Censoring Distances Based on Labeled Cortical Distance Maps in Cortical Morphometry

Shape differences are manifested in cortical structures due to neuropsychiatric disorders. Such differences can be measured by labeled cortical distance mapping (LCDM) which characterizes the morphometry of the laminar cortical mantle of cortical structures. LCDM data consist of signed distances of gray matter (GM) voxels with respect to GM/white matter (WM) surface. Volumes and descriptive measures (such as means and variances) for each subject and the pooled distances provide the morphometric differences between diagnostic groups, but they do not reveal all the morphometric information contained in LCDM distances. To extract more information from LCDM data, censoring of the distances is introduced. For censoring of LCDM distances, the range of LCDM distances is partitioned at a fixed increment size; and at each censoring step, and distances not exceeding the censoring distance are kept. Censored LCDM distances inherit the advantages of the pooled distances. Furthermore, the analysis of censored distances provides information about the location of morphometric differences which cannot be obtained from the pooled distances. However, at each step, the censored distances aggregate, which might confound the results. The influence of data aggregation is investigated with an extensive Monte Carlo simulation analysis and it is demonstrated that this influence is negligible. As an illustrative example, GM of ventral medial prefrontal cortices (VMPFCs) of subjects with major depressive disorder (MDD), subjects at high risk (HR) of MDD, and healthy control (Ctrl) subjects are used. A significant reduction in laminar thickness of the VMPFC and perhaps shrinkage in MDD and HR subjects is observed when compared to Ctrl subjects. The methodology is also applicable to LCDM-based morphometric measures of other cortical structures affected by disease.Comment: 25 pages, 10 figure

Bayesian Forecasting of US Growth using Basic Time Varying Parameter Models and Expectations Data

__Abstract__ Time varying patterns in US growth are analyzed using various univariate model structures, starting from a naive model structure where all features change every period to a model where the slow variation in the conditional mean and changes in the conditional variance are specified together with their interaction, including survey data on expected growth in order to strengthen the information in the model. Use is made of a simulation based Bayesian inferential method to determine the forecasting performance of the various model specifications. The extension of a basic growth model with a constant mean to models including time variation in the mean and variance requires careful investigation of possible identification issues of the parameters and existence conditions of the posterior under a diffuse prior. The use of diffuse priors leads to a focus on the likelihood fu nction and it enables a researcher and policy adviser to evaluate the scientific information contained in model and data. Empirical results indicate that incorporating time variation in mean growth rates as well as in volatility are important in order to improve for the predictive performances of growth models. Furthermore, using data information on growth expectations is important for forecasting growth in specific periods, such as the the recession periods around 2000s and around 2008

GÖRÜNTÜ DOSYALARININ ŞİFRELENEREK GÜVENLİ ŞEKİLDE SAKLANMASI

With the increase in internet usage and technological developments, people take hundreds of photos every day. Photos increasing day by day take up a lot of space in the phone memory. Storing these photos in flash memory, computers and phones is not very reliable due to situations such as loss and corruption. This situation has created the need for new storage areas other than the phone. Cloud storage systems are used as an alternative at this point. Cloud storage areas contain security measures against system access and attacks, but they do not directly work on the images uploaded to the system. Cloud accounts are sometimes hijacked by malicious people and photos of people can be stolen. In order to prevent this situation, a system that uses encryption algorithms on the image before storage has been proposed. Various symmetric encryption algorithms under CodeIgniter (PHP Framework) have been compared in the system and the application results are presented. Instead of using their own extensions of the image files to be encrypted, it is ensured that the images are stored with a different file extension in the Amazon Web Service environment or local environment after they are encrypted. When malicious people who want to capture images encounter a file with a different extension, they will not be able to directly determine that it is an image file. With thesystem proposed in this study, it is aimed to provide a safer storage opportunity regardless of the environment in which the images are stored

Posterior-Predictive Evidence on US Inflation using Extended Phillips Curve Models with Non-filtered Data

Changing time series properties of US inflation and economic activity, measured as marginal costs, are modeled within a set of extended Phillips Curve (PC) models. It is shown that mechanical removal or modeling of simple low frequency movements in the data may yield poor predictive results which depend on the model specification used. Basic PC models are extended to include structural time series models that describe typical time varying patterns in levels and volatilities. Forward as well as backward looking expectation mechanisms for inflation are incorporated and their relative importance evaluated. Survey data on expected inflation are introduced to strengthen the information in the likelihood. Use is made of simulation based Bayesian techniques for the empirical analysis. No credible evidence is found on endogeneity and long run stability between inflation and marginal costs. Backward-looking inflation appears stronger than forward-looking one. Levels and volatilities of inflation are estimated more precisely using rich PC models. Estimated inflation expectations track nicely the observed long run inflation from the survey data. The extended PC structures compare favorably with existing basic Bayesian Vector Autoregressive and Stochastic Volatility models in terms of fit and prediction. Tails of the complete predictive distributions indicate an increase in the probability of disinflation in recent years

Latest results from the EU project AVATAR: aerodynamic modelling of 10 MW wind turbines

This paper presents the most recent results from the EU project AVATAR in which aerodynamic models are improved and validated for wind turbines on a scale of 10 MW and more. Measurements on a DU 00-W-212 airfoil are presented which have been taken in the pressurized DNW-HDG wind tunnel up to a Reynolds number of 15 Million. These measurements are compared with measurements in the LM wind tunnel for Reynolds numbers of 3 and 6 Million and with calculational results. In the analysis of results special attention is paid to high Reynolds numbers effects. CFD calculations on airfoil performance showed an unexpected large scatter which eventually was reduced by paying even more attention to grid independency and domain size in relation to grid topology. Moreover calculations are presented on flow devices (leading and trailing edge flaps and vortex generators). Finally results are shown between results from 3D rotor models where a comparison is made between results from vortex wake methods and BEM methods at yawed conditions

Growth regulation and co-stimulation of human colorectal cancer cell lines by insulin-like growth factor I, II and transforming growth factor alpha.

We have tested growth factor responsiveness of a panel of eight human colorectal carcinoma cell lines. Insulin-like growth factors I and II (IGF-I and IGF-II) stimulated growth of five lines (HT-29, LS411N, LS513, SW480, WiDr). At 30 ng ml-1 both factors enhanced growth up to 3-fold. They induced half-maximal stimulation at 1.9-6.51 ng ml-1. Even after delayed addition IGF-I and II significantly enhanced growth in a short-term proliferation assay. They exerted maximal effects under limiting serum conditions (0.5% FCS) and at low cell density (1.25-5 x 10(4) ml-1). Using these conditions transforming growth factor alpha (TGF alpha) enhanced proliferation of all IGF-responsive cell lines, except SW480. 1.11-3.31 ng ml-1 were required to obtain a half-maximal response. With 10-20 ng ml-1 maximal stimulation occurred at plateau values different from those for IGF-I/II. Proliferation of all cell lines responsive to both IGF-I and TGF alpha was further enhanced by combining both factors, resulting a synergistic response of LS513, while the effects on HT-29, LS411N and WiDr were additive. With HT-29 and LS411N a 24 h exposure to TGF alpha was sufficient to obtain a full response in the co-stimulatory assay. Our results illustrate the importance of IGF-I/II and TGF alpha as stimulators of growth of colorectal carcinomas

Open string theory and planar algebras

In this note we show that abstract planar algebras are algebras over the topological operad of moduli spaces of stable maps with Lagrangian boundary conditions, which in the case of the projective line are described in terms of real rational functions. These moduli spaces appear naturally in the formulation of open string theory on the projective line. We also show two geometric ways to obtain planar algebras from real algebraic geometry, one based on string topology and one on Gromov-Witten theory. In particular, through the well known relation between planar algebras and subfactors, these results establish a connection between open string theory, real algebraic geometry, and subfactors of von Neumann algebras.Comment: 13 pages, LaTeX, 7 eps figure

Antibacterial, antioxidant and anti-proliferative properties and zinc content of five south Portugal herbs

Context: Crataegus monogyna L. (Rosaceae) (CM), Equisetum telmateia L. (Equisataceae) (ET), Geranium purpureum Vil. (Geraniaceae) (GP), Mentha suaveolens Ehrh. (Lamiaceae) (MS), and Lavandula stoechas L. spp. luisieri (Lamiaceae) (LS) are all medicinal. Objective: To evaluate the antioxidant, antiproliferative and antimicrobial activities of plant extracts and quantify individual phenolics and zinc. Material and methods: Aerial part extracts were prepared with water (W), ethanol (E) and an 80% mixture (80EW). Antioxidant activity was measured with TAA, FRAP and RP methods. Phenolics were quantified with a HPLC. Zinc was quantified using voltammetry. Antibacterial activity (after 48 h) was tested using Enterococcus faecalis, Bacillus cereus, Escherichia coli, Staphylococcus aureus, Pseudomonas aeruginosa and Listeria monocytogenes. Antiproliferative activity (after 24 h) was tested using HEP G2 cells and fibroblasts. Results: Solvents influenced results; the best were E and 80EW. GP had the highest antioxidant activity (TAA and FRAP of 536.90mg AAE/g dw and 783.48mg TE/g dw, respectively). CM had the highest zinc concentration (37.21 mg/kg) and phenolic variety, with neochlorogenic acid as the most abundant (92.91 mg/100 g dw). LS was rich in rosmarinic acid (301.71 mg/100 g dw). GP and LS inhibited the most microorganisms: B. cereus, E. coli and S. aureus. GP also inhibited E. faecalis. CM had the lowest MIC: 5830 mu g/mL. The antibacterial activity is explained by the phenolics present. LS and CM showed the most significant anti-proliferative activity, which is explained by their zinc content. Conclusion: The most promising plants for further studies are CM, LS and GP.FCT, Fundacao para a Ciencia e a Tecnologia of Portugal [SFRH/BSA/139/2014