Recent Progress in Stimuli-Responsive Antimicrobial Electrospun Nanofibers

Electrospun nanofibrous membranes have garnered significant attention in antimicrobial applications, owing to their intricate three-dimensional network that confers an interconnected porous structure, high specific surface area, and tunable physicochemical properties, as well as their notable capacity for loading and sustained release of antimicrobial agents. Tailoring polymer or hybrid-based nanofibrous membranes with stimuli-responsive characteristics further enhances their versatility, enabling them to exhibit broad-spectrum or specific activity against diverse microorganisms. In this review, we elucidate the pivotal advancements achieved in the realm of stimuli-responsive antimicrobial electrospun nanofibers operating by light, temperature, pH, humidity, and electric field, among others. We provide a concise introduction to the strategies employed to design smart electrospun nanofibers with antimicrobial properties. The core section of our review spotlights recent progress in electrospun nanofiber-based systems triggered by single- and multi-stimuli. Within each stimulus category, we explore recent examples of nanofibers based on different polymers and antimicrobial agents. Finally, we delve into the constraints and future directions of stimuli-responsive nanofibrous materials, paving the way for their wider application spectrum and catalyzing progress toward industrial utilization

Predictive Maintenance Model Based on Anomaly Detection in Induction Motors: A Machine Learning Approach Using Real-Time IoT Data

With the support of Internet of Things (IoT) devices, it is possible to acquire data from degradation phenomena and design data-driven models to perform anomaly detection in industrial equipment. This approach not only identifies potential anomalies but can also serve as a first step toward building predictive maintenance policies. In this work, we demonstrate a novel anomaly detection system on induction motors used in pumps, compressors, fans, and other industrial machines. This work evaluates a combination of pre-processing techniques and machine learning (ML) models with a low computational cost. We use a combination of pre-processing techniques such as Fast Fourier Transform (FFT), Wavelet Transform (WT), and binning, which are well-known approaches for extracting features from raw data. We also aim to guarantee an optimal balance between multiple conflicting parameters, such as anomaly detection rate, false positive rate, and inference speed of the solution. To this end, multiobjective optimization and analysis are performed on the evaluated models. Pareto-optimal solutions are presented to select which models have the best results regarding classification metrics and computational effort. Differently from most works in this field that use publicly available datasets to validate their models, we propose an end-to-end solution combining low-cost and readily available IoT sensors. The approach is validated by acquiring a custom dataset from induction motors. Also, we fuse vibration, temperature, and noise data from these sensors as the input to the proposed ML model. Therefore, we aim to propose a methodology general enough to be applied in different industrial contexts in the future

Reorganizando o Laboratório de Ciências: uma experiência da abordagem do PIBID/UESC de Química no espaço escolar

A formação de professores de Química tem sido discutida por diversos profissionais da educação que buscam, dentre outras coisas, apresentar os aspectos que estão envolvidos nesse processo. Sendo assim, o intuito deste trabalho é apresentar os resultados obtidos com a intervenção do PIBID/Química UESC em que houve a reorganização de um laboratório de Ciências e esta atividade foi relacionada à formação dos licenciandos envolvidos. Pretendemos também demonstrar a importância deste espaço para a formação de conceitos de Ciências, mas precisamente de Química. Para tal, executamos uma atividade em grupo onde a reorganização deste laboratório foi o foco principal, além da aplicação de um questionário buscando conhecer as impressões dos alunos a cerca do local. Pudemos então perceber que o laboratório de Ciências é um local onde os saberes de Química podem ser construídos e que a atividade por nós realizada teve implicações significativas para nossa formação como licenciandos em Químic

PIBID Química/UESC: Uma perspectiva de ensino e aprendizagem por meio da Situação de Estudo “Nutrição Consciente”

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Accuracy of Hidden Markov Models in Identifying Alterations in Movement Patterns during Biceps-Curl Weight-Lifting Exercise

This paper presents a comparison of mathematical and cinematic motion analysis regarding the accuracy of the detection of alterations in the patterns of positional sequence during biceps-curl lifting exercise. Two different methods, one with and one without metric data from the environment, were used to identify the changes. Ten volunteers performed a standing biceps-curl exercise with additional loads. A smartphone recorded their movements in the sagittal plane, providing information on joints and barbell sequential position changes during each lift attempt. An analysis of variance revealed significant differences in joint position (p < 0.05) among executions with three different loads. Hidden Markov models were trained with data from the bi-dimensional coordinates of the joint positional sequence to identify meaningful alteration with load increment. Tests of agreement tests between the results provided by the models with the environmental measurements, as well as those from image coordinates, were performed. The results demonstrated that it is possible to efficiently detect changes in the patterns of positional sequence with and without the necessity of measurement and/or environmental control, reaching an agreement of 86% between each other, and 100% and 86% for each respective method to the results of ANOVA. The method developed in this study illustrates the viability of smartphone camera use for identifying positional adjustments due to the inability to control limbs in an adequate range of motion with increasing load during a lifting task.info:eu-repo/semantics/publishedVersio

Antimicrobial and Photoantimicrobial Activities of Chitosan/CNPPV Nanocomposites

Multidrug-resistant bacteria represent a global health and economic burden that urgently calls for new technologies to combat bacterial antimicrobial resistance. Here, we developed novel nanocomposites (NCPs) based on chitosan that display different degrees of acetylation (DAs), and conjugated polymer cyano-substituted poly(p-phenylene vinylene) (CNPPV) as an alternative approach to inactivate Gram-negative (E. coli) and Gram-positive (S. aureus) bacteria. Chitosan's structure was confirmed through FT-Raman spectroscopy. Bactericidal and photobactericidal activities of NCPs were tested under dark and blue-light irradiation conditions, respectively. Hydrodynamic size and aqueous stability were determined by DLS, zeta potential (ZP) and time-domain NMR. TEM micrographs of NCPs were obtained, and their capacity of generating reactive oxygen species (ROS) under blue illumination was also characterized. Meaningful variations on ZP and relaxation time T2 confirmed successful physical attachment of chitosan/CNPPV. All NCPs exhibited a similar and shrunken spherical shape according to TEM. A lower DA is responsible for driving higher bactericidal performance alongside the synergistic effect from CNPPV, lower nanosized distribution profile and higher positive charged surface. ROS production was proportionally found in NCPs with and without CNPPV by decreasing the DA, leading to a remarkable photobactericidal effect under blue-light irradiation. Overall, our findings indicate that chitosan/CNPPV NCPs may constitute a valuable asset for the development of innovative strategies for inactivation and/or photoinactivation of bacteria. Keywords: photoantimicrobial activity; blue-light irradiation; chitosan; CNPPV; nanocomposites; E. coli; S. aureu

Petróleo: O ensino de Química Orgânica voltado para o cotidiano

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Physical characteristics of guava (Psidium guajava L.) submitted to hot water treatment

Post harvest losses of fruits and vegetables could be reduced if appropriate practices after the harvest until its commercialization are adopted. For this, not only knowledge of the physiological processes of the product is necessary, but also an adequate infrastructure and distribution logistic. The indiscriminate use of chemical products for eradication of plagues and diseases in the cultivation and also in the post harvest period is being substituted successfully by methods that do not cause harm to human beings or to the environment, reasons for which physical treatments (application of heat, cold or ionized radiation) are being intensively investigated. Some parameters related to physical and physiologic quality of the guava Pedro Sato, were determined in this research, after complete immersion of the fruits in hot water at a temperature of 47 °C during 6 min, and stored at 8 and 22 °C, with medium relative humidity equal to 89%. It was observed that the hot water treatment, in a general way, promoted retardation in the mass loss and the firmness during the storage period, but did not cause a climacteric ascension in the production of CO2 and ethylene.As perdas pós-colheita de frutas e hortaliças podem ser reduzidas se práticas adequadas desde a colheita até a sua comercialização forem adotadas, para tanto é necessário não só o conhecimento dos processos fisiológicos do produto, mas também uma infra-estrutura e logística de distribuição adequada. O uso indiscriminado de produtos químicos para erradicação de pragas e doenças na lavoura e no período pós-colheita está sendo substituído com sucesso por métodos que não causem danos ao homem nem ao meio ambiente, razão por que tratamentos físicos (aplicação de calor, frio ou radiação ionizante) estão sendo amplamente pesquisados. Foram avaliados, neste trabalho, alguns parâmetros relacionados à qualidade física e fisiológica de goiabas Pedro Sato, após a imersão de frutos íntegros em água a temperatura de 47 °C, durante 6 min, e armazenadas a 8 e 22 °C, com umidade relativa média igual a 89%. Observou-se de maneira geral, que o tratamento hidrotérmico proposto, promoveu retardamento na perda de massa e na firmeza da polpa durante o período de armazenamento mas não se constatou ascensão climatérica na produção de CO2 e etileno.40841

Triagem Inteligente: O Uso da Internet das Coisas na Classificação dos Riscos nas Emergências

Este artigo tem como objetivo apresentar a automação do processo de triagem de pacientes utilizando o atuador Arduino. O processo de triagem determina o nível de risco do paciente e sua execução pode tornar-se desnecessariamente complexa, sendo que, aproximadamente, 80% dos pacientes em serviços de emergência não necessitam de atendimento urgente. Portanto, a automatização deste processo pode provar-se bastante benéfica: os dados do paciente são analisados em tempo real, provendo um resultado seguro e em alta velocidade, garantindo prioridade a pacientes em risco e reduzindo o tempo de admissão dele

Triagem Inteligente: O Uso da Internet das Coisas na Classificação dos Riscos nas Emergências

Este artigo tem como objetivo apresentar a automação do processo de triagem de pacientes utilizando o atuador Arduino. O processo de triagem determina o nível de risco do paciente e sua execução pode tornar-se desnecessariamente complexa, sendo que, aproximadamente, 80% dos pacientes em serviços de emergência não necessitam de atendimento urgente. Portanto, a automatização deste processo pode provar-se bastante benéfica: os dados do paciente são analisados em tempo real, provendo um resultado seguro e em alta velocidade, garantindo prioridade a pacientes em risco e reduzindo o tempo de admissão dele