Biologically active Phytophthora mating hormone prepared by catalytic asymmetric total synthesis

A Phytophthora mating hormone with an array of 1,5-stereogenic centers has been synthesized by using our recently developed methodology of catalytic enantioselective conjugate addition of Grignard reagents. We applied this methodology in a diastereo- and enantioselective iterative route and obtained two of the 16 possible stereoisomers of Phytophthora hormone α1. These synthetic stereoisomers induced the formation of sexual spores (oospores) in A2 mating type strains of three heterothallic Phytophthora species, P. infestans, P. capsici, and P. nicotianae but not in A1 mating type strains. The response was concentration-dependent, and the oospores were viable. These results demonstrate that the biological activity of the synthetic hormone resembles that of the natural hormone α1. Mating hormones are essential components in the sexual life cycle of a variety of organisms. For plant pathogens like Phytophthora, sexual reproduction is important as a source of genetic variation. Moreover, the thick-walled oospores are the most durable propagules that can survive harsh environmental conditions. Sexual reproduction can thus greatly affect disease epidemics. The availability of synthetic compounds mimicking the activity of Phytophthora mating hormone will be instrumental for further unravelling sexual reproduction in this important group of plant pathogens.

Projected Destination Images on African Websites: Upgrading Branding Opportunities in the Global Tourism Value Chain

This paper explores whether websites that offer a global audience virtual access to watering holes in game parks afford African nations opportunities to diminish their international isolation as tourism destinations. The present analysis examines a sample of almost 450 tourism websites representing Rwanda, Uganda and Mozambique. Two aspects are studied in particular: the websites’ technical and social infrastructures, including website ownership and networks, and website content, i.e. the projected destination image and opportunities to bridge the main supplier-consumer gaps in the global tourism value chain. The findings indicate that there is substantial foreign involvement in Africa’s online tourism infrastructure; furthermore, that the current projected images tend to reproduce foreign stereotypes. It concludes that the potential for upgrading branding capabilities could be sourced in indigenous African cultural attributes, both high and low culture, and in contexts of the past and the contemporary

A CRISP-DM-based Methodology for Assessing Agent-based Simulation Models using Process Mining

Agent-based simulation (ABS) models are potent tools for analyzing complex systems. However, understanding and validating ABS models can be a significant challenge. To address this challenge, cutting-edge data-driven techniques offer sophisticated capabilities for analyzing the outcomes of ABS models. One such technique is process mining, which encompasses a range of methods for discovering, monitoring, and enhancing processes by extracting knowledge from event logs. However, applying process mining to event logs derived from ABSs is not trivial, and deriving meaningful insights from the resulting process models adds an additional layer of complexity. Although process mining is invaluable in extracting insights from ABS models, there is a lack of comprehensive methodological guidance for its application in ABS evaluation in the research landscape. In this paper, we propose a methodology, based on the CRoss-Industry Standard Process for Data Mining (CRISP-DM) methodology, to assess ABS models using process mining techniques. We incorporate process mining techniques into the stages of the CRISP-DM methodology, facilitating the analysis of ABS model behaviors and their underlying processes. We demonstrate our methodology using an established agent-based model, Schelling model of segregation. Our results show that our proposed methodology can effectively assess ABS models through produced event logs, potentially paving the way for enhanced agent-based model validity and more insightful decision-making

A CRISP-DM-based methodology for assessing agent-based simulation models using process mining

Agent-based simulation (ABS) models are powerful tools for analyzing complex systems. However, understanding and validating ABS models can be challenging. Data-driven techniques, such as process mining, offer promising capabilities for addressing these challenges. Process mining enables the discovery, monitoring, and enhancement of processes by extracting insights from event logs. However, applying process mining to ABS-generated logs and interpreting the results is not trivial. Despite its potential, limited methodological guidance exists for using process mining in ABS evaluation. This paper proposes a methodology, grounded in the CRoss-Industry Standard Process for Data Mining (CRISP-DM), to assess ABS models via process mining. By integrating process mining techniques into the phases of CRISP-DM, we support the analysis of ABS behaviors and their underlying processes. We demonstrate our methodology using Schelling’s segregation model. Our results indicate that our proposed methodology effectively evaluates ABS models using event logs, enhancing model validity and supporting more informed decision-making.</p

A CRISP-DM-based Methodology for Assessing Agent-based Simulation Models using Process Mining

Agent-based simulation (ABS) models are potent tools for analyzing complex systems. However, understanding and validating ABS models can be a significant challenge. To address this challenge, cutting-edge data-driven techniques offer sophisticated capabilities for analyzing the outcomes of ABS models. One such technique is process mining, which encompasses a range of methods for discovering, monitoring, and enhancing processes by extracting knowledge from event logs. However, applying process mining to event logs derived from ABSs is not trivial, and deriving meaningful insights from the resulting process models adds an additional layer of complexity. Although process mining is invaluable in extracting insights from ABS models, there is a lack of comprehensive methodological guidance for its application in ABS evaluation in the research landscape. In this paper, we propose a methodology, based on the CRoss-Industry Standard Process for Data Mining (CRISP-DM) methodology, to assess ABS models using process mining techniques. We incorporate process mining techniques into the stages of the CRISP-DM methodology, facilitating the analysis of ABS model behaviors and their underlying processes. We demonstrate our methodology using an established agent-based model, Schelling model of segregation. Our results show that our proposed methodology can effectively assess ABS models through produced event logs, potentially paving the way for enhanced agent-based model validity and more insightful decision-making

Virtual Tourism Destination Image: Glocal identities constructed, perceived and experienced

Het opdoemend netwerk van mondiale hubs en stromen van geld, media, technologie en migratie, hebben geleid tot een algemene bewustwording rond oplopende spanningen tussen mondiale en locale identiteiten en imago’s. Dubai, het onderzoeksdecor van dit proefschrift, is een goed voorbeeld. Met internet en mobiele technologie bestaat het creëren van bestemmingsimago’s niet langer uit een eenzijdig pushproces van massacommunicatie. Steeds belangrijker worden dynamische interactieve processen van reflecteren, selecteren, debatteren en ervaren. Dit proefschrift construeert daarom een dynamisch toeristisch bestemmingsimago-ontwikkelingsmodel waarbij de driehoeksverhouding tussen plaatsidentiteit, geprojecteerd imago en gepercipieerd imago leidt tot een spanningsveld, welke wordt kortgesloten tijdens de reisbeleving, wanneer host (aanbod) en gast (vraag) elkaar ontmoeten. Op dat moment kunnen drie kloven in het model een negatief effect hebben op de klanttevredenheid, hetgeen in dit proefschrift empirisch wordt onderzocht door het meten van geprojecteerd en gepercipieerd imago. Dit wordt bewerkstelligd door een innovatieve methodologie gebaseerd op geautomatiseerde inhoudsanalyse. Het geprojecteerd imago is vestgesteld door middel van inhoudsanalyse op 20 in Dubai gevestigde toeristische websites, terwijl gepercipieerd imago is gemeten door middel van inhoudsanalyse op 1.100 online reacties op een kwalitatief imago-onderzoek. De resultaten tonen aan dat men in Dubai de drie kloven dient te overbruggen, aangezien de snelle ontwikkeling van Dubai als een mondiale hub soms voorbij gaat aan de verankering in de sterke lokale identiteit en het gevestigd imago. Een theoretische oplossing voor het overbruggen van de kloven wordt besproken en conceptueel toegepast in het concluderend hoofdstuk. Het is gebaseerd op de literatuur rond stedelijke of regionale merkontwikkeling en staaft de algemene bruikbaarheid van het model en de onderzoeksmethodologie zoals die in dit proefschrift ontwikkeld werden.Robert Govers, who was born on May 16, 1968 in The Hague, The Netherlands, is currently serving as research coordinator at the Flemish Center for Tourism Policy Studies of the University of Leuven, Belgium. Prior to this he worked in Dubai as a senior lecturer in tourism and marketing for four years, including two years at the Emirates Academy of Hospitality Management. Robert graduated with a Master’ s degree in Marketing from the Rotterdam School of Management, but also holds a Bachelor’ s degree in Information Management. Robert started his teaching career as a visiting lecturer at the Witwatersrand Technikon Johannesburg (RSA). After that he was a Research Associate for the Centre for Tourism Management at the Rotterdam School of Management. With Prof. dr. Frank M. Go, Robert is the author of Entrepreneurship in Tourism, a paperback published in Dutch. He also co-authored several journal articles and conference papers in the field of tourism, hospitality and quality management, e-commerce in tourism and tourism research and marketing. As a project manager, Robert has been involved in many consultancy projects for reputable organisations such as IATA, the European Commission, the Flemish Government and various Dutch ministries and tourism promotion boards.The emerging network of global hubs and flows of finance, media, technology and migration has raised awareness regarding the tensions between global and local identities and images. Dubai, as the central research background for this dissertation, is a good case in point. With internet and mobile technology, creating destination image is no longer a one-way ‘push’ process of mass communication, but rather a dynamic one of selecting, reflecting, sharing, and experiencing. This dissertation therefore constructs a dynamic tourism destination image formation model, which identifies a triadic tension between place identity, its projection and the perceived image. This tension is short circuited during the travel experience, when host (supply) meets guest (demand). At this instance, three potential gaps could negatively affect the level of satisfaction experienced in the host – guest encounter. The empirical research focuses on measuring projected and perceived images in order to test the way in which the gaps can be assessed. This is accomplished through an innovative methodology based on computerised content analysis. The projected image is measured through a content analysis of 20 Dubai based websites while the perceived images are gauged by content analysing 1.100 online responses to a qualitative image survey. The results indicate that for Dubai, the three gaps need bridging as there is a clear tension between its rapid development as a global hub and its strong local identity and image. A theoretical solution for bridging the gaps is discussed and conceptually applied in the concluding chapter. It is based on the destination branding literature and establishes the general usefulness of the model and its research methodology

Genome sequence of the necrotrophic plant pathogen Pythium ultimum reveals original pathogenicity mechanisms and effector repertoire

Background: Pythium ultimum (P. ultimum) is a ubiquitous oomycete plant pathogen responsible for a variety of diseases on a broad range of crop and ornamental species. Results: The P. ultimum genome (42.8 Mb) encodes 15,290 genes and has extensive sequence similarity and synteny with related Phytophthora species, including the potato blight pathogen Phytophthora infestans. Whole transcriptome sequencing revealed expression of 86% of genes, with detectable differential expression of suites of genes under abiotic stress and in the presence of a host. The predicted proteome includes a large repertoire of proteins involved in plant pathogen interactions although surprisingly, the P. ultimum genome does not encode any classical RXLR effectors and relatively few Crinkler genes in comparison to related phytopathogenic oomycetes. A lower number of enzymes involved in carbohydrate metabolism were present compared to Phytophthora species, with the notable absence of cutinases, suggesting a significant difference in virulence mechanisms between P. ultimum and more host specific oomycete species. Although we observed a high degree of orthology with Phytophthora genomes, there were novel features of the P. ultimum proteome including an expansion of genes involved in proteolysis and genes unique to Pythium. We identified a small gene family of cadherins, proteins involved in cell adhesion, the first report in a genome outside the metazoans. Conclusions: Access to the P. ultimum genome has revealed not only core pathogenic mechanisms within the oomycetes but also lineage specific genes associated with the alternative virulence and lifestyles found within the pythiaceous lineages compared to the Peronosporaceae