Miracle-dz/UniFAR-FTUs huggingface dataset:
Centering: A Framework for Modeling the Local Coherence of Discourse

This paper concerns relationships among focus of attention, choice of referring expression, and perceived coherence of utterances within a discourse segment. It presents a framework and initial theory of centering intended to model the local component of attentional state. The paper examines interactions between local coherence and choice of referring expressions; it argues that differences in coherence correspond in part to the inference demands made by different types of referring expressions, given a particular attentional state. It demonstrates that the attentional state properties modeled by centering can account for these differences.
EFFICIENT MINING OF HIGH UTILITY ITEMSETS FROM TRANSACTIONAL DATABASES

In this paper, we would like to show you the working of Hadoop and MapReduce in terms of Data mining. There were many methods proposed earlier for this purpose. Data mining is concerned with analysis of large volumes of data to automatically discover interesting regularities or relationships which in turn leads to better understanding of the underlying processes. The primary goal is to discover hidden patterns, unexpected trends in the data. Data mining activities uses combination of techniques from database technologies, statistics, artificial intelligence and machine learning. Methods like Apriori algorithm, Frequent pattern mining were implemented for this purpose which were not very efficient in terms of time, space and certain parameters like weighted items. These limitations were overcome by bringing into picture the concept of Hadoop and MapReduce.
Adaptive Peer to Peer Resource Discovery in Grid Computing Based on Reinforcement Learning

Grid computing provides a distributed computing environment which supports high performance and data intensive applications by enabling the sharing and selecting various resources. In grid environment resources are heterogeneous and geographically distributed. By receiving a resource request the resource discovery mechanism should return an appropriate resource if there exist one. Resource discovery is a challenging problem because of the heterogeneity and distribution of resources. The centralized and hierarchical resource discovery mechanisms are not suitable for large scale and dynamic resources. On the other hand peer to peer systems are successful in distributed computing because of their scalability and robustness. In this paper, we propose an adaptive peer to peer resource discovery algorithm using reinforcement learning for grid computing that can be used for multi resource requests. The algorithm achieves the most suitable node that can satisfy the requested resource by using the past experience of agents. We compare our model with random walk resource discovery through simulation and the results show that the proposed algorithm provides higher success rate, less message passing and shorter response time. Also the algorithm leads to load balancing in whole grid. According to results our algorithm has a higher performance in large scale grids.
Scene flow based stereo augmentation reconstruction

In this paper, an effective technique is presented to reconstruct an accurate and reliable 3D surface model from multi-view stereo. Different from classical means, we investigate to integrate stereo and motion analysis approach in which optical flow-scene flow framework is involved. In this scheme, reconstruction is decoupled into two stages. Firstly, depth of feature points is recovered and in turn is used for building an intermediate polygonal mesh; Secondly, projection feedback on comparison views, which is generated on assumption of the established coarse mesh model, is carefully introduced to deform the primitive mesh model so as to improve its quality dramatically. The discrepancy of observation on comparison views and the corresponding predictive feedback is quantitatively evaluated by optical flow field and is employed to derive the corresponding scene flow vector field subsequently, which is then used for surface deformation. As optical flow vector field estimation outperforms traditional dense disparity for its inherent advantage of being robust to illumination change and being optimized and smoothed in global sense, the deformed surface can be improved in accuracy, which is firmly validated by encouraging experimental results.
Spreading the load using consistent hashing: a preliminary report

Consistent hashing can be used to assign objects to nodes in a distributed system. It has been used by several distributed systems including Chord, Pastry, and Tornado because of its efficient handling of node failure and repair. In this paper we analyze how well consistent hashing does at evenly distributing objects among the nodes in the system. We also extend current consistent hashing algorithms to allow for dynamic load balancing while retaining the good properties of consistent hashing. Finally we analyze our extensions using both probabilistic analysis and simulations. The algorithms derived appear to achieve much better load balancing.
Tumor-associated antigen CAPERα and microvessel density in hepatocellular carcinoma

Purpose CAPERα, a tumor-associated antigen, was identified from a cDNA clone with autoantibody from a patient with hepatocellular carcinoma (HCC). It has been implicated, by way of alternative splicing of VEGF pre-mRNA, in the regulation of microvessel formation in Ewing's sarcoma. In this study, we looked for possible association of alterations in CAPERα with microvessel density in HCC. Methods Enzyme-linked immunosorbent assay using recombinant CAPERα as antigen were used to detect antibody against CAPERα. Immunohistochemistry (IHC) on liver sections was performed to analyze expression profiles of CAPERα, VEGF and CD34 in HCC and control tissues and was further used to assess the correlation of expression among CAPERα, VEGF and CD34 in HCC development. Results Autoantibody to CAPERα was highest in HCC (22/76, 28.9%), not detected in prostate cancer (0/79) and at 3.4% (3/88) in breast cancer. In immunohistochemical analysis of grades II and III HCC tissues, significantly decreased immunostaining for CAPERα was observed and this correlated directly with decreased immunostaining for VEGF (R=0.534, P=0.0003). Using CD34 immunostaining for detecting newly formed microvessels, strong staining was observed in grades II and III HCC. Normal liver sections, all of which have high expression of CAPERα were totally negative for CD34 immunostaining. A significant inverse correlation was seen between CAPERα and CD34 immunostaining (R=−0.481, P=0.0012). Conclusions Decreased expression of CAPERα appears to be correlated with appearance of microvessels. It would be of interest to elucidate the cause of altered CAPERα since new formation of microvessels is important in progression of HCC.
The CoRoT primary target HD 52265: models and seismic tests

Aims. HD 52265 is the only known exoplanet-host star selected as a main target for the seismology programme of the CoRoT satellite. As such, it will be observed continuously during five months, which is of particular interest when studying planetary systems. This star was misclassified as a giant in the Bright Star Catalog, while it is more probably on the main-sequence or at the beginning of the subgiant branch. We performed an extensive analysis of this star, showing how asteroseismology may lead to a precise determination of its external parameters and internal structure. Methods. We first reviewed the observational constraints on the metallicity, the gravity, and the effective temperature derived from the spectroscopic observations of HD 52265. We also derived its luminosity using the Hipparcos parallax. We computed the evolutionary tracks for models of various metallicities that cross the relevant observational error boxes in the gravity-effective temperature plane. We selected eight different stellar models that satisfy the observational constraints, computed their p-modes frequencies, and analysed specific seismic tests. Results. The possible models for HD 52265, which satisfy the constraints derived from the spectroscopic observations, are different in both their external and internal parameters. They lie either on the main sequence or at the beginning of the subgiant branch. The differences in the models lead to quite different properties of their oscillation frequencies. We give evidence of an interesting specific behaviour of these frequencies in the case of helium-rich cores: the “small separations” may become negative and give constraints on the size of the core. We expect that the observations of this star by the CoRoT satellite will allow a choice between these possible models.
Is individual consistency in body mass and reproductive decisions linked to individual specialization in foraging behavior in a long‐lived seabird?

Abstract Individual specialization in diet or foraging behavior within apparently generalist populations has been described for many species, especially in polar and temperate marine environments, where resource distribution is relatively predictable. It is unclear, however, whether and how increased environmental variability – and thus reduced predictability of resources – due to global climate change will affect individual specialization. We determined the within‐ and among‐individual components of the trophic niche and the within‐individual repeatability of δ13C and δ15N in feathers and red blood cells of individual female southern rockhopper penguins (Eudyptes chrysocome) across 7 years. We also investigated the effect of environmental variables (Southern Annular Mode, Southern Oscillation Index, and local sea surface temperature anomaly) on the isotopic values, as well as the link between stable isotopes and female body mass, clutch initiation dates, and total clutch mass. We observed consistent red blood cell δ13C and δ15N values within individuals among years, suggesting a moderate degree of within‐individual specialization in C and N during the prebreeding period. However, the total niche width was reduced and individual specialization not present during the premolt period. Despite significant interannual differences in isotope values of C and N and environmental conditions, none of the environmental variables were linked to stable isotope values and thus able to explain phenotypic plasticity. Furthermore, neither the within‐individual nor among‐individual effects of stable isotopes were found to be related to female body mass, clutch initiation date, or total clutch mass. In conclusion, our results emphasize that the degree of specialization within generalist populations can vary over the course of 1 year, even when being consistent within the same season across years. We were unable to confirm that environmental variability counteracts individual specialization in foraging behavior, as phenotypic plasticity in δ13C and δ15N was not linked to any of the environmental variables studied.
Virtual Machines Cooperation for Impatient Jobs under Cloud Paradigm

The increase on the demand of IT resources diverts the enterprises to use the cloud as a cheap and scalable solution. Cloud computing promises achieved by using the virtual machine as a basic unite of computation. However, the virtual machine pre-defined settings might be not enough to handle jobs QoS requirements. This paper addresses the problem of mapping jobs have critical start deadlines to virtual machines that have predefined specifications. These virtual machines hosted by physical machines and shared a fixed amount of bandwidth. This paper proposed an algorithm that uses the idle virtual machines bandwidth to increase the quote of other virtual machines nominated as executors to urgent jobs. An algorithm with empirical study have been given to evaluate the impact of the proposed model on impatient jobs. The results show the importance of dynamic bandwidth allocation in virtualized environment and its affect on throughput metric. Keywords—Insufficient bandwidth, virtual machine, cloud provider, impatient jobs.
Driving Cessation and Dementia: Results of the Prospective Registry on Dementia in Austria (PRODEM)

Objective To assess the influence of cognitive, functional and behavioral factors, co-morbidities as well as caregiver characteristics on driving cessation in dementia patients. Methods The study cohort consists of those 240 dementia cases of the ongoing prospective registry on dementia in Austria (PRODEM) who were former or current car-drivers (mean age 74.2 (±8.8) years, 39.6% females, 80.8% Alzheimer’s disease). Reasons for driving cessation were assessed with the patients’ caregivers. Standardized questionnaires were used to evaluate patient- and caregiver characteristics. Cognitive functioning was determined by Mini-Mental State Examination (MMSE), the CERAD neuropsychological test battery and Clinical Dementia Rating (CDR), activities of daily living (ADL) by the Disability Assessment for Dementia, behavior by the Neuropsychiatric Inventory (NPI) and caregiver burden by the Zarit burden scale. Results Among subjects who had ceased driving, 136 (93.8%) did so because of “Unacceptable risk” according to caregiver’s judgment. Car accidents and revocation of the driving license were responsible in 8 (5.5%) and 1(0.7%) participant, respectively. Female gender (OR 5.057; 95%CI 1.803–14.180; p = 0.002), constructional abilities (OR 0.611; 95%CI 0.445–0.839; p = 0.002) and impairment in Activities of Daily Living (OR 0.941; 95%CI 0.911–0.973; p<0.001) were the only significant and independent associates of driving cessation. In multivariate analysis none of the currently proposed screening tools for assessment of fitness to drive in elderly subjects including the MMSE and CDR were significantly associated with driving cessation. Conclusion The risk-estimate of caregivers, but not car accidents or revocation of the driving license determines if dementia patients cease driving. Female gender and increasing impairment in constructional abilities and ADL raise the probability for driving cessation. If any of these factors also relates to undesired traffic situations needs to be determined before recommendations for their inclusion into practice parameters for the assessment of driving abilities in the elderly can be derived from our data.
Improving Hierarchical Critical Path Analysis Performance

Hierarchical critical path analysis is capable of localizing parallelism to varying granularities in a program, but is computationally expensive. Consequently, the memory and performance overheads are major impediments towards mainstream acceptance and usage. This paper examines two techniques to allocate and utilize memory more efficiently and compiler analyses and optimizations targeted at improving the performance of hierarchical critical path analysis. On the presented benchmarks, these techniques improve memory and performance overheads as high as 1.95× and 1.62× and on average 1.27× and 1.29× respectively.
Tolerating malicious resources to ensure safe computations in grid systems

Grid computing has recently seen a great importance in diverse applications domains of scientific, industrial, and commercial activities, which demand huge computational power. Unlike traditional cluster computing, large scale grids permit the sharing of grid resources spread through different administrative sites autonomy. The distributed and dynamic features of grid resources, their architectures heterogeneity, and unreliable interconnection network increases the probability of attacks and malicious behavior of grid resources. In Grid applications, reliability and security assurance of execution are two basic requirements. Thus, it is necessary to guarantee that, among the shared grid resources, there are no malicious behaviors interested in invalidating or corrupting the job results. In order to ensure reliable and safe jobs computation in grid systems, we have proposed a new approach for tolerating malicious grid resources by using reputation to improve the efficiency of majority voting mechanisms. The grid broker service investigates the trustworthy of the grid resources that are used in the voting procedure; this investigation is based on reputation management system which maintains a reputation value for each grid resource based on its historical behavior. The validation of the result is then decided based on the reputation level of the grid resources.
The Obscuring Starburst of NGC 6221 and Implications for the Hard X-Ray Background

We present NGC 6221 as a case study of "X-ray-loud composite galaxies," which appear similar to starbursts at optical wavelengths and resemble traditional active galactic nuclei in X-rays. The net optical spectrum of NGC 6221 is properly characterized as a starburst galaxy, but in X-rays, NGC 6221 is similar to Seyfert 1 galaxies, exhibiting a power-law continuum spectrum, a broad Fe Kα line, and continuum variability on timescales of days and years. High-resolution images reveal that the detected active nucleus is relatively weak, not only at optical, but also at near-infrared wavelengths. An obscuring starburst, in which the interstellar gas and dust associated with the starburst conceal the active nucleus, accounts for these peculiar features. We demonstrate quantitatively that obscuration by column density NH = 1022 cm-2 combined with relatively weak intrinsic nuclear activity can produce an optical spectrum that is characteristic of the surrounding starburst alone. While optical surveys would not identify the active nuclei that make these galaxies significant X-ray sources, such galaxies may, in fact, be important contributors to the X-ray background.
The Computerized Table Setting Test for Detecting Unilateral Neglect

Background Patients with unilateral neglect fail to respond normally to stimuli on the left side. To facilitate the evaluation of unilateral spatial neglect, we developed a new application that runs on a tablet device and investigated its feasibility in stroke patients. Methods We made the computerized table setting test (CTST) to run on the tablet computer. Forty acute ischemic stroke patients (20 patients with right hemispheric infarction with neglect, 10 patients with right hemispheric infarction without neglect, and 10 patients with left hemispheric infarction) and 10 healthy controls were prospectively enrolled to validate the CTST. The test requires subjects to set a table by dragging 12 dishes located below the table on the tablet screen. The horizontal deviation of the 12 dishes from the midline of the table, the selection tendency measured by the sequence of the dish selection, and the elapsed time for table setting were calculated automatically. Results Parameters measured by the CTST were correlated with the results of conventional neglect tests. The horizontal deviation was significantly higher in patients with right hemispheric infarction with neglect compared with the other groups. The selection tendency and elapsed time also were significantly different in patients with right hemispheric infarction with neglect compared with the left hemispheric infarction and control groups, but were similar to those with right hemispheric infarction without neglect. Conclusions The CTST is feasible to administer and comparable with conventional neglect tests. This new application may be useful for the initial diagnosis and follow-up of neglect patients.
The Co-integrating Relationship between Stock Index and Futures Prices

The paper examines five International stock index spot and futures data to verify whether there exists long-term steady relationship between the index spot and futures prices. Based on the co-integration theory and error correction model (ECM), conclusions are drawn that index spot and futures are co-integrated in most cases and it is possible to do the corresponding short-term dynamic adjustment for reaching new equilibrium in next period.
KNOW THE STAR, KNOW THE PLANET. I. ADAPTIVE OPTICS OF EXOPLANET HOST STARS

The results of an adaptive optics survey of exoplanet host stars for stellar companions are presented. We used the Advanced Electro-Optical System telescope and its adaptive optics system to collect deep images of the stars in the I band. Sixty-two exoplanet host stars were observed and fifteen multiple star systems were resolved. Of these eight are known multiples, while seven are new candidate binaries. For all binaries, we measured the relative astrometry of the pair and the differential magnitude in the I band. We improved the orbits of HD 19994 and τ Boo. These observations will provide improved statistics on the duplicity of exoplanet host stars and provide an increased understanding of the dynamics of known binary star exoplanet hosts.
Online Trust in E-tailing : A Conceptual Framework , Implications , and Future Directions

Online trust is important in both business-to-business and business-to-consumer e-business. This paper focuses on the impact of trust in online retailing (e-tailing). Based on a review of selected studies, we articulate a conceptual framework of trust in e-tailing including its antecedents, and consequences, and propose some promising future research avenues in online trust. This paper will help e-tailers better understand the online trust, thereby enabling them to build more trustworthy Web sites. Keyword E-tailing, Marketing, Review, Trust*
Aging Impairs Protein-Synthesis-Dependent Long-Term Memory in Drosophila

Although aging is known to impair intermediate-term memory in Drosophila, its effect on protein-synthesis-dependent long-term memory (LTM) is unknown. We show here that LTM is impaired with age, not due to functional defects in synaptic output of mushroom body (MB) neurons, but due to connectivity defects of dorsal paired medial (DPM) neurons with their postsynaptic MB neurons. GFP reconstitution across synaptic partners (GRASP) experiments revealed structural connectivity defects in aged animals of DPM neurons with MB axons in the α lobe neuropil. As a consequence, a protein-synthesis-dependent LTM trace in the α/β MB neurons fails to form. Aging thus impairs protein-synthesis-dependent LTM along with the α/β MB neuron LTM trace by lessening the connectivity of DPM and α/β MB neurons.
An Efficient Monte Carlo Method for Mobile Robot Localization

Traditional Kalman filter or extended Kalman filter has been used broadly for mobile robot localization. However in some circumstances, its prior Gaussian hypothesis becomes unacceptable and limits the localization precision. For this reason, Monte Carlo method is used for the robot localization. In this paper, the algorithm implementation is advanced after introducing the basic theory of Monte Carlo method. According to the characteristics of robot movement, a new resample method is presented based on adapting the sample size and their particles space distribution. Finally experiments confirm the advantage of boosting accuracy and convergence speed about this idea