The Chalcedonian Christology of St John Damascene : philosophical terminology and theological arguments

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Bayesian system identification of dynamical systems using highly informative training data

This paper is concerned with the Bayesian system identification of structural dynamical systems using experimentally obtained training data. It is motivated by situations where, from a large quantity of training data, one must select a subset to infer probabilistic models. To that end, using concepts from information theory, expressions are derived which allow one to approximate the effect that a set of training data will have on parameter uncertainty as well as the plausibility of candidate model structures. The usefulness of this concept is then demonstrated through the system identification of several dynamical systems using both physics-based and emulator models. The result is a rigorous scientific framework which can be used to select 'highly informative' subsets from large quantities of training data

A Cross-layer Monitoring Solution based on Quality Models

In order to implement cross-organizational workflows and to realize collaborations between small and medium enterprises (SMEs), the use ofWeb service technology, Service-Oriented Architecture and Infrastructure-as-a- Service (IaaS) has become a necessity. Based on these technologies, the need for monitoring the quality of (a) the acquired resources, (b) the services offered to the final users and (c) the workflow-based procedures used by SMEs in order to use services, has come to the fore. To tackle this need, we propose four metric Quality Models that cover quality terms for the Workflow, Service and Infrastructure layers and an additional one for expressing the equality and inter-dependency relations between the previous ones. To support these models we have implemented a cross-layer monitoring system, whose main advantages are the layer-specific metric aggregators and an event pattern discoverer for processing the monitoring log. Our evaluation is based on the performance and accuracy aspects of the proposed cross-layer monitoring system

Long-term effects of evolocumab in participants with HIV and dyslipidemia: results from the open-label extension period

Objectives: People with HIV (PWH) are at an increased risk of atherosclerotic cardiovascular disease. Suboptimal responses to statin therapy in PWH may result from antiretroviral therapies (ARTs). This open-label extension study aimed to evaluate the long-term safety and efficacy of evolocumab up to 52\u200aweeks in PWH. Design: This final analysis of a multinational, placebo-controlled, double-blind, randomized phase 3 trial evaluated the effect of monthly subcutaneous evolocumab 420\u200amg on low-density lipoprotein cholesterol (LDL-C) during the open-label period (OLP) following 24\u200aweeks of double-blind period in PWH with hypercholesterolemia/mixed dyslipidemia. All participants enrolled had elevated LDL-C or nonhigh-density lipoprotein cholesterol (non-HDL-C) and were on stable maximally tolerated statin and stable ART. Methods: Efficacy was assessed by percentage change from baseline in LDL-C, triglycerides, and atherogenic lipoproteins. Treatment-emergent adverse events (TEAEs) were examined. Results: Of the 467 participants randomized in the double-blind period, 451 (96.6%) received at least one dose of evolocumab during the OLP (mean age of 56.4\u200ayears, 82.5% male, mean duration with HIV of 17.4\u200ayears). By the end of the 52-week OLP, the overall mean (SD) percentage change in LDL-C from baseline was -57.8% (22.8%). Evolocumab also reduced triglycerides, atherogenic lipid parameters (non-HDL-C, apolipoprotein B, total cholesterol, very-low-density lipoprotein cholesterol, and lipoprotein[a]), and increased HDL-C. TEAEs were similar between placebo and evolocumab during the OLP. Conclusion: Long-term administration of evolocumab lowered LDL-C and non-HDL-C, allowing more PWH to achieve recommended lipid goals with no serious adverse events. Trail registration: NCT02833844. Video abstract: http://links.lww.com/QAD/C441

Pneumoproteins and biomarkers of inflammation and coagulation do not predict rapid lung function decline in people living with HIV

Chronic obstructive pulmonary disease (COPD) is among the leading causes of death worldwide and HIV is an independent risk factor for the development of COPD. However, the etiology of this increased risk and means to identify persons with HIV (PWH) at highest risk for COPD have remained elusive. Biomarkers may reveal etiologic pathways and allow better COPD risk stratification. We performed a matched case:control study of PWH in the Strategic Timing of Antiretoviral Treatment (START) pulmonary substudy. Cases had rapid lung function decline (> 40 mL/year FEV1 decline) and controls had stable lung function (+ 20 to − 20 mL/year). The analysis was performed in two distinct groups: (1) those who were virally suppressed for at least 6 months and (2) those with untreated HIV (from the START deferred treatment arm). We used linear mixed effects models to test the relationship between case:control status and blood concentrations of pneumoproteins (surfactant protein-D and club cell secretory protein), and biomarkers of inflammation (IL-6 and hsCRP) and coagulation (d-dimer and fibrinogen); concentrations were measured within ± 6 months of first included spirometry. We included an interaction with treatment group (untreated HIV vs viral suppression) to test if associations varied by treatment group. This analysis included 77 matched case:control pairs in the virally suppressed batch, and 42 matched case:control pairs in the untreated HIV batch (n = 238 total) who were followed for a median of 3 years. Median (IQR) CD4 + count was lowest in the controls with untreated HIV at 674 (580, 838). We found no significant associations between case:control status and pneumoprotein or biomarker concentrations in either virally suppressed or untreated PWH. In this cohort of relatively young, recently diagnosed PWH, concentrations of pneumoproteins and biomarkers of inflammation and coagulation were not associated with subsequent rapid lung function decline. Trial registration: NCT00867048 and NCT01797367

COVID-19-related absence among surgeons: development of an international surgical workforce prediction model.

BACKGROUND: During the initial COVID-19 outbreak up to 28.4 million elective operations were cancelled worldwide, in part owing to concerns that it would be unsustainable to maintain elective surgery capacity because of COVID-19-related surgeon absence. Although many hospitals are now recovering, surgical teams need strategies to prepare for future outbreaks. This study aimed to develop a framework to predict elective surgery capacity during future COVID-19 outbreaks. METHODS: An international cross-sectional study determined real-world COVID-19-related absence rates among surgeons. COVID-19-related absences included sickness, self-isolation, shielding, and caring for family. To estimate elective surgical capacity during future outbreaks, an expert elicitation study was undertaken with senior surgeons to determine the minimum surgical staff required to provide surgical services while maintaining a range of elective surgery volumes (0, 25, 50 or 75 per cent). RESULTS: Based on data from 364 hospitals across 65 countries, the COVID-19-related absence rate during the initial 6 weeks of the outbreak ranged from 20.5 to 24.7 per cent (mean average fortnightly). In weeks 7-12, this decreased to 9.2-13.8 per cent. At all times during the COVID-19 outbreak there was predicted to be sufficient surgical staff available to maintain at least 75 per cent of regular elective surgical volume. Overall, there was predicted capacity for surgeon redeployment to support the wider hospital response to COVID-19. CONCLUSION: This framework will inform elective surgical service planning during future COVID-19 outbreaks. In most settings, surgeon absence is unlikely to be the factor limiting elective surgery capacity