Visual Analysis of Spatio-Temporal Event Predictions: Investigating the Spread Dynamics of Invasive Species

Invasive species are a major cause of ecological damage and commercial losses. A current problem spreading in North America and Europe is the vinegar fly Drosophila suzukii. Unlike other Drosophila, it infests non-rotting and healthy fruits and is therefore of concern to fruit growers, such as vintners. Consequently, large amounts of data about infestations have been collected in recent years. However, there is a lack of interactive methods to investigate this data. We employ ensemble-based classification to predict areas susceptible to infestation by D. suzukii and bring them into a spatio-temporal context using maps and glyph-based visualizations. Following the information-seeking mantra, we provide a visual analysis system Drosophigator for spatio-temporal event prediction, enabling the investigation of the spread dynamics of invasive species. We demonstrate the usefulness of this approach in two use cases

A Cell-Permeable Inhibitor to Trap Gαq Proteins in the Empty Pocket Conformation

In spite of the crucial role of heterotrimeric G proteins as molecular switches transmitting signals from G protein-coupled receptors, their selective manipulation with small molecule, cell-permeable inhibitors still remains an unmet challenge. Here, we report that the small molecule BIM-46187, previously classified as pan-G protein inhibitor, preferentially silences Gαq signaling in a cellular context-dependent manner. Investigations into its mode of action reveal that BIM traps Gαq in the empty pocket conformation by permitting GDP exit but interdicting GTP entry, a molecular mechanism not yet assigned to any other small molecule Gα inhibitor to date. Our data show that Gα proteins may be “frozen” pharmacologically in an intermediate conformation along their activation pathway and propose a pharmacological strategy to specifically silence Gα subclasses with cell-permeable inhibitors

Polyethylene-Like Building Blocks from Plant Oils for Recyclable Polymers, Nanocrystals and Ion-Conductive Materials

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Chain Multiplication of Fatty Acids to Precise Telechelic Polyethylene

Starting from common monounsaturated fatty acids, a strategy is revealed that provides ultra-long aliphatic α,ω-difunctional building blocks by a sequence of two scalable catalytic steps that virtually double the chain length of the starting materials. The central double bond of the α,ω-dicarboxylic fatty acid self-metathesis products is shifted selectively to the statistically much-disfavored α,β-position in a catalytic dynamic isomerizing crystallization approach. "Chain doubling" by a subsequent catalytic olefin metathesis step, which overcomes the low reactivity of this substrates by using waste internal olefins as recyclable co-reagents, yields ultra-long-chain α,ω-difunctional building blocks of a precise chain length, as demonstrated up to a C48 chain. The unique nature of these structures is reflected by unrivaled melting points (Tm =120 °C) of aliphatic polyesters generated from these telechelic monomers, and by their self-assembly to polyethylene-like single crystals.publishe

Closed-loop recycling of polyethylene-like materials

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Crystallization of Long-Spaced Precision Polyacetals III : Polymorphism and Crystallization Kinetics of Even Polyacetals Spaced by 6 to 26 Methylenes

In this paper we extend the study of polymorphism and crystallization kinetics of aliphatic polyacetals to include shorter (PA-6) and longer (PA-26) methylene lengths in a series of even long-spaced systems. On a deep quenching to 0 °C, the longest even polyacetals, PA-18 and PA-26, develop mesomorphic-like disordered structures which, on heating, transform progressively to hexagonal, Form I, and Form II crystallites. Shorter polyacetals, such as PA-6 and PA-12 cannot bypass the formation of Form I. In these systems a mixture of this form and disordered structures develops even under fast deep quenching. A prediction from melting points that Form II will not develop in polyacetals with eight or fewer methylene groups between consecutive acetals was further corroborated with data for PA-6. The temperature coefficient of the overall crystallization rate of the two highest temperature polymorphs, Form I and Form II, was analyzed from the differential scanning calorimetry (DSC) peak crystallization times. The crystallization rate of Form II shows a deep inversion at temperatures approaching the polymorphic transition region from above. The new data on PA-26 confirm that at the minimum rate the heat of fusion is so low that crystallization becomes basically extinguished. The rate inversion and dramatic drop in the heat of fusion irrespective of crystallization time are associated with a competition in nucleation between Forms I and II. The latter is due to large differences in nucleation barriers between these two phases. As PA-6 does not develop Form II, the rate data of this polyacetal display a continuous temperature gradient. The data of the extended polyacetal series demonstrate the important role of methylene sequence length on polymorphism and crystallization kinetics.publishe

Visual Analysis of Urban Traffic Data based on High-Resolution and High-Dimensional Environmental Sensor Data

Urbanization is an increasing global trend resulting in a strong increase in public and individual transportation needs. Accordingly, a major challenge for traffic and urban planners is the design of sustainable mobility concepts to maintain and increase the long-term health of humans by reducing environmental pollution. Recent developments in sensor technology allow the precise tracking of vehicle sensor information, allowing a closer and more in-depth analysis of traffic data. We propose a visual analytics system for the exploration of environmental factors in these high-resolution and high-dimensional mobility sensor data. Additionally, we introduce an interactive visual logging approach to enable experts to cope with complex interactive analysis processes and the problem of the reproducibility of results. The usefulness of our approach is demonstrated via two expert studies with two domain experts from the field of environment-related projects and urban traffic planning.publishe

Visual Soccer Analytics : Understanding the Characteristics of Collective Team Movement Based on Feature-Driven Analysis and Abstraction

With recent advances in sensor technologies, large amounts of movement data have become available in many application areas. A novel, promising application is the data-driven analysis of team sport. Specifically, soccer matches comprise rich, multivariate movement data at high temporal and geospatial resolution. Capturing and analyzing complex movement patterns and interdependencies between the players with respect to various characteristics is challenging. So far, soccer experts manually post-analyze game situations and depict certain patterns with respect to their experience. We propose a visual analysis system for interactive identification of soccer patterns and situations being of interest to the analyst. Our approach builds on a preliminary system, which is enhanced by semantic features defined together with a soccer domain expert. The system includes a range of useful visualizations to show the ranking of features over time and plots the change of game play situations, both helping the analyst to interpret complex game situations. A novel workflow includes improving the analysis process by a learning stage, taking into account user feedback. We evaluate our approach by analyzing real-world soccer matches, illustrate several use cases and collect additional expert feedback. The resulting findings are discussed with subject matter experts.publishe

Visual Analysis of Spatio-Temporal Event Predictions : Investigating the Spread Dynamics of Invasive Species

Invasive species are a major cause of ecological damage and commercial losses. A current problem spreading in North America and Europe is the vinegar fly Drosophila suzukii. Unlike other Drosophila, it infests non-rotting and healthy fruits and is therefore of concern to fruit growers, such as vintners. Consequently, large amounts of data about the occurrence of D. suzukii have been collected in recent years. However, there is a lack of interactive methods to investigate this data. We employ ensemble-based classification to predict areas susceptible to the occurrence of D. suzukii and bring them into a spatio-temporal context using maps and glyph-based visualizations. Following the information-seeking mantra, we provide a visual analysis system Drosophigator for spatio-temporal event predictions, enabling the investigation of the spread dynamics of invasive species. We demonstrate the usefulness of our approach in three use cases and an evaluation with more than 30 domain experts.publishe