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The fast and accurate yield estimates with the increasing availability and variety of global satellite products and the rapid development of new algorithms remain a goal for precision agriculture and food security. However, the consistency and reliability of suitable methodologies that provide accurate crop yield outcomes still need to be explored. The study investigates the coupling of crop modeling and machine learning (ML) to improve the yield prediction of winter wheat (WW) and oil seed rape (OSR) and provides examples for the Free State of Bavaria (70,550 km2), Germany, in 2019. The main objectives are to find whether a coupling approach [Light Use Efficiency (LUE) + Random Forest (RF)] would result in better and more accurate yield predictions compared to results provided with other models not using the LUE. Four different RF models [RF1 (input: Normalized Difference Vegetation Index (NDVI)), RF2 (input: climate variables), RF3 (input: NDVI + climate variables), RF4 (input: LUE generated biomass + climate variables)], and one semi-empiric LUE model were designed with different input requirements to find the best predictors of crop monitoring. The results indicate that the individual use of the NDVI (in RF1) and the climate variables (in RF2) could not be the most accurate, reliable, and precise solution for crop monitoring; however, their combined use (in RF3) resulted in higher accuracies. Notably, the study suggested the coupling of the LUE model variables to the RF4 model can reduce the relative root mean square error (RRMSE) from −8% (WW) and −1.6% (OSR) and increase the R
2 by 14.3% (for both WW and OSR), compared to results just relying on LUE. Moreover, the research compares models yield outputs by inputting three different spatial inputs: Sentinel-2(S)-MOD13Q1 (10 m), Landsat (L)-MOD13Q1 (30 m), and MOD13Q1 (MODIS) (250 m). The S-MOD13Q1 data has relatively improved the performance of models with higher mean R
2 [0.80 (WW), 0.69 (OSR)], and lower RRMSE (%) (9.18, 10.21) compared to L-MOD13Q1 (30 m) and MOD13Q1 (250 m). Satellite-based crop biomass, solar radiation, and temperature are found to be the most influential variables in the yield prediction of both crops.
The landscape of today’s programming languages is manifold. With the diversity of applications, the difficulty of adequately addressing and specifying the used programs increases. This often leads to newly designed and implemented domain-specific languages. They enable domain experts to express knowledge in their preferred format, resulting in more readable and concise programs. Due to its flexible and declarative syntax without reserved keywords, the logic programming language Prolog is particularly suitable for defining and embedding domain-specific languages.
This thesis addresses the questions and challenges that arise when integrating domain-specific languages into Prolog. We compare the two approaches to define them either externally or internally, and provide assisting tools for each. The grammar of a formal language is usually defined in the extended Backus–Naur form. In this work, we handle this formalism as a domain-specific language in Prolog, and define term expansions that allow to translate it into equivalent definite clause grammars. We present the package library(dcg4pt) for SWI-Prolog, which enriches them by an additional argument to automatically process the term’s corresponding parse tree. To simplify the work with definite clause grammars, we visualise their application by a web-based tracer.
The external integration of domain-specific languages requires the programmer to keep the grammar, parser, and interpreter in sync. In many cases, domain-specific languages can instead be directly embedded into Prolog by providing appropriate operator definitions. In addition, we propose syntactic extensions for Prolog to expand its expressiveness, for instance to state logic formulas with their connectives verbatim. This allows to use all tools that were originally written for Prolog, for instance code linters and editors with syntax highlighting. We present the package library(plammar), a standard-compliant parser for Prolog source code, written in Prolog. It is able to automatically infer from example sentences the required operator definitions with their classes and precedences as well as the required Prolog language extensions. As a result, we can automatically answer the question: Is it possible to model these example sentences as valid Prolog clauses, and how?
We discuss and apply the two approaches to internal and external integrations for several domain-specific languages, namely the extended Backus–Naur form, GraphQL, XPath, and a controlled natural language to represent expert rules in if-then form. The created toolchain with library(dcg4pt) and library(plammar) yields new application opportunities for static Prolog source code analysis, which we also present.
Facing Enemies. Modulation of Revenge Interactions based on Opponent State Indicators of Suffering
(2023)
Research on revenge often treats vengeful acts as singular one-way experiences, an approach which fails to account for the social nature and functions of revenge. This dissertation aims to integrate emotional punishment reactions into dynamic revenge sequences to investigate the affective and cognitive consequences of revenge within a social interaction.
Exacting revenge can evoke intense affective consequences, from feelings of guilt to the genuine enjoyment of the suffering of others. In Chapter 2, affective responses towards suffering opponents and the regulation of aggression based on the appraisal of distinct suffering indicators were investigated. Results indicate that the observation of opponent pain evokes positive affect (measured via facial muscle contractions during the observation), which is followed by a downregulation of subsequent punishment. Both, positive affective reactions and the downregulation of punishment, were only observed following pain and not sadness expressions. Empathic distress, indexed by negative affective reactions, was only present following the observation of pain in non-provoking opponents. Showcasing the modulation of empathy related processes due to provocation and competition.
In Chapter 3, a significant escalation of punishment, when being confronted with Schadenfreude, was observed. Results are interpreted as supporting the assumption that opponent monitoring processes inform subsequent action selection. The observation of opponent smiles led to imitation behavior (facial mimicry), which was partially attenuated due to previous provocation. The different functions of smile mimicry in the context of the aggressive competitive setting are discussed as containing simulation aspects (to aid in opponent understanding) and as a potential mirroring of dominance gestures, to avoid submission.
In an additional series of studies, which are presented in Chapter 4, changes in memory of opponent faces following vengeful encounters were measured. Based on provocation, and punishment outcomes (pain & anger), face memory was distorted, resulting in more positive representations of opponents that expressed pain. These results are discussed as evidence of the impact of outcome appraisals in the formation of opponent representations and are theorized to aid empathy avoidance in future interactions.
The comparison of desired and observed opponent states, is theorized to result in appraisals of the punishment outcomes, which evoke affective states, inform the action selection of subsequent punishments, and are integrated into the representation of the opponent in memory.
Overall, the results indicate that suffering cues that are congruent with the chosen punishment action are appraised as positive, evoking an increase in positive affect. The emergence of positive affect during the observation of successful aggressive actions supports recent theories about the chronification of aggressive behavior based on reinforcement learning. To allow positive affect to emerge, affective empathic responses, such as distress, are theorized to be suppressed to facilitate the goal attainment process. The suffering of the opponent constitutes the proximate goal during revenge taking, which highlights the importance of a theoretical differentiation of proximate and ultimate goals in revenge to allow for a deeper understanding of the underlying motives of complex revenge behavior.
Mammalian phoshoglycolate phosphatase (PGP, also known as AUM) belongs to the ubiquitous HAD superfamily of phosphatases. As several other members of HAD phosphatases, the Mg2+-dependent dephosphorylation is conducted via a nucleophilic attack from a conserved aspartate residue in the catalytic cleft. The protein structure of PGP could not yet be solved entirely. Only a hybrid consisting of the PGP cap and the PDXP core (pyridoxal phosphatase, closest enzyme paralog) was crystallizable so far. PGP is able to efficiently dephosphorylate 2-phosphoglycolate, 2-phospho-L-lactate, 4-phospho-D-erythronate, and glycerol-3-phosphate in vitro which makes them likely physiological substrates. The first three substrates can be derived from metabolic side reactions (during glycolysis) and inhibit key enzymes in glycolysis and pentose phosphate pathway, the latter is situated at the intersection between glycolysis and lipogenesis. 2-phosphoglycolate can also be released in the context of repair of oxidative DNA damage. The activity of purified PGP can be reversibly inhibited by oxidation - physiologically likely in association with epidermal growth factor (EGF) signal transduction. In fact, an association between persistently lacking PGP activity (via downregulation) and the presence of hyperphosphorylated proteins after EGF stimulation has been identified. Reversible oxidation and transient inactivation of PGP may be particularly important for short-term and feedback regulatory mechanisms (as part of the EGF signaling). Furthermore, cellular proliferation in PGP downregulated cells is constantly reduced. Whole-body PGP inactivation in mice is embryonically lethal. Despite the many well-known features and functions, the knowledge about PGP is still incomplete.
In the present work the influence of reactive oxygen species (ROS) on PGP activity in cells und a possible connection between oxidative stress and the proliferation deficit of PGP downregulated cells was investigated. For the experiments, a spermatogonial cell line was used (due to the high PGP expression in testis). PGP activity can be reversibly inhibited in cellular lysates by H2O2 (as a ROS representative). Reversible oxidation could thus indeed be physiologically important. More oxidative DNA damage (by bleomycin) showed no PGP-dependent effects here. EGF stimulation (as an inducer of transient and well-controlled ROS production), low concentrations of menadione (as an oxidant) and N-acetylcysteine (as an antioxidant) were able to approximate the proliferation rate in PGP downregulated cells to that of control cells. The redox regulation of PGP could thus have an influence on cellular proliferation as a feedback mechanism - a mechanism that could not take place in PGP downregulated cells. However, the connections are probably even more complex and cannot be elucidated by a sole examination of the proliferation rate. The present results can thus only be regarded as preliminary experiments.
For a better understanding of the features and functions of PGP, this work then focused on specific regulation of enzyme activity by pharmacologically applicable small molecules. Four potent inhibitors had previously been identified in a screening campaign. In this work, three of these four inhibiting compounds could be further characterized in experiments with highly purified, recombinant murine and human PGP. Compounds #2 and #9 showed competitive inhibition properties with a markedly rising KM value with little or no change in vmax. The results were consistent for all tested protein variants: the murine and the human PGP as well as a PGP/PDXP hybrid protein. Compound #1 was the most potent and interesting PGP-inhibitory molecule: less change in KM and a constant decrease in vmax as well as a lower impact on the PGP/PDXP hybrid hint at a mixed mode of inhibition as a combination of competitive and non-competitive inhibition. The characterization of the potential inhibitors can serve as a basis for further structural analysis and studies on the complex physiological role of PGP.
Emotional-associative learning processes such as fear conditioning and extinction are highly relevant to not only the development and maintenance of anxiety disorders (ADs), but also to their treatment. Extinction, as the laboratory analogue to behavioral exposure, is assumed a core process underlying the treatment of ADs. Although exposure-based treatments are highly effective for the average patient suffering from an AD, there remains a gap in treatment efficacy with over one third of patients failing to achieve clinically significant symptom relief. There is ergo a pressing need for intensified research regarding the underlying neural mechanisms of aberrant emotional-associative learning processes and the neurobiological moderators of treatment (non-)response in ADs.
The current thesis focuses on different applications of the fundamental principles of fear conditioning and extinction by using two example cases of ADs from two different multicenter trials. First, we targeted alterations in fear acquisition, extinction, and its recall as a function of psychopathology in panic disorder (PD) patients compared to healthy subjects using fMRI. Second, exposure-based therapy and pre-treatment patient characteristics exerting a moderating influence on this essential learning process later on (i.e. treatment outcome) were examined using multimodal functional and structural neuroimaging in spider phobia.
We observed aberrations in emotional-associative learning processes in PD patients compared to healthy subjects indicated by an accelerated fear acquisition and an attenuated extinction recall. Furthermore, pre-treatment differences related to defensive, regulatory, attentional, and perceptual processes may exert a moderating influence on treatment outcome to behavioral exposure in spider phobia. Although the current results need further replication, on an integrative meta level, results point to a hyperactive defensive network system and deficient emotion regulation processes (including extinction processes) and top-down control in ADs. This speaks in favor of transdiagnostic deficits in important functional domains in ADs.
Deficits in transdiagnostic domains such as emotion regulation processes could be targeted by enhancing extinction learning or by means of promising tools like neurofeedback. The detection of pre-treatment clinical response moderators, for instance via machine learning frameworks, may help in supporting clinical decision making on individually tailored treatment approaches or, respectively, to avoid ineffective treatment and its related financial costs. In the long run, the identification of neurobiological markers which are capable of detecting non-responders a priori represents an ultimate goal.
To study coisotropic reduction in the context of deformation quantization we introduce constraint manifolds and constraint algebras as the basic objects encoding the additional information needed to define a reduction. General properties of various categories of constraint objects and their compatiblity with reduction are examined. A constraint Serre-Swan theorem, identifying constraint vector bundles with certain finitely generated projective constraint modules, as well as a constraint symbol calculus are proved. After developing the general deformation theory of constraint algebras, including constraint Hochschild cohomology and constraint differential graded Lie algebras, the second constraint Hochschild cohomology for the constraint algebra of functions on a constraint flat space is computed.
Despite accounting for only a small proportion of all skin cancers, malignant melanoma
displays a serious health risk with increasing incidence and high mortality rate. Fortunately,
advances in the treatment of malignant melanoma now prolong survival and enhance response
and treatment efficacy. Established biomarkers help evaluate disease progression and
facilitate choosing appropriate and individual treatment options. However, the need for easily
accessible and reliable biomarkers is rising to predict patient-specific clinical outcome.
Eosinophil infiltration into the tumor and high peripheral eosinophil counts prior and during
treatment have been associated with better response in patients for various cancer entities,
including melanoma. An analysis of a heterogeneous study cohort reported high serum ECP
levels in non-responders. Hence, eosinophil frequency and serum ECP as a soluble
eosinophil-secreted mediator were suggested as prognostic biomarkers in melanoma. We
examined whether melanoma patients treated with first-line targeted therapy could also benefit
from the effects of eosinophils. In total, 243 blood and serum samples from patients with
advanced melanoma were prospectively and retrospectively collected before and after drug
initiation. To link eosinophil function to improved clinical outcome, soluble serum markers and
peripheral blood counts were used for correlative studies using a homogeneous study cohort.
In addition, functional and phenotypical characterizations provided insights into the expression
profile and activity of freshly isolated eosinophils, including comparisons between patients and
healthy donors.
Our data showed a significant correlation between high pre-treatment blood eosinophil counts
and improved response to targeted therapy and by trend to combinatorial immunotherapy in
patients with metastatic melanoma. In accordance with previous studies our results links
eosinophil blood counts to better response in melanoma patients. High pre-treatment ECP
serum concentration correlated with response to immunotherapy but not to targeted therapy.
Eosinophils from healthy donors and patients showed functional and phenotypical similarities.
Functional assays revealed a strong cytotoxic potential of blood eosinophils towards
melanoma cells in vitro, inducing apoptosis and necrosis. In addition, in vitro cytotoxicity was
an active process of peripheral eosinophils and melanoma cells with bidirectional features and
required close cell-cell interaction. The extent of cytotoxicity was dose-dependent and showed
susceptibility to changes in physical factors like adherence. Importantly, we provide evidence
of an additive tumoricidal function of eosinophils and combinatorial targeted therapy in vitro. In
summary, we give valuable insights into the complex and treatment-dependent role of
eosinophils in melanoma. As a result, our data support the suggestion of eosinophils and their
secreted mediators as potential prognostic biomarkers. It will take additional studies to
examine the molecular mechanisms that underlie our findings.
Stroke and myocardial infarction are the most prominent and severe consequences of pathological thrombus formation. For prevention and/or treatment of thrombotic events there is a variety of anti-coagulation and antiplatelet medication that all have one side effect in common: the increased risk of bleeding. To design drugs that only intervene in the unwanted aggregation process but do not disturb general hemostasis, it is crucial to decipher the exact clotting pathway which has not been fully understood yet. Platelet membrane receptors play a vital role in the clotting pathway and, thus, the aim of this work is to establish a method to elucidate the interactions, clustering, and reorganization of involved membrane receptors such as GPIIb/IIIa and GPIX as part of the GPIb-IX-V complex. The special challenges regarding visualizing membrane receptor interactions on blood platelets are the high abundancy of the first and the small size of the latter (1—3µm of diameter). The resolution limit of conventional fluorescence microscopy and even super-resolution approaches prevents the successful differentiation of densely packed receptors from one another. Here, this issue is approached with the combination of a recently developed technique called Expansion Microscopy (ExM). The image resolution of a conventional fluorescence microscope is enhanced by simply enlarging the sample physically and thus pulling the receptors apart from each other. This method requires a complex sample preparation and holds lots of obstacles such as variable or anisotropic expansion and low images contrast. To increase ExM accuracy and sensitivity for interrogating blood platelets, it needs optimized sample preparation as well as image analysis pipelines which are the main part of this thesis. The colocalization results show that either fourfold or tenfold expanded, resting platelets allow a clear distinction between dependent, clustered, and independent receptor organizations compared to unexpanded platelets.Combining dual-color Expansion and confocal fluorescence microscopy enables to image in the nanometer range identifying GPIIb/IIIa clustering in resting platelets – a pattern that may play a key role in the clotting pathway
Spinal muscular atrophy (SMA) is a genetic pediatric condition that affects lower motoneurons leading to their degeneration and muscle weakness. It is caused by homozygous loss or mutations in the Survival Motor Neuron 1 (SMN1) gene; however, the pathomechanism leading to motoneuron degeneration is not fully resolved. Cultured embryonic SMA motoneurons display axon elongation and differentiation defects accompanied by collapsed growth cones with a disturbed actin cytoskeleton. Intriguingly, motoneurons cultured from mice deficient for the Tropomyosin-kinase receptor B (TrkB), exhibit similar pathological features. Thus, the question arises whether SMA motoneurons suffer from defective Brain-derived neurotrophic factor (BDNF)/TrkB signaling and whether there is a link to the disturbed actin cytoskeleton. In the recent years, modifier genes such as Plastin 3 (PLS3) were shown to beneficially interfere with SMA pathology. Nevertheless, the mechanism of how the actin-bundler PLS3 counteracts SMN deficiency is not well understood. In this study, we investigated TrkB localization and its activation in cultured SMA motoneurons and neuromuscular junctions (NMJs). While TrkB levels are only mildly affected locally in axon terminals, BDNF-mediated TrkB phosphorylation was massively disturbed. The activity-dependent TrkB translocation to the cell surface and its activation via BDNF were shown to be Pls3-dependent processes, that can be abolished by knockdown of Pls3. In contrast, PLS3 overexpression in SMA motoneurons rescued the defects on morphological and functional level. In particular, the relocation of TrkB to the cell surface after BDNF-induced internalization is disturbed in SMA, which is based on an actin-dependent TrkB translocation defect from intracellular stores. Lastly, AAV9-mediated PLS3 overexpression in vivo in neonatal SMA mice provided further evidence for the capacity of PLS3 to modulate actin dynamics necessary for accurate BDNF/TrkB signaling. In conclusion, we provide a novel role for PLS3 in mediating proper alignment of transmembrane proteins as prerequisite for their appropriate functioning. Hence, PLS3 is required for a key process indispensable for the development and function of motoneurons even beyond the context of SMA.
Dietary fatty acids serve as objective biomarkers for the estimation of habitual diet mainly because biomarkers are free of memory bias or inaccuracies of food databases. The aim of the present work encompassed the implementation of a gas chromatographical method coupled with a mass spectrometrical and flame-ionization detector for analysis of fatty acid biomarkers in human biospecimens, their analytical determination and statistical evaluation in two different study populations and different biospecimens as well as the elaboration of adverse reactions to food ingredients with special focus on food allergies and food intolerances in the context of a possible implementation into an application for consumer health. The first aim was the identification of potential influence of fatty acid biomarkers on desaturase and elongase indexes (Δ9DI, Δ6DI, Δ5DI and ELOVLI5), which are factors in type 2 diabetes risk, in breast adipose tissue from healthy women. Influence of further variables on respective indexes was also investigated. 40 samples were investigated and potential variables were either collected by questionnaire or determined. Principle component analysis was applied for fatty acid biomarkers (PCdiet1, PCdiet2 and PCdiet3 representative for the dietary intake of vegetable oils/nuts, fish and partially hydrogenated vegetable oils), endogenous estrogens (PCE1) and oxysterols (PCOxy1). Multiple linear regression models were applied. Δ9DI and Δ6DI were influenced non-significantly and significantly negatively by PCdiet2 supporting a putative beneficial effect of vegetable oils and nuts on type 2 diabetes risk factors. ELOVLI5 and Δ5DI were influenced significantly and non-significantly positively by PCdiet1 supporting a putative beneficial effect of fish consumption on type 2 diabetes risk factors. On the other hand, PCdiet1 also significantly and non-significantly positively influenced Δ9DI and Δ6DI supporting a putative adverse effect of fish biomarkers on type 2 diabetes risk factors. The opposing influences of PCdiet1 suggesting an ambivalent role of dietary intake of fish on investigated indexes. Δ6DI was significantly positively influenced by PCdiet3 and number of pregnancies supporting a putative adverse effect of partially hydrogenated vegetable oils and pregnancies on type 2 diabetes risk factors. Lifestyle factors like smoking significantly and non-significantly influenced Δ9DI and Δ6DI putatively adversely. Δ5DI was influenced significantly positively by estrogen active drugs suggesting a putative beneficial effect on type 2 diabetes risk factors. It must be considered that a variation coefficient of up to 0.44 only explained 44% of variance of the respective indexes, suggesting other influencing factors might play a role. The second aim was the implementation of a gas chromatographical method coupled with a mass spectrometrical and flame-ionization detector for analysis of fatty acid biomarkers in human biospecimens. The method was optimized for separation and detection of 40 fatty acids. Mean recovery for tridecanoic acid was x(tridecanoic acid) = 90.51% and for nonadecanoic acid x(nonadecanoic acid) = 96.21%. Thus, there was no significant loss of fatty acids with shorter and longer carbon chains over the extraction process to be expected. Limit of detections were calculated in adipose tissue samples and ranged from 0.007 to 0.077% of the proportion of the respective fatty acid to total fatty acids. The third aim was the investigation if differentiation between breast glandular and adipose tissue had a relevant impact on the analysis of dietary fatty acid biomarkers or if contamination of breast glandular with breast adipose tissue and vice versa was neglectable for the analysis of dietary fatty acid biomarkers. No statistical significant differences were observed for all investigated fatty acid biomarkers (pentadecanoic-, heptadecanoic-, trans palmitoleic-, eicosapentaenoic-, docosahexaenoic-, linoleic and α-linolenic acid) between breast glandular and adipose tissue. Thus, differentiation between breast glandular and adipose tissue seems not to be necessary for the analysis of fatty acids serving as biomarkers for the intake of specific food groups. Potential influence of mixed breast tissue on fatty acid biomarkers analysis seems to be neglectable. The fourth aim was the determination of fatty acid biomarkers in adipose tissue in another study population from healthy participants. 27 adipose tissue samples were analyzed. Milk and ruminant fat biomarkers exhibited proportions of 0.47% for pentadecanoic acid, 0.34% for heptadecanoic acid and 0.25% for trans palmitoleic acid. Fish fatty acid biomarkers revealed proportions of 0.034% for eicosapentaenoic acid and 0.061% for docosahexaenoic acid. The mean proportion of vegetable oils and nuts biomarkers were 9.58% for linoleic acid and 0.48% for α-linolenic acid in all adipose tissues. Principle component analysis was applied for the fatty acid biomarkers to provide objective markers of habitual diet for this study population. PCdiet1 was mainly characterized by pentadecanoic acid, heptadecanoic acid and trans palmitoleic acid and therefore served as a principle component for the dietary intake of milk and ruminant fat. PCdiet2 and PCdiet3 only exhibited pattern for ω3 and ω6 fatty acids but not for dietary intake of specific food groups and could therefore not used as objective marker. PCdiet1, 2 and 3 explained 82.76% of variance. The last aim of this thesis was the elaboration of adverse reactions to food ingredients with special focus on food allergies and food intolerances in the context of a possible implementation into an application for consumer health. Scientific information on adverse reactions to food ingredients and trigger substances was provided in this thesis and possible implementation strategies were evaluated. For food allergens, which have regulatory requirements in the context of labelling, a strategy was elaborated, where it is necessary to provide information on the list of ingredients, the nexus ’contain’ and the respective food allergen as well as information on the name of the product. For food intolerances, which do not have regulatory requirements, limits were shown in the context of the application. If the elaborated food intolerances shall be implemented into the application, a professional dietary concept has to be developed for every food intolerance because of the complexity of the implementation.