Discriminative learning of local image descriptors

In this paper, we explore methods for learning local image descriptors from training data. We describe a set of building blocks for constructing descriptors which can be combined together and jointly optimized so as to minimize the error of a nearest-neighbor classifier. We consider both linear and nonlinear transforms with dimensionality reduction, and make use of discriminant learning techniques such as Linear Discriminant Analysis (LDA) and Powell minimization to solve for the parameters. Using these techniques, we obtain descriptors that exceed state-of-the-art performance with low dimensionality. In addition to new experiments and recommendations for descriptor learning, we are also making available a new and realistic ground truth data set based on multiview stereo data

Comparative in vitro cytotoxicity assessment of selected gaseous compounds in human alveolar epithelial cells

Exposure to airborne contaminants is significantly associated with human health risks, ranging from bronchial reactivity to morbidity and mortality due to acute intense or long term low level repeated exposures. However, the precise mechanisms that derive such effects are not always understood. Although inhalation studies are technologically complicated, correct hazard characterisation is essential for comparable risk assessment of inhaled materials. The aim of this study was to investigate the comparative in vitro cytotoxicity of selected gaseous contaminants in human lung cells. The cytotoxicity of nitrogen dioxide (NO2), sulphur dioxide (SO2) and ammonia (NH3) was investigated in A549- human pulmonary type II-like epithelial cell lines cultured on porous membranes in Snapwell inserts. A dynamic direct exposure method was established by utilizing the horizontal diffusion chamber system (Harvard Apparatus Inc, USA) for delivery of test atmospheres. Test atmospheres were generated using a dynamic direct dilution method and the concentration monitored by appropriate analytical methods. A diversified battery of in vitro assays including the MTS (tetrazolium salt; Promega), NRU (neutral red uptake; Sigma) and ATP (adenosine triphosphate; Promega) assays was implemented. Airborne IC50 (50 inhibitory concentration) values were calculated based on the most sensitive assay for each test gas including NO2 (IC50 = 11 ± 3.54 ppm; NRU) > SO2 (IC50 = 48 ± 2.83 ppm; ATP)> and NH3 (IC50 = 199 ± 1.41 ppm; MTS). However, all in vitro assays revealed similar toxicity ranking for selected gaseous contaminants. Identical toxicity ranking was achieved using both in vitro and published in vivo data. This comparison suggests that results of in vitro methods are comparable to in vivo data and may provide greater sensitivity for respiratory toxicity studies of gaseous contaminants. © 2007 Elsevier Ltd. All rights reserved

An integrated in vitro approach for toxicity testing of airborne contaminants

While it is possible to establish the chemical composition of air pollutants through conventional air sampling and analytical techniques, such data do not provide direct measures of toxicity and the potential mechanisms that induce adverse effects. The aim of this study was to optimize in vitro methods for toxicity testing of airborne contaminants. An integrated approach was designed in which appropriate exposure techniques were developed. A diversified range of in vitro assays using multiple human cell systems were implemented. Direct exposure of cells to airborne contaminants was developed by culturing cells on porous membranes in conjunction with a horizontal diffusion chamber system. Concentration-response curves were generated allowing the measurement of toxicity endpoints. Regression analysis indicated a significant correlation between in vitro and published in vivo toxicity data for the majority of selected chemical contaminants. Airborne IC50 values were calculated for selected volatile organic compounds (xylene, 5350 ± 328 ppm > toluene, 10500 ± 527 ppm) and gaseous contaminants (NO2, 11 ± 3.54 ppm > SO2, 48 ± 2.83 ppm and > NH3, 199 ± 1.41 ppm). Results of this study indicate the significant potential of in vitro methods as an advanced technology for toxicity assessment of airborne contaminants. Copyright © Taylor & Francis Group, LLC

Dystroglycan Depletion Impairs Actin-Dependent Functions of Differentiated Kasumi-1 Cells

Background Dystroglycan has recently been characterised in blood tissue cells, as part of the dystrophin glycoprotein complex involved in the differentiation process of neutrophils. Purpose In the present study we have investigated the role of dystroglycan in the human promyelocytic leukemic cell line Kasumi-1 differentiated to macrophage-like cells. Methods We characterised the pattern expression and subcellular distribution of dystroglycans in non-differentiated and differentiated Kasumi-1 cells. Results Our results demonstrated by WB and flow cytometer assays that during the differentiation process to macrophages, dystroglycans were down-regulated; these results were confirmed with qRT-PCR assays. Additionally, depletion of dystroglycan by RNAi resulted in altered morphology and reduced properties of differentiated Kasumi-1 cells, including morphology, migration and phagocytic activities although secretion of IL-1β and expression of markers of differentiation are not altered. Conclusion Our findings strongly implicate dystroglycan as a key membrane adhesion protein involved in actin-based structures during the differentiation process in Kasumi-1 cells

Quantum Dynamics of the Slow Rollover Transition in the Linear Delta Expansion

We apply the linear delta expansion to the quantum mechanical version of the slow rollover transition which is an important feature of inflationary models of the early universe. The method, which goes beyond the Gaussian approximation, gives results which stay close to the exact solution for longer than previous methods. It provides a promising basis for extension to a full field theoretic treatment.Comment: 12 pages, including 4 figure

Nearly optimal solutions for the Chow Parameters Problem and low-weight approximation of halfspaces

The \emph{Chow parameters} of a Boolean function $f: \{-1,1\}^n \to \{-1,1\}$ are its $n+1$ degree-0 and degree-1 Fourier coefficients. It has been known since 1961 (Chow, Tannenbaum) that the (exact values of the) Chow parameters of any linear threshold function $f$ uniquely specify $f$ within the space of all Boolean functions, but until recently (O'Donnell and Servedio) nothing was known about efficient algorithms for \emph{reconstructing} $f$ (exactly or approximately) from exact or approximate values of its Chow parameters. We refer to this reconstruction problem as the \emph{Chow Parameters Problem.} Our main result is a new algorithm for the Chow Parameters Problem which, given (sufficiently accurate approximations to) the Chow parameters of any linear threshold function $f$, runs in time \tilde{O}(n^2)\cdot (1/\eps)^{O(\log^2(1/\eps))} and with high probability outputs a representation of an LTF $f'$ that is \eps-close to $f$. The only previous algorithm (O'Donnell and Servedio) had running time \poly(n) \cdot 2^{2^{\tilde{O}(1/\eps^2)}}. As a byproduct of our approach, we show that for any linear threshold function $f$ over $\{-1,1\}^n$, there is a linear threshold function $f'$ which is \eps-close to $f$ and has all weights that are integers at most \sqrt{n} \cdot (1/\eps)^{O(\log^2(1/\eps))}. This significantly improves the best previous result of Diakonikolas and Servedio which gave a \poly(n) \cdot 2^{\tilde{O}(1/\eps^{2/3})} weight bound, and is close to the known lower bound of $\max\{\sqrt{n},$ (1/\eps)^{\Omega(\log \log (1/\eps))}\} (Goldberg, Servedio). Our techniques also yield improved algorithms for related problems in learning theory