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Airborne and spaceborne platforms are the primary data sources for large-scale forest mapping, but visual interpretation for individual species determination is labor-intensive. Hence, various studies focusing on forests have investigated the benefits of multiple sensors for automated tree species classification. However, transferable deep learning approaches for large-scale applications are still lacking. This gap motivated us to create a novel dataset for tree species classification in central Europe based on multi-sensor data from aerial, Sentinel-1 and Sentinel-2 imagery. In this paper, we introduce the TreeSatAI Benchmark Archive, which contains labels of 20 European tree species (i.e., 15 tree genera) derived from forest administration data of the federal state of Lower Saxony, Germany. We propose models and guidelines for the application of the latest machine learning techniques for the task of tree species classification with multi-label data. Finally, we provide various benchmark experiments showcasing the information which can be derived from the different sensors including artificial neural networks and tree-based machine learning methods. We found that residual neural networks (ResNet) perform sufficiently well with weighted precision scores up to 79 % only by using the RGB bands of aerial imagery. This result indicates that the spatial content present within the 0.2 m resolution data is very informative for tree species classification. With the incorporation of Sentinel-1 and Sentinel-2 imagery, performance improved marginally. However, the sole use of Sentinel-2 still allows for weighted precision scores of up to 74 % using either multi-layer perceptron (MLP) or Light Gradient Boosting Machine (LightGBM) models. Since the dataset is derived from real-world reference data, it contains high class imbalances. We found that this dataset attribute negatively affects the models' performances for many of the underrepresented classes (i.e., scarce tree species). However, the class-wise precision of the best-performing late fusion model still reached values ranging from 54 % (Acer) to 88 % (Pinus). Based on our results, we conclude that deep learning techniques using aerial imagery could considerably support forestry administration in the provision of large-scale tree species maps at a very high resolution to plan for challenges driven by global environmental change. The original dataset used in this paper is shared via Zenodo (https://doi.org/10.5281/zenodo.6598390, Schulz et al., 2022). For citation of the dataset, we refer to this article.
Trueness and precision of milled and 3D printed root-analogue implants: A comparative in vitro study
(2023)
A company's financial documents use tables along with text to organize the data containing key performance indicators (KPIs) (such as profit and loss) and a financial quantity linked to them. The KPI’s linked quantity in a table might not be equal to the similarly described KPI's quantity in a text. Auditors take substantial time to manually audit these financial mistakes and this process is called consistency checking. As compared to existing work, this paper attempts to automate this task with the help of transformer-based models. Furthermore, for consistency checking it is essential for the table's KPIs embeddings to encode the semantic knowledge of the KPIs and the structural knowledge of the table. Therefore, this paper proposes a pipeline that uses a tabular model to get the table's KPIs embeddings. The pipeline takes input table and text KPIs, generates their embeddings, and then checks whether these KPIs are identical. The pipeline is evaluated on the financial documents in the German language and a comparative analysis of the cell embeddings' quality from the three tabular models is also presented. From the evaluation results, the experiment that used the English-translated text and table KPIs and Tabbie model to generate table KPIs’ embeddings achieved an accuracy of 72.81% on the consistency checking task, outperforming the benchmark, and other tabular models.
RELA haploinsufficiency is a recently described autoinflammatory condition presenting with intermittent fevers and mucocutaneous ulcerations. The RELA gene encodes the p65 protein, one of five NF-κB family transcription factors. As RELA is an essential regulator of mucosal homeostasis, haploinsufficiency leads to decreased NF-κB signaling which promotes TNF-driven mucosal apoptosis with impaired epithelial recovery. Thus far, only eight cases have been reported in the literature. Here, we report four families with three novel and one previously described pathogenic variant in RELA. These four families included 23 affected individuals for which genetic testing was available in 16. Almost half of these patients had been previously diagnosed with more common rheumatologic entities (such as Behcet's Disease; BD) prior to the discovery of their pathogenic RELA variants. The most common clinical features were orogenital ulcers, rash, joint inflammation, and fever. The least common were conjunctivitis and recurrent infections. Clinical variability was remarkable even among familial cases, and incomplete penetrance was observed. Patients in our series were treated with a variety of medications, and benefit was observed with glucocorticoids, colchicine, and TNF inhibitors. Altogether, our work adds to the current literature and doubles the number of reported cases with RELA-Associated Inflammatory Disease (RAID). It reaffirms the central importance of the NF-κB pathway in immunity and inflammation, as well as the important regulatory role of RELA in mucosal homeostasis. RELA associated inflammatory disease should be considered in all patients with BD, particularly those with early onset and/or with a strong family history.
This paper presents the preliminary results of the Socialist Republic of Vietnam country case study conducted as part of the research project Sustainable Labour Migration implemented by the University of Applied Science Bonn-Rhein-Sieg. The project focuses on stakeholder perspectives on countries of origin benefits and the sustainability of different transnational skill partnership schemes. Existing and ongoing small-scale initiatives indicate that opportunities exist for all three types of labour mobility pathways, from recruiting youth for apprenticeships and subsequent skilled work to recruitment and recognition of skilled 'professionals' certificates for direct work contracts to initial vocational education and training programs in a dual-track approach. While the latter has the highest potential to be more beneficial than other approaches, pursuing and supporting the scaling up of all three pathways in parallel will have additional, mutually reinforcing and supporting effects. The potential for benefits over and above those already realised by existing skill partnerships appears high, especially considering the favourable framework conditions specific to the long-standing German-Vietnamese relationship. If the potential of well-managed skill partnerships was realised, such sustainable models of skilled labour migration could serve as a unique selling point in the international competition for skilled labour.
A biodegradable blend of PBAT—poly(butylene adipate-co-terephthalate)—and PLA—poly(lactic acid)—for blown film extrusion was modified with four multi-functional chain extending cross-linkers (CECL). The anisotropic morphology introduced during film blowing affects the degradation processes. Given that two CECL increased the melt flow rate (MFR) of tris(2,4-di-tert-butylphenyl)phosphite (V1) and 1,3-phenylenebisoxazoline (V2) and the other two reduced it (aromatic polycarbodiimide (V3) and poly(4,4-dicyclohexylmethanecarbodiimide) (V4)), their compost (bio-)disintegration behavior was investigated. It was significantly altered with respect to the unmodified reference blend (REF). The disintegration behavior at 30 and 60 °C was investigated by determining changes in mass, Young’s moduli, tensile strengths, elongations at break and thermal properties. In order to quantify the disintegration behavior, the hole areas of blown films were evaluated after compost storage at 60 °C to calculate the kinetics of the time dependent degrees of disintegration. The kinetic model of disintegration provides two parameters: initiation time and disintegration time. They quantify the effects of the CECL on the disintegration behavior of the PBAT/PLA compound. Differential scanning calorimetry (DSC) revealed a pronounced annealing effect during storage in compost at 30 °C, as well as the occurrence of an additional step-like increase in the heat flow at 75 °C after storage at 60 °C. The disintegration consists of processes which affect amorphous and crystalline phase of PBAT in different manner that cannot be understood by a hydrolytic chain degradation only. Furthermore, gel permeation chromatography (GPC) revealed molecular degradation only at 60 °C for the REF and V1 after 7 days of compost storage. The observed losses of mass and cross-sectional area seem to be attributed more to mechanical decay than to molecular degradation for the given compost storage times.
Solar photovoltaic power output is modulated by atmospheric aerosols and clouds and thus contains valuable information on the optical properties of the atmosphere. As a ground-based data source with high spatiotemporal resolution it has great potential to complement other ground-based solar irradiance measurements as well as those of weather models and satellites, thus leading to an improved characterisation of global horizontal irradiance. In this work several algorithms are presented that can retrieve global tilted and horizontal irradiance and atmospheric optical properties from solar photovoltaic data and/or pyranometer measurements. The method is tested on data from two measurement campaigns that took place in the Allgäu region in Germany in autumn 2018 and summer 2019, and the results are compared with local pyranometer measurements as well as satellite and weather model data. Using power data measured at 1 Hz and averaged to 1 min resolution along with a non-linear photovoltaic module temperature model, global horizontal irradiance is extracted with a mean bias error compared to concurrent pyranometer measurements of 5.79 W m−2 (7.35 W m−2) under clear (cloudy) skies, averaged over the two campaigns, whereas for the retrieval using coarser 15 min power data with a linear temperature model the mean bias error is 5.88 and 41.87 W m−2 under clear and cloudy skies, respectively.
During completely overcast periods the cloud optical depth is extracted from photovoltaic power using a lookup table method based on a 1D radiative transfer simulation, and the results are compared to both satellite retrievals and data from the Consortium for Small-scale Modelling (COSMO) weather model. Potential applications of this approach for extracting cloud optical properties are discussed, as well as certain limitations, such as the representation of 3D radiative effects that occur under broken-cloud conditions. In principle this method could provide an unprecedented amount of ground-based data on both irradiance and optical properties of the atmosphere, as long as the required photovoltaic power data are available and properly pre-screened to remove unwanted artefacts in the signal. Possible solutions to this problem are discussed in the context of future work.
When optimizing the process parameters of the acidic ethanolic organosolv process, the aim is usually to maximize the delignification and/or lignin purity. However, process parameters such as temperature, time, ethanol and catalyst concentration, respectively, can also be used to vary the structural properties of the obtained organosolv lignin, including the molecular weight and the ratio of aliphatic versus phenolic hydroxyl groups, among others. This review particularly focuses on these influencing factors and establishes a trend analysis between the variation of the process parameters and the effect on lignin structure. Especially when larger data sets are available, as for process temperature and time, correlations between the distribution of depolymerization and condensation reactions are found, which allow direct conclusions on the proportion of lignin's structural features, independent of the diversity of the biomass used. The newfound insights gained from this review can be used to tailor organosolv lignins isolated for a specific application.
There has been a growing interest in taste research in the HCI and CSCW communities. However, the focus is more on stimulating the senses, while the socio-cultural aspects have received less attention. However, individual taste perception is mediated through social interaction and collective negotiation and is not only dependent on physical stimulation. Therefore, we study the digital mediation of taste by drawing on ethnographic research of four online wine tastings and one self-organized event. Hence, we investigated the materials, associated meanings, competences, procedures, and engagements that shaped the performative character of tasting practices. We illustrate how the tastings are built around the taste-making process and how online contexts differ in providing a more diverse and distributed environment. We then explore the implications of our findings for the further mediation of taste as a social and democratized phenomenon through online interaction.
Dried serum spots that are well prepared can be attractive alternatives to frozen serum samples for shelving specimens in a medical or research center's biobank and mailing freshly prepared serum to specialized laboratories. During the pre-analytical phase, complications can arise which are often challenging to identify or are entirely overlooked. These complications can lead to reproducibility issues, which can be avoided in serum protein analysis by implementing optimized storage and transfer procedures. With a method that ensures accurate loading of filter paper discs with donor or patient serum, a gap in dried serum spot preparation and subsequent serum analysis shall be filled. Pre-punched filter paper discs with a 3 mm diameter are loaded within seconds in a highly reproducible fashion (approximately 10% standard deviation) when fully submerged in 10 μl of serum, named the "Submerge and Dry" protocol. Such prepared dried serum spots can store several hundred micrograms of proteins and other serum components. Serum-borne antigens and antibodies are reproducibly released in 20 μl elution buffer in high yields (approximately 90%). Dried serum spot-stored and eluted antigens kept their epitopes and antibodies their antigen binding abilities as was assessed by SDS-PAGE, 2D gel electrophoresis-based proteomics, and Western blot analysis, suggesting pre-punched filter paper discs as handy solution for serological tests.
Several species of (poly)saccharides and organic acids can be found often simultaneously in various biological matrices, e.g., fruits, plant materials, and biological fluids. The analysis of such matrices sometimes represents a challenging task. Using Aloe vera (A. vera) plant materials as an example, the performance of several spectroscopic methods (80 MHz benchtop NMR, NIR, ATR-FTIR and UV-Vis) for the simultaneous analysis of quality parameters of this plant material was compared. The determined parameters include (poly)saccharides such as aloverose, fructose and glucose as well as organic acids (malic, lactic, citric, isocitric, acetic, fumaric, benzoic and sorbic acids). 500 MHz NMR and high-performance liquid chromatography (HPLC) were used as the reference methods.
UV-VIS data can be used only for identification of added preservatives (benzoic and sorbic acids) and drying agent (maltodextrin) and semiquantitative analysis of malic acid. NIR and MIR spectroscopies combined with multivariate regression can deliver more informative overview of A. vera extracts being able to additionally quantify glucose, aloverose, citric, isocitric, malic, lactic acids and fructose. Low-field NMR measurements can be used for the quantification of aloverose, glucose, malic, lactic, acetic, and benzoic acids. The benchtop NMR method was successfully validated in terms of robustness, stability, precision, reproducibility and limit of detection (LOD) and quantification (LOQ), respectively.
All spectroscopic techniques are useful for the screening of (poly)saccharides and organic acids in plant extracts and should be applied according to its availability as well as information and confidence required for the specific analytical goal. Benchtop NMR spectroscopy seems to be the most feasible solution for quality control of A. vera products.
This work presents an open source database with suitable retention parameters for prediction and simulation of GC separations and gives a short introduction to three common retention models. Useful computer simulations play an important role to save resources and time in method development in GC. Thermodynamic retention parameters for the ABC model and the K-centric model are determined by isothermal measurements. This standardized procedure of measurements and calculations, presented in this work, have a useful benefit for all chromatographers, analytical chemists, and method developers because it can be used in their own laboratories to simplify the method development. The main benefits as simulations of temperature-programed GC separations are demonstrated and compared to measurements. The observed deviations of predicted retention times are in most cases less than 1%. The database includes more than 900 entries with a large range of compounds such as VOCs, PAHs, FAMEs, PCBs, or allergenic fragrances over 20 different GC columns.
Neutral buoyancy has been used as an analog for microgravity from the earliest days of human spaceflight. Compared to other options on Earth, neutral buoyancy is relatively inexpensive and presents little danger to astronauts while simulating some aspects of microgravity. Neutral buoyancy removes somatosensory cues to the direction of gravity but leaves vestibular cues intact. Removal of both somatosensory and direction of gravity cues while floating in microgravity or using virtual reality to establish conflicts between them has been shown to affect the perception of distance traveled in response to visual motion (vection) and the perception of distance. Does removal of somatosensory cues alone by neutral buoyancy similarly impact these perceptions? During neutral buoyancy we found no significant difference in either perceived distance traveled nor perceived size relative to Earth-normal conditions. This contrasts with differences in linear vection reported between short- and long-duration microgravity and Earth-normal conditions. These results indicate that neutral buoyancy is not an effective analog for microgravity for these perceptual effects.