A New Approximate Min-Max Theorem with Applications in Cryptography

We propose a novel proof technique that can be applied to attack a broad class of problems in computational complexity, when switching the order of universal and existential quantifiers is helpful. Our approach combines the standard min-max theorem and convex approximation techniques, offering quantitative improvements over the standard way of using min-max theorems as well as more concise and elegant proofs

Quantitative assessment of prefrontal cortex in humans relative to nonhuman primates

Significance A longstanding controversy in neuroscience pertains to differences in human prefrontal cortex (PFC) compared with other primate species; specifically, is human PFC disproportionately large? Distinctively human behavioral capacities related to higher cognition and affect presumably arose from evolutionary modifications since humans and great apes diverged from a common ancestor about 6–8 Mya. Accurate determination of regional differences in the amount of cortical gray and subcortical white matter content in humans, great apes, and Old World monkeys can further our understanding of the link between structure and function of the human brain. Using tissue volume analyses, we show a disproportionately large amount of gray and white matter corresponding to PFC in humans compared with nonhuman primates.</jats:p

Preoperative drug dispensing as predictor of surgical site infection.

The system used by the National Nosocomial Infection Surveillance (NNIS) program to measure risk of surgical site infection uses a score of 3 on the American Society of Anesthesiologists (ASA)-physical status scale as a measure of underlying illness. The chronic disease score measures health status as a function of age, sex, and 29 chronic diseases, inferred from dispensing of prescription drugs. We studied the relationship between the chronic disease score and surgical site infection and whether the score can supplement the NNIS risk index. In a retrospective comparison of 191 patients with surgical site infection and 378 uninfected controls, the chronic disease score and ASA score were highly correlated. The chronic disease score improved prediction of infection by the NNIS risk index and augmented the ASA score for risk adjustment

Determination of rotation periods in solar-like stars with irregular sampling: the Gaia case

We present a study on the determination of rotation periods (P) of solar-like stars from the photometric irregular time-sampling of the ESA Gaia mission, currently scheduled for launch in 2013, taking into account its dependence on ecliptic coordinates. We examine the case of solar-twins as well as thousands of synthetic time-series of solar-like stars rotating faster than the Sun. In the case of solar twins we assume that the Gaia unfiltered photometric passband G will mimic the variability of the total solar irradiance (TSI) as measured by the VIRGO experiment. For stars rotating faster than the Sun, light-curves are simulated using synthetic spectra for the quiet atmosphere, the spots, and the faculae combined by applying semi-empirical relationships relating the level of photospheric magnetic activity to the stellar rotation and the Gaia instrumental response. The capabilities of the Deeming, Lomb-Scargle, and Phase Dispersion Minimisation methods in recovering the correct rotation periods are tested and compared. The false alarm probability (FAP) is computed using Monte Carlo simulations and compared with analytical formulae. The Gaia scanning law makes the rate of correct detection of rotation periods strongly dependent on the ecliptic latitude (beta). We find that for P ~ 1 d, the rate of correct detection increases with ecliptic latitude from 20-30 per cent at beta ~ 0{\deg} to a peak of 70 per cent at beta=45{\deg}, then it abruptly falls below 10 per cent at beta > 45{\deg}. For P > 5 d, the rate of correct detection is quite low and for solar twins is only 5 per cent on average.Comment: 12 pages, 18 figures, accepted by MNRA

Cooling in the X-ray halo of the rotating, massive early-type galaxy NGC 7049

The relative importance of the physical processes shaping the thermodynamics of the hot gas permeating rotating, massive early-type galaxies is expected to be different from that in non-rotating systems. Here, we report the results of the analysis of XMM-Newton data for the massive, lenticular galaxy NGC 7049. The galaxy harbours a dusty disc of cool gas and is surrounded by an extended hot X-ray emitting gaseous atmosphere with unusually high central entropy. The hot gas in the plane of rotation of the cool dusty disc has a multi-temperature structure, consistent with ongoing cooling. We conclude that the rotational support of the hot gas is likely capable of altering the multiphase condensation regardless of the $t_{\rm cool}/t_{\rm ff}$ ratio, which is here relatively high, $\sim 40$. However, the measured ratio of cooling time and eddy turnover time around unity ($C$-ratio $\approx 1$) implies significant condensation, and at the same time, the constrained ratio of rotational velocity and the velocity dispersion (turbulent Taylor number) ${\rm Ta_t} > 1$ indicates that the condensing gas should follow non-radial orbits forming a disc instead of filaments. This is in agreement with hydrodynamical simulations of massive rotating galaxies predicting a similarly extended multiphase disc.Comment: 11 pages, 12 figures, accepted for publication in MNRA

Web Search of Fashion Items with Multimodal Querying

In this paper, we introduce a novel multimodal fashion search paradigm where e-commerce data is searched with a multimodal query composed of both an image and text. In this setting, the query image shows a fashion product that the user likes and the query text allows to change certain product attributes to fit the product to the user’s desire. Multimodal search gives users the means to clearly express what they are looking for. This is in contrast to current e-commerce search mechanisms, which are cumbersome and often fail to grasp the customer’s needs. Multimodal search requires intermodal representations of visual and textual fashion attributes which can be mixed and matched to form the user’s desired product, and which have a mechanism to indicate when a visual and textual fashion attribute represent the same concept. With a neural network, we induce a common, multimodal space for visual and textual fashion attributes where their inner product measures their semantic similarity. We build a multimodal retrieval model which operates on the obtained intermodal representations and which ranks images based on their relevance to a multimodal query. We demonstrate that our model is able to retrieve images that both exhibit the necessary query image attributes and satisfy the query texts. Moreover, we show that our model substantially outperforms two state-of-the-art retrieval models adapted to multimodal fashion search.status: accepte