Miracle-dz/UniFAR-FTUs huggingface dataset:
High-level speaker verification via articulatory-feature based sequence kernels and SVM

Articulatory-feature based pronunciation models (AFCPMs) are capable of capturing the pronunciation variations among different speakers and are good for high-level speaker recognition. However, the likelihood-ratio scoring method of AFPCMs is based on a decision boundary created by training the target speaker model and universal background model (UBM) separately. Therefore, the method does not fully utilize the discriminative information available in the training data. To fully harness the discriminative information, this paper proposes training a support vector machine (SVM) for computing the verification scores. More precisely, the models of target speakers, individual background speakers, and claimants are converted to AF-supervectors, which form the inputs to an AF-based kernel of the SVM for computing verification scores. Results show that the proposed AF-kernel scoring is complementary to likelihood-ratio scoring, leading to better performance when the two scoring methods are combined. Further performance enhancement was also observed when the AF scores were combined with acoustic scores derived from a GMM-UBM system.
Does the Sole Description of a Tax Authority Affect Tax Evasion? - The Impact of Described Coercive and Legitimate Power

Following the classic economic model of tax evasion, taxpayers base their tax decisions on economic determinants, like fine rate and audit probability. Empirical findings on the relationship between economic key determinants and tax evasion are inconsistent and suggest that taxpayers may rather rely on their beliefs about tax authority’s power. Descriptions of the tax authority’s power may affect taxpayers’ beliefs and as such tax evasion. Experiment 1 investigates the impact of fines and beliefs regarding tax authority’s power on tax evasion. Experiments 2-4 are conducted to examine the effect of varying descriptions about a tax authority’s power on participants’ beliefs and respective tax evasion. It is investigated whether tax evasion is influenced by the description of an authority wielding coercive power (Experiment 2), legitimate power (Experiment 3), and coercive and legitimate power combined (Experiment 4). Further, it is examined whether a contrast of the description of power (low to high power; high to low power) impacts tax evasion (Experiments 2-4). Results show that the amount of fine does not impact tax payments, whereas participants’ beliefs regarding tax authority’s power significantly shape compliance decisions. Descriptions of high coercive power as well as high legitimate power affect beliefs about tax authority’s power and positively impact tax honesty. This effect still holds if both qualities of power are applied simultaneously. The contrast of descriptions has little impact on tax evasion. The current study indicates that descriptions of the tax authority, e.g., in information brochures and media reports, have more influence on beliefs and tax payments than information on fine rates. Methodically, these considerations become particularly important when descriptions or vignettes are used besides objective information.
Xor-trees for efficient anonymous multicast and reception

We examine the problem of efficient anonymous multicast and reception in general communication networks. We present algorithms that achieve anonymous communication, are protected against traffic analysis, and require O(1) amortized communication complexity on each link and low computational comlexity. The algorithms support sender anonymity, receiver(s) anonymity, or sender-receiver anonymity.
Pramanicin Analog Induces Apoptosis in Human Colon Cancer Cells: Critical Roles for Bcl-2, Bim, and p38 MAPK Signaling

Pramanicin (PMC) is an antifungal agent that was previously demonstrated to exhibit antiangiogenic and anticancer properties in a few in vitro studies. We initially screened a number of PMC analogs for their cytotoxic effects on HCT116 human colon cancer cells. PMC-A, the analog with the most potent antiproliferative effect was chosen to further interrogate the underlying mechanism of action. PMC-A led to apoptosis through activation of caspase-9 and -3. The apoptotic nature of cell death was confirmed by abrogation of cell death with pretreatment with specific caspase inhibitors. Stress-related MAPKs JNK and p38 were both activated concomittantly with the intrinsic apoptotic pathway. Moreover, pharmacological inhibition of p38 proved to attenuate the cell death induction while pretreatment with JNK inhibitor did not exhibit a protective effect. Resistance of Bax −/− cells and the protective nature of caspase-9 inhibition indicate that mitochondria play a central role in PMC-A induced apoptosis. Early post-exposure elevation of cellular Bim and Bax was followed by a marginal Bcl-2 depletion and Bid cleavage. Further analysis revealed that Bcl-2 downregulation occurs at the mRNA level and is critical to mediate PMC-A induced apoptosis, as ectopic Bcl-2 expression substantially spared the cells from death. Conversely, forced expression of Bim proved to significantly increase cell death. In addition, analyses of p53−/− cells demonstrated that Bcl-2/Bim/Bax modulation and MAPK activations take place independently of p53 expression. Taken together, p53-independent transcriptional Bcl-2 downregulation and p38 signaling appear to be the key modulatory events in PMC-A induced apoptosis.
$M$-Estimation for Discrete Data: Asymptotic Distribution Theory and Implications

Abstract : The asymptotic distribution of an M-estimator is studies when the underlying distribution is discrete. Asymptotic normality is shown to hold quite generally within the assumed parametric family. When the specification of the model is inexact, however, it is demonstrated that an M-estimator with a non-smooth score function, e.g. a Huber estimator, has a non-normal limiting distribution at certain distributions, resulting in unstable inference in the neighborhood of such distributions. Consequently, smooth score functions are proposed for discrete data. Keywords: Robust estimation; and Discrete parametric models. (Author)
Fusion of Skeletal and Silhouette-Based Features for Human Action Recognition with RGB-D Devices

Since the Microsoft Kinect has been released, the usage of marker-less body pose estimation has been enormously eased. Based on 3D skeletal pose information, complex human gestures and actions can be recognised in real time. However, due to errors in tracking or occlusions, the obtained information can be noisy. Since the RGB-D data is available, the 3D or 2D shape of the person can be used instead. However, depending on the viewpoint and the action to recognise, it might present a low discriminative value. In this paper, the combination of body pose estimation and 2D shape, in order to provide additional characteristic value, is considered so as to improve human action recognition. Using efficient feature extraction techniques, skeletal and silhouette-based features are obtained which are low dimensional and can be obtained in real time. These two features are then combined by means of feature fusion. The proposed approach is validated using a state-of-the-art learning method and the MSR Action3D dataset as benchmark. The obtained results show that the fused feature achieves to improve the recognition rates, outperforming state-of-the-art results in recognition rate and robustness.
Some scheduling techniques and an easily schedulable horizontal architecture for high performance scientific computing

Horizontal architectures are attractive for cost-effective, high performance scientific computing. They are, however, very difficult to schedule. Consequently, it is difficult to develop compilers that can generate efficient code for such architectures. The polycyclic architecture has been developed specifically to make the task of scheduling easy. As a result, it has been possible to develop a powerful scheduling algorithm that yields optimal and near-optimal schedules for iterative computations. This novel architecture and this scheduling algorithm are the topic of this paper.
Off-Target Cannabinoid Effects Mediated by GPR55

Given the vast therapeutic potential of the endocannabinoid system, the revelation of a novel cannabinoid-sensitive target was treated with great excitement. The orphan G-protein coupled receptor 55 (GPR55) was initially touted as a novel cannabinoid target in early industrial patent literature. Consequently, numerous studies have revealed GPR55 expression in a diverse array of cells and tissues, regulating various physiological and pathological processes. Although a confusing cannabinoid profile has prevented its classification as a cannabinoid receptor, the therapeutic potential of the receptor cannot be denied, with roles in cancer progression, bone resorption and analgesia. This commentary aims to summarize GPR55 expression data and speculate on potential therapeutic exploitation of this enigmatic orphan receptor.
Criteria for the assessment of pupils' compositions.

Summary An experiment was set up to discover whether ten‐ to eleven‐year‐old children would perform better on an imaginative writing task if given an aural stimulus consisting of an imaginary dialogue rather than the more commonly used written titles. The main energy of the investigation is focussed on the viability of different forms of assessing the quality of the resulting compositions. The most useful criteria from a large battery proved to be vocabulary, weighted index of modifying clauses, pre‐verb length and sequence.
Optimal meta search results clustering

By analogy with merging documents rankings, the outputs from multiple search results clustering algorithms can be combined into a single output. In this paper we study the feasibility of meta search results clustering, which has unique features compared to the general meta clustering problem. After showing that the combination of multiple search results clusterings is empirically justified, we cast meta clustering as an optimization problem of an objective function measuring the probabilistic concordance between the clustering combination and the single clusterings. We then show, using an easily computable upper bound on such a function, that a simple stochastic optimization algorithm delivers reasonable approximations of the optimal value very efficiently, and we also provide a method for labeling the generated clusters with the most agreed upon cluster labels. Optimal meta clustering with meta labeling is applied to three description-centric, state-of-the-art search results clustering algorithms. The performance improvement is demonstrated through a range of evaluation techniques (i.e., internal, classification-oriented, and information retrieval-oriented), using suitable test collections of search results with document-level relevance judgments per subtopic.
Anti‐sense‐mediated inhibition of expression of the novel striated tropomyosin isoform TPM1κ disrupts myofibril organization in embryonic axolotl hearts

Striated muscle tropomyosin (TM) is described as containing ten exons; 1a, 2b, 3, 4, 5, 6b, 7, 8, and 9a/b. Exon 9a/b has critical troponin binding domains and is found in striated muscle isoforms. We have recently discovered a smooth (exon 2a)/striated (exons 9a/b) isoform expressed in amphibian, avian, and mammalian hearts, designated as an isoform of the TPM1 gene (TPM1κ). TPM1κ expression was blocked in whole embryonic axolotl heart by transfection of exon‐specific anti‐sense oligonucleotide. Reverse transcriptase polymerase chain reaction (RT‐PCR) confirmed lower transcript expression of TPM1κ and in vitro analysis confirmed the specificity of the TPM1κ anti‐sense oligonucleotide. Altered expression of the novel TM isoform disrupted myofibril structure and function in embryonic hearts. © 2005 Wiley‐Liss, Inc.
Drivers of Twitter as a strategic communication tool for non-profit organizations

In view of the increased impact of social media, non-profit organizations (NPOs) should review their management model for stakeholder relationships. The purpose of this paper is to analyze the influence of factors on the use of Twitter by NPOs as a mechanism for disclosing information and dialogue with their stakeholders, and in particular: “donor dependence,” “fundraising expenses,” “organizational age,” “organizational size,” “online community size,” “network activity” and “board size. ”,A content analysis of Twitter use as a strategic communication tool was conducted and a multivariable linear regression analysis was performed. ,Smaller organizations and those with a larger online community are the most interested in implementing Twitter as a one or two-way communication strategy. Likewise, the NPOs with the highest degree of donor dependence strive most in the use of contents of Twitter as one-way communication mechanism. ,This study contributes to a better understanding of social media implementation in the NPO sector and advances the identification of the main causes that motivate NPOs to improve their accountability through social media. ,The paper’s subject is relatively innovative due to the scarce studies focussing on social media used by NPOs. In spite of the advantages offered by Twitter, few studies have specifically addressed NPOs’ current use of this platform, and fewer still have analyzed the factors that motivate them to use this tool.
Catch'Em All: Locating Multiple Diffusion Sources in Networks with Partial Observations

This paper studies the problem of locating multiple diffusion sources in networks with partial observations. We propose a new source localization algorithm, named Optimal-Jordan-Cover (OJC). The algorithm first extracts a subgraph using a candidate selection algorithm that selects source candidates based on the number of observed infected nodes in their neighborhoods. Then, in the extracted subgraph, OJC finds a set of nodes that "cover" all observed infected nodes with the minimum radius. The set of nodes is called the Jordan cover, and is regarded as the set of diffusion sources. Considering the heterogeneous susceptible-infected-recovered (SIR) diffusion in the Erdos-Renyi (ER) random graph, we prove that OJC can locate all sources with probability one asymptotically with partial observations. OJC is a polynomial-time algorithm in terms of network size. However, the computational complexity increases exponentially in m; the number of sources. We further propose a low-complexity heuristic based on the K-Means for approximating the Jordan cover, named Approximate-Jordan-Cover (AJC). Simulations on random graphs and real networks demonstrate that both AJC and OJC significantly outperform other heuristic algorithms.
Analysis of intracranial aneurysm wall motion and its effects on hemodynamic patterns

Hemodynamics, and in particular Wall Shear Stress (WSS), is thought to play a critical role in the progression and rupture of intracranial aneurysms. Wall motion is related to local biomechanical properties of the aneurysm, which in turn are associated with the amount of damage undergone by the tissue. The underlying hypothesis in this work is that injured regions show differential motion with respect to normal ones, allowing a connection between local wall biomechanics and a potential mechanism of wall injury such as elevated WSS. In a previous work, a novel method was presented combining wall motion estimation using image registration techniques with Computational Fluid Dynamics (CFD) simulations in order to provide realistic intra-aneurysmal flow patterns. It was shown that, when compared to compliant vessels, rigid models tend to overestimate WSS and produce smaller areas of elevated WSS and force concentration, being the observed differences related to the magnitude of the displacements. This work aims to further study the relationships between wall motion, flow patterns and risk of rupture in aneurysms. To this end, four studies containing both 3DRA and DSA studies were analyzed, and an improved version of the method developed previously was applied to cases showing wall motion. A quantification and analysis of the displacement fields and their relationships to flow patterns are presented. This relationship may play an important role in understanding interaction mechanisms between hemodynamics, wall biomechanics, and the effect on aneurysm evolution mechanisms.
Functional Gait Assessment: Concurrent, Discriminative, and Predictive Validity in Community-Dwelling Older Adults

Background The Functional Gait Assessment (FGA) is a reliable and valid measure of gait-related activities. Objective The purpose of this study was to determine the concurrent, discriminative, and predictive validity of the FGA in community-dwelling older adults. Design This was a prospective cohort study. Methods Thirty-five older adults aged 60 to 90 years completed the Activities-specific Balance Confidence Scale (ABC), Berg Balance Scale (BBS), Dynamic Gait Index (DGI), Timed “Up & Go” Test (TUG), and Functional Gait Assessment (FGA) during one session. Falls were tracked by having participants complete a monthly fall calendar for 6 months. Spearman correlation coefficients were used to determine concurrent validity among the ABC, BBS, TUG, DGI, and FGA. To determine the optimum scores to classify fall risk, sensitivity (Sn), specificity (Sp), and positive and negative likelihood ratios (LR+ and LR−) were calculated for the FGA in classifying fall risk based on the published criterion scores of the DGI and TUG and for the FGA, TUG, and DGI in identifying prospective falls. Receiver operator curves with area under the curve were used to determine the effectiveness of the FGA in classifying fall risk and of the DGI, TUG, and FGA in identifying prospective falls. Results The FGA correlated with the ABC (r=.053, P<.001), BBS (r=.84, P<.001), and TUG (r=−.84, P<.001). An FGA score of ≤22/30 provides both discriminative and predictive validity. The FGA (scores ≤22/30) provided 100% Sn, 72% Sp, LR+ of 3.6, and LR− of 0 to predict prospective falls. Limitations The study was limited by the length of time of follow-up and the small sample size that did not allow for evaluation of criterion scores by decade. Conclusions The FGA with a cutoff score of 22/30 is effective in classifying fall risk in older adults and predicting unexplained falls in community-dwelling older adults.
The effect of the color red on avoidance motivation

Results of recent studies suggest that the color red induces an voidance motivation. Elliot and his colleagues (e.g., Elliot, Maier, Binser,Friedman, & Pekrun, 2009; Elliot, Maier, Moller, Friedman, & Meinhardt, 2007; Maier, Elliot, & Lichtenfeld, 2008) have conducted a series of experiments demonstrating that participants who were presented with the color red in an achievement context exhibited responses that indicate avoidance motivation. These included impaired task performance, preference for an easier task, local focus of attention, bodily movement away from the stimulus, right prefrontal cortical activity, and so forth (see also Mehta & Zhu, 2009).
Developing culturally diverse organizations: a participative and empowerment‐based method

Purpose – This study aims to investigate the promotion of workplace multiculturalism via the use of a participative and empowerment‐based diversity training and development method.Design/methodology/approach – A two‐year long qualitative, multiple case‐study amongst 15 Finnish organizations was conducted by means of the focus group method. Altogether 20 group interviews were held with so‐called “working culture bridge groups” consisting of different stakeholders and their four coordinators to explore the approaches, modes of action, achievements and explanatory factors that contributed to the development of working cultures towards multiculturalism.Findings – The development method was directed more at individual than organizational level change processes. More specifically, the attitudes of the majority were perceived as the main problem and the goal was to influence them by enhancing their knowledge and awareness of multicultural issues. The effectiveness of the method was recognized to depend on the cl.
Chemical modifications to phosphodiamidate morpholino oligomer antisense molecules targeting VP 224 modify their efficacy against Ebola virus infection

Phosphorodiamidate morpholino oligomers (PMOs) are uncharged nucleic acid-like molecules designed to inactivate the expression of specific genes via the antisense-based steric hindrance of mRNA translation. PMOs have been successful at knocking out viral gene expression and replication in the case of acute viral infections in animal models and have been well tolerated in human clinical trials. We propose that antisense PMOs represent a promising class of therapeutic agents that may be useful for combating filoviral infections. We have previously shown that mice treated with a PMO whose sequence is complementary to a region spanning the start codon of VP24 mRNA were protected against lethal Ebola virus challenge. In the present study, we report on the abilities of two additional VP24-specific PMOs to reduce the cell-free translation of a VP24 reporter, to inhibit the in vitro replication of Ebola virus, and to protect mice against lethal challenge when the PMOs are delivered prior to infection. Additionally, structure-activity relationship evaluations were conducted to assess the enhancement of antiviral efficacy associated with PMO chemical modifications that included conjugation with peptides of various lengths and compositions, positioning of conjugated peptides to either the 5 or the 3 terminus, and the conferring of charge modifications by the addition of piperazine moieties. Conjugation with arginine-rich peptides greatly enhanced the antiviral efficacy of VP24-specific PMOs in infected cells and mice during lethal Ebola virus challenge.
Pair of Replacement Algorithms MFMR and AF-LRU on L1 and L2 Cache for Proxy Server

Access to the internet and WWW is growing extensively, which results in heavy network traffic. To reduce the network traffic proxy server is used. Proxy server reduces the load of server. If the cache replacement algorithm of proxy server's cache is efficient then proxy server will be helpful to reduce the network traffic in more efficient manner. In this paper we are considering proxy server cache to be Level 1 (L1) cache and storage cache of proxy server to be Level 2 (L2) cache. For collecting the real trace proxy server is used in an organization. Log of proxy server gives the information of various URLs accessed by various clients with time. For performing experiments various URLs were given a numeric identity. This paper analyzes the behavior of various replacement algorithms. The replacement algorithms taken into consideration are Least Recently Used (LRU), Least Frequently Used (LFU), First In First Out (FIFO). This paper proposes a new Replacement Algorithm named MFMR (Most Frequent with Maximum Reusability) for L1 which works about 16% better than existing algorithms considered in this paper. This paper also proposes a new replacement policy for L2 named AF_LRU (Average Frequency, Least Recently Used). Simulation results shows that pair of MFMR and AF-LRU is approximately 28% better than other existing pairs of replacement algorithms considered. Key Word- Level 1 Cache (L1); Level 2 Cache (L2); web access pattern; Replacement Algorithm; Proxy server; client.