Optimal dynamic control of laminated adaptive structures using a higher order model and a genetic algorithm

This paper deals with a finite element formulation based on the classical laminated plate theory, for active control of thin plate laminated structures with integrated piezoelectric layers, acting as sensors and actuators. The control is initialized through a previous optimization of the core of the laminated structure, in order to minimize the vibration amplitude. Also the optimization of the patches position is performed to maximize the piezoelectric actuator efficiency. The genetic algorithm is used for these purposes. The finite element model is a single layer triangular plate/shell element with 24 degrees of freedom for the generalized displacements, and one electrical potential degree of freedom for each piezoelectric element layer, which can be surface bonded or embedded on the laminate. To achieve a mechanism of active control of the structure dynamic response, a feedback control algorithm is used, coupling the sensor and active piezoelectric layers. To calculate the dynamic response of the laminated structures the Newmark method is considered. The model is applied in the solution of an illustrative case and the results are presented and discussed

A Novel mHealth Approach for the Monitoring and Assisted Therapeutics of Obstructive Sleep Apnea

Obstructive sleep apnea is a respiratory problem that has serious consequences for physical and mental health, but also in monetary terms, since traffic accidents and poor work performance, among other direct consequences, are attributed to it. It is estimated that between 9% and 38% of the world’s population has this disease. This is a multifactorial disease, therefore, there are several methods of detection and treatment; however, all of them cause discomfort to the patient, or to those around them. In this article we propose a system for the detection and control of obstructive sleep apnea that promises to overcome the drawbacks of the existing therapies, therefore, potentially making it a practical and effective solution for this disease. The proof of concept presented in this paper makes use of an electromyography sensor to collect the myoelectric signal produced by the genioglossus muscle. Surface electrodes provide the electromyography signals to an ESP32 microcontroller, which has the function of analyzing and comparing the data obtained with a predefined value of the apnea threshold. After the detection of an apnea, the circuit is able to create a stimulus signal that is applied directly to the muscle, so that airway occlusion does not occur, and the user does not wake up. The data from each use are automatically sent to a database to be viewed and analyzed at a later point.info:eu-repo/semantics/publishedVersio

Synthesis, characterization and preliminary antibacterial evaluation against Staphylococcus aureus of a new 2,4,5-tri(hetero)arylimidazole derivative based on azaindole heterocycle

Imidazole derivatives are known for their numerous biological applications, such as antibacterial, antifungal, antioxidant, antiviral, antiparasitic and anticancer, among others. Therefore, several imidazole derivatives have been synthesized and developed in recent years as potential drugs in the treatment of several diseases. In this communication, we report the synthesis of a new imidazole derivative, substituted at positions 2, 4 and 5 with heterocyclic groups, using a simple synthetic methodology and an easy purification procedure. The new compound was characterized by the usual spectroscopic techniques (NMR, UV-Vis absorption and emission). The evaluation of the novel imidazole derivative as a potential antibiotic drug was carried out against the Gram-positive bacterium Staphylococcus aureus, using disk test diffusion method. Results showed a dose-response effect against the bacteria under study, revealing that the rational design of this imidazole derivative is quite promising to improve antibacterial activity of imidazole derivatives.This research was funded by the Foundation for Science and Technology (FCT) through CQ/UM (UIDB/00686/2020) and “Contrato‐Programa” UIDB/04050/2020 funded by national funds. Thanks are also due to FCT for financial support to the Portuguese NMR Network (PTNMR, Bruker Avance III 400‐Univ. Minho)info:eu-repo/semantics/publishedVersio

Synthesis and screening of antibacterial activity of 2,4,5-tri(hetero)arylimidazoles based on thieno[3,2-b]thiophene

After the discovery of antibiotics, efforts were made to develop new drugs in order to treat infections caused by a wide range of bacterial strains. With the use of antibiotics for decades, bacteria have adapted, so that resistant strains have emerged. Moreover, the uncontrolled and abusive use of antibiotics has increased, which aggravates the emergence of new resistant strains. The emergence of multidrug resistant (MDR) bacteria has quickly become a worldwide health problem, so new strategies must be developed in order to control MDR bacteria, namely the rational development of new drugs. Imidazole derivatives have several biological activities, including antibacterial activity. In this sense, efforts have been made to develop imidazole-based compounds, because they present higher curative effect than other antibiotics used in clinical practice, lower toxicity and less side effects.1 With this in mind, we report the synthesis of two 2,4,5-tri(hetero)arylimidazoles 3a-b based on thieno[3,2-b]thiophene heterocyclic spacer (Figure 1), through the Radziszewski reaction2 and their characterization by 1H and 13C NMR, UV-Vis absorption and fluorescence spectroscopies. In addition, a screening for antibacterial activity with the synthetized imidazole derivatives against Bacillus subtilis was carried out, using the agar diffusion technique. The results showed the inhibition of Bacillus subtilis proliferation, suggesting antibacterial activity. Therefore, these new imidazole derivatives have the potential for the development of new antibacterial drugs.Thanks are due to Fundação para a Ciência e Tecnologia (FCT) and FEDER (European Fund for Regional Development)-COMPETE-QRENEU for financial support through the Chemistry Research Centre of the University of Minho (UID/QUI/00686/2020). This work was also supported by the “Contrato-Programa” UIDB/04050/2020 funded by national funds through the FCT I.P. Thanks are also due to FCT for financial support to the Portuguese NMR network (PTNMR, Bruker Avance III – Univ. Minho).info:eu-repo/semantics/publishedVersio

Artificial Intelligence Decision Support System Based on Artificial Neural Networks to Predict the Commercialization Time by the Evolution of Peach Quality

Climacteric fruit such as peaches are stored in cold chambers after harvest and usually are maintained there until the desired ripening is reached to direct these fruit to market. Producers, food industries and or traders have difficulties in defining the period when fruit are at the highest level of quality desired by consumers in terms of the physical‐chemical parameters (hardness –H–, soluble solids content –SSC–, and acidity –Ac–). The evolution of peach quality in terms of these parameters depends directly on storage temperature –T– and relative humidity –RH–, as well on the storage duration –t–. This paper describes an Artificial Intelligence (AI) Decision Support Sys‐ tem (DSS) designed to predict the evolution of the quality of peaches, namely the storage time re‐ quired before commercialization as well as the late commercialization time. The peaches quality is stated in terms of the values of SSC, H and Ac that consumers most like for the storage T and RH. An Artificial neuronal network (ANN) is proposed to provide this prediction. The training and val‐ idation of the ANN were conducted with experimental data acquired in three different farmers’ cold storage facilities. A user interface was developed to provide an expedited and simple predic‐ tion of the marketable time of peaches, considering the storage temperature, relative humidity, and initial physical and chemical parameters. This AI DSS may help the vegetable sector (logistics and retailers), especially smaller neighborhood grocery stores, define the marketable period of fruit. It will contribute with advantages and benefits for all parties—producers, traders, retailers, and con‐ sumers—by being able to provide fruit at the highest quality and reducing waste in the process. In this sense, the ANN DSS proposed in this study contributes to new AI‐based solutions for smart cities.This study is within the activities of project PrunusPós—Otimização de processos de ar‐ mazenamento, conservação em frio, embalamento ativo e/ou inteligente, e rastreabilidade da qual‐ idade alimentar no póscolheita de produtos frutícolas (Optimization of processes of storage, cold conservation, active and/or intelligent packaging, and traceability of food quality in the postharvest of fruit products), Operation n.º PDR2020‐101‐031695 (Partner), Consortium n.º 87, Initiative n.º 175 promoted by PDR2020 and co‐financed by FEADER under the Portugal 2020 initiative.info:eu-repo/semantics/publishedVersio

Synthesis and preliminary antibacterial evaluation of A 2,4,5-Tri(hetero)arylimidazole derivative

The imidazole ring is a planar heterocycle whose derivatives are applied in several scientific areas, such as medicinal, materials and supramolecular chemistry. The presence of the imidazole ring in these structures is the key to the development of new drugs, since it is ubiquitous in naturally occurring biological structures. Therefore, over the past few decades, several imidazole derivatives have been synthesized and occupy a unique position in the field of medicinal chemistry due to their diverse biological activities. In order to continue the work developed by the research group, we report the synthesis of 2,4,5-tri(hetero)arylimidazole derivatives and their characterization by 1H and 13C nuclear magnetic resonance (NMR) and UV-Vis absorption spectroscopies. As a complement to the characterization of the synthesized 2,4,5-tri(hetero)arylimidazole derivatives, a screening for antibacterial activity showed the inhibition of Staphylococcus aureus proliferation, suggesting antibacterial activity. Therefore, these new compounds have the potential for the development of new drugs

Road Pavement Damage Detection using Computer Vision Techniques: Approaches, Challenges and Opportunities

The work presented in this paper is the result of a preliminary research aimed at using computer vision techniques for road pavement damage detection in the context of a smart city. It first introduces the related concepts. Then, it surveys the state of the art and existing solutions, presenting their main features, strengths and limitations. The most promising solutions are identified. Finally, it discusses open challenges and research directions in this area

Real-Time Detection of Vine Trunk for Robot Localization Using Deep Learning Models Developed for Edge TPU Devices

The concept of the Internet of Things (IoT) in agriculture is associated with the use of high-tech devices such as robots and sensors that are interconnected to assess or monitor conditions on a particular plot of land and then deploy the various factors of production such as seeds, fertilizer, water, etc., accordingly. Vine trunk detection can help create an accurate map of the vineyard that the agricultural robot can rely on to safely navigate and perform a variety of agricultural tasks such as harvesting, pruning, etc. In this work, the state-of-the-art single-shot multibox detector (SSD) with MobileDet Edge TPU and MobileNet Edge TPU models as the backbone was used to detect the tree trunks in the vineyard. Compared to the SSD with MobileNet-V1, MobileNet-V2, and MobileDet as backbone, the SSD with MobileNet Edge TPU was more accurate in inference on the Raspberrypi, with almost the same inference time on the TPU. The SSD with MobileDet Edge TPU achieved the second-best accurate model. Additionally, this work examines the effects of some features, including the size of the input model, the quantity of training data, and the diversity of the training dataset. Increasing the size of the input model and the training dataset increased the performance of the model.info:eu-repo/semantics/publishedVersio

Computational Simulation of an Agricultural Robotic Rover for Weed Control and Fallen Fruit Collection—Algorithms for Image Detection and Recognition and Systems Control, Regulation, and Command

The continuous rise in the world’s population has increased the need for food, resulting in a rise of agricultural holdings to ensure the supply of these goods directly to the populations and indirectly to all processing industries in the food business. This situation has led agriculture to reinvent itself and introduce new technics and tools to ensure tighter control of the crops and increase yields in food production. However, the lack of labor coupled with the evolution of weeds resistant to herbicides created a crisis in agricultural food production. However, with the growing evolution in electronics, automation, and robotics, new paths are emerging to solve these problems. A robotic rover was designed to optimize the tasks of weed control and collection of fallen fruits of an orchard. In weed control, a localized spraying system is proposed, therefore reducing the amount of applied herbicides. With fruit collection, it is possible to direct fallen fruits for animal feeding and possible to reduce microbial activity on the next campaign crops, therefore avoiding damage. This study proposes the simulation of this robotic rover on robotic simulation software. It also proposes the replication of a similar environment of an orchard to generate an algorithm that controls the rover on the tasks of localized spraying and fallen fruit collection. Creating and testing these algorithms by using a robotic simulator speed up and ease the evaluation of different scenarios and hypotheses, with the added benefit of being able to test two tasks simultaneously. This method also allows greater freedom and creativity because there are no concerns about hardware damage. It should also be noted that development costs are very low.info:eu-repo/semantics/publishedVersio

Wireless Sensor Networks for Building Robotic Paths - A Survey of Problems and Restrictions

The conjugation of small nodes with sensing, communication and processing capabilities allows for the creation of wireless sensor networks (WSNs). These networks can be deployed to measure a very wide range of environmental phenomena and send data from remote locations back to users. They offer new and exciting possibilities for applications and research. This paper presents the background of WSNs by firstly exploring the different fields applications, with examples for each of these fields, then the challenges faced by these networks in areas such as energy-efficiency, node localization, node deployment, limited storage and routing. It aims at explaining each issue and giving solutions that have been proposed in the research literature. Finally, the paper proposes a practical scenario of deploying a WSN by autonomous robot path construction. The requirements for such a scenario and the open issues that can be tackled by it are exposed, namely the issues of associated with measuring RSSI, the degree of autonomy of the robot and connectivity restoration.The authors would like to acknowledge the company Inspiring Sci, Lda for the interest and valuable contribution to the successful development of this work.info:eu-repo/semantics/publishedVersio