11,493 research outputs found
On the Efficiency of Data Representation on the Modeling and Characterization of Complex Networks
Specific choices about how to represent complex networks can have a
substantial effect on the execution time required for the respective
construction and analysis of those structures. In this work we report a
comparison of the effects of representing complex networks statically as
matrices or dynamically as spase structures. Three theoretical models of
complex networks are considered: two types of Erdos-Renyi as well as the
Barabasi-Albert model. We investigated the effect of the different
representations with respect to the construction and measurement of several
topological properties (i.e. degree, clustering coefficient, shortest path
length, and betweenness centrality). We found that different forms of
representation generally have a substantial effect on the execution time, with
the sparse representation frequently resulting in remarkably superior
performance
Emulsion formation and stabilization by biomolecules: the leading role of cellulose
Emulsion stabilization by native cellulose has been mainly hampered because of its insolubility in water. Chemical modification is normally needed to obtain water-soluble cellulose derivatives. These modified celluloses have been widely used for a range of applications by the food, cosmetic, pharmaceutic, paint and construction industries. In most cases, the modified celluloses are used as rheology modifiers (thickeners) or as emulsifying agents. In the last decade, the structural features of cellulose have been revisited, with particular focus on its structural anisotropy (amphiphilicity) and the molecular interactions leading to its resistance to dissolution. The amphiphilic behavior of native cellulose is evidenced by its capacity to adsorb at the interface between oil and aqueous solvent solutions, thus being capable of stabilizing emulsions. In this overview, the fundamentals of emulsion formation and stabilization by biomolecules are briefly revisited before different aspects around the emerging role of cellulose as emulsion stabilizer are addressed in detail. Particular focus is given to systems stabilized by native cellulose, either molecularly-dissolved or not (Pickering-like effect).Financially support by the Portuguese Foundation for Science and Technology, FCT, via the projects PTDC/AGR-TEC/4814/2014, PTDC/ASP-SIL/30619/2017 and researcher grant IF/01005/2014. RISE Research Institutes of Sweden AB and PERFORM, a competence platform in Formulation Science at RISE, are acknowledged for additional financing. This research has been supported by
Treesearch.se.info:eu-repo/semantics/publishedVersio
Environmental Changes and the Geographic Spreading of American Cutaneous Leishmaniasis in Brazil
A systematic comparison of supervised classifiers
Pattern recognition techniques have been employed in a myriad of industrial,
medical, commercial and academic applications. To tackle such a diversity of
data, many techniques have been devised. However, despite the long tradition of
pattern recognition research, there is no technique that yields the best
classification in all scenarios. Therefore, the consideration of as many as
possible techniques presents itself as an fundamental practice in applications
aiming at high accuracy. Typical works comparing methods either emphasize the
performance of a given algorithm in validation tests or systematically compare
various algorithms, assuming that the practical use of these methods is done by
experts. In many occasions, however, researchers have to deal with their
practical classification tasks without an in-depth knowledge about the
underlying mechanisms behind parameters. Actually, the adequate choice of
classifiers and parameters alike in such practical circumstances constitutes a
long-standing problem and is the subject of the current paper. We carried out a
study on the performance of nine well-known classifiers implemented by the Weka
framework and compared the dependence of the accuracy with their configuration
parameter configurations. The analysis of performance with default parameters
revealed that the k-nearest neighbors method exceeds by a large margin the
other methods when high dimensional datasets are considered. When other
configuration of parameters were allowed, we found that it is possible to
improve the quality of SVM in more than 20% even if parameters are set
randomly. Taken together, the investigation conducted in this paper suggests
that, apart from the SVM implementation, Weka's default configuration of
parameters provides an performance close the one achieved with the optimal
configuration
Hierarchical Spatial Organization of Geographical Networks
In this work we propose the use of a hirarchical extension of the
polygonality index as a means to characterize and model geographical networks:
each node is associated with the spatial position of the nodes, while the edges
of the network are defined by progressive connectivity adjacencies. Through the
analysis of such networks, while relating its topological and geometrical
properties, it is possible to obtain important indications about the
development dynamics of the networks under analysis. The potential of the
methodology is illustrated with respect to synthetic geographical networks.Comment: 3 page, 3 figures. A wokring manuscript: suggestions welcome
Validation of a wireless bluetooth photoplethysmography sensor used on the earlobe for monitoring heart rate variability features during a stress-inducing mental task in healthy individuals
Heart rate variability (HRV), using electrocardiography (ECG), has gained popularity as a biomarker of the stress response. Alternatives to HRV monitoring, like photoplethysmography (PPG), are being explored as cheaper and unobtrusive non-invasive technologies. We report a new wireless PPG sensor that was tested in detecting changes in HRV, elicited by a mentally stressful task, and to determine if its signal can be used as a surrogate of ECG for HRV analysis. Data were collected simultaneously from volunteers using a PPG and ECG sensor, during a resting and a mentally stressful task. HRV metrics were extracted from these signals and compared to determine the agreement between them and to determine if any changes occurred in the metrics due to the stressful task. For both tasks, a moderate/good agreement was found in the mean interbeat intervals, SDNN, LF, and SD2, and a poor agreement for the pNN50, RMSSD|SD1, and HF metrics. The majority of the tested HRV metrics obtained from the PPG signal showed a significant decrease caused by the mental task. The disagreement found between specific HRV features imposes caution when comparing metrics from different technologies. Nevertheless, the tested sensor was successful at detecting changes in the HRV caused by a mental stressor.This work has been funded by National funds, through the Foundation for Science and Technology (FCT) - project UIDB/50026/2020 and UIDP/50026/2020; and by the projects NORTE-01-0145-FEDER-000013 and NORTE-01-0145-FEDER-000023, supported by Norte Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF). Bruno Correia was supported by a four-year Ph. D. grant from FCT, with the reference PD/BDE/135569/2018
Glioblastoma: is there any blood biomarker with true clinical relevance?
Glioblastoma (GBM) is the most frequent malignant primary brain tumor in adults, characterized by a highly aggressive, inflammatory and angiogenic phenotype. It is a remarkably heterogeneous tumor at several levels, including histopathologically, radiographically and genetically. The 2016 update of the WHO Classification of Tumours of the Central Nervous System highlighted molecular parameters as paramount features for the diagnosis, namely IDH1/2 mutations that distinguish primary and secondary GBM. An ideal biomarker is a molecule that can be detected/quantified through simple non- or minimally invasive methods with the potential to assess cancer risk; promote early diagnosis; increase grading accuracy; and monitor disease evolution and treatment response, as well as fundamentally being restricted to one aspect. Blood-based biomarkers are particularly attractive due to their easy access and have been widely used for various cancer types. A number of serum biomarkers with multiple utilities for glioma have been reported that could classify glioma grades more precisely and provide prognostic value among these patients. At present, screening for gliomas has no clinical relevance. This is because of the low incidence, the lack of sensitive biomarkers in plasma, and the observation that gliomas may develop apparently de novo within few weeks or months. To the best of our knowledge, there is no routine use of a serum biomarker for clinical follow-up. The purpose of this paper is to review the serum biomarkers described in the literature related to glioblastoma and their possible relationship with clinical features
Influence of sociological aspects on the level of physical activity in physical education students
Adopting and maintaining an active lifestyle for adolescent students, seems to be impaired and influenced by several factors, among them stand out environmental, psychological and social factors. Thus, the general objectives of this study were submitted to study and understand the extent to which these environmental, social and personal factors help and influence the level of physical activity (PA) by the adolescents in school age. More specifically, we will study: (1) the possible association between level of physical activity, age and gender; (2) consider and determine whether there is an association between socioeconomic variables and physical activity level of the population sample; (3) assess on the possible association between environmental variables and perceived physical activity of the adolescents. The sample consisted of 286 high school students, male gender (n = 125) and female (n = 161) aged between 15 and 18 years of age. As an instrument of study, a questionnaire was used. The main results of this study demonstrate a possible relationship between gender and level of PA, while boys tend to be more active than girls and also an association between socioeconomic variables and level of physical activity
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