1,265 research outputs found
An empirical analysis of structural models of corporate debt pricing
This paper tests empirically the performance of three structural models of corporate bond pricing, namely Merton (1974), Leland (1994) and Fan and Sundaresan (2000). While the first two models overestimate bond prices, the Fan and Sundaresan model reveals an extremely good performance. When considering the prediction of credit spreads, the three models under-estimate market spreads but, again, Fan and Sundaresan has a better performance. We find rating, maturity and asset volatility effects in the prediction power, as the models under-estimate less the spreads of riskier firms and of bonds with better rating quality and longer maturity. Moreover, our results reveal the existence of a new industry effect. Spread errors are systematically related to some bond- and firm-specific variables, as well as term structure variables.structural models, corporate debt valuation, empirical credit spreads
MODELLING TOURISM DEMAND: A COMPARATIVE STUDY BETWEEN ARTIFICIAL NEURAL NETWORKS AND THE BOX-JENKINS METHODOLOGY
This study seeks to investigate and highlight the usefulness of the Artificial Neural Networks (ANN) methodology as an alternative to the Box-Jenkins methodology in analysing tourism demand. To this end, each of the above-mentioned methodologies is centred on the treatment, analysis and modelling of the tourism time series: “Nights Spent in Hotel Accommodation per Month”, recorded in the period from January 1987 to December 2006, since this is one of the variables that best expresses effective demand. The study was undertaken for the North and Centre regions of Portugal. The results showed that the model produced by using the ANN methodology presented satisfactory statistical and adjustment qualities, suggesting that it is suitable for modelling and forecasting the reference series, when compared with the model produced by using the Box?Jenkins methodology.Artificial Neural Networks; ARIMA Models; Time Series Forecasting
Impacto do sistema de microirrigacao no ambiente - salinidade
Trata-se do quinto estudo de monitorização e avaliação do impacto do sistema de rega gota a gota no meio ambiente encomendado pela ACDI/VOCA (Agricultural Cooperative Development International et Volunteers in Overseas Cooperative Assistance). Foram colhidas 45 amostras de solos e 29 de águas, nas parcelas dos agricultores beneficiários dos projectos financiados pela referida ONG na ilha de Santiago. Essas amostras foram analisadas no Laboratório de Análise de Solos, Águas e Plantas (LASAP) do INIDA para determinar o pH, a condutividade eléctrica (ECW), o cálcio (Ca) e magnésio (Mg) com objectivo de avaliar o grau de salinidade dos solos.
58 % dos solos analisados são considerados sem efeito salino ou muito pouco salino podendo receber a maioria das hortícola, mesmo as mais sensíveis aos sais e 11% só poderão receber culturas que toleram um alto grau de salinidade, nomeadamente beterraba, espargos, espinafres, repolho, tamareira, entre outras.
os valores de condutividade eléctrica, encontrados em Achada Baleia (Egídio) , Baía e Cassunda, correspondem a solos classificados entre forte a muito fortemente salinos onde somente culturas altamente tolerantes aos sais atingem produções aceitáveis.
As amostras de água, que ano passado, foram classificadas de boa para rega, aumentaram em média cerca de 40 mS/cm no valor condutividade eléctrica.
Em termos médios, enquanto que no solo a quantidade de sais diminuiu ligeiramente, na água houve um aumento global do teor de sal. O valor máximo da condutividade eléctrica do solo encontrado no presente trabalho é de longe superior ao do ano passado para uma diferença de 1,77 mS/cm.Estudo elaborado pelo INIDA para ACDI/VOC
The elastoplastic analysis of planar frames for large displacements by mathematical programming
Imperial Users onl
Long-term balancing selection in the genomes of humans and other great apes
Balancing selection maintains advantageous genetic diversity in populations through a variety of mechanisms including overdominance, negative frequency-dependent selection, temporal or spatial variation in selective pressures, and pleiotropy. If environmental pressures are constant through time, balancing selection can affect the evolution of selected loci for millions of years, and its targets might be shared by
different species. This thesis is comprised of two different approaches aimed at detecting shared signatures of balancing selection in the genomes of humans and other great apes.
In the first part of the thesis, we focus on extreme loci where the action of balancing selection has maintained several coding trans-species polymorphisms in humans, chimpanzees and bonobos. These trSNPs segregate since the common ancestor of the Homo-Pan clade and have survived for ~14 million years of independent evolution. These loci show the characteristic signatures of long-term balancing selection, as they define haplotypes with high genetic diversity that show cluster of sequences by allele rather than by species, and segregate at intermediate allele frequencies. Apart from
several trSNPs in the MHC region, we were able to uncover a non-synonymous trSNP in the autoimmune gene LAD1.
In the second part of the thesis we explore shared signatures of balancing selection outside trSNPs. We first implement a genome scan designed to detect signatures of balancing selection using NCD2 in the genomes of nine great ape species, including chimpanzee, bonobo, gorilla and orangutan. We show that targets of balancing selection are shared between species that have diverged millions of years ago, and
that this observation cannot be explained by shared ancestry. We further demonstrate that targets of balancing selection primarily affect the evolution of genic regions of the genome, although we see evidence for their involvement in the regulation of gene expression. Overall, we provide comprehensive evidence that similar environmental pressures
maintain advantageous diversity through the action of balancing selection in humans and other great apes, notwithstanding the deep divergence times between many of
these species
Exploration of the possibility of acoustic emission technique in detection and diagnosis of bubble formation and collapse in valves
The application of acoustic emission (AE) technique in detection and monitoring of bubble formation
and collapse in valves are presented in this review. The generation of AE signals and the basic compositions of
AE detection system are briefly explained. The applications of AE technique in valves are focused on condition
monitoring and detection bubble formation (bubble cavitation), and leakage of water through valves. All results
prove that the AE technique works well for detection and diagnosis of failures during valves
Investigation of the influence of flow rate on bubble formation and collapse in ball values at various opening percentages using an AE technique
Ball valves are popularly used in many different industrial processes and hydraulic systems because of their light weight and simple structure. However, they are susceptible to cavitation phenomena and the growth and collapse of the bubbles formed lead to erosion and pitting of the metal surfaces. This paper presents the monitoring and detection of bubble formation at an early stage in a ball valve using acoustic emission (AE). It is shown that AE will detect incipient cavitation and that there is a clear correlation between AE signal level and the flow rate through the ball valve at a constant opening percentage
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