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- a-fractal function with variable parameters: an explicit representationPublication . Priyanka, T. M. C.; Serpa, Cristina; Gowrisankar, A.In this paper, new results on the alpha-fractal function with variable parameters are presented. The Weyl-Marchaud variable order fractional derivative of an alpha-fractal function with variable parameters is examined by imposing certain conditions on the scaling factors. Following the investigation of fractional derivative, the definite integral of the alpha-fractal function with variable parameters is evaluated for various intervals in the prescribed domain. Finally, an explicit structure for the alpha-fractal function is provided using the base q representation of numbers.
- Analysis of integrated calcium looping alternatives in a cement plantPublication . Amorim, Ana; Filipe, Rui; Matos, Henrique A.Calcium looping is a promising post-combustion CO2 capturing technology, highly compatible with the cement industry, one of the major industrial sources of CO2 emissions. Limestone, a raw material for clinker, forms lime, a calcium looping adsorbent. Thus, it is possible to maximize the synergies between a cement plant and a calcium looping unit by establishing an integrated configuration. Nevertheless, the integration of calcium looping in cement plants has not yet been thoroughly studied. This study examines different integration alternatives, developing models for the preheater and calciner using Aspen Plus, validated with operational data, alongside an entrained-flow carbonator model considering adsorbent deactivation. By combining these models, six integrated configurations are proposed and compared with the tail-end calcium looping configuration. The integrated configurations show a reduction in fuel consumption and net energy consumption for the same CO2 avoided emissions. The most promising configuration was identified and a comparative techno-economic analysis was conducted.
- Anti-hypercholesterolemia effects of edible seaweed extracts and metabolomic changes in Hep-G2 and Caco-2 cell linesPublication . Coelho, Mariana; Pacheco, RitaHypercholesterolemia is a major risk for the development of cardiovascular diseases (CVDs), the main cause of mortality worldwide, and it is characterized by high levels of circulating cholesterol. The drugs currently available for hypercholesterolemia control have several side effects, so it is necessary to develop new effective and safer therapies. Seaweeds serve as sources of several bioactive compounds with claimed beneficial effects. Eisenia bicyclis (Aramé) and Porphyra tenera (Nori) are edible seaweeds that were previously recognized as rich in bioactive compounds. In the present study, we aim to evaluate the anti-hypercholesterolemia effect of these two seaweed extracts and their health potential. Both extracts, but more efficiently Aramé extract, have liver 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGR) inhibitory activity as well as the capability to reduce approximately 30% of cholesterol permeation through human Caco-2 cells by simulating the intestinal lining, which is a target for hypercholesterolemia treatments. An untargeted metabolomic assay on human intestinal Caco-2 and liver Hep-G2 cell lines exposed to Aramé and Nori extracts revealed changes in the cells’ metabolism, indicating the extracts’ health beneficial effects. The metabolic pathways affected by exposure to both extracts were associated with lipid metabolism, such as phospholipids, and fatty acid metabolism, amino acid pathways, cofactors, vitamins, and cellular respiration metabolism. The effects were more profound in Aramé-treated cells, but they were also observed in Nori-exposed cells. The metabolite modifications were associated with the protection against CVDs and other diseases and to the improvement of the cells’ oxidative stress tolerance. The results obtained for the anti-hypercholesterolemia properties, in addition to the revelation of the positive impact on cell metabolism, offer an important contribution for further evaluation of these seaweed extracts as functional foods or for CVD prevention.
- Ardosia: simulating circuits and robotic systems in a platformPublication . Marnoto de Oliveira Campos, Francisco MateusCircuit simulation, together with practical sessions, is considered a fundamental tool to assist in the teaching of electronics. Robotics offers rich real-world applications that foster student interest in developing engineering projects. Despite the potential benefits of uniting these two realities, software tools that combine circuits and robotic systems in a single simulation platform are scarce. This article presents Ardosia, a simulation software that combines electronics and robotics in a single simulation arena. The electronic aspects of the simulation are handled by the Falstad Circuit Simulator, a software with proven success in promoting student interest and learning outcomes. Importantly, this software features significant interactive and visualization characteristics that are deemed valuable to enhance conceptual understanding. Non-electrical physics simulation is performed by a special-purpose engine, designed to simulate sensor and actuator behavior in a 2-D world. In combination, the two simulation engines yield a model where electronic circuits are embodied in the world through robot sensors and actuators interacting together and with the surroundings. Such a simulator is intended to promote the use of robotics projects in electronics education, since students will be equipped with software to conveniently design and evaluate robotic systems, through simulation, before applying their ideas in an experimental setting. This article presents an overview of Ardosia, complemented with examples of use in electronics education and a validation experiment comparing simulation with real-world data.
- Assessing machine learning techniques for intrusion detection in cyber-physical systemsPublication . Santos, Vinicius F.; Albuquerque, Célio; Passos, Diego; Ereno Quincozes, Silvio; Mossé, DanielCyber-physical systems (CPS) are vital to key infrastructures such as Smart Grids and water treatment, and are increasingly vulnerable to a broad spectrum of evolving attacks. Whereas traditional security mechanisms, such as encryption and firewalls, are often inadequate for CPS architectures, the implementation of Intrusion Detection Systems (IDS) tailored for CPS has become an essential strategy for securing them. In this context, it is worth noting the difference between traditional offline Machine Learning (ML) techniques and understanding how they perform under different IDS applications. To answer these questions, this article presents a novel comparison of five offline and three online ML algorithms for intrusion detection using seven CPS-specific datasets, revealing that offline ML is superior when attack signatures are present without time constraints, while online techniques offer a quicker response to new attacks. The findings provide a pathway for enhancing CPS security through a balanced and effective combination of ML techniques.
- Assessment of influential operational parameters in the mitigation of CO2 emissions in a power plant: case study in PortugalPublication . Balanuta, Vítor; Baptista, Patricia; Neves da Fonseca Cardoso Carreira, Fernando Paulo; Duarte, Gonçalo; Casaca, Cláudia Sofia Séneca da LuzThe European decarbonization goals and requirement for energy independence are mostly relying on intermittent renewable energy sources for electrification. A numerical model was developed to simulate the operation of a steam generator, allowing a study of the potential impacts of retrofitting existing coal-fired power plants to operate with biomass or coal–biomass mixtures on combustion parameters and CO2 emissions. The results obtained using the operational parameters of the Sines power plant indicate that a mixture of 25% coal and 75% pine sawdust allow operation at λ = 1.8, demonstrating that a small amount of coal allows operation near the coal combustion parameters (λ = 1.9). These conditions have the drawback of a reduction of 8.7% in adiabatic flame temperature but a significant reduction of 57.5% in CO2 emissions, considering the biomass as carbon-neutral.
- Automatic completion of data gaps applied to a system of water pumpsPublication . Enguiça, Ricardo; Soares, FilipaWe consider a time series with real data from a water lift station, equipped with three water pumps which are activated and deactivated depending on certain starting and halting thresholds. Given the water level and the number of active pumps, both read every 5 min, we aim to infer when each pump was activated or deactivated. To do so, we build an algorithm that sets a hierarchy of criteria based on the past and future of a given interval to identify which thresholds have been crossed during that interval. We then fill the gaps between the 5 min time steps, modeling the water level continuously with a piecewise linear function. This filling takes into account not only every water level reading and every previously identified change of status, but also the fact that activation and deactivation of a pump has no immediate effect on water level. This allows for the fulfillment of the ultimate objective of the problem in its real context, which is to provide the water management company an estimate of how long each pump has been working. Additionally, our estimates correct the errors contained in the time series regarding the number of active pumps.
- An autonomic parallel strategy for exhaustive search tree algorithms on shared or heterogeneous systemsPublication . Gonçalves de Oliveira Passos, Fernanda; Rebello, Vinod E. F.Backtracking branch-and-prune (BP) algorithms and their variants are exhaustive search tree techniques widely employed to solve optimization problems in many scientific areas. However, they characteristically often demand significant amounts of computing power for problem sizes representative of real-world scenarios. Given that their search domains can often be partitioned, these algorithms are frequently designed to execute in parallel by harnessing distributed computing systems. However, to achieve efficient parallel execution times, an effective strategy is required to balance the nonuniform partition workloads across the available resources. Furthermore, with the increasing integration of servers with heterogeneous resources and the adoption of resource sharing, balancing workloads is becoming complex. This paper proposes a strategy to execute parallel BP algorithms more efficiently on even shared or heterogeneous distributed systems. The approach integrates a self-adjusting dynamic partitioning method in the BP algorithm with a dynamic scheduler, provided by an application middleware, which manages the parallel execution while addressing any issues of imbalance. Empirical results indicate better scalability with efficiencies above 90% for instances of an application case study for the discretizable molecular distance geometry problem (DMDGP). Improvements of up to 38% were obtained in execution speed-ups compared to a more traditional parallel BP implementation for DMDGP.
- Biochemical methane potential assays for organic wastes as an anaerobic digestion feedstockPublication . Cabrita, Tiago Miguel; Santos, Maria TeresaThe anaerobic digestion process is applied worldwide in the treatment of various organic wastes, allowing energy production from biogas and organic recovery from digested sludge. In the evaluation of suitable substrates for anaerobic digestion, Biochemical Methane Potential assays are the most applied, and, despite several efforts to standardize this method, it is observed that there are still several studies that do not apply all the criteria. This current paper’s main goal is to present a review of anaerobic feedstocks, BMP methodologies, experimental conditions, and results of specific methane production from 2008 to 2023. A wide range of anaerobic feedstocks was found, which was divided into five groups: animal manure, sludge, food wastes, energy crops, and other organic wastes. Several parameters were used to characterize the anaerobic feedstocks, like TS, VS, COD, and pH, displaying different value ranges. The number of publications concerning BMP assays increased significantly over the years until 2021, having stabilized in the last two years. This evolution allowed for several attempts to standardize the BMP method with positive developments, but there are still some gaps in the experimental conditions and the determination of specific methane production. All of this makes the comparison of some studies a challenge.
- Blood molecular profile to predict genotoxicity from exposure to antineoplastic drugsPublication . Ladeira, Carina; Araújo, Rúben; Ramalhete, Luís; Teixeira, Hélder; Calado, CecíliaGenotoxicity is an important information that should be included in human biomonitoring programmes. How-ever, the usually applied cytogenetic assays are laborious and time-consuming, reason why it is critical to develop rapid and economic new methods. The aim of this study was to evaluate if the molecular profile of frozen whole blood, acquired by Fourier Transform Infrared (FTIR) spectroscopy, allows to assess genotoxicity in occupational exposure to antineoplastic drugs, as obtained by the cytokinesis-block micronucleus assay. For that purpose, 92 samples of peripheral blood were studied: 46 samples from hospital professionals occupationally exposed to antineoplastic drugs and 46 samples from workers in academia without exposure (controls). It was first evaluated the metabolome from frozen whole blood by methanol precipitation of macromolecules as haemoglobin, followed by centrifugation. The metabolome molecular profile resulted in 3 ratios of spectral bands, significantly different between the exposed and non-exposed group (p < 0.01) and a spectral principal component-linear discriminant analysis (PCA-LDA) model enabling to predict genotoxicity from exposure with 73 % accuracy. After optimization of the dilution degree and solution used, it was possible to obtain a higher number of significant ratios of spectral bands, i.e., 10 ratios significantly different (p < 0.001), highlighting the high sensitivity and specificity of the method. Indeed, the PCA-LDA model, based on the molecular profile of whole blood, enabled to predict genotoxicity from the exposure with an accuracy, sensitivity, and specificity of 92 %, 93 % and 91 %, respectively. All these parameters were achieved based on 1 mu L of frozen whole blood, in a high-throughput mode, i.e., based on the simultaneous analysis of 92 samples, in a simple and economic mode. In summary, it can be conclude that this method presents a very promising potential for high-dimension screening of exposure to genotoxic substances.