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- Department of Biomedical Imaging, National Cerebral and Cardiovascular Research Center, Suita, Japan (2)
- Division of Medical Technology and Science, Department of Medical Physics and Engineering, Course of Health Science, Osaka University Graduate School of Medicine, Suita Japan (2)
- Institut for Molecular Biology and CMBI, Department of Genomics, Stem Cell Biology and Regenerative Medicine, Leopold-Franzens-University Innsbruck, Innsbruck, Austria (2)
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Background:
The cardiac hormones atrial (ANP) and B-type natriuretic peptides (BNP) moderate arterial blood pressure and improve energy metabolism as well as insulin sensitivity via their shared cGMP-producing guanylyl cyclase-A (GC-A) receptor. Obesity is associated with impaired NP/GC-A/cGMP signaling, which possibly contributes to the development of type 2 diabetes and its cardiometabolic complications. In vitro, synthetic ANP, via GC-A, stimulates glucose-dependent insulin release from cultured pancreatic islets and β-cell proliferation. However, the relevance for systemic glucose homeostasis in vivo is not known. To dissect whether the endogenous cardiac hormones modulate the secretory function and/or proliferation of β-cells under (patho)physiological conditions in vivo, here we generated a novel genetic mouse model with selective disruption of the GC-A receptor in β-cells.
Methods:
Mice with a floxed GC-A gene were bred to Rip-CreTG mice, thereby deleting GC-A selectively in β-cells (β GC-A KO). Weight gain, glucose tolerance, insulin sensitivity, and glucose-stimulated insulin secretion were monitored in normal diet (ND)- and high-fat diet (HFD)-fed mice. β-cell size and number were measured by immunofluorescence-based islet morphometry.
Results:
In vitro, the insulinotropic and proliferative actions of ANP were abolished in islets isolated from β GC-A KO mice. Concordantly, in vivo, infusion of BNP mildly enhanced baseline plasma insulin levels and glucose-induced insulin secretion in control mice. This effect of exogenous BNP was abolished in β GC-A KO mice, corroborating the efficient inactivation of the GC-A receptor in β-cells. Despite this under physiological, ND conditions, fasted and fed insulin levels, glucose-induced insulin secretion, glucose tolerance and β-cell morphology were similar in β GC-A KO mice and control littermates. However, HFD-fed β GC-A KO animals had accelerated glucose intolerance and diminished adaptative β-cell proliferation.
Conclusions:
Our studies of β GC-A KO mice demonstrate that the cardiac hormones ANP and BNP do not modulate β-cell's growth and secretory functions under physiological, normal dietary conditions. However, endogenous NP/GC-A signaling improves the initial adaptative response of β-cells to HFD-induced obesity. Impaired β-cell NP/GC-A signaling in obese individuals might contribute to the development of type 2 diabetes.
Phosphines are important ligands in homogenous catalysis and have been crucial for many advances, such as in cross-coupling, hydrofunctionalization, or hydrogenation reactions. Herein we report the synthesis and application of a novel class of phosphines bearing ylide substituents. These phosphines are easily accessible via different synthetic routes from commercially available starting materials. Owing to the extra donation from the ylide group to the phosphorus center the ligands are unusually electron-rich and can thus function as strong electron donors. The donor capacity surpasses that of commonly used phosphines and carbenes and can easily be tuned by changing the substitution pattern at the ylidic carbon atom. The huge potential of ylide-functionalized phosphines in catalysis is demonstrated by their use in gold catalysis. Excellent performance at low catalyst loadings under mild reaction conditions is thus seen in different types of transformations.
Background
Wilms’ tumor 1-associating protein (WTAP) is a nuclear protein, which is ubiquitously expressed in many tissues. Furthermore, in various types of malignancies WTAP is overexpressed and plays a role as an oncogene. The function of WTAP in diffuse large B-cell lymphoma (DLBCL), however, remains unclear.
Methods
Immunohistochemistry was applied to evaluate the levels of WTAP expression in DLBCL tissues and normal lymphoid tissues. Overexpression and knock-down of WTAP in DLBCL cell lines, verified on mRNA and protein level served to analyze cell proliferation and apoptosis in DLBCL cell lines by flow cytometry. Finally, co-immunoprecipitation (Co-IP), IP, and GST-pull down assessed the interaction of WTAP with Heat shock protein 90 (Hsp90) and B-cell lymphoma 6 (BCL6) as well as determined the extend of its ubiquitinylation.
Results
WTAP protein levels were consistently upregulated in DLBCL tissues. WTAP promoted DLBCL cell proliferation and improved the ability to confront apoptosis, while knockdown of WTAP in DLBCL cell lines allowed a significant higher apoptosis rate after treatment with Etoposide, an anti-tumor drug. The stable expression of WTAP was depended on Hsp90. In line, we demonstrated that WTAP could form a complex with BCL6 via Hsp90 in vivo and in vitro.
Conclusion
WTAP is highly expressed in DLBCL, promoting growth and anti-apoptosis in DLBCL cell lines. WTAP is a client protein of Hsp90 and can appear in a complex with BCL6 and Hsp90 in DLBCL. Down-regulation of WTAP could improve the chemotherapeutic treatments in DLBCL.
Background:
In previous studies, the gram-positive firmicute genus Paenibacillus was found with significant abundances in nests of wild solitary bees. Paenibacillus larvae is well-known for beekeepers as a severe pathogen causing the fatal honey bee disease American foulbrood, and other members of the genus are either secondary invaders of European foulbrood or considered a threat to honey bees. We thus investigated whether Paenibacillus is a common bacterium associated with various wild bees and hence poses a latent threat to honey bees visiting the same flowers.
Results:
We collected 202 samples from 82 individuals or nests of 13 bee species at the same location and screened each for Paenibacillus using high-throughput sequencing-based 16S metabarcoding. We then isolated the identified strain Paenibacillus MBD-MB06 from a solitary bee nest and sequenced its genome. We did find conserved toxin genes and such encoding for chitin-binding proteins, yet none specifically related to foulbrood virulence or chitinases. Phylogenomic analysis revealed a closer relationship to strains of root-associated Paenibacillus rather than strains causing foulbrood or other accompanying diseases. We found anti-microbial evidence within the genome, confirmed by experimental bioassays with strong growth inhibition of selected fungi as well as gram-positive and gram-negative bacteria.
Conclusions:
The isolated wild bee associate Paenibacillus MBD-MB06 is a common, but irregularly occurring part of wild bee microbiomes, present on adult body surfaces and guts and within nests especially in megachilids. It was phylogenetically and functionally distinct from harmful members causing honey bee colony diseases, although it shared few conserved proteins putatively toxic to insects that might indicate ancestral predisposition for the evolution of insect pathogens within the group. By contrast, our strain showed anti-microbial capabilities and the genome further indicates abilities for chitin-binding and biofilm-forming, suggesting it is likely a useful associate to avoid fungal penetration of the bee cuticula and a beneficial inhabitant of nests to repress fungal threats in humid and nutrient-rich environments of wild bee nests.
This thesis considers a model of a scalar partial differential equation in the presence of a singular source term, modeling the interaction between an inviscid fluid represented by the Burgers equation and an arbitrary, finite amount of particles moving inside the fluid, each one acting as a point-wise drag force with a particle related friction constant.
\begin{align*}
\partial_t u + \partial_x (u^2/2) &= \sum_{i \in N(t)} \lambda_i \Big(h_i'(t)-u(t,h_i(t)\Big)\delta(x-h_i(t))
\end{align*}
The model was introduced for the case of a single particle by Lagoutière, Seguin and Takahashi, is a first step towards a better understanding of interaction between fluids and solids on the level of partial differential equations and has the unique property of considering entropy admissible solutions and the interaction with shockwaves.
The model is extended to an arbitrary, finite number of particles and interactions like merging, splitting and crossing of particle paths are considered.
The theory of entropy admissibility is revisited for the cases of interfaces and discontinuous flux conservation laws, existing results are summarized and compared, and adapted for regions of particle interactions. To this goal, the theory of germs introduced by Andreianov, Karlsen and Risebro is extended to this case of non-conservative interface coupling.
Exact solutions for the Riemann Problem of particles drifting apart are computed and analysis on the behavior of entropy solutions across the particle related interfaces is used to determine physically relevant and consistent behavior for merging and splitting of particles. Well-posedness of entropy solutions to the Cauchy problem is proven, using an explicit construction method, L-infinity bounds, an approximation of the particle paths and compactness arguments to obtain existence of entropy solutions. Uniqueness is shown in the class of weak entropy solutions using almost classical Kruzkov-type analysis and the notion of L1-dissipative germs.
Necessary fundamentals of hyperbolic conservation laws, including weak solutions, shocks and rarefaction waves and the Rankine-Hugoniot condition are briefly recapitulated.
Although many genes have been identified using high throughput technologies in endometriosis (ES), only a small number of individual genes have been analyzed functionally. This is due to the complexity of the disease that has different stages and is affected by various genetic and environmental factors. Many genes are upregulated or downregulated at each stage of the disease, thus making it difficult to identify key genes. In addition, little is known about the differences between the different stages of the disease. We assumed that the study of the identified genes in ES at a system-level can help to better understand the molecular mechanism of the disease at different stages of the development. We used publicly available microarray data containing archived endometrial samples from women with minimal/mild endometriosis (MMES), mild/severe endometriosis (MSES) and without endometriosis. Using weighted gene co-expression analysis (WGCNA), functional modules were derived from normal endometrium (NEM) as the reference sample. Subsequently, we tested whether the topology or connectivity pattern of the modules was preserved in MMES and/or MSES. Common and specific hub genes were identified in non-preserved modules. Accordingly, hub genes were detected in the non-preserved modules at each stage. We identified sixteen co-expression modules. Of the 16 modules, nine were non-preserved in both MMES and MSES whereas five were preserved in NEM, MMES, and MSES. Importantly, two non-preserved modules were found in either MMES or MSES, highlighting differences between the two stages of the disease. Analyzing the hub genes in the non-preserved modules showed that they mostly lost or gained their centrality in NEM after developing the disease into MMES and MSES. The same scenario was observed, when the severeness of the disease switched from MMES to MSES. Interestingly, the expression analysis of the new selected gene candidates including CC2D2A, AEBP1, HOXB6, IER3, and STX18 as well as IGF-1, CYP11A1 and MMP-2 could validate such shifts between different stages. The overrepresented gene ontology (GO) terms were enriched in specific modules, such as genetic disposition, estrogen dependence, progesterone resistance and inflammation, which are known as endometriosis hallmarks. Some modules uncovered novel co-expressed gene clusters that were not previously discovered.
The command area of the Rakh branch canal grows wheat, sugarcane, and rice crops in abundance. The canal water, which is trivial for irrigating these crops, is conveyed to the farms through the network of canals and distributaries. For the maintenance of this vast infrastructure; the end users are charged on a seasonal basis. The present water charges are severely criticized for not being adequate to properly manage the entire infrastructure. We use the residual value to determine the value of the irrigation water and then based on the quantity of irrigation water supplied to farm land coupled with the infrastructure maintenance cost, full cost recovery figures are executed for the study area, and policy recommendations are made for the implementation of the full cost recovery system. The approach is unique in the sense that the pricings are based on the actual quantity of water conveyed to the field for irrigating crops. The results of our analysis showed that the canal water is severely under charged in the culturable command area of selected distributaries, thus negating the plan of having a self-sustainable irrigation system.
Purpose: The metabolically most active lesion in 2-deoxy-2-(\(^{18}\)F)fluoro-D-glucose (\(^{18}\)F-FDG) PET/CT can predict progression-free survival (PFS) in patients with medullary thyroid carcinoma (MTC) starting treatment with the tyrosine kinase inhibitor (TKI) vandetanib. However, this metric failed in overall survival (OS) prediction. In the present proof of concept study, we aimed to explore the prognostic value of intratumoral textural features (TF) as well as volumetric parameters (total lesion glycolysis, TLG) derived by pre-therapeutic \(^{18}\)F-FDG PET.
Methods: Eighteen patients with progressive MTC underwent baseline \(^{18}\)F-FDG PET/CT prior to and 3 months after vandetanib initiation. By manual segmentation of the tumor burden at baseline and follow-up PET, intratumoral TF and TLG were computed. The ability of TLG, imaging-based TF, and clinical parameters (including age, tumor marker doubling times, prior therapies and RET (rearranged during transfection) mutational status) for prediction of both PFS and OS were evaluated.
Results: The TF Complexity and the volumetric parameter TLG obtained at baseline prior to TKI initiation successfully differentiated between low- and high-risk patients. Complexity allocated 10/18 patients to the high-risk group with an OS of 3.3y (vs. low-risk group, OS=5.3y, 8/18, AUC=0.78, P=0.03). Baseline TLG designated 11/18 patients to the high-risk group (OS=3.5y vs. low-risk group, OS=5y, 7/18, AUC=0.83, P=0.005). The Hazard Ratio for cancer-related death was 6.1 for Complexity (TLG, 9.5). Among investigated clinical parameters, the age at initiation of TKI treatment reached significance for PFS prediction (P=0.02, OS, n.s.).
Conclusions: The TF Complexity and the volumetric parameter TLG are both independent parameters for OS prediction.
Pictorial stimuli can vary on many dimensions, several aspects of which are captured by the term ‘visual complexity.’ Visual complexity can be described as, “a picture of a few objects, colors, or structures would be less complex than a very colorful picture of many objects that is composed of several components.” Prior studies have reported a relationship between affect and visual complexity, where complex pictures are rated as more pleasant and arousing. However, a relationship in the opposite direction, an effect of affect on visual complexity, is also possible; emotional arousal and valence are known to influence selective attention and visual processing. In a series of experiments, we found that ratings of visual complexity correlated with affective ratings, and independently also with computational measures of visual complexity. These computational measures did not correlate with affect, suggesting that complexity ratings are separately related to distinct factors. We investigated the relationship between affect and ratings of visual complexity, finding an ‘arousal-complexity bias’ to be a robust phenomenon. Moreover, we found this bias could be attenuated when explicitly indicated but did not correlate with inter-individual difference measures of affective processing, and was largely unrelated to cognitive and eyetracking measures. Taken together, the arousal-complexity bias seems to be caused by a relationship between arousal and visual processing as it has been described for the greater vividness of arousing pictures. The described arousal-complexity bias is also of relevance from an experimental perspective because visual complexity is often considered a variable to control for when using pictorial stimuli.
PURPOSE:
We aimed to (a) elucidate the concordance of visual assessment of an initial I-ioflupane scan by a human interpreter with comparison to results using a fully automatic semiquantitative method and (b) to assess the accuracy compared to follow-up (f/u) diagnosis established by movement disorder specialists.
METHODS:
An initial I-ioflupane scan was performed in 382 patients with clinically uncertain Parkinsonian syndrome. An experienced reader performed a visual evaluation of all scans independently. The findings of the visual read were compared with semiquantitative evaluation. In addition, available f/u clinical diagnosis (serving as a reference standard) was compared with results of the human read and the software.
RESULTS:
When comparing the semiquantitative method with the visual assessment, discordance could be found in 25 (6.5%) of 382 of the cases for the experienced reader (ĸ = 0.868). The human observer indicated region of interest misalignment as the main reason for discordance. With neurology f/u serving as reference, the results of the reader revealed a slightly higher accuracy rate (87.7%, ĸ = 0.75) compared to semiquantification (86.2%, ĸ = 0.719, P < 0.001, respectively). No significant difference in the diagnostic performance of the visual read versus software-based assessment was found.
CONCLUSIONS:
In comparison with a fully automatic semiquantitative method in I-ioflupane interpretation, human assessment obtained an almost perfect agreement rate. However, compared to clinical established diagnosis serving as a reference, visual read seemed to be slightly more accurate as a solely software-based quantitative assessment.
West Africa is one of the fastest growing regions in the world with annual population growth rates of more than three percent for several countries. Since the 1950s, West Africa experienced a fivefold increase of inhabitants, from 71 to 353 million people in 2015 and it is expected that the region’s population will continue to grow to almost 800 million people by the year 2050. This strong trend has and will have serious consequences for food security since agricultural productivity is still on a comparatively low level in most countries of West Africa. In order to compensate for this low productivity, an expansion of agricultural areas is rapidly progressing. The mapping and monitoring of agricultural areas in West Africa is a difficult task even on the basis of remote sensing. The small scale extensive farming practices with a low level of agricultural inputs and mechanization make the delineation of cultivated land from other land cover and land use (LULC) types highly challenging. In addition, the frequent cloud coverage in the region considerably decreases the availability of earth observation datasets. For the accurate mapping of agricultural area in West Africa, high temporal as well as spatial resolution is necessary to delineate the small-sized fields and to obtain data from periods where different LULC types are distinguishable. However, such consistent time series are currently not available for West Africa. Thus, a spatio-temporal data fusion framework was developed in this thesis for the generation of high spatial and temporal resolution time series.
Data fusion algorithms such as the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM) enjoyed increasing popularity during recent years but they have hardly been used for the application on larger scales. In order to make it applicable for this purpose and to increase the input data availability, especially in cloud-prone areas such as West Africa, the ESTARFM framework was developed in this thesis introducing several enhancements. An automatic filling of cloud gaps was included in the framework in order to use even partly cloud-covered Landsat images for the fusion without producing gaps on the output images. In addition, the ESTARFM algorithm was improved to automatically account for regional differences in the heterogeneity of the study region. Further improvements comprise the automation of the time series generation as well as the significant acceleration of the processing speed through parallelization. The performance of the developed ESTARFM framework was tested by fusing an 8-day NDVI time series from Landsat and MODIS data for a focus area of 98,000 km² in the border region between Burkina Faso and Ghana. The results of this test show the capability of the ESTARFM framework to accurately produce high temporal resolution time series while maintaining the spatial detail, even in such a heterogeneous and cloud-prone region.
The successfully tested framework was subsequently applied to generate consistent time series as the basis for the mapping of agricultural area in Burkina Faso for the years 2001, 2007, and 2014. In a first step, high temporal (8-day) and high spatial (30 m) resolution NDVI time series for the entire country and the three years were derived with the ESTARFM framework. More than 500 Landsat scenes and 3000 MODIS scenes were automatically processed for this purpose. From the fused ESTARFM NDVI time series, phenological metrics were extracted and together with the single time steps of NDVI served as input for the delineation of rainfed agricultural areas, irrigated agricultural areas and plantations. The classification was conducted with the random forest algorithm at a 30 m spatial resolution for entire Burkina Faso and the three years 2001, 2007, and 2014. For the training and validation of the classifier, a randomly sampled reference dataset was generated from Google Earth images based on expert knowledge of the region. The overall classification accuracies of 92% (2001), 91% (2007), and 91% (2014) indicate the well-functioning of the developed methodology. The resulting maps show an expansion of agricultural area of 91% from about 61,000 km² in 2001 to 116,900 km² in 2014. While rainfed agricultural areas account for the major part of this increase, irrigated areas and plantations also spread considerably. Especially the expansion of irrigation systems and plantation area can be explained by the promotion through various national and international development projects. The increase of agricultural areas goes in line with the rapid population growth in most of Burkina Faso’s provinces which still had available land resources for an expansion of agricultural area. An analysis of the development of agricultural areas in the vicinity of protected areas highlighted the increased human pressure on these reserves. The protection of the remnant habitats for flora and fauna while at the same time improving food security for a rapidly growing population, are the major challenges for the region in the future.
The developed ESTARFM framework showed great potential beyond its utilization for the mapping of agricultural area. Other large-scale research that requires a sufficiently high temporal and spatial resolution such as the monitoring of land degradation or the investigation of land surface phenology could greatly benefit from the application of this framework.
Urban areas are population, culture and infrastructure concentration points. Electricity blackouts or interruptions of water supply severely affect people when happening unexpected and at large scale. Interruptions of such infrastructure supply services alone have the potential to trigger crises. But when happening in concert with or as a secondary effect of an earthquake, for example, the crisis situation is often aggravated. This is the case for any country, but it has been observed that even highly industrialised
countries face severe risks when their degree of acquired dependency on services of what is termed Critical Infrastructure results in even bigger losses when occurring unexpectedly in a setting that usually has high reliability of services.
Cyclic diboranes(4) based on a chelating monoanionic, benzylphosphine linker were prepared by boron-silicon exchange between arylsilanes and B\(_2\)Br\(_4\). Coordination of Lewis bases to the remaining sp\(^2\) boron atom yielded unsymmetrical sp\(^3\)-sp\(^3\) diboranes, which were reduced with KC\(_8\) to their corresponding trans-diborenes. These compounds were studied by a combination of spectroscopic methods, X-ray diffraction and DFT calculations. PMe\(_3\)-stabilized diborene 6 was found to undergo thermal rearrangement to gem- diborene 8. DFT calculations on 8 reveal a polar boron-boron bond, and indicate that the compound is best described as a borylborylene.
Unraveling the connection between fibroblast growth factor and bone morphogenetic protein signaling
(2018)
Ontogeny of higher organisms as well the regulation of tissue homeostasis in adult individuals requires a fine-balanced interplay of regulating factors that individually trigger the fate of particular cells to either stay undifferentiated or to differentiate towards distinct tissue specific lineages. In some cases, these factors act synergistically to promote certain cellular responses, whereas in other tissues the same factors antagonize each other. However, the molecular basis of this obvious dual signaling activity is still only poorly understood. Bone morphogenetic proteins (BMPs) and fibroblast growth factors (FGFs) are two major signal protein families that have a lot in common: They are both highly preserved between different species, involved in essential cellular functions, and their ligands vastly outnumber their receptors, making extensive signal regulation necessary. In this review we discuss where and how BMP and FGF signaling cross paths. The compiled data reflect that both factors synchronously act in many tissues, and that antagonism and synergism both exist in a context-dependent manner. Therefore, by challenging a generalization of the connection between these two pathways a new chapter in BMP FGF signaling research will be introduced.
Background: Acute myeloid leukemia (AML) is both more common and with more biologically aggressive phenotype in the elderly. Allogenic stem cell transplantation (allo-SCT) is the best treatment option in fit patients. Either HLA-matched unrelated donor (MUD) or haploidentical (Haplo) donor are possible alternative for patients in need. Methods: We retrospectively compared non-T-cell-depleted Haplo (n = 250) to 10/10 MUD (n = 2589) in AML patients >= 60 years. Results: Median follow-up was 23 months. Disease status at transplant differs significantly between the two groups (p < 10(-4)). Reduced intensity conditioning (RIC) was administrated to 73 and 77% of Haplo and MUD, respectively (p = 0.23). Stem cell source was the bone marrow (BM) in 52% of the Haplo and 6% of MUD (p < 10(-4)). Anti-thymocyte globulin (ATG) was most frequently used in MUD (p < 10(-4)) while post-Tx cyclophosphamide (PT-Cy) was given in 62% of Haplo. Engraftment was achieved in 90% of the Haplo vs 97% of MUD (p < 10(-4)). In multivariate analysis, no significant difference was found between Haplo and MUD for acute (a) graft versus host disease (GVHD) grade II-IV, relapse incidence (RI), non-relapse mortality (NRM), leukemia free survival (LFS), graft-versus-host-free-relapse free survival (GRFS), and overall survival (OS). Extensive chronic (c) GVHD was significantly higher for MUD as compared to Haplo (HR 2, p = 0.01, 95% CI 1.17-3.47). A propensity score analysis confirmed the higher risk of extensive cGVHD for MUD without differences for other outcomes. Conclusions: Allo-SCT from both Haplo and MUD are valid option for AML patients >= 60 years of age with similar results. Transplantation from MUD was associated with higher extensive cGVHD. Our findings suggest that Haplo is a suitable and attractive graft source for patients >= 60 with AML in need of allo-SCT.
Understanding human navigation behavior has implications for a wide range of application scenarios. For example, insights into geo-spatial navigation in urban areas can impact city planning or public transport. Similarly, knowledge about navigation on the web can help to improve web site structures or service experience.
In this work, we focus on a hypothesis-driven approach to address the task of understanding human navigation: We aim to formulate and compare ideas — for example stemming from existing theory, literature, intuition, or previous experiments — based on a given set of navigational observations. For example, we may compare whether tourists exploring a city walk “short distances” before taking their next photo vs. they tend to "travel long distances between points of interest", or whether users browsing Wikipedia "navigate semantically" vs. "click randomly".
For this, the Bayesian method HypTrails has recently been proposed. However, while HypTrails is a straightforward and flexible approach, several major challenges remain:
i) HypTrails does not account for heterogeneity (e.g., incorporating differently behaving user groups such as tourists and locals is not possible), ii) HypTrails does not support the user in conceiving novel hypotheses when confronted with a large set of possibly relevant background information or influence factors, e.g., points of interest, popularity of locations, time of the day, or user properties, and finally iii) formulating hypotheses can be technically challenging depending on the application scenario (e.g., due to continuous observations or temporal constraints). In this thesis, we address these limitations by introducing various novel methods and tools and explore a wide range of case studies.
In particular, our main contributions are the methods MixedTrails and SubTrails which specifically address the first two limitations: MixedTrails is an approach for hypothesis comparison that extends the previously proposed HypTrails method to allow formulating and comparing heterogeneous hypotheses (e.g., incorporating differently behaving user groups). SubTrails is a method that supports hypothesis conception by automatically discovering interpretable subgroups with exceptional navigation behavior. In addition, our methodological contributions also include several tools consisting of a distributed implementation of HypTrails, a web application for visualizing geo-spatial human navigation in the context of background information, as well as a system for collecting, analyzing, and visualizing mobile participatory sensing data.
Furthermore, we conduct case studies in many application domains, which encompass — among others — geo-spatial navigation based on photos from the photo-sharing platform Flickr, browsing behavior on the social tagging system BibSonomy, and task choosing behavior on a commercial crowdsourcing platform. In the process, we develop approaches to cope with application specific subtleties (like continuous observations and temporal constraints). The corresponding studies illustrate the variety of domains and facets in which navigation behavior can be studied and, thus, showcase the expressiveness, applicability, and flexibility of our methods. Using these methods, we present new aspects of navigational phenomena which ultimately help to better understand the multi-faceted characteristics of human navigation behavior.
Forest ecosystems fulfill a whole host of ecosystem functions that are essential for life on our planet. However, an unprecedented level of anthropogenic influences is reducing the resilience and stability of our forest ecosystems as well as their ecosystem functions. The relationships between drivers, stress, and ecosystem functions in forest ecosystems are complex, multi-faceted, and often non-linear, and yet forest managers, decision makers, and politicians need to be able to make rapid decisions that are data-driven and based on short and long-term monitoring information, complex modeling, and analysis approaches. A huge number of long-standing and standardized forest health inventory approaches already exist, and are increasingly integrating remote-sensing based monitoring approaches. Unfortunately, these approaches in monitoring, data storage, analysis, prognosis, and assessment still do not satisfy the future requirements of information and digital knowledge processing of the 21st century. Therefore, this paper discusses and presents in detail five sets of requirements, including their relevance, necessity, and the possible solutions that would be necessary for establishing a feasible multi-source forest health monitoring network for the 21st century. Namely, these requirements are: (1) understanding the effects of multiple stressors on forest health; (2) using remote sensing (RS) approaches to monitor forest health; (3) coupling different monitoring approaches; (4) using data science as a bridge between complex and multidimensional big forest health (FH) data; and (5) a future multi-source forest health monitoring network. It became apparent that no existing monitoring approach, technique, model, or platform is sufficient on its own to monitor, model, forecast, or assess forest health and its resilience. In order to advance the development of a multi-source forest health monitoring network, we argue that in order to gain a better understanding of forest health in our complex world, it would be conducive to implement the concepts of data science with the components: (i) digitalization; (ii) standardization with metadata management after the FAIR (Findability, Accessibility, Interoperability, and Reusability) principles; (iii) Semantic Web; (iv) proof, trust, and uncertainties; (v) tools for data science analysis; and (vi) easy tools for scientists, data managers, and stakeholders for decision-making support.
We have investigated the photodynamics of \(\beta\)-D-glucose employing our field-induced surface hopping method (FISH), which allows us to simulate the coupled electron-nuclear dynamics, including explicitly nonadiabatic effects and light-induced excitation. Our results reveal that from the initially populated S\(_{1}\) and S\(_{2}\) states, glucose returns nonradiatively to the ground state within about 200 fs. This takes place mainly via conical intersections (CIs) whose geometries
in most cases involve the elongation of a single O-H bond, while in some instances ring-opening due to dissociation of a C-O bond is observed. Experimentally, excitation to a distinct excited electronic state is improbable due to the presence of a dense manifold of states bearing similar oscillator strengths. Our FISH simulations explicitly including a UV laser pulse of 6.43 eV photon energy reveals that after initial excitation the population is almost equally spread over several close-lying electronic states. This is followed by a fast nonradiative decay on the time scale of 100-200 fs, with the final return to the ground state proceeding via the S\(_{1}\) state through the same types of CIs as observed in the field-free simulations.
This paper proposes a 3-D local pose estimation system for a small Unmanned Aerial Vehicle (UAV) with a weight limit of 200 g and a very small footprint of 10 cm×10cm. The system is realized by fusing 3-D position estimations from an Ultra-Wide Band (UWB) transceiver network with Inertial Measurement Unit (IMU) sensor data and data from a barometric pressure sensor. The 3-D position from the UWB network is estimated using Multi-Dimensional Scaling (MDS) and range measurements between the transceivers. The range measurements are obtained using Double-Sided Two-Way Ranging (DS-TWR), thus eliminating the need for an additional clock synchronization mechanism. The sensor fusion is accomplished using a loosely coupled Extended Kalman Filter (EKF) architecture. Extensive evaluation of the proposed system shows that a position accuracy with a Root-Mean-Square Error (RMSE) of 0.20cm can be obtained. The orientation angle can be estimated with an RMSE of 1.93°.