Residential property loans and performance during property price booms: evidence from European

Understanding the performance of banks is of the u tmost importance due to the impact the sector may have on economic growth and financial stability. Residential mortgage loans constitute a large proportion of the portfolio of many banks and are one of the key assets in the determination of performance. Using a dynamic panel model , we analyse the impact of res idential mortgage loans on bank profitability and risk , based on a sample of 555 banks in the European Union ( EU - 15 ) , over the period from 1995 to 2008. We find that banks with larger weight s in residential mortgage loans display lower credit risk in good market conditions . This result may explain why banks rush to lend on property during b ooms due to the positive effect it has on credit risk . The results also show that credit risk and profitability are lower during the upturn in the residential property cy cle. Furthermore, t he results reveal the existence of a non - linear relationship ( U - shaped marginal effect), as a function of bank’s risk, between profitability and residential mortgage exposure . For those banks that have high er credit risk, a large exposur e to residential loans is associated with increased risk - adjusted profitability, through a reduction in risk. For banks with a moderate to low credit risk, the impact of higher exposure are also positive on risk - adjusted profitability.

An Extension of Gompertzian Growth Dynamics Weibull and Frechet Models

In this work a new probabilistic and dynamical approach to an extension of the Gompertz law is proposed. A generalized family of probability density functions, designated by Beta* (p, q), which is proportional to the right hand side of the Tsoularis-Wallace model, is studied. In particular, for p = 2, the investigation is extended to the extreme value models of Weibull and Frechet type. These models, described by differential equations, are proportional to the hyper-Gompertz growth model. It is proved that the Beta* (2, q) densities are a power of betas mixture, and that its dynamics are determined by a non-linear coupling of probabilities. The dynamical analysis is performed using techniques of symbolic dynamics and the system complexity is measured using topological entropy. Generally, the natural history of a malignant tumour is reflected through bifurcation diagrams, in which are identified regions of regression, stability, bifurcation, chaos and terminus.

The epidemiologic paradox of low birth weight in Brazil

OBJECTIVE: To examine whether the low birth weight (LBW) paradox exists in Brazil. METHODS: LBW and cesarean section rates between 1995 and 2007 were estimated based on data from SINASC (Brazilian Live Births Database). Infant mortality rates (IMRs) were obtained using an indirect method that correct for underreporting. Schooling information was obtained from census data. Trends in LBW rate were assessed using joinpoint regression models. The correlations between LBW rate and other indicators were graphically assessed by lowess regression and tested using Spearman's rank correlation. RESULTS: In Brazil, LBW rate trends were non-linear and non-significant: the rate dropped from 7.9% in 1995 to 7.7% in 2000, then increased to 8.2% in 2003 and remained nearly steady thereafter at 8.2% in 2007. However, trends varied among Brazilian regions: there were significant increases in the North from 1999 to 2003 (2.7% per year), and in the South (1.0% per year) and Central-West regions (0.6% per year) from 1995 to 2007. For the entire period studied, higher LBW and lower IMRs were seen in more developed compared to less developed regions. In Brazilian States, in 2005, the higher the IMR rate, the lower the LBW rate (p=0.009); the lower the low schooling rate, the lower the LBW rate (p=0.007); the higher the number of neonatal intensive care beds per 1,000 live births, the higher the LBW rate (p=0.036). CONCLUSIONS: The low birth weight paradox was seen in Brazil. LBW rate is increasing in some Brazilian regions. Regional differences in LBW rate seem to be more associated to availability of perinatal care services than underlying social conditions.

Benzo[c]thiophene chromophores linked to cationic Fe and Ru derivatives for NLO materials: synthesis characterization and quadratic hyperpolarizabilities

5-Monocyclopentadienyliron(II)/ruthenium(II) complexes of the general formula [M(5-C5H5)(PP)(L1)][PF6] {M = Fe, PP = dppe; M = Ru, PP = dppe or 2PPh3; L1 = 5-[3-(thiophen-2-yl)benzo[c]thiophenyl]thiophene-2-carbonitrile} have been synthesized and studied to evaluate their molecular quadratic hyperpolarizabilities. The compounds were fully characterized by NMR, FTIR and UV/Vis spectroscopy and their electrochemical behaviour studied by cyclic voltammetry. Quadratic hyperpolarizabilities () were determined by hyper-Rayleigh scattering measurements at a fundamental wavelength of 1500 nm. Density functional theory calculations were employed to rationalize the second-order non-linear optical properties of these complexes.

Controladores linguísticos Fuzzy

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica

Application-specific modified particle swarm optimization for energy resource scheduling considering vehicle-to-grid

This paper presents a modified Particle Swarm Optimization (PSO) methodology to solve the problem of energy resources management with high penetration of distributed generation and Electric Vehicles (EVs) with gridable capability (V2G). The objective of the day-ahead scheduling problem in this work is to minimize operation costs, namely energy costs, regarding he management of these resources in the smart grid context. The modifications applied to the PSO aimed to improve its adequacy to solve the mentioned problem. The proposed Application Specific Modified Particle Swarm Optimization (ASMPSO) includes an intelligent mechanism to adjust velocity limits during the search process, as well as self-parameterization of PSO parameters making it more user-independent. It presents better robustness and convergence characteristics compared with the tested PSO variants as well as better constraint handling. This enables its use for addressing real world large-scale problems in much shorter times than the deterministic methods, providing system operators with adequate decision support and achieving efficient resource scheduling, even when a significant number of alternative scenarios should be considered. The paper includes two realistic case studies with different penetration of gridable vehicles (1000 and 2000). The proposed methodology is about 2600 times faster than Mixed-Integer Non-Linear Programming (MINLP) reference technique, reducing the time required from 25 h to 36 s for the scenario with 2000 vehicles, with about one percent of difference in the objective function cost value.

Dynamics of a backlash chain

This paper studies the dynamical properties of a system with distributed backlash and impact phenomena. This means that it is considered a chain of masses that interact with each other solely by means of backlash and impact phenomena. It is observed the emergence of non-linear phenomena resembling those encountered in the Fermi-Pasta-Ulam problem.

Partial utility-driven scheduling for flexible SLA and pricing arbitration in clouds

Cloud SLAs compensate customers with credits when average availability drops below certain levels. This is too inflexible because consumers lose non-measurable amounts of performance being only compensated later, in next charging cycles. We propose to schedule virtual machines (VMs), driven by range-based non-linear reductions of utility, different for classes of users and across different ranges of resource allocations: partial utility. This customer-defined metric, allows providers transferring resources between VMs in meaningful and economically efficient ways. We define a comprehensive cost model incorporating partial utility given by clients to a certain level of degradation, when VMs are allocated in overcommitted environments (Public, Private, Community Clouds). CloudSim was extended to support our scheduling model. Several simulation scenarios with synthetic and real workloads are presented, using datacenters with different dimensions regarding the number of servers and computational capacity. We show the partial utility-driven driven scheduling allows more VMs to be allocated. It brings benefits to providers, regarding revenue and resource utilization, allowing for more revenue per resource allocated and scaling well with the size of datacenters when comparing with an utility-oblivious redistribution of resources. Regarding clients, their workloads’ execution time is also improved, by incorporating an SLA-based redistribution of their VM’s computational power.

Genus for knots and links in renormalizable templates with several branch nodes

We apply kneading theory to describe the knots and links generated by the iteration of renormalizable nonautonomous dynamical systems with reducible kneading invariants, in terms of the links corresponding to each factor. As a consequence we obtain explicit formulas for the genus for this kind of knots and links.

Modified particle swarm optimization for day-ahead distributed energy resources scheduling including vehicle-to-grid

Mestrado em Engenharia Electrotécnica – Sistemas Eléctricos de Energia

Project, modelling and simulation of air stripping columns for the treatment of groundwater contaminated with volatile organic compounds

Volatile organic compounds are a common source of groundwater contamination that can be easily removed by air stripping in columns with random packing and using a counter-current flow between the phases. This work proposes a new methodology for the column design for any particular type of packing and contaminant avoiding the necessity of a pre-defined diameter used in the classical approach. It also renders unnecessary the employment of the graphical Eckert generalized correlation for pressure drop estimates. The hydraulic features are previously chosen as a project criterion and only afterwards the mass transfer phenomena are incorporated, in opposition to conventional approach. The design procedure was translated into a convenient algorithm using C++ as programming language. A column was built in order to test the models used either in the design or in the simulation of the column performance. The experiments were fulfilled using a solution of chloroform in distilled water. Another model was built to simulate the operational performance of the column, both in steady state and in transient conditions. It consists in a system of two partial non linear differential equations (distributed parameters). Nevertheless, when flows are steady, the system became linear, although there is not an evident solution in analytical terms. In steady state the resulting system of ODE can be solved, allowing for the calculation of the concentration profile in both phases inside the column. In transient state the system of PDE was numerically solved by finite differences, after a previous linearization.

A New Approach in the Design of Air Stripping Columns for the Treatment of Groundwater Contaminated With Volatile Organic Compounds

Volatile organic compounds are a common source of groundwater contamination that can be easily removed by air stripping in columns with random packing and using a counter-current flow between the phases. This work proposes a new methodology for column design for any type of packing and contaminant which avoids the necessity of an arbitrary chosen diameter. It also avoids the employment of the usual graphical Eckert correlations for pressure drop. The hydraulic features are previously chosen as a project criterion. The design procedure was translated into a convenient algorithm in C++ language. A column was built in order to test the design, the theoretical steady-state and dynamic behaviour. The experiments were conducted using a solution of chloroform in distilled water. The results allowed for a correction in the theoretical global mass transfer coefficient previously estimated by the Onda correlations, which depend on several parameters that are not easy to control in experiments. For best describe the column behaviour in stationary and dynamic conditions, an original mathematical model was developed. It consists in a system of two partial non linear differential equations (distributed parameters). Nevertheless, when flows are steady, the system became linear, although there is not an evident solution in analytical terms. In steady state the resulting ODE can be solved by analytical methods, and in dynamic state the discretization of the PDE by finite differences allows for the overcoming of this difficulty. To estimate the contaminant concentrations in both phases in the column, a numerical algorithm was used. The high number of resulting algebraic equations and the impossibility of generating a recursive procedure did not allow the construction of a generalized programme. But an iterative procedure developed in an electronic worksheet allowed for the simulation. The solution is stable only for similar discretizations values. If different values for time/space discretization parameters are used, the solution easily becomes unstable. The system dynamic behaviour was simulated for the common liquid phase perturbations: step, impulse, rectangular pulse and sinusoidal. The final results do not configure strange or non-predictable behaviours.

Design of New Materials for Passive Vibration Control

The objective of this contribution is to extend the models of cellular/composite material design to nonlinear material behaviour and apply them for design of materials for passive vibration control. As a first step a computational tool allowing determination of optimised one-dimensional isolator behaviour was developed. This model can serve as a representation for idealised macroscopic behaviour. Optimal isolator behaviour to a given set of loads is obtained by generic probabilistic metaalgorithm, simulated annealing. Cost functional involves minimization of maximum response amplitude in a set of predefined time intervals and maximization of total energy absorbed in the first loop. Dependence of the global optimum on several combinations of leading parameters of the simulated annealing procedure, like neighbourhood definition and annealing schedule, is also studied and analyzed. Obtained results facilitate the design of elastomeric cellular materials with improved behaviour in terms of dynamic stiffness for passive vibration control.

Light memory function in a double pin SiC device

A double pi'npin heterostructure based on amorphous SiC has a non linear spectral gain which is a function of the signal wavelength that impinges on its front or back surface. An impulse of a configurable length and amplitude is applied to a 390 nm LED which illuminates one of the sensor surfaces, followed by a time period without any illumination after which an input signal with a different wavelength is impinged upon the front surface. Results show that the intensity and duration of the impulse illumination of the surfaces influences the sensor's response with different output for the same input signal. This paper studies this effect and proposes an application as a short term light memory. (C) 2015 Elsevier B.V. All rights reserved.

Day-ahead Resource Scheduling Including Demand Response for Electric Vehicles

The energy resource scheduling is becoming increasingly important, as the use of distributed resources is intensified and massive gridable vehicle (V2G) use is envisaged. This paper presents a methodology for day-ahead energy resource scheduling for smart grids considering the intensive use of distributed generation and V2G. The main focus is the comparison of different EV management approaches in the day-ahead energy resources management, namely uncontrolled charging, smart charging, V2G and Demand Response (DR) programs i n the V2G approach. Three different DR programs are designed and tested (trip reduce, shifting reduce and reduce+shifting). Othe r important contribution of the paper is the comparison between deterministic and computational intelligence techniques to reduce the execution time. The proposed scheduling is solved with a modified particle swarm optimization. Mixed integer non-linear programming is also used for comparison purposes. Full ac power flow calculation is included to allow taking into account the network constraints. A case study with a 33-bus distribution network and 2000 V2G resources is used to illustrate the performance of the proposed method.