In contrast to natural and historical diets of wild and domesticated ruminants, the diversity of plant species is limited in diets of modern dairy cows. Are “production diseases” linked to this? We conducted a trial to test the effects of a multicomponent herbal feed additive (HFA) on health, performance and fertility traits. A dose‐finding study (DF) with 62 cows on 11 commercial farms compared a low (50 g) and a high (100 g) dose of HFA (HFA‐50, HFA‐100) with a placebo (PL). In a subsequent field trial (FT) with 280 cows on 30 commercial farms, HFA‐100 was compared to PL. Cows were randomly assigned to HFA and PL groups and received HFA or PL individually daily from 14 days pre‐ to 300 days post‐calving. Data were analysed with mixed effects models. No differences between HFA and PL were found regarding performance, body condition score and overall culling rates. A tendency towards lower milk urea for HFA‐100 compared to PL (p = .06) was found in DF. HFA significantly reduced elevated milk acetone observations (≥10 mg/L) in the first 10 lactation weeks (HFA‐100: 4%; HFA‐50: 4%; PL: 12%) in DF. HFA‐50 significantly reduced lameness incidence (HFA‐100: 11%; HFA‐50: 2%; PL: 14%) in DF. Calving intervals were 15 days shorter in HFA compared to PL in both trials, which could be confirmed by tendency (p = .07) in FT. In both trials, the proportion of test days with elevated somatic cell score (≥3.0) was significantly lower in HFA compared to PL (DF: HFA‐100: 40%, HFA‐50: 45% and PL: 55%; FT: HFA‐100: 38% and PL: 55%) which is also reflected by tendency (p = .08) in lower culling rates due to udder diseases in FT. HFA showed no negative impact on any of the measured parameters. The effects of HFA indicate a potential of phytochemically rich and diverse feed additives for dairy cows' nutrition and physiology.

The doctoral workshop is one of the key elements in the IEEE E-TEMS conference series. The growing community is involving researchers in their very early stage of their research work. For that the conference offers a platform to present the topic, to discuss it, to receive feedback, to network, and to learn from the contribution of the whole conference. This report presents the concept and this year's elements. The main focus lies on the various topics of the presented doctoral works. A reflection of the participants is given in the last section.

The importance of human mobility analyses is growing in both research and practice, especially as applications for urban planning and mobility rely on them. Aggregate statistics and visualizations play an essential role as building blocks of data explorations and summary reports, the latter being increasingly released to third parties such as municipal administrations or in the context of citizen participation. However, such explorations already pose a threat to privacy as they reveal potentially sensitive location information, and thus should not be shared without further privacy measures.There is a substantial gap between state-of-the-art research on privacy methods and their utilization in practice. We thus conceptualize a standardized mobility report with differential privacy guarantees and implement it as open-source software to enable a privacy-preserving exploration of key aspects of mobility data in an easily accessible way. Moreover, we evaluate the benefits of limiting user contributions using three data sets relevant to research and practice. Our results show that even a strong limit on user contribution alters the original geospatial distribution only within a comparatively small range, while significantly reducing the error introduced by adding noise to achieve privacy guarantees.