Conifer defence against insects: microarray gene expression profiling of Sitka spruce (Picea sitchensis) induced by mechanical wounding or feeding by spruce budworms (Choristoneura occidentalis) or white pine weevils (Pissodes strobi) reveals large

Conifers are resistant to attack from a large number of potential herbivores or pathogens. Previous molecular and biochemical characterization of selected conifer defence systems support a model of multigenic, constitutive and induced defences that act on invading insects via physical, chemical, biochemical or ecological (multitrophic) mechanisms. However, the genomic foundation of the complex defence and resistance mechanisms of conifers is largely unknown. As part of a genomics strategy to characterize inducible defences and possible resistance mechanisms of conifers against insect herbivory, we developed a cDNA microarray building upon a new spruce (Picea spp.) expressed sequence tag resource. This first-generation spruce cDNA microarray contains 9720 cDNA elements representing c. 5500 unique genes. We used this array to monitor gene expression in Sitka spruce (Picea sitchensis) bark in response to herbivory by white pine weevils (Pissodes strobi, Curculionidae) or wounding, and in young shoot tips in response to western spruce budworm (Choristoneura occidentalis, Lepidopterae) feeding. Weevils are stem-boring insects that feed on phloem, while budworms are foliage feeding larvae that consume needles and young shoot tips. Both insect species and wounding treatment caused substantial changes of the host plant transcriptome detected in each case by differential gene expression of several thousand array elements at 1 or 2 d after the onset of treatment. Overall, there was considerable overlap among differentially expressed gene sets from these three stress treatments. Functional classification of the induced transcripts revealed genes with roles in general plant defence, octadecanoid and ethylene signalling, transport, secondary metabolism, and transcriptional regulation. Several genes involved in primary metabolic processes such as photosynthesis were down-regulated upon insect feeding or wounding, fitting with the concept of dynamic resource allocation in plant defence. Refined expression analysis using gene-specific primers and real-time PCR for selected transcripts was in agreement with microarray results for most genes tested. This study provides the first large-scale survey of insect-induced defence transcripts in a gymnosperm and provides a platform for functional investigation of plant-insect interactions in spruce. Induction of spruce genes of octadecanoid and ethylene signalling, terpenoid biosynthesis, and phenolic secondary metabolism are discussed in more detail.

Quantitative evaluation of route allocation solutions at large-scale passenger stations

Routing trains within passenger stations in major cities is a common scheduling problem for railway operation. Various studies have been undertaken to derive and formulate solutions to this route allocation problem (RAP) which is particularly evident in mainland China nowadays because of the growing traffic demand and limited station capacity. A reasonable solution must be selected from a set of available RAP solutions attained in the planning stage to facilitate station operation. The selection is however based on the experience of the operators only and objective evaluation of the solutions is rarely addressed. In order to maximise the utilisation of station capacity while maintaining service quality and allowing for service disturbance, quantitative evaluation of RAP solutions is highly desirable. In this study, quantitative evaluation of RAP solutions is proposed and it is enabled by a set of indices covering infrastructure utilisation, buffer times and delay propagation. The proposed evaluation is carried out on a number of RAP solutions at a real-life busy railway station in mainland China and the results highlight the effectiveness of the indices in pinpointing the strengths and weaknesses of the solutions. This study provides the necessary platform to improve the RAP solution in planning and to allow train re-routing upon service disturbances.

A review of simulation models for railway systems

With the advances in computer hardware and software development techniques in the past 25 years, digital computer simulation of train movement and traction systems has been widely adopted as a standard computer-aided engineering tool [1] during the design and development stages of existing and new railway systems. Simulators of different approaches and scales are used extensively to investigate various kinds of system studies. Simulation is now proven to be the cheapest means to carry out performance predication and system behaviour characterisation. When computers were first used to study railway systems, they were mainly employed to perform repetitive but time-consuming computational tasks, such as matrix manipulations for power network solution and exhaustive searches for optimal braking trajectories. With only simple high-level programming languages available at the time, full advantage of the computing hardware could not be taken. Hence, structured simulations of the whole railway system were not very common. Most applications focused on isolated parts of the railway system. It is more appropriate to regard those applications as primarily mechanised calculations rather than simulations. However, a railway system consists of a number of subsystems, such as train movement, power supply and traction drives, which inevitably contains many complexities and diversities. These subsystems interact frequently with each other while the trains are moving; and they have their special features in different railway systems. To further complicate the simulation requirements, constraints like track geometry, speed restrictions and friction have to be considered, not to mention possible non-linearities and uncertainties in the system. In order to provide a comprehensive and accurate account of system behaviour through simulation, a large amount of data has to be organised systematically to ensure easy access and efficient representation; the interactions and relationships among the subsystems should be defined explicitly. These requirements call for sophisticated and effective simulation models for each component of the system. The software development techniques available nowadays allow the evolution of such simulation models. Not only can the applicability of the simulators be largely enhanced by advanced software design, maintainability and modularity for easy understanding and further development, and portability for various hardware platforms are also encouraged. The objective of this paper is to review the development of a number of approaches to simulation models. Attention is, in particular, given to models for train movement, power supply systems and traction drives. These models have been successfully used to enable various ‘what-if’ issues to be resolved effectively in a wide range of applications, such as speed profiles, energy consumption, run times etc.

Efficient querying of large process model repositories

Recent years have seen an increased uptake of business process management technology in industries. This has resulted in organizations trying to manage large collections of business process models. One of the challenges facing these organizations concerns the retrieval of models from large business process model repositories. For example, in some cases new process models may be derived from existing models, thus finding these models and adapting them may be more effective and less error-prone than developing them from scratch. Since process model repositories may be large, query evaluation may be time consuming. Hence, we investigate the use of indexes to speed up this evaluation process. To make our approach more applicable, we consider the semantic similarity between labels. Experiments are conducted to demonstrate that our approach is efficient.

Meshless TL and UL approaches for large deformation analysis

To accurately and effectively simulate large deformation is one of the major challenges in numerical modeling of metal forming. In this paper, an adaptive local meshless formulation based on the meshless shape functions and the local weak-form is developed for the large deformation analysis. Total Lagrangian (TL) and the Updated Lagrangian (UL) approaches are used and thoroughly compared each other in computational efficiency and accuracy. It has been found that the developed meshless technique provides a superior performance to the conventional FEM in dealing with large deformation problems for metal forming. In addition, the TL has better computational efficiency than the UL. However, the adaptive analysis is much more efficient using the UL approach than using in the TL approach.

Pattern-Based Evaluation of Scientific Workflow Management Systems

In recent years several scientific Workflow Management Systems (WfMSs) have been developed with the aim to automate large scale scientific experiments. As yet, many offerings have been developed, but none of them has been promoted as an accepted standard. In this paper we propose a pattern-based evaluation of three among the most widely used scientific WfMSs: Kepler, Taverna and Triana. The aim is to compare them with traditional business WfMSs, emphasizing the strengths and deficiencies of both systems. Moreover, a set of new patterns is defined from the analysis of the three considered systems.

Lean project management in large scale industrial project via standardization

Lean project management is the comprehensive adaption of other lean concept like lean construction, lean manufacturing and lean thinking into project management context. Execution of many similar industrial projects creates the idea of lean project management in companies and rapidly growing in industries. This paper offers the standardization method in order to achieve Lean project management in large scale industrial project. Standardization refers to all activity which makes two projects most identical and unify to each other like standardization of design, reducing output variability, value analysis and strategic management. Although standard project may have minor effi ciency decrease, compare to custom built project; but great advantage of standard project like cost saving, time reduction and quality improvement justify standardization methodology. This paper based on empirical experience in industrial project and theoretical analysis of benefi ts of project standardization.

Multi-objective four-dimensional vehicle motion planning in large dynamic environments

This paper presents Multi-Step A* (MSA*), a search algorithm based on A* for multi-objective 4D vehicle motion planning (three spatial and one time dimension). The research is principally motivated by the need for offline and online motion planning for autonomous Unmanned Aerial Vehicles (UAVs). For UAVs operating in large, dynamic and uncertain 4D environments, the motion plan consists of a sequence of connected linear tracks (or trajectory segments). The track angle and velocity are important parameters that are often restricted by assumptions and grid geometry in conventional motion planners. Many existing planners also fail to incorporate multiple decision criteria and constraints such as wind, fuel, dynamic obstacles and the rules of the air. It is shown that MSA* finds a cost optimal solution using variable length, angle and velocity trajectory segments. These segments are approximated with a grid based cell sequence that provides an inherent tolerance to uncertainty. Computational efficiency is achieved by using variable successor operators to create a multi-resolution, memory efficient lattice sampling structure. Simulation studies on the UAV flight planning problem show that MSA* meets the time constraints of online replanning and finds paths of equivalent cost but in a quarter of the time (on average) of vector neighbourhood based A*.

Large-scale fabrication of H2(H2O)Nb2O6 and Nb2O5 hollow microspheres

Hollow micro-sized H2(H2O)Nb2O6 spheres constructed by nanocrystallites have been successfully synthesized via a bubble-template assisted hydrothermal process. In the reaction process, H2O2 acts as a bubble generator and plays a key role in the formation of the hollow structure. An in situ bubble-template mechanism has been proposed for the possible formation of the hollow structure. The spherelike assemblies of these H2(H2O)Nb2O6 nanoparticles have been transformed into their corresponding pseudohexagonal phase Nb2O5 through a moderate annealing dehydration process without destroying the hierarchical structure. Optical properties of the as-prepared hollow spheres were investigated. It is exciting that the absorption edge of the hollow Nb2O5 microspheres shifts about 18 nm to the violet compared with bulk powders in the UV/vis spectra, indicating its superior optical properties.

Variable structure control for power systems stabilization

The application of variable structure control (VSC) for power systems stabilization is studied in this paper. It is the application, aspects and constraints of VSC which are of particular interest. A variable structure control methodology has been proposed for power systems stabilization. The method is implemented using thyristor controlled series compensators. A three machine power system is stabilized using a switching line control for large disturbances which becomes a sliding control as the disturbance becomes smaller. The results demonstrate the effectiveness of the methodology proposed as an useful tool to suppress the oscillations in power systems.

Online environmental information systems

In today’s information society, electronic tools, such as computer networks for the rapid transfer of data and composite databases for information storage and management, are critical in ensuring effective environmental management. In particular environmental policies and programs for federal, state, and local governments need a large volume of up-to-date information on the quality of water, air, and soil in order to conserve and protect natural resources and to carry out meteorology. In line with this, the utilization of information and communication technologies (ICTs) is crucial to preserve and improve the quality of life. In handling tasks in the field of environmental protection a range of environmental and technical information is often required for a complex and mutual decision making in a multidisciplinary team environment. In this regard e-government provides a foundation of the transformative ICT initiative which can lead to better environmental governance, better services, and increased public participation in environmental decision- making process.

Conceptualising use for information systems (IS) success

This thesis conceptualises Use for IS (Information Systems) success. While Use in this study describes the extent to which an IS is incorporated into the user’s processes or tasks, success of an IS is the measure of the degree to which the person using the system is better off. For IS success, the conceptualisation of Use offers new perspectives on describing and measuring Use. We test the philosophies of the conceptualisation using empirical evidence in an Enterprise Systems (ES) context. Results from the empirical analysis contribute insights to the existing body of knowledge on the role of Use and demonstrate Use as an important factor and measure of IS success. System Use is a central theme in IS research. For instance, Use is regarded as an important dimension of IS success. Despite its recognition, the Use dimension of IS success reportedly suffers from an all too simplistic definition, misconception, poor specification of its complex nature, and an inadequacy of measurement approaches (Bokhari 2005; DeLone and McLean 2003; Zigurs 1993). Given the above, Burton-Jones and Straub (2006) urge scholars to revisit the concept of system Use, consider a stronger theoretical treatment, and submit the construct to further validation in its intended nomological net. On those considerations, this study re-conceptualises Use for IS success. The new conceptualisation adopts a work-process system-centric lens and draws upon the characteristics of modern system types, key user groups and their information needs, and the incorporation of IS in work processes. With these characteristics, the definition of Use and how it may be measured is systematically established. Use is conceptualised as a second-order measurement construct determined by three sub-dimensions: attitude of its users, depth, and amount of Use. The construct is positioned in a modified IS success research model, in an attempt to demonstrate its central role in determining IS success in an ES setting. A two-stage mixed-methods research design—incorporating a sequential explanatory strategy—was adopted to collect empirical data and to test the research model. The first empirical investigation involved an experiment and a survey of ES end users at a leading tertiary education institute in Australia. The second, a qualitative investigation, involved a series of interviews with real-world operational managers in large Indian private-sector companies to canvass their day-to-day experiences with ES. The research strategy adopted has a stronger quantitative leaning. The survey analysis results demonstrate the aptness of Use as an antecedent and a consequence of IS success, and furthermore, as a mediator between the quality of IS and the impacts of IS on individuals. Qualitative data analysis on the other hand, is used to derive a framework for classifying the diversity of ES Use behaviour. The qualitative results establish that workers Use IS in their context to orientate, negotiate, or innovate. The implications are twofold. For research, this study contributes to cumulative IS success knowledge an approach for defining, contextualising, measuring, and validating Use. For practice, research findings not only provide insights for educators when incorporating ES for higher education, but also demonstrate how operational managers incorporate ES into their work practices. Research findings leave the way open for future, larger-scale research into how industry practitioners interact with an ES to complete their work in varied organisational environments.

User profiling based on folksonomy information in Web 2.0 for personalized recommender systems

Information overload has become a serious issue for web users. Personalisation can provide effective solutions to overcome this problem. Recommender systems are one popular personalisation tool to help users deal with this issue. As the base of personalisation, the accuracy and efficiency of web user profiling affects the performances of recommender systems and other personalisation systems greatly. In Web 2.0, the emerging user information provides new possible solutions to profile users. Folksonomy or tag information is a kind of typical Web 2.0 information. Folksonomy implies the users‘ topic interests and opinion information. It becomes another source of important user information to profile users and to make recommendations. However, since tags are arbitrary words given by users, folksonomy contains a lot of noise such as tag synonyms, semantic ambiguities and personal tags. Such noise makes it difficult to profile users accurately or to make quality recommendations. This thesis investigates the distinctive features and multiple relationships of folksonomy and explores novel approaches to solve the tag quality problem and profile users accurately. Harvesting the wisdom of crowds and experts, three new user profiling approaches are proposed: folksonomy based user profiling approach, taxonomy based user profiling approach, hybrid user profiling approach based on folksonomy and taxonomy. The proposed user profiling approaches are applied to recommender systems to improve their performances. Based on the generated user profiles, the user and item based collaborative filtering approaches, combined with the content filtering methods, are proposed to make recommendations. The proposed new user profiling and recommendation approaches have been evaluated through extensive experiments. The effectiveness evaluation experiments were conducted on two real world datasets collected from Amazon.com and CiteULike websites. The experimental results demonstrate that the proposed user profiling and recommendation approaches outperform those related state-of-the-art approaches. In addition, this thesis proposes a parallel, scalable user profiling implementation approach based on advanced cloud computing techniques such as Hadoop, MapReduce and Cascading. The scalability evaluation experiments were conducted on a large scaled dataset collected from Del.icio.us website. This thesis contributes to effectively use the wisdom of crowds and expert to help users solve information overload issues through providing more accurate, effective and efficient user profiling and recommendation approaches. It also contributes to better usages of taxonomy information given by experts and folksonomy information contributed by users in Web 2.0.

A hybrid recommender systems based on weighted tags

Social tags in web 2.0 are becoming another important information source to describe the content of items as well as to profile users’ topic preferences. However, as arbitrary words given by users, tags contains a lot of noise such as tag synonym and semantic ambiguity a large number personal tags that only used by one user, which brings challenges to effectively use tags to make item recommendations. To solve these problems, this paper proposes to use a set of related tags along with their weights to represent semantic meaning of each tag for each user individually. A hybrid recommendation generation approaches that based on the weighted tags are proposed. We have conducted experiments using the real world dataset obtained from Amazon.com. The experimental results show that the proposed approaches outperform the other state of the art approaches.

Exponentiated gradient algorithms for large-margin structured classification

We consider the problem of structured classification, where the task is to predict a label y from an input x, and y has meaningful internal structure. Our framework includes supervised training of Markov random fields and weighted context-free grammars as special cases. We describe an algorithm that solves the large-margin optimization problem defined in [12], using an exponential-family (Gibbs distribution) representation of structured objects. The algorithm is efficient—even in cases where the number of labels y is exponential in size—provided that certain expectations under Gibbs distributions can be calculated efficiently. The method for structured labels relies on a more general result, specifically the application of exponentiated gradient updates [7, 8] to quadratic programs.