Description of the complete larval development of Lysmata amboinensis (De Man) (Decapoda: Lysmatidae) reared under laboratory conditions

This work was done under the framework of the project PLANTROF (MAR-01.04.02-FEAMP-0001) co-financed by MAR2020, Portugal2020 and European Union. MARE-Polytechnic of Leiria was supported by the Integrated Programme of SR&TD “Smart Valorization of Endogenous Marine Biological Resources Under a Changing Climate”, Portugal (Centro-01-0145-FEDER-000018), co-funded by Centro 2020 programme, Portugal 2020, Portugal, European Union through the European Regional Development Fund. The authors wish to express their sincere thanks to Ricardo Calado for his corrections and suggestions that clearly improve the manuscript.Complete larval morphological descriptions are currently only known for three of the 48 species of genus Lysmata. The present study describes and illustrates the larval development of Lysmata amboinensis (De Man) reared under laboratory conditions. Lysmata amboinensis larval development is composed by a total of ten zoea and a decapodite stage. The first zoeal stage larvae presents sessile eyes, a carapace with a pterigostomial spine and anterio-ventral marginal denticles, a long, slender, and pointed rostrum, an antennal exopod terminally segmented, a pleon with five somites, the fifth one bearing a pair of dorso-lateral spines on the posterior margin, and a triangular shaped telson with 7+7 posterior processes. The decapodite resembles a smaller adult and has extremely long antennas (more than twice the total length of the decapodite), the first two pair of pereiopods with chela, first four pairs of pereiopods with reduced and unsegmented exopods, and fully developed pleopods. The morphological features of L. amboinensis are compared with those currently available for the larval stage of the genus Lysmata.info:eu-repo/semantics/acceptedVersio

Virgin and recycled polypropylene composites reinforced with sisal by-product

Foram estudadas as propriedades térmicas e mecânicas de compósitos de polipropileno, virgem e reciclado, reforçados com 30% em massa de fibras residuais de sisal, assim como o perfil de processamento e a morfologia da matriz polimérica. Para tanto, foram determinadas a resistência à tração, o módulo de Young, alongamento na ruptura, e energia de impacto. As amostras também foram caracterizadas por MEV, DMTA e TG. Para ambos os compósitos de polipropileno, virgem e reciclado, com a adição das fibras, o alongamento na ruptura mostrou uma queda significativa, enquanto que a resistência à tração não sofreu grandes variações. Houve um aumento significativo nos valores de tração na ruptura e de energia de impacto com a adição das fibras de sisal na matriz de polipropileno. As análises térmicas mostraram ligações secundárias, como as ligações polares, entre as fibras e a matriz, concordando com o comportamento mecânico dos compósitos. Constatou-se que a temperatura de transição vítrea não variou após a adição da fibra.The mechanical and thermal properties of virgin and recycled polypropylene composites reinforced with 30% by mass of residual sisal fibers were studied, in addition to an analysis of the extrusion process and morphology of the polymeric matrix. Tensile strength, Young's modulus, elongation at break, and impact energy were determined. The samples were also characterized by SEM, DMTA and TG analyses. Elongation at break of the composites presented a significant decrease, while the tensile strength was not affected significantly by addition of sisal fibers. A significant increase was observed in the tension of rupture and in the impact energy of the composite reinforced with sisal fiber. The thermal analyses indicated secondary interactions, such as polar interactions, between the fibers and the matrix, consistent with the mechanical behavior of the composites. The glass transition temperature has not changed after fiber addition.Universidade Federal de São Carlos - Departamento de Engenharia de MateriaisFinepCNP

An outlier-resistant κ\kappa-generalized approach for robust physical parameter estimation

In this work we propose a robust methodology to mitigate the undesirable effects caused by outliers to generate reliable physical models. In this way, we formulate the inverse problems theory in the context of Kaniadakis statistical mechanics (or $\kappa$-statistics), in which the classical approach is a particular case. In this regard, the errors are assumed to be distributed according to a finite-variance $\kappa$-generalized Gaussian distribution. Based on the probabilistic maximum-likelihood method we derive a $\kappa$-objective function associated with the finite-variance $\kappa$-Gaussian distribution. To demonstrate our proposal's outlier-resistance, we analyze the robustness properties of the $\kappa$-objective function with help of the so-called influence function. In this regard, we discuss the role of the entropic index ($\kappa$) associated with the Kaniadakis $\kappa$-entropy in the effectiveness in inferring physical parameters by using strongly noisy data. In this way, we consider a classical geophysical data-inverse problem in two realistic circumstances, in which the first one refers to study the sensibility of our proposal to uncertainties in the input parameters, and the second is devoted to the inversion of a seismic data set contaminated by outliers. The results reveal an optimum $\kappa$-value at the limit $\kappa \rightarrow 2/3$, which is related to the best results.Comment: 37 pages, 23 figure

Caracterização da cinza de cama sobreposta de suínos e seu aproveitamento em compósitos cimentícios

The deep bedding is a swine alternative production, especially in the finishing phase, whose byproduct can be recycled, reducing the environmental impact. The objectives of this study were to characterize the ash coming from the controlled burning of the swine deep bedding (SDBA) based on rice husk, and to evaluate their performance in composites as a partial substitute for Portland cement (PC). To measure the differences between SDBA and rice husk ash (RHA) as a reference, we have characterized: particle size distribution, real specific density, x-ray diffraction, electrical conductivity, scanning electron microscopy, chemical analysis and loss on ignition. Samples were prepared for two experimental series: control, and another one with the partial replacement of 30% of SDBA in relation to the mass of the Portland cement. According to the results obtained for physical and mechanical characterization, the composites with SDBA can be used as a constructive element in the rural construction

Anomaly Detection in Industrial Machinery using IoT Devices and Machine Learning: a Systematic Mapping

Anomaly detection is critical in the smart industry for preventing equipment failure, reducing downtime, and improving safety. Internet of Things (IoT) has enabled the collection of large volumes of data from industrial machinery, providing a rich source of information for Anomaly Detection. However, the volume and complexity of data generated by the Internet of Things ecosystems make it difficult for humans to detect anomalies manually. Machine learning (ML) algorithms can automate anomaly detection in industrial machinery by analyzing generated data. Besides, each technique has specific strengths and weaknesses based on the data nature and its corresponding systems. However, the current systematic mapping studies on Anomaly Detection primarily focus on addressing network and cybersecurity-related problems, with limited attention given to the industrial sector. Additionally, these studies do not cover the challenges involved in using ML for Anomaly Detection in industrial machinery within the context of the IoT ecosystems. This paper presents a systematic mapping study on Anomaly Detection for industrial machinery using IoT devices and ML algorithms to address this gap. The study comprehensively evaluates 84 relevant studies spanning from 2016 to 2023, providing an extensive review of Anomaly Detection research. Our findings identify the most commonly used algorithms, preprocessing techniques, and sensor types. Additionally, this review identifies application areas and points to future challenges and research opportunities

Age effects on EEG correlates of the Wisconsin card sorting test

Body and brain undergo several changes with aging. One of the domains in which these changes are more remarkable relates with cognitive performance. In the present work, electroencephalogram (EEG) markers (power spectral density and spectral coherence) of age-related cognitive decline were sought whilst the subjects performed the Wisconsin Card Sorting Test (WCST). Considering the expected age-related cognitive deficits, WCST was applied to young, mid-age and elderly participants, and the theta and alpha frequency bands were analyzed. From the results herein presented, higher theta and alpha power were found to be associated with a good performance in the WCST of younger subjects. Additionally, higher theta and alpha coherence were also associated with good performance and were shown to decline with age and a decrease in alpha peak frequency seems to be associated with aging. Additionally, inter-hemispheric long-range coherences and parietal theta power were identified as age-independent EEG correlates of cognitive performance. In summary, these data reveals age-dependent as well as age-independent EEG correlates of cognitive performance that contribute to the understanding of brain aging and related cognitive deficits.The work was partially funded by the European Commission (FP7): “SwitchBox” (Contract HEALTH‐F2‐2010‐259772) and co‐financed by the Portuguese North Regional Operational Program (ON.2 – O Novo Norte) under the National Strategic Reference Framework (QREN), through the European Regional Development Fund (FEDER). This work was also co‐sponsored by FCT – Foundation for Science and Technology and Compete Program with the project reference FCOMP‐01‐0124‐FEDER‐021145 (PTDC/SAU‐ENB/118383/2010) and Agência De Inovação “DoIT ‐ Desenvolvimento e Operacionalização da Investigação de Translação” (project no. 13853, PPS4‐MyHealth), funded by Fundo Europeu de Desenvolvimento Regional (FEDER) through the Programa Operacional Factores de Competitividade (POFC)

Prevalence and Severity of Asthma, Rhinitis, and Atopic Eczema in 13- to 14-Year-Old Schoolchildren from Southern Brazil

The objective of this study was to investigate the prevalence and severity of asthma, rhinitis, and atopic eczema in schoolchildren from southern Brazil. A cross-sectional study was carried out with the International Study of Asthma and Allergies in Childhood phase III written questionnaire. The questionnaire was self-applied by 2,948 randomly selected schoolchildren aged 13 to 14 years. The lifetime prevalence rates of symptoms were as follows: wheezing, 40.8%; rhinitis, 40.7%; eczema, 13.6%; self-reported asthma, 14.6%; rhinitis, 31.4%; eczema, 13.4%. Rhinitis was reported by 55% of adolescents with current asthma (60% females vs 46.9% males). Girls 13 to 14 years of age had higher prevalence rates of asthma, rhinitis, and eczema than boys had. Atopic eczema was reported by 42.7% of girls and 31.4% of boys with asthma. The prevalence rates were statistically significant for symptoms of asthma, rhinitis, and atopic eczema in females. However, there were no statistically significant differences between the sexes in regard to reported asthma and bronchospasm induced by exercise

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