Miracle-dz/UniFAR-FTUs huggingface dataset:
Audio-visual person identification on the XM2VTS database

This paper presents a multimodal person identification syst em based on combination of audio and visual classifiers. The audio classifier was built by using mel-frequency cepstrum coefficient features and Gaussian mixture models. The visua l classifier was implemented by Haar-like features and AdaBoo st algorithm for face detection, and principal component anal ysis for identification. A new method is proposed to estimate the optimal weighting parameter based on probability densi ty function estimation under Gaussian assumptions. Simulati ons indicate that the proposed method obtains slightly better r esults than the frequently-used empirical method of optimising on held-out training data.
A Reliability and Validity Investigation of the Mathematics Attribution Scale

The Mathematics Attribution Scale-Algebra (MAS) was designed to assess attributions to ability, effort, task, and environment for success and failure in algebra. The present study examined the reliability and-validity of the MAS with high ability high school students. The results of this study present a complicated picture of the psychometric properties of the MAS.
Search Result Clustering Using Label Language Model

Search results clustering helps users to browse the search results and locate what they are looking for. In the search result clustering, the label selection which annotates a meaningful phrase for each cluster becomes the most fundamental issue. In this paper, we present a new method of using the language modeling approach over Dmoz for label selection, namely label language model. Experimental results show that our method is helpful to obtain meaningful clustering labels of search results.
II. Yeast sequencing reports. The two genes encoding yeast ribosomal protein S8 reside on different chromosomes, and are closely linked to the hsp70 stress protein genes SSA3 and SSA4

A 7·4 kb segment of chromosome II was sequenced and analysed. This segment is part of the 25 kb insert of cosmid clone α1004. 10 which is located on the left arm of chromosome II. Sequence analysis revealed four open reading frames (ORFs), of which two had been characterized previously (SSA3, AAR2) and one was not identified. The other ORF was precisely 600 bp long and the deduced protein sequence predicted a very basic protein (pI=11·1; molecular weight=22·5 kDa). Evidence was found that the ORF is the S40 ribosomal protein gene (RPG) S8. Consensus splice signals were found in the 5′ leader sequence and also potential RPG‐specific sequences. Chromoblot analysis revealed a second copy of the S8 RPG on chromosome IV or VIII. This copy is also closely linked to an hsp70 protein gene, SSA4. The sequence has been deposited in the EMBL data library under accession number Z26879.
Cancer Classiﬁcation Using Mass Spectrometry-based Proteomics Data

This document presents data analysis similar to Wang (2011) using R pack-age bst . Serum samples were collected from 77 benign prostate hyperplasia (BPH), 84 early stage prostate cancer, 83 late stage prostate cancer and 82 age-matched healthy men (HM). Peak detection and alignment were based on surface-enhanced laser desorption/ionization (SELDI) mass spectrometry protein proﬁles. The data have 779 peaks (predictors) for each sample.
Application of Redecision Therapy in Executive Coaching Workshops: Part 2 - A Qualitative Exploration of Participants’ Changes

This is the second paper of three and describes an investigation into the way that executive coaching as a growing field of organisational development can be based on transactional analysis theory and methods. Twelve participants who had attended a coaching workshop based on Goulding & Goulding’s (1979) redecision therapy approach completed a follow-up Change Questionnaire adapted by the first author from material by Elliott et al (2001) and responses were analysed using thematic analysis (Braun & Clarke 2006). Participants reported experiencing a wide range of personal growth experiences, positive interpersonal change and growth in their business, managerial and leadership skills as a result of participating in the work-shops. Limitations are described including the possible impact of the transferential artefact of wanting to please the workshop facilitator. The thematic analysis findings suggest that such an approach can provide an effective framework for executive coaching workshops.
Specifying the Environments around GRB, Explaining the Fe line in the X-Ray Afterglow of GRB000214

We present a model explaining the Fe K alpha line and the continuum in the afterglow of GRB000214. We pose the importance to seek the physically natural environment around GRB000214. For the reproduction of the observation, we need the ring-like remnant around the progenitor like that of SN 1987A produced by the mass-loss of the progenitor and the fireball spread over in every directions. The observation of GRB000214, in which the continuum power law spectrum decreased faster than the line, motivated us to consider the two independent systems for the line emission and the continuum spectrum. At first, the continuum spectrum can be fitted by the afterglow emission of the fireball pointing toward the observer which does not collide with the ring because the emission of GRB and the afterglow are highly collimated to the observer by the relativistic beaming effect. Secondly, the line can be fitted by the fluorescence of the Fe atoms in the ring illuminated by the X-ray afterglow. The significance of this study is that our model may constrain strongly the GRB model. Although the Supranova model assumes the extreme-ring-like remnant produced by the usual supernova explosion, this may not be probable. It is because the supernova remnants are known to be shell-like. The model also assumes two steps of explosions, on the other hand, we need only one explosion of the progenitor. In this sense, our scenario is more natural. Moreover, in the numerical simulations of Hypernova, the jet of the opening angle of only 1 degree is generated. In our model, the fireball which spreads over in every directions reconciles with the observation of 1 percent of the polarization in the observation of SN1998bw which showed the explosion might not be so collimated.
QSAR study of some 5-methyl/trifluoromethoxy- 1H-indole-2,3-dione-3-thiosemicarbazone derivatives as anti-tubercular agents

In the present study, quantitative relationships between molecular structure and anti-tubercular activity of some 5-methyl/trifluoromethoxy-1H-indole-2,3-dione-3-thiosemicarbazone derivatives were discovered. The detailed application of an efficient linear method and principal component regression (PCR) for the evaluation of quantitative structure activity relationships of the studied compounds is demonstrated. Components produced by principal component analysis were used as the input for a linear model development. Results indicate a linear relationship between the principal components obtained from molecular descriptors and the inhibitory activity of this set of molecules. The maximum variance in the activity of the molecules in PCR method was 73%. The performance of the developed model was tested by several validation methods.
The Brain's concepts: the role of the Sensory-motor system in conceptual knowledge

Concepts are the elementary units of reason and linguistic meaning. They are conventional and relatively stable. As such, they must somehow be the result of neural activity in the brain. The questions are: Where? and How? A common philosophical position is that all concepts—even concepts about action and perception—are symbolic and abstract, and therefore must be implemented outside the brain's sensory-motor system. We will argue against this position using (1) neuroscientific evidence; (2) results from neural computation; and (3) results about the nature of concepts from cognitive linguistics. We will propose that the sensory-motor system has the right kind of structure to characterise both sensory-motor and more abstract concepts. Central to this picture are the neural theory of language and the theory of cogs, according to which, brain structures in the sensory-motor regions are exploited to characterise the so-called “abstract” concepts that constitute the meanings of grammatical constructions and general inference patterns.
An Efficient Transport Protocol for delivery of Multimedia An Efficient Transport Protocol for delivery of Multimedia Content in Wireless Grids

A grid computing system is designed for solving complicated scientific and commercial problems effectively, whereas mobile computing is a traditional distributed system having computing capability with mobility and adopting wireless communications. Media and Entertainment fields can take advantage from both paradigms by applying its usage in gaming applications and multimedia data management. Multimedia data has to be stored and retrieved in an efficient and effective manner to put it in use. In this paper, we proposed an application layer protocol for delivery of multimedia data in wireless girds i.e. multimedia grid protocol (MMGP). To make streaming efficient a new video compression algorithm called dWave is designed and embedded in the proposed protocol. This protocol will provide faster, reliable access and render an imperceptible QoS in delivering multimedia in wireless grid environment and tackles the challenging issues such as i) intermittent connectivity, ii) device heterogeneity, iii) weak security and iv) device mobility. Keywords: Grid Computing, Communication Protocol, Wireless Networks, Multimedia, Video Compression, Wavelet.
Labor Adjustment in an Evolving Marketplace An Empirical Investigation

This paper is about the process of employment adjustment. It studies adjustment costs and their impact on employment and labor demand. It estimates econometrically parameters of labor adjustment based on ASI industry data from 1973 to 1997. Specifically effects of the job security regime in India on employment are estimated while accounting for the concurrent impact of product markets’ liberalization. It establishes that adjustment is slow, a significant decline in both average employment and speed of adjustment is evident after the job security regime in India is restricted, and competition mitigates only some of the adverse impact of adjustment costs. These analyses can be better conducted using a panel dataset based on the unit level data of the ASI.
Grammatical Errors in the Speech of Pre-School Children

The study of their grammatical errors was approached from two angles: improvement in elimination of error with increase in age, and the particular types of errors most frequently found. With these aims in mind, all errors in the material were carefully segregated. Tabulation was made according to age and according to type of error. An index of the amount of error in each child's conversation was calcu-
Growth Rate-Dependent Accumulation of RNA from Plasmid-Borne rRNA Operons in Escherichia coli

ABSTRACT Inadequate regulation of the expression of additional plasmid-borne rRNA operons in Escherichia coli was exaggerated at slow growth rates, resulting in increases of approximately 100% for RNA concentration and 33% for doubling time. These observations are consistent with the hypothesis that multiple rRNA operons constitute a metabolic burden at slow growth rates.
Genomic copy number variation and its potential role in lipoprotein and metabolic phenotypes

Purpose of review This review examines the role of copy number variation in the human genome as a newly recognized determinant of lipoprotein and metabolic phenotypes. Recent findings Much of the recent progress defining the molecular basis of lipoprotein disorders has been the result of studying genomic DNA at the single nucleotide level, for instance with nucleotide sequence analysis or genotyping to detect single nucleotide polymorphisms. Focus on single nucleotides, however, fails to capture the complete spectrum of potential genetic variability. Recent genome-wide mapping studies have demonstrated the surprising ubiquity of large-scale copy number variations in apparently healthy people, adding to the complexity of the ‘normal’ genome, but also emphasizing this form of genetic variation as a potential disease mechanism. The application of this understanding to the genetics of lipoprotein disorders has been rapid. For instance, the use of novel techniques to detect copy number variations, such as multiplex ligation-dependent probe amplification, has revealed many additional causative mutations in the low-density lipoprotein receptor gene in patients with familial hypercholesterolemia. Summary Copy number variations thus represent a new level of genomic variation that is both an important mechanism of monogenic lipoprotein disorders and a potential contributor to common complex lipoprotein and metabolic phenotypes in the general population.
Mixed-Band Wavelet-Chaos-Neural Network Methodology for Epilepsy and Epileptic Seizure Detection

A novel wavelet-chaos-neural network methodology is presented for classification of electroencephalograms (EEGs) into healthy, ictal, and interictal EEGs. Wavelet analysis is used to decompose the EEG into delta, theta, alpha, beta, and gamma sub-bands. Three parameters are employed for EEG representation: standard deviation (quantifying the signal variance), correlation dimension, and largest Lyapunov exponent (quantifying the non-linear chaotic dynamics of the signal). The classification accuracies of the following techniques are compared: 1) unsupervised-means clustering; 2) linear and quadratic discriminant analysis; 3) radial basis function neural network; 4) Levenberg-Marquardt backpropagation neural network (LMBPNN). To reduce the computing time and output analysis, the research was performed in two phases: band-specific analysis and mixed-band analysis. In phase two, over 500 different combinations of mixed-band feature spaces consisting of promising parameters from phase one of the research were investigated. It is concluded that all three key components of the wavelet-chaos-neural network methodology are important for improving the EEG classification accuracy. Judicious combinations of parameters and classifiers are needed to accurately discriminate between the three types of EEGs. It was discovered that a particular mixed-band feature space consisting of nine parameters and LMBPNN result in the highest classification accuracy, a high value of 96.7%.
Presynaptic NMDA Receptor Mechanisms for Enhancing Spontaneous Neurotransmitter Release

NMDA receptors (NMDARs) are required for experience-driven plasticity during formative periods of brain development and are critical for neurotransmission throughout postnatal life. Most NMDAR functions have been ascribed to postsynaptic sites of action, but there is now an appreciation that presynaptic NMDARs (preNMDARs) can modulate neurotransmitter release in many brain regions, including the neocortex. Despite these advances, the cellular mechanisms by which preNMDARs can affect neurotransmitter release are largely unknown. Here we interrogated preNMDAR functions pharmacologically to determine how these receptors promote spontaneous neurotransmitter release in mouse primary visual cortex. Our results provide three new insights into the mechanisms by which preNMDARs can function. First, preNMDARs can enhance spontaneous neurotransmitter release tonically with minimal extracellular Ca2+ or with major sources of intracellular Ca2+ blocked. Second, lowering extracellular Na+ levels reduces the contribution of preNMDARs to spontaneous transmitter release significantly. Third, preNMDAR enhance transmitter release in part through protein kinase C signaling. These data demonstrate that preNMDARs can act through novel pathways to promote neurotransmitter release in the absence of action potentials.
Collaborative peer lyric writing during music therapy training: a tool for facilitating students' reflections about clinical practicum experiences

Self-reflection is integral to effective clinical practice and yet is a skill that many intelligent students struggle to develop. This paper reports on the findings of a pilot study where students shared both positive and challenging experiences with each other and co-wrote songs that captured their experiences. Four students attending clinical practicum engaged in collaborative songwriting experiences with peers from both the same and different universities in the US and Australia. These experiences utilized both face to face and online environments utilizing Skype communication software. Lyrics were reviewed by the researchers and were compared with themes and categories about music therapy clinical training found in the literature. Findings suggest that collaborative songwriting provides opportunities for students to engage in experiences of reflection with other peers.
Industrial experiences with automated regression testing of a legacy database application

This paper presents a practical approach and tool (DART) for functional black-box regression testing of complex legacy database applications. Such applications are important to many organizations, but are often difficult to change and consequently prone to regression faults during maintenance. They also tend to be built without particular considerations for testability and can be hard to control and observe. We have therefore devised a practical solution for functional regression testing that captures the changes in database state (due to data manipulations) during the execution of a system under test. The differences in changed database states between consecutive executions of the system under test, on different system versions, can help identify potential regression faults. In order to make the regression test approach scalable for large, complex database applications, classification tree models are used to prioritize test cases. The test case prioritization can be applied to reduce test execution costs and analysis effort. We report on how DART was applied and evaluated on business critical batch jobs in a legacy database application in an industrial setting, namely the Norwegian Tax Accounting System (SOFIE) at the Norwegian Tax Department (NTD). DART has shown promising fault detection capabilities and cost-effectiveness and has contributed to identify many critical regression faults for the past eight releases of SOFIE.
Towards a Study of Meta-Predicate Semantics

We describe and compare design choices for meta-predicate semantics, as found in representative Prolog module systems and in Logtalk. We look at the consequences of these design choices from a pragmatic perspective, discussing explicit qualification semantics, computational reflection support, expressiveness of meta-predicate declarations, safety of meta-predicate definitions, portability of meta-predicate definitions, and meta-predicate performance. Our aim is to provide useful insight for debating meta-predicate semantics and portability issues based on actual implementations and common usage patterns.
Spectral clustering to model deformations for fast multimodal prostate registration

This paper proposes a method to learn deformation parameters off-line for fast multimodal registration of ultrasound and magnetic resonance prostate images during ultrasound guided needle biopsy. The registration method involves spectral clustering of the deformation parameters obtained from a spline-based nonlinear diffeomorphism between training magnetic resonance and ultrasound prostate images. The deformation models built from the principal eigen-modes of the clusters are then applied on a test magnetic resonance image to register with the test ultrasound prostate image. The deformation model with the least registration error is finally chosen as the optimal model for deformable registration. The rationale behind modeling deformations is to achieve fast multimodal registration of prostate images while maintaining registration accuracies which is otherwise computationally expensive. The method is validated for 25 patients each with a pair of corresponding magnetic resonance and ultrasound images in a leave-one-out validation framework. The average registration accuracies i.e. Dice similarity coefficient of 0.927 ± 0.025, 95% Hausdorff distance of 5.14 ± 3.67 mm and target registration error of 2.44 ± 1.17 mm are obtained by our method with a speed-up in computation time by 98% when compared to Mitra et al. [7].
Multidimensional Classroom Support to Inclusive Education Teachers in Beijing, China

Classroom support plays a salient role in successful inclusive education, hence it has been widely debated in the literature. Much extant work has only focused on a particular aspect of classroom support. A comprehensive, systematic discussion of classroom support is sporadic in the literature. Relevant research concerning the Chinese context is even more limited. To address this gap, our study developed and validated a multidimensional classroom support model conducive to teachers’ inclusive education practices. Data were drawn from our large-scale survey with inclusive education teachers in Beijing. Further analyses were conducted to compare different dimensions within the classroom support model. Drawing insights from the results, we provide some recommendations for practice and research.
60 GHz planar filters and transmission lines characterization in 0.25µm BiCMOS technology

In this article, three main aspects of passive millimeter-wave integrated filter realization are exposed. Firstly, the importance of the transmission line choice is discussed by comparing microstrip and coplanar waveguide (CPW) in BiCMOS 0. 25µm technology. 50-Ω transmission lines exhibit similar losses around 0.6 dB/mm at 60 GHz. Secondly, two filter topologies, a dual-behavior resonator based filter and a dualmode ring based filter, are compared in terms of insertion losses, surface area and out-of-band rejection. They are both designed using microstrip lines and exhibit a similar 3dB fractional bandwidth (FBW3dB) around 12% with a 60 GHz center frequency. Finally, a miniaturization method is presented using Metal-Insulator-Metal (MIM) capacitive loading. A loaded filter is then realized and characterized. Similar electrical performance are demonstrated with a size reduction factor of 2.3.
Sample-efficient Deep Reinforcement Learning for Dialog Control

Representing a dialog policy as a recurrent neural network (RNN) is attractive because it handles partial observability, infers a latent representation of state, and can be optimized with supervised learning (SL) or reinforcement learning (RL). For RL, a policy gradient approach is natural, but is sample inefficient. In this paper, we present 3 methods for reducing the number of dialogs required to optimize an RNN-based dialog policy with RL. The key idea is to maintain a second RNN which predicts the value of the current policy, and to apply experience replay to both networks. On two tasks, these methods reduce the number of dialogs/episodes required by about a third, vs. standard policy gradient methods.
Invariantes Radiométricos en Espacios de Representación del Color Color

9 Color seems to be an unalienable property of objects. 9 Evolution, such that a species adapts to its environment, has driven the use of color by perception. 9 Human perception actively assigns colors to an observed scene. 9 Objects in the world respond to daylight by reflecting differently part of the incoming light spectrum. 9 Color is one of the main cues for segmenting objects in a scene.