Multiple Linear Regression and Artificial Neural Networks to Predict Time and Efficiency of Soil Vapor Extraction

The prediction of the time and the efficiency of the remediation of contaminated soils using soil vapor extraction remain a difficult challenge to the scientific community and consultants. This work reports the development of multiple linear regression and artificial neural network models to predict the remediation time and efficiency of soil vapor extractions performed in soils contaminated separately with benzene, toluene, ethylbenzene, xylene, trichloroethylene, and perchloroethylene. The results demonstrated that the artificial neural network approach presents better performances when compared with multiple linear regression models. The artificial neural network model allowed an accurate prediction of remediation time and efficiency based on only soil and pollutants characteristics, and consequently allowing a simple and quick previous evaluation of the process viability.

Additive adaptive thinking in 1st and 2nd grades pupils

This paper is part of the Project “Adaptive thinking and flexible computation: Critical issues”. It discusses what is meant by adaptive thinking and presents the results of individual interviews with four pupils. The main goal of the study is to understand pupils’ reasoning when solving numerical tasks involving additive situations, and identify features associated with adaptive thinking. The results show that, in the case of first grade pupils, the semantic aspects of the problem are involved in its resolution and the pupils’ performance appears to be related to the development of number sense. The 2nd grade pupils seem to see the quantitative difference as an invariant numerical relationship.

Monitoring the ex-vivo expansion of human mesenchymal stem/stromal cells in xeno-free microcarrier-based reactor systems by MIR spectroscopy

Human mesenchymal stem/stromal cells (MSCs) have received considerable attention in the field of cell-based therapies due to their high differentiation potential and ability to modulate immune responses. However, since these cells can only be isolated in very low quantities, successful realization of these therapies requires MSCs ex-vivo expansion to achieve relevant cell doses. The metabolic activity is one of the parameters often monitored during MSCs cultivation by using expensive multi-analytical methods, some of them time-consuming. The present work evaluates the use of mid-infrared (MIR) spectroscopy, through rapid and economic high-throughput analyses associated to multivariate data analysis, to monitor three different MSCs cultivation runs conducted in spinner flasks, under xeno-free culture conditions, which differ in the type of microcarriers used and the culture feeding strategy applied. After evaluating diverse spectral preprocessing techniques, the optimized partial least square (PLS) regression models based on the MIR spectra to estimate the glucose, lactate and ammonia concentrations yielded high coefficients of determination (R2 ≥ 0.98, ≥0.98, and ≥0.94, respectively) and low prediction errors (RMSECV ≤ 4.7%, ≤4.4% and ≤5.7%, respectively). Besides PLS models valid for specific expansion protocols, a robust model simultaneously valid for the three processes was also built for predicting glucose, lactate and ammonia, yielding a R2 of 0.95, 0.97 and 0.86, and a RMSECV of 0.33, 0.57, and 0.09 mM, respectively. Therefore, MIR spectroscopy combined with multivariate data analysis represents a promising tool for both optimization and control of MSCs expansion processes.

Predicting Xerostomia induced by IMRT treatments: A logistic regression approach

Radiotherapy is one of the main treatments used against cancer. Radiotherapy uses radiation to destroy cancerous cells trying, at the same time, to minimize the damages in healthy tissues. The planning of a radiotherapy treatment is patient dependent, resulting in a lengthy trial and error procedure until a treatment complying as most as possible with the medical prescription is found. Intensity Modulated Radiation Therapy (IMRT) is one technique of radiation treatment that allows the achievement of a high degree of conformity between the area to be treated and the dose absorbed by healthy tissues. Nevertheless, it is still not possible to eliminate completely the potential treatments’ side-effects. In this retrospective study we use the clinical data from patients with head-and-neck cancer treated at the Portuguese Institute of Oncology of Coimbra and explore the possibility of classifying new and untreated patients according to the probability of xerostomia 12 months after the beginning of IMRT treatments by using a logistic regression approach. The results obtained show that the classifier presents a high discriminative ability in predicting the binary response “at risk for xerostomia at 12 months”

An adaptive IoT management infrastructure for eco transport networks

The complexity associated with fast growing of B2B and the lack of a (complete) suite of open standards makes difficulty to maintain the underlying collaborative processes. Aligned to this challenge, this paper aims to be a contribution to an open architecture of logistics and transport processes management system. A model of an open integrated system is being defined as an open computational responsibility from the embedded systems (on-board) as well as a reference implementation (prototype) of a host system to validate the proposed open interfaces. Embedded subsystem can, natively, be prepared to cooperate with other on-board units and with IT-systems in an infrastructure commonly referred to as a center information system or back-office. In interaction with a central system the proposal is to adopt an open framework for cooperation where the embedded unit or the unit placed somewhere (land/sea) interacts in response to a set of implemented capabilities.

Advanced image processing techniques for detection and quantification of drusen

Dissertation presented to obtain the degree of Doctor of Philosophy in Electrical Engineering, speciality on Perceptional Systems, by the Universidade Nova de Lisboa, Faculty of Sciences and Technology

Adaptive Learning in Games: Defining Profiles of Competitor Players

Artificial Intelligence has been applied to dynamic games for many years. The ultimate goal is creating responses in virtual entities that display human-like reasoning in the definition of their behaviors. However, virtual entities that can be mistaken for real persons are yet very far from being fully achieved. This paper presents an adaptive learning based methodology for the definition of players’ profiles, with the purpose of supporting decisions of virtual entities. The proposed methodology is based on reinforcement learning algorithms, which are responsible for choosing, along the time, with the gathering of experience, the most appropriate from a set of different learning approaches. These learning approaches have very distinct natures, from mathematical to artificial intelligence and data analysis methodologies, so that the methodology is prepared for very distinct situations. This way it is equipped with a variety of tools that individually can be useful for each encountered situation. The proposed methodology is tested firstly on two simpler computer versus human player games: the rock-paper-scissors game, and a penalty-shootout simulation. Finally, the methodology is applied to the definition of action profiles of electricity market players; players that compete in a dynamic game-wise environment, in which the main goal is the achievement of the highest possible profits in the market.

Sucesso terapêutico no controlo da tuberculose em Portugal : determinantes do resultado do tratamento e a sua capacidade preditiva

RESUMO - Enquadramento/objectivos: Apesar do elevado nível de comprometimento em estratégias eficazes para o controlo da tuberculose, em todo o mundo, esta constitui ainda um sério problema de Saúde Pública, com uma estimativa global de 9,4milhões de casos novos em 2008 e 1,8milhões de mortes/ano. O reduzido conhecimento das barreiras e facilitadores para o sucesso terapêutico constitui um importante obstáculo na procura de soluções eficazes de melhoramento da qualidade dos programas de controlo da tuberculose. Este estudo procura contribuir para a identificação atempada de doentes com perfis preditivos de insucesso terapêutico, através da identificação inicial de potenciais determinantes do resultado, com base num modelo epidemiológico e estatístico. Métodos: Foi desenvolvido um estudo de caso-controlo para a população de casos notificados ao Programa Nacional de Controlo da Tuberculose (n=24491), entre 2000-2007. Os factores preditivos de insucesso terapêutico foram identificados na análise bivariada e multivariada, com um nível de significância de 5%; a regressão logística foi utilizada para estimar a odds ratio de insucesso terapêutico, em comparação com o sucesso terapêutico, para diversos factores identificados na literatura, e para os quais os dados se encontravam disponíveis. Resultados: A dependência alcoólica (OR=2,889), o país de origem (OR=3,910), a situação sem-abrigo (OR=3.919), a co-infecção pelo VIH (OR=5,173), a interrupção (OR=60.615) ou falha terapêutica no tratamento anterior (OR=67.345) e a duração do tratamento inferior a 165 dias (OR=1930,133) foram identificados como factores preditivos de insucesso terapêutico. A duração do tratamento inferior a 165 dias provou ser o mais importante determinante do resultado terapêutico. Conclusões: Os resultados sugerem que um doente imigrante, em situação de sem-abrigo, dependente alcoólico, com tratamentos anteriores para a tuberculose e co-infectado pelo VIH apresenta uma elevada probabilidade de insucesso terapêutico. Assim, deverão ser definidas estratégias específicas, centradas no doente por forma a impedir este resultado. A base de dados (SVIG-TB), provou ser uma ferramenta de qualidade para a investigação sobre diversos aspectos do controlo da tuberculose. ------------------------------- ABSTRACT - Background/Objective: Despite the high commitment in good strategies for tuberculosis control worldwide, this is still a serious Public Health problem, with global estimates of 9,4million new cases in 2008 and 1,8million deaths/year. The poor understanding of the barriers and facilitators to treatment success is a major obstacle to find effective solutions to improve the quality of tuberculosis programs. This study tries to contribute to the timely identification of patients with predictive profiles of unsuccessful treatment outcomes, through the initial identification of characteristics probably affecting treatment outcome, found on the basis of an epidemiological and statistical model. Methods: A case-control study was conducted for the population of cases notified to the National Program for Tuberculosis Control (n=24 491), between 2000-2007. Predictive factors for unsuccessful outcome were assessed in a bivariate and multivariate analysis, using a significance level of 5%; a logistic regression was used to estimate the odds-ratio of unsuccessful, as compared to successful outcome, for several factors identified in the literature and to which data was available. Results: Alcohol abuse (OR=2,889), patient´s foreign origin (OR=3,910), homelessness (OR=3,919), HIV co-infection (OR=5,173), interruption (OR=60,615) or unsuccessful outcome in the previous treatment (OR=67,345) and treatment duration below 165 days (OR=1930,133) were identified as predictive of unsuccessful outcomes. A low treatment duration proved to be the most powerful factor affecting treatment outcome. Conclusions: Results suggest that a foreign-born patient, alcohol abuser, who has had a previous treatment for tuberculosis and is co-infected with HIV is very likely to have an unsuccessful outcome. Therefore, specific, patient-centered strategies should be taken to prevent an unsuccessful outcome. The database (SVIG-TB), has proved to be a quality tool on research of various aspects of tuberculosis control.

Double coverage and demand for health care: Evidence from quantile regression

An individual experiences double coverage when he bene ts from more than one health insurance plan at the same time. This paper examines the impact of such supplementary insurance on the demand for health care services. Its novelty is that within the context of count data modelling and without imposing restrictive parametric assumptions, the analysis is carried out for di¤erent points of the conditional distribution, not only for its mean location. Results indicate that moral hazard is present across the whole outcome distribution for both public and private second layers of health insurance coverage but with greater magnitude in the latter group. By looking at di¤erent points we unveil that stronger double coverage e¤ects are smaller for high levels of usage. We use data for Portugal, taking advantage of particular features of the public and private protection schemes on top of the statutory National Health Service. By exploring the last Portuguese Health Survey, we were able to evaluate their impacts on the consumption of doctor visi

Adaptive offloading for infotainment systems

Infotainment applications in vehicles are currently supported both by the in-vehicle platform, as well as by user’s smart devices, such as smartphones and tablets. More and more the user expects that there is a continuous service of applications inside or outside of the vehicle, provided in any of these devices (a simple but common example is hands-free mobile phone calls provided by the vehicle platform). With the increasing complexity of ‘apps’, it is necessary to support increasing levels of Quality of Service (QoS), with varying resource requirements. Users may want to start listening to music in the smartphone, or video in the tablet, being this application transparently ‘moved’ into the vehicle when it is started. This paper presents an adaptable offloading mechanism, following a service-oriented architecture pattern, which takes into account the QoS requirements of the applications being executed when making decisions.

Performance Model for MRC Receivers with Adaptive Modulation and Coding in Rayleigh Fading Correlated Channels with Imperfect CSIT

RTUWO Advances in Wireless and Optical Communications 2015 (RTUWO 2015). 5-6 Nov Riga, Latvia.

O Valor Prognóstico da Resposta Neutrofílica na Era da Reperfusão Mecânica do Enfarte Agudo do Miocárdico

BACKGROUND: In ST-segment elevation myocardial infarction (STEMI) patients treated with primary angioplasty, neutrophil response and its prognostic significance are not entirely understood. METHODS: We retrospectively studied 305 consecutive and non-selected STEMI patients. They were divided into three groups according to the maximum neutrophil percentage in the first 48 hours. We compared baseline demographic characteristics, coronary disease risk factors, cardiac history, clinical presentation, therapeutics administered and clinical evolution. We then assessed survival in the three groups and determined predictors of 30-day mortality. Group 1 (G1) had a mean age of 57 +/- 14 years and showed mean neutrophilia of 73.3%, Group 2 (G2) 61 +/- 13 years and 79.9%, and Group 3 (G3) 66 +/- 13 years and 84.2%. We compared outcomes and 30-day mortality between the groups. RESULTS: Mean age rose with increased neutrophil response. There were no statistically significant baseline differences between the groups except for more smokers in Groups 1 and 2, and more patients presenting with Killip class > or = 2 and fewer with uncomplicated evolution in Group 3. During 30-day follow-up there were 19 deaths (G1=1, G2=3 and G3=15). In univariate analysis mortality predictors were age > or = 75 years, anterior STEMI, maximum creatinine kinase > or = 2500 UI/L, culprit lesion in proximal anterior descending artery, incomplete revascularization, Killip > or = 2 at presentation, and being in G3. After multivariate regression analysis independent predictors were age > or = 75 years, incomplete revascularization and being in G3. CONCLUSION: In myocardial infarction patients undergoing mechanical revascularization, an intense neutrophil response (routinely, easily and inexpensively assessed) is related to worse short-term prognosis.

Improved Numerical Simulation for a Novel Adaptive Control Using Fractional Order Derivatives

A novel control technique is investigated in the adaptive control of a typical paradigm, an approximately and partially modeled cart plus double pendulum system. In contrast to the traditional approaches that try to build up ”complete” and ”permanent” system models it develops ”temporal” and ”partial” ones that are valid only in the actual dynamic environment of the system, that is only within some ”spatio-temporal vicinity” of the actual observations. This technique was investigated for various physical systems via ”preliminary” simulations integrating by the simplest 1st order finite element approach for the time domain. In 2004 INRIA issued its SCILAB 3.0 and its improved numerical simulation tool ”Scicos” making it possible to generate ”professional”, ”convenient”, and accurate simulations. The basic principles of the adaptive control, the typical tools available in Scicos, and others developed by the authors, as well as the improved simulation results and conclusions are presented in the contribution.

Inducibility of Atrial Fibrillation During Electrophysiologic Evaluation is Associated with Increased Dispersion of Atrial Refractoriness

The impact of atrial dispersion of refractoriness (Disp_A) in the inducibility and maintenance of atrial fibrillation (AF) has not been fully resolved. AIM: To study the Disp_A and the vulnerability (A_Vuln) for the induction of self-limited (<60 s) and sustained episodes of AF. METHODS AND RESULTS: Forty-seven patients with paroxysmal AF (PAF): 29 patients without structural heart disease and 18 with hypertensive heart disease. Atrial effective refractory period (ERP) was assessed at five sites--right atrial appendage and low lateral right atrium, high interatrial septum, proximal and distal coronary sinus. We compared three groups: group A - AF not inducible (n=13); group B - AF inducible, self-limited (n=18); group C - AF inducible, sustained (n=16). Age, lone AF, hypertension, left atrial and left ventricular (LV) dimensions, LV systolic function, duration of AF history, atrial flutter/tachycardia, previous antiarrhythmics, and Disp_A were analysed with logistic regression to determine association with A_Vuln for AF inducibility. The ERP at different sites showed no differences among the groups. Group A had a lower Disp_A compared to group B (47+/-20 ms vs 82+/-65 ms; p=0.002), and when compared to group C (47+/-20 ms vs 80+/-55 ms; p=0.008). There was no significant difference in Disp_A between groups B and C. By means of multivariate regression analysis, the only predictor of A_Vuln was Disp_A (p=0.04). Conclusion: In patients with PAF, increased Disp_A represents an electrophysiological marker of A_Vuln. Inducibility of both self-limited and sustained episodes of AF is associated with similar values of Disp_A. These findings suggest that the maintenance of AF is influenced by additional factors.

Giardia lamblia and other intestinal parasitic infections and their relationships with nutritional status in children in Brazilian Amazon

The objective of this survey was to assess the relationships between intestinal parasitism, nutritional status and hemoglobin level in children with Indian ascendancy living in an urban area in Brazilian Amazon. We carried out a cross-sectional survey obtaining anthropometric, parasitological and socioeconomic data, and hemoglobin measurements of children aged six to 84 months. Anthropometric data were expressed as z-scores for weight for age (WAZ), height for age (HAZ), weight for height (WHZ) and mid upper circumference for age (MUACZ) parameters. Parasitological examinations were performed through Ritchie (n = 307), Kato-Katz (n = 278), Baermann-Moraes (n = 238) and Safranin-methylene blue methods (n = 307). Hemoglobin measurements were obtained with a Hemocue® photometer (n = 282). Socioeconomic data were used in order to classify children in three family income strata (n = 242). Multiple linear regression analysis showed independent interactions between Giardia lamblia and WAZ (beta = -0.195, SE = 0.138, p = 0.003), WHZ (beta = -0.161, SE = 0.133, p = 0.018) and MUACZ (beta = -0.197, SE = 0.143, p = 0.011), controlling for age, sex, family income, Ascaris lumbricoides, and hookworm infection. Also, the multivariate model showed that the only variable associated with hemoglobin levels was age. Intestinal parasitism control should increase children's possibilities of full development in the studied area.