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Förderung der KI-Kompetenz bei Studierenden ohne Vorkenntnisse in Informatik und Programmierung
No full textDas Mechanische Neuronale Netz (MNN) ist ein physikalisches Modell eines Künstlichen Neuronalen Netzes (KNN), das die Bauteile und Funktionen eines KNN physikalisch greifbar macht. Mit dem MNN können SchülerInnen und Studierende eine der Grundlagen der Künstlichen Intelligenz (KI) einfach verstehen, ohne auf Programmierkenntnisse oder Computer angewiesen zu sein. Studien ergaben, dass sowohl der objektive als auch der subjektive Lernerfolg sowie die Zufriedenheit mit dem MNN im Vergleich zu herkömmlichen Methoden höher ist. Dabei verfolgt das MNN einen Bottom-up- Ansatz, bei dem die Grundbausteine wie die Neuronen und ihre Verbindungen und ihre Zusammenstellung zu einem Gesamtnetz erklärt werden. Darauf können mit dem MNN logische Probleme gelernt und gelöst werden. In dieser Arbeit wird aufgezeigt, wie die Brücke zu echten KNN geschlagen werden kann, indem ein Klassifikationsproblem, die Erkennung von Hunderassen, zuerst mit dem MNN und danach mit einem KNN gelöst wird. Während das MNN auf Merkmalen, wie Kopfform und Größe, operiert, nutzt das KNN Bilder. Somit ist es für die SchülerInnen und Studierenden möglich, eine Brücke zwischen den Grundbausteinen der KI, die mit dem MNN erklärt werden und echten Problemen, die heutzutage mit einer KI gelöst werden, wie beispielsweise der Bildklassifikation, zu schlagen
The Iron Quest : Unraveling Distribution and Bioavailability in Biofortified Vegetables
No full textInsufficient absorption of nutritional iron is the primary cause of the most widespread dietary micronutrient deficiency worldwide. This deficiency disproportionately affects women and is the leading cause of anaemia (iron deficiency anaemia) on a global scale. These facts highlight the importance of dietary iron for the human body, with a daily requirement ranging from 11 to 27 mg Fe for adults, depending on sex, pregnancy, and nursing status. In Germany, consumers have relatively easy access to ferrous or ferric supplements as well as iron-fortified foods. However, iron-biofortified food products are not yet available, and only 18% of German consumers are familiar with the label "biofortified food".
To address this issue, the BMBF-funded research project EiBiG was initiated. Its goal is to establish plant cultivation methods that enhance the iron content in plants through foliar iron fertilization while also improving iron bioavailability in vitamin C-rich vegetables, such as baby-leaf spinach and bell pepper. Iron bioavailability will be analyzed using combined in vitro digestion and Caco-2 cell culture models. Additionally, to gain insights into foliar iron absorption mechanisms, the spatial distribution of iron in biofortified and non-biofortified baby-leaf spinach will be investigated using techniques such as LIBS, μXRF, and LA-ICP-MS
BIM - based Applications for Construction Permits Considering Open Space
No full textA modeling guideline for BIM model outdoor facilities was developed for the BIM-based building application use case. This serves as a basis for the development of principles and procedures for the automated review of building regulation requirements with BIM-based review tools. Testing and validation were carried out using two practical example projects. The focus was also on integration into a coordination model
Impact of mechanical weed control on soil N dynamics, soil moisture, and crop yield in an organic cropping sequence
No full textMechanical weed control is a major element of weed suppression in organic farming systems. In addition to the direct effect on weed growth, mechanical weeding, such as harrowing or hoeing, is known to induce side effects on several soil- and crop-related properties. In this study, we investigated the impact of mechanical weeding on soil mineral nitrogen (SMN), soil moisture, and crop yield in an organic crop rotation of grass-clover (Lolium multiflorumLam., Trifolium pratense L.), silage maize (Zea mays L.) and winter barley (Hordeum vulgare L.). The experiment was conducted in two consecutive years (2021, 2022), where each crop was grown in each year on a Plaggic Anthrosol with sandy loam in North-West Germany. Two weed control treatments (mechanical: harrowing, hoeing; chemical: herbicide application) were implemented in a randomized block design with four replications. Greater net nitrogen (N) mineralization in maize compared to winter barley were attributed to the incorporation of grass-clover residues before sowing of maize and greater mineralization potential during the maize growing season. Higher weed growth in maize after mechanical weeding resulted in a reduction of up to 47% in SMN content in the topsoil. In barley, no differences in weed suppression were observed between the treatments and only small effects on SMN were determined after mechanical weeding. The soil water content in the mechanically weeded plots was significantly higher at several events in both years and for both crops, which was attributed to increased water infiltration by disrupting the soil crust. Neither crop yield nor N uptake in harvest products was affected by the different treatments
