Associations between energetic expenditure, physical activity and body composition: exploratory study with industrial workers

This study, which involved a target population comprised by 292 workers of different industrial areas (metalmechanics, foundry, chemical, wood, food), aimed to verify the association between energy expenditure-EE, physical activity level-PAL and body composition (Body Mass Index-BMI, Waist-Hip Ratio-WHR and Waist To Height Ratio, WTHR) of participants. The work was completed with the description of the variables relating to the gender of the individuals (male and female) and the activities carried out in the two sectors of industrial work (administrative sector and productive sector). In this research, the statistical technique of principal components analysis (PCA) and the hierarchical analysis of clusters (HCA) were used. Sociodemographic and anthropometric data were collected as well as the level of physical activity and energy expenditure were assessed. The vast majority of individuals who spend greater energy expenditure and has more intense physical activity were male. Most of these workers are in the production sector. We can confirm that that both, gender and labor activity, are factors that have influence on the EE and the PAL.

Conceptual-physical bridging – From BPMN models to physical implementations on kettle

Developing and implementing data-oriented workflows for data migration processes are complex tasks involving several problems related to the integration of data coming from different schemas. Usually, they involve very specific requirements - every process is almost unique. Having a way to abstract their representation will help us to better understand and validate them with business users, which is a crucial step for requirements validation. In this demo we present an approach that provides a way to enrich incrementally conceptual models in order to support an automatic way for producing their correspondent physical implementation. In this demo we will show how B2K (Business to Kettle) system works transforming BPMN 2.0 conceptual models into Kettle data-integration executable processes, approaching the most relevant aspects related to model design and enrichment, model to system transformation, and system execution.

Automatic generation of ETL physical systems from BPMN conceptual models

ETL conceptual modeling is a very important activity in any data warehousing system project implementation. Owning a high-level system representation allowing for a clear identification of the main parts of a data warehousing system is clearly a great advantage, especially in early stages of design and development. However, the effort to model conceptually an ETL system rarely is properly rewarded. Translating ETL conceptual models directly into something that saves work and time on the concrete implementation of the system process it would be, in fact, a great help. In this paper we present and discuss a hybrid approach to this problem, combining the simplicity of interpretation and power of expression of BPMN on ETL systems conceptualization with the use of ETL patterns to produce automatically an ETL skeleton, a first prototype system, which has the ability to be executed in a commercial ETL tool like Kettle.

Advances in microbial diagnosis: using mass spectrometry for proteomics and genomics applications

Since the last two decades mass spectrometry (MS) has been applied to analyse the chemical cellular components of microorganisms, providing rapid and discriminatory proteomic profiles for their species identification and, in some cases, subtyping. The application of MS for the microbial diagnosis is currently well-established. The remarkable reproducibility and objectivity of this method is based on the measurement of constantly expressed and highly abundant proteins, mainly important conservative ribosomal proteins, which are used as markers to generate a cellular fingerprint. Mass spectrometry based on matrix-assisted laser desorption ionization-time of flight (MALDI- TOF) technique has been an important tool for the microbial diagnostic. However, some technical limitation concerning both MALDI-TOF and its used protocols for sample preparation have fostered the research of new mass spectrometry systems (e.g. LC MS/MS). LC MS/MS is able to generate online mass spectra of specific ions with further online sequencing of these ions, which include both specific proteins and DNA fragments. In this work a set of data for yeasts and filamentous fungi diagnostic obtained through an international collaboration project involving partners from Argentina, Brazil, Chile and Portugal will be presented and discussed.

Synthesis, physical and magnetic properties of BaFe12O19/P(VDF-TrFE) multifunctional composites

Composite films with filler microparticles of Barium ferrite dispersed within P(VDF-TrFE) as polymeric matrix have been prepared by solvent evaporation. The lowest BaFO content of 1% wt acts as a small defect within the polymeric matrix, reducing the values of the dielectric and mechanical properties of the pure P(VDF-TrFE). For filler contents up to a 20%, the BaFO filler reinforces the matrix and measured properties increase their values. This trend is not followed by the electrical conductivity. We extended the study to fibers composed by BaFe12O19 microparticles in a PVDF matrix. Due to the big size of BaFO particles (1 micron in diameter), proper fabrication of the fiber shaped composites has not been achieved. We found that true BaFO content are always lower than nominal ones. Results are discussed in terms of the influence of size and morphology of the BaFO particles on the initial properties of the polymeric matrix.

Modeling separator membranes physical characteristics for optimized lithium ion battery performance

The effect of varying separator membrane physical parameters such as degree of porosity, tortuosity and thickness, on battery delivered capacity was studied in order to optimize performance of lithium-ion batteries. This was achieved by a theoretical mathematical model relating the Bruggeman coefficient with the degree of porosity and tortuosity. The inclusion of the separator membrane in the simulation model of the battery system does not affect the delivered capacity of the battery. The ionic conductivity of the separator and consequently the delivered capacity values obtained at different discharge rates depends on the value of the Bruggeman coefficient, which is related with the degree of porosity and tortuosity of the membrane. Independently of scan rate, the optimal value of the degree of porosity is above 50% and the separator thickness should range between 1 μm at 32 μm for improved battery performance.

Tailoring microstructure and physical properties of poly(vinylidene fluoride–hexafluoropropylene) porous films

This paper presents a systematic study for the production of poly(vinylidene fluoride-hexafluoropropylene), P(VDF-HFP), porous films using solvent evaporation (SE) and non-solvent induced phase separation (NIPS) techniques. Parameters such as volume fraction of the copolymer solution, film thickness, time exposure to air, non-solvent and temperature of the coagulation bath were investigated on the morphology, crystallization and mechanical properties of the samples. Films with different porous morphologies including homogeneous pore sizes, macrovoids and spherulites were obtained depending on the processing conditions, which in turn affect the wettability and mechanical properties of the material. Knowing that the phase content of the films also depends on the processing conditions, this paper shows that P(VDF-HFP) films with tailored porous morphology, electroactive phase content, hydrophobicity, cristallinity and mechanical properties can be achieved for a specific application using the adequate SE and NIPS techniques conditions.

Poly(vinylidene fluoride-trifluoroethylene) porous films: tailoring microstructure and physical properties by solvent casting strategies

A systematic study for the production of porous poly(vinylidene fluoride-trifluoroethylene), P(VDF-TrFE), films using solvent evaporation and non-solvent induced phase separation techniques is presented. Processing parameters such as copolymer volume fraction, solvent, preset exposure time to air before immersion, and non-solvent and temperature of the coagulation bath were varied and the corresponding sample morphology, hydrophobicity, thermal and mechanical properties were determined. Film morphologies including homogeneous pore distributions, micropores, microvoids, spherulites and non-porous films were obtained. The morphology variations strongly influence sample hydrophobicity and mechanical properties. All samples crystallize in the electroactive β-phase with a degree of crystallinity around 30 %.

Characterization of physical, mechanical and chemical properties of quiscal fibres : the influence of atmospheric DBD plasma treatment

This paper reports the first attempt of characterizing various physical, mechanical and chemical properties of Quiscal fibres, used by the native communities in Chile and investigating the influence of atmospheric dielectric barrier discharge plasma treatment on various properties such as diameter and linear density, fat, wax and impurity%, moisture regain, chemical elements and groups, thermal degradation, surface morphology, etc. According to the experimental observations, Quiscal fibre has lower tenacity than most of the technical grade natural fibres such as sisal, hemp, flax, etc., and plasma treatment at optimum dose improved its tenacity to the level of sisal fibres. Plasma treatment also reduced the amount of fat, wax and other foreign impurities present in Quiscal fibres as well as removed lignin and hemicellulose partially from the fibre structure. Plasma treatment led to functionalization of Quiscal fibre surface with chemical groups, as revealed from attenuated total reflection spectroscopy and also confirmed from the elemental analysis using energy dispersive Xray technique and pH and conductivity measurements of fibre aqueous extract. The wetting behavior of Quiscal fibre also improved considerably through plasma treatment. However, untreated and plasma treated Quiscal fibres showed similar thermal degradation behavior, except the final degradation stage, in which plasma treated fibres showed higher stability and incomplete degradation unlike the untreated fibres. The experimental results suggested that the plasma treated Quiscal fibres, like other technical grade natural fibres, can find potential application as reinforcement of composite materials for various industrial applications.

A soft computing approach to kidney diseases evaluation

Kidney renal failure means that one’s kidney have unexpectedly stopped functioning, i.e., once chronic disease is exposed, the presence or degree of kidney dysfunction and its progression must be assessed, and the underlying syndrome has to be diagnosed. Although the patient’s history and physical examination may denote good practice, some key information has to be obtained from valuation of the glomerular filtration rate, and the analysis of serum biomarkers. Indeed, chronic kidney sickness depicts anomalous kidney function and/or its makeup, i.e., there is evidence that treatment may avoid or delay its progression, either by reducing and prevent the development of some associated complications, namely hypertension, obesity, diabetes mellitus, and cardiovascular complications. Acute kidney injury appears abruptly, with a rapid deterioration of the renal function, but is often reversible if it is recognized early and treated promptly. In both situations, i.e., acute kidney injury and chronic kidney disease, an early intervention can significantly improve the prognosis.The assessment of these pathologies is therefore mandatory, although it is hard to do it with traditional methodologies and existing tools for problem solving. Hence, in this work, we will focus on the development of a hybrid decision support system, in terms of its knowledge representation and reasoning procedures based on Logic Programming, that will allow one to consider incomplete, unknown, and even contradictory information, complemented with an approach to computing centered on Artificial Neural Networks, in order to weigh the Degree-of-Confidence that one has on such a happening. The present study involved 558 patients with an age average of 51.7 years and the chronic kidney disease was observed in 175 cases. The dataset comprise twenty four variables, grouped into five main categories. The proposed model showed a good performance in the diagnosis of chronic kidney disease, since the sensitivity and the specificity exhibited values range between 93.1 and 94.9 and 91.9–94.2 %, respectively.

An assessment of chronic kidney diseases

Kidney renal failure means that one’s kidney have unexpectedlystoppedfunctioning,i.e.,oncechronicdiseaseis exposed, the presence or degree of kidney dysfunction and its progression must be assessed, and the underlying syndrome has to be diagnosed. Although the patient’s history and physical examination may denote good practice, some key information has to be obtained from valuation of the glomerular filtration rate, and the analysis of serum biomarkers. Indeed, chronic kidney sickness depicts anomalous kidney function and/or its makeup, i.e., there is evidence that treatment may avoid or delay its progression, either by reducing and prevent the development of some associated complications, namely hypertension, obesity, diabetes mellitus, and cardiovascular complications. Acute kidney injury appears abruptly, with a rapiddeteriorationoftherenalfunction,butisoftenreversible if it is recognized early and treated promptly. In both situations, i.e., acute kidney injury and chronic kidney disease, an early intervention can significantly improve the prognosis. The assessment of these pathologies is therefore mandatory, although it is hard to do it with traditional methodologies and existing tools for problem solving. Hence, in this work, we will focus on the development of a hybrid decision support system, in terms of its knowledge representation and reasoning procedures based on Logic Programming, that will allow onetoconsiderincomplete,unknown,and evencontradictory information, complemented with an approach to computing centered on Artificial Neural Networks, in order to weigh the Degree-of-Confidence that one has on such a happening. The present study involved 558 patients with an age average of 51.7 years and the chronic kidney disease was observed in 175 cases. The dataset comprise twenty four variables, grouped into five main categories. The proposed model showed a good performance in the diagnosis of chronic kidney disease, since the sensitivity and the specificity exhibited values range between 93.1 and 94.9 and 91.9–94.2 %, respectively.

Artificial neural networks in diagnosis of liver diseases

Liver diseases have severe patients’ consequences, being one of the main causes of premature death. These facts reveal the centrality of one`s daily habits, and how important it is the early diagnosis of these kind of illnesses, not only to the patients themselves, but also to the society in general. Therefore, this work will focus on the development of a diagnosis support system to these kind of maladies, built under a formal framework based on Logic Programming, in terms of its knowledge representation and reasoning procedures, complemented with an approach to computing grounded on Artificial Neural Networks.

Biochemical and physical surface functionalization of polycaprolactone as a key mediator of osteogenic differentiation and vascularized tissue morphogenesis

Tese de Doutoramento em Engenharia de Tecidos, Medicina Regenerativa e Células Estaminais.

Clinical Epidemiology of Buruli ulcer from Benin (2005-2013): effect of time-delay to diagnosis on clinical forms and severe phenotypes

Buruli Ulcer (BU) is a neglected infectious disease caused by Mycobacterium ulcerans that is responsible for severe necrotizing cutaneous lesions that may be associated with bone involvement. Clinical presentations of BU lesions are classically classified as papules, nodules, plaques and edematous infiltration, ulcer or osteomyelitis. Within these different clinical forms, lesions can be further classified as severe forms based on focality (multiple lesions), lesions' size (>15 cm diameter) or WHO Category (WHO Category 3 lesions). There are studies reporting an association between delay in seeking medical care and the development of ulcerative forms of BU or osteomyelitis, but the effect of time-delay on the emergence of lesions classified as severe has not been addressed. To address both issues, and in a cohort of laboratory-confirmed BU cases, 476 patients from a medical center in Allada, Benin, were studied. In this laboratory-confirmed cohort, we validated previous observations, demonstrating that time-delay is statistically related to the clinical form of BU. Indeed, for non-ulcerated forms (nodule, edema, and plaque) the median time-delay was 32.5 days (IQR 30.0-67.5), while for ulcerated forms it was 60 days (IQR 20.0-120.0) (p = 0.009), and for bone lesions, 365 days (IQR 228.0-548.0). On the other hand, we show here that time-delay is not associated with the more severe phenotypes of BU, such as multi-focal lesions (median 90 days; IQR 56-217.5; p = 0.09), larger lesions (diameter >15 cm) (median 60 days; IQR 30-120; p = 0.92) or category 3 WHO classification (median 60 days; IQR 30-150; p = 0.20), when compared with unifocal (median 60 days; IQR 30-90), small lesions (diameter =15 cm) (median 60 days; IQR 30-90), or WHO category 1+2 lesions (median 60 days; IQR 30-90), respectively. Our results demonstrate that after an initial period of progression towards ulceration or bone involvement, BU lesions become stable regarding size and focal/multi-focal progression. Therefore, in future studies on BU epidemiology, severe clinical forms should be systematically considered as distinct phenotypes of the same disease and thus subjected to specific risk factor investigation.

Evaluation of the morphological and physical characteristics of plumes from chicken feathers

This work presents a study on the properties of chicken plumes from the poultry industry, namely feathers. Studies conducted include length, diameter and weight of chicken feathers to 42 days old. Initial results indicate that the central and lower feather areas present very interesting properties and characteristics turning these materials suitable for various applications, including in clothing, thermal and acoustic insulation in buildings, cimenticious and polymeric matrices reinforcements, among others.