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This report documents the program and the outcomes of Dagstuhl Seminar 23271, "Human in the (process) mines". The seminar dealt with topics that are at the intersection of process mining and visual analytics, and can potentially contribute to both areas. Process mining is a discipline blending data science concepts with business process management. It utilizes event data recorded by IT systems for a variety of tasks, including the automated discovery of graphical process models, conformance checking between data and models, enhancement of process models with additional analytic information, run-time monitoring of processes and operational support. Ultimately, the purpose of process mining is to make sense of event data and answer business and domain-related questions to support domain-specific goals. Visual Analytics, defined as "the science of analytical reasoning facilitated by interactive visual interfaces," is a multidisciplinary approach, integrating aspects of data mining and knowledge discovery, information visualization, human-computer interaction, and cognitive science to support humans in making sense of various kinds of data. While these two research disciplines face similar challenges in different contexts, there have been few interactions and cross-fertilization efforts between the respective communities so far. This Dagstuhl Seminar is intended to bring together researchers from both communities and foster joint research efforts and collaborations to advance both fields and enrich future approaches to be developed.

Poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) is a promising biodegradable bio-based material, which is designed for a vast range of applications, depending on its composite. This study aims to assess the degradability of a PHBV-based compound under different conditions. The research group followed different methodological approaches and assessed visual and mass changes, mechanical and morphological properties, spectroscopic and structural characterisation, along with thermal behaviour. The Ph-Stat (enzymatic degradation) test and total dry solids (TDS)/total volatile solids (TVS) measurements were carried out. Finally, the team experimentally evaluated the amount of methane and carbon dioxide produced, i.e., the degree of biodegradation under aerobic conditions. According to the results, different types of tests have shown differing effects of environmental conditions on material degradation. In conclusion, this paper provides a summary of the investigations regarding the degradation behaviour of the PHBV-based compound under varying environmental factors. The main strengths of the study lie in its multi-faceted approach, combining assessments of PHBV-based compound degradability under different conditions using various analytical tools, such as visual and mass changes, mechanical and morphological properties, spectroscopic and structural characterization, and thermal behavior. These methods collectively contribute to the robustness and reliability of the undertaken work.

Background & Aims: Autoimmune pancreatitis (AIP) is an immune-mediated disease of the pancreas with distinct pathophysiology and manifestations. Our aims were to characterize type 1 AIP in a large pan-European cohort and study the effectiveness of current treatment regimens. Methods: We retrospectively analyzed adults diagnosed since 2005 with type 1 or not-otherwise-specified AIP in 42 European university hospitals. Type 1 AIP was uniformly diagnosed using specific diagnostic criteria. Patients with type 2 AIP and those who had undergone pancreatic surgery were excluded. The primary end point was complete remission, defined as the absence of clinical symptoms and resolution of the index radiologic pancreatic abnormalities attributed to AIP. Results: We included 735 individuals with AIP (69% male; median age, 57 years; 85% White). Steroid treatment was started in 634 patients, of whom 9 (1%) were lost to follow-up. The remaining 625 had a 79% (496/625) complete, 18% (111/625) partial, and 97% (607/625) cumulative remission rate, whereas 3% (18/625) did not achieve remission. No treatment was given in 95 patients, who had a 61% complete (58/95), 19% partial (18/95), and 80% cumulative (76/95) spontaneous remission rate. Higher (≥0.4 mg/kg/day) corticosteroid doses were no more effective than lower (<0.4 mg/kg/day) doses (odds ratio, 0.428; 95% confidence interval, 0.054–3.387) and neither was a starting dose duration >2 weeks (odds ratio, 0.908; 95% confidence interval, 0.818–1.009). Elevated IgG4 levels were independently associated with a decreased chance of complete remission (odds ratio, 0.639; 95% confidence interval, 0.427–0.955). Relapse occurred in 30% of patients. Relapses within 6 months of remission induction were independent of the steroid-tapering duration, induction treatment duration, and total cumulative dose. Conclusions: Patients with type 1 AIP and elevated IgG4 level may need closer monitoring. For remission induction, a starting dose

Visual Analytics as the science of analytical reasoning facilitated by interactive visual interfaces aims to enable the exploration and the understanding of large, heterogeneous, and complex data sets. Time is an important data dimension with distinct characteristics. Intertwining Visual Analytics with time and temporal reasoning introduces outstanding challenges and opportunities, which I will illustrate in this talk.

Set visualization facilitates the exploration and analysis of set-type data. However, how sets should be visualized when the data are uncertain is still an open research challenge. To address the problem of depicting uncertainty in set visualization, we ask 1) which aspects of set type data can be affected by uncertainty and 2) which characteristics of uncertainty influence the visualization design. We answer these research questions by first describing a conceptual framework that brings together 1) the information that is primarily relevant in sets (i.e., set membership, set attributes, and element attributes) and 2) different plausible categories of (un)certainty (i.e., certainty, undefined uncertainty as a binary fact, and defined uncertainty as quantifiable measure). Following the structure of our framework, we systematically discuss basic visualization examples of integrating uncertainty in set visualizations. We draw on existing knowledge about general uncertainty visualization and previous evidence of its effectiveness.

Human-centered approaches are of particular importance when analyzing urban spaces in technology-driven fields, because understanding how people perceive and react to their environments depends on several dynamic and static factors, such as traffic volume, noise, safety, urban configuration, and greenness. Analyzing and interpreting emotions against the background of environmental information can provide insights into the spatial and temporal properties of urban spaces and their influence on citizens, such as urban walkability and bikeability. In this study, we present a comprehensive mixed-methods approach to geospatial analysis that utilizes wearable sensor technology for emotion detection and combines information from sources that correct or complement each other. This includes objective data from wearable physiological sensors combined with an eDiary app, first-person perspective videos from a chest-mounted camera, and georeferenced interviews, and post-hoc surveys. Across two studies, we identified and geolocated pedestrians' and cyclists' moments of stress and relaxation in the city centers of Salzburg and Cologne. Despite open methodological questions, we conclude that mapping wearable sensor data, complemented with other sources of information - all of which are indispensable for evidence-based urban planning - offering tremendous potential for gaining useful insights into urban spaces and their impact on citizens.

Attempts to convince humanities scholars of digital approaches are met with resistance, often. The so-called Digitization Anxiety is the phenomenon that describes the fear of many traditional scientists of being replaced by digital processes. This hinders not only the progress of the scientific domains themselves – since a lot of digital potential is missing – but also makes the everyday work of researchers unnecessarily difficult. Over the past eight years, we have made various attempts to walk the tightrope between 'How can we help traditional humanities to exploit their digital potential?' and 'How can we make them understand that their expertise is not replaced by digital means, but complemented?' We will present our successful interdisciplinary collaborations: How they came about, how they developed, and the problems we encountered. In the first step, we will look at the theoretical basics, which paint a comprehensive picture of the digital humanities and introduces us to the topic of visualization. The field of visualization has shown a special ability: It manages to walk the tightrope and thus keeps digitization anxiety at bay, while not only making it easier for scholars to access their data, but also enabling entirely new research questions. After an introduction to our interdisciplinary collaborations with the Musical Instrument Museum of Leipzig University, as well as with the Bergen-Belsen Memorial, we will present a series of user scenarios that we have collected in the course of 13 publications. These show our cooperation partners solving different research tasks, which we classify using Brehmer and Munzner’s Task Classification. In this way, we show that we provide researchers with a wide range of opportunities: They can answer their traditional research questions – and in some cases verify long-standing hypotheses about the data for the first time – but also develop their own interest in previously impossible, new research questions and approaches. F

Attempts to convince humanities scholars of digital approaches are met with resistance, often. The so-called Digitization Anxiety is the phenomenon that describes the fear of many traditional scientists of being replaced by digital processes. This hinders not only the progress of the scientific domains themselves – since a lot of digital potential is missing – but also makes the everyday work of researchers unnecessarily difficult. Over the past eight years, we have made various attempts to walk the tightrope between 'How can we help traditional humanities to exploit their digital potential?' and 'How can we make them understand that their expertise is not replaced by digital means, but complemented?' We will present our successful interdisciplinary collaborations: How they came about, how they developed, and the problems we encountered. In the first step, we will look at the theoretical basics, which paint a comprehensive picture of the digital humanities and introduces us to the topic of visualization. The field of visualization has shown a special ability: It manages to walk the tightrope and thus keeps digitization anxiety at bay, while not only making it easier for scholars to access their data, but also enabling entirely new research questions. After an introduction to our interdisciplinary collaborations with the Musical Instrument Museum of Leipzig University, as well as with the Bergen-Belsen Memorial, we will present a series of user scenarios that we have collected in the course of 13 publications. These show our cooperation partners solving different research tasks, which we classify using Brehmer and Munzner’s Task Classification. In this way, we show that we provide researchers with a wide range of opportunities: They can answer their traditional research questions – and in some cases verify long-standing hypotheses about the data for the first time – but also develop their own interest in previously impossible, new research questions and approaches. F

Among the highly diverse range of biobased polymers, polylactic acid (PLA) received vast attention in recent years due to its versatility for different applications and being the first commercially used polymer produced from renewable sources. Production and application of bio-based, biodegradable plastics will have one of the most crucial roles in tackling worldwide plastic pollution. Methods: This study is based on integrative ecotoxicological assessment of an innovative PLA-based agricultural mulch film (BPE-AMF-PLA), developed under the H2020 EU project “BIO-PLASTICS EUROPE”, towards organisms from different environmental compartments (soil, fresh water and marine) and from different trophic levels. Such comprehensive evaluation has an overarching goal to promote environmentally safe and sustainable use of these PLA-based plastics for agricultural and other potential applications. Results: Low-to-no phytotoxicity was obtained in both single-species standardized bioassays, and in a multi-species microcosms experiment. Earthworm reproduction was negatively affected at the lowest test concentration of 0.1% w/w of PLA-based plastic particles. For freshwater Daphnia, reproduction was found a sensitive endpoint, upon exposure to the leachates of the PLA-based plastic. However, the reported toxicity seemed to be caused by the presence of 2-methylnaphthalene, which can be avoided in the production process. As for the marine organisms, algae growth was inhibited with a LOEC = 25 g L−1, whereas test with brine shrimp only revealed stimulation of lipase upon digestion of micro-sized PLA-based plastics. Marine lugworm ingested pristine and UV pre-treated micro-sized plastics, yet without impact either on biological activity, or on the health of the test individuals. Discussion: The approach used in the present work will contribute to product development, environmental safety and sustainable applications of the PLA-based mulch film BPE-AMF-PLA, in the scope of project BIO-PL

Set visualization facilitates the exploration and analysis of set-type data. However, how sets should be visualized when the data is uncertain is still an open research challenge. To address the problem of depicting uncertainty in set visualization, we ask (i) which aspects of set type data can be affected by uncertainty and (ii) which characteristics of uncertainty influence the visualization design. We answer these research questions by first developing a conceptual framework that brings together (i) the information that is primarily relevant in sets (i.e., set membership, set attributes, and element attributes) and (ii) different plausible categories of (un)certainty (i.e., certainty, undefined uncertainty as a binary fact, and defined uncertainty as quantifiable measure). Based on the conceptual framework, we systematically discuss visualization examples of integrating uncertainty in set visualizations. We draw on existing knowledge about general uncertainty visualization and fill gaps where set-specific aspects have not yet been considered sufficiently.

Modern science and industry rely on computational models for simulation, prediction, and data analysis. Spatial blind source separation (SBSS) is a model used to analyze spatial data. Designed explicitly for spatial data analysis, it is superior to popular non-spatial methods, like PCA. However, a challenge to its practical use is setting two complex tuning parameters, which requires parameter space analysis. In this paper, we focus on sensitivity analysis (SA). SBSS parameters and outputs are spatial data, which makes SA difficult as few SA approaches in the literature assume such complex data on both sides of the model. Based on the requirements in our design study with statistics experts, we developed a visual analytics prototype for data type agnostic visual sensitivity analysis that fits SBSS and other contexts. The main advantage of our approach is that it requires only dissimilarity measures for parameter settings and outputs. We evaluated the prototype heuristically with visualization experts and through interviews with two SBSS experts. In addition, we show the transferability of our approach by applying it to microclimate simulations. Study participants could confirm suspected and known parameter-output relations, find surprising associations, and identify parameter subspaces to examine in the future. During our design study and evaluation, we identified challenging future research opportunities.

Guidance can support users during the exploration and analysis of complex data. Previous research focused on characterizing the theoretical aspects of guidance in visual analytics and implementing guidance in different scenarios. However, the evaluation of guidance-enhanced visual analytics solutions remains an open research question. We tackle this question by introducing and validating a practical evaluation methodology for guidance in visual analytics. We identify eight quality criteria to be fulfilled and collect expert feedback on their validity. To facilitate actual evaluation studies, we derive two sets of heuristics. The first set targets heuristic evaluations conducted by expert evaluators. The second set facilitates end-user studies where participants actually use a guidance-enhanced system. By following such a dual approach, the different quality criteria of guidance can be examined from two different perspectives, enhancing the overall value of evaluation studies. To test the practical utility of our methodology, we employ it in two studies to gain insight into the quality of two guidance-enhanced visual analytics solutions, one being a work-in-progress research prototype, and the other being a publicly available visualization recommender system. Based on these two evaluations, we derive good practices for conducting evaluations of guidance in visual analytics and identify pitfalls to be avoided during such studies., Comment: Accepted to IEEE VIS 2023

Draco has been developed as an automated visualization recommendation system formalizing design knowledge as logical constraints in ASP (Answer-Set Programming). With an increasing set of constraints and incorporated design knowledge, even visualization experts lose overview in Draco and struggle to retrace the automated recommendation decisions made by the system. Our paper proposes an Visual Analytics (VA) approach to visualize and analyze Draco's constraints. Our VA approach is supposed to enable visualization experts to accomplish identified tasks regarding the knowledge base and support them in better understanding Draco. We extend the existing data extraction strategy of Draco with a data processing architecture capable of extracting features of interest from the knowledge base. A revised version of the ASP grammar provides the basis for this data processing strategy. The resulting incorporated and shared features of the constraints are then visualized using a hypergraph structure inside the radial-arranged constraints of the elaborated visualization. The hierarchical categories of the constraints are indicated by arcs surrounding the constraints. Our approach is supposed to enable visualization experts to interactively explore the design rules' violations based on highlighting respective constraints or recommendations. A qualitative and quantitative evaluation of the prototype confirms the prototype's effectiveness and value in acquiring insights into Draco's recommendation process and design constraints., Comment: To be presented at VIS 2023

The progressive substitution of petroleum-based polymers, such as polyethylene, polyvinylchloride, or polyethylene terephtalate, by so-called bioplastics facilitated the development and production of many new materials. The continuously refined properties of bioplastic compounds and their blends enable various applications. With growing production and utilization of bioplastic products, these materials are increasingly discarded into the environment. Although many of these materials are labeled biodegradable, there is limited information about their degradability under environmental conditions. We tested the enzymatic degradability of five bioplastic compounds with the rapid pH-Stat titration assay at environmentally relevant seawater temperatures between 5 and 30°C and pH 8.2. These plastics, issued from the European Horizon 2020 Project ´Bioplastics Europe´, are based on polylactic acid (PLA), polybutylene succinate (PBS), and poly(hydroxybutyrate-co-hydroxyvalerate) (PHBV). Suspensions of microparticles (< 200 µm) were incubated with each of the three hydrolytic enzymes, protease, lipase, and esterase. A PLA-based compound blended with polybutylene adipate terephthalate (PBAT) showed the highest hydrolysis rate of 30 nmol·min-1 when incubated with lipase at 30°C. All other materials showed low hydrolysis rates of less than 10 nmol·min-1. Below 20°C, hydrolysis almost ceased. Plate clearing assays with the same enzymes at 37°C and pH 5 and pH 8, respectively, largely confirmed the results of the pH-Stat titration assays. Our findings indicate that there is a potential degradation of most of the materials with at least one of these hydrolytic enzymes. Nonetheless, the rate of enzymatic degradation under environmentally relevant conditions is low, which indicates only a marginal degradability of bioplastics in the marine environment.

The presented thesis discusses the numerical modeling of acoustic metamaterials for the design of lightweight components with improved vibroacoustic properties. Therefore, two different concepts of acoustic metamaterials are analyzed: Acoustic black holes and periodically distributed resonators. Numerical models form the basis to assess the performance and derive criteria for the design of future lightweight components., Diese Arbeit befasst sich mit der numerischen Modellierung von akustischen Metamaterialien für den Entwurf von Leichtbaukomponenten mit verbesserten vibroakustischen Eigenschaften. Dazu werden zwei unterschiedliche Konzepte von akustischen Metamaterialien analysiert: Akustische Schwarze Löcher und periodisch verteilte Resonatoren. Basierend auf numerischen Modellen werden die Konzepte bewertet und Kriterien für das Design zukünftiger Leichtbaukomponenten abgeleitet.

Contains fulltext : 282680.pdf (Publisher’s version ) (Open Access)

The phenomenon of a blockchain use case called initial coin offering (ICO) is drawing increasing attention as a novel funding mechanism. ICO is a crowdfunding type that utilizes blockchain tokens to allow for truly peer-to-peer investments. Although more than \$7bn has been raised globally via ICOs as at 2018, the concept and its implications are not yet entirely understood. The research lags behind in providing in-depth analyses of ICO designs and their long-term success. We address this research gap by developing an ICO taxonomy, applying a cluster analysis to identify prevailing ICO archetypes, and providing an outlook on the token value market performance for individual archetypes. We identify five ICO design archetypes and display their secondary market development from both a short-term and a long-term perspective. We contribute to an in-depth understanding of ICOs and their implications. Further, we offer practitioners tangible design and success indications for future ICOs.

The phenomenon of a blockchain use case called initial coin offering (ICO) is drawing increasing attention as a novel funding mechanism. ICO is a crowdfunding type that utilizes blockchain tokens to allow for truly peer-to-peer investments. Although more than \$7bn has been raised globally via ICOs as at 2018, the concept and its implications are not yet entirely understood. The research lags behind in providing in-depth analyses of ICO designs and their long-term success. We address this research gap by developing an ICO taxonomy, applying a cluster analysis to identify prevailing ICO archetypes, and providing an outlook on the token value market performance for individual archetypes. We identify five ICO design archetypes and display their secondary market development from both a short-term and a long-term perspective. We contribute to an in-depth understanding of ICOs and their implications. Further, we offer practitioners tangible design and success indications for future ICOs.

The phenomenon of a blockchain use case called initial coin offering (ICO) is drawing increasing attention as a novel funding mechanism. ICO is a crowdfunding type that utilizes blockchain tokens to allow for truly peer-to-peer investments. Although more than \$7bn has been raised globally via ICOs as at 2018, the concept and its implications are not yet entirely understood. The research lags behind in providing in-depth analyses of ICO designs and their long-term success. We address this research gap by developing an ICO taxonomy, applying a cluster analysis to identify prevailing ICO archetypes, and providing an outlook on the token value market performance for individual archetypes. We identify five ICO design archetypes and display their secondary market development from both a short-term and a long-term perspective. We contribute to an in-depth understanding of ICOs and their implications. Further, we offer practitioners tangible design and success indications for future ICOs.

Contains fulltext : 282680.pdf (Publisher’s version ) (Open Access)

The phenomenon of a blockchain use case called initial coin offering (ICO) is drawing increasing attention as a novel funding mechanism. ICO is a crowdfunding type that utilizes blockchain tokens to allow for truly peer-to-peer investments. Although more than \$7bn has been raised globally via ICOs as at 2018, the concept and its implications are not yet entirely understood. The research lags behind in providing in-depth analyses of ICO designs and their long-term success. We address this research gap by developing an ICO taxonomy, applying a cluster analysis to identify prevailing ICO archetypes, and providing an outlook on the token value market performance for individual archetypes. We identify five ICO design archetypes and display their secondary market development from both a short-term and a long-term perspective. We contribute to an in-depth understanding of ICOs and their implications. Further, we offer practitioners tangible design and success indications for future ICOs.

The pollution of the environment by plastics is a perpetual problem that poses a great challenge to mankind. A promising strategy to counteract the increasing pollution is the innovation and development of biodegradable materials. However, biodegradable plastics reach into the marine environment in the same way as conventional plastics and can also be ingested by marine organisms. There is a wide variety of different polymers that are used in biodegradable materials, such as polylactic acid (PLA), polybutylene succinate (PBS) or polyhydroxyalkanoates (PHAs). Those compounds are known to be enzymatically degradable by several enzymes under certain conditions. Once ingested by marine organisms such as crustaceans, the highly active mixture of enzymes in their digestive tracts may break down compounds and facilitate degradation. In this study, the hydrolytic activity of gastric fluids from Cancer pagurus on different biodegradable and conventional plastics was evaluated with pH Stat titration. The enzymes capable of hydrolyzing biodegradable plastics were isolated from the gastric fluid and characterized using several analytical methods. Separated protein fractions with a high amount of lipolytic enzymes showed the highest potential on hydrolyzing biodegradable plastics.

The progressive substitution of petroleum-based polymers, such as polyethylene, polyvinylchloride, or polyethylene terephtalate, by so-called bioplastics facilitated the development and production of many new materials. The continuously refined properties of bioplastic compounds and their blends enable various applications. With growing production and utilization of bioplastic products, these materials are increasingly discarded into the environment. Although many of these materials are labeled biodegradable, there is limited information about their degradability under environmental conditions. We tested the enzymatic degradability of five bioplastic compounds with the rapid pH-Stat titration assay at environmentally relevant seawater temperatures between 5 and 30°C and pH 8.2. These plastics, issued from the European Horizon 2020 Project ´Bioplastics Europe´, are based on polylactic acid (PLA), polybutylene succinate (PBS), and poly(hydroxybutyrate-co-hydroxyvalerate) (PHBV). Suspensions of microparticles (< 200 µm) were incubated with each of the three hydrolytic enzymes, protease, lipase, and esterase. A PLA-based compound blended with polybutylene adipate terephthalate (PBAT) showed the highest hydrolysis rate of 30 nmol·min-1 when incubated with lipase at 30°C. All other materials showed low hydrolysis rates of less than 10 nmol·min-1. Below 20°C, hydrolysis almost ceased. Plate clearing assays with the same enzymes at 37°C and pH 5 and pH 8, respectively, largely confirmed the results of the pH-Stat titration assays. Our findings indicate that there is a potential degradation of most of the materials with at least one of these hydrolytic enzymes. Nonetheless, the rate of enzymatic degradation under environmentally relevant conditions is low, which indicates only a marginal degradability of bioplastics in the marine environment.

BackgroundPSMA-TO-1 ("Tumor-Optimized-1") is a novel PSMA ligand with longer circulation time than PSMA-617. We compared the biodistribution in subcutaneous tumor-bearing mice of PSMA-TO-1, PSMA-617 and PSMA-11 when labeled with 68Ga and 177Lu, and the survival after treatment with 225Ac-PSMA-TO-1/-617 in a murine model of disseminated prostate cancer. We also report dosimetry data of 177Lu-PSMA-TO1/-617 in prostate cancer patients.MethodsFirst, PET images of 68Ga-PSMA-TO-1/-617/-11 were acquired on consecutive days in three mice bearing subcutaneous C4-2 xenografts. Second, 50 subcutaneous tumor-bearing mice received either 30 MBq of 177Lu-PSMA-617 or 177Lu-PSMA-TO-1 and were sacrificed at 1, 4, 24, 48 and 168 h for ex vivo gamma counting and biodistribution. Third, mice bearing disseminated lesions via intracardiac inoculation were treated with either 40 kBq of 225Ac-PSMA-617, 225Ac-PSMA-TO-1, or remained untreated and followed for survival. Additionally, 3 metastatic castration-resistant prostate cancer patients received 500 MBq of 177Lu-PSMA-TO-1 under compassionate use for dosimetry purposes. Planar images with an additional SPECT/CT acquisition were acquired for dosimetry calculations.ResultsTumor uptake measured by PET imaging of 68Ga-labeled agents in mice was highest using PSMA-617, followed by PSMA-TO-1 and PSMA-11. 177Lu-PSMA tumor uptake measured by ex vivo gamma counting at subsequent time points tended to be greater for PSMA-TO-1 up to 1 week following treatment (p > 0.13 at all time points). This was, however, accompanied by increased kidney uptake and a 26-fold higher kidney dose of PSMA-TO-1 compared with PSMA-617 in mice. Mice treated with a single-cycle 225Ac-PSMA-TO-1 survived longer than those treated with 225Ac-PSMA-617 and untreated mice, respectively (17.8, 14.5 and 7.7 weeks, respectively; p < 0.0001). Kidney, salivary gland, bone marrow and mean ± SD tumor dose coefficients (Gy/GBq) for 177Lu-PSMA-TO-1 in pati

Dynamic networks reflect temporal changes occurring to the graph's structure and are used to model a wide variety of problems in many application fields. We investigate the design space of dynamic graph visualization along two major dimensions: the network structural and temporal representation. Significant research has been conducted evaluating the benefits and drawbacks of different structural representations for static graphs, however, few extend this comparison to a dynamic network setting. We conduct a study where we assess the participants' response times, accuracy, and preferences for different combinations of the graph's structural and temporal representations on typical dynamic network exploration tasks, with and without support of common interaction methods. Our results suggest that matrices provide better support for tasks on lower-level entities and basic interactions require longer response times while increasing accuracy. Node-link with auto animation proved to be the quickest and most accurate combination overall, while animation with playback control the most preferred temporal encoding., Comment: Appears in the Proceedings of the 30th International Symposium on Graph Drawing and Network Visualization (GD 2022)

A typical problem in Visual Analytics is that users are highly trained experts in their application domains, but have mostly no experience in using VA systems. Thus, users often have difficulties interpreting and working with visual representations. To overcome these problems, user assistance can be incorporated into VA systems to guide experts through the analysis while closing their knowledge gaps. Different types of user assistance can be applied to extend the power of VA, enhance the user's experience, and broaden the audience for VA. Although different approaches to visualization onboarding and guidance in VA already exist, there is a lack of research on how to design and integrate them in effective and efficient ways. Therefore, we aim at putting together the pieces of the mosaic to form a coherent whole. Based on the Knowledge-Assisted Visual Analytics model, we contribute a conceptual model of user assistance for VA by integrating the process of visualization onboarding and guidance as the two main approaches in this direction. As a result, we clarify and discuss the commonalities and differences between visualization onboarding and guidance, and discuss how they benefit from the integration of knowledge extraction and exploration. Finally, we discuss our descriptive model by applying it to VA tools integrating visualization onboarding and guidance, and showing how they should be utilized in different phases of the analysis in order to be effective and accepted by the user., Comment: Elsevier Visual Informatics (revised version under review)

The presented thesis discusses the numerical modeling of acoustic metamaterials for the design of lightweight components with improved vibroacoustic properties. Therefore, two different concepts of acoustic metamaterials are analyzed: Acoustic black holes and periodically distributed resonators. Numerical models form the basis to assess the performance and derive criteria for the design of future lightweight components., Diese Arbeit befasst sich mit der numerischen Modellierung von akustischen Metamaterialien für den Entwurf von Leichtbaukomponenten mit verbesserten vibroakustischen Eigenschaften. Dazu werden zwei unterschiedliche Konzepte von akustischen Metamaterialien analysiert: Akustische Schwarze Löcher und periodisch verteilte Resonatoren. Basierend auf numerischen Modellen werden die Konzepte bewertet und Kriterien für das Design zukünftiger Leichtbaukomponenten abgeleitet.

This report documents the program and the outcomes of Dagstuhl Seminar 19192 "Visual Analytics for Sets over Time and Space", which brought together 29 researchers working on visualization (i) from a theoretical point of view (graph drawing, computational geometry, and cognition), (ii) from a temporal point of view (visual analytics and information visualization over time, HCI), and (iii) from a space-time point of view (cartography, GIScience). The goal of the seminar was to identify specific theoretical and practical problems that need to be solved in order to create dynamic and interactive set visualizations that take into account time and space, and to begin working on these problems. The first 1.5 days were reserved for overview presentations from representatives of the different communities, for presenting open problems, and for forming interdisciplinary working groups that will focus on some of the identified open problems as a group. There were three survey talks, ten short talks, and one panel with three contributors. The remaining three days consisted of open mic sessions, working-group meetings, and progress reports. Five working groups were formed that investigated several of the open research questions. Abstracts of the talks and a report from each working group are included in this report.

This report documents the program and the outcomes of Dagstuhl Seminar 19192 "Visual Analytics for Sets over Time and Space", which brought together 29 researchers working on visualization (i) from a theoretical point of view (graph drawing, computational geometry, and cognition), (ii) from a temporal point of view (visual analytics and information visualization over time, HCI), and (iii) from a space-time point of view (cartography, GIScience). The goal of the seminar was to identify specific theoretical and practical problems that need to be solved in order to create dynamic and interactive set visualizations that take into account time and space, and to begin working on these problems. The first 1.5 days were reserved for overview presentations from representatives of the different communities, for presenting open problems, and for forming interdisciplinary working groups that will focus on some of the identified open problems as a group. There were three survey talks, ten short talks, and one panel with three contributors. The remaining three days consisted of open mic sessions, working-group meetings, and progress reports. Five working groups were formed that investigated several of the open research questions. Abstracts of the talks and a report from each working group are included in this report.

This report documents the program and the outcomes of Dagstuhl Seminar 19192 “Visual Analytics for Sets over Time and Space”, which brought together 29 researchers working on visualization(i) from a theoretical point of view (graphdrawing, computational geometry, and cognition (ii) from a temporal point of view (visual analytics and information visualization overtime, HCI), and (iii) from a space-time point of view (cartography, GIScience). The goal of the seminar was to identify specific theoretical and practical problems that need to be solved in order to create dynamic and interactive set visualizations that take into account time and space, and to begin working on these problems. The first 1.5 days were reserved for overview presentations from representatives of the different communities, for presenting open problems, and for forming interdisciplinary working groups that would focus on some of the identified open problems as a group. There were three survey talks, ten short talks, and one panel with three contributors. The remaining three days consisted of open mic sessions, working-group meetings, and progress reports. Five working groups were formed that investigated several of the open research questions. Abstracts of the talks and a report from each working group are included in this report.

The recent wave of detections of interstellar aromatic molecules has sparked interest in the chemical behavior of aromatic molecules under astrophysical conditions. In most cases, these detections have been made through chemically related molecules, called proxies, that implicitly indicate the presence of a parent molecule. In this study, we present the results of the theoretical evaluation of the hydrogenation reactions of different aromatic molecules (benzene, pyridine, pyrrole, furan, thiophene, silabenzene, and phosphorine). The viability of these reactions allows us to evaluate the resilience of these molecules to the most important reducing agent in the interstellar medium, the hydrogen atom (H). All significant reactions are exothermic and most of them present activation barriers, which are, in several cases, overcome by quantum tunneling. Instanton reaction rate constants are provided between 50 K and 500 K. For the most efficiently formed radicals, a second hydrogenation step has been studied. We propose that hydrogenated derivatives of furan, pyrrole, and specially 2,3-dihydropyrrole, 2,5-dihydropyrrole, 2,3-dihydrofuran, and 2,5-dihydrofuran are promising candidates for future interstellar detections.

Coastal sands are biocatalytic filters for dissolved and particulate organic matter of marine and terrestrial origin, thus, acting as centers of organic matter transformation. At high temporal resolution, we accessed the variability of benthic bacterial communities over two annual cycles at Helgoland (North Sea), and compared it with seasonality of communities in Isfjorden (Svalbard, 78°N) sediments, where primary production does not occur during winter. Benthic community structure remained stable in both, temperate and polar sediments on the level of cell counts and 16S rRNA-based taxonomy. Actinobacteriota of uncultured Actinomarinales and Microtrichales were a major group, with 8 ± 1% of total reads (Helgoland) and 31 ± 6% (Svalbard). Their high activity (frequency of dividing cells 28%) and in situ cell numbers of >10% of total microbes in Svalbard sediments, suggest Actinomarinales and Microtrichales as key heterotrophs for carbon mineralization. Even though Helgoland and Svalbard sampling sites showed no phytodetritus-driven changes of the benthic bacterial community structure, they harbored significantly different communities (p < 0.0001, r = 0.963). The temporal stability of benthic bacterial communities is in stark contrast to the dynamic succession typical of coastal waters, suggesting that pelagic and benthic bacterial communities respond to phytoplankton productivity very differently.

Bio-based polymers have been suggested as one possible opportunity to counteract the progressive accumulation of microplastics in the environments. The gradual substitution of conventional plastics by bio-based polymers bears a variety of novel materials. The application of bioplastics is determined by their stability and bio-degradability, respectively. With the increasing implementation of bio-based plastics, there is also a demand for rapid and non-elaborate methods to determine their bio-degradability. Here, we propose an improved pH Stat titration assay optimized for bio-based polymers under environmental conditions and controlled temperature. Exemplarily, suspensions of poly(lactic acid) (PLA) and poly(butylene succinate) (PBS) microparticles were incubated with proteolytic and lipolytic enzymes. The rate of hydrolysis, as determined by counter-titration with a diluted base (NaOH), was recorded for two hours. PLA was hydrolyzed by proteolytic enzymes but not by lipase. PBS, in contrast, showed higher hydrolysis rates with lipase than with proteases. The thermal profile of PLA hydrolysis by protease showed an exponential increase from 4 to 30 °C with a temperature quotient Q10 of 5.6. The activation energy was 110 kJ·mol−1. pH-Stat titration proved to be a rapid, sensitive, and reliable procedure supplementing established methods of determining the bio-degradability of polymers under environmental conditions.

Coastal sands are biocatalytic filters for dissolved and particulate organic matter of marine and terrestrial origin, thus, acting as centers of organic matter transformation. At high temporal resolution, we accessed the variability of benthic bacterial communities over two annual cycles at Helgoland (North Sea), and compared it with seasonality of communities in Isfjorden (Svalbard, 78°N) sediments, where primary production does not occur during winter. Benthic community structure remained stable in both, temperate and polar sediments on the level of cell counts and 16S rRNA-based taxonomy. Actinobacteriota of uncultured Actinomarinales and Microtrichales were a major group, with 8 ± 1% of total reads (Helgoland) and 31 ± 6% (Svalbard). Their high activity (frequency of dividing cells 28%) and in situ cell numbers of >10% of total microbes in Svalbard sediments, suggest Actinomarinales and Microtrichales as key heterotrophs for carbon mineralization. Even though Helgoland and Svalbard sampling sites showed no phytodetritus-driven changes of the benthic bacterial community structure, they harbored significantly different communities (p < 0.0001, r = 0.963). The temporal stability of benthic bacterial communities is in stark contrast to the dynamic succession typical of coastal waters, suggesting that pelagic and benthic bacterial communities respond to phytoplankton productivity very differently.

Bio-based polymers have been suggested as one possible opportunity to counteract the progressive accumulation of microplastics in the environments. The gradual substitution of conventional plastics by bio-based polymers bears a variety of novel materials. The application of bioplastics is determined by their stability and bio-degradability, respectively. With the increasing implementation of bio-based plastics, there is also a demand for rapid and non-elaborate methods to determine their bio-degradability. Here, we propose an improved pH Stat titration assay optimized for bio-based polymers under environmental conditions and controlled temperature. Exemplarily, suspensions of poly(lactic acid) (PLA) and poly(butylene succinate) (PBS) microparticles were incubated with proteolytic and lipolytic enzymes. The rate of hydrolysis, as determined by counter-titration with a diluted base (NaOH), was recorded for two hours. PLA was hydrolyzed by proteolytic enzymes but not by lipase. PBS, in contrast, showed higher hydrolysis rates with lipase than with proteases. The thermal profile of PLA hydrolysis by protease showed an exponential increase from 4 to 30 °C with a temperature quotient Q10 of 5.6. The activation energy was 110 kJ·mol−1. pH-Stat titration proved to be a rapid, sensitive, and reliable procedure supplementing established methods of determining the bio-degradability of polymers under environmental conditions.

Analysis of spatial multivariate data, i.e., measurements at irregularly-spaced locations, is a challenging topic in visualization and statistics alike. Such data are integral to many domains, e.g., indicators of valuable minerals are measured for mine prospecting. Popular analysis methods, like PCA, often by design do not account for the spatial nature of the data. Thus they, together with their spatial variants, must be employed very carefully. Clearly, it is preferable to use methods that were specifically designed for such data, like spatial blind source separation (SBSS). However, SBSS requires two tuning parameters, which are themselves complex spatial objects. Setting these parameters involves navigating two large and interdependent parameter spaces, while also taking into account prior knowledge of the physical reality represented by the data. To support analysts in this process, we developed a visual analytics prototype. We evaluated it with experts in visualization, SBSS, and geochemistry. Our evaluations show that our interactive prototype allows to define complex and realistic parameter settings efficiently, which was so far impractical. Settings identified by a non-expert led to remarkable and surprising insights for a domain expert. Therefore, this paper presents important first steps to enable the use of a promising analysis method for spatial multivariate data.

The recent wave of detections of interstellar aromatic molecules has sparked interest in the chemical behavior of aromatic molecules under astrophysical conditions. In most cases, these detections have been made through chemically related molecules, called proxies, that implicitly indicate the presence of a parent molecule. In this study, we present the results of the theoretical evaluation of the hydrogenation reactions of different aromatic molecules (benzene, pyridine, pyrrole, furan, thiophene, silabenzene, and phosphorine). The viability of these reactions allows us to evaluate the resilience of these molecules to the most important reducing agent in the interstellar medium, the hydrogen atom (H). All significant reactions are exothermic and most of them present activation barriers, which are, in several cases, overcome by quantum tunneling. Instanton reaction rate constants are provided between 50 K and 500 K. For the most efficiently formed radicals, a second hydrogenation step has been studied. We propose that hydrogenated derivatives of furan, pyrrole, and specially 2,3-dihydropyrrole, 2,5-dihydropyrrole, 2,3-dihydrofuran, and 2,5-dihydrofuran are promising candidates for future interstellar detections.

Visualizing big and complex multivariate data is challenging. To address this challenge, we propose flexible visual analytics (FVA) with the aim to mitigate visual complexity and interaction complexity challenges in visual analytics, while maintaining the strengths of multiple perspectives on the studied data. At the heart of our proposed approach are transitions that fluidly transform data between user-relevant views to offer various perspectives and insights into the data. While smooth display transitions have been already proposed, there has not yet been an interdisciplinary discussion to systematically conceptualize and formalize these ideas. As a call to further action, we argue that future research is necessary to develop a conceptual framework for flexible visual analytics. We discuss preliminary ideas for prioritizing multi-aspect visual representations and multi-aspect transitions between them, and consider the display user for whom such depictions are produced and made available for visual analytics. With this contribution we aim to further facilitate visual analytics on complex data sets for varying data exploration tasks and purposes based on different user characteristics and data use contexts.

Contains fulltext : 225864.pdf (publisher's version ) (Open Access), BACKGROUND: Reporting of adverse events is an important aspect of patient safety management in hospitals, which may help to prevent future adverse events. Yet, only a small proportion of such events is actually reported in German hospitals. Therefore, it is crucial to evaluate attitudes of clinical staff towards reporting of adverse events. The aim of this study was to translate the Reporting of Clinical Adverse Events Scale (RoCAES) developed by Wilson, Bekker and Fylan (2008) and validate it in a sample of German-speaking health professionals. METHODS: The questionnaire covers five factors (perceived blame, perceived criteria for identifying events that should be reported, perceptions of colleagues' expectations, perceived benefits of reporting, and perceived clarity of reporting procedures) and was translated into German language according to translation guidelines. Within a cross-sectional study in a sample of 120 health professionals in German hospitals, internal consistency (omega) and construct validity (confirmatory factor analysis) of the German scale RoCAES-D was assessed. RESULTS: The reliability was high (omega = 0.87) and the factor analysis showed a poor model fit (RMSEA: 0.074, χ(2)/df: 1.663, TLI: 0.690). Resulting from lower model fit of the original model (RMSEA: 0.082, χ(2)/df: 1.804, TLI: 0.606), one item was deleted due to low factor loadings and a low R(2) (0.001), and two items were reallocated from the factor 'perceived benefits' to 'perceived blame'. CONCLUSION: The successful translation and initial validation of the RoCAES-D might be a good starting point for further research. A cultural adaptation of the scale needs to be done to initiate a large-scale usage of the questionnaire.

Simple Summary Biomarkers for cancer diagnosis, prognosis and prediction are important tools and an urgent need in precision medicine for pancreatic cancer. In recent years, many experimental and clinical studies aimed at identifying new biomarkers for pancreatic ductal adenocarcinoma. In the review, we summarized current investigations on using novel protein markers, cell-free DNA, metabolome compounds, immune and stroma signatures and microbiome compositions as biomarkers for pancreatic cancer. Our comprehensive overview shows that although there are new promising biomarkers, CA 19-9 remains currently the only regularly used and validated biomarker for pancreatic cancer in clinical routine. Pancreatic ductal adenocarcinoma (PDAC) is an aggressive disease with a dismal prognosis that is frequently diagnosed at an advanced stage. Although less common than other malignant diseases, it currently ranks as the fourth most common cause of cancer-related death in the European Union with a five-year survival rate of below 9%. Surgical resection, followed by adjuvant chemotherapy, remains the only potentially curative treatment but only a minority of patients is diagnosed with locally resectable, non-metastatic disease. Patients with advanced disease are treated with chemotherapy but high rates of treatment resistance and unfavorable side-effect profiles of some of the used regimens remain major challenges. Biomarkers reflect pathophysiological or physiological processes linked to a disease and can be used as diagnostic, prognostic and predictive tools. Thus, accurate biomarkers can allow for better patient stratification and guide therapy choices. Currently, the only broadly used biomarker for PDAC, CA 19-9, has multiple limitations and the need for novel biomarkers is urgent. In this review, we highlight the current situation, recent discoveries and developments in the field of biomarkers of PDAC and their potential clinical applications.