Using stochastic dynamic programming to determine optimal fire management for Banksia ornata

1. A model of the population dynamics of Banksia ornata was developed, using stochastic dynamic programming (a state-dependent decision-making tool), to determine optimal fire management strategies that incorporate trade-offs between biodiversity conservation and fuel reduction. 2. The modelled population of B. ornata was described by its age and density, and was exposed to the risk of unplanned fires and stochastic variation in germination success. 3. For a given population in each year, three management strategies were considered: (i) lighting a prescribed fire; (ii) controlling the incidence of unplanned fire; (iii) doing nothing. 4. The optimal management strategy depended on the state of the B. ornata population, with the time since the last fire (age of the population) being the most important variable. Lighting a prescribed fire at an age of less than 30 years was only optimal when the density of seedlings after a fire was low (< 100 plants ha(-1)) or when there were benefits of maintaining a low fuel load by using more frequent fire. 5. Because the cost of management was assumed to be negligible (relative to the value of the persistence of the population), the do-nothing option was never the optimal strategy, although lighting prescribed fires had only marginal benefits when the mean interval between unplanned fires was less than 20-30 years.

Modelling socially optimal land allocations for sugar cane growing in North Queensland: a linked mathematical programming and choice modelling study

A modelling framework is developed to determine the joint economic and environmental net benefits of alternative land allocation strategies. Estimates of community preferences for preservation of natural land, derived from a choice modelling study, are used as input to a model of agricultural production in an optimisation framework. The trade-offs between agricultural production and environmental protection are analysed using the sugar industry of the Herbert River district of north Queensland as an example. Spatially-differentiated resource attributes and the opportunity costs of natural land determine the optimal tradeoffs between production and conservation for a range of sugar prices.

A 2D numerical model for simulating the physics of fault systems

Simulations provide a powerful means to help gain the understanding of crustal fault system physics required to progress towards the goal of earthquake forecasting. Cellular Automata are efficient enough to probe system dynamics but their simplifications render interpretations questionable. In contrast, sophisticated elasto-dynamic models yield more convincing results but are too computationally demanding to explore phase space. To help bridge this gap, we develop a simple 2D elastodynamic model of parallel fault systems. The model is discretised onto a triangular lattice and faults are specified as split nodes along horizontal rows in the lattice. A simple numerical approach is presented for calculating the forces at medium and split nodes such that general nonlinear frictional constitutive relations can be modeled along faults. Single and multi-fault simulation examples are presented using a nonlinear frictional relation that is slip and slip-rate dependent in order to illustrate the model.

Combined glucosamine and chondroitin sulfate provides functional and structural benefit in the anterior cruciate ligament transection model

Evidence that combined glucosamine sulfate and chondroitin sulfate (Gluchon) or isolated glucosamine (Glu) modifies joint damage in osteoarthritis (OA) is still lacking. We studied joint pain and cartilage damage using the anterior cruciate ligament transection (ACLT) model. Wistar rats were subjected to ACLT of the right knee ( OA) or sham operation. Groups received either Glu (500 mg/kg), Gluchon (500 mg/kg glucosamine +400 mg/kg chondroitin) or vehicle (non-treated-NT) per os starting 7 days prior to ACLT until sacrifice at 70 days. Joint pain was evaluated daily using the rat-knee joint articular incapacitation test. Structural joint damage was assessed using histology and biochemistry as the chondroitin sulfate ( CS) content of cartilage by densitometry (microgram per milligram dried cartilage), comparing to standard CS. The molar weight (Mw) of the CS samples, used as a qualitative biochemical parameter, was obtained by comparing their relative mobility on a polyacrylamide gel electrophoresis to standard CS. Gluchon, but not Glu, significantly reduced joint pain (P<0.05) compared to NT. There was an increase in CS content in the OA group (77.7 +/- 8.3 mu g/mg) compared to sham (53.5 +/- 11.2 mu g/mg) (P<0.05). The CS from OA samples had higher Mw (4:62 +/- 0:24 x 10(4) g/mol) compared to sham (4:18 +/- 0:19 x 10(4) g/mol) (P<0.05). Gluchon administration significantly reversed both the increases in CS content (54.4 +/- 12.1 mu g/mg) and Mw (4:18 +/- 0:2 x 104 g/mol) as compared to NT. Isolated Glu decreased CS content though not reaching statistical significance. Cartilage histology alterations were also significantly prevented by Gluchon administration. Gluchon provides clinical (analgesia) and structural benefits in the ACLT model. This is the first demonstration that biochemical alterations occurring in parallel to histological damage in OA are prevented by Gluchon administration.

Recognition by toll-like receptor 2 induces antigen-presenting cell activation and Th1 programming during infection by Neospora caninum

Neospora caninum is an apicomplexan parasite responsible for major economic losses due to abortions in cattle. Toll-like receptors (TLRs) sense specific microbial products and direct downstream signaling pathways in immune cells, linking innate, and adaptive immunity. Here, we analyze the role of TLR2 on innate and adaptive immune responses during N. caninum infection. Inflammatory peritoneal macrophages and bone marrow-derived dendritic cells exposed to N. caninum-soluble antigens presented an upregulated expression of TLR2. Increased receptor expression was correlated to TLR2/MyD88-dependent antigen-presenting cell maturation and pro-inflammatory cytokine production after stimulation by antigens. Impaired innate responses observed after infection of mice genetically deficient for TLR2((-/-)) was followed by downregulation of adaptive T helper 1 (Th1) immunity, represented by diminished parasite-specific CD4(+) and CD8(+) T-cell proliferation, IFN-gamma:interleukin (IL)-10 ratio, and IgG subclass synthesis. In parallel, TLR2(-/-) mice presented higher parasite burden than wild-type (WT) mice at acute and chronic stages of infection. These results show that initial recognition of N. caninum by TLR2 participates in the generation of effector immune responses against N. caninum and imply that the receptor may be a target for future prophylactic strategies against neosporosis. Immunology and Cell Biology (2010) 88, 825-833; doi:10.1038/icb.2010.52; published online 20 April 2010

MapScript: A map algebra programming language incorporating neighborhood analysis

Map algebra is a data model and simple functional notation to study the distribution and patterns of spatial phenomena. It uses a uniform representation of space as discrete grids, which are organized into layers. This paper discusses extensions to map algebra to handle neighborhood operations with a new data type called a template. Templates provide general windowing operations on grids to enable spatial models for cellular automata, mathematical morphology, and local spatial statistics. A programming language for map algebra that incorporates templates and special processing constructs is described. The programming language is called MapScript. Example program scripts are presented to perform diverse and interesting neighborhood analysis for descriptive, model-based and processed-based analysis.

A formal model of real-time program compilation

Program compilation can be formally defined as a sequence of equivalence-preserving transformations, or refinements, from high-level language programs to assembler code, Recent models also incorporate timing properties, but the resulting formalisms are intimidatingly complex. Here we take advantage of a new, simple model of real-time refinement, based on predicate transformer semantics, to present a straightforward compilation formalism that incorporates real-time constraints. (C) 2002 Elsevier Science B.V. All rights reserved.

The Three-dimensional Solution Structure of NaD1, a New Floral Defensin from Nicotiana alata and its Application to a Homology Model of the Crop Defense Protein alfAFP

NMR spectroscopy and simulated annealing calculations have been used to determine the three-dimensional structure of NaD1, a novel antifungal and insecticidal protein isolated from the flowers of Nicotiana alata. NaD1 is a basic, cysteine-rich protein of 47 residues and is the first example of a plant defensin from flowers to be characterized structurally. Its three-dimensional structure consists of an a-helix and a triple-stranded anti-parallel beta-sheet that are stabilized by four intramolecular disulfide bonds. NaD1 features all the characteristics of the cysteine-stabilized up motif that has been described for a variety of proteins of differing functions ranging from antibacterial insect defensins and ion channel-perturbing scorpion toxins to an elicitor of the sweet taste response. The protein is biologically active against insect pests, which makes it a potential candidate for use in crop protection. NaD1 shares 31% sequence identity with alfAFP, an antifungal protein from alfalfa that confers resistance to a fungal pathogen in transgenic potatoes. The structure of NaD1 was used to obtain a homology model of alfAFP, since NaD1 has the highest level of sequence identity with alfAFP of any structurally characterized antifungal defensin. The structures of NaD1 and alfAFP were used in conjunction with structure - activity data for the radish defensin Rs-AFP2 to provide an insight into structure-function relationships. In particular, a putative effector site was identified in the structure of NaD1 and in the corresponding homology model of alfAFP. (C) 2002 Elsevier Science Ltd. All rights reserved.

The use of stochastic dynamic programming in optimal landscape reconstruction for metapopulations

A decision theory framework can be a powerful technique to derive optimal management decisions for endangered species. We built a spatially realistic stochastic metapopulation model for the Mount Lofty Ranges Southern Emu-wren (Stipiturus malachurus intermedius), a critically endangered Australian bird. Using diserete-time Markov,chains to describe the dynamics of a metapopulation and stochastic dynamic programming (SDP) to find optimal solutions, we evaluated the following different management decisions: enlarging existing patches, linking patches via corridors, and creating a new patch. This is the first application of SDP to optimal landscape reconstruction and one of the few times that landscape reconstruction dynamics have been integrated with population dynamics. SDP is a powerful tool that has advantages over standard Monte Carlo simulation methods because it can give the exact optimal strategy for every landscape configuration (combination of patch areas and presence of corridors) and pattern of metapopulation occupancy, as well as a trajectory of strategies. It is useful when a sequence of management actions can be performed over a given time horizon, as is the case for many endangered species recovery programs, where only fixed amounts of resources are available in each time step. However, it is generally limited by computational constraints to rather small networks of patches. The model shows that optimal metapopulation, management decisions depend greatly on the current state of the metapopulation,. and there is no strategy that is universally the best. The extinction probability over 30 yr for the optimal state-dependent management actions is 50-80% better than no management, whereas the best fixed state-independent sets of strategies are only 30% better than no management. This highlights the advantages of using a decision theory tool to investigate conservation strategies for metapopulations. It is clear from these results that the sequence of management actions is critical, and this can only be effectively derived from stochastic dynamic programming. The model illustrates the underlying difficulty in determining simple rules of thumb for the sequence of management actions for a metapopulation. This use of a decision theory framework extends the capacity of population viability analysis (PVA) to manage threatened species.

The variety of variables in automated real-time refinement

The refinement calculus is a well-established theory for deriving program code from specifications. Recent research has extended the theory to handle timing requirements, as well as functional ones, and we have developed an interactive programming tool based on these extensions. Through a number of case studies completed using the tool, this paper explains how the tool helps the programmer by supporting the many forms of variables needed in the theory. These include simple state variables as in the untimed calculus, trace variables that model the evolution of properties over time, auxiliary variables that exist only to support formal reasoning, subroutine parameters, and variables shared between parallel processes.

Phase equilibria and surface tension of pure fluids using a molecular layer structure theory (MLST) model

This paper presents a new model based on thermodynamic and molecular interaction between molecules to describe the vapour-liquid phase equilibria and surface tension of pure component. The model assumes that the bulk fluid can be characterised as set of parallel layers. Because of this molecular structure, we coin the model as the molecular layer structure theory (MLST). Each layer has two energetic components. One is the interaction energy of one molecule of that layer with all surrounding layers. The other component is the intra-layer Helmholtz free energy, which accounts for the internal energy and the entropy of that layer. The equilibrium between two separating phases is derived from the minimum of the grand potential, and the surface tension is calculated as the excess of the Helmholtz energy of the system. We test this model with a number of components, argon, krypton, ethane, n-butane, iso-butane, ethylene and sulphur hexafluoride, and the results are very satisfactory. (C) 2002 Elsevier Science B.V. All rights reserved.

MDAI: Model based Design in Automobile Industry

It is proposed a new approach based on a methodology, assisted by a tool, to create new products in the automobile industry based on previous defined processes and experiences inspired on a set of best practices or principles: it is based on high-level models or specifications; it is component-based architecture centric; it is based on generative programming techniques. This approach follows in essence the MDA (Model Driven Architecture) philosophy with some specific characteristics. We propose a repository that keeps related information, such as models, applications, design information, generated artifacts and even information concerning the development process itself (e.g., generation steps, tests and integration milestones). Generically, this methodology receives the users' requirements to a new product (e.g., functional, non-functional, product specification) as its main inputs and produces a set of artifacts (e.g., design parts, process validation output) as its main output, that will be integrated in the engineer design tool (e.g. CAD system) facilitating the work.

A risk-averse optimization model for trading wind energy in a market environment under uncertainty

In this paper, a stochastic programming approach is proposed for trading wind energy in a market environment under uncertainty. Uncertainty in the energy market prices is the main cause of high volatility of profits achieved by power producers. The volatile and intermittent nature of wind energy represents another source of uncertainty. Hence, each uncertain parameter is modeled by scenarios, where each scenario represents a plausible realization of the uncertain parameters with an associated occurrence probability. Also, an appropriate risk measurement is considered. The proposed approach is applied on a realistic case study, based on a wind farm in Portugal. Finally, conclusions are duly drawn. (C) 2011 Elsevier Ltd. All rights reserved.

Logic programming and fuzzy Monte Carlo for distribution network reconfiguration

This paper present a methodology to choose the distribution networks reconfiguration that presents the lower power losses. The proposed methodology is based on statistical failure and repair data of the distribution power system components and uses fuzzy-probabilistic modeling for system component outage parameters. The proposed hybrid method using fuzzy sets and Monte Carlo simulation based on the fuzzyprobabilistic models allows catching both randomness and fuzziness of component outage parameters. A logic programming algorithm is applied, once obtained the system states by Monte Carlo Simulation, to get all possible reconfigurations for each system state. To evaluate the line flows and bus voltages and to identify if there is any overloading, and/or voltage violation an AC load flow has been applied to select the feasible reconfiguration with lower power losses. To illustrate the application of the proposed methodology, the paper includes a case study that considers a 115 buses distribution network.

Combining RTSJ with Fork/Join: a priority-based model

This paper discusses the increased need to support dynamic task-level parallelism in embedded real-time systems and proposes a Java framework that combines the Real-Time Specification for Java (RTSJ) with the Fork/Join (FJ) model, following a fixed priority-based scheduling scheme. Our work intends to support parallel runtimes that will coexist with a wide range of other complex independently developed applications, without any previous knowledge about their real execution requirements, number of parallel sub-tasks, and when those sub-tasks will be generated.