Comments on a class of orthogonality relations relevant to fluid-structure interaction

Copyright @ 2011 Springer Science+Business Media B.V

Why we are losing the war against COVID-19 on the data front and how to reverse the situation

With over five million covid-19 positive cases declared, more than 30,000 deaths and more than two million patients recovered, we would expect that the highly digitalised health systems of the high-income countries would have collected, processed and analysed large quantities of clinical data from COVID-19 patients. Those analysis should have served to answer important clinical questions such as: what are the risk factors for becoming infected? What are good clinical variables to predict prognosis? What kind of patients are more likely to survive mechanical ventilation? Are there clinical sub-phenotypes of the disease? All these, and many more, are crucial questions to improve our clinical strategies against the epidemic and save as many lives as possible until we find a vaccine and effective treatments. One might assume that in the era of Big Data and Machine Learning there would be an army of scientist crunching petabytes of clinical data to solve these questions. However, nothing further from the truth. Our health systems have proven completely unprepared to generate in a timely manner a flow of clinical data that could feed these analyses. De-spite gigabytes of data being generated every day, the vast immensity is locked in secure hospitals data servers and is not being made available for analysis. Routinely collected clinical data is, by and large, regarded as a tool to inform about individual patients, and not as a key resource to answer clinical questions thorough statistical analysis. The ini-tiatives to extract COVID-19 clinical data are often promoted by private groups of indi-viduals and not by the health systems. They are uncoordinated and inefficient. The con-sequence is that we have more clinical data than in any other epidemic in history, but we are failing to analyse it quickly enough to make a difference. In this paper we expose this situation and we suggest concrete ideas that the health systems could implement to dynamically analyse their routine clinical data becoming effectively “learning health systems” and reversing the current situation

Predictable arguments of knowledge

We initiate a formal investigation on the power of predictability for argument of knowledge systems for NP. Specifically, we consider private-coin argument systems where the answer of the prover can be predicted, given the private randomness of the verifier; we call such protocols Predictable Arguments of Knowledge (PAoK). Our study encompasses a full characterization of PAoK, showing that such arguments can be made extremely laconic, with the prover sending a single bit, and assumed to have only one round (i.e., two messages) of communication without loss of generality. We additionally explore PAoK satisfying additional properties (including zero-knowledge and the possibility of re-using the same challenge across multiple executions with the prover), present several constructions of PAoK relying on different cryptographic tools, and discuss applications to cryptography

MyAirCoach: the use of home-monitoring and mHealth systems to predict deterioration in asthma control and the occurrence of asthma exacerbations; study protocol of an observational study.

INTRODUCTION: Asthma is a variable lung condition whereby patients experience periods of controlled and uncontrolled asthma symptoms. Patients who experience prolonged periods of uncontrolled asthma have a higher incidence of exacerbations and increased morbidity and mortality rates. The ability to determine and to predict levels of asthma control and the occurrence of exacerbations is crucial in asthma management. Therefore, we aimed to determine to what extent physiological, behavioural and environmental data, obtained by mobile healthcare (mHealth) and home-monitoring sensors, as well as patient characteristics, can be used to predict episodes of uncontrolled asthma and the onset of asthma exacerbations. METHODS AND ANALYSIS: In an 1-year observational study, patients will be provided with mHealth and home-monitoring systems to record daily measurements for the first-month (phase I) and weekly measurements during a follow-up period of 11 months (phase II). Our study population consists of 150 patients, aged ≥18 years, with a clinician's diagnosis of asthma, currently on controller medication, with uncontrolled asthma and/or minimally one exacerbation in the past 12 months. They will be enrolled over three participating centres, including Leiden, London and Manchester. Our main outcomes are the association between physiological, behavioural and environmental data and (1) the loss of asthma control and (2) the occurrence of asthma exacerbations. ETHICS: This study was approved by the Medical Ethics Committee of the Leiden University Medical Center in the Netherlands and by the NHS ethics service in the UK. TRIAL REGISTRATION NUMBER: NCT02774772

Fiber-Flux Diffusion Density for White Matter Tracts Analysis: Application to Mild Anomalies Localization in Contact Sports Players

We present the concept of fiber-flux density for locally quantifying white matter (WM) fiber bundles. By combining scalar diffusivity measures (e.g., fractional anisotropy) with fiber-flux measurements, we define new local descriptors called Fiber-Flux Diffusion Density (FFDD) vectors. Applying each descriptor throughout fiber bundles allows along-tract coupling of a specific diffusion measure with geometrical properties, such as fiber orientation and coherence. A key step in the proposed framework is the construction of an FFDD dissimilarity measure for sub-voxel alignment of fiber bundles, based on the fast marching method (FMM). The obtained aligned WM tract-profiles enable meaningful inter-subject comparisons and group-wise statistical analysis. We demonstrate our method using two different datasets of contact sports players. Along-tract pairwise comparison as well as group-wise analysis, with respect to non-player healthy controls, reveal significant and spatially-consistent FFDD anomalies. Comparing our method with along-tract FA analysis shows improved sensitivity to subtle structural anomalies in football players over standard FA measurements

In verbis, vinum? Relating themes in an open-ended writing task to alcohol behaviors

Alcohol's function as a regulator of emotions has long been denoted in figures of speech, most famously 'in vino, veritas' (in wine,truth). In contrast, we ask whether an individual's alcohol-related behaviors can be inferred from the words they use to write about alcohol. Participants completed an open-ended essay as part of a survey on alcohol attitudes and behaviors. We used a computerized technique, the Meaning Extraction Method, to summarize the responses into thematic tropes, and correlated these with quantitative measurements of demographics, attitudes and behaviors. Participants were recruited using a random population postal survey in the U.K (n=1229). Principal components analysis identified co-occurring words to locate themes in the responses. Seven themes were identified that corresponded to both negative and positive aspects of alcohol consumption ranging from concern for the influence of alcohol on others (e.g., children and family) to participants' own enjoyment of alcohol (e.g., social drinking). Significant correlations suggested a relationship between the essay responses and individual consumption patterns and attitudes. This study therefore examines how individuals in UK drinking cultures commonly construe alcohol consumption in their own words

Spin-lattice instability to a fractional magnetization state in the spinel HgCr2O4

Magnetic systems are fertile ground for the emergence of exotic states when the magnetic interactions cannot be satisfied simultaneously due to the topology of the lattice - a situation known as geometrical frustration. Spinels, AB2O4, can realize the most highly frustrated network of corner-sharing tetrahedra. Several novel states have been discovered in spinels, such as composite spin clusters and novel charge-ordered states. Here we use neutron and synchrotron X-ray scattering to characterize the fractional magnetization state of HgCr2O4 under an external magnetic field, H. When the field is applied in its Neel ground state, a phase transition occurs at H ~ 10 Tesla at which each tetrahedron changes from a canted Neel state to a fractional spin state with the total spin, Stet, of S/2 and the lattice undergoes orthorhombic to cubic symmetry change. Our results provide the microscopic one-to-one correspondence between the spin state and the lattice distortion

Cigarette smoke induces IL-8, but inhibits eotaxin and RANTES release from airway smooth muscle

BACKGROUND: Cigarette smoke is the leading risk factor for the development of chronic obstructive pulmonary disease (COPD) an inflammatory condition characterised by neutrophilic inflammation and release of proinflammatory mediators such as interleukin-8 (IL-8). Human airway smooth muscle cells (HASMC) are a source of proinflammatory cytokines and chemokines. We investigated whether cigarette smoke could directly induce the release of chemokines from HASMC. METHODS: HASMC in primary culture were exposed to cigarette smoke extract (CSE) with or without TNFα. Chemokines were measured by enzyme-linked immunosorbent assay (ELISA) and gene expression by real time polymerase chain reaction (PCR). Data were analysed using one-way analysis of variance (ANOVA) followed by Bonferroni's t test RESULTS: CSE (5, 10 and 15%) induced IL-8 release and expression without effect on eotaxin or RANTES release. At 20%, there was less IL-8 release. TNFα enhanced CSE-induced IL-8 release and expression. However, CSE (5–30%) inhibited TNFα-induced eotaxin and RANTES production. The effects of CSE on IL-8 release were inhibited by glutathione (GSH) and associated with the induction of the oxidant sensing protein, heme oxygenase-1. CONCLUSION: Cigarette smoke may directly cause the release of IL-8 from HASMC, an effect enhanced by TNF-α which is overexpressed in COPD. Inhibition of eotaxin and RANTES by cigarette smoke is consistent with the predominant neutrophilic but not eosinophilic inflammation found in COPD