Open Gromov-Witten Invariants of Toric Calabi-Yau 3-Folds

We present a proof of the mirror conjecture of Aganagic-Vafa [arXiv:hep-th/0012041] and Aganagic-Klemm-Vafa [arXiv:hep-th/0105045] on disk enumeration in toric Calabi-Yau 3-folds for all smooth semi-projective toric Calabi-Yau 3-folds. We consider both inner and outer branes, at arbitrary framing. In particular, we recover previous results on the conjecture for (i) an inner brane at zero framing in the total space of the canonical line bundle of the projective plane (Graber-Zaslow [arXiv:hep-th/0109075]), (ii) an outer brane at arbitrary framing in the resolved conifold (Zhou [arXiv:1001.0447]), and (iii) an outer brane at zero framing in the total space of the canonical line bundle of the projective plane (Brini [arXiv:1102.0281, Section 5.3]).Comment: 39 pages, 11 figure

Optical quenching and recovery of photoconductivity in single-crystal diamond

We study the photocurrent induced by pulsed-light illumination (pulse duration is several nanoseconds) of single-crystal diamond containing nitrogen impurities. Application of additional continuous-wave light of the same wavelength quenches pulsed photocurrent. Characterization of the optically quenched photocurrent and its recovery is important for the development of diamond based electronics and sensing

Unusual statistics of interference effects in neutron scattering from compound nuclei

We consider interference effects between p-wave resonance scattering amplitude and background s-wave amplitude in low-energy neutron scattering from a heavy nucleus which goes through the compound nucleus stage. The first effect is in the difference between the forward and backward scattering cross sections. Because of the chaotic nature of the compound states, this effect is a random variable with zero mean. However, a statistical consideration shows that the probability distribution of this effect does not obey the standard central limit theorem. That is, the probability density for the effect averaged over n resonances does not become a Gaussian distribution with the variance decreasing as 1/sqrt(n) (``violation'' of the theorem!). We derive the probability distribution of the effect and the limit distribution of the average. It is found that the width of this distribution does not decrease with the increase of n, i.e., fluctuations are not suppressed by averaging. Furthermore, we consider the correlation between the neutron spin and the scattering plane and find that this effect, although much smaller, shows fluctuations which actually increase upon averaging over many measurements. Limits of the effects due to finite resonance widths are also considered. In the appendix we present a simple derivation of the limit theorem for the average of random variables with infinite variances.Comment: 15 pages, RevTeX, submitted to Phys. Rev.

One-Loop Self Energy and Renormalization of the Speed of Light for some Anisotropic Improved Quark Actions

One-loop corrections to the fermion rest mass M_1, wave function renormalization Z_2 and speed of light renormalization C_0 are presented for lattice actions that combine improved glue with clover or D234 quark actions and keep the temporal and spatial lattice spacings, a_t and a_s, distinct. We explore a range of values for the anisotropy parameter \chi = a_s/a_t and treat both massive and massless fermions.Comment: 45 LaTeX pages with 4 postscript figure

Link Mining for Kernel-based Compound-Protein Interaction Predictions Using a Chemogenomics Approach

Virtual screening (VS) is widely used during computational drug discovery to reduce costs. Chemogenomics-based virtual screening (CGBVS) can be used to predict new compound-protein interactions (CPIs) from known CPI network data using several methods, including machine learning and data mining. Although CGBVS facilitates highly efficient and accurate CPI prediction, it has poor performance for prediction of new compounds for which CPIs are unknown. The pairwise kernel method (PKM) is a state-of-the-art CGBVS method and shows high accuracy for prediction of new compounds. In this study, on the basis of link mining, we improved the PKM by combining link indicator kernel (LIK) and chemical similarity and evaluated the accuracy of these methods. The proposed method obtained an average area under the precision-recall curve (AUPR) value of 0.562, which was higher than that achieved by the conventional Gaussian interaction profile (GIP) method (0.425), and the calculation time was only increased by a few percent

Knowledge Graph Completion via Complex Tensor Factorization

In statistical relational learning, knowledge graph completion deals with automatically understanding the structure of large knowledge graphs—labeled directed graphs—and predicting missing relationships—labeled edges. State-of-the-art embedding models propose different trade-offs between modeling expressiveness, and time and space complexity. We reconcile both expressiveness and complexity through the use of complex-valued embeddings and explore the link between such complex-valued embeddings and unitary diagonalization. We corroborate our approach theoretically and show that all real square matrices—thus all possible relation/adjacency matrices—are the real part of some unitarily diagonalizable matrix. This results opens the door to a lot of other applications of square matrices factorization. Our approach based on complex embeddings is arguably simple, as it only involves a Hermitian dot product, the complex counterpart of the standard dot product between real vectors, whereas other methods resort to more and more complicated composition functions to increase their expressiveness. The proposed complex embeddings are scalable to large data sets as it remains linear in both space and time, while consistently outperforming alternative approaches on standard link prediction benchmarks

Wall-crossing, open BPS counting and matrix models

We consider wall-crossing phenomena associated to the counting of D2-branes attached to D4-branes wrapping lagrangian cycles in Calabi-Yau manifolds, both from M-theory and matrix model perspective. Firstly, from M-theory viewpoint, we review that open BPS generating functions in various chambers are given by a restriction of the modulus square of the open topological string partition functions. Secondly, we show that these BPS generating functions can be identified with integrands of matrix models, which naturally arise in the free fermion formulation of corresponding crystal models. A parameter specifying a choice of an open BPS chamber has a natural, geometric interpretation in the crystal model. These results extend previously known relations between open topological string amplitudes and matrix models to include chamber dependence.Comment: 25 pages, 8 figures, published versio

Levels of protein C and soluble thrombomodulin in critically ill patients with acute kidney injury: a multicenter prospective observational study.

Endothelial dysfunction contributes to the development of acute kidney injury (AKI) in animal models of ischemia reperfusion injury and sepsis. There are limited data on markers of endothelial dysfunction in human AKI. We hypothesized that Protein C (PC) and soluble thrombomodulin (sTM) levels could predict AKI. We conducted a multicenter prospective study in 80 patients to assess the relationship of PC and sTM levels to AKI, defined by the AKIN creatinine (AKI Scr) and urine output criteria (AKI UO). We measured marker levels for up to 10 days from intensive care unit admission. We used area under the curve (AUC) and time-dependent multivariable Cox proportional hazard model to predict AKI and logistic regression to predict mortality/non-renal recovery. Protein C and sTM were not different in patients with AKI UO only versus no AKI. On intensive care unit admission, as PC levels are usually lower with AKI Scr, the AUC to predict the absence of AKI was 0.63 (95%CI 0.44-0.78). The AUC using log10 sTM levels to predict AKI was 0.77 (95%CI 0.62-0.89), which predicted AKI Scr better than serum and urine neutrophil gelatinase-associated lipocalin (NGAL) and cystatin C, urine kidney injury molecule-1 and liver-fatty acid-binding protein. In multivariable models, PC and urine NGAL levels independently predicted AKI (p=0.04 and 0.02) and PC levels independently predicted mortality/non-renal recovery (p=0.04). In our study, PC and sTM levels can predict AKI Scr but are not modified during AKI UO alone. PC levels could independently predict mortality/non-renal recovery. Additional larger studies are needed to define the relationship between markers of endothelial dysfunction and AKI

Physical activity monitoring in Europe : the European physical activity surveillance system (EUPASS) approach and indicator testing.

Objectives: The main objective of this paper is to describe the approach and specific findings of the European Physical Activity Surveillance System (EUPASS) research project. In particular, the analysis presented aims at testing the reliability, comparability and predictive power of different sets of physical activity (PA) indicators. Design: First, a panel study based on computer-aided telephone interview (CATI) was designed to report PA data of a representative, selected group of about 100 persons per country at three points in time. Second, a CATI time series survey was carried out with the goal of realising about 100 interviews per month over six consecutive months. Setting: The project was carried out in eight European countries to support the development of the European Union's (EU) Health Monitoring Programme. Subjects: Random population samples (subjects aged 18 years and older) were drawn from each participating country. Results: While many PA indicators used in EU countries to date as well as the psychosocial and environmental measures tested in the present study had acceptable to good reliability coefficients, the test–retest reliability scores of the International Physical Activity Questionnaire (IPAQ) version tested (the short (last 7 days) telephone interview IPAQ; IPAQ-S7T) were rather low. The comparability between extant national PA items and the IPAQ-S7T was low for all countries. The strongest predictors of perceived health were the psychosocial and environmental PA indicators. Conclusions: According to the results of the present study, more research is needed to further investigate and improve the quality of the IPAQ. In addition, the specific predictive power of the tested psychosocial and environmental PA indicators on perceived health should be of particular interest for designing health surveillance activities in the future