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The innate immune system is emerging as an important mediator of host response to tumor initiation, growth, and metastases. Several chemical carcinogenesis models in mice have implicated an important role for natural killer (NK) cells, γδ+ T cells, and a specialized CD1d-restricted population of T cells bearing NK cell receptors, called NKT cells1,2. The incidence of both methylcholanthrene (MCA)-induced fibrosarcoma and dimethylbenzanthracene (DMBA) and phorbol ester (TPA)-induced skin carcinomas is higher in mice lacking these vital innate immune cells. Furthermore, in allo-bone marrow transplantation (BMT), HLA class I disparities that induce NK cell alloreactions and GVHD also mediate strong graft-versus-leukemia (GVL) effects, producing higher engraftment rates and protecting patients from GVHD3,4. In murine MHC-mismatched transplant models with no donor T cell reactivity against the recipient, the pretransplant infusion of donor-vs.-recipient alloreactive NK cells obviated the need for high-intensity conditioning and conditioned the recipients to BMT without GVHD3,4. Several other studies also strongly support a key role for innate cells and mechanisms in controlling tumor initiation and growth5-8. [ABSTRACT FROM AUTHOR]

This work describes the evaluation of a wearable plastic optical fiber (POF) sensor for monitoring seated spinal posture, and the development of a workstation interface for the posture monitoring system. A garment-integrated POF sensor was developed and tested on nine healthy subjects. Data from the wearable sensor were compared to data taken simultaneously from a marker-based motion capture system. Peak analysis of the resulting data show a mean value error of 0.64 degrees and a mean time error of 0.53 seconds. These results show that the wearable sensor approximates the accuracy of expert visual analysis, and provides enough accuracy of measurement to reliably monitor seated spinal posture. The initial development of the system hardware and software inte rface are also described. [ABSTRACT FROM AUTHOR]

Cancer immunosurveillance has been debated for well over a century, but more recent experimental data over the past 15 years has clearly been supportive for an important role for cytokines and other effector molecules in host resistance to transformation (1,2). Importantly, this molecular biology era has brought with it the discovery of new hormones (cytokines such as IL-2 and interferons [IFNs]) and messengers (chemokines) that activate and direct leukocytes in a coordinated fashion. Clinical application quickly followed (3) and immune cell/cytokine immunotherapies now herald the promise of new forms of cancer therapy. Cytokines have pivotal effects on the carcinogenic process. On the one hand they can be involved in the activation of immune effector mechanisms that limit the growth of the tumor, but on the other they may contribute to inflammation, transformation, tumor growth, invasion, and metastasis (as discussed in earlier chapters). Cytokines are produced by host stromal and immune cells, in response to molecules secreted by the tumor cells or as part of inflammation that frequently accompanies tumor growth. Tumor cells also produce cytokines in the same environment. How a local cytokine network operates in tumors is determined by the array of cytokines and receptors expressed and their relative concentrations. The net cytokine environment likely varies at various stages of tumor development. [ABSTRACT FROM AUTHOR]

The Direct Anonymous Attestation (DAA) scheme provides a means for remotely authenticating a trusted platform whilst preserving the user's privacy. The protocol has been adopted by the Trusted Computing Group (TCG) in the latest version of its Trusted Platform Module (TPM) specification. In this paper we show DAA places an unnecessarily large burden on the TPM host. We demonstrate how corrupt administrators can exploit this weakness to violate privacy. The paper provides a fix for the vulnerability. Further privacy issues concerning linkability are identified and a framework for their resolution is developed. In addition an optimisation to reduce the number of messages exchanged is proposed. [ABSTRACT FROM AUTHOR]

The social Web emphasises the increased role of millions of users in the creation of a new type of online content, often expressed in the form of opinions or judgements. This has led to some novel approaches to information access that take advantage of user opinions and activities as a way to guide users as they browse or search for information. We describe a social search technique that harnesses the experiences of a network of searchers to generate result recommendations that can complement the search results that are returned by some standard Web search engine. [ABSTRACT FROM AUTHOR]

When we search for information we are usually either trying to recover something that we have found in the past or trying to discover some new information. In this paper we will evaluate how the collaborative Web search technique, which personalizes search results for communities of like-minded users, can help in recovery-and discovery-type search tasks in a corporate search scenario. [ABSTRACT FROM AUTHOR]

The canonical transient receptor potential (TRPC) cation channels are mammalian homologs of the photoreceptor channel TRP in Drosophila melanogaster. All seven TRPCs (TRPC1 through TRPC7) can be activated through Gq/11 receptors or receptor tyrosine kinase (RTK) by mechanisms downstream of phospholipase C. The last decade saw a rapidly growing interest in understanding the role of TRPC channels in calcium entry pathways as well as in understanding the signal(s) responsible for TRPC activation. TRPC channels have been proposed to be activated by a variety of signals including store depletion, membrane lipids, and vesicular insertion into the plasma membrane. Here we discuss recent developments in the mode of activation as well as the pharmacological and electrophysiological properties of this important and ubiquitous family of cation channels. [ABSTRACT FROM AUTHOR]

Collaborative Web search is a form of meta-search that manipulates the results of underlying Web search engines in response to the learned preferences of a given community of users. Results that have previously been selected in response to similar queries by community members are promoted in the returned results. However, promotion is limited to these previously-selected results and in this paper we describe and evaluate how relevant results without a selection history can also be promoted by exploiting snippet-text and title similarities. [ABSTRACT FROM AUTHOR]

While most innovations commonly enter the marketplace with little notice or fanfare, this cannot be said for products of agricultural biotechnology. The commercialization of innovative new transgenic crops and the resulting food products have resulted in some products entering the market that are not desired by some consumers. It is argued that these new products are creating a new class of socioeconomic liabilities in the marketplace. We examine three strategies for managing these liabilities: scientific, regulatory, and market strategies. [ABSTRACT FROM AUTHOR]

Statistical language models can learn relationships between topics discussed in a document collection and persons, organizations and places mentioned in each document. We present a novel combination of statistical topic models and named-entity recognizers to jointly analyze entities mentioned (persons, organizations and places) and topics discussed in a collection of 330,000 New York Times news articles. We demonstrate an analytic framework which automatically extracts from a large collection: topics; topic trends; and topics that relate entities. [ABSTRACT FROM AUTHOR]

During the past two decades, zebrafish (Danio rerio) have become established as a prolific model for biological research (for review, see Udvadia and Linney, 2003). Zebrafish exhibit many features of an ideal model organism, including small size, rapid development, and high fecundity. Since zebrafish are vertebrates, there is a conservation of physiology with higher vertebrates, including humans. Juvenile zebrafish develop rapidly and oviparously, facilitating developmental studies without invasive procedures. Zebrafish are amenable to drug discovery, having similar responses to mammals in pharmacological tests using cardiovascular, anti-angiogenic and anti-cancer drugs (for review, see Langheinrich et al., 2002). To date, zebrafish have been used in genetic screens to identify genes involved in development and function of organs including the eye, brain, ear and heart (Haffter et al., 1996). More recently, transgenic technologies have been developed for zebrafish. In this review, we will describe how this transgenic technology can be applied to study retinal biology. [ABSTRACT FROM AUTHOR]

The PULSE project objectives are to generate and evaluate a web-based personalized educational intervention for the management of cardiovascular risk. We present a web-based adaptive hypermedia system to create and deliver the personalized education material to the patient. The adaptive personalization framework is based on a patient profile created by combining an electronic patient data capture template, the Systematic COronary Risk Evaluation (SCORE) algorithm, and a Stage of behaviour Change determination model. The interventions are designed to address both medical and psychosocial aspects of risk management and, as such, we combine staged lifestyle modification materials and non-staged messages based on Canadian clinical guidelines to motivate personal risk management. [ABSTRACT FROM AUTHOR]

In this paper we discuss ideas for adaptive support of cross-language text retrieval. In order to enable users to access multilingual information, different problems have to be solved: disambiguating and translating the query words, as well as categorizing and presenting the results appropriately. After giving a brief introduction to cross-language text retrieval, word sense disambiguation and document categorization, actual achievements of the research project are described and future work is discussed. We focus especially on the problem of browsing and navigation of the different word senses in a source and target languages. [ABSTRACT FROM AUTHOR]

This paper details the central ideas to date, from a PhD entitled ‘Player Profiling for Adaptive Artificial Intelligence in Computer and Video Games'. Computer and videogames differ from other web and productivity software in that games are much more highly interactive and immersive experiences. Whereas usability and user modelling for other software may be based on productivity alone, games require an additional factor that takes account of the quality of the user experience in playing a game. In order to describe that experience we describe a model of User, System and Experience (USE) in which the primary construct for evaluation of a player's experience will be the Experience Fluctuation Model (EFM), taken from Flow theory. We illustrate with a straightforward example how this system may be automated in real-time within a commercial game. [ABSTRACT FROM AUTHOR]

Effective navigation and information retrieval is difficult and time consuming due to the increasing size of hyperspace. The introduction of the semantic web allows us to enhance traditional search methods with semantic search capabilities that take advantage of machine readable semantic information ideally stored in an ontology. Nevertheless issues concerning the user-friendly construction of search queries and a simple yet effective presentation of search results must still be addressed. The proposed approach takes advantage of adaptive hypermedia in an enhanced faceted browser capable of dynamically adapting the set of available facets with additional support for data retrieval from an ontology and adaptive annotation of search results. [ABSTRACT FROM AUTHOR]

Adaptive Hypermedia Systems adjust the content to best suit users' personal characteristics, but rarely consider delivery performance. Performance issues are even more significant in distributed architectures such as that of an Open Corpus Adaptive Educational Hypermedia System (OAEHS). This paper introduces a Performance Oriented Adaptation Agent (POAA) that enhances OAEHS by taking into consideration not only user personal characteristics but also network delivery conditions in the content selection process. The usage of POAA is expected to bring significant delivery performance improvements in terms of learner satisfaction and learning outcome. [ABSTRACT FROM AUTHOR]

Interactive Digital TV (IDTV) opens new learning possibilities where new forms of education are needed. In this paper we explain a new conception of t-learning experiences where TV programs and learning contents are combined. In order for its creation to be possible we will use Adaptive Hypermedia techniques and Semantic Reasoning to design an Intelligent Tutoring System (ITS) whose tasks consist in selecting, combining and personalizing the contents to construct these learning experiences. [ABSTRACT FROM AUTHOR]

HCI in GIS is complicated by information overload and inappropriately designed user interfaces considering the task at hand. Implicit user profiling makes it possible to personalise both the data displayed by the GIS, and the interface used to display this data. The advance of mobile computing in recent years has put a great demand on mobile GIS to be made more efficient and user-friendly, as GIS are best experienced in the field. While operating in the field, it is quite conceivable that one's hands would be otherwise occupied, thus the advancement of a multimodal system is imperative for field operation. This doctoral consortium paper addresses the personalisation of the HCI with such a mobile GIS. [ABSTRACT FROM AUTHOR]

Personalised elearning is being heralded as one of the grand challenges of next generation learning systems, in particular, its ability to support greater effectiveness, efficiency and student empowerment. However, a key problem with such systems is their reliance on bespoke content developed for, and only used by, these systems. The challenge for adaptive systems in scalably supporting personalised elearning is its ability to source, harvest and deliver open corpus content to adaptive content services and personalised elearning systems. This paper examines the issues involved in implementing such an adaptive content service. The paper seeks to explore the accurate extraction of content requirements from the adaptive system, the sourcing and identification of suitable learning content, the harvesting and customisation of the content for delivery to adaptive elearning systems. [ABSTRACT FROM AUTHOR]

This research outline refers to the validation of interventional strategies to increase the learner's motivation and self-efficacy in an on-line learning environment. Previous work in this area is mainly based on Keller's ARCS model of instructional design and this study argues for an approach based on Bandura's Social Cognitive Theory - especially the aspects of self-efficacy and self-regulation. The research plan envisages two phases: The first phase will extract rules for interventional strategy selection from expert teachers. The second phase aims to validate these rules by providing to the learner the selected strategy and observing the resulting behavior. [ABSTRACT FROM AUTHOR]

Current adaptive systems acquire information about users mainly by simple tracking of resources, a user has requested and by asking users to supply the needed information. In this paper, we discuss user modeling based on observing a user's interaction with the system. We propose to collect usage data on the server side as well as on the client side. Collected data are then processed into knowledge about user's intentions and preferences. This processing relies on a set of heuristics, which help to interpret the usage patterns found in the collected data. [ABSTRACT FROM AUTHOR]

One of the challenges of adaptive hypermedia educational (AHE) systems is that of adapting the sequencing of learning units presented to the student. One approach is to model the set of possible sequencings with a graph, but the process of designing and maintaining the graph may be tedious and error-prone. This paper presents some ideas to overcome this, inpired by swarm intelligence techniques. Problems that may arise, as well as possible solutions, are presented. [ABSTRACT FROM AUTHOR]

The growth of available personalization services and the heterogeneity in content and representation of therein exploited User Models (UMs), raise a need for a mechanism allowing to aggregate partial UMs generated by other services. Such a mechanism will allow reuse of partial UMs in multiple personalization services that may need it. This paper discusses the details of a decentralized mediator for cross-domain and cross-technique translation and aggregation of partial UMs. The mediator facilitates enriching UMs managed by personalization services and improving the quality of the provided personalization. [ABSTRACT FROM AUTHOR]

This research outline refers to the assessment of motivation in online learning environments. It includes a presentation of previous approaches, most of them based on Keller's ARCS model, and argues for an approach based on Social Cognitive Learning Theory, in particular building on self-efficacy and self-regulation concepts. The research plan includes two steps: first, detect the learners in danger of dropping-out based on their interaction with the system; second, create a model of the learner's motivation (including self-efficacy, self-regulation, goal orientation, attribution and perceived task characteristics) upon which intervention can be done. [ABSTRACT FROM AUTHOR]

In this paper, we describe the design and development of personal information assistant (PIA), a system aiming to meet individual needs of the searchers. The system's goal is to provide more up-to-date and relevant information to users with respect to their needs and interests. The main component of the system is a profile learner for capturing temporal user needs, based on implicit feedback gathering techniques. It monitors the system usage, the documents viewed and other user actions in order to infer users' changing needs. [ABSTRACT FROM AUTHOR]

Currently, there is an increasing demand user-adaptive systems for various purposes in many different domains. The development of such systems requires computational efforts which is often challenging and off-putting. The main contribution of our work is the idea to go one step further from sharing user model data (interoperable user models) towards the exchange of user model reasoning strategies (interoperable user modeling). In this paper we discuss, exemplified in a concrete scenario, how Semantic Web techniques may be applied to the field of the Adaptive Systems in order to have a more effective and reliable user model interoperability, considering both the perspectives of User Modeling Servers and Web Servers. [ABSTRACT FROM AUTHOR]

This paper presents COLLECT-$\mathcal{UML}$, a constraint-based ITS that teaches object-oriented (OO) design using Unified Modeling Language (UML). We have developed a single-user version that supports students in learning UML class diagrams. The system was evaluated in a real classroom, and the results show that student performance increases significantly. We present our experiences in extending the system to provide support for collaboration and describe the architecture, interface and support for collaboration in the new, multi-user system. [ABSTRACT FROM AUTHOR]

We describe an intelligent interactive online tutor for computer languages. The tutor uses an ontology of programming language terms together with a language-specific ontology. These ontologies are embedded in web pages structured at different levels of student expertise to provide a web front end that can be re-assembled in many different ways to suit a particular student's attempt to compile a particular program. This dynamic reassembly copes well with the initial learning curve for a language as well as revision a few months later. We argue that such a dynamic solution is more appropriate in this case than user profiling as a student's capabilities are not the same for all parts of the language to be learnt or from one session to the next. Our system gives the student control over the learning process by the use of question answering techniques on the same ontology. Our system tracks what the user is doing in the programming exercises to understand what they are trying to write. Early trials with a real student audience have produced positive results and feedback for more research. [ABSTRACT FROM AUTHOR]

The use of Information and Communication Technologies (ICTs) is spreading inside the classrooms at all educational levels. As this integration has extended to young learners (3 to 5 years), the authorities have recommended their use so that children can acquire knowledge and dexterities they will use all their lives. Keeping in mind that it is at this age when very young learners acquire abilities and basic dexterities at their own pace, the more personalized the better. From all the premises above, we can claim that whereas other computer assisted language learning systems do not account for differences in children's cognitive development when designing computerized applications, the introduction of AHS (Adaptive Hypermedia Systems) is aimed at adapting and personalizing content to children's needs and abilities. [ABSTRACT FROM AUTHOR]

Adaptive hypermedia systems offer the functionality to personalize the information experience as per a user-model. In this paper we present a novel content adaptation approach that views information personalization as a constraint satisfaction problem. Information personalization is achieved by satisfying two constraints: (1) relevancy constraints to determine the relevance of a document to a user and (2) co-existence constraints to suggest complementing documents that either provide reinforcing viewpoints or contrasting viewpoints, as per the user's request. Our information personalization framework involves: (a) an automatic constraint acquisition method, based on association rule mining on a corpus of documents; and (b) a hybrid of constraint satisfaction and optimization methods to derive an optimal solution—i.e. personalized information. We apply this framework to filter news items using the Reuters-21578 dataset. [ABSTRACT FROM AUTHOR]

A common trend in modern applications is the move towards more mobile, adaptive, customisable software. The evolution of software from static, invariant tools for narrow portions of a task to adaptive, open interaction frameworks is embodied in the use of a variety of technologies for creating a reconfigurable application. Perhaps the two most important techniques are Adaptive architectures and Ubiquitious Computing. However, many techniques employed merging these two technologies to form the vision of a truly ubiquitous, adaptive environment have so far failed to take full account of the expressive quality of both context and adaptivity. This paper presents a new, semantic interopration-based approach to creating context-informed adaptive applications that make maximum use of the rich content that can be found in both technologies. [ABSTRACT FROM AUTHOR]

To our knowledge, every free-text Computer Assisted Assessment (CAA) system automatically scores the students and gives feedback to them according to their responses, but, none of them include yet personalization options. The free-text CAA system Atenea [1] had simple adaptation possibilities by keeping static student profiles [2]. In this paper, we present a new adaptive version called Willow. It is based on Atenea and adds the possibility of dynamically choosing the questions to be asked according to their difficulty level, the students' profile and previous answers. Both Atenea and Willow have been tested with 32 students that manifested their satisfaction after using them. The results stimulate us to continue exploiting the possibilities of incorporating dynamic adaptation to free-text CAA. [ABSTRACT FROM AUTHOR]

We built a Web-based adaptive recommendation system for students to select and suggest architectural cases when they analyze "Case Study" work within the architectural design studio course, which includes deep comparisons and analyses for meaningful architectural precedents. We applied hybrid recommendation mechanism, which is combining both content-based filtering and collaborative filtering in our suggested model. It not only retains the advantages of a content-based and collaborative filtering approach, but also improves the disadvantages found in both. We expect that the approach would be helpful for students to find relevant precedents more efficient and more precise with their preferences. [ABSTRACT FROM AUTHOR]

As there are a lot of approaches and projects within the area of adaptive e-learning, several theoretical models have been developed in the last 15 years. Against this background, the AdeLE team implemented a first prototype on basis of informal descriptions given by literature research as well as concrete circumstances of the research project. Nevertheless, a theoretical model fulfilling certain requirements for our approach is still missing. This paper points out possibilities and limitations of existing models in the scope of the AdeLE project. Further, the author's own attempt towards formalising adaptive behaviour in e-learning environments is denoted. [ABSTRACT FROM AUTHOR]

This paper describes one solution to the problem of how to collect, organize, and select Web learning resources into a coherent, focused organization for instruction to address learners' immediate and focused learning needs. By exploiting the semantic relationships that characterize learning resources and learner profile, the proposed semantic-based thematic approach supports both semantic querying and conceptual navigation of learning resources pertaining to specific topics. A system has been developed and deployed within an academic setting, enabling learners to organize, search, and share the learning resources in a flexible and personalized manner. [ABSTRACT FROM AUTHOR]

In order to support knowledge workers during their tasks of searching, locating and manipulating information, a system that provides information suitable for a particular user's needs, and that is also able to facilitate annotation, sharing and reuse information is essential. This paper presents Adaptable Personal Information Environment (a-PIE); a service-oriented framework using Open Hypermedia and Semantic Web technologies to provide an adaptable web-based system. a-PIE models the information structures (data and links) and context as Fundamental Open Hypermedia Model (FOHM) structures which are manipulated by using the Auld Linky contextual link service. a-PIE provides an information environment that enables users to search an information space based on ontologically defined domain concepts. The users can add and annotate interesting data or parts of information structures into their information space, leaving the original published data or information structures unchanged. a-PIE facilitates the shareability and reusability of knowledge according to users' requirements. [ABSTRACT FROM AUTHOR]

This paper proposes an approach to dynamically compose an adaptive curriculum for e-learning based on a topic-centered resource space. By exploiting the semantic relationships that characterize learning objects (LOs) and learner profile, the approach dynamically selects, sequences, and links learning resources into a coherent, individualized curriculum to address learners' focused learning needs. We developed an active learning system with semantic support for learners to access and navigate through learning resources in an efficient and personalized manner, while providing facilities for instructors to manipulate the structured learning resources via a convenient visual interface. [ABSTRACT FROM AUTHOR]

This paper presents and discusses an empirical study that has been conducted among different kinds of computer users. The aim of the empirical study was to find out how computer users react when they face situations which generate emotions while they interact with a computer. The study has focused on two modes of human-computer interaction namely input from the keyboard and the microphone. The results of the study have been analyzed in terms of characteristics of users that have taken part (age, educational level, computer knowledge, etc.). These results were used to create a user modeling component that monitors users silently and records their actions (in the two modes of interaction) which are then interpreted in terms of their feelings. This user modeling component can be incorporated in any application that provides adaptive interaction to users based on affect perception. [ABSTRACT FROM AUTHOR]