Distribution of fish species in a lake of the Amazon river floodplain near Manaus (Lago Camaleão), with special reference to extreme oxygen conditions

Over a period of 20 months the fish fauna distribution at Lago Camalcão, a floodplain lake of the Amazon near Manaus was studied. Special attention was given to the oxygen conditions. The lake was strongly defficient in oxygen for long periods, the surface oxygen concentrations during the day often being only about 0,5 g O2/l. Approximately 25.000 specimens were captured; 132 species belonging to 94 genera, 31 families and 10 orders were identified. About 40 species were able to live under extlemely low oxygen concentrations. 12 of these were air breathers. Another 8 are known to possess other morphological, anatomical and/or physiological adaptations to oxygen deficiency. It is presumed that the other species occurring in the area may have adaptations too. Survival strategies in respect to oxygen deficiency are discussed. It is suggested that the colonization of strongly oxygen deficient habitats reduces interspecific competition for food and diminishes predation pressure on the fish community, the total number of predatory fish species and specimens being much lower under low oxygen concentrations

Improving feeding efficiency of a sewing machine by on-line control of the presser foot

This paper presents a contribution towards the development of a new generation of sewing equipment integrating auxiliary add-on kits to improve performance and flexibility in the production of high-quality garments. An overview of all the recent developments concerning the redesign of the first PC-based controller developed for a novel electromagnetically actuated presser foot on an industrial overlock sewing machine will be presented. Other software modules, developed to ease the establishment of control references and the tuning of the controller parameters, as well as a brief discussion and analysis of the obtained results, will also be described in this paper. According to the latest results here reported, the presser foot firmly controls the fabric plies for a wide range of materials and situations

A comparison of mass parameters determination using capacitive and optical sensors

AbstractThis paper presents a comparison study between the use of 1mm resolution capacitive and optical sensors for the determination of yarn mass parameters. A parallel plate capacitive sensor to determine yarn mass variations and a yarn diameter and hairiness determination solution using optical sensors and integrating optical signal processing based on Fourier analysis are described. As there is a high correlation between yarn diameter and yarn mass, it is possible to determine yarn mass and infer variations in yarn diameter and vice-versa. Moreover, by optically detecting the degree of yarn hairiness, one can quantify its influence on the capacitive sensor mass variation measurements. Here we present the results of a signal processing analysis and statistical description of measurements carried out on a 100% cotton 295 g/km linear mass yarn. We conclude that an accurate yarn characterization can be carried out using optical sensors alone, reducing systems cost, complexity and increasing efficiency

Adaptive control of an electromagnetically actuated presser-foot for industrial sewing machines

This study describes some possibilities of setting up an adaptive control method for an electromagnetically actuated presser-foot in an industrial high-speed sewing machine. The control of fabrics feeding in sewing machines is difficult not only because of the complexity of relations between the intervening variables (material properties, sewing speed), but also because in many operations a varying number of material plies are crossed. This implies that the reference for the controller has to be adapted dynamically. Several methods, using PID and/or fuzzy logic control, have been tried and are described in this paper. A preliminary sewing test is able to provide data to tune the controller variables. With these adaptation techniques, the machine would be able to automatically adapt its feeding system according to the material being sewn.Fundação para a Ciência e a Tecnologia (FCT

Fuzzy logic based control strategies for an electromagnetic actuated sewing machine presser foot

Comunicação apresentada na International Conference on Industrial Technology, Hammamet, Tunisia, 8 - 10 Dezembro 2004.Industrial sewing machines have been significantly improved in recent years and especially electronic sewing control is now being introduced. This study concerns the development of a controller for an electromagnetically actuated presser foot. The controller is responsible for controlling the vertical movement of the presser foot. This is an important point since the presser foot tends to bounce at high sewing speeds, resulting in irregular seams. In this study a fuzzy logic controller was used. The reference displacement value is set up by an adaptive method in order to respect changes on the number of plies. The tested fuzzy logic controller allows a better performance of the control especially in relation with different fabrics. During this study another control strategy was considered. This control strategy combines a PI-algorithm with a fuzzy logic controller. Yet, the controller restricts the use of new fabrics, which have not been defined in advance. This aspect will be a major point in the future development in order to recognize the fabrics during sewing and to adapt the controller adequately.(undefined

EFFECTIVENESS OF OMALIZUMAB IN THE TREATMENT OF CHRONIC RHINOSINUSITIS WITH NASAL POLYPS: SYSTEMATIC REVIEW

BACKGROUND: Omalizumab is a monoclonal anti-IgE antibody which reduces serum and tissue IgE levels blocking the inflammatory cascade. To date this drug has authorization for treatment of moderate-to-severe allergic asthma. The chronic rhinosinusitis with Nasal Polyps (CRSwNP) is a chronic inflammatory disease whose exact pathogenesis remains unknown. In most Caucasian patients CRS is associated with eosinophilic inflammation and local production of IgE. The aim of this systematic review was to evaluate the existing evidence on the use of omalizumab in CRSwNP. MATERIALS AND METHODS: Searches were carried out in Medline, Scopus and Cochrane Library, followed by a detailed handsearch. The search was conducted from January 1990 to December 2013. Prospective and retrospective studies were included. RESULTS: Four studies met the inclusion criteria for this systematic review: two randomized controlled trials, a retrospective case-control study and a case series. Omalizumab appears to improve both endoscopic evaluation and sinonasal inflammation, with an acceptable safety profile. However, the evidence level is low. CONCLUSIONS: The evidence shows that the use of omalizumab may be an effective therapeutic alternative in CRSwNP, especially in patients with more aggressive forms of the disease, with surgical procedures history, and bronchial asthma. However, more randomized, placebo-controlled, double-blind studies with higher number of patients are still needed to determine the efficacy of anti-IgE treatment in CRSwNP

Learning prognostic models using a mixture of biclustering and triclustering: predicting the need for non-invasive ventilation in amyotrophic lateral sclerosis

© 2022 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)Longitudinal cohort studies to study disease progression generally combine temporal features produced under periodic assessments (clinical follow-up) with static features associated with single-time assessments, genetic, psychophysiological, and demographic profiles. Subspace clustering, including biclustering and triclustering stances, enables the discovery of local and discriminative patterns from such multidimensional cohort data. These patterns, highly interpretable, are relevant to identifying groups of patients with similar traits or progression patterns. Despite their potential, their use for improving predictive tasks in clinical domains remains unexplored. In this work, we propose to learn predictive models from static and temporal data using discriminative patterns, obtained via biclustering and triclustering, as features within a state-of-the-art classifier, thus enhancing model interpretation. triCluster is extended to find time-contiguous triclusters in temporal data (temporal patterns) and a biclustering algorithm to discover coherent patterns in static data. The transformed data space, composed of bicluster and tricluster features, capture local and cross-variable associations with discriminative power, yielding unique statistical properties of interest. As a case study, we applied our methodology to follow-up data from Portuguese patients with Amyotrophic Lateral Sclerosis (ALS) to predict the need for non-invasive ventilation (NIV) since the last appointment. The results showed that, in general, our methodology outperformed baseline results using the original features. Furthermore, the bicluster/tricluster-based patterns used by the classifier can be used by clinicians to understand the models by highlighting relevant prognostic patterns.This work was partially supported by Fundação para a Ciência e a Tecnologia (FCT), Portugal, the Portuguese public agency for science, technology and innovation, funding to projects AIpALS (PTDC/CCI-CIF/4613/2020), LASIGE (UIDB/ 00408/2020 and UIDP/00408/2020) and INESC-ID (UIDB/ 50021/2020) Research Units, and PhD research scholarship (2020.05100.BD) to DFS; and by the BRAINTEASER project which has received funding from the European Union’s Horizon 2020 research and innovation programme, under the grant agreement No 101017598.info:eu-repo/semantics/publishedVersio