Dual-Target Cost in Visual Search for Multiple Unfamiliar Faces.

The efficiency of visual search for one (single-target) and either of two (dual-target) unfamiliar faces was explored to understand the manifestations of capacity and guidance limitations in face search. The visual similarity of distractor faces to target faces was manipulated using morphing (Experiments 1 and 2) and multidimensional scaling (Experiment 3). A dual-target cost was found in all experiments, evidenced by slower and less accurate search in dual- than single-target conditions. The dual-target cost was unequal across the targets, with performance being maintained on one target and reduced on the other, which we label "preferred" and "non-preferred" respectively. We calculated the capacity for each target face and show reduced capacity for representing the non-preferred target face. However, results show that the capacity for the non-preferred target can be increased when the dual-target condition is conducted after participants complete the single-target conditions. Analyses of eye movements revealed evidence for weak guidance of fixations in single-target search, and when searching for the preferred target in dual-target search. Overall, the experiments show dual-target search for faces is capacity- and guidance-limited, leading to superior search for 1 face over the other in dual-target search. However, learning faces individually may improve capacity with the second face. (PsycINFO Database Recor

Understanding the contribution of target repetition and target expectation to the emergence of the prevalence effect in visual search

Behavior in visual search tasks is influenced by the proportion of trials on which a target is presented (the target prevalence). Previous research has found that when target prevalence is low (2% prevalence), participants tend to miss targets, compared with higher prevalence levels (e.g., 50% prevalence). There is an ongoing debate regarding the relative contribution of target repetition and the expectation that a target will occur in the emergence of prevalence effects. In order to disentangle these two factors, we went beyond previous studies by directly manipulating participants’ expectations regarding how likely a target was to appear on a given trial. This we achieved without using cues or feedback. Our results indicated both target repetition and target expectation contribute to the emergence of the prevalence effect

The Spectatorship of Portraits by Naïve Beholders

The spectatorship of portraits by naïve viewers (beholders) was explored in a single experiment. Twenty-five participants rated their liking for 142 portraits painted by Courbet (36 paintings), Fantin-Latour (36 paintings) and Manet (70 paintings) on a 4-point Likert scale. The portraits were classified in terms of focussed versus ambiguous nature of sitter gaze and the presence of salient features in the context beyond sitters. Participants rated portraits while having their eye movements recorded. The portraits were split into regions of interest (ROIs) defined by faces, bodies and context. Participants also completed individual difference measures of attention and task focus. Results showed naïve spectatorship to be subject to attentional capture by faces. Paradoxically, the presence of salient features in the context amplified the attentional capture by faces through increasing participants liking of portraits. Attentional capture by faces was also influenced by sitter gaze and task focus. Unsurprisingly, the spectatorship of portraits by naïve beholders is dominated by faces, but the extent of this dominance is influenced by exogenous and endogenous attentional factors

Assessing the benefits of stereoscopic displays to visual search: methodology and initial findings

Visual search is a task that is carried out in a number of important security and health related scenarios (e.g., X-ray baggage screening, radiography). With recent and ongoing developments in the technology available to present images to observers in stereoscopic depth, there has been increasing interest in assessing whether depth information can be used in complex search tasks to improve search performance. Here we outline the methodology that we developed, along with both software and hardware information, in order to assess visual search performance in complex, overlapping stimuli that also contained depth information. In doing so, our goal is to foster further research along these lines in the future. We also provide an overview with initial results of the experiments that we have conducted involving participants searching stimuli that contain overlapping objects presented on different depth planes to one another. Thus far, we have found that depth information does improve the speed (but not accuracy) of search, but only when the stimuli are highly complex and contain a significant degree of overlap. Depth information may therefore aid real-world search tasks that involve the examination of complex, overlapping stimuli

Towards Machine Wald

The past century has seen a steady increase in the need of estimating and predicting complex systems and making (possibly critical) decisions with limited information. Although computers have made possible the numerical evaluation of sophisticated statistical models, these models are still designed \emph{by humans} because there is currently no known recipe or algorithm for dividing the design of a statistical model into a sequence of arithmetic operations. Indeed enabling computers to \emph{think} as \emph{humans} have the ability to do when faced with uncertainty is challenging in several major ways: (1) Finding optimal statistical models remains to be formulated as a well posed problem when information on the system of interest is incomplete and comes in the form of a complex combination of sample data, partial knowledge of constitutive relations and a limited description of the distribution of input random variables. (2) The space of admissible scenarios along with the space of relevant information, assumptions, and/or beliefs, tend to be infinite dimensional, whereas calculus on a computer is necessarily discrete and finite. With this purpose, this paper explores the foundations of a rigorous framework for the scientific computation of optimal statistical estimators/models and reviews their connections with Decision Theory, Machine Learning, Bayesian Inference, Stochastic Optimization, Robust Optimization, Optimal Uncertainty Quantification and Information Based Complexity.Comment: 37 page

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

On the mechanisms governing gas penetration into a tokamak plasma during a massive gas injection

A new 1D radial fluid code, IMAGINE, is used to simulate the penetration of gas into a tokamak plasma during a massive gas injection (MGI). The main result is that the gas is in general strongly braked as it reaches the plasma, due to mechanisms related to charge exchange and (to a smaller extent) recombination. As a result, only a fraction of the gas penetrates into the plasma. Also, a shock wave is created in the gas which propagates away from the plasma, braking and compressing the incoming gas. Simulation results are quantitatively consistent, at least in terms of orders of magnitude, with experimental data for a D 2 MGI into a JET Ohmic plasma. Simulations of MGI into the background plasma surrounding a runaway electron beam show that if the background electron density is too high, the gas may not penetrate, suggesting a possible explanation for the recent results of Reux et al in JET (2015 Nucl. Fusion 55 093013)

Velocity-space sensitivity of the time-of-flight neutron spectrometer at JET

The velocity-space sensitivities of fast-ion diagnostics are often described by so-called weight functions. Recently, we formulated weight functions showing the velocity-space sensitivity of the often dominant beam-target part of neutron energy spectra. These weight functions for neutron emission spectrometry (NES) are independent of the particular NES diagnostic. Here we apply these NES weight functions to the time-of-flight spectrometer TOFOR at JET. By taking the instrumental response function of TOFOR into account, we calculate time-of-flight NES weight functions that enable us to directly determine the velocity-space sensitivity of a given part of a measured time-of-flight spectrum from TOFOR

Driver Fusions and Their Implications in the Development and Treatment of Human Cancers.

Gene fusions represent an important class of somatic alterations in cancer. We systematically investigated fusions in 9,624 tumors across 33 cancer types using multiple fusion calling tools. We identified a total of 25,664 fusions, with a 63% validation rate. Integration of gene expression, copy number, and fusion annotation data revealed that fusions involving oncogenes tend to exhibit increased expression, whereas fusions involving tumor suppressors have the opposite effect. For fusions involving kinases, we found 1,275 with an intact kinase domain, the proportion of which varied significantly across cancer types. Our study suggests that fusions drive the development of 16.5% of cancer cases and function as the sole driver in more than 1% of them. Finally, we identified druggable fusions involving genes such as TMPRSS2, RET, FGFR3, ALK, and ESR1 in 6.0% of cases, and we predicted immunogenic peptides, suggesting that fusions may provide leads for targeted drug and immune therapy

Relationship of edge localized mode burst times with divertor flux loop signal phase in JET

A phase relationship is identified between sequential edge localized modes (ELMs) occurrence times in a set of H-mode tokamak plasmas to the voltage measured in full flux azimuthal loops in the divertor region. We focus on plasmas in the Joint European Torus where a steady H-mode is sustained over several seconds, during which ELMs are observed in the Be II emission at the divertor. The ELMs analysed arise from intrinsic ELMing, in that there is no deliberate intent to control the ELMing process by external means. We use ELM timings derived from the Be II signal to perform direct time domain analysis of the full flux loop VLD2 and VLD3 signals, which provide a high cadence global measurement proportional to the voltage induced by changes in poloidal magnetic flux. Specifically, we examine how the time interval between pairs of successive ELMs is linked to the time-evolving phase of the full flux loop signals. Each ELM produces a clear early pulse in the full flux loop signals, whose peak time is used to condition our analysis. The arrival time of the following ELM, relative to this pulse, is found to fall into one of two categories: (i) prompt ELMs, which are directly paced by the initial response seen in the flux loop signals; and (ii) all other ELMs, which occur after the initial response of the full flux loop signals has decayed in amplitude. The times at which ELMs in category (ii) occur, relative to the first ELM of the pair, are clustered at times when the instantaneous phase of the full flux loop signal is close to its value at the time of the first ELM