855 resultados para Interest rates -- Mathematical models.
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Unsurprisingly, a great deal of attention has been paid to the economic consequences of the credit crunch. However, this paper shows that the credit crunch was preceded by a strong build-up of mortgage debt internationally, which, in the long run, could turn out to be more significant than the credit crunch itself. Indeed, the debt build-up suggests that the credit crunch is more likely to reoccur, because highly-indebted households have weaker buffers to withstand unexpected shocks to their incomes or to interest rates. The paper presents a model that can explain the debt build-up and changes to the distribution of debt between existing owners and first-time buyers, which hinders access to home-ownership for the latter, even amongst those households who would be considered as credit-worthy.
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This paper reviews the evidence relating to the question: does the risk of fungicide resistance increase or decrease with dose? The development of fungicide resistance progresses through three key phases. During the ‘emergence phase’ the resistant strain has to arise through mutation and invasion. During the subsequent ‘selection phase’, the resistant strain is present in the pathogen population and the fraction of the pathogen population carrying the resistance increases due to the selection pressure caused by the fungicide. During the final phase of ‘adjustment’, the dose or choice of fungicide may need to be changed to maintain effective control over a pathogen population where resistance has developed to intermediate levels. Emergence phase: no experimental publications and only one model study report on the emergence phase, and we conclude that work in this area is needed. Selection phase: all the published experimental work, and virtually all model studies, relate to the selection phase. Seven peer reviewed and four non-peer reviewed publications report experimental evidence. All show increased selection for fungicide resistance with increased fungicide dose, except for one peer reviewed publication that does not detect any selection irrespective of dose and one conference proceedings publication which claims evidence for increased selection at a lower dose. In the mathematical models published, no evidence has been found that a lower dose could lead to a higher risk of fungicide resistance selection. We discuss areas of the dose rate debate that need further study. These include further work on pathogen-fungicide combinations where the pathogen develops partial resistance to the fungicide and work on the emergence phase.
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The synthesis of galactooligosaccharides (GOS) by whole cells of Bifidobacterium bifidum NCIMB 41171 was investigated by developing a set of mathematical models. These were second order polynomial equations, which described responses related to the production of GOS constituents, the selectivity of lactose conversion into GOS, and the relative composition of the produced GOS mixture, as a function of the amount of biocatalyst, temperature, initial lactose concentration, and time. The synthesis reactions were followed for up to 36 h. Samples were withdrawn every 4 h, tested for β-galactosidase activity, and analysed for their carbohydrate content. GOS synthesis was well explained by the models, which were all significant (P < 0.001). The GOS yield increased as temperature increased from 40 °C to 60 °C, as transgalactosylation became more pronounced compared to hydrolysis. The relative composition of GOS produced changed significantly with the initial lactose concentration (P < 0.001); higher ratios of tri-, tetra-, and penta-galactooligosaccharides to transgalactosylated disaccharides were obtained as lactose concentration increased. Time was a critical factor, as a balanced state between GOS synthesis and hydrolysis was roughly attained in most cases between 12 and 20 h, and was followed by more pronounced GOS hydrolysis than synthesis.
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We consider the time-harmonic Maxwell equations with constant coefficients in a bounded, uniformly star-shaped polyhedron. We prove wavenumber-explicit norm bounds for weak solutions. This result is pivotal for convergence proofs in numerical analysis and may be a tool in the analysis of electromagnetic boundary integral operators.
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Spiking neural networks are usually limited in their applications due to their complex mathematical models and the lack of intuitive learning algorithms. In this paper, a simpler, novel neural network derived from a leaky integrate and fire neuron model, the ‘cavalcade’ neuron, is presented. A simulation for the neural network has been developed and two basic learning algorithms implemented within the environment. These algorithms successfully learn some basic temporal and instantaneous problems. Inspiration for neural network structures from these experiments are then taken and applied to process sensor information so as to successfully control a mobile robot.
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Property ownership can tie up large amounts of capital and management energy that business could employ more productively elsewhere. Competitive pressures, accounting changes and increasingly sophisticated occupier requirements are building demand for new and innovative ways to satisfy corporate occupation needs. The investment climate is also changing. Falling interest rates and falling inflation can be expected to undermine returns from the traditional FRI lease. In future, investment returns will be more dependent on active and innovative management geared to the needs of occupiers on whom income depends. Occupier and investor interests, therefore, look set to coincide, but unlocking the potential for both parties will depend on developing new finance and investment vehicles that align their respective needs. In the UK, examples include PFI in the public sector and off-balance sheet financing in the private sector. In the USA, “synthetic lease” structures have also become popular. Growing investment market experience in assessing risks and returns suggests scope for further innovative arrangements in the corporate sector. But how can such arrangements be structured? What are the risks, drivers and barriers?
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ESA’s Venus Express Mission has monitored Venus since April 2006, and scientists worldwide have used mathematical models to investigate its atmosphere and model its circulation. This book summarizes recent work to explore and understand the climate of the planet through a research program under the auspices of the International Space Science Institute (ISSI) in Bern, Switzerland. Some of the unique elements that are discussed are the anomalies with Venus’ surface temperature (the huge greenhouse effect causes the surface to rise to 460°C, without which would plummet as low as -40°C), its unusual lack of solar radiation (despite being closer to the Sun, Venus receives less solar radiation than Earth due to its dense cloud cover reflecting 76% back) and the juxtaposition of its atmosphere and planetary rotation (wind speeds can climb up to 200 m/s, much faster than Venus’ sidereal day of 243 Earth-days).
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Proactive motion in hand tracking and in finger bending, in which the body motion occurs prior to the reference signal, was reported by the preceding researchers when the target signals were shown to the subjects at relatively high speed or high frequencies. These phenomena indicate that the human sensory-motor system tends to choose an anticipatory mode rather than a reactive mode, when the target motion is relatively fast. The present research was undertaken to study what kind of mode appears in the sensory-motor system when two persons were asked to track the hand position of the partner with each other at various mean tracking frequency. The experimental results showed a transition from a mutual error-correction mode to a synchronization mode occurred in the same region of the tracking frequency with that of the transition from a reactive error-correction mode to a proactive anticipatory mode in the mechanical target tracking experiments. Present research indicated that synchronization of body motion occurred only when both of the pair subjects operated in a proactive anticipatory mode. We also presented mathematical models to explain the behavior of the error-correction mode and the synchronization mode.
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Soil-dwelling insect herbivores are significant pests in many managed ecosystems. Because eggs and larvae are difficult to observe, mathematical models have been developed to predict life-cycle events occurring in the soil. To date, these models have incorporated very little empirical information about how soil and drought conditions interact to shape these processes. This study investigated how soil temperature (10, 15, 20 and 25 °C), water content (0.02 (air dried), 0.10 and 0.25 g g−1) and pH (5, 7 and 9) interactively affected egg hatching and early larval lifespan of the clover root weevil (Sitona lepidus Gyllenhal, Coleoptera: Curculionidae). Eggs developed over 3.5 times faster at 25 °C compared with 10 °C (hatching after 40.1 and 11.5 days, respectively). The effect of drought on S. lepidus eggs was investigated by exposing eggs to drought conditions before wetting the soil (2–12 days later) at four temperatures. No eggs hatched in dry soil, suggesting that S. lepidus eggs require water to remain viable. Eggs hatched significantly sooner in slightly acidic soil (pH 5) compared with soils with higher pH values. There was also a significant interaction between soil temperature, pH and soil water content. Egg viability was significantly reduced by exposure to drought. When exposed to 2–6 days of drought, egg viability was 80–100% at all temperatures but fell to 50% after 12 days exposure at 10 °C and did not hatch at all at 20 °C and above. Drought exposure also increased hatching time of viable eggs. The effects of soil conditions on unfed larvae were less influential, except for soil temperature which significantly reduced larval longevity by 57% when reared at 25 °C compared with 10 °C (4.1 and 9.7 days, respectively). The effects of soil conditions on S. lepidus eggs and larvae are discussed in the context of global climate change and how such empirically based information could be useful for refining existing mathematical models of these processes.
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A central difficulty in modeling epileptogenesis using biologically plausible computational and mathematical models is not the production of activity characteristic of a seizure, but rather producing it in response to specific and quantifiable physiologic change or pathologic abnormality. This is particularly problematic when it is considered that the pathophysiological genesis of most epilepsies is largely unknown. However, several volatile general anesthetic agents, whose principle targets of action are quantifiably well characterized, are also known to be proconvulsant. The authors describe recent approaches to theoretically describing the electroencephalographic effects of volatile general anesthetic agents that may be able to provide important insights into the physiologic mechanisms that underpin seizure initiation.
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The inhibitory effects of toxin-producing phytoplankton (TPP) on zooplankton modulate the dynamics of marine plankton. In this article, we employ simple mathematical models to compare theoretically the dynamics of phytoplankton–zooplankton interaction in situations where the TPP are present with those where TPP are absent. We consider two sets of three-component interaction models: one that does not include the effect of TPP and the other that does. The negative effects of TPP on zooplankton is described by a non-linear interaction term. Extensive theoretical analyses of the models have been performed to understand the qualitative behaviour of the model systems around every possible equilibria. The results of local-stability analysis and numerical simulations demonstrate that the two model-systems differ qualitatively with regard to oscillations and stability. The model system that does not include TPP is asymptotically stable around the coexisting equilibria, whereas, the system that includes TPP oscillates for a range of parametric values associated with toxin-inhibition rate and competition coefficients. Our analysis suggests that the qualitative dynamics of the plankton–zooplankton interactions are very likely to alter due to the presence of TPP species, and therefore the effects of TPP should be considered carefully while modelling plankton dynamics.
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Real estate securities have a number of distinct characteristics that differentiate them from stocks generally. Key amongst them is that under-pinning the firms are both real as well as investment assets. The connections between the underlying macro-economy and listed real estate firms is therefore clearly demonstrated and of heightened importance. To consider the linkages with the underlying macro-economic fundamentals we extract the ‘low-frequency’ volatility component from aggregate volatility shocks in 11 international markets over the 1990-2014 period. This is achieved using Engle and Rangel’s (2008) Spline-Generalized Autoregressive Conditional Heteroskedasticity (Spline-GARCH) model. The estimated low-frequency volatility is then examined together with low-frequency macro data in a fixed-effect pooled regression framework. The analysis reveals that the low-frequency volatility of real estate securities has strong and positive association with most of the macroeconomic risk proxies examined. These include interest rates, inflation, GDP and foreign exchange rates.
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Industrial robotic manipulators can be found in most factories today. Their tasks are accomplished through actively moving, placing and assembling parts. This movement is facilitated by actuators that apply a torque in response to a command signal. The presence of friction and possibly backlash have instigated the development of sophisticated compensation and control methods in order to achieve the desired performance may that be accurate motion tracking, fast movement or in fact contact with the environment. This thesis presents a dual drive actuator design that is capable of physically linearising friction and hence eliminating the need for complex compensation algorithms. A number of mathematical models are derived that allow for the simulation of the actuator dynamics. The actuator may be constructed using geared dc motors, in which case the benefits of torque magnification is retained whilst the increased non-linear friction effects are also linearised. An additional benefit of the actuator is the high quality, low latency output position signal provided by the differencing of the two drive positions. Due to this and the linearised nature of friction, the actuator is well suited for low velocity, stop-start applications, micro-manipulation and even in hard-contact tasks. There are, however, disadvantages to its design. When idle, the device uses power whilst many other, single drive actuators do not. Also the complexity of the models mean that parameterisation is difficult. Management of start-up conditions still pose a challenge.
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The issue of imperfect information plays a much more important role in financing “informationally opaque” small businesses than in financing large companies.1 This chapter examines the asymmetric information issue in entrepreneurial finance from two perspectives: the effects of relationship lending and the impacts of credit market concentration on entrepreneurial financial behavior. These two perspectives are strongly linked to each other via the asymmetric information issue in entrepreneurial finance. Existing literature has recognized the important role played by relationship lending in alleviating the problem of asymmetric information. However, mixed empirical results have been reported. For example, it has been found that the development of relationship lending can improve the availability of finance for small businesses borrowers (Petersen and Rajan, 1994) and reduce the costs of finance (Berger and Udell, 1995). Meanwhile, with monopoly power, banks may extract rents, in terms of charging higher-than-market interest rates, from small businesscustomers who have very concentrated banking relationships (Ongena and Smith, 2001). In addition, both favorable and unfavorable effects of credit market concentration on financing small businesses have been acknowledged. Small business borrowers may have to pay a higher-than-market price on loans (Degryse and Ongena, 2005) and are more likely to be financially constrained (Cetorelli, 2004) than in competitive markets. On the other hand, empirical studies have shown that market concentration create a strong motive for lenders to invest in private information from small business customers, and therefore a concentrated market is more efficient in terms of private information acquisition (Han et al., 2009b). The objective of this chapter is to investigate, by reviewing existing literature, the role played by relationship lending and the effects of market concentration on financing entrepreneurial businesses that are supposed to be informationally opaque. In the first section we review literature on the important role played by asymmetric information in entrepreneurial finance from two perspectives: asymmetric information and relationship lending, and the theoretical modeling of asymmetric information. Then we examine the relationship between capital market conditions and entrepreneurial finance and attempt to answer two questions: Why is the capital market condition important for entrepreneurial finance? and What are the effects of capital market conditions on entrepreneurial financial behavior in terms of discouraged borrowers, cash holding, and the availability and costs of finance?