Miracle-dz/UniFAR-FTUs huggingface dataset:
A syllable, articulatory-feature, and stress-accent model of speech recognition

Current-generation automatic speech recognition (ASR) systems assume that words are readily decomposable into constituent phonetic components (“phonemes”). A detailed linguistic dissection of state-of-the-art speech recognition systems indicates that the conventional phonemic “beads-on-a-string” approach is of limited utility, particularly with respect to informal, conversational material. The study shows that there is a significant gap between the observed data and the pronunciation models of current ASR systems. It also shows that many important factors affecting recognition performance are not modeled explicitly in these systems. Motivated by these findings, this dissertation analyzes spontaneous speech with respect to three important, but often neglected, components of speech (at least with respect to English ASR). These components are articulatory-acoustic features (AFs), the syllable and stress accent. Analysis results provide evidence for an alternative approach of speech modeling, one in which the syllable assumes pre-eminent status and is melded to the lower as well as the higher tiers of linguistic representation through the incorporation of prosodic information such as stress accent. Using concrete examples and statistics from spontaneous speech material it is shown that there exists a systematic relationship between the realization of AFs and stress accent in conjunction with syllable position. This relationship can be used to provide an accurate and parsimonious characterization of pronunciation variation in spontaneous speech. An approach to automatically extract AFs from the acoustic signal is also developed, as is a system for the automatic stress-accent labeling of spontaneous speech. Based on the results of these studies a syllable-centric, multi-tier model of speech recognition is proposed. The model explicitly relates AFs, phonetic segments and syllable constituents to a framework for lexical representation, and incorporates stress-accent information into recognition. A test-bed implementation of the model is developed using a fuzzy-based approach for combining evidence from various AF sources and a pronunciation-variation modeling technique using AF-variation statistics extracted from data. Experiments on a limited-vocabulary speech recognition task using both automatically derived and fabricated data demonstrate the advantage of incorporating AF and stress-accent modeling within the syllable-centric, multi-tier framework, particularly with respect to pronunciation variation in spontaneous speech.
Myosin light chain kinase binding to a unique site on F-actin revealed by three-dimensional image reconstruction

Ca2+–calmodulin-dependent phosphorylation of myosin regulatory light chains by the catalytic COOH-terminal half of myosin light chain kinase (MLCK) activates myosin II in smooth and nonmuscle cells. In addition, MLCK binds to thin filaments in situ and F-actin in vitro via a specific repeat motif in its NH2 terminus at a stoichiometry of one MLCK per three actin monomers. We have investigated the structural basis of MLCK–actin interactions by negative staining and helical reconstruction. F-actin was decorated with a peptide containing the NH2-terminal 147 residues of MLCK (MLCK-147) that binds to F-actin with high affinity. MLCK-147 caused formation of F-actin rafts, and single filaments within rafts were used for structural analysis. Three-dimensional reconstructions showed MLCK density on the extreme periphery of subdomain-1 of each actin monomer forming a bridge to the periphery of subdomain-4 of the azimuthally adjacent actin. Fitting the reconstruction to the atomic model of F-actin revealed interaction of MLCK-147 close to the COOH terminus of the first actin and near residues 228–232 of the second. This unique location enables MLCK to bind to actin without interfering with the binding of any other key actin-binding proteins, including myosin, tropomyosin, caldesmon, and calponin.
All-in-One: Graph Processing in RDBMSs Revisited

To support analytics on massive graphs such as online social networks, RDF, Semantic Web, etc. many new graph algorithms are designed to query graphs for a specific problem, and many distributed graph processing systems are developed to support graph querying by programming. In this paper, we focus on RDBM, which has been well studied over decades to manage large datasets, and we revisit the issue how RDBM can support graph processing at the SQL level. Our work is motivated by the fact that there are many relations stored in RDBM that are closely related to a graph in real applications and need to be used together to query the graph, and RDBM is a system that can query and manage data while data may be updated over time. To support graph processing, in this work, we propose 4 new relational algebra operations, MM-join, MV-join, anti-join, and union-by-update. Here, MM-join and MV-join are join operations between two matrices and between a matrix and a vector, respectively, followed by aggregation computing over groups, given a matrix/vector can be represented by a relation. Both deal with the semiring by which many graph algorithms can be supported. The anti-join removes nodes/edges in a graph when they are unnecessary for the following computing. The union-by-update addresses value updates to compute PageRank, for example. The 4 new relational algebra operations can be defined by the 6 basic relational algebra operations with group-by & aggregation. We revisit SQL recursive queries and show that the 4 operations with others are ensured to have a fixpoint, following the techniques studied in DATALOG, and enhance the recursive WITH clause in SQL'99. We conduct extensive performance studies to test 10 graph algorithms using 9 large real graphs in 3 major RDBMs. We show that RDBMs are capable of dealing with graph processing in reasonable time. The focus of this work is at SQL level. There is high potential to improve the efficiency by main-memory RDBMs, efficient join processing in parallel, and new storage management.
Ten Years of SkyServer II: How Astronomers and the Public Have Embraced e-Science

A comprehensive analysis of 10 years of Web and SQL traffic on SkyServer-the online portal to the multiterabyte Sloan Digital Sky Survey archive--shows the impressive reach of the SDSS to the research community and the public, and provides insight into how methods of e-science are being taken up by the scientific community.
THE ACT OF CREATING HUMOROUS ACRONYMS

Our species cannot survive without humor and future human-machine interaction systems will be required to handle humor. From a practical point of view, humor is an important resource for getting selective attention, help in memorizing names and situations, etc. Even if deep modeling of humor in all of its facets is not something available in the near future, there is something concrete that has been achieved and that can help in providing attention to the field. The paper refers to the results of HAHACRONYM, a project devoted to humorous acronym production, a circumscribed task that nonetheless requires various generic components. The project opens the way to developments for creative language. Electronic commerce, for instance, will include flexible and individual-oriented humorous promotion more or less as it happened in the world of broadcasted advertisement.
Vertebrate Protein CTCF and its Multiple Roles in a Large-Scale Regulation of Genome Activity

The CTCF transcription factor is an 11 zinc fingers multifunctional protein that uses different zinc finger combinations to recognize and bind different sites within DNA. CTCF is thought to participate in various gene regulatory networks including transcription activation and repression, formation of independently functioning chromatin domains and regulation of imprinting. Sequencing of human and other genomes opened up a possibility to ascertain the genomic distribution of CTCF binding sites and to identify CTCF-dependent cis-regulatory elements, including insulators. In the review, we summarized recent data on genomic distribution of CTCF binding sites in the human and other genomes within a framework of the loop domain hypothesis of large-scale regulation of the genome activity. We also tried to formulate possible lines of studies on a variety of CTCF functions which probably depend on its ability to specifically bind DNA, interact with other proteins and form di- and multimers. These three fundamental properties allow CTCF to serve as a transcription factor, an insulator and a constitutive dispersed genome-wide demarcation tool able to recruit various factors that emerge in response to diverse external and internal signals, and thus to exert its signal-specific function(s).
Maximal ratio combining for respiratory effort extraction from pressure sensor arrays

Respiratory effort signals may be measured using pressure sensors placed below a mattress. When few of the sensors include the respiratory effort signal or the signal power is low, output respiratory effort signal quality is low. This paper examines current signal combining methods used in pressure sensor array breathing estimation and proposes a maximal ratio combining method to produce the best estimate in these conditions. Data was collected from two participants and the effects of low signal power and low signal availability were simulated by corrupting the recordings. The results show that the proposed method offers 2.5 dB higher signal to noise ratio in the presence of substantial noise and good correlation (> 0.92) to gold standard respiration bands.
Impairment of neutrophil extracellular trap degradation is associated with lupus nephritis

Systemic lupus erythematosus (SLE) is an autoimmune disease in which patients develop autoantibodies to DNA, histones, and often to neutrophil proteins. These form immune complexes that are pathogenic and may cause lupus nephritis. In SLE patients, infections can initiate flares and are a major cause of mortality. Neutrophils respond to infections and release extracellular traps (NETs), which are antimicrobial and are made of DNA, histones, and neutrophil proteins. The timely removal of NETs may be crucial for tissue homeostasis to avoid presentation of self-antigens. We tested the hypothesis that SLE patients cannot clear NETs, contributing to the pathogenesis of lupus nephritis. Here we show that serum endonuclease DNase1 is essential for disassembly of NETs. Interestingly, a subset of SLE patients’ sera degraded NETs poorly. Two mechanisms caused this impaired NET degradation: (i) the presence of DNase1 inhibitors or (ii) anti-NET antibodies prevented DNase1 access to NETs. Impairment of DNase1 function and failure to dismantle NETs correlated with kidney involvement. Hence, identification of SLE patients who cannot dismantle NETs might be a useful indicator of renal involvement. Moreover, NETs might represent a therapeutic target in SLE.
Vector-Value Markov Decision Process for multi-objective stochastic path planning

The problem of path planning in stochastic environments where the shortest path is not always the best one is a challenging issue required in many real-world applications such as autonomous vehicles, robotics, logistics, etc. … In this paper, we consider the problem of path planning in stochastic environments where the length of the path is not the unique criterion to consider. We formalize this problem as a multi-objective decision-theoretic path planning and we transform this latter into 2VMDP Vector-Valued Markov Decision Process. We show, then, how we can compute a policy balancing between different considered criteria. We describe different techniques that allow us to derive an optimal policy where it is hard to express the expected utilities, rewards and values with a unique numerical measure. Firstly, we examine different existing approaches based on preferences and we define notions of optimality with preferred solutions and secondly we present approaches based on egalitarian social welfare techniques. Finally, some experimental results have been developed to show the feasibility of the approach and the benefit of this approach on the single-objective techniques.
The effects of walking, feedback and control method on pressure-based interaction

This paper presents a study looking into the effects of walking and the use of visual and audio feedback on the application of pressure for linear targeting. Positional and Rate-based control methods are compared in order to determine which allows for more stable and accurate selections, both while sitting and mobile. Results suggest that Rate-based control is superior for both mobile (walking) and static (sitting) linear targeting, and that mobility significantly increases errors, selection time and subjective workload. The use of only audio feedback significantly increased errors and task time for Positional control and static Rate-based control, but not mobile Rate-based control. Despite this, the results still suggest that audio control of pressure interaction while walking is highly accurate and usable.
Visualising Crime Clusters in a Space‐time Cube: An Exploratory Data‐analysis Approach Using Space‐time Kernel Density Estimation and Scan Statistics

For an effective interpretation of spatio‐temporal patterns of crime clusters/hotspots, we explore the possibility of three‐dimensional mapping of crime events in a space‐time cube with the aid of space‐time variants of kernel density estimation and scan statistics. Using the crime occurrence dataset of snatch‐and‐run offences in Kyoto City from 2003 to 2004, we confirm that the proposed methodology enables simultaneous visualisation of the geographical extent and duration of crime clusters, by which stable and transient space‐time crime clusters can be intuitively differentiated. Also, the combined use of the two statistical techniques revealed temporal inter‐cluster associations showing that transient clusters alternatively appeared in a pair of hotspot regions, suggesting a new type of “displacement” phenomenon of crime. Highlighting the complementary aspects of the two space‐time statistical approaches, we conclude that combining these approaches in a space‐time cube display is particularly valuable for a spatio‐temporal exploratory data analysis of clusters to extract new knowledge of crime epidemiology from a data set of space‐time crime events.
Occult Cranial Cervical Dislocation: A Case Report and Brief Literature Review

Study Design. Retrospective case report and review. Objective. Cranial cervical dislocation (CCD) is commonly a devastating injury. Delay in diagnosis has been found to lead to worse outcomes. Our purpose is to describe a rare case of occult cranial cervical dislocation (CCD) and use it to highlight key clinical and radiographic findings to ensure expedited diagnosis and proper management avoiding delays and subsequent neurologic deterioration. Method. Case report with literature review. Results. We describe a unique case of occult cranial cervical dislocation where initial imaging of the cervical spine failed to illustrate displacement of the occipital-cervical (O-C1) articulation or C1-C2 articulation. Careful evaluation of subtle radiographic clues suggested a more severe injury than initial review. Additional imaging was obtained due to these subtle clues confirming true cranial cervical dislocation allowing subsequent treatment with no neurologic sequelae. Conclusion. A high index of suspicion of CCD may prevent injury in select patients who present without gross cord compromise. Careful consideration of associated fractures, soft tissue injuries, and mechanism of injury are essential clues to the correct diagnosis and management of injuries to the craniocervical junction (CCJ).
Estimation of Rapidly Time-Varying Channels for OFDM Systems

Channel estimation for OFDM systems in rapidly time-varying environments is challenging. In this paper, relying on a basis expansion channel model, we propose a scheme for estimating channel parameters varying within a transmission block. Along with the estimation scheme, we also derive the optimal pilot sequence and optimal placement of pilot tones with respect to the mean square error (MSE) of the channel estimate. It is shown that the optimal pilot sequence consists of some adjacent equipowered and equispaced subsequences that are constrained by certain phase conditions. Simulation results demonstrate the performance of the proposed scheme in rapidly time-varying scenarios
Robust Active Vibration Isolation: A Multivariable Data-Driven Approach

Abstract Active vibration isolation is essential for a large range of high precision motion systems in industry. This paper aims to develop a framework for high performance robust vibration isolation by explicitly addressing multivariable flexible dynamical behavior. A framework is proposed that connects identification and control. In addition, a new data-driven uncertainty modeling procedure is used that results in a nonconservative model error bound. Application on an active vibration isolation system confirms high performance robust vibration isolation.
Region-Based Retrieval of Remote Sensing Images Using an Unsupervised Graph-Theoretic Approach

This letter introduces a novel unsupervised graph-theoretic approach in the framework of region-based retrieval of remote sensing (RS) images. The proposed approach is characterized by two main steps: (1) modeling each image by a graph, which provides region-based image representation combining both local information and related spatial organization, and (2) retrieving the images in the archive that are most similar to the query image by evaluating graph-based similarities. In the first step, each image is initially segmented into distinct regions and then modeled by an attributed relational graph, where nodes and edges represent region characteristics and their spatial relationships, respectively. In the second step, a novel inexact graph matching strategy, which jointly exploits a subgraph isomorphism algorithm and a spectral graph embedding technique, is applied to match corresponding graphs and to retrieve images in the order of graph similarity. Experiments carried out on an archive of aerial images point out that the proposed approach significantly improves the retrieval performance compared to the state-of-the-art unsupervised RS image retrieval methods. (RS) images.
Combining eye tracking with navigation paths for identification of cross-language code dependencies

In recent years, fine-grained monitoring of software developers during software development and maintenance activities has increased in popularity, together with use of devices for eye tracking and recording developer’s biometric data. We look for everyday application of such data to support developers in their work. In this paper we discuss an approach to identify potential code dependencies in source code, even when written in different programming languages, by combining identification of areas-of-interest in source code using eye tracking with developer’s navigation paths. Our plan is to evaluate it with data of developers working on real development tasks.
Assessmentof Electric FieldDistributionin AnisotropicCorticalandSubcortical Regions Under the Influenceof tDCS

The focus of this study is to estimate the contribution of regional anisotropic conductivity on the spatial distribution of an induced electric field across gray matter (GM), white matter (WM), and subcortical regions under transcranial direct current stimulation (tDCS). The assessment was conducted using a passive high-resolution finite element head model with inhomogeneous and variable anisotropic conductivities derived from the diffusion tensor data. Electric field distribution was evaluated across different cortical as well as subcortical regions under four bicephalic electrode configurations. Results indicate that regional tissue heterogeneity and anisotropy cause the pattern of induced fields to vary in orientation and strength when compared to the isotropic scenario. Different electrode montages resulted in distinct distribution patterns with noticeable variations in field strengths. The effect of anisotropy is highly montage dependent and directional conductivity has a more profound effect in defining the strength of the induced field. The inclusion of anisotropy in the GM and subcortical regions has a significant effect on the strength and spatial distribution of the induced electric field. Under the (C3 Fp2) montage, the inclusion of GM and subcortical anisotropy increased the average percentage difference in the electric field strength of brain from 5% to 34% (WM anisotropy only). In terms of patterns distribution, the topographic errors increased from 9.9% to 40% (WM anisotropy only) across the brain. Bioelectromagnetics 9999:1 17, 2013. © 2013 Wiley Periodicals, Inc.
Accompanist recognition and tracking for intelligent wheelchairs

Recently, several robotic wheelchairs have been proposed that employ autonomous functions. In designing wheelchairs, it is important to reduce the accompanist load. To provide such a task, the mobile robot needs to recognize and track people. In this paper, we propose to utilize the multisensory data fusion to track a target accompanist. First, the simultaneous localization and map building is achieved by using the laser range finder (LRF) and inertial sensors with the extended Kalman filter recursively. To track the target person robustly, the accompanist, are tracked by fusing laser and vision data. The human objects are detected by LRF, and the identity of accompanist is recognized using a PTZ camera with a pre-defined signature using the speed-up robust features algorithm. The proposed system can adaptively search visual signature and track the accompanist by dynamically zooming the PTZ camera based on LRF detection results to enlarge the range of human following. The experimental results verified and demonstrated the performance of the proposed system.
2 Reflections on an initial trust-building model

Trust is important to organizations because it lubricates the relationships that form the interlocking components of coordination, which, like gears, turn the wheels of commerce. Trust becomes especially important during an organizational crisis (Mishra, 1996) or when supportive structures are inadequate. Thus it is vital to examine how trust forms in various work and commercial settings, because if one can understand the conditions, factors and processes determining this, one can thereby influence the coordinative consequents of trust. One of many depictions of how trust forms is found in McKnight et al. (1998). Here trust is depicted as it forms in the initial phase of a relationship. The initial phase refers to when parties are unfamiliar with each other (Bigley and Pearce, 1998). By unfamiliar, we mean they have little solid, verifiable information about each other, and what they do know is not from first-hand, personal experience. This condition usually results from the newness of the relationship (that is, when parties first meet), but may also result from a combination of newness and relationship distance, because when parties are socially distant (for example, virtual team members or Internet transactional partners), they may not receive first-hand, verifiable information about the other for some time. This definition of the initial phase means the initial phase stops after parties gain verifiable information by first-hand interactional or transactional experience with each other. Hence experience is not considered a factor of initial trust.