Abstract
Overuse of antibiotics is causing the environment to become polluted with them. This is a major threat to global health, with bacteria developing resistance to antibiotics because of it. To monitor this threat, multiple antibiotic detection methods have been developed; however, they are normally complex and costly. In this work, an affordable, easy to use alternative based on digital colourimetry is proposed. Photographs of samples next to a colour reference target were acquired to build a dataset. The algorithm proposed detects the reference target, based on binarisation algorithms, in order to standardise the collected images using a colour correction matrix converting from RGB to XYZ, providing a necessary colour constancy between photographs from different devices. Afterwards, the sample is extracted through edge detection and Hough transform algorithms. Finally, the sulfonamide concentration is estimated resorting to an experimentally designed calibration curve, which correlates the concentration and colour information. Best performance was obtained using Hue colour, achieving a relative standard deviation value of less than 3.5%. © 2019, Springer Nature Switzerland AG.

Abstract
Our research goal is to assess creativity and innovation in the profiles of digital influencers (DIs) and examine how they participate in the shared process of content creation with their partner brands. Based on in-depth interviews with 30 Brazilian DI who had at least one partnership with a brand, we showed that they expressed four out of the nine dimensions of creativity, in addition to a new attribute that we designated as 'Originality'. We also found that DIs regard as strategic sharing creative, innovative, quality content and also being involved in content production with the brands during the different stages of message development. The current literature tends to stress DIs' reactive role in the co-creation experience. We analysed how they manifest (process) their creative task as well as their strategies for generating innovative content. Our results help brand managers to cooperate more efficiently and respectfully with their DIs.

Abstract
Escalonamento na arquitetura cloud e no paradigma fog continuam a apresentar alguns desafios aliciantes. Na cloud, segundo o conhecimento dos autores, ela é amplamente estudada e em muitas pesquisas é abordada na perspetiva de provedores de serviço. Na fog, é muito complexo e, existem poucos estudos. Procurando trazer contributos inovadores nas áreas de escalonamento de tarefas, neste artigo, propomos uma solução para o problema de escalonamento de aplicações móveis sensíveis ao contexto para o paradigma fog computing onde diferentes parâmetros de contexto são normalizados através da normalização Min-Max, as prioridades são definidas através da aplicação da técnica da Regressão Linear Múltipla (RLM) e o escalonamento é feito recorrendo a técnica de Otimização de Programação Não Linear Multi-objetivo (MONLP).;Scheduling in cloud architecture and in the fog paradigm continue to present some exciting challenges. In the cloud, according to the authors' knowledge, it is widely studied and in many researches, it is addressed from the perspective of service providers. In fog, it is very complex and there are few studies. Trying to bring innovative contributions in the areas of task scheduling, in this paper we propose a solution to the problem of context-aware scheduling of mobile applications for the fog computing paradigm, where different context parameters are normalized through Min-Max normalization, priorities are defined by applying the Multiple Linear Regression (MLR) technique and scheduling is performed using Multi-Objective Nonlinear Programming Optimization (MONLP) technique.

Abstract

Abstract
Background Self-reported client assessments during online treatments enable the development of statistical models for the prediction of client improvement and symptom development. Evaluation of these models is mandatory to ensure their validity. Methods For this purpose, we suggest besides a model evaluation based on study data the use of a simulation analysis. The simulation analysis provides insight into the model performance and enables to analyse reasons for a low predictive accuracy. In this study, we evaluate a temporal causal model (TCM) and show that it does not provide reliable predictions of clients' future mood levels. Results Based on the simulation analysis we investigate the potential reasons for the low predictive performance, for example, noisy measurements and sampling frequency. We conclude that the analysed TCM in its current form is not sufficient to describe the underlying psychological processes. Conclusions The results demonstrate the importance of model evaluation and the benefit of a simulation analysis. The current manuscript provides practical guidance for conducting model evaluation including simulation analysis.

Abstract
Delivering information timely across the logistics network is a challenge considering the diversity of entities, technologies, IT maturity and legislation. A way to overcome those challenges is to bring all the parties to a common level by providing technology able to fast and easily connect every system and a common language to allow efficient communication between logistics stakeholders. When we apply the Synchromodality and the Digital twin concepts to logistics, significant improvements can be achieved. Shippers and Integrators can act more precisely, deciding in any step of the global operation by what mode should be selected or combined and following the strict regulations and issuing the mandatory documents timely to avoid bottlenecks. This work produced one real business scenario where the 4-corner model technology-based solution enables synchromodality across the logistics network of one industry unit and its providers and the Digital twin for the process and the VGM (Verified Gross Mass) formality documents. As a solution to this scenario we propose collaboration networks between logistics stakeholders that provide interoperable, low-cost, reliable and secure data exchange, without requiring significant IT developments. To this purpose we studied and developed a demonstrator and tested our solution that consists of the adoption of the 4-corner model as described by Connecting Europe Facility (CEF) eDelivery using access points and the adoption of the standard e-Freight to exchange data over the collaboration network. The widespread use of this solution will increase global efficiency, make the inclusion of every client and provider regardless of resources available, and avoid imponderables in the logistics network. © 2020 IEEE.