Exploring the relationship between research funding and social media: disciplinary analysis of the distribution of funding acknowledgements and Twitter mention in scientific publications

This article presents an exploratory analysis of which disciplines acknowledge more financial support (through funding acknowledgments - FA) and those whose publications attract more attention on Twitter. We argue that such combined approach can provide interesting information for both funding bodies and policy makers about how funding activities and the attention in social media of scientific research relate to each other

The Use of Reaction Kinetics in Classifying Alkali Silica Reactivity Potential of Aggregates

The Australian Standard accelerated mortar bar test (AMBT) method, AS 1141.60.1, adopts the expansion limits at two exposure periods to classify the alkali silica reactivity (ASR) of aggregate. This was a first step toward the use of ‘reaction kinetics’ or ‘rate of reaction’ to detect and classify alkali silica reactivity. The AS 1141.60.2 concrete prism test (CPT), on the other hand, uses a single expansion limit at one year to classify ASR. This paper examines the validity of the use of reaction kinetics, evaluated from the AMBT expansion data, to gauge and classify the reactivity. This may enable a better quantification of the degrees of reactivity and a more fundamental approach to ASR mitigatio

SBML models and MathSBML

MathSBML is an open-source, freely-downloadable Mathematica package that facilitates working with Systems Biology Markup Language (SBML) models. SBML is a toolneutral,computer-readable format for representing models of biochemical reaction networks, applicable to metabolic networks, cell-signaling pathways, genomic regulatory networks, and other modeling problems in systems biology that is widely supported by the systems biology community. SBML is based on XML, a standard medium for representing and transporting data that is widely supported on the internet as well as in computational biology and bioinformatics. Because SBML is tool-independent, it enables model transportability, reuse, publication and survival. In addition to MathSBML, a number of other tools that support SBML model examination and manipulation are provided on the sbml.org website, including libSBML, a C/C++ library for reading SBML models; an SBML Toolbox for MatLab; file conversion programs; an SBML model validator and visualizer; and SBML specifications and schemas. MathSBML enables SBML file import to and export from Mathematica as well as providing an API for model manipulation and simulation

Take Me Out In A Velie Car

https://digitalcommons.library.umaine.edu/mmb-vp/6353/thumbnail.jp

Deformation and rupture of armour grade steel under localised blast loading

A series of 30 blast experiments were conducted on monolithic steel panels of two armour grade steels. The two steels evaluated were a high hardness armour (HHA) and a rolled homogenous armour (RHA). Tests were conducted at two standoff distances using a fixed charge diameter. The charge weight was varied to produce specific magnitudes of blast loading and to isolate the rupture threshold of each material. The results indicated that the HHA steel, generally reserved for ballistic protection, outperformed a more ductile RHA steel in terms of both its deformation resistance and rupture threshold. Optical and scanning electron microscopy was utilised for fractographic analysis of the ruptured plates. The failure of the steels in this investigation was found to be initiated by slant shear fracture with little to no localised thinning. This is in contrast to the tensile instability and ductile tearing predicted by established theories of plate rupture for mild steels under blast loading. The deformation and rupture of the candidate steels was analysed for all experimental conditions and compared to current empirical models based on a non-dimensional impulse parameter. While deformation behaviour is well predicted, the blast rupture threshold of the armour grade steels is poorly captured by current empirical modelling approaches. The identified shear fracture mode leads to lower energy absorption capabilities of the material compared to more ductile tensile failure

Reinstated episodic context guides sampling-based decisions for reward.

How does experience inform decisions? In episodic sampling, decisions are guided by a few episodic memories of past choices. This process can yield choice patterns similar to model-free reinforcement learning; however, samples can vary from trial to trial, causing decisions to vary. Here we show that context retrieved during episodic sampling can cause choice behavior to deviate sharply from the predictions of reinforcement learning. Specifically, we show that, when a given memory is sampled, choices (in the present) are influenced by the properties of other decisions made in the same context as the sampled event. This effect is mediated by fMRI measures of context retrieval on each trial, suggesting a mechanism whereby cues trigger retrieval of context, which then triggers retrieval of other decisions from that context. This result establishes a new avenue by which experience can guide choice and, as such, has broad implications for the study of decisions

The definition and diagnosis of developmental prosopagnosia.

Over the last 20 years much attention in the field of face recognition has been directed towards the study of developmental prosopagnosia (DP), with some authors investigating the behavioural characteristics of the condition, and many others using these individuals to further our theoretical understanding of the typical face-processing system. It is broadly agreed that the term "DP" refers to people who have failed to develop the ability to recognize faces in the absence of neurological illness or injury, yet more precise terminology in relation to potential subtypes of the population are yet to be confirmed. Furthermore, specific diagnostic techniques and inclusion and exclusion criteria have yet to be uniformly accepted across the field, making cross-paper comparisons and meta-analyses very difficult. This paper presents an overview of the current challenges that face research into DP and introduces a series of papers that attempt to further our understanding of the condition's characteristics. It is hoped that this special issue will provide a springboard for further research addressing these issues, improving the current state of the art by ensuring the quality of theoretical investigations into DP, and by posing advances that will assist those who have the condition