Besteuerung von Ertrag und Umsatz im Electronic Commerce

Internet und Electronic Commerce haben zu weitreichenden Veränderungen des wirtschaftlichen Umfelds geführt: Virtuelle Güter und Dienstleistungen werden auf elektronischen, von geographischen und politischen Grenzen unabhängigen Märkten gehandelt, und Anonymität und Virtualität erschweren die Durchführung der Besteuerung, wenn die notwendigen subjektiven und objektiven Besteuerungsmerkmale nicht oder nur teilweise vorliegen. Während die beteiligten Staaten eine Erosion ihrer Steuerbasis befürchten, sehen sich die Unternehmen neuen Möglichkeiten der internationalen Steuerarbitrage gegenüber. Christoph Knödler analysiert, ob die Besteuerung des Electronic Commerce als eine spezifische Form der wirtschaftlichen Betätigung in den bestehenden steuerrechtlichen Rahmen integriert werden kann. Diskutiert werden sowohl ertrag- als auch umsatzsteuerliche Problemfelder. Der Schwerpunkt der Untersuchung liegt auf den Lösungsvorschlägen aus den Reihen der OECD und der Europäischen Union. Hierfür entwickelt der Autor einen Beurteilungsmaßstab, der neben dem Kriterium der Neutralität der Besteuerung auch die Aspekte der Gleichmäßigkeit der Besteuerung und der administrativen Eignung der entsprechenden Rechtsnormen einbezieht

Towards automated joining element design

Product variety and its induced manufacturing complexity remains to increase and therefore greatens challenges for design of joining elements. Historically, joining element design was a paper-based process with incomplete variety documentation and is digitalized only by replacing paper for 3D space. Currently, joining element design remains an ambiguous manual task with limited automation, resulting in long iterative, error prone development trajectories and costly reworks. Thus, processes in practice conflict with required capabilities. Artificial intelligence helps to solve such conflicts by taking over repetitive tasks, preventing human errors, optimizing designs and enabling designers to focus on their core competencies. This paper proposes a novel artificial intelligence method toolbox as a foundation to automate joining element design in manufacturing industries. The methodology aims to incorporate multiple lifecycle requirements including large product variety

Evaluation of Biomarkers for the Prediction of Venous Thromboembolism in Ambulatory Cancer Patients

Background: Venous thromboembolism (VTE) is a common complication of cancer. This study aimed to evaluate immature platelet fraction (IPF), mean platelet volume (MPV), P-selectin, D-dimer, and thrombin generation (TG) as predictive biomarkers for VTE and further the improvement of existing risk assessment models (RAMs). Methods: A prospective, observational, exploratory study was conducted on ambulatory cancer patients with indication for systemic chemotherapy. Baseline RAMs included the Khorana-, Vienna Cancer, Thrombosis-, Protecht-, ONKOTEV-, and Catscore. IPF, MPV, P-selectin, D-dimer, and TG were analysed at baseline and 3-month follow-up. Results: We enrolled 100 patients, of whom 89 completed the follow-up. Frequent tumour types were breast (30%), gastric (14%), gynaecological (14%), and colorectal (14%) cancer. Ten of the 89 patients (11.2%) developed VTE. The highest VTE rate was observed in patients with cholangiocarcinoma (3/5; 60%). Baseline D-dimer levels but not IPF, MPV, or P-selectin were associated with the risk of developing VTE (HR 6.9; p = 0.021). None of the RAMs showed statistical significance in predicting VTE. Peak thrombin and endogenous thrombin potential were lower in patients who developed VTE. Biomarker changes between baseline and follow-up were not associated with VTE risk. Conclusions: VTE risk was well predicted by baseline D-dimer levels. Adding D-dimer could improve existing RAMs to better identify patients who may benefit from primary VTE prophylaxis. The VTE risk among patients with cholangiocarcinoma should be further evaluate

Evaluation of Biomarkers for the Prediction of Venous Thromboembolism in Ambulatory Cancer Patients

Background: Venous thromboembolism (VTE) is a common complication of cancer. This study aimed to evaluate immature platelet fraction (IPF), mean platelet volume (MPV), P-selectin, D-dimer, and thrombin generation (TG) as predictive biomarkers for VTE and further the improvement of existing risk assessment models (RAMs). Methods: A prospective, observational, exploratory study was conducted on ambulatory cancer patients with indication for systemic chemotherapy. Baseline RAMs included the Khorana-, Vienna Cancer, Thrombosis-, Protecht-, ONKOTEV-, and Catscore. IPF, MPV, P-selectin, D-dimer, and TG were analysed at baseline and 3-month follow-up. Results: We enrolled 100 patients, of whom 89 completed the follow-up. Frequent tumour types were breast (30%), gastric (14%), gynaecological (14%), and colorectal (14%) cancer. Ten of the 89 patients (11.2%) developed VTE. The highest VTE rate was observed in patients with cholangiocarcinoma (3/5; 60%). Baseline D-dimer levels but not IPF, MPV, or P-selectin were associated with the risk of developing VTE (HR 6.9; p = 0.021). None of the RAMs showed statistical significance in predicting VTE. Peak thrombin and endogenous thrombin potential were lower in patients who developed VTE. Biomarker changes between baseline and follow-up were not associated with VTE risk. Conclusions: VTE risk was well predicted by baseline D-dimer levels. Adding D-dimer could improve existing RAMs to better identify patients who may benefit from primary VTE prophylaxis. The VTE risk among patients with cholangiocarcinoma should be further evaluate