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According to results of a recent literature search performed by the European Academy of Dermatology and Venereology (EADV) Task Forces (TF) on Quality of Life and Patient Oriented Outcomes (QoL and PO) and Acne, Rosacea and Hidradenitis Suppurativa (ARHS), most of the publications where health-related (HR) QoL of acne patients was studied were clinical trials. Members of the EADV TF on QoL and PO

Both empirical and theoretical studies show that an individual's spatial position within a group can impact the risk of being targeted by predators. Spatial positions can be quantified in numerous ways, but there are no direct comparisons of different spatial measures in predicting the risk of being targeted by real predators. Here, we assess these spatial measures in groups of stationary and movi

A science project as part of a student’s curriculum, which we call student science, might be the answer to two problems for a low-income country like Ethiopia: conventional science can be expensive and many students lack training in practical skills. Earlier studies have been conducted with respect to lay people (citizens or students) conducting (parts of) research (e.g. citizen science), but rare

Biopharmaceuticals are complex biological molecules that require careful storage and handling to ensure medication integrity. In this study, a work system analysis of real-world protein drug (PD) handling was performed with the following goals: identify main barriers and facilitators for successful adherence to accepted recommendations in PD handling, analyse differences in two organizations, and

INTRODUCTION: The aim of this study was to compare different methods to predict acute coronary syndrome (ACS) using only data from a single electrocardiogram (ECG) in the emergency department (ED). METHOD: We compared the ACS prediction abilities of classical ECG criteria, human expert ECG interpretation, a logistic regression model and an artificial neural network ensemble (ANN). The ED ECG and d

During the past decade, scholars have produced a vast amount of research using linked historical individual-level data, shaping and changing our understanding of the past. This linked data revolution has been powered by methodological and computational advances, partly focused on supervised machine-learning methods that rely on training data. The importance of obtaining high-quality training data

Coalescence during emulsification has a significant effect on the outcome of the process, especially for the high volume fractions of disperse phase common in food and pharmaceutical processing. Controlling emulsification requires that the extent of coalescence during different conditions can be quantified. The step-down technique is the most commonly used method for measuring coalescence frequenc