Livestock infectious disease and climate change: a review of selected literature

It is indisputable that climate is an important factor in many livestock diseases. Nevertheless, our knowledge of the impact of climate change on livestock infectious diseases is much less certain.Therefore, the aim of the article is to conduct a systematic review of the literature on the topic utilizing available retrospective data and information. Across a corpus of 175 formal publications,limited empirical evidence was offered to underpin many of the main arguments. The literature reviewed was highly polarized and often inconsistent regarding what the future may hold. Historical explorations were rare. However, identifying past drivers to livestock disease may not fully capture the extent that new and unknown drivers will influence future change. As such, our current predictive capacity is low. We offer a number of recommendations to strengthen this capacity in the coming years. We conclude that our current approach to research on the topic is limiting and unlikely to yield sufficient, actionable evidence to inform future praxis. Therefore, we argue for the creation of a reflexive, knowledge-based system, underpinned by a collective intelligence framework to support the drawing of inferences across the literature.

Resource determinants of strategy and performance: the case of British exporters

This study adopts the RBV of the firm in order to identify critical advantage-generating resources and capabilities with strong positive export strategy and performance implications. The proposed export performance model is tested using a structural equation modeling approach on a sample of 356 British exporters. We examine the individual as well as the concurrent (simultaneous) direct and indirect effects of five resource bundles on export performance. We find that four resources/capabilities: managerial, knowledge, planning, and technology, have a significant positive direct effect on export performance, while relational and physical resources exhibited no unique positive effect. We also find that the firm’s export strategy mediates the resource-performance nexus in the case of managerial and knowledge-based resources. The theoretical and methodological grounding of this study contributes to the advancement of export related research by providing better specification of the nature of the effects – direct or indirect – of particular resource factors on export performance.

Jmax-pruning: a facility for the information theoretic pruning of modular classification rules

The Prism family of algorithms induces modular classification rules in contrast to the Top Down Induction of Decision Trees (TDIDT) approach which induces classification rules in the intermediate form of a tree structure. Both approaches achieve a comparable classification accuracy. However in some cases Prism outperforms TDIDT. For both approaches pre-pruning facilities have been developed in order to prevent the induced classifiers from overfitting on noisy datasets, by cutting rule terms or whole rules or by truncating decision trees according to certain metrics. There have been many pre-pruning mechanisms developed for the TDIDT approach, but for the Prism family the only existing pre-pruning facility is J-pruning. J-pruning not only works on Prism algorithms but also on TDIDT. Although it has been shown that J-pruning produces good results, this work points out that J-pruning does not use its full potential. The original J-pruning facility is examined and the use of a new pre-pruning facility, called Jmax-pruning, is proposed and evaluated empirically. A possible pre-pruning facility for TDIDT based on Jmax-pruning is also discussed.

Computationally efficient induction of classification rules with the PMCRI and J-PMCRI frameworks

In order to gain knowledge from large databases, scalable data mining technologies are needed. Data are captured on a large scale and thus databases are increasing at a fast pace. This leads to the utilisation of parallel computing technologies in order to cope with large amounts of data. In the area of classification rule induction, parallelisation of classification rules has focused on the divide and conquer approach, also known as the Top Down Induction of Decision Trees (TDIDT). An alternative approach to classification rule induction is separate and conquer which has only recently been in the focus of parallelisation. This work introduces and evaluates empirically a framework for the parallel induction of classification rules, generated by members of the Prism family of algorithms. All members of the Prism family of algorithms follow the separate and conquer approach.

Animal infectious disease and climate change: a selected review

It is indisputable that climate is an important factor in many livestock diseases. Nevertheless, our knowledge of the impact of climate change on livestock infectious diseases is much less certain. Therefore, the aim of the article is to conduct a systematic review of the literature on the topic utilizing available retrospective data and information. Across a corpus of 175 formal publications, limited empirical evidence was offered to underpin many of the main arguments. The literature reviewed was highly polarized and often inconsistent regarding what the future may hold. Historical explorations were rare. However, identifying past drivers to livestock disease may not fully capture the extent that new and unknown drivers will influence future change. As such, our current predictive capacity is low. We offer a number of recommendations to strengthen this capacity in the coming years. We conclude that our current approach to research on the topic is limiting and unlikely to yield sufficient, actionable evidence to inform future praxis. Therefore, we argue for the creation of a reflexive, knowledge-based system, underpinned by a collective intelligence framework to support the drawing of inferences across the literature.

Evaluation and revision of inferential comprehension in narrative texts: an eye movement study

We investigated the processes of how adult readers evaluate and revise their situation model during reading by monitoring their eye movements as they read narrative texts and subsequent critical sentences. In each narrative text, a short introduction primed a knowledge-based inference, followed by a target concept that was either expected (e.g., “oven”) or unexpected (e.g., “grill”) in relation to the inferred concept. Eye movements showed that readers detected a mismatch between the new unexpected information and their prior interpretation, confirming their ability to evaluate inferential information. Just below the narrative text, a critical sentence included a target word that was either congruent (e.g., “roasted”) or incongruent (e.g., “barbecued”) with the expected but not the unexpected concept. Readers spent less time reading the congruent than the incongruent target word, reflecting the facilitation of prior information. In addition, when the unexpected (but not expected) concept had been presented, participants with lower verbal (but not visuospatial) working memory span exhibited longer reading times and made more regressions (from the critical sentence to previous information) on encountering congruent information, indicating difficulty in inhibiting their initial incorrect interpretation and revising their situation model

Where were the monsoon regions and arid zones in Asia prior to the Tibetan Plateau uplift?

The impact of the Tibetan Plateau uplift on the Asian monsoons and inland arid climates is an important but also controversial question in studies of paleoenvironmental change during the Cenozoic. In order to achieve a good understanding of the background for the formation of the Asian monsoons and arid environments, it is necessary to know the characteristics of the distribution of monsoon regions and arid zones in Asia before the plateau uplift. In this study, we discuss in detail the patterns of distribution of the Asian monsoon and arid regions before the plateau uplift on the basis of modeling results without topography from a global coupled atmosphere–ocean general circulation model, compare our results with previous simulation studies and available biogeological data, and review the uncertainties in the current knowledge. Based on what we know at the moment, tropical monsoon climates existed south of 20°N in South and Southeast Asia before the plateau uplift, while the East Asian monsoon was entirely absent in the extratropics. These tropical monsoons mainly resulted from the seasonal shifts of the Inter-Tropical Convergence Zone. There may have been a quasi-monsoon region in central-southern Siberia. Most of the arid regions in the Asian continent were limited to the latitudes of 20–40°N, corresponding to the range of the subtropical high pressure year-around. In the meantime, the present-day arid regions located in the relatively high latitudes in Central Asia were most likely absent before the plateau uplift. The main results from the above modeling analyses are qualitatively consistent with the available biogeological data. These results highlight the importance of the uplift of the Tibetan Plateau in the Cenozoic evolution of the Asian climate pattern of dry–wet conditions. Future studies should be focused on effects of the changes in land–sea distribution and atmospheric CO2 concentrations before and after the plateau uplift, and also on cross-comparisons between numerical simulations and geological evidence, so that a comprehensive understanding of the evolution of the Cenozoic paleoenvironments in Asia can be achieved.

Software maintenance project delays prediction using Bayesian Networks

Managing software maintenance is rarely a precise task due to uncertainties concerned with resources and services descriptions. Even when a well-established maintenance process is followed, the risk of delaying tasks remains if the new services are not precisely described or when resources change during process execution. Also, the delay of a task at an early process stage may represent a different delay at the end of the process, depending on complexity or services reliability requirements. This paper presents a knowledge-based representation (Bayesian Networks) for maintenance project delays based on specialists experience and a corresponding tool to help in managing software maintenance projects. (c) 2006 Elsevier Ltd. All rights reserved.

GRASSIUS: A Platform for Comparative Regulatory Genomics across the Grasses

Transcription factors (TFs) are major players in gene regulatory networks and interactions between TFs and their target genes furnish spatiotemporal patterns of gene expression. Establishing the architecture of regulatory networks requires gathering information on TFs, their targets in the genome, and the corresponding binding sites. We have developed GRASSIUS (Grass Regulatory Information Services) as a knowledge-based Web resource that integrates information on TFs and gene promoters across the grasses. In its initial implementation, GRASSIUS consists of two separate, yet linked, databases. GrassTFDB holds information on TFs from maize (Zea mays), sorghum (Sorghum bicolor), sugarcane (Saccharum spp.), and rice (Oryza sativa). TFs are classified into families and phylogenetic relationships begin to uncover orthologous relationships among the participating species. This database also provides a centralized clearinghouse for TF synonyms in the grasses. GrassTFDB is linked to the grass TFome collection, which provides clones in recombination-based vectors corresponding to full-length open reading frames for a growing number of grass TFs. GrassPROMDB contains promoter and cis-regulatory element information for those grass species and genes for which enough data are available. The integration of GrassTFDB and GrassPROMDB will be accomplished through GrassRegNet as a first step in representing the architecture of grass regulatory networks. GRASSIUS can be accessed from www.grassius.org.

ANALYSIS & STUDY OF AI TECHNIQUES FORAUTOMATIC CONDITION MONITORING OFRAILWAY TRACK INFRASTRUCTURE : Artificial Intelligence Techniques

Since the last decade the problem of surface inspection has been receiving great attention from the scientific community, the quality control and the maintenance of products are key points in several industrial applications.The railway associations spent much money to check the railway infrastructure. The railway infrastructure is a particular field in which the periodical surface inspection can help the operator to prevent critical situations. The maintenance and monitoring of this infrastructure is an important aspect for railway association.That is why the surface inspection of railway also makes importance to the railroad authority to investigate track components, identify problems and finding out the way that how to solve these problems. In railway industry, usually the problems find in railway sleepers, overhead, fastener, rail head, switching and crossing and in ballast section as well. In this thesis work, I have reviewed some research papers based on AI techniques together with NDT techniques which are able to collect data from the test object without making any damage. The research works which I have reviewed and demonstrated that by adopting the AI based system, it is almost possible to solve all the problems and this system is very much reliable and efficient for diagnose problems of this transportation domain. I have reviewed solutions provided by different companies based on AI techniques, their products and reviewed some white papers provided by some of those companies. AI based techniques likemachine vision, stereo vision, laser based techniques and neural network are used in most cases to solve the problems which are performed by the railway engineers.The problems in railway handled by the AI based techniques performed by NDT approach which is a very broad, interdisciplinary field that plays a critical role in assuring that structural components and systems perform their function in a reliable and cost effective fashion. The NDT approach ensures the uniformity, quality and serviceability of materials without causing any damage of that materials is being tested. This testing methods use some way to test product like, Visual and Optical testing, Radiography, Magnetic particle testing, Ultrasonic testing, Penetrate testing, electro mechanic testing and acoustic emission testing etc. The inspection procedure has done periodically because of better maintenance. This inspection procedure done by the railway engineers manually with the aid of AI based techniques.The main idea of thesis work is to demonstrate how the problems can be reduced of thistransportation area based on the works done by different researchers and companies. And I have also provided some ideas and comments according to those works and trying to provide some proposal to use better inspection method where it is needed.The scope of this thesis work is automatic interpretation of data from NDT, with the goal of detecting flaws accurately and efficiently. AI techniques such as neural networks, machine vision, knowledge-based systems and fuzzy logic were applied to a wide spectrum of problems in this area. Another scope is to provide an insight into possible research methods concerning railway sleeper, fastener, ballast and overhead inspection by automatic interpretation of data.In this thesis work, I have discussed about problems which are arise in railway sleepers,fastener, and overhead and ballasted track. For this reason I have reviewed some research papers related with these areas and demonstrated how their systems works and the results of those systems. After all the demonstrations were taking place of the advantages of using AI techniques in contrast with those manual systems exist previously.This work aims to summarize the findings of a large number of research papers deploying artificial intelligence (AI) techniques for the automatic interpretation of data from nondestructive testing (NDT). Problems in rail transport domain are mainly discussed in this work. The overall work of this paper goes to the inspection of railway sleepers, fastener, ballast and overhead.

Akademisk kvalitet, vad är det? : Om utarmningen av den akademiska autonomin

What is academic quality? On the decline of academic autonomy In light of the transformations that universities currently undergo, with Bologna as a keyword, the following questions are put: What ideals lie behind the assessment of academic “excellence” and “quality”? What agents have the ability to define what is good science and education today? These questions are approached through Pierre Bourdieus concept of field. Looking at the development the last decade, traditional academic values, such as the ideal of universal knowledge as (personal and collective) enrichment and the intellectual independence “of all political authority and economic power”, as stated in the Magna Charta Universitatum, seem to have emerged into the shadow of employability, knowledge control, competitiveness, and economic benefit. In connection with the formation of concepts such as “the knowledge society” and “knowledge based economies” the university has received a somewhat different and more central role in society. The university has come to take the role more of a knowledge producing enterprise clearly directed towards the surrounding society. There are higher demands on academic knowledge to contribute to economic, regional or national development and competitiveness. When the university is regarded as a knowledge company whose task is to accoun tfor the requests of the students, the labour market, and the business world it undertakes to follow trends and short term social phases rather than to critically examine them, which has been a traditional task for the university. If the academic work is guided by the market economical principle, that the client requests decide what quality is, instead of the experts on the academic field themselves (i.e. the scientists,) it is obviously not scientific ideals that constitute the criteria for what is good science and education.

Narration in Swedish pre- and primary school : a recourse for language development and multilingualism

Increased immigration in Europe and worldwide has led to more pre- and primary school students being educated through the medium of a second language, and there is considerable research, much of it coming from Australia, to suggest that in order to cope with this situation, children will need to begin to acquire, from their earliest years in pre-school, a variety of knowledge-based language skills that will be sufficient to carry them through the subject-based education they will encounter in their subsequent schooling. This is particularly important for L2-students who are less likely to meet academic language outside the school. In this paper, based on transcripts of oral interactions in the classroom, it is argued that conversational and story-telling skills, oral and written, provide a rich environment for the development of academic school language, while at the same time promoting and making good use of the cultural diversity that is increasingly a feature of pre-primary and primary classrooms.

När det inte blir som man har tänkt sig : - En fallstudie av undervisningssituationer med elever med behov av särskilt stöd

Fallstudien beskriver och diskuterar några lektioner med elever som har specifika inlärnings-svårigheter, utifrån skolverkets Allmänna råd, och belyser vilka pedagogiskt svårhanterliga problem och dilemman som kan uppstå när det inte blir som läraren har planerat. Teorin om den proximala utvecklingszonen åskådliggörs. Aktivitetens betydelse för inlärning belyses. Komplexiteten kring lärarskap och ledarskap illustreras. Skolverkets teori om kunskap genom progression, enligt givna årskurser med givet innehåll, stämmer inte alltid med erfarenheterna hos några av verklighetens elever. Samspelet mellan lärare och elever belyses i studien. Be-skrivningar av utvecklingsrelaterade funktionsnedsättningar och psykiskt sårbara barn visar ytterligare hur elevers individuella förutsättningar kan ge konsekvenser för inlärning.

Granularity and disaggregation in compositional modelling with applications to ecological systems

In the past decade, compositional modelling (CM) has established itself as the predominant knowledge-based approach to construct mathematical (simulation) models automatically. Although it is mainly applied to physical systems, there is a growing interest in applying CM to other domains, such as ecological and socio-economic systems. Inspired by this observation, this paper presents a method for extending the conventional CM techniques to suit systems that are fundamentally presented by interacting populations of individuals instead of physical components or processes. The work supports building model repositories for such systems, especially in addressing the most critical outstanding issues of granularity and disaggregation in ecological systems modelling.