17 research outputs found

    The Gonotrophic-Age Structure of a Population of the \u3ci\u3eSimulium Venustum\u3c/i\u3e Complex (Diptera: Simuliidae) in Algonquin Park, Ontario

    Get PDF
    Eight techniques for the determination of parity and gonotrophic age were assessed for the obligatorily anautogenous blackfly-species complex, Simulium venustum Say. All females could be age-graded by the presence or absence of dilatations on the ovarioles. However, multiple dilatations on a single ovariole were not found and the Polovodova method could not be used to determine the number of completed gonotrophic cycles. Most females could be age-graded by the appearance of the Malpighian tubules, which undergo morphological changes, probably as a result of a bloodmeal. In some cases, the size of the fat body, the presence of retained (relict), mature ova and the presence of meconium in the gut could be used as accessory age-grading criteria. Insemination status, the volume of the esophageal diverticulum, and the stage of development of the terminal ovarian follicles could not be used to age-grade females. The literature of age-grading in blackflies is reviewed, with special reference to the interpretability of the Polovodova method. Seasonal changes in the gonotrophic-age structure of a population of the S. venustum complex in Algonquin Park, ON, Canada, were examined over two years. The maximal proportion of parous females in the population was 75 and 62% in the two years, respectively. There was weak evidence that parous females were more likely to host seek in the morning and nulliparous females in the afternoon. Parity declined in mid-season, due to the recruitment of newly emerged adults to the population

    Best-Fit Action-Cost Domain Model Acquisition and its application to authorship in interactive narrative

    Get PDF
    Domain model acquisition is the problem of learning the structure of a state-transition system from some input data, typically example transition sequences. Recent work has shown that it is possible to learn action costs of PDDL models, given the overall costs of individual plans. In this work we have explored the extension of these ideas to narrative planning where cost can represent a variety of features (e.g. tension or relationship strength) and where exact solutions don’t exist. Hence in this paper we generalise earlier results to show that when an exact solution does not exist, a best-fit costing can be generated. This approach is of particular interest in the context of plan-based narrative generation where the input cost functions are based on subjective input. In order to demonstrate the effectiveness of the approach, we have learnt models of narratives using subjective measures of narrative tension. These were obtained with narratives (presented as video in this case) that were encoded as action traces, and then scored for subjective narrative tension by viewers. This provided a collection of input plan traces for our domain model acquisition system to learn a best-fit model. Using this learnt model we demonstrate how it can be used to generate new narratives that fit different target levels of tension

    Framer: Planning Models from Natural Language Action Descriptions

    Get PDF
    In this paper, we describe an approach for learning planning domain models directly from natural language (NL) descriptions of activity sequences. The modelling problem has been identified as a bottleneck for the widespread exploitation of various technologies in Artificial Intelligence, including automated planners. There have been great advances in modelling assisting and model generation tools, including a wide range of domain model acquisition tools. However, for modelling tools, there is the underlying assumption that the user can formulate the problem using some formal language. And even in the case of the domain model acquisition tools, there is still a requirement to specify input plans in an easily machine readable format. Providing this type of input is impractical for many potential users. This motivates us to generate planning domain models directly from NL descriptions, as this would provide an important step in extending the widespread adoption of planning techniques. We start from NL descriptions of actions and use NL analysis to construct structured representations, from which we construct formal representations of the action sequences. The generated action sequences provide the necessary structured input for inducing a PDDL domain, using domain model acquisition technology. In order to capture a concise planning model, we use an estimate of functional similarity, so sentences that describe similar behaviours are represented by the same planning operator. We validate our approach with a user study, where participants are tasked with describing the activities occurring in several videos. Then our system is used to learn planning domain models using the participants' NL input. We demonstrate that our approach is effective at learning models on these tasks

    Plasmodium falciparum Merozoite Invasion Is Inhibited by Antibodies that Target the PfRh2a and b Binding Domains

    Get PDF
    Plasmodium falciparum, the causative agent of the most severe form of malaria in humans invades erythrocytes using multiple ligand-receptor interactions. The P. falciparum reticulocyte binding-like homologue proteins (PfRh or PfRBL) are important for entry of the invasive merozoite form of the parasite into red blood cells. We have analysed two members of this protein family, PfRh2a and PfRh2b, and show they undergo a complex series of proteolytic cleavage events before and during merozoite invasion. We show that PfRh2a undergoes a cleavage event in the transmembrane region during invasion consistent with activity of the membrane associated PfROM4 protease that would result in release of the ectodomain into the supernatant. We also show that PfRh2a and PfRh2b bind to red blood cells and have defined the erythrocyte-binding domain to a 15 kDa region at the N-terminus of each protein. Antibodies to this receptor-binding region block merozoite invasion demonstrating the important function of this domain. This region of PfRh2a and PfRh2b has potential in a combination vaccine with other erythrocyte binding ligands for induction of antibodies that would block a broad range of invasion pathways for P. falciparum into human erythrocytes

    An EGF-like Protein Forms a Complex with PfRh5 and Is Required for Invasion of Human Erythrocytes by Plasmodium falciparum

    Get PDF
    Invasion of erythrocytes by Plasmodium falciparum involves a complex cascade of protein-protein interactions between parasite ligands and host receptors. The reticulocyte binding-like homologue (PfRh) protein family is involved in binding to and initiating entry of the invasive merozoite into erythrocytes. An important member of this family is PfRh5. Using ion-exchange chromatography, immunoprecipitation and mass spectroscopy, we have identified a novel cysteine-rich protein we have called P. falciparum Rh5 interacting protein (PfRipr) (PFC1045c), which forms a complex with PfRh5 in merozoites. Mature PfRipr has a molecular weight of 123 kDa with 10 epidermal growth factor-like domains and 87 cysteine residues distributed along the protein. In mature schizont stages this protein is processed into two polypeptides that associate and form a complex with PfRh5. The PfRipr protein localises to the apical end of the merozoites in micronemes whilst PfRh5 is contained within rhoptries and both are released during invasion when they form a complex that is shed into the culture supernatant. Antibodies to PfRipr1 potently inhibit merozoite attachment and invasion into human red blood cells consistent with this complex playing an essential role in this process

    Narrative Planning Model Acquisition from Text Summaries and Descriptions

    No full text
    AI Planning has been shown to be a useful approach for the generation of narrative in interactive entertainment systems and games. However, the creation of the underlying narrative domain models is challenging: the well documented AI planning modelling bottleneck is further compounded by the need for authors, who tend to be non-technical, to create content. We seek to support authors in this task by allowing natural language (NL) plot synopses to be used as a starting point from which planning domain models can be automatically acquired. We present a solution which analyses input NL text summaries, and builds structured representations from which a pddl model is output (fully automated or author in-the-loop). We introduce a novel sieve-based approach to pronoun resolution that demonstrates consistently high performance across domains. In the paper we focus on authoring of narrative planning models for use in interactive entertainment systems and games. We show that our approach exhibits comprehensive detection of both actions and objects in the system-extracted domain models, in combination with significant improvement in the accuracy of pronoun resolution due to the use of contextual object information. Our results and an expert user assessment show that our approach enables a reduction in authoring effort required to generate baseline narrative domain models from which variants can be built

    A Competency-Based Model for Developing Human Resource Professionals

    No full text
    This article describes a framework for the design and implementation o
    corecore