In this paper we report the set-up and results of the Multimodal Brain Tumor Image Segmentation Benchmark (BRATS) organized in conjunction with the MICCAI 2012 and 2013 conferences. Twenty state-of-the-art tumor segmentation algorithms were applied to a set of 65 multi-contrast MR scans of low- and high-grade glioma patients—manually annotated by up to four raters—and to 65 comparable scans generated using tumor image simulation software. Quantitative evaluations revealed considerable disagreement between the human raters in segmenting various tumor sub-regions (Dice scores in the range 74%–85%), illustrating the difficulty of this task. We found that different algorithms worked best for different sub-regions (reaching performance comparable to human inter-rater variability), but that no single algorithm ranked in the top for all sub-regions simultaneously. Fusing several good algorithms using a hierarchical majority vote yielded segmentations that consistently ranked above all individual algorithms, indicating remaining opportunities for further methodological improvements. The BRATS image data and manual annotations continue to be publicly available through an online evaluation system as an ongoing benchmarking resource.

Here we present a scheme to separate particles according to their characteristic physical properties, including size, charge, polarizability, deformability, surface charge mobility, dielectric features, and local capacitance. Separation is accomplished using a microdevice based on direct current insulator gradient dielectrophoresis that can isolate and concentrate multiple analytes simultaneously at different positions. The device is dependent upon dielectrophoretic and electrokinetic forces incorporating a global longitudinal direct current field as well as using shaped insulating features within the channel to induce local gradients. This design allows for the production of strong local field gradients along a global field causing particles to enter, initially transported through the channel by electrophoresis and electroosmosis (electrokinetics), and to be isolated via repulsive dielectrophoretic forces that are proportional to an exponent of the field gradient. Sulfate-capped polystyrene nano and microparticles (20, 200 nm, and 1 μm) were used as probes to demonstrate the influence of channel geometry and applied longitudinal field on separation behavior. These results are consistent with models using similar channel geometry and indicate that specific particulate species can be isolated within a distinct portion of the device, whereas concentrating particles by factors from 10(3) to 10(6).

Insulator based dielectrophoresis is powerful tool for separating and charactering particles, yet it is limited by a lack of quantitative characterizations. Here this limitation is addressed by employing a method capable of quantifying the dielectrophoretic mobility of particles. Using streak-based velocimetry the particle properties are deduced from their motion in a microfluidic channel with a constant electric field gradient. From this approach the dielectrophoretic mobility of 1 μm polystyrene particles was found to be −2 ± 0.4 × 10−8 cm4/(V2·s). In the future, such quantitative treatment will allow for the elucidation of unique insights and rational design of devices.

The performance of fallible counters is investigated in the context of pacemaker-counter models of interval timing. Failure to reliably transmit signals from one stage of a counter to the next generates periodicity in mean and variance of counts registered, with means power functions of input and standard deviations approximately proportional to the means (Weber's law). The transition diagrams and matrices of the counter are self-similar: Their eigenvalues have a fractal form and closely approximate Julia sets. The distributions of counts registered and of hitting times approximate Weibull densities, which provide the foundation for a signal-detection model of discrimination. Different schemes for weighting the values of each stage may be established by conditioning. As higher order stages of a cascade come on-line the veridicality of lower order stages degrades, leading to scale-invariance in error. The capacity of a counter is more likely to be limited by fallible transmission between stages than by a paucity of stages. Probabilities of successful transmission between stages of a binary counter around 0.98 yield predictions consistent with performance in temporal discrimination and production and with channel capacities for identification of unidimensional stimuli.

This study presents an unbiased high-resolution separation and characterization of NSPC subpopulations using direct current insulator-based dielectrophoresis.

BACKGROUND In 2008, the US Food and Drug Administration (FDA) issued a Guidance for Industry statement formally recognizing (during drug development) the conjoined nature of type 2 diabetes (T2D) and cardiovascular disease (CVD), which has precipitated an urgent need for panels of markers (and means of analysis) that are able to differentiate subtypes of CVD in the context of T2D. Here, we explore the possibility of creating such panels using the working hypothesis that proteins, in addition to carrying time-cumulative marks of hyperglycemia (e.g., protein glycation in the form of Hb A1c), may carry analogous information with regard to systemic oxidative stress and aberrant enzymatic signaling related to underlying pathobiologies involved in T2D and/or CVD. METHODS We used mass spectrometric immunoassay to quantify, in targeted fashion, relative differences in the glycation, oxidation, and truncation of 11 specific proteins. RESULTS Protein oxidation and truncation (owing to modified enzymatic activity) are able to distinguish between subsets of diabetic patients with or without a history of myocardial infarction and/or congestive heart failure where markers of glycation alone cannot. CONCLUSION Markers based on protein modifications aligned with the known pathobiologies of T2D represent a reservoir of potential cardiovascular markers that are needed to develop the next generation of antidiabetes medications.

How might religion shape intergroup conflict? We tested whether religious infusion-the extent to which religious rituals and discourse permeate the everyday activities of groups and their members-moderated the effects of two factors known to increase intergroup conflict: competition for limited resources and incompatibility of values held by potentially conflicting groups. We used data from the Global Group Relations Project to investigate 194 groups (e.g., ethnic, religious, national) at 97 sites around the world. When religion was infused in group life, groups were especially prejudiced against those groups that held incompatible values, and they were likely to discriminate against such groups. Moreover, whereas disadvantaged groups with low levels of religious infusion typically avoided directing aggression against their resource-rich and powerful counterparts, disadvantaged groups with high levels of religious infusion directed significant aggression against them-despite the significant tangible costs to the disadvantaged groups potentially posed by enacting such aggression. This research suggests mechanisms through which religion may increase intergroup conflict and introduces an innovative method for performing nuanced, cross-societal research.

The optimal strategy in detection theory is to partition the decision axis at a criterion C, labeling all events that score above C "Signal", and all those that fall below "Noise." The optimal position of C, C*, depends on signal probability and payoffs. If observers place their criterion at some place other than C*, they suffer a loss in the Expected Value (EV) of payoffs over the course of many decisions. We provide an explicit equation for the degree of loss, where it is shown that the falloff in value will be steep in contexts of good discrimination and will be a flatter gradient in contexts of poor discrimination. It is these gradients of loss in EV that, in theory, drive C toward C*, strongly when discrimination is good, weakly when discrimination is poor. When signal probabilities or distributions variances are unequal, the basins of attraction are asymmetric, so that dynamic adjustments in C will be asymmetric, and thus, as we show, will leave it biased. We address our analysis to acquisition speed, response variability, discrimination reversal and other aspects of discriminated performance. In the final section, we develop an error correction model that predicts empirically observed deviations from C* that are inconsistent with the standard model, but follow from the proposed model given knowledge of d'. (PsycINFO Database Record