Decentralized Exchanges: The Profitability Frontier of Constant Product Market Makers

In this paper we analyze constant product market makers (CPMMs). We formalize the liquidity providers' profitability conditions and introduce a concept we call the profitability frontier in the xyk-space. We study the effect of mint and burn fees on the profitability frontier, consider various pool types, and compile a large data set from all Uniswap V2 transactions. We use this data to further study our theoretical framework and the profitability conditions. We show how the profitability of liquidity provision is severely affected by the costs of mint and burn events relative to the portfolio size and the characteristics of the trading pair

Blockchain Vending Machine: A Smart Contract-Based Peer-to-Peer Marketplace for Physical Goods

In this paper, we propose an autonomous vending machine that is governed by a public Blockchain and smart contracts platform. Set up as a decentralized autonomous organization, it serves as an open marketplace for physical goods, where anyone can buy and/or sell objects. We propose a basic architecture for the machine, analyze pricing and fee mechanisms and examine potential pitfalls. Moreover, we discuss open issues, possible extensions and further areas for improvement. We conclude that the deployment of such machines could significantly improve our understanding of decentralized autonomous organizations and build a bridge between virtual and physical markets. Insights gained from such an experiment may raise important questions for further researc

Experimental approaches to understand the role of genetic and environmental influences on the microbial community associated with "Daphnia"

Every multicellular organism on this planet is associated with a diverse community of microorganisms referred to as its microbiota. In recent years, myriads of effects resulting from this interaction have been revealed. The series of experiments condensed in this thesis aimed at investigating this relationship in more detail in planktonic crustaceans from the genus Daphnia and in particular the water flea Daphnia magna. The findings from these experiments provide important basic knowledge essential for future host-microbiota related research in this system. Part one of the thesis comprises all experiments conducted by myself. In the first chapter I reciprocally transplanted the microbiota between the two species Daphnia magna and Daphnia pulex to examine the degree of specificity in these associations and determine the effects on host fitness as a consequence thereof. We found that being associated with a foreign microbial community did not negatively affect maturity, fecundity and size in both Daphnia species, letting us speculate that the two partners did not adapt to each other. This hypothesis was further supported by the insights gained when investigating the transmission of the whole microbial community, which was the purpose of the second chapter. Compositional comparisons between maternal and offspring microbiota revealed a stable fraction of microbes that gets transmitted, neither influenced by the origin nor the diversity of the microbial community. The third chapter of the thesis aimed at assessing the stability of the Daphnia-microbiota association and to what degree established microbial communities were still modifiable. We paired and raised juveniles from three different locations (Belgium, Germany and Switzerland) in a full factorial design and compared their microbiota. We found that the microbiota is easily modifiable and that microbial communities greatly influence each other’s composition. In addition, the results allowed the conclusion that the microbiota is not genetically controlled. We further investigated this in the fourth chapter dedicated to evaluate if the homozygosity level of the host influences microbial diversity by comparing the microbiota of selfed and outcrossed animals. From the results we conclude that the host genotype has little influence on the diversity of the microbiota. Taken together, these results suggest that although microbial communities play a crucial role in Daphnia, the two partners did not adapt to one another leading us to propose a scenario of how transmission in the Daphnia-microbiota association might take place. Part two of the thesis encompasses work resulting from collaborations. In chapter five, Alexandra Mushegian tested the role of bacteria for animal functioning, showing a positive effect on embryonic development under warm temperature conditions. The goal of the last chapter, conducted by Karen Sullam, was to investigate the effect of temperature, host clone, and their interaction on host-associated microbiota. The experiment showed that the interaction of the factors affected microbial community structure while their diversity was more affected by host clonal background

Natürlich – holzbasierte Schäume

Für Anwendungen im Dämmstoff- und Struktur- schaumbereich entwickelt das Institut für Werkstoff und Holztechnologie IWH der BFH holzbasierte Hartschäume. Neben einer Erhöhung des Anteils nachhaltig gewonnener und biobasierter Grundstoffe bei der Schaumherstellung stehen eine Senkung der Herstellkosten und eine Verbesserung des Brand- widerstands der Schäume im Fokus

Temperature-dependent benefits of bacterial exposure in embryonic development of Daphnia magna resting eggs

The environments in which animals develop and evolve are profoundly shaped by bacteria, which affect animals both indirectly through their role in biogeochemical processes and directly through antagonistic or beneficial interactions. The outcomes of these activities can differ according to environmental context. In a series of laboratory experiments with diapausing eggs of the water flea Daphnia magna, we manipulated two environmental parameters, temperature and presence of bacteria, and examined their effect on development. At elevated temperatures (≥ 26 °C), resting eggs developing without live bacteria had reduced hatching success and correspondingly higher rates of severe morphological abnormalities compared with eggs with bacteria in their environment. The beneficial effect of bacteria was strongly reduced at 20 °C. Neither temperature nor the presence of bacteria affected directly developing parthenogenetic eggs. The mechanistic basis of this effect of bacteria on development is unclear, but these results highlight the complex interplay of biotic and abiotic factors influencing animal development after diapause

Resource use and outcome in critically ill patients with hematological malignancy: a retrospective cohort study

INTRODUCTION: The paucity of data on resource use in critically ill patients with hematological malignancy and on these patients' perceived poor outcome can lead to uncertainty over the extent to which intensive care treatment is appropriate. The aim of the present study was to assess the amount of intensive care resources needed for, and the effect of treatment of, hemato-oncological patients in the intensive care unit (ICU) in comparison with a nononcological patient population with a similar degree of organ dysfunction. METHODS: A retrospective cohort study of 101 ICU admissions of 84 consecutive hemato-oncological patients and 3,808 ICU admissions of 3,478 nononcological patients over a period of 4 years was performed. RESULTS: As assessed by Therapeutic Intervention Scoring System points, resource use was higher in hemato-oncological patients than in nononcological patients (median (interquartile range), 214 (102 to 642) versus 95 (54 to 224), P < 0.0001). Severity of disease at ICU admission was a less important predictor of ICU resource use than necessity for specific treatment modalities. Hemato-oncological patients and nononcological patients with similar admission Simplified Acute Physiology Score scores had the same ICU mortality. In hemato-oncological patients, improvement of organ function within the first 48 hours of the ICU stay was the best predictor of 28-day survival. CONCLUSION: The presence of a hemato-oncological disease per se is associated with higher ICU resource use, but not with increased mortality. If withdrawal of treatment is considered, this decision should not be based on admission parameters but rather on the evolutional changes in organ dysfunctions

Blockchain: Disrupting the Renewable Energy Landscape

This study, performed by SUSI Partners AG in cooperation with the Center for Innovative Finance of the University of Basel, provides an overview of the applications of blockchain technology in the field of renewable energies. We show that the use of blockchain technology can generate new and promising approaches for solutions to the current challenges facing the electricity and energy market. The most important insights of the study are summarized in the following four points: - This white paper identifies 14 use cases of blockchain technology in the area of renewable energies and divides them into five categories. - Some of the applications have a disruptive character and could thus result in great changes in the respective area. In particular peer-to-peer (P2P) electricity trading but also applications in the field of "asset management &amp; operations" fall into this category. - Other areas of application can also be used in today's system. In this way, possible efficiency increases could be achieved primarily in the areas "asset transparency" and "grid operations". - The market overview (Chapter 4.2) shows a great interest in the potential applications of blockchain in the energy market. New blockchain start-ups and established companies are already active on the market. Since blockchain technology is very young, only few of the use cases have been able to reach market maturity at this point. One also has to consider that a regulatory framework still has to be created for the comprehensive use of blockchain technology in the energy market. However, this study illustrates the versatile potential of blockchain technology in the different areas, in order to facilitate the early positioning of all involved actors. It makes sense for investors to study this topic now - blockchain represents a key technology similar to the internet and will replace or at least alter existing business models

Blockchain Vending Machine: A Smart Contract-Based Peer-to-Peer Marketplace for Physical Goods

In this paper, we propose an autonomous vending machine that is governed by a public Blockchain and smart contracts platform. Set up as a decentralized autonomous organization, it serves as an open marketplace for physical goods, where anyone can buy and/or sell objects. We propose a basic architecture for the machine, analyze pricing and fee mechanisms and examine potential pitfalls. Moreover, we discuss open issues, possible extensions and further areas for improvement. We conclude that the deployment of such machines could significantly improve our understanding of decentralized autonomous organizations and build a bridge between virtual and physical markets. Insights gained from such an experiment may raise important questions for further research

Alpine snow cover in a changing climate: a regional climate model perspective

An analysis is presented of an ensemble of regional climate model (RCM) experiments from the ENSEMBLES project in terms of mean winter snow water equivalent (SWE), the seasonal evolution of snow cover, and the duration of the continuous snow cover season in the European Alps. Two sets of simulations are considered, one driven by GCMs assuming the SRES A1B greenhouse gas scenario for the period 1951-2099, and the other by the ERA-40 reanalysis for the recent past. The simulated SWE for Switzerland for the winters 1971-2000 is validated against an observational data set derived from daily snow depth measurements. Model validation shows that the RCMs are capable of simulating the general spatial and seasonal variability of Alpine snow cover, but generally underestimate snow at elevations below 1,000m and overestimate snow above 1,500m. Model biases in snow cover can partly be related to biases in the atmospheric forcing. The analysis of climate projections for the twenty first century reveals high inter-model agreement on the following points: The strongest relative reduction in winter mean SWE is found below 1,500m, amounting to 40-80% by mid century relative to 1971-2000 and depending upon the model considered. At these elevations, mean winter temperatures are close to the melting point. At higher elevations the decrease of mean winter SWE is less pronounced but still a robust feature. For instance, at elevations of 2,000-2,500m, SWE reductions amount to 10-60% by mid century and to 30-80% by the end of the century. The duration of the continuous snow cover season shows an asymmetric reduction with strongest shortening in springtime when ablation is the dominant factor for changes in SWE. We also find a substantial ensemble-mean reduction of snow reliability relevant to winter tourism at elevations below about 1,800m by mid century, and at elevations below about 2,000m by the end of the centur

Statistical learning and big data applications

The amount of data generated in the field of laboratory medicine has grown to an extent that conventional laboratory information systems (LISs) are struggling to manage and analyze this complex, entangled information (“Big Data”). Statistical learning, a generalized framework from machine learning (ML) and artificial intelligence (AI) is predestined for processing “Big Data” and holds the potential to revolutionize the field of laboratory medicine. Personalized medicine may in particular benefit from AI-based systems, especially when coupled with readily available wearables and smartphones which can collect health data from individual patients and offer new, cost-effective access routes to healthcare for patients worldwide. The amount of personal data collected, however, also raises concerns about patient-privacy and calls for clear ethical guidelines for “Big Data” research, including rigorous quality checks of data and algorithms to eliminate underlying bias and enable transparency. Likewise, novel federated privacy-preserving data processing approaches may reduce the need for centralized data storage. Generative AI-systems including large language models such as ChatGPT currently enter the stage to reshape clinical research, clinical decision-support systems, and healthcare delivery. In our opinion, AI-based systems have a tremendous potential to transform laboratory medicine, however, their opportunities should be weighed against the risks carefully. Despite all enthusiasm, we advocate for stringent added-value assessments, just as for any new drug or treatment. Human experts should carefully validate AI-based systems, including patient-privacy protection, to ensure quality, transparency, and public acceptance. In this opinion paper, data prerequisites, recent developments, chances, and limitations of statistical learning approaches are highlighted