Produtos têxteis inteligentes incorporando filamentos compósitos com nanotubos de carbono

Programa Doutoral em Engenharia Têxtil.

A novel approach for honey pollen profile assessment using an electronic tongue and chemometric tools

Nowadays the main honey producing countries require accurate labeling of honey before commercialization, including floral classification. Traditionally, this classification is made by melissopalynology analysis, an accurate but time-consuming task requiring laborious sample pre-treatment and high-skilled technicians. In this work the potential use of a potentiometric electronic tongue for pollinic assessment is evaluated, using monofloral and polyfloral honeys. The results showed that after splitting honeys according to color (white, amber and dark), the novel methodology enabled quantifying the relative percentage of the main pollens (Castanea sp., Echium sp., Erica sp., Eucaliptus sp., Lavandula sp., Prunus sp., Rubus sp. and Trifolium sp.). Multiple linear regression models were established for each type of pollen, based on the best sensors sub-sets selected using the simulated annealing algorithm. To minimize the overfitting risk, a repeated K-fold cross-validation procedure was implemented, ensuring that at least 10-20% of the honeys were used for internal validation. With this approach, a minimum average determination coefficient of 0.91 ± 0.15 was obtained. Also, the proposed technique enabled the correct classification of 92% and 100% of monofloral and polyfloral honeys, respectively. The quite satisfactory performance of the novel procedure for quantifying the relative pollen frequency may envisage its applicability for honey labeling and geographical origin identification. Nevertheless, this approach is not a full alternative to the traditional melissopalynologic analysis; it may be seen as a practical complementary tool for preliminary honey floral classification, leaving only problematic cases for pollinic evaluation.

The quantified-Self and wearable technologies in the workplace: implications and challenges for their implementations

Introduction of technologies in the workplace have led to a dramatic change. These changes have come with an increased capacity to gather data about one’s working performance (i.e. productivity), as well as the capacity to track one’s personal responses (i.e. emotional, physiological, etc.) to this changing workplace environment. This movement of self-monitoring or self-sensing using diverse types of wearable sensors combined with the use of computing has been identified as the Quantified-Self. Miniaturization of sensors, reduction in cost and a non-stop increase in the computer power capacity has led to a panacea of wearables and sensors to track and analyze all types of information. Utilized in the personal sphere to track information, a looming question remains, should employers use the information from the Quantified-Self to track their employees’ performance or well-being in the workplace and will this benefit employees? The aim of the present work is to layout the implications and challenges associated with the use of Quantified-Self information in the workplace. The Quantified-Self movement has enabled people to understand their personal life better by tracking multiple information and signals; such an approach could allow companies to gather knowledge on what drives productivity for their business and/or well-being of their employees. A discussion about the implications of this approach will cover 1) Monitoring health and well-being, 2) Oversight and safety, and 3) Mentoring and training. Challenges will address the question of 1) Privacy and Acceptability, 2) Scalability and 3) Creativity. Even though many questions remain regarding their use in the workplace, wearable technologies and Quantified-Self data in the workplace represent an exciting opportunity for the industry and health and safety practitioners who will be using them.

Development of polymer wicks for the fabrication of bio-medical sensors

Polymer based wicking structures were fabricated by sintering powders of polycarbonate (PC), ultra-high molecular weight polyethylene and polyamide 12, aiming at selecting a suitable material for an innovative electroencephalography (EEG) bio-electrode. Preliminary experiments showed that PC based wicks displayed the best mechanical properties, therefore more detailed studies were carried out with PC to evaluate the influence of powder granulometry and processing parameters (pressure, temperature and time) on the mechanical properties, porosity, mean pore radius and permeability of the wicks. It was concluded that the mechanical properties are significantly enhanced by increasing the processing time and pressure, although at the expense of a significant decrease of porosity and mean pore diameter (and thus permeability), particularly for the highest applied pressures (74kPa). However, a good compromise between porosity/permeability and mechanical properties could be obtained by sintering PC powders of particle sizes below 500μm at 165°C for 5min, upon an applied pressure of 56kPa. Moreover, PC proved to be chemically stable in contact with an EEG common used disinfectant. Thus, wicking structures with appropriate properties for the fabrication of reusable bio-electrodes could be fabricated from the sintering of PC powders.

Towards "green" smart materials for force and strain sensors: The case of polyaniline

Stress/strain sensors constitute a class of devices with a global ever-growing market thanks to their use in many fields of modern life. They are typically constituted by thin metal foils deposited on flexible supports. However, the low inherent resistivity and limited flexibility of their constituents make them inadequate for several applications, such as measuring large movements in robotic systems and biological tissues. As an alternative to the traditional compounds, in the present work we will show the advantages to employ a smart material, polyaniline (PANI), prepared by an innovative environmentally friendly route, for force/strain sensor applications wherein simple processing, environmental friendliness and sensitivity are particularly required.

Inkjet printing technology for flexible pressure sensors

Tese de Doutoramento Ciência e Engenharia de Polímeros e Compósitos.

Testing Nelder-Mead based repulsion algorithms for multiple roots of nonlinear systems via a two-level factorial design of experiments

This paper addresses the challenging task of computing multiple roots of a system of nonlinear equations. A repulsion algorithm that invokes the Nelder-Mead (N-M) local search method and uses a penalty-type merit function based on the error function, known as 'erf', is presented. In the N-M algorithm context, different strategies are proposed to enhance the quality of the solutions and improve the overall efficiency. The main goal of this paper is to use a two-level factorial design of experiments to analyze the statistical significance of the observed differences in selected performance criteria produced when testing different strategies in the N-M based repulsion algorithm. The main goal of this paper is to use a two-level factorial design of experiments to analyze the statistical significance of the observed differences in selected performance criteria produced when testing different strategies in the N-M based repulsion algorithm.

Project scheduling and cost minimization with multiple availability constrained resources under stochastic conditions

The authors propose a mathematical model to minimize the project total cost where there are multiple resources constrained by maximum availability. They assume the resources as renewable and the activities can use any subset of resources requiring any quantity from a limited real interval. The stochastic nature is inferred by means of a stochastic work content defined per resource within an activity and following a known distribution and the total cost is the sum of the resource allocation cost with the tardiness cost or earliness bonus in case the project finishes after or before the due date, respectively. The model was computationally implemented relying upon an interchange of two global optimization metaheuristics – the electromagnetism-like mechanism and the evolutionary strategies. Two experiments were conducted testing the implementation to projects with single and multiple resources, and with or without maximum availability constraints. The set of collected results shows good behavior in general and provide a tool to further assist project manager decision making in the planning phase.

Are cognitive interventions for multiple sclerosis effective and feasible?

Purpose: Fifty percent of patients with Multiple Sclerosis (MS) are estimated to have cognitive impairments leading to considerable decline in productivity and quality of life. Cognitive intervention has been considered to complement pharmacological treatments. However, a lack of agreement concerning the efficacy of cognitive interventions in MS still exists. A systematic review and meta-analysis was conducted to assess the effects of cognitive interventions in MS. Methods: To overcome limitations of previous meta-analyses, several databases were searched only for Randomized Clinical Trials (RCTs) with low risk of bias. Results: Five studies (total of 139 participants) met our eligibility criteria. Although good completion and adherence rates were evident, we found no evidence of intervention effects on cognition or mood in post-intervention or follow-up assessments. Conclusions: This is the first meta-analysis assessing the effects of cognitive intervention in MS including only RCTs with comparable conditions. Research regarding efficacy, cost-effectiveness and feasibility is still in its infancy. Caution is advised when interpreting these results due to the small number of RCTs meeting the inclusion criteria. Considering the costs of disease, good completion and adherence rates of this approach, further research is warranted. Recommendations concerning improved research practices in the field are presented as well.

Risk of multiple myeloma is associated with polymorphisms within telomerase genes and telomere length

Compelling biological and epidemiological evidences point to a key role of genetic variants of the TERT and TERC genes in cancer development. We analyzed the genetic variability of these two gene regions using samples of 2,267 multiple myeloma (MM) cases and 2,796 healthy controls. We found that a TERT variant, rs2242652, is associated with reduced MM susceptibility (OR?=?0.81; 95% CI: 0.72-0.92; p?=?0.001). In addition we measured the leukocyte telomere length (LTL) in a subgroup of 140 cases who were chemotherapy-free at the time of blood donation and 468 controls, and found that MM patients had longer telomeres compared to controls (OR?=?1.19; 95% CI: 0.63-2.24; ptrend ?=?0.01 comparing the quartile with the longest LTL versus the shortest LTL). Our data suggest the hypothesis of decreased disease risk by genetic variants that reduce the efficiency of the telomerase complex. This reduced efficiency leads to shorter telomere ends, which in turn may also be a marker of decreased MM risk.

Characterization of the oculomotor alterations in inicial phase of Multiple Sclerosis

Dissertação de mestrado em Advanced Optometry

Single line for assembly just-in-sequence multiple models

Programa Doutoral em Líderes para as Indústrias Tecnológicas

Cognitive functioning and efficacy of cognitive intervention in Multiple Sclerosis

Tese de Doutoramento em Psicologia Clínica / Psicologia

Type 2 diabetes-related variants influence the risk of developing multiple myeloma: results from the IMMEnSE consortium

Type 2 diabetes (T2D) has been suggested to be a risk factor for multiple myeloma (MM), but the relationship between the two traits is still not well understood. The aims of this study were to evaluate whether 58 genome-wide-association-studies (GWAS)-identified common variants for T2D influence the risk of developing MM and to determine whether predictive models built with these variants might help to predict the disease risk. We conducted a case–control study including 1420 MM patients and 1858 controls ascertained through the International Multiple Myeloma (IMMEnSE) consortium. Subjects carrying the KCNQ1rs2237892T allele or the CDKN2A-2Brs2383208G/G, IGF1rs35767T/T and MADDrs7944584T/T genotypes had a significantly increased risk of MM (odds ratio (OR)=1.32–2.13) whereas those carrying the KCNJ11rs5215C, KCNJ11rs5219T and THADArs7578597C alleles or the FTOrs8050136A/A and LTArs1041981C/C genotypes showed a significantly decreased risk of developing the disease (OR=0.76–0.85). Interestingly, a prediction model including those T2D-related variants associated with the risk of MM showed a significantly improved discriminatory ability to predict the disease when compared to a model without genetic information (area under the curve (AUC)=0.645 vs AUC=0.629; P=4.05×10-06). A gender-stratified analysis also revealed a significant gender effect modification for ADAM30rs2641348 and NOTCH2rs10923931 variants (Pinteraction=0.001 and 0.0004, respectively). Men carrying the ADAM30rs2641348C and NOTCH2rs10923931T alleles had a significantly decreased risk of MM whereas an opposite but not significant effect was observed in women (ORM=0.71 and ORM=0.66 vs ORW=1.22 and ORW=1.15, respectively). These results suggest that TD2-related variants may influence the risk of developing MM and their genotyping might help to improve MM risk prediction models.

Patterned CNT-PDMS nanocomposites for flexible pressure sensors

This paper reports the fabrication process and characterization of a flexible pressure sensor based on polydimethylsiloxane (PDMS) and multi-walled carbon nanotubes (CNT-PDMS). The proposed approach relies on patterned CNT-PDMS nanocomposite strain gauges fabricated with SU-8 microstructures (with the micropatterns) in a low‑cost and simple fabrication process. This nanocomposite polymer is mounted over a PDMS membrane, which, in turn, lies on top of a PDMS diaphragm like structure. This configuration enables the PDMS membrane to bend when pressure is applied, thereby affecting the nanocomposite strain gauges, effectively changing their electrical resistance. Carbon nanotubes have several advantages such as excellent mechanical properties, high electrical conductivity and thermal stability. Furthermore, the measurement range of the proposed sensor can be adapted according to the application by varying the CNTs content and geometry of microstructure. In addition, the sensor’s biocompatibility, low cost and simple fabrication makes it very appealing for biomechanical strain sensing. The sensor’s sensitivity was about 0.073%ΔR/mmHg.