Miracle-dz/UniFAR-FTUs huggingface dataset:
The HTK large vocabulary recognition system for the 1995 ARPA H3 task

The HTK large vocabulary speech recognition system has previously shown very good performance for clean speech. This paper describes developments of the system aimed at recognition of speech from the ARPA H3 task which contains data of a relatively low signal-to-noise ratio from unknown microphones. It is shown that a two-phase approach can be eeective. The rst phase is to derive an initial set of models that are more appropriate for the current conditions than using models trained on clean speech. This is done using either single-pass retraining with multiple microphone data or parallel model combination which combines HMMs trained on clean data with estimates of convolutional and additive noise. The second stage provides more detailed environmental and speaker adapatation using maximum likelihood linear regression which estimates a set of linear transformations of the model parameters to the current conditions. Experiments are reported on both the 1994 ARPA CSR S5 (alternate microphones) and S10 (additive noise) spoke tasks as well as the 1995 ARPA CSR H3 task. The HTK system yielded the lowest error rates in both the H3-P0 and H3-C0 tests.
On the Succinctness of Query Rewriting over OWL 2 QL Ontologies with Shallow Chases

We investigate the size of first-order rewritings of conjunctive queries over OWL 2 QL ontologies of depth 1 and 2 by means of hypergraph programs computing Boolean functions. Both positive and negative results are obtained. Conjunctive queries over ontologies of depth 1 have polynomial-size nonrecursive datalog rewritings; tree-shaped queries have polynomial positive existential rewritings; however, in the worst case, positive existential rewritings can only be of superpolynomial size. Positive existential and nonrecursive datalog rewritings of queries over ontologies of depth 2 suffer an exponential blowup in the worst case, while first-order rewritings are superpolynomial unless $\text{NP} \subseteq \text{P}/\text{poly}$. We also analyse rewritings of tree-shaped queries over arbitrary ontologies and observe that the query entailment problem for such queries is fixed-parameter tractable.
Zebrafish Shoaling Behavior: Its Development, Quantification, Neuro-chemical Correlates, and Application in a Disease Model

Abnormal social behavior is a symptom of many human conditions, including Fetal Alcohol Spectrum Disorders (FASD). The zebrafish may be an excellent model to study embryonic alcohol effects, owing to the ease of drug administration. In recent decades, zebrafish have become increasingly popular in behavioral neuroscience, and their elaborate behavioral repertoire can provide insights in brain functioning and social behavior in response to teratogens or pharmaceutical agents. Shoaling is the zebrafish’s most notable behavioral feature, but has not been well characterized. I have started this characterization by describing the ontogeny of shoaling behavior. Embryonic exposure to low doses of ethanol has been shown to impair social behavior without any gross morphological alterations in zebrafish. However, this has not been studied in freely moving groups (shoals). Validation for using a shoaling task in behavioral testing, and potentially for high throughput analyses in the future, hinges on thorough characterization of the behavioral effects, however subtle in alcohol treated zebrafish. In my studies, I have shown that social behavior is impaired in zebrafish in a group setting after one time embryonic ethanol exposure. I have also discovered that this impairment is accompanied by a reduction of dopamine, serotonin, DOPAC and 5HIAA, neurochemicals measured in whole brain samples using HPLC. I have developed refined methods of measuring shoaling behavior in ten member zebrafish groups, laying the foundation for high throughput screening of adult zebrafish. Zebrafish are an economical model, and therefore lend themselves particularly well for high throughput
Incident angle-dependent spectra of an anisotropic optical microcavity

We simulate spectra of the optical microcavity based on a composite (mesoporous silicon)/(nematic liquid crystal). The incident angle-dependent calculations predict the transmission peak blueshift and splitting of transverse electric and transverse magnetic polarized modes due to birefringence of both porous host material and the anisotropic filler.
Significance of Write References on Nonvolatile Buffer Cache and its Implication on Hit Ratio and the Optimal MIN Replacement Algorithm

Summary Performance studies of buffer caches have generally been done with write references ignored. In this study, we show that once we consider write references in buffer caches that include nonvolatile memory, the traditional hit ratio performance measure is no longer an accurate representation, and that the disk access ratio should be used. We also show that in regards to this measure, the MIN replacement algorithm is either non-optimal or non-applicable.
with primary immunodeficiencies The altered landscape of the human skin microbiome in patients Material

Material Supplemental http://genome.cshlp. org/content/suppl/2013/10/23/gr.159467. 113.DC1. html P<P Published online October 29, 2013 in advance of the print journal. License Commons Creative . http://creativecommons.org/licenses/by-nc/3.0/ described at a Creative Commons License (Attribution-NonCommercial 3.0 Unported), as ). After six months, it is available under http://genome.cshlp. org/site/misc/terms.xhtml first six months after the full-issue publication date (see This article is distributed exclusively by Cold Spring Harbor Laboratory Press for the
GERONTOLOGICAL EDUCATION FOR STUDENTS IN NURSING AND SOCIAL WORK: KNOWLEDGE, ATTITUDES, AND PERCEIVED BARRIERS

Most health care and social service providers are routinely required to work with elderly clients and clients’ aging family members. Research suggests that students entering these professions have knowledge deficits and lack positive attitudes toward older people. Few prefer to work with aging clients. Professional curricula are not providing students with adequate training to serve the current needs of this population, much less to meet projected increases in demand for services. To examine this issue, 67 master's students in nursing and social work completed questionnaires assessing (1) knowledge about aging, (2) attitudes toward old people, and (3) perceived barriers to gerontological education. Results confirmed the existence of knowledge deficits among respondents. Attitudes tended to be neutral rather than strongly positive or negative. Knowledge scores were related to attitudes, to respondents’ ages, and to their having lived in households with older relatives. Nursing students identified the great.
A hybrid and distributed architecture for an interoperable One-Stop E-government portal

An effective e-government platform provides greater access to government services among citizens, businesses, and tourists. However, most e-government portals lack in integration and interoperability. This problem causes each government agency has its own portal. It prevents to provide services in a single access point. This paper proposes a one-stop e-government architecture that integrates one-stop portal, e-government service application, and e-government service provider. The architecture provides seamless integration and interoperability of e-government services among different government agencies using hybrid distributed e-government architecture. Finally, this work presents the proof-of-concept of the proposed architecture and a prototype case study in the Malaysian One-Stop E-government (MyOneEG) system as a case study.
Malfunctions of robotic system in surgery: role and responsibility of surgeon in legal point of view

Abstract Robotic surgery (RS) technology has undergone rapid growth in the surgical field since its approval. In clinical practice, failure of robotic procedures mainly results from a surgeon’s inability or to a device malfunction. We reviewed the literature to estimate the impact of this second circumstance in RS and its consequent legal implications. According to data from the literature, device malfunction is rare. We believe it is necessary to complement surgical training with a technical understanding of RS devices.
Affect Recognition during Active Game Playing based on Posture Skeleton Data

The affective state of a player during game playing has a significant effect on the player’s motivation and engagement. Recognising player’s emotions during games can help game designers improve the user experience by providing sophisticated behaviours to the game characters and the system itself. This paper presents work-in-progress towards novel recognition of player’s emotions using posture skeleton data as input from non-intrusive interfaces. A database of samples of non-acted posture skeleton data was captured during active game playing using Microsoft Kinect’s sensors. Four observers were asked to annotate the selected postures with an emotion label from a given emotion set. Based on Cohen’s kappa, the agreement level of the observers was above or equal to ‘good’ with overall agreement levels that outperform existing benchmarks. The data was used in a series of experiments for training the system in recognising emotions. The results indicate that the compiled database of postures annotated with emotion labels performs considerably above chance level recognition of emotions and offers interesting research questions for improvements and future directions in the area.
An estimator of forward and backward delay for multipath transport

Multipath transport protocols require awareness of the capability of different paths being used for transmission. It is well known that round trip time (RTT) can be used to estimate retransmission timeout with reasonable accuracy. However, using RTT to evaluate the delay of forward or backward paths is not always suitable. In fact, these paths are usually dissimilar, and therefore the packet delay can be significantly different in each direction. We propose a forward and backward delay estimator that aims to solve this problem. Based on the results of the estimator, a new retransmission heuristic mechanism for multipath transport is proposed. With this same technique we also build two other heuristics: A bottleneck bandwidth estimator and a shared congestion detector. These help the sender to choose the high bandwidth path in retransmission and ensure TCP-friendliness in multipath transport, respectively.
Protection of location privacy in continuous LBSs against adversaries with background information

Privacy issues in continuous Location-Based Services (LBSs) have gained attractive attentions in literature over recent years. In this paper, we illustrate the limitations of existing work and define an entropy-based privacy metric to quantify the privacy degree based on a set of vital observations. To tackle the privacy issues, we propose an efficient privacy-preserving scheme, DUMMY-T, which aims to protect LBSs user's privacy against adversaries with background information. By our Dummy Locations Generating (DLG) algorithm, we first generate a set of realistic dummy locations for each snapshot with considering the minimum cloaking region and background information. Further, our proposed Dummy Paths Constructing (DPC) algorithm guarantees the location reachability by taking the maximum distance of the moving mobile users into consideration. Security analysis and empirical evaluation results further verify the effectiveness and efficiency of our DUMMY-T.
Reliability-Aware Exceptions: Tolerating intermittent faults in microprocessor array structures

In future technology nodes, reliability is expected to become a first-order design constraint. Faults encountered in a chip can be classified into three categories: transient, intermittent, and permanent. Fault classification allows a chip to take the appropriate corrective action. Mechanisms have been proposed to distinguish transient from non-transient faults where all non-transient faults are handled as permanent. Intermittent faults induced by wearout phenomena have become the dominant reliability concern in nanoscale technology, yet there is no mechanism that provides finer classification of non-transient faults into intermittent and permanent faults. In this paper, we present a new class of exceptions called Reliability-Aware Exceptions (RAEs) which provide the ability to distinguish intermittent faults in microprocessor array structures. The RAE handlers have the ability to manipulate microprocessor array structures to recover from all three categories of faults. Using RAEs, we demonstrate that the reliability of two representative microarchitecture structures, load/store queue and reorder buffer in an out-of-order processor, is improved by average factors of 1.3 and 1.95, respectively.
A Fuzzy Logic Based Handoff Technique in Cognitive Radio Network

To address the problem of the under-utilization of the licensed spectrum in cognitive radio networks(CRN), secondary (unlicensed) users(SUs) are allowed to sense and access available spectrum opportunistically without causing harmful interference to primary users(PU)s. Fuzzy logic theory is suitable to deal with the uncertain and heterogeneous information in CRN , there has been some work in this area, however, validate the Fuzzy Logic Control System for a more general context has not been carefully investigated so far. In this paper , a whole process to perform spectrum handoff in a general framework in CRN is described and a concrete spectrum handoff paradigm based on Fuzzy Logic Control System is proposed . The proposed approach is able to make effective spectrum handoff decision on the condition that SUs causing harmful interference to PUs. Simulated results demonstrate that fuzzy logic based power control scheme can increase the transmit efficiency and achieve lower spectrum handoff rates .
University of Amsterdam at INEX 2009: Ad hoc, Book, and Entity Ranking Tracks

In this paper we describe our participation in INEX 2009 in the Ad Hoc Track, the Book Track, and the Entity Ranking Track. In the Ad Hoc track we investigate focused link evidence, using only links from retrieved sections. The new collection is not only annotated with Wikipedia categories, but also with YAGO/WordNet categories. We ex- plore how we can use both types of category information, in the Ad Hoc Track as well as in the Entity Ranking Track. Results in the Ad Hoc Track show Wikipedia categories are more eective than WordNet cate- gories, and Wikipedia categories in combination with relevance feedback lead to the best results.
Electronic cigarettes: human health effects

Objective With the rapid increase in use of electronic nicotine delivery systems (ENDS), such as electronic cigarettes (e-cigarettes), users and non-users are exposed to the aerosol and product constituents. This is a review of published data on the human health effects of exposure to e-cigarettes and their components. Methods Literature searches were conducted through September 2013 using multiple electronic databases. Results Forty-four articles are included in this analysis. E-cigarette aerosols may contain propylene glycol, glycerol, flavourings, other chemicals and, usually, nicotine. Aerosolised propylene glycol and glycerol produce mouth and throat irritation and dry cough. No data on the effects of flavouring inhalation were identified. Data on short-term health effects are limited and there are no adequate data on long-term effects. Aerosol exposure may be associated with respiratory function impairment, and serum cotinine levels are similar to those in traditional cigarette smokers. The high nicotine concentrations of some products increase exposure risks for non-users, particularly children. The dangers of secondhand and thirdhand aerosol exposure have not been thoroughly evaluated. Conclusions Scientific evidence regarding the human health effects of e-cigarettes is limited. While e-cigarette aerosol may contain fewer toxicants than cigarette smoke, studies evaluating whether e-cigarettes are less harmful than cigarettes are inconclusive. Some evidence suggests that e-cigarette use may facilitate smoking cessation, but definitive data are lacking. No e-cigarette has been approved by FDA as a cessation aid. Environmental concerns and issues regarding non-user exposure exist. The health impact of e-cigarettes, for users and the public, cannot be determined with currently available data.
Influence of Hydrocarbons on Plant Cell Ultrastructure and Main Metabolic Enzymes

Influence of octane and benzene on plant cell ultrastructure and enzymes of basic metabolism, such as nitrogen assimilation and energy generation have been studied. Different plants: perennial ryegrass (Lolium perenne) and alfalfa (Medicago sativa); crops- maize (Zea mays L.) and bean (Phaseolus vulgaris); shrubs - privet (Ligustrum sempervirens) and trifoliate orange (Poncirus trifoliate); trees - poplar (Populus deltoides) and white mulberry (Morus alba L.) were exposed to hydrocarbons of different concentrations (1, 10 and 100 mM). Destructive changes in bean and maize leaves cells ultrastructure under the influence of benzene vapour were revealed at the level of photosynthetic and energy generation subcellular organells. Different deviations at the level of subcellular organelles structure and distribution were observed in alfalfa and ryegrass root cells under the influence of benzene and octane, absorbed through roots. The level of destructive changes is concentration dependent. Benzene at low 1 and 10 mM concentration caused the increase in glutamate dehydrogenase (GDH) activity in maize roots and leaves and in poplar and mulberry shoots, though to higher extent in case of lower, 1mM concentration. The induction was more intensive in plant roots. The highest tested 100mM concentration of benzene was inhibitory to the enzyme in all plants. Octane caused induction of GDH in all grassy plants at all tested concentrations; however the rate of induction decreased parallel to increase of the hydrocarbon concentration. Octane at concentration 1 mM caused induction of GDH in privet, trifoliate and white mulberry shoots. The highest, 100mM octane was characterized by inhibitory effect to GDH activity in all plants. Octane had inductive effect on malate dehydrogenase in almost all plants and tested concentrations, indicating the intensification of Trycarboxylic Acid Cycle. The data could be suggested for elaboration of criteria for plant selection for phytoremediation of oil hydrocarbons contaminated soils.
Learning Multiple Models for Reward Maximization

We present an approach to reward maximiza-tion in a non-stationary mobile robot environment. The approach works within the realistic constraints of limited local sensing and limited a priori knowledge of the environment. It is based on the use of augmented Markov models (AMMs), a general modeling tool we have developed. AMMs are essentially Markov chains having additional statistics associated with states and state transitions. We have developed an algorithm that constructs AMMs on-line and in real-time with little computational and space overhead, making it practical to learn multiple models of the interaction dynamics between a robot and its environment during the execution of a task. For the purposes of reward maximiza-tion in a non-stationary environment, these models monitor events at increasing intervals of time and provide statistics used to discard redundant or outdated information while reducing the probability of conforming to noise. We have successfully implemented this approach with a physical mobile robot performing a mine collection task. In the context of this task, we rst present experimental results validating our reward max-imization criterion in a stationary environment. We then incorporate our algorithm for redundant/outdated information reduction using multiple models and apply the approach to a non-stationary environment with an abrupt change. Finally, we apply the technique to a simulated version of the task with a gradually shifting environment.
Coupled bloch-phonon oscillations in semiconductor superlattices

We investigate coherent Bloch oscillations in GaAs/AlxGa1-xAs superlattices with electronic miniband widths larger than the optical phonon energy. In these superlattices the Bloch frequency can be tuned into resonance with the optical phonon. Close to resonance a direct coupling of Bloch oscillations to LO phonons is observed which gives rise to the coherent excitation of LO phonons. The density necessary for driving coherent LO phonons via Bloch oscillations is about 2 orders of magnitude smaller than the density necessary to drive coherent LO phonons in bulk GaAs. The experimental observations are confirmed by the theoretical description of this phenomenon [A.W. Ghosh et al., Phys. Rev. Lett. 85, 1084 (2000)].
Initial Encryption of large Searchable Data Sets using Hadoop

With the introduction and the widely use of external hosted infrastructures, secure storage of sensitive data becomes more and more important. There are systems available to store and query encrypted data in a database, but not all applications may start with empty tables rather than having sets of legacy data. Hence, there is a need to transform existing plaintext databases to encrypted form. Usually existing enterprise databases may contain terabytes of data. A single machine would require many months for the initial encryption of a large data set. We propose encrypting data in parallel using a Hadoop cluster which is a simple five step process including the Hadoop set up, target preparation, source data import, encrypting the data, and finally exporting it to the target. We evaluated our solution on real world data and report on performance and data consumption. The results show that encrypting data in parallel can be done in a very scalable manner. Using a parallelized encryption cluster compared to a single server machine reduces the encryption time from months down to days or even hours.
Heuristic algorithm for off-lattice protein folding problem

Enlightened by the law of interactions among objects in the physical world, we propose a heuristic algorithm for solving the three-dimensional (3D) off-lattice protein folding problem. Based on a physical model, the problem is converted from a nonlinear constraint-satisfied problem to an unconstrained optimization problem which can be solved by the well-known gradient method. To improve the efficiency of our algorithm, a strategy was introduced to generate initial configuration. Computational results showed that this algorithm could find states with lower energy than previously proposed ground states obtained by nPERM algorithm for all chains with length ranging from 13 to 55.
Near threshold cloud processors for dark silicon mitigation: the impact on emerging scale-out workloads

The breakdown of Dennard scaling has made computing energy limited and therefore restricts the performance and brings rise to dark silicon. To effectively leverage the advantage of increased number of transistors and alleviate the dark silicon problem, designers consider a set of design paradigms in the processor manufacturing. Among those, Near - Threshold Voltage Computing (NTC) is a promising candidate. However, prior efforts largely focus on a specific design option based on legacy desktop applications, lacking comprehensive analysis of emerging scale-out applications with multiple design options. In this paper, we characterize different perspectives including performance and energy efficiency in the context of NTC cloud processors by running emerging scale-out workloads. We find NTC can improve performance by 1.6X, and improve energy efficiency by 50%. Meanwhile, we also show that tiled-OoO architecture improve performance of scale-out workloads upto 3.7X and energy efficiency upto 6X over alternative chip organizations, making it a preferable design paradigm for scale-out workloads. We believe that our observations will provide insights for the design of cloud processors in the era of dark silicon.