Miracle-dz/UniFAR-FTUs huggingface dataset:
A phonetic similarity based noisy channel approach to ASR hypothesis re-ranking and error detection

We present a new method to augment the correct transcript from automatic speech recognition (ASR) output containing multiple hypotheses. The error-prone ASR process is taken as black box and modeled as a noisy channel on phoneme level. The probabilities of the individual phoneme errors are assigned according to phonetic confusability. We score potential candidate hypotheses by their posterior probability of being the channel input given the competing ASR hypotheses as observed output. The resulting scores provide useful information not included in traditional confidence measures. We investigated the usefulness of the method for rescoring, re-ranking and word error detection. The method alone is not powerful enough to improve the recognition results, but by employing a decision tree classifier it is possible to isolate cases where the method works very well. Our results show that the combination with other knowledge sources and postprocessing techniques can lead to promising improvements.
Modulator Domain Adaptive Gain Equalizer for Speech Enhancement

This paper presents a speech enhancement method for personal communication where the input signal is divided into a number of sub bands that are individually and adaptively weighted in time domain according to a short term SNR estimate in each sub band at every time an enhanced noise reduction method. The input signal is divided into a number of sub bands that are individually weighted in the time domain according to the short time signal to noise ratio estimate (SNR) in each sub band. Instead of focusing on suppression of the noise the method focuses on speech enhancement algorithms. The method has proven to be advantageous since it offers low complexity, low delay and low distortion. There working of AGE in modulation frequency domain with the use of a convex optimization demodulation technique. The performance of the modified AGE is compared with the traditional AGE and another modulation frequency domain AGE based on demodulation using the spectral center-of-gravity used performance measures are Signal to Noise Ratio Improvement (SNRI).
HUBUNGAN ANTARA RELIGIUSITAS DENGAN MORALITAS PADA REMAJA DI MADRASAH ALIYAH (MA)

Abstract Adolescents who exhibit behaviors according to the prevailing norms and values, the teen said to have morality. While teens who show behavior contrary to the prevailing norms and values, then the teenager is said to commit immoral acts. The results of previous studies, concluded that, individuals need a controller in thinking, behaving , acting , namely religion or religiosity. Religiosity can affect every aspect of an individual’s life, both psychologically and physically. This study aims to examine the relationship between religiosity and morality in adolescents at Madrasah Aliyah. This type of research uses a quantitative approach to the type of correlational research. The population numbered 93 students of Madrasah Aliyah 2012- 2013 school year. The sampling technique using simple random technique, the sample in the study totaled 63 students. Analyzed using product moment. The results of this study showed a correlation coefficient ( r) of 0.775 with a significance ( p ) of 0.000, where p < 0.01. Based on data analysis, the conclusions drawn from this study is that there was a significant relationship between religiosity and morality teen Madrasah Aliyah Boarding Schools in the city of Palembang. Keywords : Morality, Religiosity.
The Risk for Insulin Resistance according to the Degree of Non-Alcoholic Fatty Liver Disease in Korean Men

Insulin resistance (IR) plays a significant role in the development and progression of non-alcoholic fatty liver disease (NAFLD). However, the natural course of insulin sensitivity under NAFLD remained unclear. Accordingly, this study was designed to investigate the effect of NAFLD on insulin resistance. A total of 20,628 Korean men without homeostasis model assessment of insulin resistance (HOMA-IR < 2.7) were followed-up for 5 years. They were serially checked for HOMA-IR to monitor the development of IR (HOMA-IR ≥ 2.7). The incidence rate of IR increased according to the degree of NAFLD (normal: 11.6%, mild: 28.8%, moderate to severe: 40.5%, P < 0.001). Cox proportional hazards model showed that HRs (95% CI) for IR increased proportionally to the degree of NAFLD (mild: 1.19 [1.02–1.39], moderate to severe: 1.32 [1.08–1.57]). IR was more potentially associated with the more progressive NAFLD than normal and milder state. In addition, NAFLD was the independent risk factor of the development of IR. These results suggest the potential availability of NAFLD as a predictor of IR.
Evaluation of Antioxidant and Antiangiogenic Properties of Caesalpinia Echinata Extracts

Natural products contain important combinations of ingredients, which may to some extent help to modulate the effects produced by oxidation substrates in biological systems. It is known that substances capable of modulating the action of these oxidants on tissue may be important allies in the control of neovascularization in pathological processes. The aim of this study was to evaluate the antioxidant and antiangiogenic properties of an ethanol extract of Caesalpinia echinata. The evaluation of antioxidant properties was tested using two methods (DPPH inhibition and sequestration of nitric oxide). The antiangiogenic properties were evaluated using the inflammatory angiogenesis model in the corneas of rats. The extract of C. echinata demonstrated a high capacity to inhibit free radicals, with IC50 equal to 42.404 µg/mL for the DPPH test and 234.2 µg/mL for nitric oxide. Moreover, it showed itself capable of inhibiting the inflammatory angiogenic response by 77.49%. These data suggest that biochemical components belonging to the extract of C. echinata interfere in mechanisms that control the angiogenic process, mediated by substrates belonging to the arachidonic acid cascade, although the data described above also suggest that the NO buffer may contribute to some extent to the reduction in the angiogenic response.
The skeleton in the cognitive map: a computational hypothesis

Experts seem to find routes in a complex environment by finding a connection from the starting place to a subset of major paths(cid:151)the (cid:147)skeleton(cid:148)(cid:151)then moving within the skeleton to the neighborhood of the destination, making a final connection to the destination. We present a computational hypothesis to account for the skeleton as an emergent phenomenon, arising from the interaction of three factors. (1) The topological map is represented as a bipartite graph of places and paths, where a path is an extended one-dimensional description of an ordered set of places. (2) Travel through the environment allows the traveler to incrementally accumulate topological relationships, including the relation of a place to a path serving as a dividing boundary separating two regions. (3) A bounding path is often a natural subgoal during way-finding search, meaning that paths rich in boundary relations are likely to appear in routes, which means they are likely to acquire more boundary relations. This posi-tive-feedback loop leads to an oligarchy of paths rich in boundary relations. We propose computational and empirical tests for this hypothesis.
Delay Differential Analysis of Electroencephalographic Data

Abstract We propose a time-domain approach to detect frequencies, frequency couplings, and phases using nonlinear correlation functions. For frequency analysis, this approach is a multivariate extension of discrete Fourier transform, and for higher-order spectra, it is a linear and multivariate alternative to multidimensional fast Fourier transform of multidimensional correlations. This method can be applied to short and sparse time series and can be extended to cross-trial and cross-channel spectra (CTS) for electroencephalography data where multiple short data segments from multiple trials of the same experiment are available. There are two versions of CTS. The first one assumes some phase coherency across the trials, while the second one is independent of phase coherency. We demonstrate that the phase-dependent version is more consistent with event-related spectral perturbation analysis and traditional Morlet wavelet analysis. We show that CTS can be applied to short data windows and yields higher temporal resolution than traditional Morlet wavelet analysis. Furthermore, the CTS can be used to reconstruct the event-related potential using all linear components of the CTS.
Fairness and classifications

The growing trend in computer systems towards using scheduling policies that prioritize jobs with small service requirements has resulted in a new focus on the fairness of such policies. In particular, researchers have been interested in whether prioritizing small job sizes results in large jobs being treated "unfairly. " However, fairness is an amorphous concept and thus difficult to define and study. This article provides a short survey of recent work in this area.
Two Essential DNA Polymerases at the Bacterial Replication Fork

DNA replication in bacteria is carried out by a multiprotein complex, which is thought to contain only one essential DNA polymerase, specified by the dnaE gene inEscherichia coli and the polC gene inBacillus subtilis. Bacillus subtilis genome analysis has revealed another DNA polymerase gene,dnaEBS , which is homologous to dnaE. We show that, in B. subtilis, dnaEBS is essential for cell viability and for the elongation step of DNA replication, as is polC, and we conclude that there are two different essential DNA polymerases at the replication fork of B. subtilis, as was previously observed in eukaryotes.dnaEBS appears to be involved in the synthesis of the lagging DNA strand and to be associated with the replication factory, which suggests that two different polymerases carry out synthesis of the two DNA strands in B. subtilis and in many other bacteria that contain both polC and dnaEgenes.
Transnational Urbanism in the Reform-era Chinese City: Landscapes from Shenzhen

While the conventions of area studies scholarship have historically limited landscape analysis in China, the globalisation of scholarship and the new built environments of the reform-era Chinese city invite contemporary assessment. In Shenzhen, China's leading Special Economic Zone, the planning and construction of a new city centre complex are designed to symbolise the city's transformation from a manufacturing zone to a 'world city' and to function as its service-sector core. This landscape analysis applies the perspective of transnational urbanism to assess how the effort to instantiate 'world city' status in the built environment works through plans, ideologies and representations of domestic and transnational elites to establish legitimacy. The continuing strong role of the state in China makes the production of a new city centre a state-dominated enterprise; contesting meanings of these new landscapes takes place indirectly and symbolically in the arena of the state's spiritual civilisation campaign.
A Local Search Approach to Modelling and Solving Interval Algebra Problems

Local search techniques have attracted considerable interest in the artificial intelligence community since the development of GSAT and the min-conflicts heuristic for solving propositional satisfiability (SAT) problems and binary constraint satisfaction problems (CSPs) respectively. Newer techniques, such as the discrete Langrangian method (DLM), have significantly improved on GSAT and can also be applied to general constraint satisfaction and optimization. However, local search has yet to be successfully employed in solving temporal constraint satisfaction problems (TCSPs). This paper argues that current formalisms for representing TCSPs are inappropriate for a local search approach, and proposes an alternative CSP-based end-point ordering model for temporal reasoning. The paper looks at modelling and solving problems formulated using Allen's interval algebra (IA) and proposes a new constraint weighting algorithm derived from DLM. Using a set of randomly generated IA problems, it is shown that local search outperforms existing consistency-enforcing algorithms on those problems that the existing techniques find most difficult.
Compressing , Streaming , and Processing of Large Polygon Meshes

This document proposes a set of deliverables for which—upon completion—I hope to be given the PhD degree. In the next section I motivate why I should spend four years of my life and several ten-thousand dollars of my supervisor’s grant money into the development of various algorithms that operate on polygon meshes. In Section 2 I detail the research contributions that I aim to achieve in the order they lead from one to the next. At the same time I reference the research literature that I will familiarize myself in the course of carrying out the proposed research. In Section 3 I list completed milestones and estimated completion dates for missing milestones. In the last section I anticipate the immediate and the potential impact of my work on the field mesh processing.
Extracellular Loops 2 and 4 of GLYT2 Are Required for N-Arachidonylglycine Inhibition of Glycine Transport*

Concentrations of extracellular glycine in the central nervous system are regulated by Na+/Cl−-dependent glycine transporters, GLYT1 and GLYT2. N-Arachidonylglycine (NAGly) is an endogenous inhibitor of GLYT2 with little or no effect on GLYT1 and is analgesic in rat models of neuropathic and inflammatory pain. Understanding the molecular basis of NAGly interactions with GLYT2 may allow for the development of novel therapeutics. In this study, chimeric transporters were used to determine the structural basis for differences in NAGly sensitivity between GLYT1 and GLYT2 and also the actions of a series of related N-arachidonyl amino acids. Extracellular loops 2 and 4 of GLYT2 are important in the selective inhibition of GLYT2 by NAGly and by the related compounds N-arachidonyl-γ-aminobutyric acid and N-arachidonyl-d-alanine, whereas only the extracellular loop 4 of GLYT2 is required for N-arachidonyl-l-alanine inhibition of transport. These observations suggest that the structure of the head group of these compounds is important in determining how they interact with extracellular loops 2 and 4 of GLYT2. Site-directed mutagenesis of GLYT2 EL4 residues was used to identify the key residues Arg531, Lys532, and Ile545 that contribute to the differences in NAGly sensitivity.
Cognitive neuroscience of natural language use

1. Cognitive neuroscience of natural language use: introduction Roel M. Willems 2. fMRI methods for studying the neurobiology of language under naturalistic conditions Michael Andric and Steven L. Small 3. Why study connected speech production? Sharon Ash and Murray Grossman 4. Situation models in naturalistic comprehension Christopher A. Kurby and Jeffrey M. Zacks 5. Language comprehension in rich non-linguistic contexts: combining eye tracking and event related brain potentials Pia Knoeferle 6. The NOLB model. A model of the natural organization of language and the brain Jeremy I. Skipper 7. Towards a neurocognitive poetics model of literary reading Arthur M. Jacobs 8. Putting Broca's region into context - fMRI evidence for a role in predictive language processing Line Burholt Kristensen and Mikkel Wallentin 9. Towards a multi-brain perspective on communication in dialogue Anna K. Kuhlen, Carsten Allefeld, Silke Anders and John-Dylan Haynes 10. On the generation of shared symbols Arjen Stolk, Mark Blokpoel, Iris van Rooij and Ivan Toni 11. What are naturalistic comprehension paradigms teaching us about language? Uri Hasson and Giovanna Egidi.
Quantitative Analysis of Gamma‐Hydroxybutyrate at Endogenous Concentrations in Hair using Liquid Chromatography Tandem Mass Spectrometry

Abstract: A method capable of quantifying endogenous concentrations of gamma‐hydroxybutyrate (GHB) in human head hair was developed and validated using liquid chromatography/mass spectrometry/mass spectrometry (LC/MS/MS). Hair was digested under alkaline conditions, and GHB was isolated using liquid–liquid extraction. LC/MS/MS was performed using atmospheric pressure chemical ionization in the negative mode, multiple reaction monitoring, and deuterated internal standard (GHB‐D6). Linearity was observed between 0.1 and 100 ng/mg GHB (R2 = 1.000). The limits of detection and quantitation in human hair were 0.2 and 0.4 ng/mg, respectively. Accuracy at 2 ng/mg and 10 ng/mg was determined to be 97% and 94%, and intra‐assay CVs at these concentrations were 5.2% and 7.4% (n = 4). Beta‐hydroxybutyrate (BHB), alpha‐hydroxybutyrate, gamma‐butyrolactone, and 1,4‐butanediol did not produce an interference, and there was negligible ion suppression or enhancement from the matrix.
Evaluation of a Stream of Top-N Selection Queries in Relational Databases

In relational databases and their applications, an important issue is to evaluate a stream of top-N selection queries. For this issue, we propose a new method with learning-based strategies and region clustering techniques in this paper. This method uses a knowledge base to store related information of some past queries, groups the search regions of the past queries into larger regions and retrieves the tuples from the larger regions. To answer a newly submitted query, our method tries to obtain most results from the previously retrieved tuples that are still in main memory. Thus, this method seeks to minimize the response time by reducing the search regions or avoiding accesses to the underlying databases. Extensive experiments are carried out to measure the performance of this new strategy and the results indicate that it is significantly better than the naive method for both low-dimensional and high-dimensional data.
On the impact of passive voice requirements on domain modelling

Context: The requirements specification is a central artefact in the software engineering (SE) process, and its quality (might) influence downstream activities like implementation or testing. One quality defect that is often mentioned in standards is the use of passive voice. However, the consequences of this defect are still unclear. Goal: We need to understand whether the use of passive voice in requirements has an influence on other activities in SE. In this work we focus on domain modelling. Method: We designed an experiment, in which we ask students to draw a domain model from a given set of requirements written in active or passive voice. We compared the completeness of the resulting domain model by counting the number of missing actors, domain objects and their associations with respect to a specified solution. Results: While we could not see a difference in the number of missing actors and objects, participants which received passive sentences missed almost twice the associations. Conclusion: Our experiment indicates that, against common knowledge, actors and objects in a requirement can often be understood from the context. However, the study also shows that passive sentences complicate understanding how certain domain concepts are interconnected.
Fast & Confident Probabilistic Categorization

We describe NRC's submission to the Anomaly Detection/Text Mining competition organised at the Text Mining Workshop 2007. This submission relies on a straightforward implementation of the probabilistic categoriser described in (Gaussier et al., ECIR'02). This categoriser is adapted to handle multiple labelling and a piecewise-linear confidence estimation layer is added to provide an estimate of the labelling confidence. This technique achieves a score of 1.689 on the test data.
Face Recognition Algorithms Based on Orthogonal Sparse Preserving Projections of Kernel

According to the error approximation problem the sparse preserving projections (SPP) reconstruct the original sample. This paper proposes the algorithms based on orthogonal sparse preserving projections of kernel. In order to get sparse representation coefficients that contain more identification information by kernel method, it mapped samples to highdimensional feature space to. Then, reconstructing sparse coefficient of kernel sparse representation increase the similar non neighbor sample weight, and reduce heterogeneous neighbor sample weight. Finally, the whole orthogonal constraint transformation improve the ability of sparse retain sample. The algorithm experiments were carried out on the YALE_B and ORL face database, and the recognition rate reached 96.3%, and the results verify the effectiveness and robustness of the algorithm.
e-Epidemic Model On Highly Infectious Nodes in the Computer Network

Abstract In this paper, we have developed a compartmental e-Epidemic SIJR (Susceptible-Infectious-Highly InfectiousRecovered) model of viruses in a computer network with natural death (that is, crashing of nodes due to the reason other than the attack of viruses). The local asymptotically stability of the system has been discussed using the Jacobian and the explicit formula for basic reproduction number has been derived. Numerical methods and MATLAB are employed to solve and simulate the system of equations developed and analysis of the model gives remarkable exposure. Key-words e-Epidemic Model; Basic Reproduction Number; Asymptotically Stability; Virus
Hierarchical Probabilistic Matrix Factorization with Network Topology for Multi-relational Social Network

Link prediction in multi-relational social networks has attracted much attention. For instance, we may care the chance of two users being friends based on their contacts of other patterns, e.g., SMS and phone calls. In previous work, matrix factorization models are typically applied in single-relational networks; however, two challenges arise to extend it into multi-relational networks. First, the interaction of different relation types is hard to be captured. The second is the cold start problem, as the prediction of new entities in multi-relational networks becomes even more challenging. In this article we propose a novel method called Hierarchical Probabilistic Matrix Factorization with Network Topology (HPMFNT). Our model exploits the network topology by extending the Katz index into multi-relational settings, which could efficiently model the multidimensional interplay via the auxiliary information from other relationships. We also utilize the extended Katz index along with entitiy attributes to solve the cold-start problem. Experiments on two real world datasets have shown that our model outperforms the state-of-the-art with a significant margin.