Using decision tree to select forecasting algorithms in distinct electricity consumption context of an office building

The flexibility and management in the storage and control of building expertise in the energy optimization can be enhanced with the support of algorithms involved in forecasting tasks. These play an important role on obtaining anticipated and accurate consumption predictions associated to different contexts through extensive consumption patterns analysis. This paper evaluates the most viable forecasting algorithm for consumption predictions of a building in different contexts according to two alternatives: artificial neural networks and k-nearest neighbors. These algorithms use patterns of data from consumptions integrated in different contexts while retaining additional information from sensors data. The different contexts are classified on a sequence of periods that take place from five-to-five minutes. The decision criterion to evaluate which of the two forecasting algorithms is the most suitable in each five minutes periods is supported with decision trees that select the forecasting algorithms that looks to be more suitable followed by a logical answer that clarifies if the selection was the most viable option. Parameterization updates concerning the depth are studied to understand the forecasting accuracy impact. The decision trees approach has the potential to improve the accuracy of prediction as it plays a promising role in decision making.The present work has been developed under the EUREKA - ITEA3 Project TIoCPS, Portugal (ITEA-18008), Project TIoCPS, Portugal (ANIP2020 POCI-01-0247-FEDER-046182), and has received funding from European Regional Development Fund through COMPETE 2020 - Operational Programme for Competitiveness and Internationalization. The work has been done also in the scope of projects UIDB/00760/2020, and CEECIND/02887/2017, financed by FEDER Funds through COMPETE program and from National Funds through (FCT, Portugal ).info:eu-repo/semantics/publishedVersio

The role of emergent processing technologies in tailoring plant protein functionality: New insights

Background Plant proteins possess promising technological-functional properties that can be used for the development of innovative protein systems. Following the global requirements of environmentally friendly politics, green and cost-effective processing technologies, such as ohmic heating and high pressure processing are of great interest. These technologies have demonstrated their potential to modify protein structure and therefore their function, opening interesting possibilities for the design of functional food systems. However, these innovations must also include nutritional and health/wellness aspects, such as the interaction with other food components, and the behavior in the gastrointestinal tract (digestibility and bioavailability). Scope and approach This review addresses the most promising technological-functional attributes of plant proteins, as well as considerations and strategies needed for the development of innovative food systems. New insights will also be provided on how emerging processing technologies such as ohmic heating and high pressure processing can affect the behavior of proteins. The processing effects in proteins structure and in their technological-functional properties and ultimately in the biofunctional and nutritional aspects of foods made therefrom will be critically discussed. Key findings and conclusions Fundamental research regarding the relationship between structural modifications and functionality of more conventional proteins is still required. Furthermore, additional research is necessary on proteins from less studied sources, highlighting those displaying both functional and quality parameters of interest. Emergent processing technologies can help guaranteeing the quality and preservation of foods, as well as act as effective tools to develop technological-functional attributes of food proteins ensuring nutritional and health/wellness aspects.This study was supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UIDB/04469/2020 unit and BioTecNorte operation (NORTE-01-0145-FEDER 000004) funded by the European Regional Development Fund under the scope of Norte2020 - Programa Operacional Regional do Norte. Ac knowledgments are also due to University of Aveiro and FCT/MCT for the financial support for LAQV-REQUIMTE research Unit (FCT UIDB/50006/2020) through national funds and, where applicable, co financed by the FEDER, within the PT2020 Partnership Agreement. Zita Avelar acknowledges the Foundation for Science and Technology (FCT) for its fellowship SFRH/BD/146347/2019.info:eu-repo/semantics/publishedVersio

An Efficient, Green Chemical Synthesis of the Malaria\ud Drug, Piperaquine

To provide a robust, efficient synthesis of the malaria drug piperaquine for potential use in resource-poor settings. We used in-process analytical technologies (IPAT; HPLC) and a program of experiments to develop a synthesis of piperaquine that avoids the presence of a toxic impurity in the API and is optimized for overall yield and operational simplicity. A green-chemical synthesis of piperaquine is described that proceeds in 92 – 93 % overall yield. The chemistry is robust and provides very pure piperaquine tetraphosphate salt (> 99.5 %). The overall process utilizes modest amounts (about 8 kg/kg) of 2-propanol and ethyl acetate as the only organic materials not incorporated into the API; roughly 60 % of this waste can be recycled into the production process. This process also completely avoids the formation of a toxic impurity commonly seen in piperaquine that is otherwise difficult to remove. An efficient synthesis of piperaquine is described that may be useful for application in resource-poor settings as a means of expanding access to and reducing the cost of ACTs

Intelligent training in control centres based on an ambient intelligence paradigm

This article describes a new approach in the Intelligent Training of Operators in Power Systems Control Centres, considering the new reality of Renewable Sources, Distributed Generation, and Electricity Markets, under the emerging paradigms of Cyber-Physical Systems and Ambient Intelligence. We propose Intelligent Tutoring Systems as the approach to deal with the intelligent training of operators in these new circumstances

An intelligent tutoring system for operators’ training in power system control centres

The activity of Control Center operators is important to guarantee the effective performance of Power Systems. Operators’ actions are crucial to deal with incidents, especially severe faults, like blackouts. In this paper we present an Intelligent Tutoring approach for training Portuguese Control Centre operators in tasks like incident analysis and diagnosis, and service restoration of Power Systems. Intelligent Tutoring System (ITS) approach is used in the training of the operators, taking into account context awareness and the unobtrusive integration in the working environment

Effects of moderate electric fields in beta-lactoglobulinthermal denaturation: structural changes and binding properties

This study was supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2019 unit and BioTecNorte operation (NORTE-01-0145-FEDER-000004) funded by the European Regional Development Fund under the scope of Norte2020 - Programa Operacional Regional do Norte. Rui M. Rodrigues gratefully acknowledge FCT for their financial grant with reference SFRH/BD/110723/2015.info:eu-repo/semantics/publishedVersio

Population dynamics, delta vulnerability and environmental change: comparison of the Mekong, Ganges–Brahmaputra and Amazon delta regions

Tropical delta regions are at risk of multiple threats including relative sea level rise and human alterations, making them more and more vulnerable to extreme floods, storms, surges, salinity intrusion, and other hazards which could also increase in magnitude and frequency with a changing climate. Given the environmental vulnerability of tropical deltas, understanding the interlinkages between population dynamics and environmental change in these regions is crucial for ensuring efficient policy planning and progress toward social and ecological sustainability. Here, we provide an overview of population trends and dynamics in the Ganges–Brahmaputra, Mekong and Amazon deltas. Using multiple data sources, including census data and Demographic and Health Surveys, a discussion regarding the components of population change is undertaken in the context of environmental factors affecting the demographic landscape of the three delta regions. We find that the demographic trends in all cases are broadly reflective of national trends, although important differences exist within and across the study areas. Moreover, all three delta regions have been experiencing shifts in population structures resulting in aging populations, the latter being most rapid in the Mekong delta. The environmental impacts on the different components of population change are important, and more extensive research is required to effectively quantify the underlying relationships. The paper concludes by discussing selected policy implications in the context of sustainable development of delta regions and beyond

Social differentiation and well‑being in the Italian Iron Age: exploring the relationship between sex, age, biological stress, and burial complexity among the Picenes of Novilara (8th–7th c. BC)

The restoration of the archaeological finds from Novilara was performed in the frame of the "Progetto di restauro degli oggetti di corredo rinvenuti nella necropoli picena di Novilara" (Swiss Federal Office of Culture) and with the additional financial support of Fondazione Scavolini (Italy).The possible association between “biological” and “social” status in the past is a central topic in bioarchaeological studies. For the Italian Iron Age, previous research comparing skeletal and funerary variables depicts a multifaceted scenario consistent with nuanced biocultural patterns. This calls for additional studies on a broader series of archaeological contexts and skeletal assemblages. Here, we contribute new data about the biological correlates of social differentiation during the Italian Iron Age by comparing paleopathological and funerary variables in the Picene necropolis of Novilara (Marche region, 8th–7th c. BC). Novilara is one of the largest Picene necropolises in the Italian Peninsula and one of the most important funerary sites of the Italian Iron Age. The skeletal sample includes 147 individuals (females: 70; males: 35; 10 unsexed adults; 32 non-adults). We use linear enamel hypoplasia, cribra orbitalia, porotic hyperostosis, non-specific periosteal lesions, and stature to approximate non-specific stressors and compare them with archaeological variables summarizing funerary variability by means of logistic models, Mann–Whitney and Spearman tests. Results are heterogeneous and vary according to the considered variables. On average, they however show that (a) adults featuring a more complex funerary treatment have a lower probability of showing stress-related skeletal changes, and (b) even though funerary features suggests a strong gender differentiation, frequencies of paleopathological variables do not differ between sexes. Our analyses point to a complex link between biological and social status in this population and call for a critical reflection about the theoretical and methodological issues affecting similar studies.Fondazione Scavolini (Italy