Miracle-dz/UniFAR-FTUs huggingface dataset:
Interpolation of n-gram and mutual-information based trigger pair language models for Mandarin speech recognition

While n-gram modeling is simple and dominant in speech recognition, it can only capture the short-distance context dependency within an n-word window where currently the largest practical n for natural language is three. However, many of the context dependencies in natural language occur beyond a three-word window. This paper proposes a new language modeling approach to capture the preferred relationships between words over a short or long distance through the concept of MI-Trigger pairs. Different MI-Trigger-based models are constructed in either a distance-dependent or a distance-independent way within a window from 1 to 10 words. This new MI-Trigger-based modeling is also compared and merged with word bigram modeling. It is found that the MI-Trigger-based modeling has better performance than word bigram modeling. It is also found that n-gram and MI-Trigger models have good complementarity and their proper merging can further increase the recognition rate when tested on Mandarin speech recognition. One advantage of MI-Trigger-based modeling is that the number of parameters needed for MI-Trigger modeling is much less than that of word bigram modeling. Another advantage is that the number of trigger pairs in an MI-Trigger model can be kept to a reasonable size without losing too much of its modeling power. c © 1999 Academic Press
Spin detection hardware for improved management of multithreaded systems

Spinning is a synchronization mechanism commonly used in applications and operating systems. Excessive spinning, however, often indicates performance or correctness (e.g., livelock) problems. Detecting if applications and operating systems are spinning is essential for achieving high performance, especially in consolidated servers running virtual machines. Prior research has used source or binary instrumentation to detect spinning. However, these approaches place a significant burden on programmers and may even be infeasible in certain situations. In this paper, we propose efficient hardware to detect spinning in unmodified applications and operating systems. Based on this hardware, we develop 1) scheduling and power policies that adaptively manage resources for spinning threads, 2) system support that helps detect when a multithreaded program is livelocked, and 3) hardware performance counters that accurately reflect system performance. Using full-system simulation with SPEC OMP, SPLASH-2, and Wisconsin commercial workloads, we demonstrate that our mechanisms effectively improve the management of multithreaded systems
The Alzheimer's Disease Centers' Uniform Data Set (UDS): The Neuropsychologic Test Battery

The neuropsychologic test battery from the Uniform Data Set (UDS) of the Alzheimer's Disease Centers (ADC) program of the National Institute on Aging consists of brief measures of attention, processing speed, executive function, episodic memory, and language. This paper describes development of the battery and preliminary data from the initial UDS evaluation of 3268 clinically cognitively normal men and women collected over the first 24 months of utilization. The subjects represent a sample of community-dwelling, individuals who volunteer for studies of cognitive aging. Subjects were considered “clinically cognitively normal” based on clinical assessment, including the Clinical Dementia Rating scale and the Functional Assessment Questionnaire. The results demonstrate performance on tests sensitive to cognitive aging and to the early stages of Alzheimer disease in a relatively well-educated sample. Regression models investigating the impact of age, education, and sex on test scores indicate that these variables will need to be incorporated in subsequent normative studies. Future plans include: (1) determining the psychometric properties of the battery; (2) establishing normative data, including norms for different ethnic minority groups; and (3) conducting longitudinal studies on cognitively normal subjects, individuals with mild cognitive impairment, and individuals with Alzheimer disease and other forms of dementia.
P-DONAS: A P2P-Based Domain Name System in Access Networks

The domain name system (DNS) includes infrastructures deployed by Internet service providers (ISPs) and third-party suppliers to ensure high responsiveness, resilience, and load sharing. This equipment implies high effort and energy for 24/7 operation. To facilitate cost reductions in this regard, P-DONAS—a peer-to-peer (P2P)-based DNS—organizes access nodes (ANs) of an ISP’s access network, which possess available resources, into a decentralized, self-organizing distributed hash table--based P2P network. Each AN acts as traditional DNS server and solely stores a piece of DNS data. DNS requests issued to an AN are resolved via P2P lookups while maintaining full compatibility with traditional DNS. The article discusses the application of P-DONAS as both a complement and an alternative to traditional DNS. Results from both simulations and a practical test arrangement prove P-DONAS’ high scalability and its performance comparable to that of a commercial DNS name server relieving this name server by 53% to 75% of DNS traffic.
Exploring linguistically-rich patterns for question generation

Linguistic patterns reflect the regularities of Natural Language and their applicability is acknowledged in several Natural Language Processing tasks. Particularly, in the task of Question Generation, many systems depend on patterns to generate questions from text. The approach we follow relies on patterns that convey lexical, syntactic and semantic information, automatically learned from large-scale corpora. In this paper we discuss the impact of varying several parameters during pattern learning and matching in the Question Generation task. In particular, we introduce semantics (by means of named entities) in our lexico-syntactic patterns. We evaluate and compare the number and quality of the learned patterns and the matched text segments. Also, we detail the influence of the patterns in the generation of natural language questions.
Neutrino mass models: A road map

In this talk we survey some of the recent promising developments in the search for the theory behind neutrino mass and mixing, and indeed all fermion masses and mixing. The talk is organized in terms of a neutrino mass models road map according to which the answers to experimental questions provide sign posts to guide us through the maze of theoretical models eventually towards a complete theory of flavour and unification.
Applying Agile Principles for Distributed Software Development

The necessity of finding right skilled people, sharing resource and limitation on cost has made distributed software development indispensable. In a distributed development project, but are working collaboratively toward the outcome. Such offshore service providers follow the traditional process models. Agile practices promote development iterations, open collaboration, and process adaptability throughout the life cycle of the project. Adapting these practices in a distributed environment can help distributed development tackle the challenges of cultural incompatibility, leadership struggle and lack of trust. This paper describes the benefits of using Agile process and Scrum the iterative incremental process in Distributed Software development, and proposes two team structures for its implementation.
UML with meaning: executable modeling in foundational UML and the Alf action language

To most in the software community, "modeling" is drawing pictures, something much different than "coding". While programming languages must be specified precisely enough to be executable, this has not necessarily been the case for modeling languages. Indeed, the well-known Unified Modeling Language (UML) has for years had a specification that is far from precise. However, precise models are quite common in other engineering disciplines, and there has been a minority even in software engineering that have created models that are precise enough to be, themselves, executable. Over the last decade, the UML community has more generally come to realize the benefits of having at least a subset of UML specified with precise execution semantics. While not all models need to be executable, executable models can support early testing and analysis of the design of critical software systems, as well as supporting simulation for communities using UML for modeling beyond just software (such as SysML for systems engineering). As a result, there has been a great deal of work in recent years toward the standardization of precise, executable semantics for UML models - the "meaning" behind the pictures: Foundational UML (fUML), the Action Language for fUML (Alf) and the recently completed Precise Semantics for UML Composite Structures. These new specifications provide the promise of widespread support for executable modeling across the many UML tools now on the market.
POSTER: Utilizing dataflow-based execution for coupled cluster methods

Computational chemistry comprises one of the driving forces of High Performance Computing. In particular, manybody methods, such as Coupled Cluster methods (CC) (Bartlett and Musial, 2007) of the quantum chemistry package NWCHEM (Valiev, et.al., 2010), are of particular interest for the applied chemistry community. With the increase in scale, complexity, and heterogeneity of modern platforms, traditional programming models fail to deliver the expected performance scalability. On our way to Exascale, we believe that dataflow-based programming models - in contrast to the control flow model (e.g., as implemented in languages such as C) - may be the only viable way for achieving and maintaining computation at scale. In this paper, we discuss a dataflow-based programming model and its applicability to NWCHEM's CC methods. Our dataflow version of the CC kernels breaks down the algorithm into finer grained tasks with explicitly defined data dependencies. As a result, the serialization imposed by the traditional, linear algorithms can be transformed into parallelism, allowing the overall computation to scale to much larger computational resources. We build this experiment using the Parallel Runtime Scheduling and Execution Control (PARSEC) framework (Bosilca, et.al., 2012) - a task-based dataflow-driven execution engine - that enables efficient task scheduling on distributed systems.
Enzymatic and Cryoreduction EPR Studies of the Hydroxylation of Methylated Nω-Hydroxy-l-arginine Analogues by Nitric Oxide Synthase from Geobacillus stearothermophilus

Nitric oxide synthase (NOS) catalyzes the conversion of l-arginine to l-citrulline and NO in a two-step process involving the intermediate Nω-hydroxy-l-arginine (NHA). It was shown that Cpd I is the oxygenating species for l-arginine; the hydroperoxo ferric intermediate is the reactive intermediate with NHA. Methylation of the Nω-OH and Nω-H of NHA significantly inhibits the conversion of NHA into NO and l-citrulline by mammalian NOS. Kinetic studies now show that Nω-methylation of NHA has a qualitatively similar effect on H2O2-dependent catalysis by bacterial gsNOS. To elucidate the effect of methylating Nω-hydroxy l-arginine on the properties and reactivity of the one-electron-reduced oxy-heme center of NOS, we have applied cryoreduction/annealing/EPR/ENDOR techniques. Measurements of solvent kinetic isotope effects during 160 K cryoannealing cryoreduced oxy-gsNOS/NHA confirm the hydroperoxo ferric intermediate as the catalytically active species of step two. Product analysis for cryoreduced samples with methylated NHA’s, NHMA, NMOA, and NMMA, annealed to 273 K, show a correlation of yields of l-citrulline with the intensity of the g 2.26 EPR signal of the peroxo ferric species trapped at 77 K, which converts to the reactive hydroperoxo ferric state. There is also a correlation between the yield of l-citrulline in these experiments and kobs for the H2O2-dependent conversion of the substrates by gsNOS. Correspondingly, no detectable amount of cyanoornithine, formed when Cpd I is the reactive species, was found in the samples. Methylation of the NHA guanidinium Nω-OH and Nω-H inhibits the second NO-producing reaction by favoring protonation of the ferric-peroxo to form unreactive conformers of the ferric-hydroperoxo state. It is suggested that this is caused by modification of the distal-pocket hydrogen-bonding network of oxy gsNOS and introduction of an ordered water molecule that facilitates delivery of the proton(s) to the one-electron-reduced oxy-heme moiety. These results illustrate how variations in the properties of the substrate can modulate the reactivity of a monooxygenase.
The Alternative Epac/cAMP Pathway and the MAPK Pathway Mediate hCG Induction of Leptin in Placental Cells

Pleiotropic effects of leptin have been identified in reproduction and pregnancy, particularly in the placenta, where it works as an autocrine hormone. In this work, we demonstrated that human chorionic gonadotropin (hCG) added to JEG-3 cell line or to placental explants induces endogenous leptin expression. We also found that hCG increased cAMP intracellular levels in BeWo cells in a dose-dependent manner, stimulated cAMP response element (CRE) activity and the cotransfection with an expression plasmid of a dominant negative mutant of CREB caused a significant inhibition of hCG stimulation of leptin promoter activity. These results demonstrate that hCG indeed activates cAMP/PKA pathway, and that this pathway is involved in leptin expression. Nevertheless, we found leptin induction by hCG is dependent on cAMP levels. Treatment with (Bu)2cAMP in combination with low and non stimulatory hCG concentrations led to an increase in leptin expression, whereas stimulatory concentrations showed the opposite effect. We found that specific PKA inhibition by H89 caused a significant increase of hCG leptin induction, suggesting that probably high cAMP levels might inhibit hCG effect. It was found that hCG enhancement of leptin mRNA expression involved the MAPK pathway. In this work, we demonstrated that hCG leptin induction through the MAPK signaling pathway is inhibited by PKA. We observed that ERK1/2 phosphorylation increased when hCG treatment was combined with H89. In view of these results, the involvement of the alternative cAMP/Epac signaling pathway was studied. We observed that a cAMP analogue that specifically activates Epac (CPT-OMe) stimulated leptin expression by hCG. In addition, the overexpression of Epac and Rap1 proteins increased leptin promoter activity and enhanced hCG. In conclusion, we provide evidence suggesting that hCG induction of leptin gene expression in placenta is mediated not only by activation of the MAPK signaling pathway but also by the alternative cAMP/Epac signaling pathway.
Comparative study of thermally cured and electron-beam-exposed hydrogen silsesquioxane resists

A comparative study of the changes in the chemical structure and properties of hydrogen silsesquioxane (HSQ) resists induced by thermal curing and electron-beam exposure has been conducted. Studies using Fourier transform infrared (FTIR) spectroscopy suggested similar behavior in the redistribution of bonds for both processes. Quantitative analysis of both spectra revealed the existence of a critical temperature and electron dose for the achievement of development for pattern generation. As a complementary technique, x-ray reflectivity measurements were performed to monitor changes in the film density. Notwithstanding the similar changes in bond redistribution observed from the FTIR spectra for both thermal curing and electron-beam exposure, the film densification processes seem to occur in quite distinctive fashions. This was confirmed through dry etching experiments; the results of which were consistent for both Freon and Cl2∕Ar reactive ion etching. While effective film densification occurred only at c.
Mucin Depleted Foci, Colonic Preneoplastic Lesions Lacking Muc2, Show Up-Regulation of Tlr2 but Not Bacterial Infiltration

Mucin depleted foci (MDF) are precancerous lesions of the colon in carcinogen-treated rodents and humans at high risk. Since MDF show signs of inflammation we hypothesized that the defective mucous production would expose them to the risk of being penetrated by intestinal bacteria, which can be sensed by Toll-like receptors (Tlrs) and activate inflammatory pathways. To verify this hypothesis we tested the expression of 84 genes coding for Tlrs and associated pathways using RT-qPCR in MDF (n = 7) from 1,2-dimethylhydrazine (DMH)-treated rats. Among the 84 tested genes, 26 were differentially expressed in MDF with 5 genes significantly up-regulated and 21 down-regulated when compared to the normal mucosa. Tlr2, as well as other downstream genes (Map4k4, Hspd1, Irak1, Ube2n), was significantly up-regulated. Among the genes regulating the NFkB pathway, only Map4k4 was significantly up-regulated, while 19 genes were not varied and 6 were down-regulated. Tlr2 protein was weakly expressed both in normal mucosa and MDF. To determine whether inflammation observed in MDF could be caused by bacteria contacting or infiltrating crypts, we performed fluorescence in situ hybridization (FISH) experiments with a rRNA universal bacterial probe. None of the 21 MDF tested, showed bacteria inside the crypts, while among the colonic tumors (n = 15), only one had very few bacteria on the surface and on the surrounding normal mucosa. In conclusion, the up-regulation of Tlr2 in MDF, suggests a link between this receptor and carcinogenesis, possibly related to a defective barrier function of these lesions. The data of FISH experiments do not support the hypothesis that inflammation in MDF and tumors is stimulated by bacterial infiltration.
TLR2 Mediates Neuroinflammation and Neuronal Damage1

Innate immunity relies on pattern recognition receptors to detect the presence of infectious pathogens. In the case of Gram-positive bacteria, binding of bacterial lipopeptides to TLR2 is currently regarded as an important mechanism. In the present study, we used the synthetic bacterial lipopeptide Pam3CysSK4, a selective TLR2 agonist, to induce meningeal inflammation in rodents. In a 6-h rat model, intrathecal application of Pam3CysSK4 caused influx of leukocytes into the cerebrospinal fluid (CSF) and induced a marked increase of regional cerebral blood flow and intracranial pressure. In wild-type mice, we observed CSF pleocytosis and an increased number of apoptotic neurons in the dentate gyrus 24 h after intrathecal challenge. Inflammation and associated neuronal loss were absent in TLR2 knockout mice. In purified neurons, cytotoxicity of Pam3CysSK4 itself was not observed. Exposure of microglia to Pam3CysSK4 induced neurotoxic properties in the supernatant of wild-type, but not TLR2-deficient microglia. We conclude that TLR2-mediated signaling is sufficient to induce the host-dependent key features of acute bacterial meningitis. Therefore, synthetic lipopeptides are a highly specific tool to study mechanisms of TLR2-driven neurodegeneration in vivo.
Cryptocurrency and criminality

Bitcoin has become the currency of choice for cybercriminals. Its distinctive characteristics of decentralisation and pseudo-anonymity are also attractive to criminal actors in general, and yet Bitcoin has been assessed as representing only a low money laundering risk. In many respects, cryptocurrencies are still viewed as an unfamiliar, marginal phenomenon restricted to the purview of specialists. This article seeks: to demystify the Bitcoin concept; to demonstrate that, far from being low-risk, Bitcoin constitutes a substantial danger in terms of criminal enterprise; and to promote the case for greater awareness among criminal justice professionals and law enforcement officers in particular.
Exploring Knowledge Sharing in the Department of Defense

A phenomenological study using Nonaka and Takeuchi’s socialization, externalization, combination, and internalization (SECI) model explored the organized, continual method of tacit-toexplicit knowledge theory for organizational knowledge creation. Twenty participants shared their lived experiences in semistructured interviews. Ten primary themes emerged, with results indicating the foundation for supporting the knowledge sharing process. Procedures Prior to this study, a pilot survey was administered to 3 participants to ensure the integrity of the study. Purposive sampling of participants occurred based on their level of contracting experience and availability to participate in the interview process. The snowball sampling technique was used for recruiting the 20 participants. Data were collected through personal, semistructured interviews. Participants were recorded using the Echo Smartpen. Seventeen interview questions were proposed to participants after in-depth analysis was conducted by the researcher and approved by Walden instructors.
A process algebra based verification of a production system

Studying industrial systems by simulation enables the designer to study the dynamic behaviour and to determine some characteristics of the system. Unfortunately simulation also has some disadvantages. These can be overcome by using formal methods. Formal methods allow a thorough analysis of the possible behaviours of a system, parameterised system analysis and a modular approach to the analysis of systems. We present a case study in which a model of an industrial system is studied in a formal way. For this purpose, the model is first specified and simulated using the CSP-based executable specification language /spl chi/. The model is translated into a model in the process algebra ACP/sup T/. This enables us to give a correctness proof of the parameterised model and to study the model in isolation.
A Unified Error Control Coding Scheme to Enhance the Reliability of a Hybrid Wireless Network-on-Chip

Hybrid wireless Network-on-Chip (NoC) has emerged as an alternative to the traditional multi-hop wire line NoC to achieve higher performance and low energy dissipation in on-chip data transfer. However, introduction of on-chip wireless links lowers the overall reliability of the data communication fabric. In this paper we propose a unified Error Control Coding (ECC) mechanism which can be effectively used to restore the reliability of a Wireless NoC (WiNoC). We demonstrate that with carefully designed ECC schemes in the WiNoC it is possible to achieve high gains in performance due to the wireless links while maintaining comparable reliability as that of a traditional wire line NoC.
A Cross-modal Multi-task Learning Framework for Image Annotation

With the advance of internet, multi-modal data can be easily collected from many social websites such as Wikipedia, Flickr, YouTube, etc. Images shared on the web are usually associated with social tags or other textual information. Although existing multi-modal methods can make use of associated text to improve image annotation, the disadvantages of them are that associated text is also required for a new image to be predicted. In this paper, we propose the cross-modal multi-task learning (CMMTL) framework for image annotation. Labeled and unlabeled multi-modal data are both levaraged for training in CMMTL, and it finally obtains visual classifiers which can predict concepts for a single image without any associated information. CMMTL integrates graph learning, multi-task learning and cross-modal learning into a joint framework, where a shared subspace is learned to preserve both cross-modal correlation and concept correlation. The optimal solution of the proposed framework can be obtained by solving a generalized eigenvalue problem. We conduct comprehensive experiments on two real world image datasets: MIR Flickr and NUS-WIDE, to evaluate the performance of the proposed framework. Experimental results demonstrate that CMMTL obtains a significant improvement over several representative methods for cross-modal image annotation.