Domain Agnostic Real-Valued Specificity Prediction

Sentence specificity quantifies the level of detail in a sentence, characterizing the organization of information in discourse. While this information is useful for many downstream applications, specificity prediction systems predict very coarse labels (binary or ternary) and are trained on and tailored toward specific domains (e.g., news). The goal of this work is to generalize specificity prediction to domains where no labeled data is available and output more nuanced real-valued specificity ratings. We present an unsupervised domain adaptation system for sentence specificity prediction, specifically designed to output real-valued estimates from binary training labels. To calibrate the values of these predictions appropriately, we regularize the posterior distribution of the labels towards a reference distribution. We show that our framework generalizes well to three different domains with 50%~68% mean absolute error reduction than the current state-of-the-art system trained for news sentence specificity. We also demonstrate the potential of our work in improving the quality and informativeness of dialogue generation systems.Comment: AAAI 2019 camera read

Prediction of corporate financial distress : an application of the composite rule induction system

The economic consequence of corporate failure is enormous, especially for the stakeholders of public-held companies. Prior to a corporate failure, the firm’s financial status is frequently in distress. Consequently, finding a method to identify corporate financial distress as early as possible is clearly a matter of considerable interest to investors, creditors, auditors and other stakeholders. This paper uses a composite rule induction system (CRIS; Liang 1992) to derive rules for predicting corporate financial distress in Taiwan. In addition, this paper compares the prediction performance of cris, neural computing and the logit model. The empirical results indicate that both CRIS and neural computing outperform the logit model in predicting financial distress. Although both CRIS and neural computing perform rather well, CRIS has the advantage that the derived rules are easier to understand and interpret.La consecuencia económica de un fracaso corporativo es enorme, especialmente para los actores clave de las compañías públicas. En las fases previas a un fracaso corporativo, es común que el estatus financiero de la firma se encuentre normalmente en apuros. Consecuentemente, encontrar un método para identificar peligros financieros en una corporación tan pronto como sea posible es claramente un asunto con gran interés para los inversores, acreedores, auditores y otros actores clave. Este artículo usa un sistema de reglas inductivas compuestas (CRIS; Liang 1992) para elaborar reglas y patrones que ayuden a predecir problemas económicos en Taiwan. Además, este artículo compara el rendimiento y predicciones de CRIS, la informática neuronal y el modelo logístico. Los resultados empíricos indican que tanto CRIS como la informática neuronal funcionan generalmente bien a la hora de predecir los problemas financieros. Aunque ambos funcionan correctamente, CRIS tiene la ventaja de que sus reglas son más sencillas de entender e interpretar

2-(2-Meth­oxy-5-methyl­phen­yl)-2H-benzotriazole

In the title mol­ecule, C14H13N3O, the dihedral angle between the mean planes of the benzotriazole ring system and the benzene ring is 57.8 (2)°

Deranged Bioenergetics and Defective Redox Capacity in T Lymphocytes and Neutrophils Are Related to Cellular Dysfunction and Increased Oxidative Stress in Patients with Active Systemic Lupus Erythematosus

Urinary excretion of N-benzoyl-glycyl-Nε-(hexanonyl)lysine, a biomarker of oxidative stress, was higher in 26 patients with active systemic lupus erythematosus (SLE) than in 11 non-SLE patients with connective tissue diseases and in 14 healthy volunteers. We hypothesized that increased oxidative stress in active SLE might be attributable to deranged bioenergetics, defective reduction-oxidation (redox) capacity, or other factors. We demonstrated that, compared to normal cells, T lymphocytes (T) and polymorphonuclear neutrophils (PMN) of active SLE showed defective expression of facilitative glucose transporters GLUT-3 and GLUT-6, which led to increased intracellular basal lactate and decreased ATP production. In addition, the redox capacity, including intracellular GSH levels and the enzyme activity of glutathione peroxidase (GSH-Px) and γ-glutamyl-transpeptidase (GGT), was decreased in SLE-T. Compared to normal cells, SLE-PMN showed decreased intracellular GSH levels, and GGT enzyme activity was found in SLE-PMN and enhanced expression of CD53, a coprecipitating molecule for GGT. We conclude that deranged cellular bioenergetics and defective redox capacity in T and PMN are responsible for cellular immune dysfunction and are related to increased oxidative stress in active SLE patients

Search for direct production of charginos and neutralinos in events with three leptons and missing transverse momentum in √s = 7 TeV pp collisions with the ATLAS detector

A search for the direct production of charginos and neutralinos in final states with three electrons or muons and missing transverse momentum is presented. The analysis is based on 4.7 fb−1 of proton–proton collision data delivered by the Large Hadron Collider and recorded with the ATLAS detector. Observations are consistent with Standard Model expectations in three signal regions that are either depleted or enriched in Z-boson decays. Upper limits at 95% confidence level are set in R-parity conserving phenomenological minimal supersymmetric models and in simplified models, significantly extending previous results

Inclusive search for same-sign dilepton signatures in pp collisions at root s=7 TeV with the ATLAS detector

An inclusive search is presented for new physics in events with two isolated leptons (e or mu) having the same electric charge. The data are selected from events collected from p p collisions at root s = 7 TeV by the ATLAS detector and correspond to an integrated luminosity of 34 pb(-1). The spectra in dilepton invariant mass, missing transverse momentum and jet multiplicity are presented and compared to Standard Model predictions. In this event sample, no evidence is found for contributions beyond those of the Standard Model. Limits are set on the cross-section in a fiducial region for new sources of same-sign high-mass dilepton events in the ee, e mu and mu mu channels. Four models predicting same-sign dilepton signals are constrained: two descriptions of Majorana neutrinos, a cascade topology similar to supersymmetry or universal extra dimensions, and fourth generation d-type quarks. Assuming a new physics scale of 1 TeV, Majorana neutrinos produced by an effective operator V with masses below 460 GeV are excluded at 95% confidence level. A lower limit of 290 GeV is set at 95% confidence level on the mass of fourth generation d-type quarks

Measurement of the top quark-pair production cross section with ATLAS in pp collisions at \sqrt{s}=7\TeV

A measurement of the production cross-section for top quark pairs(\ttbar) in $pp$ collisions at \sqrt{s}=7 \TeV is presented using data recorded with the ATLAS detector at the Large Hadron Collider. Events are selected in two different topologies: single lepton (electron $e$ or muon $\mu$) with large missing transverse energy and at least four jets, and dilepton ($ee$, $\mu\mu$ or $e\mu$) with large missing transverse energy and at least two jets. In a data sample of 2.9 pb-1, 37 candidate events are observed in the single-lepton topology and 9 events in the dilepton topology. The corresponding expected backgrounds from non-\ttbar Standard Model processes are estimated using data-driven methods and determined to be $12.2 \pm 3.9$ events and $2.5 \pm 0.6$ events, respectively. The kinematic properties of the selected events are consistent with SM \ttbar production. The inclusive top quark pair production cross-section is measured to be \sigmattbar=145 \pm 31 ^{+42}_{-27} pb where the first uncertainty is statistical and the second systematic. The measurement agrees with perturbative QCD calculations.Comment: 30 pages plus author list (50 pages total), 9 figures, 11 tables, CERN-PH number and final journal adde

Urinary Neutrophil Gelatinase-Associated Lipocalin Is a Potential Biomarker for Renal Damage in Patients with Systemic Lupus Erythematosus

Neutrophil gelatinase-associated lipocalin (NGAL) has been demonstrated to be a novel biomarker in acute and chronic kidney disease. We hypothesized that 24-hour urinary NGAL excretion may be a predictor for renal damage in patients with systemic lupus erythematosus (SLE). Thirty-four SLE patients with renal involvement (SLE-renal group), 8 SLE patients without renal involvement (SLE-nonrenal group), 14 patients with non-SLE autoimmune diseases (disease control or DC group), and 12 healthy volunteers (normal control or NC group) were compared for 24-hour urinary excretion of NGAL and different cytokines. We found that the 24-hour urinary NGAL excretion in the SLE-renal group was higher than that in the SLE-non-renal, DC, and NC groups. However, the excretion of interleukin-10, transforming growth factor-β1, and tumor necrosis factor-α was not different between the SLE-renal and SLE-non-renal groups. Furthermore, NGAL excretion in the SLE-renal group was correlated with serum creatinine levels and creatinine clearance, but not with the SLE Disease Activity Index score. Multivariate logistic regression analysis and receiver operating characteristic curve analysis revealed that 24-hour urinary NGAL excretion is a potential biomarker for renal damage in SLE patients, with higher sensitivity and specificity than anti-dsDNA antibody titers