Yarn parameterization and fabrics prediction using image processing

This paper presents the main characteristics and functionalities of a system based on image processing techniques applied to quality assessment of yarns. In Textile Industry we used image processing to determine yarn mass parameters as well as yarn production characteristics. A low cost solution based on a web-pc camera plus the optics of a low cost analogue microscope and a software tool based on IMAQ Vision from LabVIEW was designed. Several tests were performed and compared with other methodologies of yarn parameterization validating the proposed solution. With the results one can support that this can be an alternative solution to the traditional yarn testers, with several advantages (among others, low cost, weight, volume, easy maintenance and reduced hardware). Moreover, this yarn parameterization can be used to assess the quality of the fabrics resultant

Automated Ecological Assessment of Physical Activity: Advancing Direct Observation.

Technological advances provide opportunities for automating direct observations of physical activity, which allow for continuous monitoring and feedback. This pilot study evaluated the initial validity of computer vision algorithms for ecological assessment of physical activity. The sample comprised 6630 seconds per camera (three cameras in total) of video capturing up to nine participants engaged in sitting, standing, walking, and jogging in an open outdoor space while wearing accelerometers. Computer vision algorithms were developed to assess the number and proportion of people in sedentary, light, moderate, and vigorous activity, and group-based metabolic equivalents of tasks (MET)-minutes. Means and standard deviations (SD) of bias/difference values, and intraclass correlation coefficients (ICC) assessed the criterion validity compared to accelerometry separately for each camera. The number and proportion of participants sedentary and in moderate-to-vigorous physical activity (MVPA) had small biases (within 20% of the criterion mean) and the ICCs were excellent (0.82-0.98). Total MET-minutes were slightly underestimated by 9.3-17.1% and the ICCs were good (0.68-0.79). The standard deviations of the bias estimates were moderate-to-large relative to the means. The computer vision algorithms appeared to have acceptable sample-level validity (i.e., across a sample of time intervals) and are promising for automated ecological assessment of activity in open outdoor settings, but further development and testing is needed before such tools can be used in a diverse range of settings

Tailoring elastase inhibition with synthetic peptides

Chronic wounds are the result of excessive amounts of tissue destructive proteases such as human neutrophil elastase (HNE). The high levels of this enzyme found on those types of wounds inactivate the endogenous inhibitor barrier thus, the search for new HNE inhibitors is required. This work presents two new HNE inhibitor peptides, which were synthesized based on the reactive-site loop of the Bowman–Birk inhibitor protein. The results obtained indicated that these new peptides are competitive inhibitors for HNE and, the inhibitory activity can be modulated by modifications introduced at the N- and C-terminal of the peptides. Furthermore, these peptides were also able to inhibit elastase from a human wound exudate while showing no cytotoxicity against human skin fibroblasts in vitro, greatly supporting their potential application in chronic wound treatment.We would like to acknowledge FCT - Portuguese Foundation for Science and Technology for the scholarship concession; European project Lidwine, contract no. NMP2-CT-2006-026741

Use of textile fibres in the reinforcement of a gypsum-cork based composite material

The study presented herein focus on the analysis of a series of experimental tests aiming at characterizing the performance of distinct textile fibers acting as a reinforcement of a gypsum-cork composite material. Two groups of textile fibers were selected, namely synthetic fibers (glass and basalt) and natural fibers (banana and sisal). The reinforced composite material was submitted to distinct types of loading, namely compression tests, which it was possible to obtain the compressive strength and to calculate the elastic modulus, and flexural loading Additionally, aiming at assessing the mode I fracture energy, indirect tests on notched beams were carried out

Pigments extraction from Cyanobium sp. a comparison between pressure-based and electric fields-based technologies

Pigments from cyanobacteria, in special carotenoids and phycobiliproteins, have been seen with considerable interest for industrial applications due to their bioactive properties and their natural product characteristics. The extraction of these compounds is focused on the methodologies of cell disruption and on the chemical solubility of the compounds. In this study, two different methods were optimised and evaluated in terms of pigments´ extraction from the marine cyanobacterium Cyanobium sp.: a continuous pressurized solvent extraction (CPSE) system, and an electric fields-assisted extraction system based in ohmic heating (OH). For each method, a Central Composite Design (23) was performed. Optimal conditions for each extraction method were then compared to determine the best method for the extraction of pigments from Cyanobium sp. In both optimisation and comparison steps, two extracts were obtained from the same biomass: an ethanolic extract (carotenoids-targeted) and a successive water extract (phycobiliproteins-targeted). The content and profile of carotenoids and phycobiliproteins and the respective antioxidant capacity of extracts were evaluated. OH provided the best ethanolic extract, with a carotenoids content of 41.6 ± 1.7 mg gDW-1, and total antioxidant capacity of 8.0 ± 0.3 mgTE gDW-1, representing an increase of 1.3-fold and 2.5-fold respectively, when compared to CPSE. Regarding the aqueous extract, both methods led to the same content of phycobiliprotein (135 ± 10.0 mg gDW-1), although OH led to an antioxidant capacity of this extract of 8.3 ± 0.3 mgTE gDW-1, 3.6-fold higher when compared to CPSE. In terms of profile, no major variation was found between extraction methods, being lutein, zeaxanthin, echinenone and -carotene the major carotenoids (>60 % of total carotenoids), and phycocyanin and allophycocyanin the only present phycobiliproteins (in a 1:2 ratio). In addition to the productivity and composition of the extracts, the design and applicability of the system must be considered. Once again, OH overtook the other methods due to the scalability and possible continuous operation. Overall, OH proved to be the best of the two methodologies for pigments co-extraction from Cyanobium sp..A PhD fellowship (reference SFRH/BD/136767/2018) for author Fernando Pagels was granted by Fundação para a Ciência e Tecnologia (FCT, Portugal) under the auspices of Programa Operacional Capital Humano (POCH), supported by the European Social Fund and Portuguese funds (MECTES). This work was financially co-supported by the strategical funding from FCT UIDB/04423/2020, UIDP/04423/2020 and UIDB/04469/2020; and the project ALGAVALOR – MicroALGAs: produção integrada e VALORização da biomassa e das suas diversas aplicações (POCI-01-0247-FEDER-035234), supported by the European Regional Development Fund 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.info:eu-repo/semantics/publishedVersio

Leveraging deep neural networks for automatic and standardised wound image acquisition

Wound monitoring is a time-consuming and error-prone activity performed daily by healthcare professionals. Capturing wound images is crucial in the current clinical practice, though image inadequacy can undermine further assessments. To provide sufficient information for wound analysis, the images should also contain a minimal periwound area. This work proposes an automatic wound image acquisition methodology that exploits deep learning models to guarantee compliance with the mentioned adequacy requirements, using a marker as a metric reference. A RetinaNet model detects the wound and marker regions, further analysed by a post-processing module that validates if both structures are present and verifies that a periwound radius of 4 centimetres is included. This pipeline was integrated into a mobile application that processes the camera frames and automatically acquires the image once the adequacy requirements are met. The detection model achieved [email protected] values of 0.39 and 0.95 for wound and marker detection, exhibiting a robust detection performance for varying acquisition conditions. Mobile tests demonstrated that the application is responsive, requiring 1.4 seconds on average to acquire an image. The robustness of this solution for real-time smartphone-based usage evidences its capability to standardise the acquisition of adequate wound images, providing a powerful tool for healthcare professionals.info:eu-repo/semantics/publishedVersio

Automated High-Frequency Observations of Physical Activity Using Computer Vision.

PurposeTo test the validity of the Ecological Video Identification of Physical Activity (EVIP) computer vision algorithms for automated video-based ecological assessment of physical activity in settings such as parks and schoolyards.MethodsTwenty-seven hours of video were collected from stationary overhead video cameras across 22 visits in nine sites capturing organized activities. Each person in the setting wore an accelerometer, and each second was classified as moderate-to-vigorous physical activity or sedentary/light activity. Data with 57,987 s were used to train and test computer vision algorithms for estimating the total number of people in the video and number of people active (in moderate-to-vigorous physical activity) each second. In the testing data set (38,658 s), video-based System for Observing Play and Recreation in Communities (SOPARC) observations were conducted every 5 min (130 observations). Concordance correlation coefficients (CCC) and mean absolute errors (MAE) assessed agreement between (1) EVIP and ground truth (people counts+accelerometry) and (2) SOPARC observation and ground truth. Site and scene-level correlates of error were investigated.ResultsAgreement between EVIP and ground truth was high for number of people in the scene (CCC = 0.88; MAE = 2.70) and moderate for number of people active (CCC = 0.55; MAE = 2.57). The EVIP error was uncorrelated with camera placement, presence of obstructions or shadows, and setting type. For both number in scene and number active, EVIP outperformed SOPARC observations in estimating ground truth values (CCC were larger by 0.11-0.12 and MAE smaller by 41%-48%).ConclusionsComputer vision algorithms are promising for automated assessment of setting-based physical activity. Such tools would require less manpower than human observation, produce more and potentially more accurate data, and allow for ongoing monitoring and feedback to inform interventions

Compensatory T-Cell Regulation in Unaffected Relatives of SLE Patients, and Opposite IL-2/CD25-Mediated Effects Suggested by Coreferentiality Modeling

In human systemic lupus erythematosus (SLE), diverse autoantibodies accumulate over years before disease manifestation. Unaffected relatives of SLE patients frequently share a sustained production of autoantibodies with indiscriminable specificity, usually without ever acquiring the disease. We studied relations of IgG autoantibody profiles and peripheral blood activated regulatory T-cells (aTregs), represented by CD4+CD25bright T-cells that were regularly 70–90% Foxp3+. We found consistent positive correlations of broad-range as well as specific SLE-associated IgG with aTreg frequencies within unaffected relatives, but not patients or unrelated controls. Our interpretation: unaffected relatives with shared genetic factors compensated pathogenic effects by aTregs engaged in parallel with the individual autoantibody production. To study this further, we applied a novel analytic approach named coreferentiality that tests the indirect relatedness of parameters in respect to multivariate phenotype data. Results show that independently of their direct correlation, aTreg frequencies and specific SLE-associated IgG were likely functionally related in unaffected relatives: they significantly parallelled each other in their relations to broad-range immunoblot autoantibody profiles. In unaffected relatives, we also found coreferential effects of genetic variation in the loci encoding IL-2 and CD25. A model of CD25 functional genetic effects constructed by coreferentiality maximization suggests that IL-2-CD25 interaction, likely stimulating aTregs in unaffected relatives, had an opposed effect in SLE patients, presumably triggering primarily T-effector cells in this group. Coreferentiality modeling as we do it here could also be useful in other contexts, particularly to explore combined functional genetic effects

Abstracts

Resumos, em língua inglesa, dos artigos publicados nesta edição.Resumos, para a língua inglesa, dos artigos publicados nesta edição

Active regulatory T-cells contribute to broadened T-cell repertoire diversity in ivIg-treated SLE patients

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