Priority threat management of non-native plants to maintain ecosystem integrity across heterogeneous landscapes

Invasive non-native plants have negatively impacted on biodiversity and ecosystem functions world-wide. Because of the large number of species, their wide distributions and varying degrees of impact, we need a more effective method for prioritizing control strategies for cost-effective investment across heterogeneous landscapes. Here, we develop a prioritization framework that synthesizes scientific data, elicits knowledge from experts and stakeholders to identify control strategies, and appraises the cost-effectiveness of strategies. Our objective was to identify the most cost-effective strategies for reducing the total area dominated by high-impact non-native plants in the Lake Eyre Basin (LEB). We use a case study of the ˜120 million ha Lake Eyre Basin that comprises some of the most distinctive Australian landscapes, including Uluru-Kata Tjuta National Park. More than 240 non-native plant species are recorded in the Lake Eyre Basin, with many predicted to spread, but there are insufficient resources to control all species. Lake Eyre Basin experts identified 12 strategies to control, contain or eradicate non-native species over the next 50 years. The total cost of the proposed Lake Eyre Basin strategies was estimated at AU$1·7 billion, an average of AU$34 million annually. Implementation of these strategies is estimated to reduce non-native plant dominance by 17 million ha – there would be a 32% reduction in the likely area dominated by non-native plants within 50 years if these strategies were implemented. The three most cost-effective strategies were controlling Parkinsonia aculeata, Ziziphus mauritiana and Prosopis spp. These three strategies combined were estimated to cost only 0·01% of total cost of all the strategies, but would provide 20% of the total benefits. Over 50 years, cost-effective spending of AU$2·3 million could eradicate all non-native plant species from the only threatened ecological community within the Lake Eyre Basin, the Great Artesian Basin discharge springs. Synthesis and applications. Our framework, based on a case study of the ˜120 million ha Lake Eyre Basin in Australia, provides a rationale for financially efficient investment in non-native plant management and reveals combinations of strategies that are optimal for different budgets. It also highlights knowledge gaps and incidental findings that could improve effective management of non-native plants, for example addressing the reliability of species distribution data and prevalence of information sharing across states and regions.

Supersonic flutter of composite skin panels of repeated-sublaminate layup

In high-speed aerospace vehicles, supersonic flutter is a well-known phenomenon of dynamic instability to which external skin panels are prone. In theory, the instability stage is expressed by the 'flutter critical parameter' Q(crit), which is a function of the stiffness-, and dynamic pressure parameters. For a composite skin panel, Q(crit) can be maximised by lay-up optimisation. Repeated-sublaminate lay-up schemes possess good potential for economical lay-up optimisation because the corresponding effort is limited to a family of sublaminates of few layers only. When Q(crit) is obtained for all sublaminates of a family, and the sublaminates ranked accordingly, the resulting ranking reveals not only the optimum lay-up, but also the near-optimum lay-ups, which are useful design alternatives, and the inferior lay-ups which should be avoided. In this paper, we examine sublaminate-ranking characteristics for a composite panel prone to supersonic flutter. In particular, we consider a simple supported midplane-symmetrical rectangular panel of typical aspect ratio alpha and flow angle psi, and for four-layered sublaminates, obtain the Q(crit)-based rankings for a wide range of the number of repeats, r. From the rankings, we find that an optimum lay-up can exist for which the outermost layer is oriented wide of, rather than along, the flow. Furthermore, for many lay-ups other than the optimum and the inferior, we see that as r increases, Q(crit) undergoes significant change in the course of converging. To reconcile these findings, eigenvalue-coalescence characteristics are discussed in detail for specific cases.

A fuzzy dynamic flood routing model for natural channels

A fuzzy dynamic flood routing model (FDFRM) for natural channels is presented, wherein the flood wave can be approximated to a monoclinal wave. This study is based on modification of an earlier published work by the same authors, where the nature of the wave was of gravity type. Momentum equation of the dynamic wave model is replaced by a fuzzy rule based model, while retaining the continuity equation in its complete form. Hence, the FDFRM gets rid of the assumptions associated with the momentum equation. Also, it overcomes the necessity of calculating friction slope (S-f) in flood routing and hence the associated uncertainties are eliminated. The fuzzy rule based model is developed on an equation for wave velocity, which is obtained in terms of discontinuities in the gradient of flow parameters. The channel reach is divided into a number of approximately uniform sub-reaches. Training set required for development of the fuzzy rule based model for each sub-reach is obtained from discharge-area relationship at its mean section. For highly heterogeneous sub-reaches, optimized fuzzy rule based models are obtained by means of a neuro-fuzzy algorithm. For demonstration, the FDFRM is applied to flood routing problems in a fictitious channel with single uniform reach, in a fictitious channel with two uniform sub-reaches and also in a natural channel with a number of approximately uniform sub-reaches. It is observed that in cases of the fictitious channels, the FDFRM outputs match well with those of an implicit numerical model (INM), which solves the dynamic wave equations using an implicit numerical scheme. For the natural channel, the FDFRM Outputs are comparable to those of the HEC-RAS model.

Data-aware task scheduling for all-to-all comparison problems in heterogeneous distributed systems

Solving large-scale all-to-all comparison problems using distributed computing is increasingly significant for various applications. Previous efforts to implement distributed all-to-all comparison frameworks have treated the two phases of data distribution and comparison task scheduling separately. This leads to high storage demands as well as poor data locality for the comparison tasks, thus creating a need to redistribute the data at runtime. Furthermore, most previous methods have been developed for homogeneous computing environments, so their overall performance is degraded even further when they are used in heterogeneous distributed systems. To tackle these challenges, this paper presents a data-aware task scheduling approach for solving all-to-all comparison problems in heterogeneous distributed systems. The approach formulates the requirements for data distribution and comparison task scheduling simultaneously as a constrained optimization problem. Then, metaheuristic data pre-scheduling and dynamic task scheduling strategies are developed along with an algorithmic implementation to solve the problem. The approach provides perfect data locality for all comparison tasks, avoiding rearrangement of data at runtime. It achieves load balancing among heterogeneous computing nodes, thus enhancing the overall computation time. It also reduces data storage requirements across the network. The effectiveness of the approach is demonstrated through experimental studies.

Trade Liberalization, Heterogeneous Firms and Industrial Dynamics

This master thesis studies how trade liberalization affects the firm-level productivity and industrial evolution. To do so, I built a dynamic model that considers firm-level productivity as endogenous to investigate the influence of trade on firm’s productivity and the market structure. In the framework, heterogeneous firms in the same industry operate differently in equilibrium. Specifically, firms are ex ante identical but heterogeneity arises as an equilibrium outcome. Under the setting of monopolistic competition, this type of model yields an industry that is represented not by a steady-state outcome, but by an evolution that rely on the decisions made by individual firms. I prove that trade liberalization has a general positive impact on technological adoption rates and hence increases the firm-level productivity. Besides, this endogenous technology adoption model also captures the stylized facts: exporting firms are larger and more productive than their non-exporting counterparts in the same sector. I assume that the number of firms is endogenous, since, according to the empirical literature, the industrial evolution shows considerably different patterns across countries; some industries experience large scale of firms’ exit in the period of contracting market shares, while some industries display relative stable number of firms or gradually increase quantities. The special word “shakeout” is used to describe the dramatic decrease in the number of firms. In order to explain the causes of shakeout, I construct a model where forward-looking firms decide to enter and exit the market on the basis of their state of technology. In equilibrium, firms choose different dates to adopt innovation which generate a gradual diffusion process. It is exactly this gradual diffusion process that generates the rapid, large-scale exit phenomenon. Specifically, it demonstrates that there is a positive feedback between firm’s exit and adoption, the reduction in the number of firms increases the incentives for remaining firms to adopt innovation. Therefore, in the setting of complete information, this model not only generates a shakeout but also captures the stability of an industry. However, the solely national view of industrial evolution neglects the importance of international trade in determining the shape of market structure. In particular, I show that the higher trade barriers lead to more fragile markets, encouraging the over-entry in the initial stage of industry life cycle and raising the probability of a shakeout. Therefore, more liberalized trade generates more stable market structure from both national and international viewpoints. The main references are Ederington and McCalman(2008,2009).

Minimizing total weighted tardiness on heterogeneous batch processors with incompatible job families

In this paper, we address a scheduling problem for minimizing total weighted tardiness. The background for the paper is derived from the automobile gear manufacturing process. We consider the bottleneck operation of heat treatment stage of gear manufacturing. Real-life scenarios like unequal release times, incompatible job families, nonidentical job sizes, heterogeneous batch processors, and allowance for job splitting have been considered. We have developed a mathematical model which takes into account dynamic starting conditions. The problem considered in this study is NP-hard in nature, and hence heuristic algorithms have been proposed to address it. For real-life large-size problems, the performance of the proposed heuristic algorithms is evaluated using the method of estimated optimal solution available in literature. Extensive computational analyses reveal that the proposed heuristic algorithms are capable of consistently obtaining near-optimal statistically estimated solutions in very reasonable computational time.

PriDyn: Enabling Differentiated I/O Services in Cloud Using Dynamic Priorities

Virtualization is one of the key enabling technologies for Cloud computing. Although it facilitates improved utilization of resources, virtualization can lead to performance degradation due to the sharing of physical resources like CPU, memory, network interfaces, disk controllers, etc. Multi-tenancy can cause highly unpredictable performance for concurrent I/O applications running inside virtual machines that share local disk storage in Cloud. Disk I/O requests in a typical Cloud setup may have varied requirements in terms of latency and throughput as they arise from a range of heterogeneous applications having diverse performance goals. This necessitates providing differential performance services to different I/O applications. In this paper, we present PriDyn, a novel scheduling framework which is designed to consider I/O performance metrics of applications such as acceptable latency and convert them to an appropriate priority value for disk access based on the current system state. This framework aims to provide differentiated I/O service to various applications and ensures predictable performance for critical applications in multi-tenant Cloud environment. We demonstrate through experimental validations on real world I/O traces that this framework achieves appreciable enhancements in I/O performance, indicating that this approach is a promising step towards enabling QoS guarantees on Cloud storage.

Spatio-temporal correlations in aqueous systems: computational studies of static and dynamic heterogeneity by 2D-IR spectroscopy

Local heterogeneity is ubiquitous in natural aqueous systems. It can be caused locally by external biomolecular subsystems like proteins, DNA, micelles and reverse micelles, nanoscopic materials etc., but can also be intrinsic to the thermodynamic nature of the aqueous solution itself (like binary mixtures or at the gas-liquid interface). The altered dynamics of water in the presence of such diverse surfaces has attracted considerable attention in recent years. As these interfaces are quite narrow, only a few molecular layers thick, they are hard to study by conventional methods. The recent development of two dimensional infra-red (2D-IR) spectroscopy allows us to estimate length and time scales of such dynamics fairly accurately. In this work, we present a series of interesting studies employing two dimensional infra-red spectroscopy (2D-IR) to investigate (i) the heterogeneous dynamics of water inside reverse micelles of varying sizes, (ii) supercritical water near the Widom line that is known to exhibit pronounced density fluctuations and also study (iii) the collective and local polarization fluctuation of water molecules in the presence of several different proteins. The spatio-temporal correlation of confined water molecules inside reverse micelles of varying sizes is well captured through the spectral diffusion of corresponding 2D-IR spectra. In the case of supercritical water also, we observe a strong signature of dynamic heterogeneity from the elongated nature of the 2D-IR spectra. In this case the relaxation is ultrafast. We find remarkable agreement between the different tools employed to study the relaxation of density heterogeneity. For aqueous protein solutions, we find that the calculated dielectric constant of the respective systems unanimously shows a noticeable increment compared to that of neat water. However, the `effective' dielectric constant for successive layers shows significant variation, with the layer adjacent to the protein having a much lower value. Relaxation is also slowest at the surface. We find that the dielectric constant achieves the bulk value at distances more than 3 nm from the surface of the protein.

Falcon: A Graph Manipulation Language for Heterogeneous Systems

Graph algorithms have been shown to possess enough parallelism to keep several computing resources busy-even hundreds of cores on a GPU. Unfortunately, tuning their implementation for efficient execution on a particular hardware configuration of heterogeneous systems consisting of multicore CPUs and GPUs is challenging, time consuming, and error prone. To address these issues, we propose a domain-specific language (DSL), Falcon, for implementing graph algorithms that (i) abstracts the hardware, (ii) provides constructs to write explicitly parallel programs at a higher level, and (iii) can work with general algorithms that may change the graph structure (morph algorithms). We illustrate the usage of our DSL to implement local computation algorithms (that do not change the graph structure) and morph algorithms such as Delaunay mesh refinement, survey propagation, and dynamic SSSP on GPU and multicore CPUs. Using a set of benchmark graphs, we illustrate that the generated code performs close to the state-of-the-art hand-tuned implementations.

Molecular Cage Impregnated Palladium Nanoparticles: Efficient, Additive-Free Heterogeneous Catalysts for Cyanation of Aryl Halides

Two shape-persistent covalent cages (CC1(r) and CC2(r)) have been devised from triphenyl amine-based trialdehydes and cyclohexane diamine building blocks utilizing the dynamic imine chemistry followed by imine bond reduction. The cage compounds have been characterized by several spectroscopic techniques which suggest that CC1(r) and CC2(r) are 2+3] and 8+12] self-assembled architectures, respectively. These state-of-the-art molecules have a porous interior and stable aromatic backbone with multiple palladium binding sites to engineer the controlled synthesis and stabilization of ultrafine palladium nanoparticles (PdNPs). As-synthesized cage-embedded PdNPs have been characterized by transmission electron microscopy (TEM), scanning electron microscopy (SEM), and powder X-ray diffraction (PXRD). Inductively coupled plasma optical emission spectrometry reveals that Pd@CC1(r) and Pd@CC2(r) have 40 and 25 wt% palladium loading, respectively. On the basis of TEM analysis, it has been estimated that as small as similar to 1.8 nm PdNPs could be stabilized inside the CC1(r), while larger CC2(r) could stabilize similar to 3.7 nm NPs. In contrast, reduction of palladium salts in the absence of the cages form structure less agglomerates. The well-dispersed cage-embedded NPs exhibit efficient catalytic performance in the cyanation of aryl halides under heterogeneous, additive-free condition. Moreover, these materials have excellent stability and recyclability without any agglomeration of PdNPs after several cycles.

A dynamic view of the spread and intracellular distribution of Salmonella enterica.

The events that determine the dynamics of proliferation, spread and distribution of microbial pathogens within their hosts are surprisingly heterogeneous and poorly understood. We contend that understanding these phenomena at a sophisticated level with the help of mathematical models is a prerequisite for the development of truly novel, targeted preventative measures and drug regimes. We describe here recent studies of Salmonella enterica infections in mice which suggest that bacteria resist the antimicrobial environment inside host cells and spread to new sites, where infection foci develop, and thus avoid local escalation of the adaptive immune response. We further describe implications for our understanding of the pathogenic mechanism inside the host.

Catastrophic Rupture Induced Damage Coalescence in Heterogeneous Brittle Media

In heterogeneous brittle media, the evolution of damage is strongly influenced by the multiscale coupling effect. To better understand this effect, we perform a detailed investigation of the damage evolution, with particular attention focused on the catastrophe transition. We use an adaptive multiscale finite-element model (MFEM) to simulate the damage evolution and the catastrophic failure of heterogeneous brittle media. Both plane stress and plane strain cases are investigated for a heterogeneous medium whose initial shear strength follows the Weibull distribution. Damage is induced through the application of the Coulomb failure criterion to each element, and the element mesh is refined where the failure criterion is met. We found that as damage accumulates, there is a stronger and stronger nonlinear increase in stress and the stress redistribution distance. The coupling of the dynamic stress redistribution and the heterogeneity at different scales result in an inverse cascade of damage cluster size, which represents rapid coalescence of damage at the catastrophe transition.

Comparison Of The Quasi-Static Method And The Dynamic Method For Simulating Fracture Processes In Concrete

Concrete is heterogeneous and usually described as a three-phase material, where matrix, aggregate and interface are distinguished. To take this heterogeneity into consideration, the Generalized Beam (GB) lattice model is adopted. The GB lattice model is much more computationally efficient than the beam lattice model. Numerical procedures of both quasi-static method and dynamic method are developed to simulate fracture processes in uniaxial tensile tests conducted on a concrete panel. Cases of different loading rates are compared with the quasi-static case. It is found that the inertia effect due to load increasing becomes less important and can be ignored with the loading rate decreasing, but the inertia effect due to unstable crack propagation remains considerable no matter how low the loading rate is. Therefore, an unrealistic result will be obtained if a fracture process including unstable cracking is simulated by the quasi-static procedure.

Catastrophic Rupture Induced Damage Coalescence in Heterogeneous Brittle Media

In heterogeneous brittle media, the evolution of damage is strongly influenced by the multiscale coupling effect. To better understand this effect, we perform a detailed investigation of the damage evolution, with particular attention focused on the catastrophe transition. We use an adaptive multiscale finite-element model (MFEM) to simulate the damage evolution and the catastrophic failure of heterogeneous brittle media. Both plane stress and plane strain cases are investigated for a heterogeneous medium whose initial shear strength follows the Weibull distribution. Damage is induced through the application of the Coulomb failure criterion to each element, and the element mesh is refined where the failure criterion is met. We found that as damage accumulates, there is a stronger and stronger nonlinear increase in stress and the stress redistribution distance. The coupling of the dynamic stress redistribution and the heterogeneity at different scales result in an inverse cascade of damage cluster size, which represents rapid coalescence of damage at the catastrophe transition.

Deformation and fracture of impulsively loaded sandwich panels

Light metal sandwich panel structures with cellular cores have attracted interest for multifunctional applications which exploit their high bend strength and impact energy absorption. This concept has been explored here using a model 6061-T6 aluminum alloy system fabricated by friction stir weld joining extruded sandwich panels with a triangular corrugated core. Micro-hardness and miniature tensile coupon testing revealed that friction stir welding reduced the strength and ductility in the welds and a narrow heat affected zone on either side of the weld by approximately 30%. Square, edge clamped sandwich panels and solid plates of equal mass per unit area were subjected to localized impulsive loading by the impact of explosively accelerated, water saturated, sand shells. The hydrodynamic load and impulse applied by the sand were gradually increased by reducing the stand-off distance between the test charge and panel surfaces. The sandwich panels suffered global bending and stretching, and localized core crushing. As the pressure applied by the sand increased, face sheet fracture by a combination of tensile stretching and shear-off occurred first at the two clamped edges of the panels that were parallel with the corrugation and weld direction. The plane of these fractures always lay within the heat affected zone of the longitudinal welds. For the most intensively loaded panels additional cracks occurred at the other clamped boundaries and in the center of the panel. To investigate the dynamic deformation and fracture processes, a particle-based method has been used to simulate the impulsive loading of the panels. This has been combined with a finite element analysis utilizing a modified Johnson-Cook constitutive relation and a Cockcroft-Latham fracture criterion that accounted for local variation in material properties. The fully coupled simulation approach enabled the relationships between the soil-explosive test charge design, panel geometry, spatially varying material properties and the panel's deformation and dynamic failure responses to be explored. This comprehensive study reveals the existence of a strong instability in the loading that results from changes in sand particle reflection during dynamic evolution of the panel's surface topology. Significant fluid-structure interaction effects are also discovered at the sample sides and corners due to changes of the sand reflection angle by the edge clamping system. © 2012 Elsevier Ltd. All rights reserved.