We studied the development of cognitive abilities related to intelligence and creativity (N = 48, 6–10 years old), using a longitudinal design (over one school year), in order to evaluate an Enrichment Program for gifted primary school children initiated by the government of the German federal state of Rhineland-Palatinate (Entdeckertag Rheinland Pfalz, Germany; ET; Day of Discoverers). A group of German primary school children (N = 24), identified earlier as intellectually gifted and selected to join the ET program was compared to a gender-, class- and IQ- matched group of control children that did not participate in this program. All participants performed the Standard Progressive Matrices (SPM) test, which measures intelligence in well-defined problem space; the Creative Reasoning Task (CRT), which measures intelligence in ill-defined problem space; and the test of creative thinking-drawing production (TCT-DP), which measures creativity, also in ill-defined problem space. Results revealed that problem space matters: the ET program is effective only for the improvement of intelligence operating in well-defined problem space. An effect was found for intelligence as measured by SPM only, but neither for intelligence operating in ill-defined problem space (CRT) nor for creativity (TCT-DP). This suggests that, depending on the type of problem spaces presented, different cognitive abilities are elicited in the same child. Therefore, enrichment programs for gifted, but also for children attending traditional schools, should provide opportunities to develop cognitive abilities related to intelligence, operating in both well- and ill-defined problem spaces, and to creativity in a parallel, using an interactive approach.

Areal optical surface topography measurement is an emerging technology for industrial quality control. However, neither calibration procedures nor the utilization of material measures are standardized. State of the art is the calibration of a set of metrological characteristics with multiple calibration samples (material measures). Here, we propose a new calibration sample (artefact) capable of providing the entire set of relevant metrological characteristics within only one single sample. Our calibration artefact features multiple material measures and is manufactured with two-photon laser lithography (direct laser writing, DLW). This enables a holistic calibration of areal topography measuring instruments with only one series of measurements and without changing the sample.

Ecophysiological characterizations of photoautotrophic communities are not only necessary to identify the response of carbon fixation related to different climatic factors, but also to evaluate risks connected to changing environments. In biological soil crusts (BSCs), the description of ecophysiological features is difficult, due to the high variability in taxonomic composition and variable methodologies applied. Especially for BSCs in early successional stages, the available datasets are rare or focused on individual constituents, although these crusts may represent the only photoautotrophic component in many heavily disturbed ruderal areas, such as parking lots or building areas with increasing surface area worldwide. We analyzed the response of photosynthesis and respiration to changing BSC water contents (WCs), temperature and light in two early successional BSCs. We investigated whether the response of these parameters was different between intact BSC and the isolated dominating components. BSCs dominated by the cyanobacterium Nostoc commune and dominated by the green alga Zygogonium ericetorum were examined. A major divergence between the two BSCs was their absolute carbon fixation rate on a chlorophyll basis, which was significantly higher for the cyanobacterial crust. Nevertheless, independent of species composition, both crust types and their isolated organisms had convergent features such as high light acclimatization and a minor and very late-occurring depression in carbon uptake at water suprasaturation. This particular setup of ecophysiological features may enable these communities to cope with a high variety of climatic stresses and may therefore be a reason for their success in heavily disturbed areas with ongoing human impact. However, the shape of the response was different for intact BSC compared to separated organisms, especially in absolute net photosynthesis (NP) rates. This emphasizes the importance of measuring intact BSCs under natural conditions for collecting reliable data for meaningful analysis of BSC ecosystem services.

Motivation: Mathematical models take an important place in science and engineering. A model can help scientists to explain dynamic behavior of a system and to understand the functionality of system components. Since length of a time series and number of replicates is limited by the cost of experiments, Boolean networks as a structurally simple and parameter-free logical model for gene regulatory networks have attracted interests of many scientists. In order to fit into the biological contexts and to lower the data requirements, biological prior knowledge is taken into consideration during the inference procedure. In the literature, the existing identification approaches can only deal with a subset of possible types of prior knowledge. Results: We propose a new approach to identify Boolean networks fromtime series data incorporating prior knowledge, such as partial network structure, canalizing property, positive and negative unateness. Using vector form of Boolean variables and applying a generalized matrix multiplication called the semi-tensor product (STP), each Boolean function can be equivalently converted into a matrix expression. Based on this, the identification problem is reformulated as an integer linear programming problem to reveal the system matrix of Boolean model in a computationally efficient way, whose dynamics are consistent with the important dynamics captured in the data. By using prior knowledge the number of candidate functions can be reduced during the inference. Hence, identification incorporating prior knowledge is especially suitable for the case of small size time series data and data without sufficient stimuli. The proposed approach is illustrated with the help of a biological model of the network of oxidative stress response. Conclusions: The combination of efficient reformulation of the identification problem with the possibility to incorporate various types of prior knowledge enables the application of computational model inference to systems with limited amount of time series data. The general applicability of thismethodological approachmakes it suitable for a variety of biological systems and of general interest for biological and medical research.

Durch die stetige Zunahme von dezentralen Erzeugungsanlagen, den anstehenden Smart-Meter Rollout sowie die zu erwartende Elektrifizierung des Verkehrssektors (E-Mobilität) steht die Netzplanung und Netzbetriebsführung von Niederspannungsnetzen (NS-Netzen) in Deutschland vor großen Herausforderungen. In den letzten Jahren wurden daher viele Studien, Forschungs- und Demonstrationsprojekte zu den oben genannten Themen durchge-führt und die Ergebnisse sowie die entwickelten Methoden publiziert. Jedoch lassen sich die publizierten Methoden meist nicht nachbilden bzw. validieren, da die Untersuchungsmodelle oder die angesetzten Szenarien für Dritte nicht nachvollziehbar sind. Es fehlen einheitliche Netzmodelle, die die deutschen NS-Netze abbilden und für Ver-gleichsuntersuchungen herangezogen werden können, ähnlich dem Beispiel der nordamerikanischen Verteilnetzmodelle des IEEE. Im Gegensatz zum Übertragungsnetz, dessen Struktur hinreichend genau bekannt ist, sind passende Netzmodelle für NS-Netze wegen der hohen Anzahlen der NS-Netze und Verteilnetzbetreiber (VNB) nur schwer abzubilden. Des Weiteren ist eine detaillierte Darstellung realer NS-Netze in wissenschaftlichen Publikationen aus daten-schutzrechtlichen Gründen meist nicht erwünscht. Für Untersuchungen im Rahmen eines Forschungsprojekts wurden darum möglichst charakteristische synthetische NS-Netzmodelle erstellt, die sich an gängigen deutschen Siedlungsstrukturen und üblichen Netzplanungsgrundsätzen orientieren. In dieser Arbeit werden diese NS-Netzmodelle sowie ihre Entwicklung im Detail erklärt. Damit stehen erstmals für die Öffentlichkeit nachvollziehbare NS-Netzmodelle für den deutschsprachigen Raum zur Verfügung. Sie können als Benchmark für wissenschaftliche Untersuchungen sowie zur Methodenentwicklung verwendet werden.