Hypothesis Testing Ordinary Meaning

Corpus linguistic tools promise to make determinations of the ordinary meaning (OM) of a word or phrase in a statute more objective, replicable, and transparent. However, significant questions remain as to how corpora may best be employed in the process of determining OM. In this paper, we argue that objectivity, replicability, and transparency are bolstered when legal practitioners take a hypothesis testing approach to determining ordinary meaning. In this approach, the corpus (a large collection of authentic texts) is treated as a sample of data which the practitioner may use to draw inductive inferences about the meaning of the term in question for the population to which the statute applies. This article presents a rationale for viewing OM determinations in this way and a conceptual overview of hypothesis testing as it is employed in the wider scientific community, as well as a step-by-step demonstration of hypothesis testing applied to an OM determination

Targeted treatments for multiple myeloma: Specific role of carfilzomib

Carfilzomib is a selective, irreversible proteasome inhibitor, initially approved in the US in 2012 as single-agent therapy for relapsed and refractory multiple myeloma. Numerous Phase II studies have evaluated carfilzomib in the relapsed and refractory as well as the newly diagnosed setting, and Phase III studies are entering their final analysis. Data continue to grow to support its use as both single-agent therapy and in combination with immunomodulatory and other novel agents. This review discusses the role of carfilzomib in the treatment of multiple myeloma. Its mechanism of action, pharmacokinetics, and role in clinical management will be reviewed

Ulcerative C2 neurocutaneous dysesthesia (trigeminal trophic syndrome in an alternative distribution)

Trigeminal trophic syndrome is an uncommon condition characterized by paresthesia, itch, and self-inflicted wounds following the trigeminal dermatome(s). Similar processes adhering to cervical nerve distributions have been reported, calling into question the specificity of trigeminal trophic syndrome for the trigeminal network. Herein, we report patient with trigeminal trophic syndrome adhering to the C2 dermatome, a previously unreported distribution

Type 2 myocardial infarction: the chimaera of cardiology?

The term type 2 myocardial infarction first appeared as part of the universal definition of myocardial infarction. It was introduced to cover a group of patients who had elevation of cardiac troponin but did not meet the traditional criteria for acute myocardial infarction although they were considered to have an underlying ischaemic aetiology for the myocardial damage observed. Since first inception, the term type 2 myocardial infarction has always been vague. Although attempts have been made to produce a systematic definition of what constitutes a type 2 myocardial infarction, it has been more often characterised by what it is not rather than what it is. Clinical studies that have used type 2 myocardial infarction as a diagnostic criterion have produced disparate incidence figures. The range of associated clinical conditions differs from study to study. Additionally, there are no agreed or evidence-based treatment strategies for type 2 myocardial infarction. The authors believe that the term type 2 myocardial infarction is confusing and not evidence-based. They consider that there is good reason to stop using this term and consider instead the concept of secondary myocardial injury that relates to the underlying pathophysiology of the primary clinical condition

Identifying and describing functional discourse units in the BNC Spoken 2014

On the surface, it appears that conversational language is produced in a stream of spoken utterances. In reality conversation is composed of contiguous units that are characterized by coherent communicative purposes. A large number of important research questions about the nature of conversational discourse could be addressed if researchers could investigate linguistic variation across functional discourse units. To date, however, no corpus of conversational language has been annotated according to functional units, and there are no existing methods for carrying out this type of annotation. We introduce a new method for segmenting transcribed conversation files into discourse units and characterizing those units based on their communicative purposes. The development and piloting of this method is described in detail and the final framework is presented. We conclude with a discussion of an ongoing project where we are applying this coding framework to the British National Corpus Spoken 2014

Human-Agent Interaction Model Learning based on Crowdsourcing

Missions involving humans interacting with automated systems become increasingly common. Due to the non-deterministic behavior of the human and possibly high risk of failing due to human factors, such an integrated system should react smartly by adapting its behavior when necessary. A promise avenue to design an efficient interaction-driven system is the mixed-initiative paradigm. In this context, this paper proposes a method to learn the model of a mixed-initiative human-robot mission. The first step to set up a reliable model is to acquire enough data. For this aim a crowdsourcing campaign was conducted and learning algorithms were trained on the collected data in order to model the human-robot mission and to optimize a supervision policy with a Markov Decision Process (MDP). This model takes into account the actions of the human operator during the interaction as well as the state of the robot and the mission. Once such a model has been learned, the supervision strategy can be optimized according to a criterion representing the goal of the mission. In this paper, the supervision strategy concerns the robot’s operating mode. Simulations based on the MDP model show that planning under uncertainty solvers can be used to adapt robot’s mode according to the state of the human-robot system. The optimization of the robot’s operation mode seems to be able to improve the team’s performance. The dataset that comes from crowdsourcing is therefore a material that can be useful for research in human-machine interaction, that is why it has been made available on our website

A presynaptic phosphosignaling hub for lasting homeostatic plasticity

Stable function of networks requires that synapses adapt their strength to levels of neuronal activity, and failure to do so results in cognitive disorders. How such homeostatic regulation may be implemented in mammalian synapses remains poorly understood. Here we show that the phosphorylation status of several positions of the active-zone (AZ) protein RIM1 are relevant for synaptic glutamate release. Position RIMS1045 is necessary and sufficient for expression of silencing-induced homeostatic plasticity and is kept phosphorylated by serine arginine protein kinase 2 (SRPK2). SRPK2-induced upscaling of synaptic release leads to additional RIM1 nanoclusters and docked vesicles at the AZ and is not observed in the absence of RIM1 and occluded by RIMS1045E. Our data suggest that SRPK2 and RIM1 represent a presynaptic phosphosignaling hub that is involved in the homeostatic balance of synaptic coupling of neuronal networks

Inferring stabilizing mutations from protein phylogenies : application to influenza hemagglutinin

One selection pressure shaping sequence evolution is the requirement that a protein fold with sufficient stability to perform its biological functions. We present a conceptual framework that explains how this requirement causes the probability that a particular amino acid mutation is fixed during evolution to depend on its effect on protein stability. We mathematically formalize this framework to develop a Bayesian approach for inferring the stability effects of individual mutations from homologous protein sequences of known phylogeny. This approach is able to predict published experimentally measured mutational stability effects (ΔΔG values) with an accuracy that exceeds both a state-of-the-art physicochemical modeling program and the sequence-based consensus approach. As a further test, we use our phylogenetic inference approach to predict stabilizing mutations to influenza hemagglutinin. We introduce these mutations into a temperature-sensitive influenza virus with a defect in its hemagglutinin gene and experimentally demonstrate that some of the mutations allow the virus to grow at higher temperatures. Our work therefore describes a powerful new approach for predicting stabilizing mutations that can be successfully applied even to large, complex proteins such as hemagglutinin. This approach also makes a mathematical link between phylogenetics and experimentally measurable protein properties, potentially paving the way for more accurate analyses of molecular evolution