The effect of pre-exposure on family resemblance categorization for stimuli of varying levels of perceptual difficulty

This study investigated the effect that pre-exposure to a set of stimuli has on the prevalence of family resemblance categorization. 64 participants were tested to examine the effect that pre-exposure type (same-stimuli vs unrelated-stimuli) and the perceptual difficulty of the stimuli (perceptually similar vs perceptually different) has on categorization strategy. There was a significant effect of perceptual difficulty, indicating that perceptually different stimuli evoked a higher level of family resemblance sorting than perceptually similar stimuli. There was no significant main effect of pre-exposure type; however, there was a significant interaction between pre-exposure type and level of perceptual difficulty. Post-hoc tests revealed that this interaction was the result of an increase in family resemblance sorting for the perceptually different stimuli under relevant preexposure but no such effect for perceptually similar stimuli. The theoretical implications of these findings are discussed

The magnetic properties of zinc and its compounds

The object of this research is an investigation of the magnetic properties of Zinc and its commoner compounds. The magnetic susceptibilities of twenty-eight highly purified zinc compounds have been determined , and from a consideration of the values obtained a mean experimental value of the susceptibility of the Zinc ion has been found, a comparison between the experimental value and the theoretical value, calculated from considerations of atomic structure, has been made. From a consideration of the molecular susceptibilities of the compounds measured, it-was found that there is a probable relationship between magnetic susceptibility and co-ordination number. The susceptibilities of the Zinc halides were found and, from a graph showing the relationship between molar susceptibility and the total number of electrons, it was found that Ikenmeyer's flattening of the curve is without justification. From the susceptibilities of the organic salts measured, the value of the group has been calculated; and also, the effect of substituting a Qhlorine atom for a Hydrogen atom in the side-chain of a fatty acid, has been estimated. The zinc salts of the oxy-acids of Phosphorous were found to behave in an anomalous manner. There was found to be some regularity in these compounds showing that the anomaly is similar throughout the series.<p

Detecting modification of biomedical events using a deep parsing approach

<p>Abstract</p> <p>Background</p> <p>This work describes a system for identifying event mentions in bio-molecular research abstracts that are either speculative (e.g. <it>analysis of IkappaBalpha phosphorylation</it>, where it is not specified whether phosphorylation did or did not occur) or negated (e.g. <it>inhibition of IkappaBalpha phosphorylation</it>, where phosphorylation did <it>not </it>occur). The data comes from a standard dataset created for the BioNLP 2009 Shared Task. The system uses a machine-learning approach, where the features used for classification are a combination of shallow features derived from the words of the sentences and more complex features based on the semantic outputs produced by a deep parser.</p> <p>Method</p> <p>To detect event modification, we use a Maximum Entropy learner with features extracted from the data relative to the trigger words of the events. The shallow features are bag-of-words features based on a small sliding context window of 3-4 tokens on either side of the trigger word. The deep parser features are derived from parses produced by the English Resource Grammar and the <it>RASP </it>parser. The outputs of these parsers are converted into the Minimal Recursion Semantics formalism, and from this, we extract features motivated by linguistics and the data itself. All of these features are combined to create training or test data for the machine learning algorithm.</p> <p>Results</p> <p>Over the test data, our methods produce approximately a 4% absolute increase in F-score for detection of event modification compared to a baseline based only on the shallow bag-of-words features.</p> <p>Conclusions</p> <p>Our results indicate that grammar-based techniques can enhance the accuracy of methods for detecting event modification.</p

The effect of pre-exposure on overall similarity categorization

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Excavating the 'Rutland Sea Dragon': The largest ichthyosaur skeleton ever found in the UK (Whitby Mudstone Formation, Toarcian, Lower Jurassic)

An almost complete ichthyosaur skeleton 10 m long was discovered in January 2021 at the Rutland Water Nature Reserve in the county of Rutland, UK. This was excavated by a small team of palaeontologists in the summer of the same year. Nicknamed ‘The Rutland Sea Dragon’, this almost fully articulated skeleton is an example of the large-bodied Early Jurassic ichthyosaur Temnodontosaurus. The specimen was analysed in situ, recorded (including a 3D scan using photogrammetry), excavated and removed from the site in a series of large plaster field jackets to preserve taphonomic information. Significantly, the specimen is the largest ichthyosaur skeleton to have been found in the UK and it may be the first recorded example of Temnodontosaurus trigonodon to be found in the country, extending its known geographic range significantly. It also represents the most complete skeleton of a large prehistoric reptile to have been found in the UK. We provide an account of the discovery and describe the methods used for excavating, recording and lifting the large skeleton which will aid palaeontologists facing similar challenges when collecting extensive remains of large and fragile fossil vertebrates. We also discuss the preliminary research findings and the global impact this discovery has had through public engagement

Automated annotation of chemical names in the literature with tunable accuracy

<p>Abstract</p> <p>Background</p> <p>A significant portion of the biomedical and chemical literature refers to small molecules. The accurate identification and annotation of compound name that are relevant to the topic of the given literature can establish links between scientific publications and various chemical and life science databases. Manual annotation is the preferred method for these works because well-trained indexers can understand the paper topics as well as recognize key terms. However, considering the hundreds of thousands of new papers published annually, an automatic annotation system with high precision and relevance can be a useful complement to manual annotation.</p> <p>Results</p> <p>An automated chemical name annotation system, MeSH Automated Annotations (MAA), was developed to annotate small molecule names in scientific abstracts with tunable accuracy. This system aims to reproduce the MeSH term annotations on biomedical and chemical literature that would be created by indexers. When comparing automated free text matching to those indexed manually of 26 thousand MEDLINE abstracts, more than 40% of the annotations were false-positive (FP) cases. To reduce the FP rate, MAA incorporated several filters to remove "incorrect" annotations caused by nonspecific, partial, and low relevance chemical names. In part, relevance was measured by the position of the chemical name in the text. Tunable accuracy was obtained by adding or restricting the sections of the text scanned for chemical names. The best precision obtained was 96% with a 28% recall rate. The best performance of MAA, as measured with the F statistic was 66%, which favorably compares to other chemical name annotation systems.</p> <p>Conclusions</p> <p>Accurate chemical name annotation can help researchers not only identify important chemical names in abstracts, but also match unindexed and unstructured abstracts to chemical records. The current work is tested against MEDLINE, but the algorithm is not specific to this corpus and it is possible that the algorithm can be applied to papers from chemical physics, material, polymer and environmental science, as well as patents, biological assay descriptions and other textual data.</p