344 research outputs found
CommAID: Visual Analytics for Communication Analysis through Interactive Dynamics Modeling
Communication consists of both meta-information as well as content.
Currently, the automated analysis of such data often focuses either on the
network aspects via social network analysis or on the content, utilizing
methods from text-mining. However, the first category of approaches does not
leverage the rich content information, while the latter ignores the
conversation environment and the temporal evolution, as evident in the
meta-information. In contradiction to communication research, which stresses
the importance of a holistic approach, both aspects are rarely applied
simultaneously, and consequently, their combination has not yet received enough
attention in automated analysis systems. In this work, we aim to address this
challenge by discussing the difficulties and design decisions of such a path as
well as contribute CommAID, a blueprint for a holistic strategy to
communication analysis. It features an integrated visual analytics design to
analyze communication networks through dynamics modeling, semantic pattern
retrieval, and a user-adaptable and problem-specific machine learning-based
retrieval system. An interactive multi-level matrix-based visualization
facilitates a focused analysis of both network and content using inline visuals
supporting cross-checks and reducing context switches. We evaluate our approach
in both a case study and through formative evaluation with eight law
enforcement experts using a real-world communication corpus. Results show that
our solution surpasses existing techniques in terms of integration level and
applicability. With this contribution, we aim to pave the path for a more
holistic approach to communication analysis.Comment: 12 pages, 7 figures, Computer Graphics Forum 2021 (pre-peer reviewed
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Visual Analytics for Temporal Hypergraph Model Exploration
Many processes, from gene interaction in biology to computer networks to
social media, can be modeled more precisely as temporal hypergraphs than by
regular graphs. This is because hypergraphs generalize graphs by extending
edges to connect any number of vertices, allowing complex relationships to be
described more accurately and predict their behavior over time. However, the
interactive exploration and seamless refinement of such hypergraph-based
prediction models still pose a major challenge. We contribute Hyper-Matrix, a
novel visual analytics technique that addresses this challenge through a tight
coupling between machine-learning and interactive visualizations. In
particular, the technique incorporates a geometric deep learning model as a
blueprint for problem-specific models while integrating visualizations for
graph-based and category-based data with a novel combination of interactions
for an effective user-driven exploration of hypergraph models. To eliminate
demanding context switches and ensure scalability, our matrix-based
visualization provides drill-down capabilities across multiple levels of
semantic zoom, from an overview of model predictions down to the content. We
facilitate a focused analysis of relevant connections and groups based on
interactive user-steering for filtering and search tasks, a dynamically
modifiable partition hierarchy, various matrix reordering techniques, and
interactive model feedback. We evaluate our technique in a case study and
through formative evaluation with law enforcement experts using real-world
internet forum communication data. The results show that our approach surpasses
existing solutions in terms of scalability and applicability, enables the
incorporation of domain knowledge, and allows for fast search-space traversal.
With the technique, we pave the way for the visual analytics of temporal
hypergraphs in a wide variety of domains.Comment: 11 pages, 6 figures, IEEE VIS VAST 2020 - Proceedings of IEEE
Conference on Visual Analytics Science and Technology (VAST), 202
Communication Analysis through Visual Analytics: Current Practices, Challenges, and New Frontiers
The automated analysis of digital human communication data often focuses on
specific aspects such as content or network structure in isolation. This can
provide limited perspectives while making cross-methodological analyses,
occurring in domains like investigative journalism, difficult. Communication
research in psychology and the digital humanities instead stresses the
importance of a holistic approach to overcome these limiting factors. In this
work, we conduct an extensive survey on the properties of over forty
semi-automated communication analysis systems and investigate how they cover
concepts described in theoretical communication research. From these
investigations, we derive a design space and contribute a conceptual framework
based on communication research, technical considerations, and the surveyed
approaches. The framework describes the systems' properties, capabilities, and
composition through a wide range of criteria organized in the dimensions (1)
Data, (2) Processing and Models, (3) Visual Interface, and (4) Knowledge
Generation. These criteria enable a formalization of digital communication
analysis through visual analytics, which, we argue, is uniquely suited for this
task by tackling automation complexity while leveraging domain knowledge. With
our framework, we identify shortcomings and research challenges, such as group
communication dynamics, trust and privacy considerations, and holistic
approaches. Simultaneously, our framework supports the evaluation of systems
and promotes the mutual exchange between researchers through a structured
common language, laying the foundations for future research on communication
analysis.Comment: 11 pages, 2 tables, 1 figur
New acyl derivatives of 3-aminofurazanes and their antiplasmodial activities
An N-acylated furazan-3-amine of a Medicines for Malaria Venture (MMV) project has shown activity against different strains of Plasmodium falciparum. Seventeen new derivatives were prepared and tested in vitro for their activities against blood stages of two strains of Plasmodium falciparum. Several structure-activity relationships were revealed. The activity strongly depended on the nature of the acyl moiety. Only benzamides showed promising activity. The substitution pattern of their phenyl ring affected the activity and the cytotoxicity of compounds. In addition, physicochemical parameters were calculated (log P, log D, ligand efficiency) or determined experimentally (permeability) via a PAMPA. The N-(4-(3,4-diethoxyphenyl)-1,2,5-oxadiazol-3-yl)-3-(trifluoromethyl)benzamide possessed good physicochemical properties and showed high antiplasmodial activity against a chloroquine-sensitive strain (IC50(NF54) = 0.019 microM) and even higher antiplasmodial activity against a multiresistant strain (IC50(K1) = 0.007 microM). Compared to the MMV compound, the permeability and the activity against the multiresistant strain were improved
New derivatives of the multi-stage active Malaria Box compound MMV030666 and their antiplasmodial potencies
MMV's Malaria Box compound MMV030666 shows multi-stage activity against various strains of Plasmodium falciparum and lacks resistance development. To evaluate the importance of its diarylether partial structure, diarylthioethers and diphenylamines with varying substitution patterns were prepared. A number of evident structure-activity relationships were revealed. Physicochemical and pharmacokinetic parameters were determined experimentally (passive permeability) or calculated. Compared to the lead compound a diarylthioether was more active and less cytotoxic resulting in an excellent selectivity index of 850. In addition, pharmacokinetic and physicochemical parameters were improved
Synthesis and structure-activity relationships of new 2-phenoxybenzamides with antiplasmodial activity
The 2-phenoxybenzamide 1 from theMedicines for Malaria Venture Malaria Box Project has shown promising multi-stage activity against different strains of P. falciparum. It was successfully synthesized via a retrosynthetic approach. Subsequently, twenty-one new derivatives were prepared and tested for their in vitro activity against blood stages of the NF54 strain of P. falciparum. Several insights into structure-activity relationships were revealed. The antiplasmodial activity and cytotoxicity of compounds strongly depended on the substitution pattern of the anilino partial structure as well as on the size of substituents. The diaryl ether partial structure had further impacts on the activity. Additionally, several physicochemical and pharmacokinetic parameters were calculated (log P, log D7.4 and ligand efficiency) or determined experimentally (passive permeability and CYP3A4 inhibition). The tertbutyl- 4-{4-[2-(4-fluorophenoxy)-3-(trifluoromethyl)benzamido]phenyl}piperazine-1-carboxylate possesses high antiplasmodial activity against P. falciparum NF54 (PfNF54 IC50 = 0.2690 M) and very low cytotoxicity (L-6 cells IC50 = 124.0 M) resulting in an excellent selectivity index of 460. Compared to the lead structure 1 the antiplasmodial activity was improved as well as the physicochemical and some pharmacokinetic parameters
Grain-size dependent demagnetizing factors in permanent magnets
This is the final version of the article. Available from the American Institute of Physics via the DOI in this record.The coercive field of permanent magnets decreases with increasing grain size. The grain size dependence of coercivity is explained by a size dependent demagnetizing factor. In Dy free NdFeB magnets the size dependent demagnetizing factor ranges from 0.2 for a grain size of 55 nm to 1.22 for a grain size of 8300 nm. The comparison of experimental data with micromagnetic simulations suggests that the grain size dependence of the coercive field in hard magnets is due to the non-uniform magnetostatic field in polyhedral grains.This work is based on results obtained from the future pioneering program “Development of magnetic material technology for high-efficiency motors” commissioned by the New Energy and Industrial Technology Development Organization (NEDO). We acknowledge the financial support from the Austrian Science Fund (F4112-N13)
Gestaltung von Anpassungspfaden im Klimarisikomanagement. Leitfaden für Entscheidungsträgerinnen und Entscheidungsträger
Entscheidungen im lokalen Management von klimabedingten Risiken, wie z.B. im Hochwasserrisikomanagement, erfolgen regelmäßig sehr rasch nach einem Ereignis, u.a. auch aufgrund massiven Drucks der lokalen Bevölkerung. Dabei werden meist Maßnahmen umgesetzt, die allgemein bekannt sind und dem Stand der Technik entsprechen. Diese singulären und sich an der Vergangenheit orientierenden Entscheidungen führen aber dazu, dass sich das Schadenspotential in den Gemeinden und Regionen meist weiterentwickelt und den zukünftigen Herausforderungen im Risikomanagement aufgrund des Klimawandels nur unzureichend genügt. Deshalb ist es wichtig, aktuelle Pfadabhängigkeiten frühzeitig zu erkennen und eine Entkoppelung davon zu erzielen. Nur so kann ein antizipatives Klimarisikomanagement umgesetzt und verstetigt werden, welches auch über einzelne klimabedingte Risiken hinweg agiert.
Der Leitfaden „Gestaltung von Anpassungspfaden im Klimarisikomanagement“ dient als mögliche Erweiterung des „Vorsorgechecks Naturgefahren im Klimawandel“, welcher den Status Quo aller in einer Gemeinde möglichen Naturgefahren abhandelt. Dieser Leitfaden richtet sich somit vorrangig an jene österreichischen Gemeinden, die entweder bereits einen solchen „Naturgefahrencheck“ absolviert haben oder dies in Zukunft noch vorhaben. Der Leitfaden schlägt fünf konkrete Schritte vor, um im Anschluss an die Methodik des Naturgefahrenchecks (1) das Bewusstsein für die Zusammenhänge zwischen einzelnen klimabedingten Risiken zu schärfen, (2) aus den bisher gemachten Erfahrungen im Naturgefahrenmanagement für die „neuen“ Risiken zu lernen und (3) gemeinsam konkrete Maßnahmen zu entwerfen und nächste Umsetzungsschritte zu definieren, wie diese Risiken in Zukunft zusammen gedacht und proaktiv angegangen werden können. Der Leitfaden ist so aufgebaut, dass bei Bedarf auch jeder Schritt als einzelnes gesondertes Erweiterungsmodul für den „Vorsorgechecks Naturgefahren im Klimawandel“ dienen kann
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