Miracle-dz/UniFAR-FTUs huggingface dataset:
The Relationship Between Artificial and Second Language Learning

Artificial language learning (ALL) experiments have become an important tool in exploring principles of language and language learning. A persistent question in all of this work, however, is whether ALL engages the linguistic system and whether ALL studies are ecologically valid assessments of natural language ability. In the present study, we considered these questions by examining the relationship between performance in an ALL task and second language learning ability. Participants enrolled in a Spanish language class were evaluated using a number of different measures of Spanish ability and classroom performance, which was compared to IQ and a number of different measures of ALL performance. The results show that success in ALL experiments, particularly more complex artificial languages, correlates positively with indices of L2 learning even after controlling for IQ. These findings provide a key link between studies involving ALL and our understanding of second language learning in the classroom.
Distributed under Creative Commons Cc-by 4.0 the Single-species Metagenome: Subtyping Staphylococcus Aureus Core Genome Sequences from Shotgun Metagenomic Data

In this study we developed a genome-based method for detecting Staphylococcus aureus subtypes from metagenome shotgun sequence data. We used a binomial mixture model and the coverage counts at >100,000 known S. aureus SNP (single nucleotide polymorphism) sites derived from prior comparative genomic analysis to estimate the proportion of 40 subtypes in metagenome samples. We were able to obtain >87% sensitivity and >94% specificity at 0.025X coverage for S. aureus. We found that 321 and 149 metagenome samples from the Human Microbiome Project and metaSUB analysis of the New York City subway, respectively, contained S. aureus at genome coverage >0.025. In both projects, CC8 and CC30 were the most common S. aureus clonal complexes encountered. We found evidence that the subtype composition at different body sites of the same individual were more similar than random sampling and more limited evidence that certain body sites were enriched for particular subtypes. One surprising finding was the apparent high frequency of CC398, a lineage often associated with livestock, in samples from the tongue dorsum. Epidemiologic analysis of the HMP subject population suggested that high BMI (body mass index) and health insurance are possibly associated with S. aureus carriage but there was limited power to identify factors linked to carriage of even the most common subtype. In the NYC subway data, we found a small signal of geographic distance affecting subtype clustering but other unknown factors influence taxonomic distribution of the species around the city.
Pilot-aided estimation of carrier frequency offsets and channel impulse responses for OFDM cooperative communications

We consider a cooperative communication system where the destination node receives an orthogonal frequency-division multiplexing (OFDM) signal transmitted from two relay nodes. We propose and compare two pilot-aided algorithms for the estimation of the carrier frequency offsets (CFOs) and the channel impulse responses (CIRs) associated with the two relay-destination links. The first algorithm uses a basis expansion model (BEM) to estimate a time-varying (TV) multiple-input single-output (MISO) channel that incorporates both CFOs and CIRs effects. The CFOs are then extracted from the estimated TV-MISO channel by applying estimation of signal parameters via rotational invariance techniques (ESPRIT). The second algorithm exploits the structure of a specific pilot sequence and estimates the CFOs by directly applying ESPRIT on the observed signal. Simulation results show the effectiveness of the proposed algorithms.
The Cyberhand: on the design of a cybernetic prosthetic hand intended to be interfaced to the peripheral nervous system

The objective of the project described in this paper is the development of a cybernetic prosthesis, replicating as much as possible the sensory-motor capabilities of the natural hand. The human hand is not only an effective tool but also an ideal instrument to acquire information from the external environment. The development of a truly human-like artificial hand is probably the most widely known paradigm of "bionics". The Cyberhand Project aims to obtain a cybernetic prosthetic hand interfaced to the peripheral nervous system. In particular this paper is focused on the hand mechanisms design and it presents preliminary results in developing the three fingered anthropomorphic hand prototype and its sensory system.
Cook’s Collage: Two Exploratory Designs

Gathered from observations and studies of how people busily manage tasks amidst distractions, forgetfulness, and multitasking in their homes, we identify two common cooking predicaments. We introduce Cook’s Collage, a context-aware system that passively displays recent activities. We posit that a cook, by glancing at these visual cues, can easily resume his task following an interruption when he otherwise might not be able to recover.
Predictive Transmit Antenna Selection with Maximal Ratio Combining

Antenna selection has long been a pragmatic method for exploiting spatial diversity in wireless systems with lower complexity than space-time or MIMO coding, and potentially having reduced hardware cost due to the reduction in the number of RF chains required. Whilst receive antenna selection is perhaps more common, transmit antenna selection also has several advantages, particularly for hardware-costly transmit schemes such as those requiring linearisation. However transmit antenna selection (TAS) requires either channel knowledge, or receiver knowledge at the transmitter, typically achieved using data transmission in the reverse direction, and this implies a delay between the channel being sampled and being acted upon. This outdated channel knowledge degrades system performance. In this paper, the degradation is determined, and related to the channel characteristics. A prediction scheme is then applied to mitigate against this degradation for the case of a (2,1;2) TAS system, where one of two transmit antenna is selected to communicate with two receive antennae employing maximal ratio combining.
Representation and optimal recognition of human activities

Towards the goal of realizing a generic automatic human activity recognition system, a new formalism is proposed. Activities are described by a chained hierarchical representation using three type of entities: image features, mobile object properties and scenarios. Taking image features of tracked moving regions from an image sequence as input, mobile object properties are first computed by specific methods while noise is suppressed by statistical methods. Scenarios are recognized from mobile object properties based on Bayesian analysis. Several scenarios are recognized by an algorithm using a probabilistic finite-state automaton (a variant of structured HMM). A demonstration of the optimality of this recognition method is discussed. Finally, the validity and the effectiveness of our approach is demonstrated on both real-world and perturbed data.
Evaluating design alternatives for reliable communication on high-speed networks

We systematically evaluate the performance of five implementations of a single, user-level communication interface. Each implementation makes different architectural assumptions about the reliability of the network hardware and the capabilities of the network interface. The implementations differ accordingly in their division of protocol tasks between host software, network-interface firmware, and network hardware. Using microbenchmarks, parallel-programming systems, and parallel applications, we assess the performance impact of different protocol decompositions. We show how moving protocol tasks to a relatively slow network interface yields both performance advantages and disadvantages, depending on the characteristics of the application and the underlying parallel-programming system. In particular, we show that a communication system that assumes highly reliable network hardware and that uses network-interface support to process multicast traffic performs best for all applications.
Diagnostic value of an immunochromatographic test over clinical predictors for tuberculosis in HIV patients

Purpose: The value of an immunochromatographic test for tuberculosis (ICT-TB) combined with clinical predictors has yet to be evaluated in Thailand. This study aimed to assess any additional diagnostic value of an ICT-TB test over that of clinical predictors in a group of human immunodeficiency virus (HIV) patients as well as in subgroups of HIV patients classified by clinical risk scores. Patients and methods: An extended cross-sectional study was conducted at a community hospital in Chiang Rai and a general hospital in Lampang. HIV patients registered between April 2009 and May 2010 were screened by a locally made ICT-TB test, including 38, 16, and 6 kD Microbacterium tuberculosis antigens, as well as by routine evaluations for TB diagnosis. Demographic data, medical history, signs, and symptoms were recorded. Participants were followed up for 2 months for final ascertainment of TB diagnosis. Results: Of 206 patients, 37 (18%) had TB. Four clinical predictors were identified: low body mass index (<19 kg/m2), prolonged cough (duration >2 weeks), shaking chills (≥1 week), and no use of antiretrovirals. The area under the receiver operating curve was 90.2%; adding the ICT-TB test result increased the area nonsignificantly to 91.6% (P = 0.40). When patients were categorized by risk scores derived from selected clinical predictors into low (scores ≤7) and high (scores >7) TB risk groups, a positive ICT-TB test increased the positive predictive value nonsignificantly in the low risk group (from 12.5% to 27.3%, P = 0.17) and the high risk group (from 78.6% to 80.8%, P = 0.73). Conclusion: In this study setting, the ICT-TB test did not enhance TB diagnosis over the four clinical predictors in the overall group or any subgroups of HIV patients classified by clinical risk scores.
The MITLL NIST LRE 2015 Language Recognition System

Abstract : In this paper we describe the most recent MIT Lincoln Laboratory language recognition system developed for the NIST 2015 Language Recognition Evaluation (LRE). The submission features a fusion of five core classifiers, with most systems developed in the context of an i-vector framework. The 2015 evaluation presented new paradigms. First, the evaluation included fixed training and open training tracks for the first time; second, language classification performance was measured across 6 language clusters using 20 language classes instead of an N-way language task; and third, performance was measured across a nominal 3-30 second range. Results are presented for the overall performance across the six language clusters for both the fixed and open training tasks. On the 6-cluster metric the Lincoln system achieved overall costs of 0.173 and 0.168 for the fixed and open tasks respectively.
Bridging the gap between intensional and extensional query evaluation in probabilistic databases

There are two broad approaches to query evaluation over probabilistic databases: (1) Intensional Methods proceed by manipulating expressions over symbolic events associated with uncertain tuples. This approach is very general and can be applied to any query, but requires an expensive postprocessing phase, which involves some general-purpose probabilistic inference. (2) Extensional Methods, on the other hand, evaluate the query by translating operations over symbolic events to a query plan; extensional methods scale well, but they are restricted to safe queries. In this paper, we bridge this gap by proposing an approach that can translate the evaluation of any query into extensional operators, followed by some post-processing that requires probabilistic inference. Our approach uses characteristics of the data to adapt smoothly between the two evaluation strategies. If the query is safe or becomes safe because of the data instance, then the evaluation is completely extensional and inside the database. If the query/data combination departs from the ideal setting of a safe query, then some intensional processing is performed, whose complexity depends only on the distance from the ideal setting.
A Fully Bayesian Approach to the Efficient Global Optimization Algorithm

Finding the global optimum(s) of a non-convex function is of great importance in numerous applications in science and engineering where the function takes the form of an expensive computer code and its inputs are the independent variables. For this type of problem, Jones et al. [12] proposed the idea of expected improvement (EI) and embedded it in an algorithm called ecient global optimization, or EGO. Neither EI nor EGO consider the uncertainty in the parameter estimates. One way to account for these uncertainties is to use Bootstrapping. In this paper, instead, we formulate the expected improvement method from a fully Bayesian perspective which results in a corresponding Bayesian EGO method. The performance of the proposed Bayesian EGO is illustrated and compared with the standard EGO method of Jones et al. and the bootstrapped EGO of Kleijnen et al. [13]. Furthermore, we apply the Bayesian EGO algorithm for the optimization of a stochastic inventory simulation model.
Review of deep inspiration breath-hold techniques for the treatment of breast cancer

Radiation treatment to the left breast is associated with increased cardiac morbidity and mortality. The deep inspiration breath‐hold technique (DIBH) can decrease radiation dose delivered to the heart and this may facilitate the treatment of the internal mammary chain nodes. The aim of this review is to critically analyse the literature available in relation to breath‐hold methods, implementation, utilisation, patient compliance, planning methods and treatment verification of the DIBH technique. Despite variation in the literature regarding the DIBH delivery method, patient coaching, visual feedback mechanisms and treatment verification, all methods of DIBH delivery reduce radiation dose to the heart. Further research is required to determine optimum protocols for patient training and treatment verification to ensure the technique is delivered successfully.
Expressing Adaptation Strategies Using Adaptation Patterns

Today, there is a real challenge to enable personalized access to information. Several systems have been proposed to address this challenge including Adaptive Hypermedia Systems (AHSs). However, the specification of adaptation strategies remains a difficult task for creators of such systems. In this paper, we consider the problem of the definition of adaptation strategies at a high level. We present two main contributions: a typology of elementary adaptation patterns for the adaptive navigation; and a process to generate adaptation strategies based on the use and the semiautomatic combination of patterns. We also describe how the generated adaptation strategies can be integrated into existing AHSs. A prototype has been implemented and an experiment in the e-learning domain has been conducted with a group of volunteers. This experiment shows that our pattern-based approach for defining adaptation strategies is more suitable than those based on “traditional” AH languages.
Standardization of techniques for using planar (2D) imaging for aerosol deposition assessment of orally inhaled products.

Two-dimensional (2D or planar) imaging with (99m)Tc radiolabels enables quantification of whole-lung and regional lung depositions for orally inhaled drug products. This article recommends standardized methodology for 2D imaging studies. Simultaneous anterior and posterior imaging with a dual-headed gamma camera is preferred, but imaging with a single-headed gamma camera is also acceptable. Correction of raw data for the effects of gamma ray attenuation is considered essential for accurate quantification, for instance, using transmission scanning with a flood-field source of (99m)Tc or (57)Co. Evidence should be provided of the accuracy of the quantification method, for instance, by determining "mass balance. " Lung deposition may be expressed as a percentage of ex-valve or ex-device dose, but should also be given as mass of drug when possible. Assessment of regional lung deposition requires delineation of the lung borders, using X-ray computed tomography, radioactive gas scans ((133)Xe or (81m)Kr), or transmission scans. When quantifying regional lung deposition, the lung should be divided into outer (O) and inner (I) zones. A penetration index should be calculated, as the O/I ratio for aerosol, normalized to that for a radioactive gas or transmission scan. A variety of methods can be used to assess lung deposition and distribution. Methodology and results should be documented in detail, so that data from different centers may be compared. The use of appropriate methodology will provide greater confidence in the results of 2D imaging studies, and should allay concerns that such studies are qualitative or semiquantitative in nature.
Surface-Based Analysis on Shape and Fractional Anisotropy of White Matter Tracts in Alzheimer's Disease

Background White matter disruption has been suggested as one of anatomical features associated with Alzheimer's disease (AD). Diffusion tensor imaging (DTI), which has been widely used in AD studies, obtains new insights into the white matter structure. Methods We introduced surface-based geometric models of the deep white matter tracts extracted from DTI, allowing the characterization of their shape variations relative to an atlas as well as fractional anisotropy (FA) variations on the atlas surface through large deformation diffeomorphic metric mapping (LDDMM). We applied it to assess local shapes and FA variations of twenty-three deep white matter tracts in 13 patients with AD and 19 healthy control subjects. Results Our results showed regionally-specific shape abnormalities and FA reduction in the cingulum tract and the sagittal stratum tract in AD, suggesting that disruption in the white matter tracts near the temporal lobe may represent the secondary consequence of the medial temporal lobe pathology in AD. Moreover, the regionally-specific patterns of FA and shape of the white matter tracts were shown to be of sufficient sensitivity to robustly differentiate patients with AD from healthy comparison controls when compared with the mean FA and volumes within the regions of the white matter tracts. Finally, greater FA or deformation abnormalities of the white matter tracts were associated with lower MMSE scores. Conclusion The regionally-specific shape and FA patterns could be potential imaging markers for differentiating AD from normal aging.
Particle Swarm Optimization Using Adaptive Mutation

Two new variants of particle swarm optimization (PSO) called AMPSO1 and AMPSO2 are proposed for global optimization problems. Both the algorithms use adaptive mutation using beta distribution. AMPSO1 mutates the personal best position of the swarm and AMPSO2, mutates the global best swarm position. The performance of proposed algorithms is evaluated on twelve unconstrained test problems and three real life constrained problems taken from the field of electrical engineering. The numerical results show the competence of the proposed algorithms with respect some other contemporary techniques.
Effect of Sarcosine (a Glycine Transport 1 Inhibitor) and Risperidone (an Atypical antipsychotic Drug) on MK-801 Induced Learning and Memory Deficits in Rats

Abstract The present study was carried out to evaluate whether the combined administration of sarcosine with risperidone possess any advantageous effects on dopaminergic and NMDA receptor-mediated glutamatergic neurotransmissions as compared to single drug administration in rats. The Wistar rats were divided into 7 groups each with different treatments. MK-801 (0.1 mg/kg, i.p.) was injected as single dose on 14th day for inducing learning and memory deficits in animals. Sarcosine (300 and 600 mg/kg, i.p.) and risperidone (0.2 mg/kg, i.p.) were administered daily for 14 days. Spatial habituation learning and hole board tests were performed on 14th day followed by measurement of GABA and 5-HT levels in brain tissues of rats. Pretreatment of sarcosine (600 mg/kg, i.p.) non-significantly improved learning and memory deficits induced by non-competitive NMDA receptor antagonist MK-801, significantly increased the GABA and decreased the 5-HT levels (p<0.05). Combined administration of sarcosine (300 mg/kg, i.p.) with risperidone (0.1 mg/kg, i.p.) synergistically improved cognitive deficits significantly, decreased % errors in hole board learning test, and increased centre time, corner time in spatial habituation learning test (p<0.05). The combined administration also potentiated the GABA and decreased 5-HT levels, indicating that the increased synaptic glycine concentrations may enhance NMDA receptor function which is directly linked with increased GABAergic transmission in striatum region and decreased 5-HT levels showed antagonistic action hence, enhancing the cognition. Our results suggest that combined administration of sarcosine with risperidone may strengthen glutamatergic tone in striatum. Thus, it may be a novel regime to improve psychotic symptoms and cognitive deficit in schizophrenia.
The Interactive 3D BreakAway Map: a navigation and examination aid for multi-floor 3D worlds

In this paper, we propose the Interactive 3D BreakAway Map (I3BAM), an extension of the well-known Worlds In Miniature (R. Stoakley et al., 1995). The I3BAM supports user navigation in virtual buildings as a navigation aid, but also provides a means of examining any floor of a virtual building without having to necessarily navigate it. The aid presents multiple views of a virtual building and provides information about both the internal and external structure of a building. The paper also includes some implementation details and shows an application of the I3BAM to help users learn how to navigate real buildings
Does a Longer Usage Mean Flow Experience? An Evaluation of Learning Experience with Curriculum Sequencing Systems (CSS)

This article reports on a study concerning an optimal learning experience by curriculum sequencing systems (CSS) that is being frequently used in adaptive e-learning systems design. In doing so, we first implemented a CSS application – ‘IT-Tutor’ to teach tertiary students vis-à-vis ‘Computer Network’ – using ‘dynamic sequencing approach (DSA)’. Next, we evaluated the usage of IT-Tutor through Csikszentmihalyi’s flow experience theory, in order to project their learning experience. This empirical study showed that, to some extent, CSS with DSA provided learners with a better learning experience against static-time lined learning path, and the usage pattern generated from this rather different learning experience would be a possible learning outcome that counts. Further, in the experimental context, learning with DSA can be seen to promote learning motivation and ambitious behaviours rather than the other learning environments.