Miracle-dz/UniFAR-FTUs huggingface dataset:
Leveraging Wikipedia Characteristics for Search and Candidate Generation in Question Answering

Most existing Question Answering (QA) systems adopt a type-and-generate approach to candidate generation that relies on a pre-defined domain ontology. This paper describes a type independent search and candidate generation paradigm for QA that leverages Wikipedia characteristics. This approach is particularly useful for adapting QA systems to domains where reliable answer type identification and type-based answer extraction are not available. We present a three-pronged search approach motivated by relations an answer-justifying title-oriented document may have with the question/answer pair. We further show how Wikipedia metadata such as anchor texts and redirects can be utilized to effectively extract candidate answers from search results without a type ontology. Our experimental results show that our strategies obtained high binary recall in both search and candidate generation on TREC questions, a domain that has mature answer type extraction technology, as well as on Jeopardy! questions, a domain without such technology. Our high-recall search and candidate generation approach has also led to high overall QA performance in Watson, our end-to-end system.
Extracting Attributes and their Values from Web pages

We propose a method for extracting attributes and their values from Web pages. Our method makes use of word distributions estimated from plain Web pages. The key idea is to estimate word distribution by consulting ontologies built from HTML tables. In a series of experiments, we show that estimated word distributions are useful for extracting attributes and their values in various kinds of HTML representations other than tables.
On failure classification: the impact of "getting it wrong"

Bug classification is a well-established practice which supports important activities such as enhancing verification and validation (V&V) efficiency and effectiveness. The state of the practice is manual and hence classification errors occur. This paper investigates the sensitivity of the value of bug classification (specifically, failure type classification) to its error rate; i.e., the degree to which misclassified historic bugs decrease the V&V effectiveness (i.e., the ability to find bugs of a failure type of interest). Results from the analysis of an industrial database of more than 3,000 bugs show that the impact of classification error rate on V&V effectiveness significantly varies with failure type. Specifically, there are failure types for which a 5% classification error can decrease the ability to find them by 66%. Conversely, there are failure types for which the V&V effectiveness is robust to very high error rates. These results show the utility of future research aimed at: 1) providing better tool support for decreasing human errors in classifying the failure type of bugs, 2) providing more robust approaches for the selection of V&V techniques, and 3) including robustness as an important criterion when evaluating technologies.
Tracking the Orbital and Superorbital Periods of SMC X-1

The high-mass X-ray binary (HMXB) SMC X-1 demonstrates an orbital variation of ~3.89 days and a superorbital variation with an average length of ~55 days. As we show here, however, the length of the superorbital cycle varies by almost a factor of 2, even across adjacent cycles. To study both the orbital and superorbital variation, we utilize light curves from the Rossi X-Ray Timing Explorer All-Sky Monitor (RXTE ASM). We employ the orbital ephemeris from P. Wojdowski et al. to obtain the average orbital profile, and we show that this profile exhibits complex modulation during noneclipse phases. In addition, a very interesting "bounceback" in X-ray count rate is seen during midorbital eclipse phases, with a softening of the emission during these periods. This bounceback has not been previously identified in pointed observations. We then define a superorbital ephemeris (the phase of the superorbital cycle as a function of date) based on the ASM light curve and analyze the trend and distribution of superorbital cycle lengths. SMC X-1 exhibits a bimodal distribution of these lengths, similar to what has been observed in other systems (e.g., Her X-1), but with more dramatic changes in cycle length. There is some hint, but not conclusive evidence, for a dependence of the superorbital cycle length on the underlying orbital period, as has been observed previously for Her X-1 and Cyg X-2. Using our superorbital ephemeris, we are also able to create an average superorbital profile over the 71 observed cycles, for which we witness overall hardening of the spectrum during low count rate times. We combine the orbital and superorbital ephemerides to study the correlation between the orbital and superorbital variations in the system, but find that the ASM light curve provides insufficient statistics to draw any definitive conclusions on possible correlations.
ARA*+: Improved Path Planning Algorithm Based on ARA*

A* path planning algorithm cannot always guarantee the continuity of a robot's movements when the allocated time is limited, however Anytime Repairing A*(ARA*) can get a sub-optimal solution quickly, and then work on improving the solution until the allocated time expires. This paper proposes a variation of ARA* algorithm (ARA*+) which executes multiple Weighted A* to search the solution. During the first search of ARA*+, Weighted A* with a bigger inflation factor is applied and no state is expanded more than once, in this way, the time needed for finding a sub-optimal solution can be remarkably shortened. Then, Weighted A* will be executed again for better path, by decreasing the inflation factor and reusing the previous planning efforts. Here, with the same inflation factor the expanded states can be used again, and this is different from ARA*, which forbids the expanded states to be expanded again. If the allocated time does not expire, this process will not stop until the optimal solution is found, or the current sub-optimal solution will be regarded as the output. According to our robot path planning experiments, in most cases the number of expanded states in ARA*+ was smaller than that in ARA*, as a result, the time spent to get the optimal solution will be shorter.
Applying an ensemble learning method for improving multi-label classification performance

In recent years, multi-label classification problem has become a controversial issue. In this kind of classification, each sample is associated with a set of class labels. Ensemble approaches are supervised learning algorithms in which an operator takes a number of learning algorithms, namely base-level algorithms and combines their outcomes to make an estimation. The simplest form of ensemble learning is to train the base-level algorithms on random subsets of data and then let them vote for the most popular classifications or average the predictions of the base-level algorithms. In this study, an ensemble learning method is proposed for improving multi-label classification evaluation criteria. We have compared our method with well-known base-level algorithms on some data sets. Experiment results show the proposed approach outperforms the base well-known classifiers for the multi-label classification problem.
Modulation of membrane traffic by mechanical stimuli

[PDF] [Full Text] [Abstract] , March 1, 2008; 59 (4): 861-873. J. Exp. Bot. L. Zonia and T. Munnik tobacco pollen tubes Vesicle trafficking dynamics and visualization of zones of exocytosis and endocytosis in [PDF] [Full Text] [Abstract] , June 1, 2008; 586 (11): 2779-2798. J. Physiol. K. Woo, A. K. Dutta, V. Patel, C. Kresge and A. P. Feranchak biliary epithelial cells through a PKC{zeta}-dependent pathway Fluid flow induces mechanosensitive ATP release, calcium signalling and Cltransport in [PDF] [Full Text] [Abstract] , January 1, 2009; 20 (1): 282-295. Mol. Biol. Cell W. Yu, P. Khandelwal and G. Apodaca Traffic at the Apical Surface of Bladder Umbrella Cells Distinct Apical and Basolateral Membrane Requirements for Stretch-induced Membrane [PDF] [Full Text] [Abstract] , January 1, 2009; 40 (1): 76-82. Am. J. Respir. Cell Mol. Biol. R. C. Geiger, C. D. Kaufman, A. P. Lam, G. R. S. Budinger and D. A. Dean Tubulin Acetylation and Histone Deacetylase 6 Activity in the Lung under Cyclic Load [PDF] [Full Text] [Abstract] , March 13, 2009; 104 (5): 679-687. Circ. Res. E. Deelman and O. Kamp A. M.G. Versteilen, W. J. Paulus, W. H. van Gilst, K. Kooiman, N. de Jong, R. J.P. Musters, L. B. D.M. Meijering, L. J.M. Juffermans, A. van Wamel, R. H. Henning, I. S. Zuhorn, M. Emmer, Induction of Endocytosis and Pore Formation Ultrasound and Microbubble-Targeted Delivery of Macromolecules Is Regulated by
High-spin binary black hole mergers

We study identical mass black hole binaries with spins perpendicular to the binary's orbital plane. These binaries have individual spins ranging from $s/{m}^{2}=\ensuremath{-}0.90$ to 0.90, (${s}_{1}={s}_{2}$ in all cases) which is near the limit possible with standard Bowen-York puncture initial data. The extreme cases correspond to the largest initial spin simulations to date. Our results expand the parameter space covered by Rezzolla et al., and when combining both data sets, we obtain estimations for the minimum and maximum values for the intrinsic angular momenta of the remnant of binary black hole mergers of $J/{M}^{2}=0.341\ifmmode\pm\else\textpm\fi{}0.004$ and $0.951\ifmmode\pm\else\textpm\fi{}0.004$, respectively. Note, however, that these values are reached through extrapolation to the singular cases $|{s}_{1}|=|{s}_{2}|=1$ and thus remain as estimates until full-fledged numerical simulations provide confirmation.
International Journal of Multidisciplinary and Current Research the Detail Survey of Anomaly/outlier Detection Methods in Data Mining

Anomaly detection is an important problem that has been researched within diverse research areas and application domains. Many real-world applications such as intrusion or credit card fraud detection require an effective and efficient framework to identify deviated data instances. This template provides an easier and succinct understanding and comparisons between each of the outlier detection techniques for different applications. And introduce a new efficient approach which detects outlier with imperfect labels.
The algebra of secondary homotopy operations in ring spectra

In this paper we develop a theory of stable homotopy 2‐groups for spectra which is compatible with the smash product on the structured models for the stable homotopy category, therefore the homotopy 2‐groups of a ring spectrum form a 2‐ring, etc. For instance, the primary algebraic model of a ring spectrum R is the ring π*R of homotopy groups. We introduce the secondary model π*, *R which has the structure of a secondary analogue of a ring. The homology of π*, *R is π*R and triple Massey products in π*, *R coincide with triple Toda brackets in π*R. We also describe the secondary model π*, *Q of a commutative ring spectrum Q from which we derive the cup‐one square operation in the graded commutative ring π*Q. As an application we obtain for each ring spectrum R new derivations of the ring π*R.
A logical foundation for ontology representation in NKI

A formal representation of ontologies is proposed, based on F-logic and O-logic; and the works in the building of ontologies in NKI. An ontology includes class frames, slot frames, class-slot frames, object frames and axioms. The value restrictions of slots are defined in slot frames. For each slot and each class, there is a class-slot frame representing the specific value restrictions of the slot when defining the class; and the relations between class-slot frames and slot frames are discussed. For a slot in a class frame, its values are inherited to its subclasses without blocking; and its default values are inherited to its subclasses taking overriding, revising and conflict resolution into account. After giving the formal representation of ontologies, the semantics of ontologies are discussed, and main results are presented.
Clustering Gene Expression Data Based on Harmony Search and K-harmonic Means

Clustering is one of the most commonly data explorer techniques in Data Mining. K-harmonic means clustering (KHM) is an extension of K-means (KM) and solves the problem of KM initialization using a built-in boosting function. However, it is also suffering from running into local optima. As a stochastic global optimization technique, harmony search (HS) can solve this problem. HS-based KHM, HSKHM not only helps KHM clustering escaping from local optima but also overcomes the shortcoming of slow convergence speed of HS. In this paper, we proposed a hybrid data-clustering algorithm, HSKHM. The experimental results on four real gene expression datasets indicate that HSKHM is superior KHM and HS in most cases. The HSKHM algorithm not only improves the convergence speed of HS but also helps KHM escaping from local optima.
Injections of an opioid antagonist into the locus coeruleus and periaqueductal gray but not the amygdala precipitates morphine withdrawal in the 7‐day‐old rat

Opiate withdrawal behaviors in the infant differ from those of the adult. The neural circuitry underlying opioid withdrawal in the adult rat is well defined and includes the locus coeruleus (LC) and periaqueductal gray (PAG), with a minor role of the amygdala. Because the different behaviors that constitute the infant syndrome may be mediated by different neural circuits, we tested the hypothesis that these three sites are involved in opiate withdrawal. Pups were injected with morphine from day 1–6 after birth (b.i.d.) and on the morning of the seventh day. Withdrawal was then elicited by local injection of the opioid antagonist methylnaloxonium into the LC, PAG, or amygdala. Withdrawal signs were precipitated in a dose‐dependent manner following injection into the LC or PAG, but not the amygdala. The withdrawal behaviors elicited from the LC and PAG included both the same and different behaviors. The results support the hypothesis that the neural circuitry mediating opiate withdrawal behaviors is similar in infant and adult animals, but the behaviors expressed are age‐specific. Synapse 39:139–151, 2001. © 2001 Wiley‐Liss, Inc.
Simultaneous Consideration of TQM and ISO 9000 on Performance and Motivation: An Empirical Study of Spanish Companies

After more than two decades since quality became part of managers’ everyday lexicon, total quality management (TQM) and ISO 9000 have taken the centre stage. However, there has been much debate about how they might be related to each other. This research is a new contribution to the knowledge on the relationships between TQM and ISO 9000, and it addresses their implications on performance and motivations for implementation. While past studies have considered them separately, we study them together in one study. As might be expected, both TQM and ISO 9000 lead to improvement in performance. However, it appears that internal motivation to implement ISO 9000 is associated with high performance, whereas external motivation is not. Further, companies with high internal motivation for ISO 9000 naturally show a high level of TQM practices. We use institutional theory and resource-based views to consider the internal versus external motivations for implementing ISO 9000. The data for this research have been obtained from a large sample of Spanish industrial companies. Longitudinal objective data have also been used. r 2007 Elsevier B.V. All rights reserved.
The Implications of Proteolytic Background for Shotgun Proteomics*S

The analysis by liquid chromatography coupled to tandem mass spectrometry of complex peptide mixtures, generated by proteolysis of protein samples, is the main proteomics method used today. The approach is based on the assumption that each protein present in a sample reproducibly and predictably generates a relatively small number of peptides that can be identified by mass spectrometry. In this study this assumption was examined by a targeted peptide sequencing strategy using inclusion lists to trigger peptide fragmentation attempts. It was found that the number of peptides observed from a single protein is at least one order of magnitude greater than previously assumed. This unexpected complexity of proteomics samples implies substantial technical challenges, explains some perplexing results in the proteomics literature, and prompts the need for developing alternative experimental strategies for the rapid and comprehensive analysis of proteomes.
Factor Analysis Back Ends for MLLR Transforms in Speaker Recognition

The purpose of this work is to show how recent developments in cepstral-based systems for speaker recognition can be leveraged for the use of Maximum Likelihood Linear Regression (MLLR) transforms. Speaker recognition systems based on MLLR transforms have shown to be greatly beneficial in combination with standard systems, but most of the advances in speaker modeling techniques have been implemented for cepstral features. We show how these advances, based on Factor Analysis, such as eigenchannel and ivector, can be easily employed to achieve very high accuracy. We show that they outperform the current state-of-the-art MLLR-SVM system that SRI submitted during the NIST SRE 2010 evaluation. The advantages of leveraging the new approaches are manyfold: the ability to process a large amount of data, working in a reduced dimensional space, importing any advances made for cepstral systems to the MLLR features, and the potential for system combination at the ivector level.
A Poissonian explanation for heavy tails in e-mail communication

Patterns of deliberate human activity and behavior are of utmost importance in areas as diverse as disease spread, resource allocation, and emergency response. Because of its widespread availability and use, e-mail correspondence provides an attractive proxy for studying human activity. Recently, it was reported that the probability density for the inter-event time τ between consecutively sent e-mails decays asymptotically as τ−α, with α ≈ 1. The slower-than-exponential decay of the inter-event time distribution suggests that deliberate human activity is inherently non-Poissonian. Here, we demonstrate that the approximate power-law scaling of the inter-event time distribution is a consequence of circadian and weekly cycles of human activity. We propose a cascading nonhomogeneous Poisson process that explicitly integrates these periodic patterns in activity with an individual's tendency to continue participating in an activity. Using standard statistical techniques, we show that our model is consistent with the empirical data. Our findings may also provide insight into the origins of heavy-tailed distributions in other complex systems.
Amphetamine Blocks Long-Term Synaptic Depression in the Ventral Tegmental Area

The mesolimbic dopamine system is essential for reward-seeking behavior, and drugs of abuse are thought to usurp the normal functioning of this pathway. A growing body of evidence suggests that glutamatergic synapses on dopamine neurons in the ventral tegmental area (VTA) are modified during exposure to addictive drugs, producing sensitization, a progressive augmentation in the rewarding properties of psychostimulant drugs with repeated exposure. We have tested the hypothesis that psychostimulant exposure interferes with the synaptic plasticity of glutamatergic inputs to the VTA. We find that excitatory synapses onto VTA dopamine neurons exhibit long-term depression (LTD) in response to low-frequency stimulation and modest depolarization. LTD in the VTA is NMDA receptor-independent but is dependent on intracellular Ca2+ and can be induced by driving Ca2+ into the dopamine neuron. Brief exposure to amphetamine entirely blocks LTD at glutamatergic synapses in the VTA, by releasing endogenous dopamine that acts at D2 dopamine receptors. The block of LTD is selective, because amphetamine has no effect on hippocampal LTD. The LTD we have discovered in the VTA is likely to be an important component of excitatory control of the reward pathway; amphetamine will inhibit LTD, removing this normal brake on the glutamatergic drive to dopamine neurons. This effect of amphetamine represents an important mechanism by which normal function of the brain reward system may be impaired during substance abuse.
Endogenous sex hormones and the development of type 2 diabetes in older men and women: the Rancho Bernardo study.

OBJECTIVE To determine the prospective association between endogenous sex hormones and the development of type 2 diabetes in older men and women. RESEARCH DESIGN AND METHODS A standardized medical history was obtained, an oral glucose tolerance test was performed, and plasma samples for sex hormones and covariates were collected from ambulatory, community-dwelling men and women at baseline from 1984 to 1987. Approximately 8 years later (1992-1996), another medical history was obtained, an oral glucose tolerance test was performed, fasting and 2-h insulin levels were measured, and the homeostasis model assessment for insulin resistance (HOMA-IR) was evaluated. This report is based on the 294 men and 233 women, aged 55-89 years, who completed both visits and who did not have diabetes as determined by history or glucose tolerance test at baseline, as well as women who were postmenopausal and not taking replacement estrogen. RESULTS In age-adjusted correlation analyses, total testosterone was inversely and significantly related to subsequent levels of fasting and postchallenge glucose and insulin in men, whereas bioavailable testosterone and bioavailable estradiol were positively and significantly related to fasting and postchallenge glucose and insulin in women (all P <0.05). There was similar significant association with insulin resistance (HOMA-IR) in unadjusted and multiply adjusted analyses (P <0.05). There were 26 men and 17 women with new (incident) diabetes. The odds for new diabetes were 2.7 (95% CI 1.1-6.6) for men in the lowest quartile of total testosterone and 2.9 (1.1-8.4) for women in the highest quartile of bioavailable testosterone. CONCLUSIONS Low testosterone levels in men and high testosterone levels in women predict insulin resistance and incident type 2 diabetes in older adults.
Ontology-Based User Modeling for E-Commerce System

User modeling, often addressed as user profile and a simple way of capturing his/her preferences, plays key roles in marketing and personalized services in E-commerce. Due to its powerful knowledge representation and inference mechanism, ontology-based user modeling is emerging as a natural choice to represent knowledge about users in E-commerce context. This paper has presented ontology-based user modeling system, and relies on user ontology to provide customized services in the context of E-commerce. A generic framework of implicit and explicit ontology-based user modeling is presented and described using Semantic Web technology, i.e. OWL specification, which can improve the quality of returned information for user's queries.
Energy recovery DC/AC converter for piezoelectric transformer

Piezoelectric transformers have been used successfully in DC/AC or DC/DC converter. However, the use of piezoelectric transformers presents a major challenges for power electronic design: the capacitive nature of such devices makes their use delicate as the instantaneous power may be much greater than the average effective power. Due to this challenge, conventional drive circuits, especially inductor, become too bulky. This work describes a converter suitable to drive piezoelectric transformer with low inductor. The proposed converter is a DC/AC structure, which is capable of producing a unipolar square voltage. The circuit provides for recovery of the energy stored on the clamped capacitance back to the primary power supply when the transformer is de-energized. In our design, an auxiliary shunt circuits are connected to the input terminal. The proposed structure of both theoretical and experimental validations has demonstrated the effectiveness of the proposed technique for recovery energy.