22 research outputs found

    Computer Aided Verification

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    This open access two-volume set LNCS 13371 and 13372 constitutes the refereed proceedings of the 34rd International Conference on Computer Aided Verification, CAV 2022, which was held in Haifa, Israel, in August 2022. The 40 full papers presented together with 9 tool papers and 2 case studies were carefully reviewed and selected from 209 submissions. The papers were organized in the following topical sections: Part I: Invited papers; formal methods for probabilistic programs; formal methods for neural networks; software Verification and model checking; hyperproperties and security; formal methods for hardware, cyber-physical, and hybrid systems. Part II: Probabilistic techniques; automata and logic; deductive verification and decision procedures; machine learning; synthesis and concurrency. This is an open access book

    Software Engineering 2021 : Fachtagung vom 22.-26. Februar 2021 Braunschweig/virtuell

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    Guidelines for the use of flow cytometry and cell sorting in immunological studies (second edition)

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    These guidelines are a consensus work of a considerable number of members of the immunology and flow cytometry community. They provide the theory and key practical aspects of flow cytometry enabling immunologists to avoid the common errors that often undermine immunological data. Notably, there are comprehensive sections of all major immune cell types with helpful Tables detailing phenotypes in murine and human cells. The latest flow cytometry techniques and applications are also described, featuring examples of the data that can be generated and, importantly, how the data can be analysed. Furthermore, there are sections detailing tips, tricks and pitfalls to avoid, all written and peer-reviewed by leading experts in the field, making this an essential research companion

    An adaptive model for digital game based learning

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    Digital Game-based Learning (DGBL) has the potential to be a more effective means of instruction than traditional methods. However meta-analyses of studies on the effectiveness of DGBL have yielded mixed results. One of the challenges faced in the design and development of effective and motivating DGBL is the integration of learning and gameplay. A game that is effective at learning transfer, yet is no fun to play, is not going to engage learners for very long. This served as the motivation to devise a systematic approach to the design, development and evaluation of effective and engaging DGBL. A comprehensive literature review examined: how games can be made engaging and how the mechanics of learning can be mapped to the mechanics of gameplay; how learning can be designed to be universal to all; how learning analytics can empower learners and educators; and how an agile approach to the development of instructional materials leads to continuous improvement. These and other considerations led to the development of the Adaptive Model for Digital Game Based Learning (AMDGBL). To test how successful the model would be in developing effective, motivating and universal DGBL, a Virtual Reality (VR) game that teaches graph theory was designed, built and evaluated using the AMDGBL. An accompanying platform featuring an Application Programming Interface (API) for storing learner interaction data and a web-based learning analytics dashboard (LAD) were developed. A mixed methods approach was taken for a study of learners (N=20) who playtested the game and viewed visualizations in the dashboard. Observational and think aloud notes were recorded as they played and gameplay data was stored via the API. The participants also filled out a questionnaire. The notes taken were thematically analysed, and the gameplay data and questionnaire responses were statistically analysed. Triangulation of data improved confidence in findings and yielded new insights. The learner study became a case study for a second, qualitative study of DGBL practitioners (N=12). The VR game was demonstrated and a series of visualizations presented to the participants. They then completed a questionnaire featuring open questions about: the need for the model; the benefits of VR; and the embedding of learning analytics, universal design for learning, iteration with formative evaluation, and triangulation at the heart of the model. The responses were thematically analysed. The results of both studies supported the following assertions: that the AMDGBL would allow for iterative improvement of a DGBL prototype; that employing the AMDGBL would lead to an effective DGBL solution; that the inclusion of UDL would lead to a more universally-designed game; that the LAD would help learners with executive functions; and that VR would foster learner autonomy

    Design and Implementation of a Scalable Crowdsensing Platform for Geospatial Data

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    In the recent years smart devices and small low-powered sensors are becoming ubiquitous and nowadays everything is connected altogether, which is a promising foundation for crowdsensing of data related to various environmental and societal phenomena. Very often, such data is especially meaningful when related to time and location, which is possible by already equipped GPS capabilities of modern smart devices. However, in order to gain knowledge from high-volume crowd-sensed data, it has to be collected and stored in a central platform, where it can be processed and transformed for various use cases. Conventional approaches built around classical relational databases and monolithic backends, that load and process the geospatial data on a per-request basis are not suitable for supporting the data requests of a large crowd willing to visualize phenomena. The possibly millions of data points introduce challenges for calculation, data-transfer and visualization on smartphones with limited graphics performance. We have created an architectural design, which combines a cloud-native approach with Big Data concepts used in the Internet of Things. The architectural design can be used as a generic foundation to implement a scalable backend for a platform, that covers aspects important for crowdsensing, such as social- and incentive features, as well as a sophisticated stream processing concept to calculate incoming measurement data and store pre-aggregated results. The calculation is based on a global grid system to index geospatial data for efficient aggregation and building a hierarchical geospatial relationship of averaged values, that can be directly used to rapidly and efficiently provide data on requests for visualization. We introduce the Noisemap project as an exemplary use case of such a platform and elaborate on certain requirements and challenges also related to frontend implementations. The goal of the project is to collect crowd-sensed noise measurements via smartphones and provide users information and a visualization of noise levels in their environment, which requires storing and processing in a central platform. A prototypic implementation for the measurement context of the Noisemap project is showing that the architectural design is indeed feasible to realize

    Study of earth observation business models by means of the Business Model Canvas methodology

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    This project tries to study and compare two big players in the Earth Observation market to identify their main peculiarities that make them succeed in the market.Idenfity two big players in Earth Observation marketStudy in detail each case study and see how they operate applying the business model CANVAS Identify the case study peculiarities that make them succeed in the market Propose the successful factors that should be taken into account in this market according the case studie

    Epidemiological, Radiological and Genetic Aspects of Endocrine Bone Diseases

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    Epidemiological, Radiological and Genetic Aspects of Endocrine Bone Diseases

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    Stability of protein-based drugs: Herceptin a case study

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    There is a lack of stability data for in-use parenteral drugs. Manufacturers state a shelf-life of 24 hours for infusions based on microbiological contamination. The lack of data is of particular significance with protein-based drugs where action is determined by their complex structure. A range of techniques are required to assess stability, including biological assessment to support other data. There has been an increase in published data but often the few studies that address in-use stability are incomplete as they do not employ biological assessment to assess potency. Trastuzumab is an antibody-based drug used to treat cancers where the Epidermal Growth Factor Receptor 2 (HER2) is over expressed or over abundant on the cell surface. Trastuzumab infusions have been assigned by the manufacturer to be stable for 24 hours at temperatures not exceeding 30 oC. If stability is shown beyond this point it would enable extended storage and administration. To this end, methods were selected and developed with biological assessment central to the approach to assess clinically relevant infusion concentrations (0.5 mg/mL and 6.0 mg/mL) and a sub-clinical infusion concentration (0.1 mg/mL). This may enhance instability and provide opportunity to study degradation. A Cell Counting Kit CCK8 (Sigma Aldrich) was ultimately adopted as a basis for a colorimetric assay to assess cell viability. Attenuated Total Reflectance Infra-Red Spectroscopy and Size Exclusion Chromatography methods were developed to evaluate secondary structure and aggregation respectively. These methods were applied to a shelf-life study (43 days) as a collaboration with Quality Control North West (NHS) and Clatterbridge Centre for Oncology NHS Foundation Trust, Clatterbridge Hospital. There was no evidence of degradation and no loss efficacy for clinically relevant infusions (0.5 mg/mL and 6.0 mg/mL) over 43 days, whilst the sub-clinical infusions (0.1 mg/mL) developed particles after 7 days of storage between 2 oC and 8 oC. Furthermore, evidence of stability at day 119 gave increased confidence for the data from earlier time points. This work assisted in the shelf-life being recommended to be extended to 28 days for Trastuzumab stored in polyolefin IV bags at concentrations between 0.5 mg/mL and 6.0 mg/mL with 0.9% saline between 2 oC and 8 oC. However, infusions with concentrations below 0.5 mg/mL were not recommended for storage
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