Publikationen

Phenological shifts across plant species is a powerful indicator to quantify the effects of climate change. Today, mobile applications with automated species identification open new possibilities for phenological monitoring across space and time. Here, we introduce an innovative spatio-temporal machine learning methodology that harnesses such crowd-sourced data to quantify phenological dynamics across taxa, space and time. Our algorithm links individual phenological responses across thousands of species and geographical locations, using a similarity measure. The analysis draws on nearly ten million plant observations collected through the AI-based plant identification app Flora Incognita in Germany from 2018 to 2021. Our method quantifies changes in synchronisation across the annual cycle. During the growing season, synchronised behaviour can be encoded by a few characteristic macrophenological patterns. Nonlinear spatio-temporal changes of these patterns can be efficiently quantified using a data compressibility measure. Outside the growing season, the phenological synchronisation diminishes introducing noise into the patterns. Despite biases and uncertainties associated with crowd-sourced data, for example due to human data collection behaviour, our study demonstrates the feasibility of deriving meaningful indicators for monitoring plant macrophenology from individual plant observations. As crowd-sourced databases continue to expand, our approach holds promise to study climate-induced phenological shifts and feedback loops.

Using magnetic nanoparticles (MNPs) for extracorporeal heating applications results in higher field strength and, therefore, particles of higher coercivity can be used, compared to intracorporeal applications. In this study, we report the synthesis and characterization of barium hexa-ferrite (BaFe12O19) nanoparticles as potential particles for magnetic heating. Using a precipitation method followed by high-temperature calcination, we first studied the influence of varied synthesis parameters on the particles’ properties. Second, the iron-to-barium ratio (Fe/Ba = r) was varied between 2 and 12. Vibrating sample magnetometry, scanning electron microscopy and X-ray diffraction were used for characterization. A considerable influence of the calcination temperature (Tcal) was found on the resulting magnetic properties, with a decrease in coercivity (HC) from values above 370 kA/m for Tcal = 800-1000 ˚C to HC = 45-70 kA/m for Tcal = 1200 ˚C. We attribute this drop in HC mainly to the formation of entirely multi-domain particles at high Tcal. For the varying Fe/Ba ratios, increasing amounts of BaFe2O4 as an additional phase were detected by XRD in the small r (barium surplus) samples, lowering the particles’ magnetization. A decrease in HC was found in the increased r samples. Crystal size ranged from 47 nm to 240 nm and large agglomerates were seen in SEM images. The reported particles, due to their controllable coercivity, can be a candidate for extracorporeal heating applications in the biomedical or biotechnological field.

Spatial analysis of EEG data, e.g. using short-term stable microstates, is increasingly used in neuroscience and clinical applications. At the same time, scenarios involving mobility, sports, and home-based activities are becoming more prevalent in EEG studies. For this purpose, dry EEG electrodes are more and more commonly used. Thus, our objective was a comparison of microstates analysis between dry and gel-based EEGs. 256-channel EEGs were recorded from 30 volunteers using dry and gel-based electrodes during resting state eyes closed and eyes open. Microstates were extracted for each measurement and time-domain parameters were calculated. We found a high degree of consistency between the microstate maps extracted from dry and gel-based measurements for both eyes closed and eyes open conditions. The topographic similarities between the average maps for dry and gel-based recordings were above 81.5% for each of the seven extracted maps. We conclude that topographic microstate analyses are feasible using multichannel EEG setups with new dry EEG electrodes.

Although species are central units for biological research, recent findings in genomics are raising awareness that what we call species can be ill-founded entities due to solely morphology-based, regional species descriptions. This particularly applies to groups characterized by intricate evolutionary processes such as hybridization, polyploidy, or asexuality. Here, challenges of current integrative taxonomy (genetics/genomics + morphology + ecology, etc.) become apparent: different favored species concepts, lack of universal characters/markers, missing appropriate analytical tools for intricate evolutionary processes, and highly subjective ranking and fusion of datasets. Now, integrative taxonomy combined with artificial intelligence under a unified species concept can enable automated feature learning and data integration, and thus reduce subjectivity in species delimitation. This approach will likely accelerate revising and unraveling eukaryotic biodiversity.

The differentiation of noisy signals using the family of homogeneous differentiators is considered. It includes the high-gain (linear) as well as robust exact (discontinuous) differentiator. To characterize the effect of noise and disturbance on the differentiation estimation error, the generalized, homogeneous L2-gain is utilized. Analog to the classical Lp-gain, it is not defined for the discontinuous case w.r.t. disturbances acting on the last channel. Thus, only continuous differentiators are addressed. The gain is estimated using a differential dissipation inequality, where a scaled Lyapunov function acts as storage function for the homogeneous L2 supply rate. The fixed differentiator gains are scaled with a gain-scaling parameter similar to the high-gain differentiator. This paper shows the existence of an optimal scaling which minimizes the homogeneous L2-gain estimate and provides a procedure to obtain it locally. Differentiators of dimension two are considered and the results are illustrated via numerical evaluation and a simulation example.