ZELab: planning a living lab to educate modern engineering professionals

Buildings are now complex systems that traditionally have been studied in an isolated mode, seeking to respond to a specific need and dealing with a restricted set of variables. The targets established for energy efficient buildings and energy sustainability imply that these new systems are now more comprehensive and combine various independent systems. This new topology requires a new kind of engineering professionals trained in a more integrative and collaborative way. These new engineering professionals need to have not only expertise in a specific area, but also more comprehensive proficiencies that allow them to understand how to integrate their particular project into a wider functional system, and to communicate with experts from different areas. This paper addresses some challenges and issues posed to Higher Education institutions on the educational paradigms of future engineering professionals and proposes the ZELab teaching / research space as an integrative educational tool.info:eu-repo/semantics/publishedVersio

Sustainable development in higher education: Different teaching & learning approaches

Linking the economic, social and environmental aspects of any plan, project or activity is fundamental to act according to the sustainable development goals. These three dimensions are interrelated and interconnected in such a way that it is sometimes very hard to discriminate what their individual effects are, or on the contrary, how their joint effects are synergistic. And if this is generically a difficult task, when it comes to education the difficulty becomes even more significant, as one must be very careful defining concepts in an absolutely clear and undoubtful way. While the specialization is required to educate professionals able to accurately project and build these projects, it is now mandatory that everyone is also able to understand the causes and effects of their actions, towards sustainable development. In this Track, different teaching & learning approaches have been presented and discussed, aiming to use Higher Education as a highway to educate the professionals of the near future as strategic partners for the development of different mindsets, able to tackle the real problems.This work was financially supported by project UID/EQU/00511/2019 – Laboratory for Process Engineering, Environment, Biotechnology and Energy – LEPABE and by project UID/EQU/04730/2019 – Center for Innovation in Engineering and Industrial Technology, both funded by national funds through FCT/MCTES (PIDDAC).info:eu-repo/semantics/publishedVersio

Indicators Used in the Energy Sector

World energy mix still depends heavily on fossil fuels but the foreseen increase demand, the scarcity of those resources, their unevenly distribution as well as other factors such as economic burdens due to fossil fuel prices and climate change concerns contributed to the establishment and implementation of new policies in the energy sector. Renewable energy sources are being promoted worldwide as a pathway to reduce external energy dependency, moving towards lower carbon energy systems. It is important to policy makers, investors and other stakeholders to have tools for deciding which policies, investments and measures should be implemented in the future. Thus indicators play very important role for fulfilling that task. This work present a structured presentation of several indicators commonly used to compare solutions in the energy domain

Carbohydrate counting: how accurate should it be to achieve glycemic control in patients on intensive insulin regimens?

Carbohydrate counting is an important meal-planning tool for patients on intensive insulin regimens. Preprandial insulin bolus is adjusted taking into account the carbohydrate content of each meal and the insulin-to-carb ratio of each patient throughout the day. Evidence suggests that accurate carbohydrate counting may have positive effects not only on reducing glycosylated hemoglobin concentration but also on decreasing the incidence of hypoglycemic episodes. Nevertheless, despite its benefits, the efficacy of carbohydrate counting depends on the ability of each patient, or its caregiver, to accurately estimate the carbohydrate content of each meal. Therefore, it is of great importance to understand how accurate should carbohydrate counting be, and the impact of inaccurate carbohydrate counting on the glycemic control of each patient. Within this work, we propose an analytic method that uses the insulin-to-carb ratio and the insulin sensitivity factor, along with the glycemic targets of each patient to calculate the limits of accurate carbohydrate counting, in order to achieve better glycemic control and to reduce hypoglycemic episodes.publishe

Mathematical modelling of Portuguese hydroelectric energy system

Hydropower is one of the most traditional renewable energy source and a major contributor for renewable energy production inmany countries. In Portugal it was the only renewable energy source for many years but nowadays wind presents similar production levels and for example in 2015 wind was the main source producing 45.5 % of the total renewable energy. However hydro energy will continue to be important in the renewable energy production and in this work ranking of nine models for hydro energy production with various numbers of parameters was done using adjusted R-squared and corrected Akaike information criterion (AICc).info:eu-repo/semantics/publishedVersio

An adaptive mealtime bolus calculator to minimize the effects of inaccurate carbohydrate counting

Evidence suggests that accurate carbohydrate counting along with self-monitoring of blood glucose is the key to a successful diabetes management, in particular for patients on intensive insulin regimens. However, despite its benefits, accurate carbohydrate counting is a complex, difficult, time-consuming, and error-prone task for most patients. Several studies show that most patients frequently estimate the carbohydrate content of meals within an error of about 10-15 g of the real value. In addition, fearing hypoglycemic events, patients frequently underestimate the carbohydrate content of meals and, consequently, they have high levels of HbA1C. Therefore, is important to avoid the consequences of incorrect carbohydrate counting in order to improve the patient’s glycemic control. To that end, this work presents an adaptive mealtime bolus calculator that uses the patient’s glycemic data to dynamically adjust the mealtime bolus and counterbalance the negative effects of inaccurate carbohydrate counting.publishe

Carbohydrate counting : how accurate should it be to achieve glycemic control in patients on intensive insulin regimens?

Carbohydrate counting is an important meal-planning tool for patients on intensive insulin regimens. Preprandial insulin bolus is adjusted taking into account the carbohydrate content of each meal and the insulin-to-carb ratio of each patient throughout the day. Evidence suggests that accurate carbohydrate counting may have positive effects not only on reducing glycosylated hemoglobin concentration but also on decreasing the incidence of hypoglycemic episodes. Nevertheless, despite its benefits, the efficacy of carbohydrate counting depends on the ability of each patient, or its caregiver, to accurately estimate the carbohydrate content of each meal. Therefore, it is of great importance to understand how accurate should carbohydrate counting be, and the impact of inaccurate carbohydrate counting on the glycemic control of each patient. Within this work, we propose an analytic method that uses the insulin-to-carb ratio and the insulin sensitivity factor, along with the glycemic targets of each patient to calculate the limits of accurate carbohydrate counting, in order to achieve better glycemic control and to reduce hypoglycemic episodes.511F-603F-4B30 | Francisco MirandaN/

An adaptive mealtime bolus calculator to minimize the effects of inaccurate carbohydrate counting

Evidence suggests that accurate carbohydrate counting along with self-monitoring of blood glucose is the key to a successful diabetes management, in particular for patients on intensive insulin regimens. However, despite its benefits, accurate carbohydrate counting is a complex, difficult, time-consuming, and error-prone task for most patients. Several studies show that most patients frequently estimate the carbohydrate content of meals within an error of about 10-15 g of the real value. In addition, fearing hypoglycemic events, patients frequently underestimate the carbohydrate content of meals and, consequently, they have high levels of HbA1C. Therefore, is important to avoid the consequences of incorrect carbohydrate counting in order to improve the patient's glycemic control. To that end, this work presents an adaptive mealtime bolus calculator that uses the patient's glycemic data to dynamically adjust the mealtime bolus and counterbalance the negative effects of inaccurate carbohydrate counting.511F-603F-4B30 | Francisco MirandaN/

Energy transition in a business company – solar PV for a car fleet

Fossil fuels are increasingly limited in today's world, causing an energy crisis due to external factors, increasing prices in international markets. To solve this global problem, the energy transition related to mobility in companies that oversee their car fleets is highlighted. This transition to electric mobility influences several economic, technical, and social aspects, thus it becomes crucial for companies to adapt their infrastructure and dynamics to have more sustainable practices. According to the 2021-2022 EIB Climate Survey, 55% of Portuguese young people consider climate change when looking for a job. Furthermore, when asked about future car purchases, 84% of Portuguese car buyers say they will purchase either a hybrid or electric car, making Portugal the EU No. 1 country in terms of intentions to purchase electric cars. These statistics show the urgency for companies to adapt to future needs, as well as align with the European goals of reducing greenhouse gases emissions to 45% by 2030 and to zero by 2050.This work was financially supported by Base Funding – UIDB/04730/2020 of Center for Innovation in Engineering and Industrial Technology, Portugal, CIETI – funded by national funds through the FCT/MCTES (PIDDAC), Portugal; LA/P/0045/2020 (ALiCE) and UIDB/00511/2020 - UIDP/00511/2020 (LEPABE) funded by national funds through FCT/MCTES (PIDDAC).info:eu-repo/semantics/submittedVersio

Macro Modelling of Electricity Price Towards Sdg7

Energy challenges are crucial issues to achieve Sustainable Development and its goals. Energy availability and affordability are pillars for ending poverty, giving access to commodities as well as water, etc. Modern lives rely on appliances and gadgets based on electric energy being its price a key issue making it worth to analyze and promote simple models able to predict electric energy prices to support in decision-making processes and in management. This work studied the correlation of electricity price with variables such as the electricity mix , GDP, energy productivity, electricity consumption per capita, fossil fuel reserves, and diesel price, using Spearman correlation. To the significant correlations found it was then applied the Kruskal-Wallis test and the variables that presented statistically significant differences were then considered to model electricity price based on these macro variables. Our findings revealed that the best models were a logarithmic and a linear model of energy productivity to predict electricity price. In the validation process, these models presented an average deviation of 10.3% and 11.7%, respectively, which is reasonable considering the simplicity of the models developed.info:eu-repo/semantics/publishedVersio