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

Source sentence simplification for statistical machine translation

Long sentences with complex syntax and long-distance dependencies pose difficulties for machine translation systems. Short sentences, on the other hand, are usually easier to translate. We study the potential of addressing this mismatch using text simplifi- cation: given a simplified version of the full input sentence, can we use it in addition to the full input to improve translation? We show that the spaces of original and simplified translations can be effectively combined using translation lattices and compare two decoding approaches to process both inputs at different levels of integration. We demonstrate on source-annotated portions of WMT test sets and on top of strong baseline systems combining hierarchical and neural translation for two language pairs that source simplification can help to improve translation quality.This work was supported by the EPSRC grant Improving Target Language Fluency in Statistical Machine Translation, grant number EP/L027623/1

Coiled-coil protein composition of 22 proteomes – differences and common themes in subcellular infrastructure and traffic control

BACKGROUND: Long alpha-helical coiled-coil proteins are involved in diverse organizational and regulatory processes in eukaryotic cells. They provide cables and networks in the cyto- and nucleoskeleton, molecular scaffolds that organize membrane systems and tissues, motors, levers, rotating arms, and possibly springs. Mutations in long coiled-coil proteins have been implemented in a growing number of human diseases. Using the coiled-coil prediction program MultiCoil, we have previously identified all long coiled-coil proteins from the model plant Arabidopsis thaliana and have established a searchable Arabidopsis coiled-coil protein database. RESULTS: Here, we have identified all proteins with long coiled-coil domains from 21 additional fully sequenced genomes. Because regions predicted to form coiled-coils interfere with sequence homology determination, we have developed a sequence comparison and clustering strategy based on masking predicted coiled-coil domains. Comparing and grouping all long coiled-coil proteins from 22 genomes, the kingdom-specificity of coiled-coil protein families was determined. At the same time, a number of proteins with unknown function could be grouped with already characterized proteins from other organisms. CONCLUSION: MultiCoil predicts proteins with extended coiled-coil domains (more than 250 amino acids) to be largely absent from bacterial genomes, but present in archaea and eukaryotes. The structural maintenance of chromosomes proteins and their relatives are the only long coiled-coil protein family clearly conserved throughout all kingdoms, indicating their ancient nature. Motor proteins, membrane tethering and vesicle transport proteins are the dominant eukaryote-specific long coiled-coil proteins, suggesting that coiled-coil proteins have gained functions in the increasingly complex processes of subcellular infrastructure maintenance and trafficking control of the eukaryotic cell

Shaping Cooperation Behavior: The Role of Accessibility Experiences

The present research investigates the influence on cooperative behavior of accessibility experiences associated with the retrieval of fairness-relevant information from memory. We argue that the decision whether to cooperate in negotiations depends not only on information about the appropriateness of the negotiation procedure, but also on the experience of how difficult or easy it is to come up with this information. Supporting this hypothesis, it is shown that in the context of a bargaining experiment, participants' experiences of ease or difficulty in retrieving unfair aspects of the respective negotiation procedure strongly influence their cooperation behavior. In addition, we hypothesize and empirically substantiate that the influence of accessibility experiences on cooperation behavior occurs particularly in situations of certainty salience. Implications for future research on cooperation and on accessibility experiences are discussed

Product assurance technology for custom LSI/VLSI electronics

The technology for obtaining custom integrated circuits from CMOS-bulk silicon foundries using a universal set of layout rules is presented. The technical efforts were guided by the requirement to develop a 3 micron CMOS test chip for the Combined Release and Radiation Effects Satellite (CRRES). This chip contains both analog and digital circuits. The development employed all the elements required to obtain custom circuits from silicon foundries, including circuit design, foundry interfacing, circuit test, and circuit qualification

Progress in the analysis of membrane protein structure and function

Structural information on membrane proteins is sparse, yet they represent an important class of proteins that is encoded by about 30% of all genes. Progress has primarily been achieved with bacterial proteins, but efforts to solve the structure of eukaryotic membrane proteins are also increasing. Most of the structures currently available have been obtained by exploiting the power of X-ray crystallography. Recent results, however, have demonstrated the accuracy of electron crystallography and the imaging power of the atomic force microscope. These instruments allow membrane proteins to be studied while embedded in the bi-layer, and thus in a functional state. The low signal-to-noise ratio of cryo-electron microscopy is overcome by crystallizing membrane proteins in a two- dimensional protein-lipid membrane, allowing its atomic structure to be determined. In contrast, the high signal-to- noise ratio of atomic force microscopy allows individual protein surfaces to be imaged at subnanometer resolution, and their conformational states to be sampled. This review summarizes the steps in membrane protein structure determination and illuminates recent progress. (C) 2002 Published by Elsevier Science B.V. on behalf of the Federation of European Biochemical Societies

Syntactically Guided Neural Machine Translation

We investigate the use of hierarchical phrase-based SMT lattices in end-to-end neural machine translation (NMT). Weight pushing transforms the Hiero scores for complete translation hypotheses, with the full translation grammar score and full n-gram language model score, into posteriors compatible with NMT predictive probabilities. With a slightly modified NMT beam-search decoder we find gains over both Hiero and NMT decoding alone, with practical advantages in extending NMT to very large input and output vocabularies.Engineering and Physical Sciences Research Council (Grant ID: EP/L027623/1

Coordination-Driven Monolayer-to-Bilayer Transition in 2D Metal-Organic Networks

We report on monolayer-to-bilayer transitions in 2D metal−organic networks (MONs) from amphiphiles supported at the water−air interface. Functionalized calix[4]arenes are assembled through the coordination of selected transition metal ions to yield monomolecular 2D crystalline layers. In the presence of Ni(II) ions, interfacial self-assembly and coordination yields stable monolayers. Cu(II) promotes 2D coordination of a monolayer which is then diffusively reorganizing, nucleates, and grows a progressive amount of second layer islands. Atomic force microscopic data of these layers after transfer onto solid substrates reveal crystalline packing geometries with submolecular resolution as they are varying in function of the building blocks and the kinetics of the assembly. We assign this monolayer-to- bilayer transition to a diffusive reorganization of the initial monolayers owing to chemical vacancies of the predominant coordination motif formed by Cu2+ ions. Our results introduce a new dimension into the controlled monolayer-to-multilayer architecturing of 2D metal− organic networks

Neural Machine Translation by Minimising the Bayes-risk with Respect to Syntactic Translation Lattices

We present a novel scheme to combine neural machine translation (NMT) with traditional statistical machine translation (SMT). Our approach borrows ideas from linearised lattice minimum Bayes-risk decoding for SMT. The NMT score is combined with the Bayes-risk of the translation according the SMT lattice. This makes our approach much more flexible than n-best list or lattice rescoring as the neural decoder is not restricted to the SMT search space. We show an efficient and simple way to integrate risk estimation into the NMT decoder which is suitable for word-level as well as subword-unit-level NMT. We test our method on English-German and Japanese-English and report significant gains over lattice rescoring on several data sets for both single and ensembled NMT. The MBR decoder produces entirely new hypotheses far beyond simply rescoring the SMT search space or fixing UNKs in the NMT output.This work was supported by the U.K. Engineering and Physical Sciences Research Council (EPSRC grant EP/L027623/1)