One PLOT to Show Them All: Visualization of Efficient Sets in Multi-Objective Landscapes

Visualization techniques for the decision space of continuous multi-objective optimization problems (MOPs) are rather scarce in research. For long, all techniques focused on global optimality and even for the few available landscape visualizations, e.g., cost landscapes, globality is the main criterion. In contrast, the recently proposed gradient field heatmaps (GFHs) emphasize the location and attraction basins of local efficient sets, but ignore the relation of sets in terms of solution quality. In this paper, we propose a new and hybrid visualization technique, which combines the advantages of both approaches in order to represent local and global optimality together within a single visualization. Therefore, we build on the GFH approach but apply a new technique for approximating the location of locally efficient points and using the divergence of the multi-objective gradient vector field as a robust second-order condition. Then, the relative dominance relationship of the determined locally efficient points is used to visualize the complete landscape of the MOP. Augmented by information on the basins of attraction, this Plot of Landscapes with Optimal Trade-offs (PLOT) becomes one of the most informative multi-objective landscape visualization techniques available.Comment: This version has been accepted for publication at the 16th International Conference on Parallel Problem Solving from Nature (PPSN XVI

Comparing individual-based approaches to modelling the self-organization of multicellular tissues.

The coordinated behaviour of populations of cells plays a central role in tissue growth and renewal. Cells react to their microenvironment by modulating processes such as movement, growth and proliferation, and signalling. Alongside experimental studies, computational models offer a useful means by which to investigate these processes. To this end a variety of cell-based modelling approaches have been developed, ranging from lattice-based cellular automata to lattice-free models that treat cells as point-like particles or extended shapes. However, it remains unclear how these approaches compare when applied to the same biological problem, and what differences in behaviour are due to different model assumptions and abstractions. Here, we exploit the availability of an implementation of five popular cell-based modelling approaches within a consistent computational framework, Chaste (http://www.cs.ox.ac.uk/chaste). This framework allows one to easily change constitutive assumptions within these models. In each case we provide full details of all technical aspects of our model implementations. We compare model implementations using four case studies, chosen to reflect the key cellular processes of proliferation, adhesion, and short- and long-range signalling. These case studies demonstrate the applicability of each model and provide a guide for model usage

Capabilities and Limitations of Tissue Size Control through Passive Mechanical Forces

Embryogenesis is an extraordinarily robust process, exhibiting the ability to control tissue size and repair patterning defects in the face of environmental and genetic perturbations. The size and shape of a developing tissue is a function of the number and size of its constituent cells as well as their geometric packing. How these cellular properties are coordinated at the tissue level to ensure developmental robustness remains a mystery; understanding this process requires studying multiple concurrent processes that make up morphogenesis, including the spatial patterning of cell fates and apoptosis, as well as cell intercalations. In this work, we develop a computational model that aims to understand aspects of the robust pattern repair mechanisms of the Drosophila embryonic epidermal tissues. Size control in this system has previously been shown to rely on the regulation of apoptosis rather than proliferation; however, to date little work has been done to understand the role of cellular mechanics in this process. We employ a vertex model of an embryonic segment to test hypotheses about the emergence of this size control. Comparing the model to previously published data across wild type and genetic perturbations, we show that passive mechanical forces suffice to explain the observed size control in the posterior (P) compartment of a segment. However, observed asymmetries in cell death frequencies across the segment are demonstrated to require patterning of cellular properties in the model. Finally, we show that distinct forms of mechanical regulation in the model may be distinguished by differences in cell shapes in the P compartment, as quantified through experimentally accessible summary statistics, as well as by the tissue recoil after laser ablation experiments

SoK: A Consensus Taxonomy in the Blockchain Era

Consensus (a.k.a. Byzantine agreement) is arguably one of the most fundamental problems in distributed systems, playing also an important role in the area of cryptographic protocols as the enabler of a (secure) broadcast functionality. While the problem has a long and rich history and has been analyzed from many different perspectives, recently, with the advent of blockchain protocols like Bitcoin, it has experienced renewed interest from a much wider community of researchers and has seen its application expand to various novel settings. One of the main issues in consensus research is the many different variants of the problem that exist as well as the various ways the problem behaves when different setup, computational assumptions and network models are considered. In this work we perform a systematization of knowledge in the landscape of consensus research starting with the original formulation in the early 1980s up to the present blockchain-based new class of consensus protocols. Our work is a roadmap for studying the consensus problem under its many guises, classifying the way it operates in many settings and highlighting the exciting new applications that have emerged in the blockchain era

Privacy enhancing technologies (PETs) for connected vehicles in smart cities

This is an accepted manuscript of an article published by Wiley in Transactions on Emerging Telecommunications Technologies, available online: https://doi.org/10.1002/ett.4173 The accepted version of the publication may differ from the final published version.Many Experts believe that the Internet of Things (IoT) is a new revolution in technology that has brought many benefits for our organizations, businesses, and industries. However, information security and privacy protection are important challenges particularly for smart vehicles in smart cities that have attracted the attention of experts in this domain. Privacy Enhancing Technologies (PETs) endeavor to mitigate the risk of privacy invasions, but the literature lacks a thorough review of the approaches and techniques that support individuals' privacy in the connection between smart vehicles and smart cities. This gap has stimulated us to conduct this research with the main goal of reviewing recent privacy-enhancing technologies, approaches, taxonomy, challenges, and solutions on the application of PETs for smart vehicles in smart cities. The significant aspect of this study originates from the inclusion of data-oriented and process-oriented privacy protection. This research also identifies limitations of existing PETs, complementary technologies, and potential research directions.Published onlin

Neuartiges Modell zur Untersuchung der Insulintherapie auf die Ausbildung Biofilm-assoziierter Wunden in diabetischen Mäusen

Objective: Diabetic patients suffer more frequently from biofilm-associated infections than normoglycemic patients. Well described in the literature is a relationship between elevated blood glucose levels in patients and the occurrence of biofilm-associated wound infections. Nevertheless, the underlying pathophysiological pathways leading to this increased infection vulnerability and its effects on biofilm development still need to be elucidated. We developed in our laboratory a model to allow the investigation of a biofilm-associated wound infection in diabetic mice under controlled insulin treatment. Methods: A dorsal skinfold chamber was used on 16 weeks old BKS.Cg-Dock7m +/+ Leprdb/J mice and a wound within the observation field of the dorsal skinfold chamber was created. These wounds were infected with Staphylococcus aureus ATCC 49230 (106 cells/mL). Simultaneously, we implanted implants for sustained insulin release into the ventral subcutaneous tissue (N=5 mice). Mice of the control group (N=5) were treated with sham implants. Serum glucose levels were registered before intervention and daily after the operation. Densitometrical analysis of the wound size was performed at day 0, 3, and 6 after intervention. Mice were sacrificed on day 6 and wound tissue was submitted to fluorescence in situ hybridization (FISH) and colony forming unit (CFU) analysis in addition to immunohistochemical staining to observe wound healing. Experiments were carried out in accordance with the National Institute of Health Guidelines for the Care and Use of Laboratory Animals (protocol number 05/19).Results: The insulin implants were able to reduce blood glucose levels in the mice. Hence, the diabetic mice in the intervention group were normoglycemic after the implantation. The combination with the dorsal skinfold chamber allowed for continuous, in vivo measurements of the infection development. Implantation of the insulin implant and the dorsal skinfold chamber was a tolerable condition for the diabetic mice. We succeeded to realize reproducible biofilm infections in the animals. Discussion: We developed a novel model to assess interactions between blood glucose level and S. aureus -induced biofilm-associated wound infections. The combination of the dorsal skinfold chamber model with a sustained insulin treatment has not been described so far. It allows a broad field of glucose and insulin dependent studies of infection.Einleitung: Patienten mit Diabetes mellitus leiden häufiger unter Biofilm-assoziierten Infekten als normoglykämische Patienten. Das vermehrte zeitgleiche Auftreten erhöhter Blutzuckerwerte und Biofilm-assoziierter Wundinfekte ist gut beschrieben; der dieser erhöhten Infektvulnerabilität zugrundeliegende Pathomechanismus ist allerdings bisher nicht abschließend erforscht. Um dieses Forschungsfeld künftig tiefergehend zu studieren, haben wir in unserem Labor ein neues Tiermodel zur Untersuchung der Biofilmbildung in diabetischen Mäusen unter einer kontrollierten Insulinbehandlung etabliert. Material und Methoden: 16 Wochen alten BKS.Cg-Dock7m +/+ Leprdb/J Mäusen wurde in einem Rückenhautkammermodell eine dermale Wunde gesetzt. Diese Wunden wurden mit Staphylococcus aureus ATCC 49230 (106 Zellen/mL) infiziert. Zeitgleich wurden den Tieren je nach Versuchsgruppe (je N=5) entweder Insulin verabreichende subkutane Implantate (LinShin Canada Inc., Toronto, Canada) oder wirkstofffreie Implantate appliziert. Die Tiere lebten insgesamt 6 Tage. Täglich wurden das Gewicht, die Temperatur und Blutzuckerwerte der Tiere bestimmt. Nach 6 Tagen wurden Gewebeproben jeweils für Fluoreszenz-in-situ -Hybridisierung, CFU und immunhistochemische Färbungen gewonnen. Die Versuche sind entsprechend der Tierversuchsordnung des Landes Sachsen durchgeführt worden (TVV05/19).Ergebnisse: Wir konnten ein neuartiges zuverlässiges Modell zur Untersuchung der Insulintherapie auf die Ausbildung Biofilm-assoziierter Wunden in diabetischen Mäusen etablieren. Die Insulinpumpentherapie konnte eine Reduktion der Blutzuckerwerte erreichen. Die Kombination des Rückenhautkammermodells, welches kontinuierliche In-vivo-Untersuchungen der Infektion erlaubt, mit Insulinimplantaten ist ein für die diabetischen Mäuse gut tolerierbares Modell.Diskussion: Wir haben ein neuartiges Modell zur Untersuchung des Zusammenhangs zwischen Insulin- und Blutzuckerwerten auf die Bildung von Biofilm-assoziierten Wundinfekten am diabetischen Tiermodell entwickelt. Dieses Modell eröffnet ein weites Spektrum an künftigen Forschungsfeldern

A Preliminary Study on Handling Uncertainty in Indicator-Based Multiobjective Optimization

Real-world optimization problems are often subject to uncertainties, which can arise regarding stochastic model parameters, objective functions and decision variables. These uncertainties can take di#erent forms in terms of distribution, bound and central tendency