the lexicon in the ASR decoding phase to the lexicon used for the acoustic adaptation.
When is it possible to simulate a DMC channel from another?

In this paper, we study the problem of simulating a DMC channel from another DMC channel. We assume that the input to the channel we are simulating is i.i. d. and that the transmitter and receivers are provided with common randomness at limited rates. We prove bounds for simulating point-to-point, MAC and broadcast channels. As a special case, we recover the achievability part of the result of Cuff for point-to-point channel simulation via a noiseless link and shared randomness.
Predictors of Hope Among Members of Mental Health Self-Help Agencies

Abstract Hope is a key construct for successful community adjustment among those with severe mental illnesses, particularly given the strengths-based recovery model increasingly prevalent in mental health services and in social work. Consumer-run mental health self-help agencies (SHAs) are well suited to fostering hope via their supportive program environments. This study examines factors associated with hope among members of four self-help agencies via a two-stage least squares regression model (N =310). Findings provide evidence of both individual and program-level associations with hope. These findings mirror social work ethical values of focusing on consumer strengths and self-determination, which are primary goals of SHAs.
An Algorithm for Synthesis of Reversible Logic Circuits

Reversible logic finds many applications, especially in the area of quantum computing. A completely specified n-input, n-output Boolean function is called reversible if it maps each input assignment to a unique output assignment and vice versa. Logic synthesis for reversible functions differs substantially from traditional logic synthesis and is currently an active area of research. The authors present an algorithm and tool for the synthesis of reversible functions. The algorithm uses the positive-polarity Reed-Muller expansion of a reversible function to synthesize the function as a network of Toffoli gates. At each stage, candidate factors, which represent subexpressions common between the Reed-Muller expansions of multiple outputs, are explored in the order of their attractiveness. The algorithm utilizes a priority-based search tree, and heuristics are used to rapidly prune the search space. The synthesis algorithm currently targets the generalized n-bit Toffoli gate library. However, other algorithms exist that can convert an n-bit Toffoli gate into a cascade of smaller Toffoli gates. Experimental results indicate that the authors' algorithm quickly synthesizes circuits when tested on the set of all reversible functions of three variables. Furthermore, it is able to quickly synthesize all four-variable and most five-variable reversible functions that were in the test suite. The authors also present results for some benchmark functions widely discussed in literature and some new benchmarks that the authors have developed. The algorithm is shown to synthesize many, but not all, randomly generated reversible functions of as many as 16 variables with a maximum gate count of 25
Relaxation dynamics of maximally clustered networks

We study the relaxation dynamics of fully clustered networks (maximal number of triangles) to an unclustered state under two different edge dynamics-the double-edge swap, corresponding to degree-preserving randomization of the configuration model, and single edge replacement, corresponding to full randomization of the Erdős-Rényi random graph. We derive expressions for the time evolution of the degree distribution, edge multiplicity distribution and clustering coefficient. We show that under both dynamics networks undergo a continuous phase transition in which a giant connected component is formed. We calculate the position of the phase transition analytically using the Erdős-Rényi phenomenology.
Brown carbon aerosol in the North American continental troposphere: sources, abundance, and radiative forcing

Abstract. Chemical components of organic aerosol (OA) selectively absorb light at short wavelengths. In this study, the prevalence, sources, and optical importance of this so-called brown carbon (BrC) aerosol component are investigated throughout the North American continental tropospheric column during a summer of extensive biomass burning. Spectrophotometric absorption measurements on extracts of bulk aerosol samples collected from an aircraft over the central USA were analyzed to directly quantify BrC abundance. BrC was found to be prevalent throughout the 1 to 12 km altitude measurement range, with dramatic enhancements in biomass-burning plumes. BrC to black carbon (BC) ratios, under background tropospheric conditions, increased with altitude, consistent with a corresponding increase in the absorption Angstrom exponent (AAE) determined from a three-wavelength particle soot absorption photometer (PSAP). The sum of inferred BC absorption and measured BrC absorption at 365 nm was within 3 % of the measured PSAP absorption for background conditions and 22 % for biomass burning. A radiative transfer model showed that BrC absorption reduced top-of-atmosphere (TOA) aerosol forcing by ~ 20 % in the background troposphere. Extensive radiative model simulations applying this study background tropospheric conditions provided a look-up chart for determining radiative forcing efficiencies of BrC as a function of a surface-measured BrC : BC ratio and single scattering albedo (SSA). The chart is a first attempt to provide a tool for better assessment of brown carbon's forcing effect when one is limited to only surface data. These results indicate that BrC is an important contributor to direct aerosol radiative forcing.
Critical Current Characteristics and Flux Pinning in Fe-Based Pnictide Superconductor

The superconducting Ba1-xKxFe2As2 (x = 0.4) single crystals were prepared by the so-called FeAs self-flux method. The critical temperature by ac susceptibility measurement was estimated to be about 36 K. The magnetic field and temperature dependences of critical current densities were investigated by an ac inductive measurement (Campbell’s method). Unlike the phenomenon of co-existence of the global and local critical current densities observed in many polycrystalline Fe-based superconducting pnictides, it was found that only a uniform critical current density (Jc) flows through the whole sample. The value of Jc at 20 K and 1 T was about 5×108 A/m2, which is much smaller than the local critical current density observed in polycrystalline samples. This result implies that a dissimilarity of flux pinning mechanism exists between these two kinds of materials. The force-displacement characteristic of fluxoids in sample was investigated. The Labusch parameter was found to increase monotonously with increasing magnetic field, while the interaction distance was proportional to the fluxoid spacing. These results are consistent with the prediction based on a simple flux pinning mechanism.
Position-dependent effects on stability in tricyclo-DNA modified oligonucleotide duplexes

A series of oligodeoxyribonucleotides and oligoribonucleotides containing single and multiple tricyclo(tc)-nucleosides in various arrangements were prepared and the thermal and thermodynamic transition profiles of duplexes with complementary DNA and RNA evaluated. Tc-residues aligned in a non-continuous fashion in an RNA strand significantly decrease affinity to complementary RNA and DNA, mostly as a consequence of a loss of pairing enthalpy ΔH. Arranging the tc-residues in a continuous fashion rescues Tm and leads to higher DNA and RNA affinity. Substitution of oligodeoxyribonucleotides in the same way causes much less differences in Tm when paired to complementary DNA and leads to substantial increases in Tm when paired to complementary RNA. CD-spectroscopic investigations in combination with molecular dynamics simulations of duplexes with single modifications show that tc-residues in the RNA backbone distinctly influence the conformation of the neighboring nucleotides forcing them into higher energy conformations, while tc-residues in the DNA backbone seem to have negligible influence on the nearest neighbor conformations. These results rationalize the observed affinity differences and are of relevance for the design of tc-DNA containing oligonucleotides for applications in antisense or RNAi therapy.
Tanning Behavior of London-Area Youth

Background: The World Health Organization recommends that tanning parlors not be used by individuals under age 18 years. The impact of self-tanners on tanning parlor and sunscreen use by Canadian teens is unknown. Objective: To determine teens' use of, knowledge of, attitudes toward, and behavior regarding tanning parlors, self-tanning products, and sunscreen. Methods: Self-report questionnaire of grade 10 students in Thames Valley district, Ontario. Results: Indoor tanning parlors were used by 14%, self-tanners by 28%, and sunscreen daily or most days by 36%. Use was more common in females. There was a strong association between parental and child use of tanning parlors and use of self-tanners. Sixty-two percent believe that self-tanners give adequate photoprotection. Conclusions: Further education is required to address teen tanning parlor use, infrequent sunscreen use, and lack of knowledge about the safety of tanning parlors and self-tanning products.
Using human observer eye movements in automatic image classifiers

We explore the way in which people look at images of different semantic categories and directly relate those results to computational approaches for automatic image classification. Our hypothesis is that the eye movements of human observers differ for images of different semantic categories, and that this information can be effectively used in automatic content-based classifiers. First, we present eye tracking experiments that show the variation in eye movements across different individuals for image of 5 different categories: handshakes, crowd, landscapes, main object in uncluttered background, and miscellaneous. The eye tracking results suggest that similar viewing patterns occur when different subjects view different images in the same semantic category. Using these results, we examine how empirical data obtained from eye tracking experiments across different semantic categories can be integrated with existing computational frameworks, or used to construct new ones. In particular, we examine the Visual Apprentice, a system in which images classifiers are learned form user input as the user defines a multiple level object definition hierarchy based on an object and its parts and labels examples for specific classes. The resulting classifiers are applied to automatically classify new images. Although many eye tracking experiments have been performed, to our knowledge, this is the first study that specifically compares eye movements across categories, and that links category-specific eye tracking results to automatic image classification techniques.
Prognostic Role of Common MicroRNA Polymorphisms in Cancers: Evidence from a Meta-Analysis

Background The morbidity and mortality of cancer increase remarkably every year. It's a heavy burden for family and society. The detection of prognostic biomarkers can help to improve the theraputic effect and prolong the lifetime of patients. microRNAs have an influential role in cancer prognosis. The results of articles discussing the relationship between microRNA polymorphisms and cancer prognosis are inconsistent. Methods We conduct a meta-analysis of 19 publications concerning the association of four common polymorphisms, mir-146a rs2910164, mir-149 rs2292832, mir-196a2 rs11614913 and mir-499 rs3746444, with cancer prognosis. Pooled Hazard Ratios with 95% Confidence Intervals for the relationship between four genetic polymorphisms and Overall Survival, Recurrence-free Survival, Disease-free survival, recurrence are calculated. Subgroup analysis by population and type of tumor are conducted. Results GG genotype of mir-146a may be the protective factor for overall survival, especially in Caucasian population. C-containing genotypes of mir-196a2 act as a risk role for overall survival. The same result exists in Asian population, in Non-Small Cell Lung Cancer and digestive cancer. The patients with C allele of mir-149 have a better overall survival, especially in Non-Small Cell Lung Cancer. No significant results are obtained for mir-499 polymorphisms. Conclusions Genetic polymorphisms in mir-146a, mir-196a2 and mir-149 may be associated with overall survival. This effect varies with different types of cancer. Genetic polymorphism in mir-499 may have nothing to do with cancer prognosis.
Analysis of optimality in natural and perturbed metabolic networks

Text 1) Clearly mark all of your changes and answers to author queries in the margins next to the article text in the proofs; 2) Review and answer ALL author queries (marked in the margin of the text with AQ:A, AQ:B, etc.) that are listed on the query sheet(s); 3) Check figure numbering and placement; 4) Proofread tables and equations carefully; and 5) Make sure that any Greek or special characters appear correctly throughout the text.
HelPal: A Search System for Mobile Crowd Service

Proliferation of ubiquitous mobile devices makes location based services prevalent. Mobile users are able to volunteer as providers of specific services and in the meanwhile to search these services. For example, drivers may be interested in tracking available nearby users who are willing to help with motor repair or are willing to provide travel directions or first aid. With the diffusion of mobile users, it is necessary to provide scalable means of enabling such users to connect with other nearby users so that they can help each other with specific services. Motivated by these observations, we design and implement a general location based system HelPal for mobile users to provide and enjoy instant service, which is called mobile crowd service. In this demo, we introduce a mobile crowd service system featured with several novel techniques. We sketch the system architecture and illustrate scenarios via several cases. Demonstration shows the user-friendly search interface for users to conveniently find skilled and qualified nearby service providers.
View-Dependent Real-Time Rendering of Large Outdoor Scenes

A new real-time point-based rendering method of large outdoor scenes is presented. Based on our interactive subdivide method, polygonal trees and other vegetation were converted to point-based models, and then different level of details of trees and other vegetation were created using hierarchical clustering. Different level of details of terrain were created using diamond tree backbone of ROAM2.0 method. Therefore, trees and other vegetation were rendered using point-based method on GPU and terrain was rendered using triangle based method. A compromise between terrain rendering performance and plant rendering quality was made to achieve ideal visual effect. By our method, the rendering primitive decreased and the fidelity of outdoor scenes was kept. Experiments show that our hybrid rendering method could render large outdoor scenes in real-time.
Affinity Separation: M13 Bacteriophage-Activated Superparamagnetic Beads for Affinity Separation

The growth of the biopharmaceutical industry has created a demand for new technologies for the purification of genetically engineered proteins.The efficiency of large-scale, high-gradient magnetic fishing could be improved if magnetic particles offering higher binding capacity and magnetization were available. This article describes several strategies for synthesizing microbeads that are composed of a M13 bacteriophage layer assembled on a superparamagnetic core. Chemically cross-linking the pVIII proteins to a carboxyl functionalized bead produced highly responsive superparamagnetic particles (SPM) with a side-on oriented, adherent virus monolayer. Also, the genetic manipulation of the pIII proteins with a His 6 peptide sequence allowed reversible assembly of the bacteriophage on a nitrilotriacetic acid functionalized core in an end-on configuration. These phage-magnetic particles were successfully used to separate antibodies from high-protein concentration solutions in a single step with a > 90 % purity. The dense magnetic core of these particles makes themfive times more responsive to magnetic fields than commercial materialscomposed of polymer-iron oxide compositesand a monolayer of phage could produced a 1000 fold higher antibody binding capacity. These new bionanomaterials appear to be well-suited to large-scale high-gradient magnetic fishing separation and promise to be cost effective as a result of the self-assembling and self-replicating properties of genetically engineered M13 bacteriophage.
Identity awareness and re-use of research data in veillance and social computing

Identity awareness of research data has been introduced as a requirement for open research, transparency and reusability of research data in the context of eScience. This requirement includes the capability of linking research data to researchers, research projects and publications, and identifying the license for the data. This connectivity between research data and other elements in research ecosystems is required in order to make the data available and reusable beyond the initial research. In this paper, we examine these capabilities in the domains of veillance and social computing. The dataset cases presented in this paper articulate the challenges that researchers face as they seek to expose data created as a result of research activities.
Regression Based on Conditional Quantile Restriction with Weak-Identification-Robust Inference

Extending the L1-IV estimator proposed by Sakata (1997, 2007), we develop a method, named the ρτ -IV estimator, to estimate structural equations based on the conditional quantile restriction imposed on the error terms. We study its asymptotic behavior and show how to make statistical inferences on the regression parameters. Given practical importance of weak identification, a highlight of the paper is proposal of a test robust to the weak identification. The statistics used in our method can be viewed as a natural counterpart of the Anderson and Rubin’s (1949) statistic in the ρτ -IV estimation. As is the case for the Anderson-Rubin test in the standard IV regression, our test can have a low power, when there many instruments excluded from the regression equation. We show how we could avoid such problem
Supplementary Material to Curriculum Dropout

Pattern Analysis & Computer Vision (PAVIS) – Istituto Italiano di Tecnologia – Genova, 16163, Italy Department of Biomedial Engineering – Johns Hopkins University – Baltimore, MD 21218, USA Electrical, Electronics and Telecommunication Engineering and Naval Architecture Department (DITEN) – Università degli Studi di Genova – Genova, 16145, Italy Computer Science Department – Università di Verona – Verona, 37134, Italy {pietro.morerio,jacopo.cavazza,riccardo.volpi,vittorio.murino}@iit.it, rvidal@cis.jhu. edu
Human-Computer Interaction Based on Hand Gestures Using RGB-D Sensors

In this paper we present a new method for hand gesture recognition based on an RGB-D sensor. The proposed approach takes advantage of depth information to cope with the most common problems of traditional video-based hand segmentation methods: cluttered backgrounds and occlusions. The algorithm also uses colour and semantic information to accurately identify any number of hands present in the image. Ten different static hand gestures are recognised, including all different combinations of spread fingers. Additionally, movements of an open hand are followed and 6 dynamic gestures are identified. The main advantage of our approach is the freedom of the user's hands to be at any position of the image without the need of wearing any specific clothing or additional devices. Besides, the whole method can be executed without any initial training or calibration. Experiments carried out with different users and in different environments prove the accuracy and robustness of the method which, additionally, can be run in real-time.
A Continuous and Reversible LOD Algorithm for Highway Terrain

In view of the inherent contradiction between mass data and real-time browsing in Highway 3D Visualization System, this paper proposes an edge folding algorithm for weighted average elevation base on vertex degrees, which will improve the model simplification effective. In the process of building a continuous LOD model, the algorithm uses mesh line to blocky process the terrain model to eliminate the adverse effects of long and narrow triangles, adopts Hoppe’s reversible progressive meshes construction algorithm to build grid-based LOD terrain model of continuous reversible, finally adopts LOD scheduling algorithm based on viewpoint, realizing multi-resolution terrain display of continuous reversible.
Surveillance Event Detection

We have developed and evaluated three generalized systems for event detection. The first system is a simple brute force search method, where each space-time location in the video is evaluated by a binary decision rule on whether it contains the event or not. The second system is build on top of a head tracker to avoid costly brute force searching. The decision stage is a combination of state of the art feature extractors and classifiers. Our third system has a probabilistic framework. From the observations, the pose of the people are estimated and used to determine the presence of event. Finally we introduce two ad-hoc methods that were designed to specifically detect OpposingFlow and TakePicture events. The results are promising as we are able to get good results on several event categories, while for all events we have gained valuable insights and experience.
Supercomputing in molecular biology: applications to sequence analysis

Genetic data, accumulating at a rapid pace, are ideally suited to computer analysis. These data pose problems of a magnitude that requires supercomputing. The National Cancer Institute of the US National Institutes of Health (NIH) has developed the Advanced Scientific Computing Laboratory to utilize these data for basic research of relevance to cancer and other diseases. The facility and its use for several research problems of biomedical importance are discussed below. The problems considered are sequence comparisons, nucleic acid second structure prediction, Monte Carlo tests, molecular dynamics, and drug design. Computer time in spent various areas of research is summarized. <<ETX>>
A new adaptive linear multi-stage multiuser detector for DS-CDMA systems

Conventional linear multi-user detectors (MUD) such as the decorrelating MUD and MMSE MUD require the inversion of a matrix or solution of a system of linear equations. The high complexity involved makes direct matrix inversion or direct solution of the system of linear equations difficult especially when the number of users is large. In this paper, we propose a new adaptive linear multi-stage MUD that has lower complexity. Parameters of the proposed structure can be optimized offline or update on the fly according to channel conditions. Simulation results show that the proposed MUD with a few numbers of stages almost achieves the performance of the linear MMSE MUD.