Threshold Model

The aim of this paper is to determine the optimal Taylor-type rule and the appropriate variables for the Tunisian economy in its conduct of the economic policy. Our starting point is the traditional Taylor rule. The results of the estimation of the reaction function in its static version confirm the hypothesis that Tunisia has been leading an efficient policy to control its inflation. Based on Akaike and Schwarz criteria, the results indicate that the static model better represents the reaction function of the Reserve Bank of Tunisia.

The objective of this study is to explore the inflation-economic growth linkage, if any, in Bangladesh. With this view, various tables and charts, correlation matrices, pair-wise Granger Causality tests and a quadratic regression equation estimated by OLS based on time series annual data covering the sample period from 1976 to 2012 are used. The results of all the data including regression analysis convincingly demonstrate that the relationship between inflation and growth is non-linear with an existence of a threshold level of inflation within the range of 7-8 percent. This implies that targeting too low an inflation level (relative to the threshold) would be hurtful for growth in terms of potential cost of forgone output and, at the same time, too high level of inflation would also impede economic growth. Thus, Government's inflation target of 7.5 percent set in FY12/13 budget seems to be reasonable as it stands within the estimated range of threshold levels of inflation found in the study. Despite recent moderating trends in inflation, current restrictive monetary policy stance of Bangladesh Bank seems to be in the right direction, as inflation is still running far beyond indicated threshold level. Besides, continuous coordinated efforts are required to contain inflation around the threshold band of 7-8 percent inflation for the sake of optimal economic growth in Bangladesh.

In this chapter, we establish limit theorems for some statistics based on order statistics and record values. The finite-sample as well as asymptotic properties of statistics based on invariant confidence intervals are investigated and their use in statistical inference is outlined.

This paper uses household and village-level survey data to investigate the food security of male-and female-headed households in Bangladesh with particular attention to indigenous ethnic groups, and finds no significant differences in the food security between these two types of households. The absence of social and cultural restrictions among the indigenous groups permitting their females greater freedom to participate in the labor force coupled with informal redistributive mechanism is attributed to their less food insecurity. This result indicates that noneconomic institutions can significantly impact economic outcomes such as food security.

Various efforts ([?, ?, ?]) have been made in recent years to derandomize probabilistic algorithms using the complexity theoretic assumption that there exists a problem in E = dtime(2 O(n) ), that requires circuits of size s(n), (for some function s). These results are based on the NW-generator [?]. For the strong lower bound s(n) = 2 n , [?], and later [?] get the optimal derandomization, P = BP P . However, for weaker lower bound functions s(n), these constructions fall far short of the natural conjecture for optimal derandomization, namely that bptime(t) ⊆ dtime(2 O(s -1 (t)) ). The gap in these constructions is due to an inherent limitation on efficiency in NW-style pseudo-random generators. In this paper we are able to get derandomization in almost optimal time using any lower bound s(n). We do this by using the NW-generator in a new, more sophisticated way. We view any failure of the generator as a reduction from the given "hard" function to its restrictions on smaller input sizes. Thus, either the original construction works (almost) optimally, or one of the restricted functions is (almost) as hard as the original. Any such restriction can then be plugged into the NW-generator recursively. This process generates many "candidate" generators -all are (almost) optimal, and at least one is guaranteed to be "good". Then, to perform the approximation of the acceptance probability of the given circuit (which is the key to derandomization), we use ideas from [?]: we run a tournament between the "candidate" generators which yields an accurate estimate. Following Trevisan, we explore information theoretic analogs of our new construction. Trevisan [?] (and then [?]) used the NW-generator to construct efficient extractors. However, the inherent limitation of the NW-generator mentioned above makes the extra randomness required by that extractor suboptimal (for certain parameters). Applying our construction, we show how to use a weak random souce with optimal amount of extra randomness, for the (simpler than extraction) task of estimating the probability of any event (which is given by an oracle).

Min-entropy is a statistical measure of the amount of randomness that a particular distribution contains. In this paper we investigate the notion of computational min-entropy which is the computational analog of statistical min-entropy. We consider three possible definitions for this notion, and show equivalence and separation results for these definitions in various computational models. We also study whether or not certain properties of statistical min-entropy have a computational analog. In particular, we consider the following questions: 1. Let X be a distribution with high computational min-entropy. Does one get a pseudorandom distribution when applying a "randomness extractor" on X? 2. Let X and Y be (possibly dependent) random variables. Is the computational min-entropy of (X, Y ) at least as large as the computational min-entropy of X? 3. Let X be a distribution over {0, 1} n that is "weakly unpredictable" in the sense that it is hard to predict a constant fraction of the coordinates of X with a constant bias. Does X have computational min-entropy Ω(n)? We show that the answers to these questions depend on the computational model considered. In some natural models the answer is false and in others the answer is true. Our positive results for the third question exhibit models in which the "hybrid argument bottleneck" in "moving from a distinguisher to a predictor" can be avoided.

The Nisan-Wigderson pseudo-random generator [NW94] was constructed to derandomize probabilistic algorithms under the assumption that there exist explicit functions which are hard for small circuits. We give the first explicit construction of a pseudo-random generator with asymptotically optimal seed length even when given a function which is hard for relatively small circuits. Generators with optimal seed length were previously known only assuming hardness for exponential size circuits [IW97, STV01]. We also give the first explicit construction of an extractor which uses asymptotically optimal seed length for random sources of arbitrary min-entropy. Our construction is the first to use the optimal seed length for sub-polynomial entropy levels. It builds on the fundamental connection between extractors and pseudo-random generators discovered by Trevisan [Tre01], combined with the construction above. The key is a new analysis of the NW-generator [NW94]. We show that it fails to be pseudo random only if a much harder function can be efficiently constructed from the given hard function. By repeatedly using this idea we get a new recursive generator, which may be viewed as a reduction from the general case of arbitrary hardness to the solved case of exponential hardness. * This paper is based on two conference papers [ISW99, ISW00] by the same authors.

This paper treats estimation in a class of new nonlinear threshold autoregressive models with both a stationary and a unit root regime. Existing literature on nonstationary threshold models have basically focused on models where the nonstationarity can be removed by differencing and/or where the threshold variable is stationary. This is not the case for the process we consider, and nonstandard estimation problems are the result. This paper proposes a parameter estimation method for such nonlinear threshold autoregressive models using the theory of null recurrent Markov chains. Under certain assumptions, we show that the ordinary least squares (OLS) estimators of the parameters involved are asymptotically consistent. Furthermore, it can be shown that the OLS estimator of the coefficient parameter involved in the stationary regime can still be asymptotically normal while the OLS estimator of the coefficient parameter involved in the nonstationary regime has a nonstandard asymptotic distribution. In the limit, the rate of convergence in the stationary regime is asymptotically proportional to n -1 4 , whereas it is n -1 in the nonstationary regime. The proposed theory and estimation method are illustrated by both simulated data and a real data example.

We develop a new method to estimate the parameters of threshold distributions for market participation based upon an agent-specific attribute and its decision outcome. This method requires few behavioral assumptions, is not data demanding, and can adapt to various parametric distributions. Monte Carlo simulations show that the algorithm successfully recovers three different parametric distributions and is resilient to assumption violations. An application to export decisions by French firms shows that threshold distributions are generally right-skewed. We then reveal the asymmetric effects of past policies over different quantiles of the threshold distributions.

Foram obtidas estimativas de herdabilidade e preditas diferenças esperadas na progênie para probabilidade de permanência no rebanho (stayability) de 4180 touros com filhas na base de dados do Programa de Melhoramento Genético da Raça Nelore. Modelo de limiar e modelo linear foram utilizados sob análise Bayesiana via software multiple-trait Gibbs sampler for animal models. A implementação adotada considerou tamanho de cadeia de Gibbs de 225 mil, período de descarte amostral de 25 mil e tomada de amostra a cada mil rodadas. As estimativas de herdabilidade foram de menor magnitude para o modelo linear, 0,065, contra 0,158 sob modelo de limiar. Quando transformadas para escala normal subjacente, o valor obtido ficou em 0,13±0,05, bem próximo àquele encontrado sob modelo de limiar. A correlação entre classificações foi de 97%. O modelo de análise considerado para stayability, sob enfoque bayesiano, parece não influenciar a classificação dos animais quanto aos valores genéticos preditos. ...

We propose a new GARCH model with tree-structured multiple thresholds for volatility estimation in financial time series. The approach relies on the idea of a binary tree where every terminal node parameterizes a (local) GARCH model for a partition cell of the predictor space. Fitting of such trees is constructed within the likelihood framework for non-Gaussian observations: it is very different from the well-known CART procedure for regression based on residual sum of squares. Our strategy includes the classical GARCH model and allows in a systematic and flexible way to increase model-complexity. We conclude with simulations and real data analysis that the new method has better predictive potential compared to other approaches.

We argue that given even an infinitely long data sequence, it is impossible (with any test statistic) to distinguish perfectly between linear and nonlinear processes (including slightly noisy chaotic processes). Our approach is to consider the set of moving-average (linear) processes and study its closure under a suitable metric. We give the precise characterization of this closure, which is unexpectedly large, containing nonergodic processes, which are Poisson sums of independent and identically distributed copies of a stationary process. Proofs of these results will appear elsewhere.

We propose a new GARCH model with tree-structured multiple thresholds for volatility estimation in financial time series. The approach relies on the idea of a binary tree where every terminal node parameterizes a (local) GARCH model for a partition cell of the predictor space. Fitting of such trees is constructed within the likelihood framework for non-Gaussian observations: it is very different from the well-known CART procedure for regression based on residual sum of squares. Our strategy includes the classical GARCH model and allows in a systematic and flexible way to increase model-complexity. We conclude with simulations and real data analysis that the new method has better predictive potential compared to other approaches.

We describe some limitations of econometrics, starting with one of the basic tools (simple linear regression), presenting how and why such methods do not necessarily seem to do what is purported by researchers investigating certain types of phenomena. We go through descriptive arguments with some mathematical intuition. The observations hint at why such methods might not work out of sample, which should motivate one to build more suitable methods. Assumptions should thus be verified before using econometric analyses.

In [H] it is proven, among other things, that the size of any depth k circuit computing the parity or the majority function is n(2o. 1 (o.311)""-u). In th'is note we generalize th~ptoof given there to yield similar lower bounds•for arbitrary .symmetric functions of {O,l}". This irpprpves results in [FKPS], where it was shown that the non-existence cf polynomi'!1-size; constant-depth circuits for the majority function implies the non-existence of such circuits for other symmetric fUl'lctions. • • . . f d • ,.

Este artigo analisa o processo de convergência do valor da produção agrícola dos municípios cearenses utilizando um modelo com efeito threshold no período de 1970 a 1996. Os resultados mostraram a existência de quatro clubes de convergência. Um formado pelo grupo de municípios mais ricos, outro formado pelo grupo de municípios mais pobres e dois grupos intermediários. Os resultados intra-clubes indicam que tanto o capital humano como o capital físico são importantes na explicação do processo de crescimento da agricultura cearense. Já os resultados para a terra mostraram que este fator é importante apenas para os dois clubes mais ricos.

Este artigo analisa o processo de convergência do valor da produção agrícola dos municípios cearenses utilizando um modelo com efeito threshold no período de 1970 a 1996. Os resultados mostraram a existência de quatro clubes de convergência. Um formado pelo grupo de municípios mais ricos, outro formado pelo grupo de municípios mais pobres e dois grupos intermediários. Os resultados intra-clubes indicam que tanto o capital humano como o capital físico são importantes na explicação do processo de crescimento da agricultura cearense. Já os resultados para a terra mostraram que este fator é importante apenas para os dois clubes mais ricos.

In this paper, a physically based two-dimensional analytical model of potential profile is proposed for both symmetric and asymmetric p-type-doped Double Gate Junctionless Field Effect Transistors (DG JLFETs). The proposed model keeps its validity in the subthreshold region. In order to establish the model, 2-D Poisson's equation is solved in the channel region while assuming cubic potential distribution along the channel region. We also propose a 2-D analytical model of symmetric Double Gate Stack-Oxide Junctionless Field Effect Transistors (DGS JLFETs). In order to check out the validity of our proposed model, we have used SILVACO ATLAS simulator. Comparison of potential distribution is made between different structures. Between symmetric and asymmetric structures, symmetric structure shows better potential profile as they have shown higher potential distribution in channel region. But when DG JLFET is compared with DGS JLFET, we find better potential profile distribution in DGS JLFET. Important performance parameters like I on /I off ratio, SS, DIBL, Threshold Voltage, I-V characteristics for different structures are found out and compared among them. Asymmetric structure with same electrode materials in both gates but having lower bottom gate oxide thickness showed better performances like higher I on /I off ratio, lower SS, less DIBL compared to other DG JLFETs with and without stack oxide.

This study tests a key behavioral prediction of Prospect Theory: whether stock returns differ after previous-day gains versus losses. Using daily data from the S&P 100 over the past year, we examine whether nextday returns are systematically lower after losses. We find that only a minority of stocks exhibit statistically significant behavior consistent with loss aversion.

Background-Studies evaluating circulating dendritic cells (DCs) and natural and induced regulatory T cells (nTregs, iTregs) are often obtained at a single time point and difficult to interpret without understanding their intrinsic day-to-day biologic variability. Methods-We investigated the day-to-day variability in quantifying DCs, nTregs (FoxP3+CD25+CD4+) and cytokine production by iTregs (Granzyme B -GZB, Th1/2 cytokines following CD3 plus CD46 in vitro activation) from peripheral blood mononuclear cells (PBMC) collected on three consecutive days in healthy adults. Intraclass correlation coefficients (ICC) were used to evaluate intra-individual variability. Results-In 10 healthy adults, the %PBMC of plasmacytoid (pDC) and myeloid (mDC1 and mDC2) were 0.27±0.12, 0.22±0.10, and 0.02±0.02, with ICC 0.91, 0.90, and 0.17 respectively. Natural Tregs (3.27±1.27% CD4+ cells) had an ICC of 0.86. Inducible Tregs (GZB-positive, 35.3±17.7% CD4+ cells) had an ICC of 0.77. The ICC for IL-10, TNF-α, IFN-γ, IL-4, and IL-5 production by iTregs were 0.49, 0.63, 0.68, 0.74, and 0.82, respectively. There were no significant changes in ICC (<0.1) after adjusting for age, gender and atopy except for IL-4. Substantial variability for iTregs was determined for the control condition (PBS with IL-2).

In this chapter, we establish limit theorems for some statistics based on order statistics and record values. The finite-sample as well as asymptotic properties of statistics based on invariant confidence intervals are investigated and their use in statistical inference is outlined.

The Man-machine Integrated Design and Analysis System (MIDAS) is an integrated human performance modeling software tool that symbolically represents a human's perceptual, cognitive and motor systems in an integrated fashion to produce emergent, high level behavioral predictions characteristic of actual human performance. MIDAS has been augmented in a number of significant ways to simulate even more realistic simulations of human behavior in various aerospace operational contexts. The effort undertaken in the current project culminated in an agent-based sub model (e.g. slots) that can be used by a variety of models to predict and recreate short-and long-term effects of stressors (fatigue, stress, time pressure, inadequate situation awareness, etc.) on performance in aerospace accidents/incidents causation. A computational simulation demonstrated performance influences brought to task performance by fatigue (as characterized by the Yerkes-Dodson theoretical threshold model) that is incurred while undertaking activities required to complete a goal behavior, and the impact of performance-influencing factors (PIFs) on human performance output by combining this with a primitive based action error vulnerability. This paper discusses the computational development effort undertaken in creating the conceptual relationship and PIF implementation in MIDAS.

Dual-process theory, which holds that recognition decisions can be based on recollection or familiarity, has long seemed incompatible with signal detection theory, which holds that recognition decisions are based on a singular, continuous memory-strength variable. Formal dual-process models typically regard familiarity as a continuous process (i.e., familiarity comes in degrees), but they construe recollection as a categorical process (i.e., recollection either occurs or does not occur). A continuous process is characterized by a graded relationship between confidence and accuracy, whereas a categorical process is characterized by a binary relationship such that high confidence is associated with high accuracy but all lower degrees of confidence are associated with chance accuracy. Using a source-memory procedure, we found that the relationship between confidence and source-recollection accuracy was graded. Because recollection, like familiarity, is a continuous process, dual-process theory is more compatible with signal detection theory than previously thought.

People are generally skilled at using a confidence scale to rate the strength of their memories over a wide range. Specifically, low-confidence recognition decisions are often associated with close-to-chance accuracy, whereas high-confidence recognition decisions can be associated with close-to-perfect accuracy. However, using a 20-point rating scale, the authors found that the ability to scale memory strength had its limitations in that a high proportion of list items received the highest rating of 20. Efforts to induce participants to differentiate between these strong memories using emphatic instructions and alternative scales were not successful. Remember/know judgments indicated that these strong and hard-to-scale memories were often based on familiarity (not just recollection). Providing error feedback on a plurals discrimination task finally produced a high-confidence criterion shift. The authors suggest that the ability to scale strong (and almost perfectly accurate) memories may be limited because of the absence of differential error feedback for very strong memories in the past (the kind of differential error feedback that may account for the memory-scaling expertise that participants otherwise exhibit).

for an Invited Paper for the MAR10 Meeting of the American Physical Society Simple models for ultracold molecular collisions PAUL S. JULIENNE, Joint Quantum Institute, NIST and the University of Maryland A simple yet general model of reactive collisions having a quantum defect form is possible based on the separation of the collision dynamics into a long range and a short range part. 1 2 The long range region governs the quantum transmission of the incident de Broglie wave into the short range region, where reaction occurs. The van der Waals interaction is characterized by a length scale on the order of 5 to 10 nm. Reactive chemical dynamics is characterized by a length scale less than 1 nm. The wave function in the entrance channel in the long range region beyond 1 nm is characterized by two dimensionless quantum defect parameters y and s, which respectively represent the probability of reaction in the short range zone and the phase of the reflected wave from this zone. We find universal collision rate constants in the "black hole" limit y = 1, for which there is a unit probability of loss from the entrance channel in the short range zone and no reflected wave back into the entrance channel. In this limit we get universal low temperature event rate constants depending only on the strength of the van der Waals potential for s wave collisions for bosons or unlike fermions and for p wave collisions of identical fermions. We find good agreement with the recent experimental measurements of the JILA group 3 for reactive collision rates for fermionic KRb molecules below 1 microkelvin, as well as for collisions of KRb with K atoms. The model is readily generalized to treat collisions in reduced dimensions and to include the effect of an electric field on polar molecules.

The present study investigates the impact of threshold inflation on economic growth of Pakistan using factors from growth theories. The empirical analysis is based on data from 1973 to 2023. The study used threshold regression to estimate the threshold level of inflation. The estimated threshold levels are 9.3 and 9.6 percent for inflation computed from consumer price index and wholesale price index respectively. The estimates revealed that after reaching the threshold inflation level, labour force growth and trade act as Keynesian theory suggests but the role of money supply contradicts from the Monetarists theory. This study is foremost in using regression trees in the analysis of threshold inflation and growth. The analysis of regression trees indicates that inflation and money supply are the major determinants of the growth of economy. The study concludes inflation above the threshold level of inflation corresponds to very low levels of growth in the country. The study suggests keeping inflation below threshold for the sustainable growth of the country  .

Ordinal data classification (ODC) has a wide range of applications in areas where human evaluation plays an important role, ranging from psychology and medicine to information retrieval. In ODC the output variable has a natural order; however, there is not a precise notion of the distance between classes. The recently proposed method for ordinal data, Kernel Discriminant Learning Ordinal Regression (KDLOR), is based on Linear Discriminant Analysis (LDA), a simple tool for classification. KDLOR brings LDA to the forefront in the ODC field, motivating further research. This paper compares three LDA based algorithms for ODC. The first method uses the generic framework of Frank and Hall for ODC instantiated with a kernel version of LDA. Similarly, the second method is based on the also generic Data Replication framework for ODC instantiated with the same kernel version of LDA. Both the Frank and Hall and Data Replication methods address the ODC problem by the use of a base binary classifier. Finally, the third method under comparison is KDLOR. The experiments are carried out on synthetic and real datasets. A comparison between the performances of the three systems is made based on tstatistics. The performance and running time complexity of the methods do not support any advantage of KDLOR over the other two methods.

The relationship between inflation and economic growth has been a subject of enduring interest and debate in the field of economics. This study revisits the inflation and growth nexus in Nigeria, with a particular emphasis on the threshold effecta non-linear phenomenon positing that the impact of inflation on growth varies depending on the level of inflation. Specifically, the study examines the threshold effect of inflation on growth in Nigeria using secondary data from 1986 to 2022, and employs two-regime threshold autoregressive regression modelling. The findings show that the pattern of relationship between inflation and growth is indeed nonlinear and conditional on certain levels of inflation rate. Findings reveal that the optimal threshold for inflation rate is 15.7%. Below the identified threshold, moderate inflation was associated with growth stimulation through mechanisms like reduced real interest rates and increased investment. However, beyond this threshold level (15.7%), the negative effects of inflation became pronounced, hindering economic growth in Nigeria. The findings of this study have several implications for Nigeria's monetary and fiscal policies, offering guidance on how to maintain inflation within a growth-stimulating range. Additionally, businesses and investors operating in Nigeria will gain insights into adapting their strategies to mitigate risks and capitalize on opportunities arising from varying inflation levels. Ultimately, this study contributes to the ongoing discourse on the inflation and growth nexus, providing valuable insights for policymakers navigating Nigeria's economic landscape about the threshold effect of inflation and its financial and practical implications for Nigeria's economic stability and growth prospects.

We define and describe the related problems of new event detection and event tracking within a stream of broadcast news stories. We focus on a strict on-line setting-i.e., the system must make decisions about one story before looking at any subsequent stories. Our approach to detection uses a single pass clustering algorithm and a novel thresholding model that incorporates the properties of events as a major component. Our approach to tracking is similar to typical information filtering methods. We discuss the value of "surprising" features that have unusual occurrence characteristics, and briefly explore on-line adaptive filtering to handle evolving events in the news. New event detection and event tracking are part of the Topic Detection and Tracking (TDT) initiative.

Two well known, biologically inspired non-dynamical models of stochastic resonance, the threshold-crossing model and the fluctuating rate model, are analyzed in terms of channel information capacity and dissipation of energy necessary for small-signal transduction. Using analogies to spike propagation in neurons we postulate the average output pulse rate as a measure of dissipation. The dissipation increases monotonically with the input noise. We find that for small dissipation both models give a close to linear dependence of the channel information capacity on dissipation. In both models the channel information capacity, as a function of dissipation, has a maximum at input noise amplitude that is different from that in the standard signal-to-noise ratio versus input noise plot. Though a direct comparison is not straightforward, for small signals the threshold model gives appreciably higher density of information per dissipation than the exponential fluctuating rate model. We show that a formal introduction of cooperativity in the rate fluctuating model permits us to imitate the response function of the threshold model and to enhance performance. This finding may have direct relevance to real neural spike generation where, due to a strong positive feedback, the ion channel currents add up in a synchronized way.

We present a new decision-making model that can account for trial-by-trial variability induced by a process ("pre-process") that occurs before an explicit sensory signal specifying a later motor response. A process after explicit sensory signals, referred to herein as the "post-process", has been investigated by a variety of so-called rise-to-threshold models including the LATER model. The LATER model formulates post-process variability but treats the pre-process as fixed within a block of an experiment. We propose an extension of the LATER model, which we call the extended LATER (ELATER) model, to account for trial-by-trial variability of both pre-and post-processes together. We present the mathematical formulation of the ELATER model and analyze its characteristics, including numerical examples and an example of saccade latency data in rewardmanipulated conditions with caudate activity. The ELATER model is useful for investigating decision making by taking account of trial-by-trial variability of both pre-and post-processes.

In this study, we employ a recently developed econometric technique of the threshold model with the GJR-GARCH process on error terms to investigate the relationships between weather factors and stock market returns in Taiwan using daily data for the period of 1 July 1997-22 October 2003. The major weather factors studied include temperature, humidity, and cloud cover. Our empirical evidence shows that temperature and cloud cover are two important weather factors that affect the stock returns in Taiwan. Our empirical findings further support the previous arguments that advocate the inclusion of economically neutral behavioral variables in asset pricing models. These results also have significant implications for individual investors and financial institutions planning to invest in the Taiwan stock market.

In this study, we employ a recently developed econometric technique of the threshold model with the GJR-GARCH process on error terms to investigate the relationships between weather factors and stock market returns in Taiwan using daily data for the period of 1 July 1997-22 October 2003. The major weather factors studied include temperature, humidity, and cloud cover. Our empirical evidence shows that temperature and cloud cover are two important weather factors that affect the stock returns in Taiwan. Our empirical findings further support the previous arguments that advocate the inclusion of economically neutral behavioral variables in asset pricing models. These results also have significant implications for individual investors and financial institutions planning to invest in the Taiwan stock market.

We present both theoretical and numerical analyses of a cellular automaton version of a slider-block model or threshold model that includes long-range interactions. Theoretically we develop a coarse-grained description in the mean-field ͑infinite range͒ limit and discuss the relevance of the metastable state, limit of stability ͑spinodal͒, and nucleation to the phenomenology of the model. We also simulate the model and confirm the relevance of the theory for systems with long-but finite-range interactions. Results of particular interest include the existence of Gutenberg-Richter-like scaling consistent with that found on real earthquake fault systems, the association of large events with nucleation near the spinodal, and the result that such systems can be described, in the mean-field limit, with techniques appropriate to systems in equilibrium.

This paper considers several issues relevant to the debate on the extent to which poverty, or development progress in general, should be measured by income or by a broader set of objectives. (See Robert Sugden's review (1993) of Amartya Sen's Inequality Revisited (1992) for a comparison of the two approaches.) Issues covered here are: practical implications of the two approaches for poverty reduction efforts; the impact of growth on basic social indicators; and how national achievement on social indicators is best measured. Sri Lanka and Pakistan, countries often cited in this debate, are used as examples.

Energy has become one of the most crucial problem in modern society which must be investigated, analyzed and solved. The main goal of this dissertation is to look at the economics of energy by analyzing the relationship between the availability of energy resources and the economic activity in a network context. The idea is to provide an efficient distribution of energy resources. The methodology that has been used is that of Network Flow optimization and it has been applied to solve Integrated Energy Systems problems

In this work we propose a semiparametric likelihood procedure for the threshold selection for extreme values. This is achieved under a semiparametric model, which assumes there is a threshold above which the excess distribution belongs to the generalized Pareto family. The motivation of our proposal lays on a particular characterization of the threshold under the aforementioned model. A simulation study is performed to show empirically the properties of the proposal and we also compare it with other estimators.

Automatic gradient threshold selection for edge detection is a non-trivial task due to the presence of image noise, This problem is posed within a statistical framework based on a cubic facet model for the image data and a Gaussian model for the noise. Under these assumptions, two statistics which are functions of the gradient strength and facet residual error are derived. Experiments show that thresholds on these statistics produce results which are superior to those obtained by the best subjective threshold on the gradient image. A Bayes decision procedure is developed which makes threshold selection automatic. Threshold selection

Honey bees (Apis mellifera) have become a model system for studies on the influence of genetic diversity on disease. Honey bee queens mate with a remarkably high number of males—up to 29 in the current study—from which they produce a colony of genetically diverse daughter workers. Recent evidence suggests a significant benefit of intracolony genetic diversity on disease resistance. Here, we explored the relationship between the level of genetic diversity and multiple physiological mechanisms of cellular and humoral immune defense (encapsulation response and phenoloxidase activity). We also investigated an effect of genetic diversity on a measure of body condition (fat body mass). While we predicted that mean colony phenoloxidase activity, encapsulation response, and fat body mass would show a positive relationship with increased intracolonial genetic diversity, we found no significant relationship between genetic diversity and these immune measures, and found no consistent effect on...

Under intensive husbandry conditions, the natural behaviour repertoire of livestock is often contrary to an optimal productivity and also animal welfare. This problem can be reduced by technically manipulating the animal behaviour in terms of precision livestock farming, so that husbandry conditions and animal behaviour adjust mutually to one another. The current work exemplifies this approach for appetitive stimulations at the example of call feeding gestating sows and for aversive stimulations at the example of preliminary studies for a method to actively prevent piglet crushing.Unter intensiven Haltungsbedingungen ist das angeborene Verhaltensrepertoire von Nutztieren häufig einer optimalen Produktivität aber auch einem optimalen Tierwohl zuwiderlaufend. Durch technische Verhaltensbeeinflussung im Sinne von precision livestock farming kann eine gegenseitige Anpassung der Haltungsbedingungen und des Tierverhaltens umgesetzt werden, die dieses Problem verringert. Dieser Ansatz wird...

In social insects, newly emerged individuals learn the colony-specifi c chemical label from their natal comb shortly after their emergence. These labels help to identify each individual's colony of origin and are used as a recognition template against which individuals can discriminate nestmates from non-nestmates. Our previous studies with Polybia paulista von Ihering support this general pattern, and the acceptance rate of young female and male wasps decreased as a function of their age. Our study also showed in P. paulista that more than 90% of newly emerged female wasps might be accepted by conspecifi c unrelated colonies. However, it has not been investigated whether the acceptance rate of newly emerged female wasps depends on colony developmental stage of recipient colonies. We introduced newly emerged female wasps of P. paulista into different colony developmental stags of recipient colonies, i.e., worker-producing and male-producing colonies. We found that the acceptance rate of newly emerged female wasps by alien colonies was pretty lower by male-producing colonies than worker-producing colonies. This is the fi rst study to show that the acceptance rate of young female wasps depends on stages of recipient colonies.

Current selection schemes for livestock improvement use a wide variety of phenotypic traits. Some of them, such as sensory, type, or carcass traits, obtain their records from subjective grading performed by trained technicians. Data from this subjective evaluation usually involve classification under a categorical and arbitrary predefined scale, whose output may lead to strong departures from the Gaussian distribution. In addition, the scale of grading may be different according to different technicians. To study this phenomenon, we have analyzed subjective conformation (CON) and fat cover (FAT) scores in the Pirenaica beef cattle breed from data provided by 12 different slaughterhouses. Three statistical models were used: 1) a Gaussian linear model; 2) an ordered category threshold model; and 3) a specific slaughterhouse ordered category threshold model. These models were analyzed through a Bayesian analysis via a Gibbs sampler with a data augmentation step. Posterior mean estimate...

Barley (Hordeum vulgare L.) seeds (grains) exhibit dormancy at maturity that is largely due to the presence of the glumellae (hulls) that reduce the availability of oxygen (O 2 ) to the embryo. In addition, abscisic acid (ABA) and gibberellins (GAS) interact with O 2 to regulate barley seed dormancy. A population-based threshold model was applied to quantify the sensitivities of seeds and excised embryos to O 2 , ABA, and GA, and to their interactive effects. The median O 2 requirement for germination of dormant intact barley seeds was 400-fold greater than for excised embryos, indicating that the tissues enclosing the embryo markedly limit O 2 penetration. However, embryo O 2 thresholds decreased by another order of magnitude following after-ripening. Thus, increases in both permeability of the hull to O 2 and embryo sensitivity to O 2 contribute to the improvement in germination capacity during after-ripening. Both ABA and GA had relatively small effects on the sensitivity of germination to O 2 , but ABA and GA thresholds varied over several orders of magnitude in response to O 2 availability, with sensitivity to ABA increasing and sensitivity to GA decreasing with hypoxia. Simple additive models of O 2 -ABA and O 2 -GA interactions required consideration of these O 2 effects on hormone sensitivity to account for actual germination patterns. These quantitative and interactive relationships among O 2 , ABA, and GA sensitivities provide insight into how dormancy and germination are regulated by a combination of physical (O 2 diffusion through the hull) and physiological (ABA and GA sensitivities) factors.

Objective Unnecessary radiological examination should be avoided, particularly for children, who are more vulnerable to radiation than adults. Replacement of X-ray examination with 18F-fluoro-2-deoxy-D-glucose (18FDG) positron emission tomography/computed tomography (PET/CT) is a potential option for reduction of radiation exposure, and thus improvement in the quality of life (QOL) of patients. Therefore, this study aimed to evaluate new plans integrating 18FDG PET/CT versus current conventional imaging (CI) plans for patients with pediatric cancers. The effects of radiation exposure from the two kinds of plans were compared using shortening of the average life expectancy as an index, and the related findings and effects of radiation exposure are discussed. Methods Effective radiation doses from CT scanning were calculated using the ImPACT CT Patient Dosimetry Calculator software. Radiation doses in different organs and tissues from radiopharmaceuticals were obtained from the International Commission on Radiological Protection (ICRP) publication 80. Shortening of average life expectancy was calculated using software in which the linear non-threshold model (LNT) by the ICRP was adopted. In current CI plans, the mean effective dose was 168.8 mSv (range 50.5-513.4 mSv) for males and 127 mSv (range 54-239.7 mSv) for females. The mean shortening of average life expectancy was 177 days (range 53.3-542 days) for males and 185 days (range 80.4-371 days) for females. In new plans, the mean effective dose was 64.1 mSv (range 54.1-84.5 mSv) for males and 68.2 mSv (range 58.1-88.0 mSv) for females. The mean shortening of life expectancy was 67.6 days (range 57.1-89.2 days) for males and 102.5 days (range 86.8-132.6 days) for females. Conclusions New 18FDG PET/CT plans may relieve the patient's physical burden and contribute to improvement of the patient's QOL. These plans may also reduce medical costs because the number of examinations to be performed is reduced. Although deterministic effects are not observed in the CI plan, careful attention should be paid to other potential effects. Because the effective dose resulting from this plan is over 100 mSv, at which stochastic effects are known to occur, radiation-induced cancers may be expected.