Sit-and-Wait Strategies in Dynamic Visual Search

The role of memory in visual search has lately become a controversial issue. Horowitz and Wolfe (1998) observed that performance in a visual search task was little affected by whether the stimuli were static or randomly relocated every 111 ms. Because a memory-based mechanism, such as inhibition of return, would be of no use in the dynamic condition, Horowitz and Wolfe concluded that memory is likewise not involved in the static condition. However, Horowitz and Wolfe could not effectively rule out the possibility that observers adopted a different strategy in the dynamic condition than in the static condition. That is, in the dynamic condition observers may have attended to a subregion of the display and waited for the target to appear there (sit-and-wait strategy). This hypothesis is supported by experimental data showing that performance in their dynamic condition does not differ from performance in another dynamic condition in which observers are forced to adopt a sit-and-wait strategy by being presented with a limited region of the display only

The Role of Surprise in Hindsight Bias – A Metacognitive Model of Reduced and Reversed Hindsight Bias

Hindsight bias is the well researched phenomenon that people falsely believe that they would have correctly predicted the outcome of an event once it is known. In recent years, several authors have doubted the ubiquity of the effect and have reported a reversal under certain conditions. This article presents an integrative model on the role of surprise as one factor explaining the malleability of the hindsight bias. Three ways in which surprise influences the reconstruction of pre-outcome predictions are assumed: (1) Surprise is used as direct metacognitive heuristic to estimate the distance between outcome and prediction. (2) Surprise triggers a deliberate sense-making process, and (3) also biases this process by enhancing the retrieval of surprise-congruent information and expectancy-based hypothesis testing.

The role of surprise in hindsight bias : a metacognitive model of reduced and reversed hindsight bias

Hindsight bias is the well researched phenomenon that people falsely believe that they would have correctly predicted the outcome of an event once it is known. In recent years, several authors have doubted the ubiquity of the effect and have reported a reversal under certain conditions. This article presents an integrative model on the role of surprise as one factor explaining the malleability of the hindsight bias. Three ways in which surprise influences the reconstruction of pre-outcome predictions are assumed: (1) Surprise is used as direct metacognitive heuristic to estimate the distance between outcome and prediction. (2) Surprise triggers a deliberate sense-making process, and (3) also biases this process by enhancing the retrieval of surprise-congruent information and expectancy-based hypothesis testing

Quantitative analysis of backscattered‐electron contrast in scanning electron microscopy

Backscattered-electron scanning electron microscopy (BSE-SEM) imaging is a valuable technique for materials characterisation because it provides information about the homogeneity of the material in the analysed specimen and is therefore an important technique in modern electron microscopy. However, the information contained in BSE-SEM images is up to now rarely quantitatively evaluated. The main challenge of quantitative BSE-SEM imaging is to relate the measured BSE intensity to the backscattering coefficient η and the (average) atomic number Z to derive chemical information from the BSE-SEM image. We propose a quantitative BSE-SEM method, which is based on the comparison of Monte–Carlo (MC) simulated and measured BSE intensities acquired from wedge-shaped electron-transparent specimens with known thickness profile. The new method also includes measures to improve and validate the agreement of the MC simulations with experimental data. Two different challenging samples (ZnS/Zn(O$_x$S$_{1–x}$)/ZnO/Si-multilayer and PTB7/PC$_{71}$BM-multilayer systems) are quantitatively analysed, which demonstrates the validity of the proposed method and emphasises the importance of realistic MC simulations for quantitative BSE-SEM analysis. Moreover, MC simulations can be used to optimise the imaging parameters (electron energy, detection-angle range) in advance to avoid tedious experimental trial and error optimisation. Under optimised imaging conditions pre-determined by MC simulations, the BSE-SEM technique is capable of distinguishing materials with small composition differences

Electron-beam broadening in electron microscopy by solving the electron transport equation

Scanning transmission electron microscopy (STEM) and scanning electron microscopy (SEM) are prominent techniques for the structural characterization of materials. STEM in particular provides high spatial resolution down to the sub-ångström range. The spatial resolution in STEM and SEM is ultimately limited by the electron-beam diameter provided by the microscope\u27s electron optical system. However, the resolution is frequently degraded by the interaction between electron and matter leading to beam broadening, which depends on the thickness of the analyzed sample. Numerous models are available to calculate beam broadening. However, most of them neglect the energy loss of the electrons and large-angle scattering. These restrictions severely limit the applicability of the approaches for large sample thicknesses in STEM and SEM. In this work, we address beam broadening in a more general way. We numerically solve the electron transport equation without any simplifications, and take into account energy loss along the electron path. For this purpose, we developed the software package CeTE (Computation of electron Transport Equation). We determine beam broadening, energy deposition, and the interaction volume of the scattered electrons in homogeneous matter. The calculated spatial and angular distributions of electrons are not limited to forward scattering and small sample thicknesses. We focus on low electron energies of 30 keV and below, where beam broadening is particularly pronounced. These electron energies are typical for SEM and STEM in scanning electron microscopes

Histidine Residue 94 Is Involved in pH Sensing by Histidine Kinase ArsS of Helicobacter pylori

The ArsRS two-component system is the master regulator of acid adaptation in the human gastric pathogen Helicobacter pylori. Low pH is supposed to trigger the autophosphorylation of the histidine kinase ArsS and the subsequent transfer of the phosphoryl group to its cognate response regulator ArsR which then acts as an activator or repressor of pH-responsive genes. Orthologs of the ArsRS two-component system are also present in H. pylori's close relatives H. hepaticus, Campylobacter jejuni and Wolinella succinogenes which are non-gastric colonizers.In order to investigate the mechanism of acid perception by ArsS, derivatives of H. pylori 26695 expressing ArsS proteins with substitutions of the histidine residues present in its periplasmic input domain were constructed. Analysis of pH-responsive transcription of selected ArsRS target genes in these mutants revealed that H94 is relevant for pH sensing, however, our data indicate that protonatable amino acids other than histidine contribute substantially to acid perception by ArsS. By the construction and analysis of H. pylori mutants carrying arsS allels from the related epsilon-proteobacteria we demonstrate that WS1818 of W. succinogenes efficiently responds to acidic pH.We show that H94 in the input domain of ArsS is crucial for acid perception in H. pylori 26695. In addition our data suggest that ArsS is able to adopt different conformations depending on the degree of protonation of acidic amino acids in the input domain. This might result in different activation states of the histidine kinase allowing a gradual transcriptional response to low pH conditions. Although retaining considerable similarity to ArsS the orthologous proteins of H. hepaticus and C. jejuni may have evolved to sensors of a different environmental stimulus in accordance with the non gastric habitat of these bacteria

Object-related regularities are processed automatically: evidence from the visual mismatch negativity

One of the most challenging tasks of our visual systems is to structure and integrate the enormous amount of incoming information into distinct coherent objects. It is an ongoing debate whether or not the formation of visual objects requires attention. Implicit behavioral measures suggest that object formation can occur for task-irrelevant and unattended visual stimuli. The present study investigated pre-attentive visual object formation by combining implicit behavioral measures and an electrophysiological indicator of pre-attentive visual irregularity detection, the visual mismatch negativity (vMMN) of the event-related potential. Our displays consisted of two symmetrically arranged, task-irrelevant ellipses, the objects. In addition, there were two discs of either high or low luminance presented on the objects, which served as targets. Participants had to indicate whether the targets were of the same or different luminance. In separate conditions, the targets either usually were enclosed in the same object or in two different objects (standards). Occasionally, the regular target-to-object assignment was changed (deviants). That is, standards and deviants were exclusively defined on the basis of the task-irrelevant target-to-object assignment but not on the basis of some feature regularity. Although participants did not notice the regularity nor the occurrence of the deviation in the sequences, task-irrelevant deviations resulted in increased reaction times. Moreover, compared with physically identical standard displays deviating target-to-object assignments elicited a negative potential in the 246–280 ms time window over posterio-temporal electrode positions which was identified as vMMN. With variable resolution electromagnetic tomography (VARETA) object-related vMMN was localized to the inferior temporal gyrus. Our results support the notion that the visual system automatically structures even task-irrelevant aspects of the incoming information into objects

Quantification of the thickness of TEM samples by low-energy scanning transmission electron microscopy

Precise knowledge of the local sample thickness is often required for quantitative scanning (transmission) electron microscopy (STEM). The local sample thickness can be determined by the comparison of measured intensities from high-angle annular dark-field (HAADF)-STEM at low energies (<30 keV) with Monte-Carlo simulations. However, a suitable choice of the scattering cross-section (CS) used in the simulations is necessary to gain reliable thickness results. In this work, simulations using different CS, including the Screened Rutherford CS and different Mott CSs, were performed. The results were then compared with measurements on samples with known thickness and composition, for which an SEM equipped with a STEM detector was used. In most cases, the Screened Rutherford CS describes the experiment better than other CSs

Beam broadening measured in transmission mode at low electron energies in a scanning electron microscope

The broadening of the electron beam in the sample has to be considered when performing scanning transmission electron microscopy (STEM) at low primary electron energies. This work presents direct measurements of the beam broadening in a range of materials. The experimental results are compared with the theoretical model by Gauvin and Rudinsky that uses the concept of anomalous diffusion to obtain an analytical equation for the beam broadening

Degradation of Chloroaromatics: Purification and Characterization of a Novel Type of Chlorocatechol 2,3-Dioxygenase of Pseudomonas putida GJ31

A purification procedure for a new kind of extradiol dioxygenase, termed chlorocatechol 2,3-dioxygenase, that converts 3-chlorocatechol productively was developed. Structural and kinetic properties of the enzyme, which is part of the degradative pathway used for growth of Pseudomonas putida GJ31 with chlorobenzene, were investigated. The enzyme has a subunit molecular mass of 33.4 kDa by sodium dodecyl sulfate-polyacrylamide gel electrophoresis. Estimation of the native Mr value under nondenaturating conditions by gel filtration gave a molecular mass of 135 ± 10 kDa, indicating a homotetrameric enzyme structure (4 × 33.4 kDa). The pI of the enzyme was estimated to be 7.1 ± 0.1. The N-terminal amino acid sequence (43 residues) of the enzyme was determined and exhibits 70 to 42% identity with other extradiol dioxygenases. Fe(II) seems to be a cofactor of the enzyme, as it is for other catechol 2,3-dioxygenases. In contrast to other extradiol dioxygenases, the enzyme exhibited great sensitivity to temperatures above 40°C. The reactivity of this enzyme toward various substituted catechols, especially 3-chlorocatechol, was different from that observed for other catechol 2,3-dioxygenases. Stoichiometric displacement of chloride occurred from 3-chlorocatechol, leading to the production of 2-hydroxymuconate.