Electronic transport across linear defects in graphene

We investigate the low-energy electronic transport across grain boundaries in graphene ribbons and infinite flakes. Using the recursive Green’s function method, we calculate the electronic transmission across different types of grain boundaries in graphene ribbons. We show results for the charge density distribution and the current flow along the ribbon. We study linear defects at various angles with the ribbon direction, as well as overlaps of two monolayer ribbon domains forming a bilayer region. For a class of extended defect lines with periodicity 3, an analytic approach is developed to study transport in infinite flakes. This class of extended grain boundaries is particularly interesting, since the K and K0 Dirac points are superposed.

Paving the way for predictive diagnostics and personalized treatment of invasive aspergillosis

Invasive aspergillosis (IA) is a life-threatening fungal disease commonly diagnosed among individuals with immunological deficits, namely hematological patients undergoing chemotherapy or allogeneic hematopoietic stem cell transplantation. Vaccines are not available, and despite the improved diagnosis and antifungal therapy, the treatment of IA is associated with a poor outcome. Importantly, the risk of infection and its clinical outcome vary significantly even among patients with similar predisposing clinical factors and microbiological exposure. Recent insights into antifungal immunity have further highlighted the complexity of host-fungus interactions and the multiple pathogen-sensing systems activated to control infection. How to decode this information into clinical practice remains however, a challenging issue in medical mycology. Here, we address recent advances in our understanding of the host-fungus interaction and discuss the application of this knowledge in potential strategies with the aim of moving toward personalized diagnostics and treatment (theranostics) in immunocompromised patients. Ultimately, the integration of individual traits into a clinically applicable process to predict the risk and progression of disease, and the efficacy of antifungal prophylaxis and therapy, holds the promise of a pioneering innovation benefiting patients at risk of IA.

Wear of PEEK-Ti6Al4V systems under micro-abrasion and linear sliding conditions

Dissertação de mestrado integrado em Engenharia Biomédica

Desenvolvimento e otimização do projeto mecatrónico para um Tribómetro Linear

Dissertação de mestrado integrado em Engenharia Mecânica

Monovarietal extra-virgin olive oil classification: a fusion of human sensory attributes and an electronic tongue

Olive oil quality grading is traditionally assessed by human sensory evaluation of positive and negative attributes (olfactory, gustatory, and final olfactorygustatory sensations). However, it is not guaranteed that trained panelist can correctly classify monovarietal extra-virgin olive oils according to olive cultivar. In this work, the potential application of human (sensory panelists) and artificial (electronic tongue) sensory evaluation of olive oils was studied aiming to discriminate eight single-cultivar extra-virgin olive oils. Linear discriminant, partial least square discriminant, and sparse partial least square discriminant analyses were evaluated. The best predictive classification was obtained using linear discriminant analysis with simulated annealing selection algorithm. A low-level data fusion approach (18 electronic tongue signals and nine sensory attributes) enabled 100 % leave-one-out cross-validation correct classification, improving the discrimination capability of the individual use of sensor profiles or sensory attributes (70 and 57 % leave-one-out correct classifications, respectively). So, human sensory evaluation and electronic tongue analysis may be used as complementary tools allowing successful monovarietal olive oil discrimination.

Associations, causation and model in psychiatry

This paper discusses models, associations and causation in psychiatry. The different types of association (linear, positive, negative, exponential, partial, U shaped relationship, hidden and spurious) between variables involved in mental disorders are presented as well as the use of multiple regression analysis to disentangle interrelatedness amongst multiple variables. A useful model should have internal consistency, external validity and predictive power; be dynamic in order to accommodate new sound knowledge; and should fit facts rather than they other way around. It is argued that whilst models are theoretical constructs they also convey a style of reasoning and can change clinical practice. Cause and effect are complex phenomena in that the same cause can yield different effects. Conversely, the same effect can have a different range of causes. In mental disorders and human behaviour there is always a chain of events initiated by the indirect and remote cause; followed by intermediate causes; and finally the direct and more immediate cause. Causes of mental disorders are grouped as those: (i) which are necessary and sufficient; (ii) which are necessary but not sufficient; and (iii) which are neither necessary nor sufficient, but when present increase the risk for mental disorders.

A linear algebra approach to OLAP

Inspired by the relational algebra of data processing, this paper addresses the foundations of data analytical processing from a linear algebra perspective. The paper investigates, in particular, how aggregation operations such as cross tabulations and data cubes essential to quantitative analysis of data can be expressed solely in terms of matrix multiplication, transposition and the Khatri–Rao variant of the Kronecker product. The approach offers a basis for deriving an algebraic theory of data consolidation, handling the quantitative as well as qualitative sides of data science in a natural, elegant and typed way. It also shows potential for parallel analytical processing, as the parallelization theory of such matrix operations is well acknowledged.

Aplicação da metodologia ROC na avaliação de desempenho de índices de gravidade clínica em unidades de neonatologia de Portugal

Tese de Doutoramento em Engenharia Industrial e de Sistemas

O efeito da deposição salina nas características das escorrências rodoviárias em zonas costeiras

Tese de Doutoramento em Engenharia Civil.

Promising blood-derived biomarkers for estimation of the postmortem interval

A precise estimation of the postmortem interval (PMI) is one of the most important topics in forensic pathology. However, the PMI estimation is based mainly on the visual observation of cadaverous pheno- mena (e.g. algor, livor and rigor mortis) and on alternative methods such as thanatochemistry that remain relatively imprecise. The aim of this in vitro study was to evaluate the kinetic alterations of several bio- chemical parameters (i.e. proteins, enzymes, substrates, electrolytes and lipids) during putrefaction of human blood. For this purpose, we performed kinetic biochemical analysis during a 264 hour period. The results showed a significant linear correlation between total and direct bilirubin, urea, uric acid, transferrin, immunoglobulin M (IgM), creatine kinase (CK), aspartate transaminase (AST), calcium and iron with the time of blood putrefaction. These parameters allowed us to develop two mathematical models that may have predictive values and become important complementary tools of traditional methods to achieve a more accurate PMI estimation

Predictive value of clinical and electrophysiological variables in patients with chronic chagasic cardiomyopathy and nonsustained ventricular tachycardia

OBJECTIVE: Risk stratification of patients with nonsustained ventricular tachycardia (NSVT) and chronic chagasic cardiomyopathy (CCC). METHODS: Seventy eight patients with CCC and NSVT were consecutively and prospectively studied. All patients underwent to 24-hour Holter monitoring, radioisotopic ventriculography, left ventricular angiography, and electrophysiologic study. With programmed ventricular stimulation. RESULTS: Sustained monomorphic ventricular tachycardia (SMVT) was induced in 25 patients (32%), NSVT in 20 (25.6%) and ventricular fibrillation in 4 (5.1%). In 29 patients (37.2%) no arrhythmia was inducible. During a 55.7-month-follow-up, 22 (28.2%) patients died, 16 due to sudden death, 2 due to nonsudden cardiac death and 4 due to noncardiac death. Logistic regression analysis showed that induction was the independent and main variable that predicted the occurrence of subsequent events and cardiac death (probability of 2.56 and 2.17, respectively). The Mantel-Haenszel chi-square test showed that survival probability was significantly lower in the inducible group than in the noninductible group. The percentage of patients free of events was significantly higher in the noninducible group. CONCLUSION: Induction of SMVT during programmed ventricular stimulation was a predictor of arrhythmia occurrence cardiac death and general mortality in patients with CCC and NSVT.

Arrhythmogenic cardiomyopathy of the right ventricle. Predictive value of QT interval dispersion to assess arrhythmogenic risk and sudden death

OBJECTIVE: To determine in arrhythmogenic right ventricular cardiomyopathy the value of QT interval dispersion for identifying the induction of sustained ventricular tachycardia in the electrophysiological study or the risk of sudden cardiac death. METHODS: We assessed QT interval dispersion in the 12-lead electrocardiogram of 26 patients with arrhythmogenic right ventricular cardiomyopathy. We analyzed its association with sustained ventricular tachycardia and sudden cardiac death, and in 16 controls similar in age and sex. RESULTS: (mean ± SD). QT interval dispersion: patients = 53.8±14.1ms; control group = 35.0±10.6ms, p=0.001. Patients with induction of ventricular tachycardia: 52.5±13.8ms; without induction of ventricular tachycardia: 57.5±12.8ms, p=0.420. In a mean follow-up period of 41±11 months, five sudden cardiac deaths occurred. QT interval dispersion in this group was 62.0±17.8, and in the others it was 51.9±12.8ms, p=0.852. Using a cutoff > or = 60ms to define an increase in the degree of the QT interval dispersion, we were able to identify patients at risk of sudden cardiac death with a sensitivity of 60%, a specificity of 57%, and positive and negative predictive values of 25% and 85%, respectively. CONCLUSION: Patients with arrhythmogenic right ventricular cardiomyopathy have a significant increase in the degree of QT interval dispersion when compared with the healthy population. However it, did not identify patients with induction of ventricular tachycardia in the electrophysiological study, showing a very low predictive value for defining the risk of sudden cardiac death in the population studied.

A cumulative risk model of child physical maltreatment potential: findings from a community-based study

"Published online before print November 20, 2015"

Experimental validation of a proposed single-phase five-level active rectifier operating with model predictive current control

This paper presents a model predictive current control applied to a proposed single-phase five-level active rectifier (FLAR). This current control strategy uses the discrete-time nature of the active rectifier to define its state in each sampling interval. Although the switching frequency is not constant, this current control strategy allows to follow the reference with low total harmonic distortion (THDF). The implementation of the active rectifier that was used to obtain the experimental results is described in detail along the paper, presenting the circuit topology, the principle of operation, the power theory, and the current control strategy. The experimental results confirm the robustness and good performance (with low current THDF and controlled output voltage) of the proposed single-phase FLAR operating with model predictive current control.

Predictive factors of in-hospital mortality and of severe perioperative complications in myocardial revascularization surgery

OBJECTIVE: To investigate preoperative predictive factors of severe perioperative intercurrent events and in-hospital mortality in coronary artery bypass graft (CABG) surgery and to develop specific models of risk prediction for these events, mainly those that can undergo changes in the preoperative period. METHODS: We prospectively studied 453 patients who had undergone CABG. Factors independently associated with the events of interest were determined with multiple logistic regression and Cox proportional hazards regression model. RESULTS: The mortality rate was 11.3% (51/453), and 21.2% of the patients had 1 or more perioperative intercurrent events. In the final model, the following variables remained associated with the risk of intercurrent events: age ³ 70 years, female sex, hospitalization via SUS (Sistema Único de Saúde - the Brazilian public health system), cardiogenic shock, ischemia, and dependence on dialysis. Using multiple logistic regression for in-hospital mortality, the following variables participated in the model of risk prediction: age ³ 70 years, female sex, hospitalization via SUS, diabetes, renal dysfunction, and cardiogenic shock. According to the Cox regression model for death within the 7 days following surgery, the following variables remained associated with mortality: age ³ 70 years, female sex, cardiogenic shock, and hospitalization via SUS. CONCLUSION: The aspects linked to the structure of the Brazilian health system, such as factors of great impact on the results obtained, indicate that the events investigated also depend on factors that do not relate to the patient's intrinsic condition.