Folding processes and solitary waves in structural geology

Evolution of localized folding patterns in layered elastic and visco-elastic materials is reviewed in the context of compressed geological systems. The thin strut or plate embedded in a visco-elastic medium is used as an archetypal example to describe localized buckles which, in contrast to those from earlier formulations, appear in the absence of triggering imperfections. Structural and material effects are surveyed and important nonlinear characteristics are identified. A brief review of possible methods of analysis is conducted.

Branching processes and computational collapse of discretized unimodal mappings

In computer simulations of smooth dynamical systems, the original phase space is replaced by machine arithmetic, which is a finite set. The resulting spatially discretized dynamical systems do not inherit all functional properties of the original systems, such as surjectivity and existence of absolutely continuous invariant measures. This can lead to computational collapse to fixed points or short cycles. The paper studies loss of such properties in spatial discretizations of dynamical systems induced by unimodal mappings of the unit interval. The problem reduces to studying set-valued negative semitrajectories of the discretized system. As the grid is refined, the asymptotic behavior of the cardinality structure of the semitrajectories follows probabilistic laws corresponding to a branching process. The transition probabilities of this process are explicitly calculated. These results are illustrated by the example of the discretized logistic mapping.

Process systems modelling and applications in granulation: A review

Granulation is one of the fundamental operations in particulate processing and has a very ancient history and widespread use. Much fundamental particle science has occurred in the last two decades to help understand the underlying phenomena. Yet, until recently the development of granulation systems was mostly based on popular practice. The use of process systems approaches to the integrated understanding of these operations is providing improved insight into the complex nature of the processes. Improved mathematical representations, new solution techniques and the application of the models to industrial processes are yielding better designs, improved optimisation and tighter control of these systems. The parallel development of advanced instrumentation and the use of inferential approaches provide real-time access to system parameters necessary for improvements in operation. The use of advanced models to help develop real-time plant diagnostic systems provides further evidence of the utility of process system approaches to granulation processes. This paper highlights some of those aspects of granulation. (c) 2005 Elsevier Ltd. All rights reserved.

Modelling, nitrogen dynamics in sugarcane systems: Recent advances and applications

Substantial amounts of nitrogen (N) fertiliser are necessary for commercial sugarcane production because of the large biomass produced by sugarcane crops. Since this fertiliser is a substantial input cost and has implications if N is lost to the environment, there are pressing needs to optimise the supply of N to the crops' requirements. The complexity of the N cycle and the strong influence of climate, through its moderation of N transformation processes in the soil and its impact on N uptake by crops, make simulation-based approaches to this N management problem attractive. In this paper we describe the processes to be captured in modelling soil and plant N dynamics in sugarcane systems, and review the capability for modelling these processes. We then illustrate insights gained into improved management of N through simulation-based studies for the issues of crop residue management, irrigation management and greenhouse gas emissions. We conclude by identifying processes not currently represented in the models used for simulating N cycling in sugarcane production systems, and illustrate ways in which these can be partially overcome in the short term. (c) 2005 Elsevier B.V. All rights reserved.

The diagnostic interview for psychoses (DIP): development, reliability and applications

Background. We describe the development, reliability and applications of the Diagnostic Interview for Psychoses (DIP), a comprehensive interview schedule for psychotic disorders. Method. The DIP is intended for use by interviewers with a clinical background and was designed to occupy the middle ground between fully structured, lay-administered schedules, and semi-structured., psychiatrist-administered interviews. It encompasses four main domains: (a) demographic data; (b) social functioning and disability; (c) a diagnostic module comprising symptoms, signs and past history ratings; and (d) patterns of service utilization Lind patient-perceived need for services. It generates diagnoses according to several sets of criteria using the OPCRIT computerized diagnostic algorithm and can be administered either on-screen or in a hard-copy format. Results. The DIP proved easy to use and was well accepted in the field. For the diagnostic module, inter-rater reliability was assessed on 20 cases rated by 24 clinicians: good reliability was demonstrated for both ICD-10 and DSM-III-R diagnoses. Seven cases were interviewed 2-11 weeks apart to determine test-retest reliability, with pairwise agreement of 0.8-1.0 for most items. Diagnostic validity was assessed in 10 cases, interviewed with the DIP and using the SCAN as 'gold standard': in nine cases clinical diagnoses were in agreement. Conclusions. The DIP is suitable for use in large-scale epidemiological studies of psychotic disorders. as well as in smaller Studies where time is at a premium. While the diagnostic module stands on its own, the full DIP schedule, covering demography, social functioning and service utilization makes it a versatile multi-purpose tool.

The relationship between radiation-induced chemical processes and transverse relaxation times in polymer gel dosimeters

The effects of ionizing radiation in different compositions of polymer gel dosimeters are investigated using FT-Raman spectroscopy and NMR T-2 relaxation times. The dosimeters are manufactured from different concentrations of comonomers (acrylamide and N,N'-methylene-bis-acrylamide) dispersed in different concentrations of an aqueous gelatin matrix. Results are analysed using a model of fast exchange of magnetization between three proton pools. The fraction of protons in each pool is determined using the known chemical composition of the dosimeter and FT-Raman spectroscopy. Based on these results, the physical and chemical processes in interplay in the dosimeters are examined in view of their effect on the changes in T-2 The precipitation of growing macroradicals and the scavenging of free radicals by gelatin are used to explain the rate of polymerization. The model describes the changes in T-2 as a function of the absorbed dose up to 50 Gy for the different compositions. This is expected to aid the theoretical design of new, more efficient dosimeters, since it was demonstrated that the optimum dosimeter (i.e, with the lowest dose resolution) must have a range of relaxation times which match the range of T-2 values which can be determined with the lowest uncertainty using an MRI scanner.

Computational methods for prediction of T-cell epitopes - a framework for modelling, testing, and applications

Computational models complement laboratory experimentation for efficient identification of MHC-binding peptides and T-cell epitopes. Methods for prediction of MHC-binding peptides include binding motifs, quantitative matrices, artificial neural networks, hidden Markov models, and molecular modelling. Models derived by these methods have been successfully used for prediction of T-cell epitopes in cancer, autoimmunity, infectious disease, and allergy. For maximum benefit, the use of computer models must be treated as experiments analogous to standard laboratory procedures and performed according to strict standards. This requires careful selection of data for model building, and adequate testing and validation. A range of web-based databases and MHC-binding prediction programs are available. Although some available prediction programs for particular MHC alleles have reasonable accuracy, there is no guarantee that all models produce good quality predictions. In this article, we present and discuss a framework for modelling, testing, and applications of computational methods used in predictions of T-cell epitopes. (C) 2004 Elsevier Inc. All rights reserved.