Basket trial designs based on power priors

In basket trials a treatment is investigated in several subgroups. They are primarily used in oncology in early clinical phases as single-arm trials with a binary endpoint. For their analysis primarily Bayesian methods have been suggested, as they allow partial sharing of information based on the observed similarity between subgroups. Fujikawa et al. (2020) suggested an approach using empirical Bayes methods that allows flexible sharing based on easily interpreteable weights derived from the Jensen-Shannon divergence between the subgroupwise posterior distributions. We show that this design is closely related to the method of power priors and investigate several modifications of Fujikawa's design using methods from the power prior literature. While in Fujikawa's design, the amount of information that is shared between two baskets is only determined by their pairwise similarity, we also discuss extensions where the outcomes of all baskets are considered in the computation of the sharing-weights. The results of our comparison study show that the power prior design has compareable performance to fully Bayesian designs in a range of different scenarios. At the same time, the power prior design is computationally cheap and even allows analytical computation of operating characteristics in some settings

An AI formalization of Betty the Crow's sequential geometric tool use

Betty The Crow was a new caledonian crow that, in the lab of Alex Kacelnik, demonstrated surprising skill in sequentially using tools to reach for other tools to reach for a reward. The goal of this work is to find an AI formalization of such behaviour that combines reasoning over a sequence of first-order logic decision variables as well as over the geometric path to execute the reaching and tool use motions. For that, we first consider the general area of Task And Motion Planning problems; we use an approach of decomposing the problem into smaller ones solvable by (existing, blackbox) modules; we test a simple implementation of the resulting method on some small problem instances.Betty die Krähe war eine Neukaledonienkrähe, die in Versuchen Alex Kacelniks erstaunliche Fähigkeiten zeigte, sequenziell Werkzeuge zu benutzen, um an andere Werkzeuge heranzukommen, um eine Belohnung zu erreichen. Das Ziel dieser Arbeit ist es, eine KI Formalisierung solchen Verhaltens zu finden, die Überlegungen über eine Sequenz von prädikatenlogischen Entscheidungsvariablen sowie über den geometrischen Pfad um die Greifund Werkzeugnutzungsbewegungen auszuführen kombiniert. Dazu betrachten wir zunächst das allgemeine Gebiet von Task And Motion Planning Problemen; wir benutzen einen Ansatz, das Problem in kleinere, von (existierenden, Blackbox) Modulen lösbare, zu zerlegen; und wir testen eine einfache Implementierung des resultierenden Verfahrens an einigen kleinen Probleminstanzen

FlexEnergy - A Prosumer-based Approach For The Automated Marketing Of Manufacturing Companies' Energy Flexibility

The transition to renewable energy sources and the need to address climate change has significantly changed the energy landscape. However, the fluctuating nature of renewables and increased electricity price volatility pose challenges to power grids and companies. This study focuses on energy flexibility achieved through industrial demand-side management (DSM) as a solution. Information technology (IT) and standardization are vital for enabling energy flexibility by optimizing energy consumption and facilitating interoperability. Digital energy platforms allow energy-intensive industries to optimize energy usage, thus enabling industrial demand optimization and effective communication within the energy ecosystem. Standardization ensures the efficient implementation of energy flexibilitymeasures across diverse energymarkets.Thisstudy proposes a process model to streamline the integration of energy flexibility measures into production processes. This model eliminates the labor-intensive manual implementation process, enabling seamless adoption of energy flexibility measures and participation in energy markets. Marketing energy flexibility is addressed through the prosumer-based process that leverages standardized communication facilitated by the energy flexibility data model (EFDM), optimizing the energy consumption of manufacturing companies. The contributions of this research lie in the proposed processmodelfor marketing energy flexibility,streamlining energy flexibility implementation through automated EFDM modeling. The findings provide insights for researchers and practitioners, guiding the adoption of energy flexibility measures and supporting a sustainable energy future

SMAuC -- The Scientific Multi-Authorship Corpus

With an ever-growing number of new publications each day, scientific writing poses an interesting domain for authorship analysis of both single-author and multi-author documents. Unfortunately, most existing corpora lack either material from the science domain or the required metadata. Hence, we present SMAuC, a new metadata-rich corpus designed specifically for authorship analysis in scientific writing. With more than three million publications from various scientific disciplines, SMAuC is the largest openly available corpus for authorship analysis to date. It combines a wide and diverse range of scientific texts from the humanities and natural sciences with rich and curated metadata, including unique and carefully disambiguated author IDs. We hope SMAuC will contribute significantly to advancing the field of authorship analysis in the science domain

How Sustainable is Machine Learning in Energy Applications? – The Sustainable Machine Learning Balance Sheet

Information Systems play a central role in the energy sector for achieving climate targets. With increasing digitization and data availability in the energy sector, data-driven machine learning (ML) approaches emerged, showing high potential. So far, research has focused on optimizing ML approaches’ prediction performance. However, this is a one-sided perspective. ML approaches require large computation times and capacities leading to high energy consumption. With the goal of sustainable energy systems, research on ML approaches should be extended to include the application’s energy consumption. ML solutions must be designed in such a way that the resulting savings in energy (and emissions) are greater than the energy consumption caused using the ML solution. To address this need, we develop the Sustainable Machine Learning Balance Sheet as a framework allowing to holistically evaluate and develop sustainable ML solutions which we validated in a case study and through expert interviews

Deriving Digital Energy Platform Archetypes for Manufacturing – A Data-Driven Clustering Approach

External factors such as climate change and the current energy crisis due to global conflicts are leading to the increasing relevance of energy consumption and energy procurement in the manufacturing industry. In addition to the growing call for sustainability, companies are increasingly struggling with rising energy costs and the reliability of the power grid, which endangers the competitiveness of companies and regions affected by high energy prices. Appropriate measures for energy-efficient and, not least, energy-flexible production are necessary. In addition to innovations and optimizations of plants and processes, digital energy platforms for the visualization, analysis, optimization, and control of energy flows are becoming essential. Over time, several digital energy platforms emerged on the market. The number and the different functionalities of the platforms make it challenging for classic manufacturing companies to keep track and select the right digital energy platform. In literature, the characteristics and functionalities of digital energy platforms have already been identified and structured. However, a classification of existing platforms into archetypes makes it easier for companies to select the platforms providing the missing functionality. To tackle this issue, we conducted an explorative and data-driven cluster analysis based on 49 existing digital energy platforms to identify digital energy platform archetypes and derive implications for research and practice. The results show five different archetypes that differ primarily in terms of functionalities on energy market integration. The identified archetypes provide a well-founded overview of the similarities and differences of digital energy platforms. Decision makers in manufacturing companies will benefit from the archetypes in future analyses as decision support in procurement processes and modifications of digital energy platforms

COx_{x} Fixation to Elementary Building Blocks: Anaerobic Syngas Fermentation vs. Chemical Catalysis

Heterogeneous catalysis and anaerobic syngas fermentation represent two different approaches for the conversion of synthesis gas into chemicals and fuels. This review provides a unique comparison of different reaction paths for the fixation of CO$_{2}$, CO and H$_{2}$ into elementary building blocks such as methanol, acetic acid and ethanol. Operating conditions, reactor engineering, influence of gas impurities, yields, conversion efficiencies as well as downstream product recovery are compared. It was found that mass-specific productivity ranges in the same order of magnitude for both technologies, while space-time yield of heterogeneous catalysis is up to three orders of magnitude higher

Application of an artificial intelligence-based tool in [18F]FDG PET/CT for the assessment of bone marrow involvement in multiple myeloma

Purpose: [18F]FDG PET/CT is an imaging modality of high performance in multiple myeloma (MM). Nevertheless, the inter-observer reproducibility in PET/CT scan interpretation may be hampered by the different patterns of bone marrow (BM) infiltration in the disease. Although many approaches have been recently developed to address the issue of standardization, none can yet be considered a standard method in the interpretation of PET/CT. We herein aim to validate a novel three-dimensional deep learning-based tool on PET/CT images for automated assessment of the intensity of BM metabolism in MM patients. Materials and methods: Whole-body [18F]FDG PET/CT scans of 35 consecutive, previously untreated MM patients were studied. All patients were investigated in the context of an open-label, multicenter, randomized, active-controlled, phase 3 trial (GMMG-HD7). Qualitative (visual) analysis classified the PET/CT scans into three groups based on the presence and number of focal [18F]FDG-avid lesions as well as the degree of diffuse [18F]FDG uptake in the BM. The proposed automated method for BM metabolism assessment is based on an initial CT-based segmentation of the skeleton, its transfer to the SUV PET images, the subsequent application of different SUV thresholds, and refinement of the resulting regions using postprocessing. In the present analysis, six different SUV thresholds (Approaches 1–6) were applied for the definition of pathological tracer uptake in the skeleton [Approach 1: liver SUVmedian 7 1.1 (axial skeleton), gluteal muscles SUVmedian 7 4 (extremities). Approach 2: liver SUVmedian 7 1.5 (axial skeleton), gluteal muscles SUVmedian 7 4 (extremities). Approach 3: liver SUVmedian 7 2 (axial skeleton), gluteal muscles SUVmedian 7 4 (extremities). Approach 4: ≥ 2.5. Approach 5: ≥ 2.5 (axial skeleton), ≥ 2.0 (extremities). Approach 6: SUVmax liver]. Using the resulting masks, subsequent calculations of the whole-body metabolic tumor volume (MTV) and total lesion glycolysis (TLG) in each patient were performed. A correlation analysis was performed between the automated PET values and the results of the visual PET/CT analysis as well as the histopathological, cytogenetical, and clinical data of the patients. Results: BM segmentation and calculation of MTV and TLG after the application of the deep learning tool were feasible in all patients. A significant positive correlation (p < 0.05) was observed between the results of the visual analysis of the PET/CT scans for the three patient groups and the MTV and TLG values after the employment of all six [18F]FDG uptake thresholds. In addition, there were significant differences between the three patient groups with regard to their MTV and TLG values for all applied thresholds of pathological tracer uptake. Furthermore, we could demonstrate a significant, moderate, positive correlation of BM plasma cell infiltration and plasma levels of β2-microglobulin with the automated quantitative PET/CT parameters MTV and TLG after utilization of Approaches 1, 2, 4, and 5. Conclusions: The automated, volumetric, whole-body PET/CT assessment of the BM metabolic activity in MM is feasible with the herein applied method and correlates with clinically relevant parameters in the disease. This methodology offers a potentially reliable tool in the direction of optimization and standardization of PET/CT interpretation in MM. Based on the present promising findings, the deep learning-based approach will be further evaluated in future prospective studies with larger patient cohorts

Agriculture in the Face of Changing Markets, Institutions and Policies: Challenges and Strategies

Since the late 1980s, agriculture in Central and Eastern European Countries (CEECs) has been under considerable adjustment pressure due to changing political, economic and institutional environments. These changes have been linked to the transition process, as well as the ongoing integration into the European Union and the world market. Reduced subsidies, increased environmental and food quality demands, as well as structural changes in the supply, processing and food retailing sector call for major structural adjustments and the improvement of farmersâ managerial abilities. Though such changes always carry significant threats to farms, they also offer new opportunities for the farms' entrepreneurial engagement. Upcoming changes in the agricultural environment and their possible consequences for farm structures across Europe are thus still timely subjects. The objective of the IAMO Forum 2006 is to contribute to the success of agriculture in the CEECs, as well as their neighboring countries, in todayâs increasingly competitive environment. Concrete questions the conference focuses on are: What are the most suitable farm organizations, cooperative arrangements and contractual forms? How to improve efficiency and productivity? Where do market niches lie and what are the new product demands? This book contains 33 invited and selected contributions. These papers will be presented at the IAMO Forum 2006 in order to offer a platform for scientists, practitioners and policy-makers to discuss challenges and potential strategies at the farm, value chain, rural society and policy levels in order to cope with the upcoming challenges. IAMO Forum 2006, as well as this book, would not have been possible without the engagement of many people and institutions. We thank the authors of the submitted abstracts and papers, as well as the referees, for their evaluation of the abstracts from which the papers were selected. In particular, we would like to express our thanks to OLIVER JUNGKLAUS, GABRIELE MEWES, KLAUS REINSBERG and ANGELA SCHOLZ, who significantly contributed to the organization of the Forum. Furthermore, our thanks goes to SILKE SCHARF for her work on the layout and editing support of this book, and to JIM CURTISS, JAMIE BULLOCH, and DÃNALL Ã MEARÃIN for their English proof-reading. As experience from previous years documents, the course of the IAMO Forum continues to profit from the support and engagement of the IAMO administration, which we gratefully acknowledge. Last but not least, we are very grateful to the Robert Bosch Foundation, the Federal Ministry of Nutrition, Agriculture and Consumer Protection (BMELV), the German Research Foundation (DFG), the Haniel Foundation and the Leibniz Institute of Agricultural Development in Central and Eastern Europe (IAMO) for their respective financial support.Agribusiness, Community/Rural/Urban Development, Farm Management, Industrial Organization, International Development, Labor and Human Capital, Land Economics/Use, Productivity Analysis,