Abstract
The evolution of technology and the increasing connectivity between devices lead to an increased risk of cyberattacks. Good protection systems, such as Intrusion Detection System (IDS) and Intrusion Prevention System (IPS), are essential in trying to prevent, detect and counter most of the attacks. However, the increasing creativity and type of attacks raise the need for more resources and processing power for the protection systems which, in turn, requires horizontal scalability to keep up with the massive companies' network infrastructure and with the complexity of attacks. Technologies like machine learning, show promising results and can be of added value in the detection and prevention of attacks in real-time. But good algorithms and tools are not enough. They require reliable and solid datasets to be able to effectively train the protection systems. The development of a good dataset requires horizontal-scalable, robust, modular and fault-tolerance systems, so that the analyses may be done also in real-time. This paper describes an architecture for horizontal-scaling capture architecture, able to collect packets from multiple sources and prepared for real-time analysis. It depends on multiple modular nodes with specific roles to support different algorithms and tools.

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This study presents a simulation-based procedure to analyse a production line of a metalworking company. We use a simulation tool, ProModel ® software, to reproduce the existing production line layout of the company best-selling product which represents about 70% of the total sales. Our purpose is to get information about the existing system behaviour, and to find strategies to increase actual production level to meet the market’s demand. Based on an initial simulation model, different production scenarios were proposed and results have shown that it is possible to increase the production level allowing to meet the increasing demand for the product. The following changes in the production system were considered: (i) the use of intermediate stock of work-in-process items, (ii) the introduction of new equipment, and (iii) a mixed strategy where the introduction of new equipment is combined with the use of intermediate stock of work-in-process items. In summary, this research exhibits the flexibility of the simulation technique to address manufacturing problems throughout the creation of different scenarios providing some of the behaviour of the systems allowing the anticipation of final outputs. © 2021, Springer Nature Switzerland AG.

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Introduction: Disease-related undernutrition is highly prevalent and requires timely intervention. However, identifying undernutrition often relies on physician judgment. As Internal Medicine wards are the backbone of the hospital setting, insight into the prevalence of nutritional risk in this population is essential. We aimed to determine the prevalence of nutritional risk in Internal Medicine wards, to identify its correlates, and to assess the agreement between the physicians' impression of nutritional risk and evaluation by Nutritional Risk Screening 2002. Material and Methods: A cross-sectional multicentre study was performed in Internal Medicine wards of 24 Portuguese hospitals during 2017. Data on demographics, previous hospital admissions, primary diagnosis, and Charlson comorbidity index score were collected. Nutritional risk at admission was assessed using Nutritional Risk Screening 2002. Agreement between physicians' impression of nutritional risk and Nutritional Risk Screening 2002 was tested by Cohen's kappa. Results: The study included 729 participants (mean age 74 +/- 14.6 years, 51% male). The main reason for admission was respiratory disease. Mean Charlson comorbidity index score was 5.8 +/- 2.8. Prevalence of nutritional risk was 51%. Nutritional risk was associated with admission during the previous year (odds ratio = 1.65, 95% confidence interval: 1.22 - 2.24), solid tumour with metastasis (odds ratio = 4.73, 95% confidence interval: 2.06 - 10.87), any tumour without metastasis (odds ratio = 2.04, 95% confidence interval:1.24 - 3.34), kidney disease (odds ratio = 1.83, 95% confidence interval: 1.21 - 2.75), peptic ulcer (odds ratio = 2.17, 95% confidence interval: 1.10 - 4.25), heart failure (odds ratio = 1.51, 95% confidence interval: 1.11 - 2.04), dementia (odds ratio = 3.02, 95% confidence interval: 1.96 - 4.64), and cerebrovascular disease (odds ratio = 1.62, 95% confidence interval: 1.12 - 2.35). Agreement between physicians' evaluation of nutritional status and Nutritional Risk Screening 2002 was weak (Cohen's kappa = 0.415, p < 0.001). Discussion: Prevalence of nutritional risk in the Internal Medicine population is very high. Admission during the previous year and multiple comorbidities increase the odds of being at-risk. Subjective physician evaluation is not appropriate for nutritional screening. Conclusion: The high prevalence of at-risk patients and poor subjective physician evaluation suggest the need to implement mandatory nutritional screening.

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Considering the nature, extent, and purpose of food processing, this study aims to identify dietary patterns (DPs) and their associations with sociodemographic factors and diet quality in Portuguese children and adolescents. Cross-sectional data were obtained from the National Food, Nutrition and Physical Activity Survey (2015-2016) of the Portuguese population. Dietary intake was obtained from two non-consecutive days and food items were classified according to the NOVA system. The proportion (in grams) of foods in the total daily diet was considered to identify DPs by latent class analysis, with age and sex as concomitant variables. Associations of DPs with sociodemographic characteristics were assessed using multinomial logistic regression. Linear regressions adjusted by sociodemographic characteristics tested associations of DPs with diet quality. DPs identified were: "Unhealthy " (higher sugar-sweetened beverages, industrial breads, and sausages intake), "Traditional " (higher vegetables, fish, olive oil, breads, ultra-processed yogurts, and sausages intake), and "Dairy " (higher intake of milk, yogurt, and milk-based beverages). "Unhealthy " was associated with older ages and lower intake of dietary fibre and vitamins and the highest free sugars and ultra-processed foods (UPF), although all DPs presented significant consumption of UPF. These findings should be considered for the design of food-based interventions and school-feeding policies in Portugal.