On the robustness of short-term interest rate models

This paper investigates the robustness of a range of short–term interest rate models. We examine the robustness of these models over different data sets, time periods, sampling frequencies, and estimation techniques. We examine a range of popular one–factor models that allow the conditional mean (drift) and conditional variance (diffusion) to be functions of the current short rate. We find that parameter estimates are highly sensitive to all of these factors in the eight countries that we examine. Since parameter estimates are not robust, these models should be used with caution in practice.

Modelos de previsão de inflação e estudo da dinâmica inflacionária brasileira

O objetivo dessa dissertação é analisar as variáveis importantes da inflação para a decisão de política econômica do Banco Central. Considerando a importância de reações forward looking das autoridades monetárias num regime de metas de inflação, estudam-se alguns modelos de projeção de inflação de curto prazo para verificar qual modelo possui maior capacidade de previsão. Com o objetivo de entender a dinâmica inflacionária brasileira ao longo desses anos desde a implementação do sistema de metas de inflação, procura-se analisar a dinâmica da inércia inflacionária e do repasse cambial.

Short-Term Load Forecast Of A Low Loadfactor Power System For Optimization Of Merit Order Dispatch Using Adaptive Learning Algorithm

Short term load forecasting is one of the key inputs to optimize the management of power system. Almost 60-65% of revenue expenditure of a distribution company is against power purchase. Cost of power depends on source of power. Hence any optimization strategy involves optimization in scheduling power from various sources. As the scheduling involves many technical and commercial considerations and constraints, the efficiency in scheduling depends on the accuracy of load forecast. Load forecasting is a topic much visited in research world and a number of papers using different techniques are already presented. The accuracy of forecast for the purpose of merit order dispatch decisions depends on the extent of the permissible variation in generation limits. For a system with low load factor, the peak and the off peak trough are prominent and the forecast should be able to identify these points to more accuracy rather than minimizing the error in the energy content. In this paper an attempt is made to apply Artificial Neural Network (ANN) with supervised learning based approach to make short term load forecasting for a power system with comparatively low load factor. Such power systems are usual in tropical areas with concentrated rainy season for a considerable period of the year

Concreteness effects in different tasks: implications for models of short-term memory

This study investigates concreteness effects in tasks requiring short-term retention. Concreteness effects were assessed in serial recall, matching span, order reconstruction, and free recall. Each task was carried out both in a control condition and under articulatory suppression. Our results show no dissociation between tasks that do and do not require spoken output. This argues against the redintegration hypothesis according to which lexical-semantic effects in short-term memory arise only at the point of production. In contrast, concreteness effects were modulated by task demands that stressed retention of item versus order information. Concreteness effects were stronger in free recall than in serial recall. Suppression, which weakens phonological representations, enhanced the concreteness effect with item scoring. In a matching task, positive effects of concreteness occurred with open sets but not with closed sets of words. Finally, concreteness effects reversed when the task asked only for recall of word positions (as in the matching task), when phonological representations were weak (because of suppression), and when lexical semantic representations overactivated (because of closed sets). We interpret these results as consistent with a model where phonological representations are crucial for the retention of order, while lexical-semantic representations support maintenance of item identity in both input and output buffers.

Real-time energy resources scheduling considering short-term and very short-term wind forecast

This paper proposes an energy resources management methodology based on three distinct time horizons: day-ahead scheduling, hour-ahead scheduling, and real-time scheduling. In each scheduling process it is necessary the update of generation and consumption operation and of the storage and electric vehicles storage status. Besides the new operation condition, it is important more accurate forecast values of wind generation and of consumption using results of in short-term and very short-term methods. A case study considering a distribution network with intensive use of distributed generation and electric vehicles is presented.

Metaheuristic approach to the Holt-Winters optimal short term load forecast

Electricity short-term load forecast is very important for the operation of power systems. In this work a classical exponential smoothing model, the Holt-Winters with double seasonality was used to test for accurate predictions applied to the Portuguese demand time series. Some metaheuristic algorithms for the optimal selection of the smoothing parameters of the Holt-Winters forecast function were used and the results after testing in the time series showed little differences among methods, so the use of the simple local search algorithms is recommended as they are easier to implement.

Metaheuristhic approach to the Holt-Winters optimal short term load forecast

Electricity short-term load forecast is very important for the operation of power systems. In this work a classical exponential smoothing model, the Holt-Winters with double seasonality was used to test for accurate predictions applied to the Portuguese demand time series. Some metaheuristic algorithms for the optimal selection of the smoothing parameters of the Holt-Winters forecast function were used and the results after testing in the time series showed little differences among methods, so the use of the simple local search algorithms is recommended as they are easier to implement.

Optimization of short term power trading between Russia, Finland and Baltic countries

Russian and Baltic electricity markets are in the process of reformation and development on the way for competitive and transparent market. Nordic market also undergoes some changes on the way to market integration. Old structure and practices have been expired whereas new laws and rules come into force. The master thesis describes structure and functioning of wholesale electricity markets, cross-border connections between different countries. Additionally methods of cross-border trading using different methods of capacity allocation are disclosed. The main goal of present thesis is to study current situation at different electricity markets and observe changes coming into force as well as the capacity and electricity balances forecast in order to optimize short term power trading between countries and estimate the possible profit for the company.

Influence of short term climatic fluctuations on the agricultural land use in Kerala

In the present study, the land use over Kerala State and its spatial and temporal variations, spatio-temporal variations of water budget elements, climatic shifts, incidence of droughts and the influence of inter-annual fluctuations of rainfall on area. production and yield of selected crops, have been studied in detail. The thesis consists of seven chapters including the introduction. The first section of the Second Chapter deals with the importance of agrocliinatological studies in general and its application in agricultural land use in particular. It also gives an overview of the short term climatic fluctuations, water balance studies, crop weather relationships, land use patterns and various agricultural indices. This includes a detailed review of available literature in this field. The basic concepts. data used and the methodology adopted in the study forms, the second section of this Chapter. The Third Chapter gives the details of the physical features of the State such as the relief, geology, geomorphologysoils, drainage, and vegetation. The agroclimatology of the State is discussed in detail in Chapter Four. The first Section presents annual and seasonal variations of temperature and rainfall of the State along with a discussion on the water balance of the State. The secondSection of this Chapter deals with the influence of rainfall and water balance elements on various crops. The district-wise general land use pattern of theState and its spatio-temporal variations are discussed in Chapter Five. The first Section of Chapter Six gives an overview of the agricultural land use pattern of the State, cropping patterns, cropping intensity, crop combination and their spatio-temporal variations. The inter-annual variability of water balances of various stations of the State computed using the method of Thornthwaite (1948) and Thornthwaite & Mather (1955) is presented in the second Section of Chapter Six. This also includes a discussion of how the climatic shifts have occurred over the State and the influence of variations of climatic and water balance elements on the crops. The Seventh Chapter gives the summary of the work carried out and the results obtained from the study. Interpretations of the results, conclusions and suggestions made,based on the observations of the study are incorporated in this Chapter.

Incorporating voltage/reactive representation to short-term generation scheduling models

This paper proposes a methodology to incorporate voltage/reactive representation to Short Term Generation Scheduling (STGS) models, which is based on active/reactive decoupling characteristics of power systems. In such approach STGS is decoupled in both Active (AGS) and Reactive (RGS) Generation Scheduling models. AGS model establishes an initial active generation scheduling through a traditional dispatch model. The scheduling proposed by AGS model is evaluated from the voltage/reactive points of view, through the proposed RGS model. RGS is formulated as a sequence of T nonlinear OPF problems, solved separately but taking into account load tracking between consecutive time intervals. This approach considerably reduces computational effort to perform the reactive analysis of the RGS problem as a whole. When necessary, RGS model is capable to propose active generation redispatches, such that critical reactive problems (in which all reactive variables have been insufficient to control the reactive problems) can be overcome. The formulation and solution methodology proposed are evaluated in the IEEE30 system in two case studies. These studies show that the methodology is robust enough to incorporate reactive aspects to STGS problem.

Quantification of uncertainties associated with space-time estimates of short-term soil CO2 emissions in a sugar cane area

The characterization of soil CO2 emissions (FCO2) is important for the study of the global carbon cycle. This phenomenon presents great variability in space and time, a characteristic that makes attempts at modeling and forecasting FCO2 challenging. Although spatial estimates have been performed in several studies, the association of these estimates with the uncertainties inherent in the estimation procedures is not considered. This study aimed to evaluate the local, spatial, local-temporal and spatial-temporal uncertainties of short-term FCO2 after harvest period in a sugar cane area. The FCO2 was featured in a sampling grid of 60m×60m containing 127 points with minimum separation distances from 0.5 to 10m between points. The FCO2 was evaluated 7 times within a total period of 10 days. The variability of FCO2 was described by descriptive statistics and variogram modeling. To calculate the uncertainties, 300 realizations made by sequential Gaussian simulation were considered. Local uncertainties were evaluated using the probability values exceeding certain critical thresholds, while the spatial uncertainties considering the probability of regions with high probability values together exceed the adopted limits. Using the daily uncertainties, the local-spatial and spatial-temporal uncertainty (Ftemp) was obtained. The daily and mean emissions showed a variability structure that was described by spherical and Gaussian models. The differences between the daily maps were related to variations in the magnitude of FCO2, covering mean values ranging from 1.28±0.11μmolm-2s-1 (F197) to 1.82±0.07μmolm-2s-1 (F195). The Ftemp showed low spatial uncertainty coupled with high local uncertainty estimates. The average emission showed great spatial uncertainty of the simulated values. The evaluation of uncertainties associated with the knowledge of temporal and spatial variability is an important tool for understanding many phenomena over time, such as the quantification of greenhouse gases or the identification of areas with high crop productivity. © 2013 Elsevier B.V.

Impact of short-term preconceptional exposure to particulate air pollution on treatment outcome in couples undergoing in vitro fertilization and embryo transfer (IVF/ET)

To assess the potential effects of short-term exposure to particulate air pollution during follicular phase on clinical, laboratory, and pregnancy outcomes of women undergoing IVF/ET. Retrospective cohort study of 400 first IVF/ET cycles of women exposed to ambient particulate matter during follicular phase. Particulate matter (PM) was categorized into quartiles (Q(1): a parts per thousand currency sign30.48 A mu g/m(3), Q(2): 30.49-42.00 A mu g/m(3), Q(3): 42.01-56.72 A mu g/m(3), and Q(4): > 56.72 A mu g/m(3)). Clinical, laboratory, or treatment variables were not affected by follicular phase PM exposure periods. Women exposed to Q(4) period during the follicular phase of conception cycles had a higher risk of miscarriage (odds ratio, 5.05; 95% confidence interval: 1.04-25.51) when compared to women exposed to Q(1-3) periods. Our results show an association between brief exposure to high levels of ambient PM during the preconceptional period and early pregnancy loss, although no effect of this exposure on clinical, laboratory, and treatment outcomes was observed.

Consequences of lifetime isolated growth hormone (GH) deficiency and effects of short-term GH treatment on bone in adults with a mutation in the GHRH-receptor gene

Growth hormone (GH) influences bone mass maintenance. However, the consequences of lifetime isolated GH deficiency (IGHD) on bone are not well established. We assessed the bone status and the effect of 6 months of GH replacement in GH-naive adults with IGHD due to a homozygous mutation of the GH-releasing hormone (GHRH)-receptor gene (GHRHR). We studied 20 individuals (10 men) with IGHD at baseline, after 6 months of depot GH treatment, and 6 and 12 months after discontinuation of GH. Quantitative ultrasound (QUS) of the heel was performed and serum osteocalcin (OC) and C-terminal cross-linking telopeptide of type I collagen (ICTP) were measured. QUS was also performed at baseline and 12 months later in a group of 20 normal control individuals (CO), who did not receive GH treatment. At baseline, the IGHD group had a lower T-score on QUS than CO (-1.15 +/- 0.9 vs. -0.07 +/- 0.9, P < 0.001). GH treatment improved this parameter, with improvement persisting for 12 months post-treatment (T-score for IGHD = -0.59 +/- 0.9, P < 0.05). GH also caused an increase in serum OC (baseline vs. pGH, P < 0.001) and ICTP (baseline vs. pGH, P < 0.01). The increase in OC was more marked during treatment and its reduction was slower after GH discontinuation than in ICTP. These data suggest that lifetime severe IGHD is associated with significant reduction in QUS parameters, which are partially reversed by short-term depot GH treatment. The treatment induces a biochemical pattern of bone anabolism that persists for at least 6 months after treatment discontinuation.

Effects of short-term acetaminophen and celecoxib treatment on orthodontic tooth movement and neuronal activation in rat

Non-steroidal anti-inflammatory drugs (NSAIDs) have been used for pain relief in orthodontics, but clinical studies reported that they may reduce tooth movement (TM). By other side, TM seems to activate brain structures related to nociception, but the effects of NSAIDs in this activation have not been studied yet. We analyzed the effect of short-term treatment with acetaminophen or celecoxib in the separation of rat upper incisors, as well as in neuronal activation of the spinal trigeminal nucleus, following tooth movement. Thirty rats (400-420 g) were pretreated through oral gavage (1 ml/dose)with acetaminophen (200 mg/kg), celecoxib (50 mg/kg) or vehicle (carboxymethylcellulose 0.4%). After 30 min, they received an activated (30 g) orthodontic appliance for TM. In controls, this appliance was immediately removed after its introduction. Rats received ground food, and every 12 h, one of the drugs or vehicle. After 48 h, they were anesthetized, maxilla was radiographed, and were perfused with 4% paraformaldehyde. Brains were further processed for Fos immunohistochemistry. TM induced incisor distalization (p < 0.05) and neuronal activation of the spinal trigeminal nucleus. Treatment with both drugs did not affect tooth movement, but reduced c-fos expression in the caudalis subnucleus. No changes in c-fos expression were seen in the oralis and interpolaris subnuclei. We conclude that neither celecoxib nor acetaminophen seems to affect tooth movement, when used for 2 days, but both drugs are able to reduce the activation of brain structures related to nociception. Short-term treatment with celecoxib, thus, may be a therapeutic alternative to acetaminophen when the latter is contra indicated. (C) 2009 Elsevier Inc. All rights reserved.