Miracle-dz/UniFAR-FTUs huggingface dataset:
Stitching Web Tables for Improving Matching Quality

HTML tables on web pages ("web tables") cover a wide variety of topics. Data from web tables can thus be useful for tasks such as knowledge base completion or ad hoc table extension. Before table data can be used for these tasks, the tables must be matched to the respective knowledge base or base table. The challenges of web table matching are the high heterogeneity and the small size of the tables. Though it is known that the majority of web tables are very small, the gold standards that are used to compare web table matching systems mostly consist of larger tables. In this experimental paper, we evaluate T2K Match, a web table to knowledge base matching system, and COMA, a standard schema matching tool, using a sample of web tables that is more realistic than the gold standards that were previously used. We find that both systems fail to produce correct results for many of the very small tables in the sample. As a remedy, we propose to stitch (combine) the tables from each web site into larger ones and match these enlarged tables to the knowledge base or base table afterwards. For this stitching process, we evaluate different schema matching methods in combination with holistic correspondence refinement. Limiting the stitching procedure to web tables from the same web site decreases the heterogeneity and allows us to stitch tables with very high precision. Our experiments show that applying table stitching before running the actual matching method improves the matching results by 0.38 in F1-measure for T2K Match and by 0.14 for COMA. Also, stitching the tables allows us to reduce the amount of tables in our corpus from 5 million original web tables to as few as 100,000 stitched tables.
A Directional-Change Events Approach for Studying Financial Time Series

Financial markets witness high levels of activity at certain times, but remain calm at others. This makes the flow of physical time discontinuous. Therefore using physical time scales for studying financial time series, runs the risk of missing important activities. An alternative approach is the use of an event-based time that captures periodic activities in the market. In this paper, we use a special type of event, called a directional-change event, and show its usefulness in capturing periodic market activities. Our study confirms that the length of the price curve coastline as defined by directional-change events, turns out to be a long one.
Novel Structural Components of the Ventral Disc and Lateral Crest in Giardia intestinalis

Giardia intestinalis is a ubiquitous parasitic protist that is the causative agent of giardiasis, one of the most common protozoan diarrheal diseases in the world. Giardia trophozoites attach to the intestinal epithelium using a specialized and elaborate microtubule structure, the ventral disc. Surrounding the ventral disc is a less characterized putatively contractile structure, the lateral crest, which forms a continuous perimeter seal with the substrate. A better understanding of ventral disc and lateral crest structure, conformational dynamics, and biogenesis is critical for understanding the mechanism of giardial attachment to the host. To determine the components comprising the ventral disc and lateral crest, we used shotgun proteomics to identify proteins in a preparation of isolated ventral discs. Candidate disc-associated proteins, or DAPs, were GFP-tagged using a ligation-independent high-throughput cloning method. Based on disc localization, we identified eighteen novel DAPs, which more than doubles the number of known disc-associated proteins. Ten of the novel DAPs are associated with the lateral crest or outer edge of the disc, and are the first confirmed components of this structure. Using Fluorescence Recovery After Photobleaching (FRAP) with representative novel DAP::GFP strains we found that the newly identified DAPs tested did not recover after photobleaching and are therefore structural components of the ventral disc or lateral crest. Functional analyses of the novel DAPs will be central toward understanding the mechanism of ventral disc-mediated attachment and the mechanism of disc biogenesis during cell division. Since attachment of Giardia to the intestine via the ventral disc is essential for pathogenesis, it is possible that some proteins comprising the disc could be potential drug targets if their loss or disruption interfered with disc biogenesis or function, preventing attachment.
Biology and Treatment of Paget's Disease of Bone

Paget's disease of bone (PDB) is a common skeletal disorder characterized by increased and disorganized bone remodeling affecting one or more skeletal sites. Although some patients are asymptomatic others develop complications such as bone pain, deformity, nerve compression syndromes, and fragility fractures. Genetic factors play an important role in the pathogenesis of PDB and there is strong evidence that susceptibility is determined by variants within or close to genes that regulate osteoclast function. Environmental factors also play a key role but the nature of the environmental triggers is less clear. Bisphosphonates are a highly effective treatment for the elevations in bone turnover that are characteristic of PDB but it is unclear at present if they alter the natural history of the disease. Here, we review the epidemiology, clinical, cellular, and molecular abnormalities in PDB as well as environmental and genetic triggers, and current available treatment options. J. Cell. Biochem. 117: 289–299, 2016. © 2015 Wiley Periodicals, Inc.
Definition and Complexity of Some Basic Metareasoning Problems

In most real-world settings, due to limited time or other resources, an agent cannot perform all potentially useful deliberation and information gathering actions. This leads to the metareasoning problem of selecting such actions. Decision-theoretic methods for metareasoning have been studied in AI, but there are few theoretical results on the complexity of metareasoning. We derive hardness results for three settings which most real metareasoning systems would have to encompass as special cases. In the first, the agent has to decide how to allocate its deliberation time across anytime algorithms running on different problem instances. We show this to be ATP-complete. In the second, the agent has to (dynamically) allocate its deliberation or information gathering resources across multiple actions that it has to choose among. We show this to be AfP-hard even when evaluating each individual action is extremely simple. In the third, the agent has to (dynamically) choose a limited number of deliberation or information gathering actions to disambiguate the state of the world. We show that this is AfP-hard under a natural restriction, and PSP ACE hard in general.
Weyl's law and quantum ergodicity for maps with divided phase space

For a general class of unitary quantum maps, whose underlying classical phase space is divided into several invariant domains of positive measure, we establish analogues of Weyl's law for the distribution of eigenphases. If the map has one ergodic component, and is periodic on the remaining domains, we prove the Schnirelman–Zelditch–Colin de Verdiere theorem on the equidistribution of eigenfunctions with respect to the ergodic component of the classical map (quantum ergodicity). We apply our main theorems to quantized linked twist maps on the torus. In the appendix, Zelditch connects these studies to some earlier results on 'pimpled spheres' in the setting of Riemannian manifolds. The common feature is a divided phase space with a periodic component.
Recent advances in the pathophysiology of acute pain.

The peripheral receptors of the sensory systems have transduction mechanisms that ensure maximal sensitivity to only a small spectrum of the wide range of stimuli that impinge upon them. Because there is a minimal overlap in sensitivity between the receptors of the different sensory systems, each is specialized and possesses its own "specific" or "adequate" stimulus. Maintaining this receptor-generated specificity, sensory pathways in the central nervous system are, to a considerable extent, arranged so that inputs from similar classes of receptor run through neural networks that are closely aligned anatomically. This enables functionally discrete systems such as the visual, auditory and tactile sensory systems to be seen to be structurally distinct. At each level of the neuraxis where sensory information is relayed, complex processing and modulation occurs to assist in denning the location, onset, duration, intensity and dynamic properties of a stimulus. Ultimately, activation of the highest levels of the nervous system may produce a conscious awareness of the stimulus, either as a relatively pure sensation or as a complex hybrid one resulting from parallel sensory inputs. In this way photons falling upon the retina are unambiguously perceived as light, movement of hair cells in the cochlea as sound and deformation of mechanoreceptor terminals in the skin as touch. Is pain the perceptual consequence of the activation of a specialized sensory system that resembles in its neural organization the visual, auditory or tactile sensory systems ? This is not an abstruse academic issue, but the key to understanding the pathophysiology of pain. The current view of many basic scientists and clinicians is that there is a sensory system specific for pain, which
Classical Cepheid Pulsation Models. IX. New Input Physics

We constructed several sequences of classical Cepheid envelope models at solar chemical composition (Y = 0.28, Z = 0.02) to investigate the dependence of the pulsation properties predicted by linear and nonlinear hydrodynamic models on input physics. To study the dependence on the equation of state (EOS) we performed several numerical experiments by using the simplified analytical EOS originally developed by Stellingwerf and the recent analytical EOS developed by Irwin. Current findings suggest that the pulsation amplitudes, as well as the topology of the instability strip, marginally depend on the adopted EOS. To compromise between accuracy and numerical complexity we computed new EOS tables using the Irwin analytical EOS. We found that the difference between analytical and tabular thermodynamic quantities and their derivatives are smaller than 2% when adopting suitable steps in temperature and density. To improve the numerical accuracy of physical quantities, we are now adopting bicubic splines to interpolate both opacity and EOS tables. The new approach presents a substantial advantage to avoiding numerical derivatives in both linear and nonlinear models. The EOS first- and second-order derivatives are estimated by means of the analytical EOS or by means of analytical derivatives of the interpolating function. The opacity first-order derivatives are evaluated by means of analytical derivatives of the interpolating function. We also investigated the dependence of observables predicted by theoretical models on the mass-luminosity (ML) relation and on the spatial resolution across the hydrogen and the helium partial ionization regions. We found that nonlinear models are marginally affected by these physical and numerical assumptions. In particular, the difference between new and old models in the location as well as in the temperature width of the instability strip is, on average, less than 200 K. However, the spatial resolution somehow affects the pulsation properties. The new fine models predict a period at the center of the Hertzsprung progression (PHP = 9.65-9.84 days) that reasonably agrees with empirical data based on light curves (PHP = 10.0 ± 0.5 days); and radial velocity curves (PHP = 9.95 ± 0.05 days); they improve previous predictions by Bono, Castellani, & Marconi.
Resilience in children at high risk for psychological disorder.

This longitudinal study examined factors related to healthy adjustment in young children who had experienced conditions and stresses known to carry a substantial risk of adverse outcome. Psychological adjustment of 109 children at age 6 to 7 years was examined for its relationship to infancy risk status, determined at age I month by means of a multifactor screen assessing perinatal stress, psychological problems and stresses in the family, maternal attitudes toward self and parenthood, and maternal perceptions of infant temperament. Several variables believed to mediate outcome for high-risk children were studied, including subsequent stressful life events, social support available to child and mother, and child's locus of control orientation. Interactions between predictor variables showed that life events magnify synergistically the adverse effects of infancy risk factors, and social support and internal control orientation potently buffer the effects of risk and stress. Considered jointly in conjunction with their interactions, the predictor variables were strongly predictive of outcome, explaining 56% of the variance observed in behavior problems and 64% of the variance in school problems.
Alcoholism and dampened temporal limbic activation to emotional faces.

BACKGROUND Excessive chronic drinking is accompanied by a broad spectrum of emotional changes ranging from apathy and emotional flatness to deficits in comprehending emotional information, but their neural bases are poorly understood. METHODS Emotional abnormalities associated with alcoholism were examined with functional magnetic resonance imaging in abstinent long-term alcoholic men in comparison to healthy demographically matched controls. Participants were presented with emotionally valenced words and photographs of faces during deep (semantic) and shallow (perceptual) encoding tasks followed by recognition. RESULTS Overall, faces evoked stronger activation than words, with the expected material-specific laterality (left hemisphere for words, and right for faces) and depth of processing effects. However, whereas control participants showed stronger activation in the amygdala and hippocampus when viewing faces with emotional (relative to neutral) expressions, the alcoholics responded in an undifferentiated manner to all facial expressions. In the alcoholic participants, amygdala activity was inversely correlated with an increase in lateral prefrontal activity as a function of their behavioral deficits. Prefrontal modulation of emotional function as a compensation for the blunted amygdala activity during a socially relevant face appraisal task is in agreement with a distributed network engagement during emotional face processing. CONCLUSIONS Deficient activation of amygdala and hippocampus may underlie impaired processing of emotional faces associated with long-term alcoholism and may be a part of the wide array of behavioral problems including disinhibition, concurring with previously documented interpersonal difficulties in this population. Furthermore, the results suggest that alcoholics may rely on prefrontal rather than temporal limbic areas in order to compensate for reduced limbic responsivity and to maintain behavioral adequacy when faced with emotionally or socially challenging situations.
Stable Expression of Human Muscle-Specific Kinase in HEp-2 M4 Cells for Automatic Immunofluorescence Diagnostics of Myasthenia Gravis

Muscle-specific kinase (MuSK) belongs to the nicotinic acetylcholine receptor complex which is targeted by pathogenic autoantibodies causing Myasthenia gravis. While up to 95% of patients with generalized Myasthenia gravis were shown to be positive for acetylcholine receptor-specific autoantibodies, up to 70% of the remaining patients develop autoantibodies against MuSK. Discrimination of the autoantibody specificity is important for therapy of Myasthenia gravis. Recently, the new automatic fluorescence assessment platform AKLIDES has been developed for immunofluorescence-based diagnostics of autoimmune diseases. In order to establish an AKLIDES procedure for the detection of MuSK-specific autoantibodies (anti-MuSK), we developed a recombinant HEp-2 cell clone expressing the human MuSK cDNA. Here we show at the mRNA and protein level that the cell clone HEp-2 M4 stably expresses human MuSK. We provide evidence for a localization of MuSK at the cell membrane. Using cell clone HEp-2 M4 on the AKLIDES system, we investigated 34 patient sera that were previously tested anti-MuSK positive by radioimmunoassay as positive controls. As negative controls, we tested 29 acetylcholine receptor-positive but MuSK-negative patient sera, 30 amytrophic lateral sclerosis (ALS) patient sera and 45 blood donors. HEp-2 M4 cells revealed a high specificity for the detection of MuSK autoantibodies from 25 patient sera assessed by a specific pattern on HEp-2 M4 cells. By using appropriate cell culture additives, the fraction of cells stained positive with anti-MuSK containing sera can be increased from 2–16% to 10–48%, depending on the serum. In conclusion, we provide data showing that the novel recombinant cell line HEp-2 M4 can be used to screen for anti-MuSK with the automatic AKLIDES system.
Learning and Controlling Network Diffusion in Dependent Cascade Models

Diffusion processes have increasingly been used to represent flow of ideas, traffic and diseases in networks. Learning and controlling the diffusion dynamics through management actions has been studied extensively in the context of independent cascade models, where diffusion on outgoing edges from a node are independent of each other. Our work, in contrast, addresses (a) learning diffusion dynamics parameters and (b) taking management actions to alter the diffusion dynamics to achieve a desired outcome in dependent cascade models. A key characteristic of such dependent cascade models is the flow preservation at all nodes in the network. For example, traffic and people flow is preserved at each network node. As a case study, we address learning visitor mobility pattern at a theme park based on observed historical wait times at individual attractions, and use the learned model to plan management actions that reduce wait time at attractions. We test on real-world data from a theme park in Singapore and show that our learning approach can achieve an accuracy close to 80% for popular attractions, and the decision support algorithm can provide about 10-20% reduction in wait time.
An Analytical Comparison between Software Inspection and Pair Development

Peer review is one of the essential activities in software quality assurance to remove defects at the early stages of development. Peer review can be performed to verify almost all software artifacts in every phase of the software development life cycle such as requirement, design, code and test. According to [Fagan, 1976], software inspection, the most formal structure of peer review, can remove as much as 80% of total defects.
Constrained Single-Objective Optimization Using Particle Swarm Optimization

Particle Swarm Optimization (PSO) is an optimization method that is derived from the behavior of social groups like bird flocks or fish schools. In this work PSO is used for the optimization of the constrained test suite of the special session on constrained real parameter optimization at CEC06. Constraint-handling is done by modifying the procedure for determining personal and neighborhood best particles. No additional parameters are needed for the handling of constraints. Numerical results are presented, and statements are given about which types of functions have been successfully optimized and which features present difficulties.
Rates of bluetongue virus transmission between Culicoides sonorensis and sheep

Abstract Two experiments were undertaken to estimate the transmission rates of bluetongue virus (BTV) serotype 1 between a biting midge vector, Culicoides sonorensis (Wirth & Jones) (Ceratopogonidae), and a natural host, sheep. In an experiment to measure the transmission rate from vector to host (V→H), six batches of one, five and 20 intrathoracically infected midges were fed on a total of 18 bluetongue (BT)‐naïve sheep. The sheep were then monitored for 21 days for clinical signs of BT, viraemia and antibody response. All sheep fed on by five or 20 midges and five of six sheep fed on by just one midge showed signs of BT, were viraemic and developed antibody. The sixth sheep fed on by a single infected midge did not show signs of BT or have detectable viraemia; it did, however, develop a weak antibody response. A bite from a single infected midge is therefore able to transmit BTV to naïve sheep with 80–100% efficiency. Sheep fed upon by larger numbers of infected midges took less time to reach maximum viraemia and developed stronger antibody responses. Sheep exposed to greater amounts of BTV in feeding midges developed a higher level of viraemia and stronger antibody responses. In a second experiment to measure the transmission rate from host to vector (H→V), batches of up to 500 uninfected female C. sonorensis fed every 1–2 days on two experimentally infected sheep during the course of infection. Of 3929 engorged midges that were individually titrated after surviving the extrinsic incubation period, only 23 (0.6%) were infected with BTV. Viraemia in the sheep extended for up to 19 days post‐inoculation. No infected midges, however, were detected from 14 days post‐infection.
Probabilistic analysis of the human transcriptome with side information

Understanding functional organization of genetic information is a major challenge in modern biology. Following the initial publication of the human genome sequence in 2001, advances in high-throughput measurement technologies and efficient sharing of research material through community databases have opened up new views to the study of living organisms and the structure of life. In this thesis, novel computational strategies have been developed to investigate a key functional layer of genetic information, the human transcriptome, which regulates the function of living cells through protein synthesis. The key contributions of the thesis are general exploratory tools for high-throughput data analysis that have provided new insights to cell-biological networks, cancer mechanisms and other aspects of genome function. A central challenge in functional genomics is that high-dimensional genomic observations are associated with high levels of complex and largely unknown sources of variation. By combining statistical evidence across multiple measurement sources and the wealth of background information in genomic data repositories it has been possible to solve some the uncertainties associated with individual observations and to identify functional mechanisms that could not be detected based on individual measurement sources. Statistical learning and probabilistic models provide a natural framework for such modeling tasks. Open source implementations of the key methodological contributions have been released to facilitate further adoption of the developed methods by the research community.