Forecasting regional crop production using SOI phases: an example for the Australian peanut industry

Using peanuts as an example, a generic methodology is presented to forward-estimate regional crop production and associated climatic risks based on phases of the Southern Oscillation Index (SOI). Yield fluctuations caused by a highly variable rainfall environment are of concern to peanut processing and marketing bodies. The industry could profitably use forecasts of likely production to adjust their operations strategically. Significant, physically based lag-relationships exist between an index of ocean/atmosphere El Nino/Southern Oscillation phenomenon and future rainfall in Australia and elsewhere. Combining knowledge of SOI phases in November and December with output from a dynamic simulation model allows the derivation of yield probability distributions based on historic rainfall data. This information is available shortly after planting a crop and at least 3-5 months prior to harvest. The study shows that in years when the November-December SOI phase is positive there is an 80% chance of exceeding average district yields. Conversely, in years when the November-December SOI phase is either negative or rapidly falling there is only a 5% chance of exceeding average district yields, but a 95% chance of below average yields. This information allows the industry to adjust strategically for the expected volume of production. The study shows that simulation models can enhance SOI signals contained in rainfall distributions by discriminating between useful and damaging rainfall events. The methodology can be applied to other industries and regions.

A review of the impact of education and prior experience on new venture performance

The importance of education and experience to the successful performance of new firms is well recognized both by management practitioners and academics. Yet empirical research to support the significance of this relationship is inconclusive. This paper discusses theories describing the relationship between education and experience and firm performance. It also analyses and classifies the differing measures of performance, education and experience, and compares the results of multiple studies undertaken between 1977 and 2000. Possible reasons for conflicting results are identified, such as lack of sound theoretical bases that relate education and experience to performance, varying definitions of the key variables and the diversity of measures used. Finally, a framework is developed that incorporates variables that interact with experience and education to influence new venture performance.

Derivation of the probability distribution function for the local density of states of a disordered quantum wire via the replica trick and supersymmetry

We consider the statistical properties of the local density of states of a one-dimensional Dirac equation in the presence of various types of disorder with Gaussian white-noise distribution. It is shown how either the replica trick or supersymmetry can be used to calculate exactly all the moments of the local density of states.' Careful attention is paid to how the results change if the local density of states is averaged over atomic length scales. For both the replica trick and supersymmetry the problem is reduced to finding the ground state of a zero-dimensional Hamiltonian which is written solely in terms of a pair of coupled spins which are elements of u(1, 1). This ground state is explicitly found for the particular case of the Dirac equation corresponding to an infinite metallic quantum wire with a single conduction channel. The calculated moments of the local density of states agree with those found previously by Al'tshuler and Prigodin [Sov. Phys. JETP 68 (1989) 198] using a technique based on recursion relations for Feynman diagrams. (C) 2001 Elsevier Science B.V. All rights reserved.

Cavity QED analog of the harmonic-oscillator probability distribution function and quantum collapses

We establish a connection between the simple harmonic oscillator and a two-level atom interacting with resonant, quantized cavity and strong driving fields, which suggests an experiment to measure the harmonic-oscillator's probability distribution function. To achieve this, we calculate the Autler-Townes spectrum by coupling the system to a third level. We find that there are two different regions of the atomic dynamics depending on the ratio of the: Rabi frequency Omega (c) of the cavity field to that of the Rabi frequency Omega of the driving field. For Omega (c)

What is the value of firms' prior knowledge? Building organisational knowledge capabilities

A firm's prior knowledge facilitates the absorption of new knowledge, thereby renewing a firm's systematic search, transfer and absorption capabilities. The rapidly expanding field of biotechnology is characterised by the convergence of disparate sciences and technologies. This paper, the shift from proteinbased to DNA-based diagnostic technologies, quantifies the value of a firm's prior knowledge and its relation to future knowledge development. Four dimensions of diagnostic and four dimensions of knowledge in biotechnology firms are analysed. A simple scaled matrix method is developed to quantify the positive and negative heuristic values of prior scientific and technological knowledge that is useful for the acquisition and absorption of new knowledge.

Mean anisotropy of homogeneous Gaussian random fields and anisotropic norms of linear translation-invariant operators on multidimensional integer lattices

Sensitivity of output of a linear operator to its input can be quantified in various ways. In Control Theory, the input is usually interpreted as disturbance and the output is to be minimized in some sense. In stochastic worst-case design settings, the disturbance is considered random with imprecisely known probability distribution. The prior set of probability measures can be chosen so as to quantify how far the disturbance deviates from the white-noise hypothesis of Linear Quadratic Gaussian control. Such deviation can be measured by the minimal Kullback-Leibler informational divergence from the Gaussian distributions with zero mean and scalar covariance matrices. The resulting anisotropy functional is defined for finite power random vectors. Originally, anisotropy was introduced for directionally generic random vectors as the relative entropy of the normalized vector with respect to the uniform distribution on the unit sphere. The associated a-anisotropic norm of a matrix is then its maximum root mean square or average energy gain with respect to finite power or directionally generic inputs whose anisotropy is bounded above by a≥0. We give a systematic comparison of the anisotropy functionals and the associated norms. These are considered for unboundedly growing fragments of homogeneous Gaussian random fields on multidimensional integer lattice to yield mean anisotropy. Correspondingly, the anisotropic norms of finite matrices are extended to bounded linear translation invariant operators over such fields.

Valuing of firm's prior knowledge: A measure of knowledge distance

Knowledge, especially scientific and technological knowledge, grows according to knowledge trajectories and guideposts that make up the prior knowledge of an organization. We argue that these knowledge structures and their specific components lead to successful innovation. A firm's prior knowledge facilitates the absorption of new knowledge, thereby renewing a firm's systematic search, transfer and acquisition of knowledge and capabilities. In particular, the exponential growth in biotechnology is characterized by the convergence of disparate scientific and technological knowledge resources. This paper examines the shift from protein-based to DNA-based diagnostic technologies as an example, to quantify the value of a firm's prior knowledge using relative values of knowledge distance. The distance between core prior knowledge and the rate of transition from one knowledge system to another has been identified as a proxy for the value a firm's prior knowledge. The overall difficulty of transition from one technology paradigm to another is discussed. We argue this transition is possible when the knowledge distance is minimal and the transition process has a correspondingly high value of absorptive capacities. Our findings show knowledge distance is a determinant of the feasibility, continuity and capture of scientific and technological knowledge. Copyright © 2003 John Wiley & Sons, Ltd.

Parathyroid hormone venous sampling prior to reoperation for primary hyperparathyroidism

Background: The surgical cure rate for primary hyperparathyroidism is greater than 95%. For those who have recurrent or persistent disease, preoperative localization improves reoperation success rates. Selective parathyroid venous sampling (SPVS) for intact parathyroid hormone is particularly useful when non-invasive localization techniques are negative or inconclusive. Methods: We present all known cases (n = 13) between 1994 and 2002 who had venous sampling for localization at our institution prior to reoperation for recurrent or persistent primary hyperparathyroidism. Comparison was made with non-invasive localization procedures. Results of invasive and non-invasive localization were correlated with surgical findings. Results: Of the nine reoperated cases, eight had positive correlations between SPVS and operative findings and histopathology. SPVS did not reveal the parathyroid hormone source in one case with negative non-invasive localization procedures. Comparisons between SPVS, computerized tomography (CT), and parathyroid scintigraphy (MIBI) as expressed in terms of true positive (TP), false positive (FP) and false negative (FN) were: SPVS - TP 88.8%, FP 0%, FN 11.1%; CT - TP 22.2%, FP 22.2%, FN 55.5%; and MIBI - TP 33.3%, FP 0%, FN 66.6%. At least seven of the nine operated cases have been cured; another remained normocalcaemic 2 weeks after subtotal parathyroidectomy. Conclusion: In our institution SPVS has proven to be a valuable tool in cases with recurrent or persistent primary hyperparathyroidism and negative non-invasive localization procedures.

Experimental manipulation of prior experience: Effects on item and associative recognition

Frequency of exposure to very low- and high-frequency words was manipulated in a three-phase (familiarisation, study, and test) design. During familiarisation, words were presented with their definition (once, four times, or not presented). One week (Experiment 1) or one day (Experiment 2) later, participants studied a list of homogeneous pairs (i.e., pair members were matched on background and familiarisation frequency). Item and associative recognition of high- and very low-frequency words presented in intact, rearranged, old-new, or new-new pairs were tested in Experiment 1. Associative recognition of very low-frequency words was tested in Experiment 2. Results showed that prior familiaris ation improved associative recognition of very low-frequency pairs, but had no effect on high-frequency pairs. The role of meaning in the formation of item-to-item and item-to-context associations and the implications for current models of memory are discussed.

Local Utility Functions and Local Probability Transformations

This note shows that, under appropriate conditions, preferences may be locally approximated by the linear utility or risk-neutral preference functional associated with a local probability transformation.

Events in Indonesia: exploring the limits to formal tourism trends forecasting methods in complex crisis situations

The desire to know the future is as old as humanity. For the tourism industry the demand for accurate foretelling of the future course of events is a task that consumes considerable energy and is of great significance to investors. This paper examines the issue of forecasting by comparing forecasts of inbound tourism made prior to the political and economic crises that engulfed Indonesia from 1997 onwards with actual arrival figures. The paper finds that current methods of forecasting are not able to cope with unexpected crises and other disasters and that alternative methods need to be examined including scenarios, political risk and application of chaos theory. The paper outlines a framework for classifying shocks according to a scale of severity, probability, type of event, level of certainty and suggested forecasting tools for each scale of shock. (C) 2003 Elsevier Science Ltd. All rights reserved.

A liberation model for comminution based on probability theory

Mineral processing plants use two main processes; these are comminution and separation. The objective of the comminution process is to break complex particles consisting of numerous minerals into smaller simpler particles where individual particles consist primarily of only one mineral. The process in which the mineral composition distribution in particles changes due to breakage is called 'liberation'. The purpose of separation is to separate particles consisting of valuable mineral from those containing nonvaluable mineral. The energy required to break particles to fine sizes is expensive, and therefore the mineral processing engineer must design the circuit so that the breakage of liberated particles is reduced in favour of breaking composite particles. In order to effectively optimize a circuit through simulation it is necessary to predict how the mineral composition distributions change due to comminution. Such a model is called a 'liberation model for comminution'. It was generally considered that such a model should incorporate information about the ore, such as the texture. However, the relationship between the feed and product particles can be estimated using a probability method, with the probability being defined as the probability that a feed particle of a particular composition and size will form a particular product particle of a particular size and composition. The model is based on maximizing the entropy of the probability subject to mass constraints and composition constraint. Not only does this methodology allow a liberation model to be developed for binary particles, but also for particles consisting of many minerals. Results from applying the model to real plant ore are presented. A laboratory ball mill was used to break particles. The results from this experiment were used to estimate the kernel which represents the relationship between parent and progeny particles. A second feed, consisting primarily of heavy particles subsampled from the main ore was then ground through the same mill. The results from the first experiment were used to predict the product of the second experiment. The agreement between the predicted results and the actual results are very good. It is therefore recommended that more extensive validation is needed to fully evaluate the substance of the method. (C) 2003 Elsevier Ltd. All rights reserved.