Age estimation of unaccompanied minors: A portuguese overview

Licensed under a Creative Commons Attribution 4.0 International License.

Estimation of leaf area in grapevine cv. Syrah using empirical models

Aiming to obtain empirical models for the estimation of Syrah leaf area a set of 210 fruiting shoots was randomly collected during the 2013 growing season in an adult experimental vineyard, located in Lisbon, Portugal. Samples of 30 fruiting shoots were taken periodically from the stage of inflorescences visible to veraison (7 sampling dates). At the lab, from each shoot, primary and lateral leaves were separated and numbered according to node insertion. For each leaf, the length of the central and lateral veins was recorded and then the leaf area was measured by a leaf area meter. For single leaf area estimation the best statistical models uses as explanatory variable the sum of the lengths of the two lateral leaf veins. For the estimation of leaf area per shoot it was followed the approach of Lopes & Pinto (2005), based on 3 explanatory variables: number of primary leaves and area of the largest and smallest leaves. The best statistical model for estimation of primary leaf area per shoot uses a calculated variable obtained from the average of the largest and smallest primary leaf area multiplied by the number of primary leaves. For lateral leaf area estimation another model using the same type of calculated variable is also presented. All models explain a very high proportion of variability in leaf area. Our results confirm the already reported strong importance of the three measured variables (number of leaves and area of the largest and smallest leaf) as predictors of the shoot leaf area. The proposed models can be used to accurately predict Syrah primary and secondary leaf area per shoot in any phase of the growing cycle. They are inexpensive, practical, non-destructive methods which do not require specialized staff or expensive equipment.

An analysis of the effects of preferential trade policies through the estimation of quantitative models: the case of Portugal.

Doutoramento em Economia.

Configuring a Better Estimation of Kidney Size in Obese Children and Adolescents

Background: Obesity ignites numerous health and psychosocial problems and is associated with various comorbidities. Body mass index (BMI) is also independently associated with improved risk for numerous kidney disorders. As renal length is considered a vital parameter in the clinical assessment of renal patients, normal renal length has to be defined in accordance to BMI. Objectives: The aim of this study was to define normal kidney length in obese children, comparing ultrasound measurements of the kidney length in obese and non-obese children and adolescents, in order to reduce unnecessary evaluations for nephromegaly. Patients and Methods: Fifty obese children and adolescents and 50 non-obese children and adolescents, aged 1-19 years, were selected from patients of pediatric clinics in two hospitals (Rasoul-e-Akram and Shahid Fahmideh) in Tehran between June 2010 and 2012. After the nephrologist’s and endocrinologist’s approval, the largest longitudinal renal dimension was measured in deep inspiration position by abdomino-pelvic ultrasonography in both groups. Results: It was revealed that both kidneys in obese group were significantly larger than in control group (P = 0.044 and 0.040, respectively). Obesity status, height and age were proven to be significant and independent predictors of length of both kidneys. In both groups length of left kidney was significantly larger than that of right kidney (P < 0.001). Conclusions: A specific standard cut-point limit or norm gram has to be formulated for obese children and adolescents in order to facilitate the diagnosis of kidney diseases, including organomegaly, in these patients.

A method for the estimation of potential evapotranspiration and/or open pan evaporation over Brazil.

This paper presents a simple regression model to estimate potential evapotranspiration and/or open pan evaporation data for a wide network of stations in Brazil. The model uses the readily available data sets like geocoordinates (latitude) and precipitation as inputs. Potential evapotranspiration presents a high correlation with the precipitation during summer months and with latitude during winter months. It also shows association with longitude and elevation; the magnitude of variation appears to be very small. This model gave a R2 varying from 0.460 to 0.902 for different months. The model is also extended to weekly periods of individual years ant tested with the open pan evaporation data of Bebedouro and Mandacaru. The agreement between observed and predicted values appears to be good.

3D Block Modeling and Reserve Estimation of a Garnet Deposit

The purpose of this project is to develop a three-dimensional block model for a garnet deposit in the Alder Gulch, Madison County, Montana. Garnets occur in pre-Cambrian metamorphic Red Wash gneiss and similar rocks in the vicinity. This project seeks to model the percentage of garnet in a deposit called the Section 25 deposit using the Surpac software. Data available for this work are drillhole, trench and grab sample data obtained from previous exploration of the deposit. The creation of the block model involves validating the data, creating composites of assayed garnet percentages and conducting basic statistics on composites using Surpac statistical tools. Variogram analysis will be conducted on composites to quantify the continuity of the garnet mineralization. A three-dimensional block model will be created and filled with estimates of garnet percentage using different methods of reserve estimation and the results compared.

Bayesian Estimation of Small Proportions Using Binomial Group Test

Group testing has long been considered as a safe and sensible relative to one-at-a-time testing in applications where the prevalence rate p is small. In this thesis, we applied Bayes approach to estimate p using Beta-type prior distribution. First, we showed two Bayes estimators of p from prior on p derived from two different loss functions. Second, we presented two more Bayes estimators of p from prior on π according to two loss functions. We also displayed credible and HPD interval for p. In addition, we did intensive numerical studies. All results showed that the Bayes estimator was preferred over the usual maximum likelihood estimator (MLE) for small p. We also presented the optimal β for different p, m, and k.

Reducing Uncertainties in Estimation of Wind Effects on Tall Buildings Using Aerodynamic Wind Tunnel Tests

Tall buildings are wind-sensitive structures and could experience high wind-induced effects. Aerodynamic boundary layer wind tunnel testing has been the most commonly used method for estimating wind effects on tall buildings. Design wind effects on tall buildings are estimated through analytical processing of the data obtained from aerodynamic wind tunnel tests. Even though it is widely agreed that the data obtained from wind tunnel testing is fairly reliable the post-test analytical procedures are still argued to have remarkable uncertainties. This research work attempted to assess the uncertainties occurring at different stages of the post-test analytical procedures in detail and suggest improved techniques for reducing the uncertainties. Results of the study showed that traditionally used simplifying approximations, particularly in the frequency domain approach, could cause significant uncertainties in estimating aerodynamic wind-induced responses. Based on identified shortcomings, a more accurate dual aerodynamic data analysis framework which works in the frequency and time domains was developed. The comprehensive analysis framework allows estimating modal, resultant and peak values of various wind-induced responses of a tall building more accurately. Estimating design wind effects on tall buildings also requires synthesizing the wind tunnel data with local climatological data of the study site. A novel copula based approach was developed for accurately synthesizing aerodynamic and climatological data up on investigating the causes of significant uncertainties in currently used synthesizing techniques. Improvement of the new approach over the existing techniques was also illustrated with a case study on a 50 story building. At last, a practical dynamic optimization approach was suggested for tuning structural properties of tall buildings towards attaining optimum performance against wind loads with less number of design iterations.

Online impedance spectroscopy estimation of a battery

Electrochemical impedance spectroscopy (EIS) is a helpful tool to understand how a battery is behaving and how it degrades. One of the disadvantages is that it is typically an 'off-line' process. This paper investigates an alternative method of looking at impedance spectroscopy of a battery system while it is on-line and operational by manipulating the switching pattern of the dc-dc converter to generate low frequency harmonics in conjunction with the normal high frequency switching pattern to determine impedance in real time. However, this adds extra ripple on the inductor which needs to be included in the design calculations. The paper describes the methodology and presents some experimental results in conjunction with EIS results to illustrate the concept.

Estimation of water use and crop coefficients for an intensive olive orchard using sap flow measurements and modeled data

Olive tree sap flow measurements were collected in an intensive orchard near Évora, Portugal, during the irrigation seasons of 2013 and 2014, to calculate daily tree transpiration rates (T_SF). Meteorological variables were also collected to calculate reference evapotranspiration (ETo). Both data were used to assess values of basal crop coefficient (Kcb) for the period of the sap flow observations. The soil water balance model SIMDualKc was calibrated with soil, biophysical ground data and sap flow measurements collected in 2013. Validated in 2014 with collected sap flow observations, the model was used to provide estimates of dual e single crop coefficients for 2014 crop growing season. Good agreement between model simulated daily transpiration rates and those obtained with sapflow measurements was observed for 2014 (R2=0.76, RMSE=0.20 mm d-1), the year of validation, with an estimation average absolute error (AAE) of 0.20 mm d-1. Olive modeled daily actual evapotranspiration resulted in atual ETc values of 0.87, 2.05 and 0.77 mm d-1 for 2014 initial, mid- and end-season, respectively. Actual crop coefficient (Kc act) values of 0.51, 0.43 and 0.67 were also obtained for the same periods, respectively. Higher Kc values during spring (initial stage) and autumn (end-stage) were published in FAO56, varying between 0.65 for Kc ini and 0.70 for Kc end. The lower Kc mid value of 0.43 obtained for the summer (mid-season) is also inconsistent with the FAO56 expected Kc mid value of 0.70 for the period. The modeled Kc results are more consistent with the ones published by Allen & Pereira [1] for olive orchards with effective ground cover of 0.25 to 0.5, which vary between 0.40 and 0.80 for Kc ini, 0.40–0.60 for Kc mid with no active ground cover, and 0.35–0.75 for Kc end, depending on ground cover. The SIMDualKc simulation model proved to be appropriate for obtaining evapotranspiration and crop coefficient values for our intensive olive orchard in southern Portugal.

Dynamical modeling of biogas production supported by an experimental anaerobic digestion process

This paper presents the development of a combined experimental and numerical approach to study the anaerobic digestion of both the wastes produced in a biorefinery using yeast for biodiesel production and the wastes generated in the preceding microbial biomass production. The experimental results show that it is possible to valorise through anaerobic digestion all the tested residues. In the implementation of the numerical model for anaerobic digestion, a procedure for the identification of its parameters needs to be developed. A hybrid search Genetic Algorithm was used, followed by a direct search method. In order to test the procedure for estimation of parameters, first noise-free data was considered and a critical analysis of the results obtain so far was undertaken. As a demonstration of its application, the procedure was applied to experimental data.

On The Use of Genetic Algorithms for Parameter Identification in Anaerobic Digestion Modelling

Anaerobic digestion (AD) of wastewater is a very interesting option for waste valorization, energy production and environment protection. It is a complex, naturally occurring process that can take place inside bioreactors. The capability of predicting the operation of such bioreactors is important to optimize the design and the operation conditions of the reactors, which, in part, justifies the numerous AD models presently available. The existing AD models are not universal, have to be inferred from prior knowledge and rely on existing experimental data. Among the tasks involved in the process of developing a dynamical model for AD, the estimation of parameters is one of the most challenging. This paper presents the identifiability analysis of a nonlinear dynamical model for a batch reactor. Particular attention is given to the structural identifiability of the model, which considers the uniqueness of the estimated parameters. To perform this analysis, the GenSSI toolbox was used. The estimation of the model parameters is achieved with genetic algorithms (GA) which have already been used in the context of AD modelling, although not commonly. The paper discusses its advantages and disadvantages.

Estimation of the Traffic Intensity in a Piecewise-stationary Mt/Gt/1 Queue with Probing

We use a probing strategy to estimate the time dependent traffic intensity in an Mt/Gt/1 queue, where the arrival rate and the general service-time distribution change from one time interval to another, and derive statistical properties of the proposed estimator. We present a method to detect a switch from a stationary interval to another using a sequence of probes to improve the estimation. At the end, we compare our results with two estimators proposed in the literature for the M/G/1 queue.

Sensitivity analysis of parameters of a photovoltaic cell under different condition

A photovoltaic cell is a component which converts light energy into electrical energy. Different environmental parameters and internal parameters have a great impact on the output of the photovoltaic cell. To identify its characteristics and estimate the output, the well known Shockley diode equation is used. This equation contains all the parameters, as one environmental and different internal. The properties of these parameters were studied and their sensitivity have been analyzed through the use of an error function; this error function allows the study of the behaviour of the parameters and their characteristics against the output of the photovoltaic cell through the analysis of its curves giving the sensitivity of the different parameters to the output of the photovoltaic cell. Using these results the impact of the parameters of the photovoltaic cell has been clearly identified. White noise is included both with the ideal values and the simulation and the ideal value is imposed to get the real time environment flavor. This work analyses both systems with and without white noise.

Estimation of climatological water deficit in an experimental watershed in the brazilian cerrado.

ABSTRACT: This study aimed to estimate the probability of climatological water deficit in an experimental watershed in the Cerrado biome, located in the central plateau of Brazil. For that, it was used a time series of 31 years (1982?2012). The probable climatological water deficit was calculated by the difference between rainfall and probable reference evapotranspiration, on a decennial scale. The reference evapotranspiration (ET0) was estimated by the standard FAO-56 Penman-Monteith method. To estimate water deficit, it was used gamma distribution, time series of rainfall and reference evapotranspiration. The adherence of the estimated probabilities to the observed data was verified by the Kolmogorov-Smirnov nonparametric test, with significance level (a-0.05), which presented a good adjustment to the distribution models. It was observed a climatological water deficit, in greater or lesser intensity, between the annual decennials 2 and 32.