Integration of geometric consistency contributory factors in three-leg junctions collision prediction models of Portuguese two-lane national highways

This paper aims at developing a collision prediction model for three-leg junctions located in national roads (NR) in Northern Portugal. The focus is to identify factors that contribute for collision type crashes in those locations, mainly factors related to road geometric consistency, since literature is scarce on those, and to research the impact of three modeling methods: generalized estimating equations, random-effects negative binomial models and random-parameters negative binomial models, on the factors of those models. The database used included data published between 2008 and 2010 of 177 three-leg junctions. It was split in three groups of contributing factors which were tested sequentially for each of the adopted models: at first only traffic, then, traffic and the geometric characteristics of the junctions within their area of influence; and, lastly, factors which show the difference between the geometric characteristics of the segments boarding the junctionsâ area of influence and the segment included in that area were added. The choice of the best modeling technique was supported by the result of a cross validation made to ascertain the best model for the three sets of researched contributing factors. The models fitted with random-parameters negative binomial models had the best performance in the process. In the best models obtained for every modeling technique, the characteristics of the road environment, including proxy measures for the geometric consistency, along with traffic volume, contribute significantly to the number of collisions. Both the variables concerning junctions and the various national highway segments in their area of influence, as well as variations from those characteristics concerning roadway segments which border the already mentioned area of influence have proven their relevance and, therefore, there is a rightful need to incorporate the effect of geometric consistency in the three-leg junctions safety studies.

Using data mining for prediction of hospital length of stay: an application of the CRISP-DM Methodology

Hospitals are nowadays collecting vast amounts of data related with patient records. All this data hold valuable knowledge that can be used to improve hospital decision making. Data mining techniques aim precisely at the extraction of useful knowledge from raw data. This work describes an implementation of a medical data mining project approach based on the CRISP-DM methodology. Recent real-world data, from 2000 to 2013, were collected from a Portuguese hospital and related with inpatient hospitalization. The goal was to predict generic hospital Length Of Stay based on indicators that are commonly available at the hospitalization process (e.g., gender, age, episode type, medical specialty). At the data preparation stage, the data were cleaned and variables were selected and transformed, leading to 14 inputs. Next, at the modeling stage, a regression approach was adopted, where six learning methods were compared: Average Prediction, Multiple Regression, Decision Tree, Artificial Neural Network ensemble, Support Vector Machine and Random Forest. The best learning model was obtained by the Random Forest method, which presents a high quality coefficient of determination value (0.81). This model was then opened by using a sensitivity analysis procedure that revealed three influential input attributes: the hospital episode type, the physical service where the patient is hospitalized and the associated medical specialty. Such extracted knowledge confirmed that the obtained predictive model is credible and with potential value for supporting decisions of hospital managers.

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.

Annular flow of viscoelastic fluids: Analytical and numerical solutions

This work provides analytical and numerical solutions for the linear, quadratic and exponential Phan–Thien–Tanner (PTT) viscoelastic models, for axial and helical annular fully-developed flows under no slip and slip boundary conditions, the latter given by the linear and nonlinear Navier slip laws. The rheology of the three PTT model functions is discussed together with the influence of the slip velocity upon the flow velocity and stress fields. For the linear PTT model, full analytical solutions for the inverse problem (unknown velocity) are devised for the linear Navier slip law and two different slip exponents. For the linear PTT model with other values of the slip exponent and for the quadratic PTT model, the polynomial equation for the radial location (β) of the null shear stress must be solved numerically. For both models, the solution of the direct problem is given by an iterative procedure involving three nonlinear equations, one for β, other for the pressure gradient and another for the torque per unit length. For the exponential PTT model we devise a numerical procedure that can easily compute the numerical solution of the pure axial flow problem

Implementation of integral viscoelastic constitutive models in OpenFOAM® computational library

This work reports the implementation and verification of a new so lver in OpenFOAM® open source computational library, able to cope with integral viscoelastic models based on the integral upper-convected Maxwell model. The code is verified through the comparison of its predictions with analytical solutions and numerical results obtained with the differential upper-convected Maxwell model

Structure-property relationships in polymer nanocomposites

Tese de Doutoramento em Ciência e Engenharia de Polímeros e Compósitos

Lithium ion rechargeable batteries: State of the art and future needs of microscopic theoretical models and simulations

This review deals with the recent developments and present status of the theoretical models for the simulation of the performance of lithium ion batteries. Preceded by a description of the main materials used for each of the components of a battery -anode, cathode and separator- and how material characteristics affect battery performance, a description of the main theoretical models describing the operation and performance of a battery are presented. The influence of the most relevant parameters of the models, such as boundary conditions, geometry and material characteristics are discussed. Finally, suggestions for future work are proposed.

Extreme value Birnbaum-Saunders regression models applied to environmental data

Extreme value models are widely used in different areas. The Birnbaum–Saunders distribution is receiving considerable attention due to its physical arguments and its good properties. We propose a methodology based on extreme value Birnbaum–Saunders regression models, which includes model formulation, estimation, inference and checking. We further conduct a simulation study for evaluating its performance. A statistical analysis with real-world extreme value environmental data using the methodology is provided as illustration.

Exploring female mice interstrain differences relevant for models of depression

Depression is an extremely heterogeneous disorder. Diverse molecular mechanisms have been suggested to underlie its etiology. To understand the molecular mechanisms responsible for this complex disorder, researchers have been using animal models extensively, namely mice from various genetic backgrounds and harboring distinct genetic modifications. The use of numerous mouse models has contributed to enrich our knowledge on depression. However, accumulating data also revealed that the intrinsic characteristics of each mouse strain might influence the experimental outcomes, which may justify some conflicting evidence reported in the literature. To further understand the impact of the genetic background, we performed a multimodal comparative study encompassing the most relevant parameters commonly addressed in depression, in three of the most widely used mouse strains: Balb/c, C57BL/6, and CD-1. Moreover, female mice were selected for this study taken into account the higher prevalence of depression in women and the fewer animal studies using this gender. Our results show that Balb/c mice have a more pronounced anxious-like behavior than CD-1 and C57BL/6 mice, whereas C57BL/6 animals present the strongest depressive-like trait. Furthermore, C57BL/6 mice display the highest rate of proliferating cells and brain-derived neurotrophic factor (Bdnf) expression levels in the hippocampus, while hippocampal dentate granular neurons of Balb/c mice show smaller dendritic lengths and fewer ramifications. Of notice, the expression levels of inducible nitric oxide synthase (iNos) predict 39.5% of the depressive-like behavior index, which suggests a key role of hippocampal iNOS in depression. Overall, this study reveals important interstrain differences in several behavioral dimensions and molecular and cellular parameters that should be considered when preparing and analyzing experiments addressing depression using mouse models. It further contributes to the literature by revealing the predictive value of hippocampal iNos expression levels in depressive-like behavior, irrespectively of the mouse strain.

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.

Cylindrically symmetric models of gravitational collapse to black holes: a short review

We survey results about exact cylindrically symmetric models of gravitational collapse in General Relativity. We focus on models which result from the matching of two spacetimes having collapsing interiors which develop trapped surfaces and vacuum exteriors containing gravitational waves. We collect some theorems from the literature which help to decide a priori about eventual spacetime matchings. We revise, in more detail, some toy models which include some of the main mathematical and physical issues that arise in this context, and compute the gravitational energy flux through the matching boundary of a particular collapsing region. Along the way, we point out several interesting open problems.

On the length of bank-firm relationships: an empirical application to a major French bank

NIPE - WP 01/ 2016

Specification and testing of multiplicative time-varying GARCH models with applications

In this article, we develop a specification technique for building multiplicative time-varying GARCH models of Amado and Teräsvirta (2008, 2013). The variance is decomposed into an unconditional and a conditional component such that the unconditional variance component is allowed to evolve smoothly over time. This nonstationary component is defined as a linear combination of logistic transition functions with time as the transition variable. The appropriate number of transition functions is determined by a sequence of specification tests. For that purpose, a coherent modelling strategy based on statistical inference is presented. It is heavily dependent on Lagrange multiplier type misspecification tests. The tests are easily implemented as they are entirely based on auxiliary regressions. Finite-sample properties of the strategy and tests are examined by simulation. The modelling strategy is illustrated in practice with two real examples: an empirical application to daily exchange rate returns and another one to daily coffee futures returns.

Effect of the alkyl chain length of the ionic liquid anion on polymer electrolytes properties

New polymer electrolytes (PEs) based on chitosan and three ionic liquid (IL) families ([C2mim][CnSO3], [C2mim][CnSO4] and [C2mim][diCnPO4]) were synthesized by the solvent casting method. The effect of the length of the alkyl chain of the IL anion on the thermal, morphological and electrochemical properties of the PEs was studied. The solid polymer electrolytes (SPE) membranes were analyzed by differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive X-ray (EDX), polarized optical microscopy (POM), atomic force microscopy (AFM), complex impedance spectroscopy (ionic conductivity) and cyclic voltammetry (CV). The obtained results evidenced an influence of the alkyl chain length of the IL anion on the temperature of degradation, birefringence, surface roughness and ionic conductivity of the membranes. The DSC, XRD and CV results showed independency from the length of the IL-anion-alkyl chain. The PEs displayed an predominantly amorphous morphology, a minimum temperature of degradation of 135 °C, a room temperature (T = 25 °C) ionic conductivity of 7.78 × 10−4 S cm−1 and a wide electrochemical window of ∼ 4.0 V.