Special Issue on Spatial Moment Techniques for Modelling Biological Processes

Over the last two decades, there has been an increasing awareness of, and interest in, the use of spatial moment techniques to provide insight into a range of biological and ecological processes. Models that incorporate spatial moments can be viewed as extensions of mean-field models. These mean-field models often consist of systems of classical ordinary differential equations and partial differential equations, whose derivation, at some point, hinges on the simplifying assumption that individuals in the underlying stochastic process encounter each other at a rate that is proportional to the average abundance of individuals. This assumption has several implications, the most striking of which is that mean-field models essentially neglect any impact of the spatial structure of individuals in the system. Moment dynamics models extend traditional mean-field descriptions by accounting for the dynamics of pairs, triples and higher n-tuples of individuals. This means that moment dynamics models can, to some extent, account for how the spatial structure affects the dynamics of the system in question.

Simulating the evolution of glyphosate resistance in grains farming in northern Australia.

Background and Aims: The evolution of resistance to herbicides is a substantial problem in contemporary agriculture. Solutions to this problem generally consist of the use of practices to control the resistant population once it evolves, and/or to institute preventative measures before populations become resistant. Herbicide resistance evolves in populations over years or decades, so predicting the effectiveness of preventative strategies in particular relies on computational modelling approaches. While models of herbicide resistance already exist, none deals with the complex regional variability in the northern Australian sub-tropical grains farming region. For this reason, a new computer model was developed. Methods: The model consists of an age- and stage-structured population model of weeds, with an existing crop model used to simulate plant growth and competition, and extensions to the crop model added to simulate seed bank ecology and population genetics factors. Using awnless barnyard grass (Echinochloa colona) as a test case, the model was used to investigate the likely rate of evolution under conditions expected to produce high selection pressure. Key Results: Simulating continuous summer fallows with glyphosate used as the only means of weed control resulted in predicted resistant weed populations after approx. 15 years. Validation of the model against the paddock history for the first real-world glyphosate-resistant awnless barnyard grass population shows that the model predicted resistance evolution to within a few years of the real situation. Conclusions: This validation work shows that empirical validation of herbicide resistance models is problematic. However, the model simulates the complexities of sub-tropical grains farming in Australia well, and can be used to investigate, generate and improve glyphosate resistance prevention strategies.

Heat-Capacity Measurements - Progress In Experimental-Techniques

The heat capacity of a substance is related to the structure and constitution of the material and its measurement is a standard technique of physical investigation. In this review, the classical methods are first analyzed briefly and their recent extensions are summarized. The merits and demerits of these methods are pointed out. The newer techniques such as the a.c. method, the relaxation method, the pulse methods, the laser flash calorimetry and other methods developed to extend the heat capacity measurements to newer classes of materials and to extreme conditions of sample geometry, pressure and temperature are comprehensively reviewed. Examples of recent work and details of the experimental systems are provided for each method. The introduction of automation in control systems for the monitoring of the experiments and for data processing is also discussed. Two hundred and eight references and 18 figures are used to illustrate the various techniques.

Application of Mathematical Programming to the Plywood Design and Manufacturing Problem

Plywood manufacture includes two fundamental stages. The first is to peel or separate logs into veneer sheets of different thicknesses. The second is to assemble veneer sheets into finished plywood products. At the first stage a decision must be made as to the number of different veneer thicknesses to be peeled and what these thicknesses should be. At the second stage, choices must be made as to how these veneers will be assembled into final products to meet certain constraints while minimizing wood loss. These decisions present a fundamental management dilemma. Costs of peeling, drying, storage, handling, etc. can be reduced by decreasing the number of veneer thicknesses peeled. However, a reduced set of thickness options may make it infeasible to produce the variety of products demanded by the market or increase wood loss by requiring less efficient selection of thicknesses for assembly. In this paper the joint problem of veneer choice and plywood construction is formulated as a nonlinear integer programming problem. A relatively simple optimal solution procedure is developed that exploits special problem structure. This procedure is examined on data from a British Columbia plywood mill. Restricted to the existing set of veneer thicknesses and plywood designs used by that mill, the procedure generated a solution that reduced wood loss by 79 percent, thereby increasing net revenue by 6.86 percent. Additional experiments were performed that examined the consequences of changing the number of veneer thicknesses used. Extensions are discussed that permit the consideration of more than one wood species.

Recognition And Top-Down Generation Of Beta-Acyclic Database Schemes

Database schemes can be viewed as hypergraphs with individual relation schemes corresponding to the edges of a hypergraph. Under this setting, a new class of "acyclic" database schemes was recently introduced and was shown to have a claim to a number of desirable properties. However, unlike the case of ordinary undirected graphs, there are several unequivalent notions of acyclicity of hypergraphs. Of special interest among these are agr-, beta-, and gamma-, degrees of acyclicity, each characterizing an equivalence class of desirable properties for database schemes, represented as hypergraphs. In this paper, two complementary approaches to designing beta-acyclic database schemes have been presented. For the first part, a new notion called "independent cycle" is introduced. Based on this, a criterion for beta-acyclicity is developed and is shown equivalent to the existing definitions of beta-acyclicity. From this and the concept of the dual of a hypergraph, an efficient algorithm for testing beta-acyclicity is developed. As for the second part, a procedure is evolved for top-down generation of beta-acyclic schemes and its correctness is established. Finally, extensions and applications of ideas are described.

Rab8 and Rab8-interacting proteins as players in cell polarization

Rab8 and its interacting proteins as regulators of cell polarization During the development of a multi-cellular organism, progenitor cells have to divide and migrate appropriately as well as organize their differentiation with one another, in order to produce a viable embryo. To divide, differentiate and migrate cells have to undergo polarization, a process where internal and external components such as actin, microtubules and adhesion receptors are reorganized to produce a cell that is asymmetric, with functionally different surfaces. Also in the adult organism there is a continuous need for these processes, as cells need to migrate in response to tissue damage and to fight infection. Improper regulation of cell proliferation and migration can conversely lead to disease such as cancer. GTP-binding proteins function as molecular switches by cycling between a GTP-bound (active) conformation and a GDP-bound (inactive) conformation. The Ras super-family of small GTPases are found in all eukaryotic cells. They can be functionally divided into five subfamilies. The Ras family members mainly regulate gene expression, controlling cell proliferation and differentiation. Ras was in fact the first human oncogene to be characterized, and as much as 30% of all human tumors may be directly or indirectly caused by mutations of Ras molecules The Rho family members mainly regulate cytoskeletal reorganization. Arf proteins are known to regulate vesicle budding and Rab proteins regulate vesicular transport. Ran regulates nuclear transport as well as microtubule organization during mitosis. The focus of the thesis of Katarina Hattula, is on Rab8, a small GTPase of the Rab family. Activated Rab8 has previously been shown to induce the formation of new surface extensions, reorganizing both actin and microtubules, and to have a role in directed membrane transport to cell surfaces. However, the exact membrane route it regulates has remained elusive. In the thesis three novel interactors of Rab8 are presented. Rabin8 is a Rab8-specific GEF that localizes to vesicles where it presumably recruits and activates its target Rab8. Its expression in cells leads to remodelling of actin and the formation of polarized cell surface domains. Optineurin, known to be associated with a leading cause of blindness in humans (open-angle glaucoma), is shown to interact specifically with GTP-bound Rab8. Rab8 binds to an amino-terminal region and interestingly, the Huntingtin protein binds a carboxy-terminal region of optineurin. (Aberrant Huntingtin protein is known to be the cause Huntington s disease in humans.) Co-expression of Huntingtin and optineurin enhanced the recruitment of Huntingtin to Rab8-positive vesicular structures. Furthermore, optineurin promoted cell polarization in a similar way to Rab8. A third novel interactor of Rab8 presented in this thesis is JFC1, a member of the synaptogamin-like protein (Slp) family. JFC1 interacts with Rab8 specifically in its GTP-bound form, co-localizes with endogenous Rab8 on tubular and vesicular structures, and is probably involved in controlling Rab8 membrane dynamics. Rab8 is in this thesis work clearly shown to have a strong effect on cell shape. Blocking Rab8 activity by expression of Rab8 RNAi, or by expressing the dominant negative Rab8 (T22N) mutant leads to loss of cell polarity. Conversely, cells expressing the constitutively active Rab8 (Q67L) mutant exhibit a strongly polarized phenotype. Experiments in live cells show that Rab8 is associated with macropinosomes generated at ruffling areas of the membrane. These macropinosomes fuse with or transform into tubules that move toward the cell centre, from where they are recycled back to the leading edge to participate in protrusion formation. The biogenesis of these tubules is shown to be dependent on both actin and microtubule dynamics. The Rab8-specific membrane route studied contained several markers known to be internalized and recycled (1 integrin, transferrin, transferrin receptor, cholera toxin B subunit (CTxB), and major histocompatibility complex class I protein (MHCI)). Co-expression studies revealed that Rab8 localization overlaps with that of Rab11 and Arf6. Rab8 is furthermore clearly functionally linked to Arf6. The data presented in this thesis strongly suggests a role for Rab8 as a regulator for a recycling compartment, which is involved in providing structural and regulatory components to the leading edge to participate in protrusion formation.

Target Cell Topography and Cytoskeletal Reorganization in Natural Killer Cell Activity

The immune system has to recognize and destroy abnormal or infected cells to maintain homeostasis. Natural killer (NK) cells directly recognize and kill transformed or virus-infected cells without prior sensitization. We have studied both virus-infected and tumor cells in order to identify the target structures involved in triggering NK activity. Mouse/human cell hybrids containing various human chromosomes were used as targets. The human chromosome responsible for activating NK cell killing was identified to chromosome number 6. The results suggest that activated NK cells recognize ligands that are encoded on human chromosome 6. We showed that the ligand on the target cell side was intercellular adhesion molecule 2 (ICAM-2). There was no difference in the level of expression of ICAM-2, however, but a drastic difference was seen in the distribution of the molecule: ICAM-2 was evenly distributed on the surface of the NK-resistant cells, but almost totally redistributed to the tip of uropods, bud-like extensions, which were absent from the parental cells. Interestingly, the gene coding for cytoskeletal linker protein ezrin has been localized to human chromosome 6, and there was a colocalization of ezrin and ICAM-2 in the uropods. Furthermore, the transfected human ezrin into NK cell-resistant cells induced uropod formation, ICAM-2 and ezrin redistribution to newly formed uropods, and sensitized target cells to NK cell killing. These data reveal a novel form of NK cell recognition: target structures are already present on normal cells; they become detectable only after abnormal redistribution into hot spots on the target cell membrane. NK cells are central players in the defence against virus infections. They inhibit the spread of infection, allowing time for specific immune responses to develop. The virus-proteins that directly activate human NK cell killing are largely unknown. We studied the sensitivity of virus-specific early proteins of Semliki Forest virus (SFV) to NK killing. The viral non-structural proteins (nsP1-4) translated early in the virus cycle were transfected in NK-resistant cells. Viral early gene nsP1 alone efficiently sensitized target cells to NK activity, and the tight membrane association of nsP1 seems to be critical in the triggering of NK killing. NsP1 protein colocalized with (redistributed) ezrin in filopodia-like structures to which the NK cells were bound. The results suggest that also in viral infections NK cells react to rapid changes in membrane topography. Based on the results of this thesis, a new model of target cell recognition of NK cells can be suggested: reorganization of the cytoskeleton induces alterations in cell surface topography, and this new pattern of surface molecules is recognized as "altered-self".

Increasing attractiveness of high-end products

An important decision brand managers have to make when positioning their products in a retail setting is to whether price new line extensions at parity or let products vary in the price/quality spectrum. Despite the growing interest in vertical line extension issues, there has been little research investigating how product-line length affects extension favorability. Therefore, this paper investigates the framing effect that a product line price structure has on consumer judgments of vertical extensions and, in particular, of upscale extensions. A basic proposition of this research is that the parent brand price range affects the perceived or psychological distance between extension and parent brand, influencing extension favorability ratings. In two experiments, it is shown that positioning an upscale extension in the context of a wide product-line will lead to higher consistency perceptions between the parent brand and a new upscale extension than an equivalent upscale extension positioned in the context of a narrow parent brand product-line.

Design and Performance Evaluation of EXMAN: An EXtended MANchester Data Flow Computer

Data flow computers are high-speed machines in which an instruction is executed as soon as all its operands are available. This paper describes the EXtended MANchester (EXMAN) data flow computer which incorporates three major extensions to the basic Manchester machine. As extensions we provide a multiple matching units scheme, an efficient, implementation of array data structure, and a facility to concurrently execute reentrant routines. A simulator for the EXMAN computer has been coded in the discrete event simulation language, SIMULA 67, on the DEC 1090 system. Performance analysis studies have been conducted on the simulated EXMAN computer to study the effectiveness of the proposed extensions. The performance experiments have been carried out using three sample problems: matrix multiplication, Bresenham's line drawing algorithm, and the polygon scan-conversion algorithm.

New distribution and lure records of Dacinae (Diptera: Tephritidae) from Queensland, Australia, and description of a new species of Dacus Fabricius

New distribution records for 42 species of fruit flies (Diptera: Tephritidae: Dacinae) in Queensland are presented, resulting from exotic fruit fly monitoring from 1996 to 2011. Summaries of previously known Australian distributions are provided. Fruit flies were collected at cue lure and methyl eugenol traps and reared from host fruit. No new distributions south of Townsville were recorded for the economic species Bactrocera frauenfeldi (Schiner, 1868), Bactrocera kraussi (Hardy, 1951) and Bactrocera musae (Tryon, 1927). Minor range extensions are noted for Bactrocera neohumeralis (Hardy, 1951) and Bactrocera tryoni (Froggatt, 1897). Bactrocera jarvisi (Tryon, 1927) is recorded being weakly attracted to cue lure in Queensland and the first lure record (one specimen from cue lure) is provided for Dacus (Mellesis) petioliforma (May, 1956). Taxonomic issues with Bactrocera melanothoracica Drew (1989) and Bactrocera unirufa Drew (1989) are discussed. Dacus (Neodacus) coenensis sp. n. is described and illustrated from Cape York Peninsula.

Effects of three different nano-silver formulations on cut Acacia holosericea vase life

The relative efficacies of three chemically different nano-silver (NS) formulations were evaluated for their potential to extend the vase life of short-lived cut Acacia holosericea foliage. The novel proprietary formulations were neutral NS, acidic NS and ionic NS. They were characterised in terms of particle size, pH value, colour and odour. The NS treatments were applied as vase (lower concentrations) or pulse (higher concentrations) solutions. Among the treatments compared, neutral NS as a 4 mg L-1 vase solution or as a 40 mg L-1 24 h pulse treatment and acidic NS as a 0.5 mg L-1 vase solution or as a 5 mg L-1 24 h pulse treatment significantly (P <= 0.05) extended the vase life of A. holosericea. Vase life extensions over the deionised water (DI) controls were associated with better maintenance of relative fresh weight and vase water uptake, suppression of bacterial growth in the vase water and stem-end, and delaying stem blockage. In contrast, ionic-NS applied as a 0.5 or 1 mg L-1 vase solution treatment or as a 5 or 10 mg L-1 pulse treatment caused severe phytotoxicity to cut A. holosericea stems. The results suggest that NS treatments, especially neutral NS and acidic NS pulse treatments, could be a potential postharvest technology for commercial application to cut A. holosericea. (C) 2011 Elsevier B.V. All rights reserved.

Axisymmetric solidification in a long cylindrical mold

Using a new embedding technique, short time exact analytical solution of a two-dimensional axisymmetric problem of solidification of a superheated melt in a long cylindrical mold is presented in this paper. The prescribed flux could be space and time dependent. The method of solution is simple and is applicable to a variety of problems and consists of assuming suitable fictitious initial temperatures for some suitable fictitious extensions of the actual regions. The numerical results indicate that even a small solidified thickness can affect the initial temperature of the melt appreciably.

Bayesian model comparison in cosmology with Population Monte Carlo

We use Bayesian model selection techniques to test extensions of the standard flat LambdaCDM paradigm. Dark-energy and curvature scenarios, and primordial perturbation models are considered. To that end, we calculate the Bayesian evidence in favour of each model using Population Monte Carlo (PMC), a new adaptive sampling technique which was recently applied in a cosmological context. The Bayesian evidence is immediately available from the PMC sample used for parameter estimation without further computational effort, and it comes with an associated error evaluation. Besides, it provides an unbiased estimator of the evidence after any fixed number of iterations and it is naturally parallelizable, in contrast with MCMC and nested sampling methods. By comparison with analytical predictions for simulated data, we show that our results obtained with PMC are reliable and robust. The variability in the evidence evaluation and the stability for various cases are estimated both from simulations and from data. For the cases we consider, the log-evidence is calculated with a precision of better than 0.08. Using a combined set of recent CMB, SNIa and BAO data, we find inconclusive evidence between flat LambdaCDM and simple dark-energy models. A curved Universe is moderately to strongly disfavoured with respect to a flat cosmology. Using physically well-motivated priors within the slow-roll approximation of inflation, we find a weak preference for a running spectral index. A Harrison-Zel'dovich spectrum is weakly disfavoured. With the current data, tensor modes are not detected; the large prior volume on the tensor-to-scalar ratio r results in moderate evidence in favour of r=0.

On the Geometry of Infinite-Dimensional Grassmannian Manifolds and Gauge Theory

This PhD Thesis is about certain infinite-dimensional Grassmannian manifolds that arise naturally in geometry, representation theory and mathematical physics. From the physics point of view one encounters these infinite-dimensional manifolds when trying to understand the second quantization of fermions. The many particle Hilbert space of the second quantized fermions is called the fermionic Fock space. A typical element of the fermionic Fock space can be thought to be a linear combination of the configurations m particles and n anti-particles . Geometrically the fermionic Fock space can be constructed as holomorphic sections of a certain (dual)determinant line bundle lying over the so called restricted Grassmannian manifold, which is a typical example of an infinite-dimensional Grassmannian manifold one encounters in QFT. The construction should be compared with its well-known finite-dimensional analogue, where one realizes an exterior power of a finite-dimensional vector space as the space of holomorphic sections of a determinant line bundle lying over a finite-dimensional Grassmannian manifold. The connection with infinite-dimensional representation theory stems from the fact that the restricted Grassmannian manifold is an infinite-dimensional homogeneous (Kähler) manifold, i.e. it is of the form G/H where G is a certain infinite-dimensional Lie group and H its subgroup. A central extension of G acts on the total space of the dual determinant line bundle and also on the space its holomorphic sections; thus G admits a (projective) representation on the fermionic Fock space. This construction also induces the so called basic representation for loop groups (of compact groups), which in turn are vitally important in string theory / conformal field theory. The Thesis consists of three chapters: the first chapter is an introduction to the backround material and the other two chapters are individually written research articles. The first article deals in a new way with the well-known question in Yang-Mills theory, when can one lift the action of the gauge transformation group on the space of connection one forms to the total space of the Fock bundle in a compatible way with the second quantized Dirac operator. In general there is an obstruction to this (called the Mickelsson-Faddeev anomaly) and various geometric interpretations for this anomaly, using such things as group extensions and bundle gerbes, have been given earlier. In this work we give a new geometric interpretation for the Faddeev-Mickelsson anomaly in terms of differentiable gerbes (certain sheaves of categories) and central extensions of Lie groupoids. The second research article deals with the question how to define a Dirac-like operator on the restricted Grassmannian manifold, which is an infinite-dimensional space and hence not in the landscape of standard Dirac operator theory. The construction relies heavily on infinite-dimensional representation theory and one of the most technically demanding challenges is to be able to introduce proper normal orderings for certain infinite sums of operators in such a way that all divergences will disappear and the infinite sum will make sense as a well-defined operator acting on a suitable Hilbert space of spinors. This research article was motivated by a more extensive ongoing project to construct twisted K-theory classes in Yang-Mills theory via a Dirac-like operator on the restricted Grassmannian manifold.

Mining Sequential Data – in Search of Segmental Structures

Segmentation is a data mining technique yielding simplified representations of sequences of ordered points. A sequence is divided into some number of homogeneous blocks, and all points within a segment are described by a single value. The focus in this thesis is on piecewise-constant segments, where the most likely description for each segment and the most likely segmentation into some number of blocks can be computed efficiently. Representing sequences as segmentations is useful in, e.g., storage and indexing tasks in sequence databases, and segmentation can be used as a tool in learning about the structure of a given sequence. The discussion in this thesis begins with basic questions related to segmentation analysis, such as choosing the number of segments, and evaluating the obtained segmentations. Standard model selection techniques are shown to perform well for the sequence segmentation task. Segmentation evaluation is proposed with respect to a known segmentation structure. Applying segmentation on certain features of a sequence is shown to yield segmentations that are significantly close to the known underlying structure. Two extensions to the basic segmentation framework are introduced: unimodal segmentation and basis segmentation. The former is concerned with segmentations where the segment descriptions first increase and then decrease, and the latter with the interplay between different dimensions and segments in the sequence. These problems are formally defined and algorithms for solving them are provided and analyzed. Practical applications for segmentation techniques include time series and data stream analysis, text analysis, and biological sequence analysis. In this thesis segmentation applications are demonstrated in analyzing genomic sequences.