Reduction of Protein Levels in Broiler Feed for Commercial Application – A German Case

A project was initiated to apply dietary CP reduction under commercial conditions. The main objective was to demonstrate and validate that dietary CP can be reduced without compromising broiler performance in a production system which is already rather efficient. In addition, we wanted to demonstrate the potential of dietary CP reduction on reducing N-excretions especially in the context of German revised regulations and monitoring attempts. Finally, as previous research suggested, few further aspects such as impact of dietary CP reduction on litter quality and quantity, footpad health, change of ingredient inclusion levels and related impact on sustainability impact factors were evaluated

Top-Down Influence? Predicting CEO Personality and Risk Impact from Speech Transcripts

How much does a CEO’s personality impact the performanceof their company? Management theory posits a great influence, but it is difficult to show empirically—there is a lack of publicly available self-reported personality data of top managers. Instead, we propose a text-based personality regressor based on crowd-sourced Myers–Briggs Type Indicator (MBTI) assessments. The ratings have a high internal and external validity and can be predicted with moderate to strong correlations for three out of four dimensions. Providing evidence for the upper echelons theory, we demonstrate that the predicted CEO personalities have explanatory power of financial risk

Auswirkungen einer Rohprotein- reduzierten Fütterung auf die betrieblichen Stoffstrombilanzen und Nachhaltigkeitsparameter bei Broilern

Auf Basis von drei Proteinabsenkungsversuchen auf einem Praxisbetrieb in Nord-West Deutschland und einem in einem Versuchsstall wurden die Auswirkungen dieser Fütterung auf betriebliche N-Bilanzen und ausgewählte Nachhaltigkeitsparameter betrachtet. Die N-Reduktion in den jeweiligen Versuchsgruppen hatte keine Verringerung des N-Überschusses zur Folge. Die N-Ausscheidungen konnten in allen 4 Projekten deutlich reduziert werden und sie unterschieden sich signifikant voneinander. Die N-Effizienz verbesserte sich ebenfalls signifikant. Bei den Klimabilanzen entscheidet alleinig die Herkunft des Sojaextraktionsschrotes (Nord- oder Südamerika) ob der Einsatz einer stark N-reduzierten Fütterung sinnvoll ist oder nicht. Eine generelle Verbesserung der Klimabilanz durch Einsparung von Sojaschrot konnte nicht belegt werden

Evaluating the impact of AI-based priced parking with social simulation

Across the world, increasing numbers of cars in urban centers lead to congestion and adverse effects on public health as well as municipal climate goals. Reflecting cities’ ambitions to mitigate these issues, a growing body of research evaluates the use of innovative pricing strategies for parking, such as Dynamic Pricing (DP), to efficiently manage parking supply and demand. We contribute to this research by exploring the effects of Reinforcement Learning (RL)-based DP on urban parking. In particular, we introduce a theoretical framework for AI-based priced parking under traffic and social constraints. Furthermore, we present a portable and generalizable Agent-Based Model (ABM) for priced parking to evaluate our approach and run extensive experiments comparing the effect of several learners on different urban policy goals. We find that (1) outcomes are highly sensitive to the employed reward function; (2) trade-offs between different goals are challenging to balance; (3) single-reward functions may have unintended consequences on other policy areas (e.g., optimizing occupancy punishes low-income individuals disproportionately). In summary, our observations stress that fair DP schemes need to account for social policy measures beyond traffic parameters such as occupancy or traffic flow