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Identifying urban pluvial flood-prone areas is necessary but the application of two-dimensional hydrodynamic models is limited to small areas. Data-driven models have been showing their ability to map flood susceptibility but their application in urban pluvial flooding is still rare. A flood inventory (4333 flooded locations) and 11 factors which potentially indicate an increased hazard for pluvial flooding were used to implement convolutional neural network (CNN), artificial neural network (ANN), random forest (RF) and support vector machine (SVM) to: (1) Map flood susceptibility in Berlin at 30, 10, 5, and 2 m spatial resolutions. (2) Evaluate the trained models' transferability in space. (3) Estimate the most useful factors for flood susceptibility mapping. The models' performance was validated using the Kappa, and the area under the receiver operating characteristic curve (AUC). The results indicated that all models perform very well (minimum AUC = 0.87 for the testing dataset). The RF models outperformed all other models at all spatial resolutions and the RF model at 2 m spatial resolution was superior for the present flood inventory and predictor variables. The majority of the models had a moderate performance for predictions outside the training area based on Kappa evaluation (minimum AUC = 0.8). Aspect and altitude were the most influencing factors on the image-based and point-based models respectively. Data-driven models can be a reliable tool for urban pluvial flood susceptibility mapping wherever a reliable flood inventory is available.
Large-scale databases that report the inhibitory capacities of many combinations of candidate drug compounds and cultivated cancer cell lines have driven the development of preclinical drug-sensitivity models based on machine learning. However, cultivated cell lines have devolved from human cancer cells over years or even decades under selective pressure in culture conditions. Moreover, models that have been trained on in vitro data cannot account for interactions with other types of cells. Drug-response data that are based on patient-derived cell cultures, xenografts, and organoids, on the other hand, are not available in the quantities that are needed to train high-capacity machine-learning models. We found that pre-training deep neural network models of drug sensitivity on in vitro drug-sensitivity databases before fine-tuning the model parameters on patient-derived data improves the models’ accuracy and improves the biological plausibility of the features, compared to training only on patient-derived data. From our experiments, we can conclude that pre-trained models outperform models that have been trained on the target domains in the vast majority of cases.
Large-scale databases that report the inhibitory capacities of many combinations of candidate drug compounds and cultivated cancer cell lines have driven the development of preclinical drug-sensitivity models based on machine learning. However, cultivated cell lines have devolved from human cancer cells over years or even decades under selective pressure in culture conditions. Moreover, models that have been trained on in vitro data cannot account for interactions with other types of cells. Drug-response data that are based on patient-derived cell cultures, xenografts, and organoids, on the other hand, are not available in the quantities that are needed to train high-capacity machine-learning models. We found that pre-training deep neural network models of drug sensitivity on in vitro drug-sensitivity databases before fine-tuning the model parameters on patient-derived data improves the models’ accuracy and improves the biological plausibility of the features, compared to training only on patient-derived data. From our experiments, we can conclude that pre-trained models outperform models that have been trained on the target domains in the vast majority of cases.
Background
Animal personality has emerged as a key concept in behavioral ecology. While many studies have demonstrated the influence of personality traits on behavioral patterns, its quantification, especially in wild animal populations, remains a challenge. Only a few studies have established a link between personality and recurring movements within home ranges, although these small-scale movements are of key importance for identifying ecological interactions and forming individual niches. In this regard, differences in space use among individuals might reflect different exploration styles between behavioral types along the shy-bold continuum.
Methods
We assessed among-individual differences in behavior in the European hare (Lepus europaeus), a characteristic mammalian herbivore in agricultural landscapes using a standardized box emergence test for captive and wild hares. We determined an individuals’ degree of boldness by measuring the latencies of behavioral responses in repeated emergence tests in captivity. During capture events of wild hares, we conducted a single emergence test and recorded behavioral responses proven to be stable over time in captive hares. Applying repeated novel environment tests in a near-natural enclosure, we further quantified aspects of exploration and activity in captive hares. Finally, we investigated whether and how this among-individual behavioral variation is related to general activity and space use in a wild hare population. Wild and captive hares were treated similarly and GPS-collared with internal accelerometers prior to release to the wild or the outdoor enclosure, respectively. General activity was quantified as overall dynamic body acceleration (ODBA) obtained from accelerometers. Finally, we tested whether boldness explained variation in (i) ODBA in both settings and (ii) variation in home ranges and core areas across different time scales of GPS-collared hares in a wild population.
Results
We found three behavioral responses to be consistent over time in captive hares. ODBA was positively related to boldness (i.e., short latencies to make first contact with the new environment) in both captive and wild hares. Space use in wild hares also varied with boldness, with shy individuals having smaller core areas and larger home ranges than bold conspecifics (yet in some of the parameter space, this association was just marginally significant).
Conclusions
Against our prediction, shy individuals occupied relatively large home ranges but with small core areas. We suggest that this space use pattern is due to them avoiding risky, and energy-demanding competition for valuable resources. Carefully validated, activity measurements (ODBA) from accelerometers provide a valuable tool to quantify aspects of animal personality along the shy-bold continuum remotely. Without directly observing—and possibly disturbing—focal individuals, this approach allows measuring variability in animal personality, especially in species that are difficult to assess with experiments. Considering that accelerometers are often already built into GPS units, we recommend activating them at least during the initial days of tracking to estimate individual variation in general activity and, if possible, match them with a simple novelty experiment. Furthermore, information on individual behavioral types will help to facilitate mechanistic understanding of processes that drive spatial and ecological dynamics in heterogeneous landscapes.
Background
Animal personality has emerged as a key concept in behavioral ecology. While many studies have demonstrated the influence of personality traits on behavioral patterns, its quantification, especially in wild animal populations, remains a challenge. Only a few studies have established a link between personality and recurring movements within home ranges, although these small-scale movements are of key importance for identifying ecological interactions and forming individual niches. In this regard, differences in space use among individuals might reflect different exploration styles between behavioral types along the shy-bold continuum.
Methods
We assessed among-individual differences in behavior in the European hare (Lepus europaeus), a characteristic mammalian herbivore in agricultural landscapes using a standardized box emergence test for captive and wild hares. We determined an individuals’ degree of boldness by measuring the latencies of behavioral responses in repeated emergence tests in captivity. During capture events of wild hares, we conducted a single emergence test and recorded behavioral responses proven to be stable over time in captive hares. Applying repeated novel environment tests in a near-natural enclosure, we further quantified aspects of exploration and activity in captive hares. Finally, we investigated whether and how this among-individual behavioral variation is related to general activity and space use in a wild hare population. Wild and captive hares were treated similarly and GPS-collared with internal accelerometers prior to release to the wild or the outdoor enclosure, respectively. General activity was quantified as overall dynamic body acceleration (ODBA) obtained from accelerometers. Finally, we tested whether boldness explained variation in (i) ODBA in both settings and (ii) variation in home ranges and core areas across different time scales of GPS-collared hares in a wild population.
Results
We found three behavioral responses to be consistent over time in captive hares. ODBA was positively related to boldness (i.e., short latencies to make first contact with the new environment) in both captive and wild hares. Space use in wild hares also varied with boldness, with shy individuals having smaller core areas and larger home ranges than bold conspecifics (yet in some of the parameter space, this association was just marginally significant).
Conclusions
Against our prediction, shy individuals occupied relatively large home ranges but with small core areas. We suggest that this space use pattern is due to them avoiding risky, and energy-demanding competition for valuable resources. Carefully validated, activity measurements (ODBA) from accelerometers provide a valuable tool to quantify aspects of animal personality along the shy-bold continuum remotely. Without directly observing—and possibly disturbing—focal individuals, this approach allows measuring variability in animal personality, especially in species that are difficult to assess with experiments. Considering that accelerometers are often already built into GPS units, we recommend activating them at least during the initial days of tracking to estimate individual variation in general activity and, if possible, match them with a simple novelty experiment. Furthermore, information on individual behavioral types will help to facilitate mechanistic understanding of processes that drive spatial and ecological dynamics in heterogeneous landscapes.
The importance of carbohydrate structures is enormous due to their ubiquitousness in our lives. The development of so-called glycomaterials is the result of this tremendous significance. These are not exclusively used for research into fundamental biological processes, but also, among other things, as inhibitors of pathogens or as drug delivery systems. This work describes the development of glycomaterials involving the synthesis of glycoderivatives, -monomers and -polymers. Glycosylamines were synthesized as precursors in a single synthesis step under microwave irradiation to significantly shorten the usual reaction time. Derivatization at the anomeric position was carried out according to the methods developed by Kochetkov and Likhorshetov, which do not require the introduction of protecting groups. Aminated saccharide structures formed the basis for the synthesis of glycomonomers in β-configuration by methacrylation. In order to obtain α-Man-based monomers for interactions with certain α-Man-binding lectins, a monomer synthesis by Staudinger ligation was developed in this work, which also does not require protective groups. Modification of the primary hydroxyl group of a saccharide was accomplished by enzyme-catalyzed synthesis. Ribose-containing cytidine was transesterified using the lipase Novozym 435 and microwave irradiation. The resulting monomer synthesis was optimized by varying the reaction partners. To create an amide bond instead of an ester bond, protected cytidine was modified by oxidation followed by amide coupling to form the monomer. This synthetic route was also used to isolate the monomer from its counterpart guanosine. After obtaining the nucleoside-based monomers, they were block copolymerized using the RAFT method. Pre-synthesized pHPMA served as macroCTA to yield cytidine- or guanosine-containing block copolymer. These isolated block copolymers were then investigated for their self-assembly behavior using UV-Vis, DLS and SEM to serve as a potential thermoresponsive drug delivery system.
Insight by de—sign
(2023)
The calculus of design is a diagrammatic approach towards the relationship between design and insight. The thesis I am evolving is that insights are not discovered, gained, explored, revealed, or mined, but are operatively de—signed. The de in design neglects the contingency of the space towards the sign. The — is the drawing of a distinction within the operation. Space collapses through the negativity of the sign; the command draws a distinction that neglects the space for the form's sake. The operation to de—sign is counterintuitively not the creation of signs, but their removal, the exclusion of possible sign propositions of space. De—sign is thus an act of exclusion; the possibilities of space are crossed into form.
Diabetes is hallmarked by high blood glucose levels, which cause progressive generalised vascular damage, leading to microvascular and macrovascular complications. Diabetes-related complications cause severe and prolonged morbidity and are a major cause of mortality among people with diabetes. Despite increasing attention to risk factors of type 2 diabetes, existing evidence is scarce or inconclusive regarding vascular complications and research investigating both micro- and macrovascular complications is lacking. This thesis aims to contribute to current knowledge by identifying risk factors – mainly related to lifestyle – of vascular complications, addressing methodological limitations of previous literature and providing comparative data between micro- and macrovascular complications.
To address this overall aim, three specific objectives were set. The first was to investigate the effects of diabetes complication burden and lifestyle-related risk factors on the incidence of (further) complications. Studies suggest that diabetes complications are interrelated. However, they have been studied mainly independently of individuals’ complication burden. A five-state time-to-event model was constructed to examine the longitudinal patterns of micro- (kidney disease, neuropathy and retinopathy) and macrovascular complications (myocardial infarction and stroke) and their association with the occurrence of subsequent complications. Applying the same model, the effect of modifiable lifestyle factors, assessed alone and in combination with complication load, on the incidence of diabetes complications was studied. The selected lifestyle factors were body mass index (BMI), waist circumference, smoking status, physical activity, and intake of coffee, red meat, whole grains, and alcohol. Analyses were conducted in a cohort of 1199 participants with incident type 2 diabetes from the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam, who were free of vascular complications at diabetes diagnosis. During a median follow-up time of 11.6 years, 96 cases of macrovascular complications (myocardial infarction and stroke) and 383 microvascular complications (kidney disease, neuropathy and retinopathy) were identified. In multivariable-adjusted models, the occurrence of a microvascular complication was associated with a higher incidence of further micro- (Hazard ratio [HR] 1.90; 95% Confidence interval [CI] 0.90, 3.98) and macrovascular complications (HR 4.72; 95% CI 1.25, 17.68), compared with persons without a complication burden. In addition, participants who developed a macrovascular event had a twofold higher risk of future microvascular complications (HR 2.26; 95% CI 1.05, 4.86). The models were adjusted for age, sex, state duration, education, lifestyle, glucose-lowering medication, and pre-existing conditions of hypertension and dyslipidaemia. Smoking was positively associated with macrovascular disease, while an inverse association was observed with higher coffee intake. Whole grain and alcohol intake were inversely associated with microvascular complications, and a U-shaped association was observed for red meat intake. BMI and waist circumference were positively associated with microvascular events. The associations between lifestyle factors and incidence of complications were not modified by concurrent complication burden, except for red meat intake and smoking status, where the associations were attenuated among individuals with a previous complication.
The second objective was to perform an in-depth investigation of the association between BMI and BMI change and risk of micro- and macrovascular complications. There is an ongoing debate on the association between obesity and risk of macrovascular and microvascular outcomes in type 2 diabetes, with studies suggesting a protective effect among people with overweight or obesity. These findings, however, might be limited due to suboptimal control for smoking, pre-existing chronic disease, or short-follow-up. After additional exclusion of persons with cancer history at diabetes onset, the associations between pre-diagnosis BMI and relative annual change between pre- and post-diagnosis BMI and incidence of complications were evaluated in multivariable-adjusted Cox models. The analyses were adjusted for age, sex, education, smoking status and duration, physical activity, alcohol consumption, adherence to the Mediterranean diet, and family history of diabetes and cardiovascular disease (CVD). Among 1083 EPIC-Potsdam participants, 85 macrovascular and 347 microvascular complications were identified during a median follow-up period of 10.8 years. Higher pre-diagnosis BMI was associated with an increased risk of total microvascular complications (HR per 5 kg/m2 1.21; 95% CI 1.07, 1.36), kidney disease (HR 1.39; 95% CI 1.21, 1.60) and neuropathy (HR 1.12; 95% CI 0.96, 1.31); but no association was observed for macrovascular complications (HR 1.05; 95% CI 0.81, 1.36). Effect modification was not evident by sex, smoking status, or age groups. In analyses according to BMI change categories, BMI loss of more than 1% indicated a decreased risk of total microvascular complications (HR 0.62; 95% CI 0.47, 0.80), kidney disease (HR 0.57; 95% CI 0.40, 0.81) and neuropathy (HR 0.73; 95% CI 0.52, 1.03), compared with participants with a stable BMI. No clear association was observed for macrovascular complications (HR 1.04; 95% CI 0.62, 1.74). The impact of BMI gain on diabetes-related vascular disease was less evident. Associations were consistent across strata of age, sex, pre-diagnosis BMI, or medication but appeared stronger among never-smokers than current or former smokers.
The last objective was to evaluate whether individuals with a high-risk profile for diabetes and cardiovascular disease (CVD) also have a greater risk of complications. Within the EPIC-Potsdam study, two accurate prognostic tools were developed, the German Diabetes Risk Score (GDRS) and the CVD Risk Score (CVDRS), which predict the 5-year type 2 diabetes risk and 10-year CVD risk, respectively. Both scores provide a non-clinical and clinical version. Components of the risk scores include age, sex, waist circumference, prevalence of hypertension, family history of diabetes or CVD, lifestyle factors, and clinical factors (only in clinical versions). The association of the risk scores with diabetes complications and their discriminatory performance for complications were assessed. In crude Cox models, both versions of GDRS and CVDRS were positively associated with macrovascular complications and total microvascular complications, kidney disease and neuropathy. Higher GDRS was also associated with an elevated risk of retinopathy. The discrimination of the scores (clinical and non-clinical) was poor for all complications, with the C-index ranging from 0.58 to 0.66 for macrovascular complications and from 0.60 to 0.62 for microvascular complications.
In conclusion, this work illustrates that the risk of complication development among individuals with type 2 diabetes is related to the existing complication load, and attention should be given to regular monitoring for future complications. It underlines the importance of weight management and adherence to healthy lifestyle behaviours, including high intake of whole grains, moderation in red meat and alcohol consumption and avoidance of smoking to prevent major diabetes-associated complications, regardless of complication burden. Risk scores predictive for type 2 diabetes and CVD were related to elevated risks of complications. By optimising several lifestyle and clinical factors, the risk score can be improved and may assist in lowering complication risk.
Among the multitude of geomorphological processes, aeolian shaping processes are of special character, Pedogenic dust is one of the most important sources of atmospheric aerosols and therefore regarded as a key player for atmospheric processes. Soil dust emissions, being complex in composition and properties, influence atmospheric processes and air quality and has impacts on other ecosystems. In this because even though their immediate impact can be considered low (exceptions exist), their constant and large-scale force makes them a powerful player in the earth system. dissertation, we unravel a novel scientific understanding of this complex system based on a holistic dataset acquired during a series of field experiments on arable land in La Pampa, Argentina. The field experiments as well as the generated data provide information about topography, various soil parameters, the atmospheric dynamics in the very lower atmosphere (4m height) as well as measurements regarding aeolian particle movement across a wide range of particle size classes between 0.2μm up to the coarse sand.
The investigations focus on three topics: (a) the effects of low-scale landscape structures on aeolian transport processes of the coarse particle fraction, (b) the horizontal and vertical fluxes of the very fine particles and (c) the impact of wind gusts on particle emissions.
Among other considerations presented in this thesis, it could in particular be shown, that even though the small-scale topology does have a clear impact on erosion and deposition patterns, also physical soil parameters need to be taken into account for a robust statistical modelling of the latter. Furthermore, specifically the vertical fluxes of particulate matter have different characteristics for the particle size classes. Finally, a novel statistical measure was introduced to quantify the impact of wind gusts on the particle uptake and its application on the provided data set. The aforementioned measure shows significantly increased particle concentrations during points in time defined as gust event.
With its holistic approach, this thesis further contributes to the fundamental understanding of how atmosphere and pedosphere are intertwined and affect each other.
The increasing demand for energy in the current technological era and the recent political decisions about giving up on nuclear energy diverted humanity to focus on alternative environmentally friendly energy sources like solar energy. Although silicon solar cells are the product of a matured technology, the search for highly efficient and easily applicable materials is still ongoing. These properties made the efficiency of halide perovskites comparable with silicon solar cells for single junctions within a decade of research. However, the downside of halide perovskites are poor stability and lead toxicity for the most stable ones.
On the other hand, chalcogenide perovskites are one of the most promising absorber materials for the photovoltaic market, due to their elemental abundance and chemical stability against moisture and oxygen. In the search of the ultimate solar absorber material, combining the good optoelectronic properties of halide perovskites with the stability of chalcogenides could be the promising candidate.
Thus, this work investigates new techniques for the synthesis and design of these novel chalcogenide perovskites, that contain transition metals as cations, e.g., BaZrS3, BaHfS3, EuZrS3, EuHfS3 and SrHfS3. There are two stages in the deposition techniques of this study: In the first stage, the binary compounds are deposited via a solution processing method. In the second stage, the deposited materials are annealed in a chalcogenide atmosphere to form the perovskite structure by using solid-state reactions.
The research also focuses on the optimization of a generalized recipe for a molecular ink to deposit precursors of chalcogenide perovskites with different binaries. The implementation of the precursor sulfurization resulted in either binaries without perovskite formation or distorted perovskite structures, whereas some of these materials are reported in the literature as they are more favorable in the needle-like non-perovskite configuration.
Lastly, there are two categories for the evaluation of the produced materials: The first category is about the determination of the physical properties of the deposited layer, e.g., crystal structure, secondary phase formation, impurities, etc. For the second category, optoelectronic properties are measured and compared to an ideal absorber layer, e.g., band gap, conductivity, surface photovoltage, etc.