Refine
Has Fulltext
- yes (308) (remove)
Year of publication
- 2021 (308) (remove)
Document Type
- Postprint (149)
- Doctoral Thesis (124)
- Working Paper (16)
- Monograph/Edited Volume (6)
- Master's Thesis (4)
- Article (3)
- Part of Periodical (3)
- Conference Proceeding (1)
- Habilitation Thesis (1)
- Other (1)
Language
- English (308) (remove)
Is part of the Bibliography
- yes (308) (remove)
Keywords
- Arabidopsis thaliana (4)
- Spektroskopie (4)
- climate change (4)
- embodied cognition (4)
- machine learning (4)
- spectroscopy (4)
- 20. Jahrhundert (3)
- 20th century (3)
- COVID-19 (3)
- Klimawandel (3)
Institute
- Institut für Biochemie und Biologie (42)
- Institut für Geowissenschaften (36)
- Institut für Physik und Astronomie (31)
- Hasso-Plattner-Institut für Digital Engineering GmbH (25)
- Institut für Chemie (21)
- Strukturbereich Kognitionswissenschaften (19)
- Department Psychologie (18)
- Institut für Umweltwissenschaften und Geographie (16)
- Center for Economic Policy Analysis (CEPA) (15)
- Extern (15)
Crochet is a popular handcraft all over the world. While other techniques such as knitting or weaving have received technical support over the years through machines, crochet is still a purely manual craft. Not just the act of crochet itself is manual but also the process of creating instructions for new crochet patterns, which is barely supported by domain specific digital solutions. This leads to unstructured and often also ambiguous and erroneous pattern instructions. In this report, we propose a concept to digitally represent crochet patterns. This format incorporates crochet techniques which allows domain specific support for crochet pattern designers during the pattern creation and instruction writing process. As contributions, we present a thorough domain analysis, the concept of a graph structure used as domain specific language to specify crochet patterns and a prototype of a projectional editor using the graph as representation format of patterns and a diagramming system to visualize them in 2D and 3D. By analyzing the domain, we learned about crochet techniques and pain points of designers in their pattern creation workflow. These insights are the basis on which we defined the pattern representation. In order to evaluate our concept, we built a prototype by which the feasibility of the concept is shown and we tested the software with professional crochet designers who approved of the concept.
We investigate models for incremental binary classification, an example for supervised online learning. Our starting point is a model for human and machine learning suggested by E.M.Gold.
In the first part, we consider incremental learning algorithms that use all of the available binary labeled training data in order to compute the current hypothesis. For this model, we observe that the algorithm can be assumed to always terminate and that the distribution of the training data does not influence learnability. This is still true if we pose additional delayable requirements that remain valid despite a hypothesis output delayed in time. Additionally, we consider the non-delayable requirement of consistent learning. Our corresponding results underpin the claim for delayability being a suitable structural property to describe and collectively investigate a major part of learning success criteria. Our first theorem states the pairwise implications or incomparabilities between an established collection of delayable learning success criteria, the so-called complete map. Especially, the learning algorithm can be assumed to only change its last hypothesis in case it is inconsistent with the current training data. Such a learning behaviour is called conservative.
By referring to learning functions, we obtain a hierarchy of approximative learning success criteria. Hereby we allow an increasing finite number of errors of the hypothesized concept by the learning algorithm compared with the concept to be learned. Moreover, we observe a duality depending on whether vacillations between infinitely many different correct hypotheses are still considered a successful learning behaviour. This contrasts the vacillatory hierarchy for learning from solely positive information.
We also consider a hypothesis space located between the two most common hypothesis space types in the nearby relevant literature and provide the complete map.
In the second part, we model more efficient learning algorithms. These update their hypothesis referring to the current datum and without direct regress to past training data. We focus on iterative (hypothesis based) and BMS (state based) learning algorithms. Iterative learning algorithms use the last hypothesis and the current datum in order to infer the new hypothesis.
Past research analyzed, for example, the above mentioned pairwise relations between delayable learning success criteria when learning from purely positive training data. We compare delayable learning success criteria with respect to iterative learning algorithms, as well as learning from either exclusively positive or binary labeled data. The existence of concept classes that can be learned by an iterative learning algorithm but not in a conservative way had already been observed, showing that conservativeness is restrictive. An additional requirement arising from cognitive science research %and also observed when training neural networks is U-shapedness, stating that the learning algorithm does diverge from a correct hypothesis. We show that forbidding U-shapes also restricts iterative learners from binary labeled data.
In order to compute the next hypothesis, BMS learning algorithms refer to the currently observed datum and the actual state of the learning algorithm. For learning algorithms equipped with an infinite amount of states, we provide the complete map. A learning success criterion is semantic if it still holds, when the learning algorithm outputs other parameters standing for the same classifier. Syntactic (non-semantic) learning success criteria, for example conservativeness and syntactic non-U-shapedness, restrict BMS learning algorithms. For proving the equivalence of the syntactic requirements, we refer to witness-based learning processes. In these, every change of the hypothesis is justified by a later on correctly classified witness from the training data. Moreover, for every semantic delayable learning requirement, iterative and BMS learning algorithms are equivalent. In case the considered learning success criterion incorporates syntactic non-U-shapedness, BMS learning algorithms can learn more concept classes than iterative learning algorithms.
The proofs are combinatorial, inspired by investigating formal languages or employ results from computability theory, such as infinite recursion theorems (fixed point theorems).
Skilled reading requires information processing of the fixated and the not-yet-fixated words to generate precise control of gaze. Over the last 30 years, experimental research provided evidence that word processing is distributed across the perceptual span, which permits recognition of the fixated (foveal) word as well as preview of parafoveal words to the right of fixation. However, theoretical models have been unable to differentiate the specific influences of foveal and parafoveal information on saccade control. Here we show how parafoveal word difficulty modulates spatial and temporal control of gaze in a computational model to reproduce experimental results. In a fully Bayesian framework, we estimated model parameters for different models of parafoveal processing and carried out large-scale predictive simulations and model comparisons for a gaze-contingent reading experiment. We conclude that mathematical modeling of data from gaze-contingent experiments permits the precise identification of pathways from parafoveal information processing to gaze control, uncovering potential mechanisms underlying the parafoveal contribution to eye-movement control.
During sentence reading the eyes quickly jump from word to word to sample visual information with the high acuity of the fovea. Lexical properties of the currently fixated word are known to affect the duration of the fixation, reflecting an interaction of word processing with oculomotor planning. While low level properties of words in the parafovea can likewise affect the current fixation duration, results concerning the influence of lexical properties have been ambiguous (Drieghe, Rayner, & Pollatsek, 2008; Kliegl, Nuthmann, & Engbert, 2006). Experimental investigations of such lexical parafoveal-on-foveal effects using the boundary paradigm have instead shown, that lexical properties of parafoveal previews affect fixation durations on the upcoming target words (Risse & Kliegl, 2014). However, the results were potentially confounded with effects of preview validity.
The notion of parafoveal processing of lexical information challenges extant models of eye movements during reading. Models containing serial word processing assumptions have trouble explaining such effects, as they usually couple successful word processing to saccade planning, resulting in skipping of the parafoveal word. Although models with parallel word processing are less restricted, in the SWIFT model (Engbert, Longtin, & Kliegl, 2002) only processing of the foveal word can directly influence the saccade latency.
Here we combine the results of a boundary experiment (Chapter 2) with a predictive modeling approach using the SWIFT model, where we explore mechanisms of parafoveal inhibition in a simulation study (Chapter 4). We construct a likelihood function for the SWIFT model (Chapter 3) and utilize the experimental data in a Bayesian approach to parameter estimation (Chapter 3 & 4).
The experimental results show a substantial effect of parafoveal preview frequency on fixation durations on the target word, which can be clearly distinguished from the effect of preview validity. Using the eye movement data from the participants, we demonstrate the feasibility of the Bayesian approach even for a small set of estimated parameters, by comparing summary statistics of experimental and simulated data. Finally, we can show that the SWIFT model can account for the lexical preview effects, when a mechanism for parafoveal inhibition is added. The effects of preview validity were modeled best, when processing dependent saccade cancellation was added for invalid trials. In the simulation study only the control condition of the experiment was used for parameter estimation, allowing for cross validation. Simultaneously the number of free parameters was increased. High correlations of summary statistics demonstrate the capabilities of the parameter estimation approach. Taken together, the results advocate for a better integration of experimental data into computational modeling via parameter estimation.
To achieve a sustainable energy economy, it is necessary to turn back on the combustion of fossil fuels as a means of energy production and switch to renewable sources. However, their temporal availability does not match societal consumption needs, meaning that renewably generated energy must be stored in its main generation times and allocated during peak consumption periods. Electrochemical energy storage (EES) in general is well suited due to its infrastructural independence and scalability. The lithium ion battery (LIB) takes a special place, among EES systems due to its energy density and efficiency, but the scarcity and uneven geological occurrence of minerals and ores vital for many cell components, and hence the high and fluctuating costs will decelerate its further distribution.
The sodium ion battery (SIB) is a promising successor to LIB technology, as the fundamental setup and cell chemistry is similar in the two systems. Yet, the most widespread negative electrode material in LIBs, graphite, cannot be used in SIBs, as it cannot store sufficient amounts of sodium at reasonable potentials. Hence, another carbon allotrope, non-graphitizing or hard carbon (HC) is used in SIBs. This material consists of turbostratically disordered, curved graphene layers, forming regions of graphitic stacking and zones of deviating layers, so-called internal or closed pores.
The structural features of HC have a substantial impact of the charge-potential curve exhibited by the carbon when it is used as the negative electrode in an SIB. At defects and edges an adsorption-like mechanism of sodium storage is prevalent, causing a sloping voltage curve, ill-suited for the practical application in SIBs, whereas a constant voltage plateau of relatively high capacities is found immediately after the sloping region, which recent research attributed to the deposition of quasimetallic sodium into the closed pores of HC.
Literature on the general mechanism of sodium storage in HCs and especially the role of the closed pore is abundant, but the influence of the pore geometry and chemical nature of the HC on the low-potential sodium deposition is yet in an early stage. Therefore, the scope of this thesis is to investigate these relationships using suitable synthetic and characterization methods. Materials of precisely known morphology, porosity, and chemical structure are prepared in clear distinction to commonly obtained ones and their impact on the sodium storage characteristics is observed. Electrochemical impedance spectroscopy in combination with distribution of relaxation times analysis is further established as a technique to study the sodium storage process, in addition to classical direct current techniques, and an equivalent circuit model is proposed to qualitatively describe the HC sodiation mechanism, based on the recorded data. The obtained knowledge is used to develop a method for the preparation of closed porous and non-porous materials from open porous ones, proving not only the necessity of closed pores for efficient sodium storage, but also providing a method for effective pore closure and hence the increase of the sodium storage capacity and efficiency of carbon materials.
The insights obtained and methods developed within this work hence not only contribute to the better understanding of the sodium storage mechanism in carbon materials of SIBs, but can also serve as guidance for the design of efficient electrode materials.
Background
The metabolic syndrome (MetS) is a risk cluster for a number of secondary diseases. The implementation of prevention programs requires early detection of individuals at risk. However, access to health care providers is limited in structurally weak regions. Brandenburg, a rural federal state in Germany, has an especially high MetS prevalence and disease burden. This study aims to validate and test the feasibility of a setup for mobile diagnostics of MetS and its secondary diseases, to evaluate the MetS prevalence and its association with moderating factors in Brandenburg and to identify new ways of early prevention, while establishing a “Mobile Brandenburg Cohort” to reveal new causes and risk factors for MetS.
Methods
In a pilot study, setups for mobile diagnostics of MetS and secondary diseases will be developed and validated. A van will be equipped as an examination room using point-of-care blood analyzers and by mobilizing standard methods. In study part A, these mobile diagnostic units will be placed at different locations in Brandenburg to locally recruit 5000 participants aged 40-70 years. They will be examined for MetS and advice on nutrition and physical activity will be provided. Questionnaires will be used to evaluate sociodemographics, stress perception, and physical activity. In study part B, participants with MetS, but without known secondary diseases, will receive a detailed mobile medical examination, including MetS diagnostics, medical history, clinical examinations, and instrumental diagnostics for internal, cardiovascular, musculoskeletal, and cognitive disorders. Participants will receive advice on nutrition and an exercise program will be demonstrated on site. People unable to participate in these mobile examinations will be interviewed by telephone. If necessary, participants will be referred to general practitioners for further diagnosis.
Discussion
The mobile diagnostics approach enables early detection of individuals at risk, and their targeted referral to local health care providers. Evaluation of the MetS prevalence, its relation to risk-increasing factors, and the “Mobile Brandenburg Cohort” create a unique database for further longitudinal studies on the implementation of home-based prevention programs to reduce mortality, especially in rural regions.
Trial registration
German Clinical Trials Register, DRKS00022764; registered 07 October 2020—retrospectively registered.
Cyber-physical systems often encompass complex concurrent behavior with timing constraints and probabilistic failures on demand. The analysis whether such systems with probabilistic timed behavior adhere to a given specification is essential. When the states of the system can be represented by graphs, the rule-based formalism of Probabilistic Timed Graph Transformation Systems (PTGTSs) can be used to suitably capture structure dynamics as well as probabilistic and timed behavior of the system. The model checking support for PTGTSs w.r.t. properties specified using Probabilistic Timed Computation Tree Logic (PTCTL) has been already presented. Moreover, for timed graph-based runtime monitoring, Metric Temporal Graph Logic (MTGL) has been developed for stating metric temporal properties on identified subgraphs and their structural changes over time. In this paper, we (a) extend MTGL to the Probabilistic Metric Temporal Graph Logic (PMTGL) by allowing for the specification of probabilistic properties, (b) adapt our MTGL satisfaction checking approach to PTGTSs, and (c) combine the approaches for PTCTL model checking and MTGL satisfaction checking to obtain a Bounded Model Checking (BMC) approach for PMTGL. In our evaluation, we apply an implementation of our BMC approach in AutoGraph to a running example.
Spinal muscular atrophy (SMA) and Duchenne muscular dystrophy (DMD) both are rare genetic neuromuscular diseases with progressive loss of motor ability. The neuromotor developmental course of those diseases is well documented. In contrast, there is only little evidence about characteristics of general and specific cognitive development. In both conditions the final motor outcome is characterized by an inability to move autonomously: children with SMA never accomplish independent motoric exploration of their environment, while children with DMD do but later lose this ability again. These profound differences in developmental pathways might affect cognitive development of SMA vs. DMD children, as cognition is shaped by individual motor experiences. DMD patients show impaired executive functions, working memory, and verbal IQ, whereas only motor ability seems to be impaired in SMA. Advanced cognitive capacity in SMA may serve as a compensatory mechanism for achieving in education, career progression, and social satisfaction. This study aimed to relate differences in basic numerical concepts and arithmetic achievement in SMA and DMD patients to differences in their motor development and resulting sensorimotor and environmental experiences. Horizontal and vertical spatial-numerical associations were explored in SMA/DMD children ranging between 6 and 12 years through the random number generation task. Furthermore, arithmetic skills as well as general cognitive ability were assessed. Groups differed in spatial number processing as well as in arithmetic and domain-general cognitive functions. Children with SMA showed no horizontal and even reversed vertical spatial-numerical associations. Children with DMD on the other hand revealed patterns in spatial numerical associations comparable to healthy developing children. From the embodied Cognition perspective, early sensorimotor experience does play a role in development of mental number representations. However, it remains open whether and how this becomes relevant for the acquisition of higher order cognitive and arithmetic skills.
Detecting and categorizing particular entities in the environment are important visual tasks that humans have had to solve at various points in our evolutionary time. The question arises whether characteristics of entities that were of ecological significance for humans play a particular role during the development of visual categorization.
The current project addressed this question by investigating the effects of developing visual abilities, visual properties and ecological significance on categorization early in life. Our stimuli were monochromatic photographs of structure-like assemblies and surfaces taken from three categories: vegetation, non-living natural elements, and artifacts. A set of computational and rated visual properties were assessed for these stimuli. Three empirical studies applied coherent research concepts and methods in young children and adults, comprising (a) two card-sorting tasks with preschool children (age: 4.1-6.1 years) and adults (age: 18-50 years) which assessed classification and similarity judgments, (b) a gaze contingent eye-tracking search task which investigated the impact of visual properties and category membership on 8-month-olds' ability to segregate visual structure. Because eye-tracking with infants still provides challenges, a methodological study (c) assessed the effect of infant eye-tracking procedures on data quality with 8- to 12-month-old infants and adults.
In the categorization tasks we found that category membership and visual properties impacted the performance of all participant groups. Sensitivity to the respective categories varied between tasks and over the age groups. For example, artifact images hindered infants' visual search but were classified best by adults, whereas sensitivity to vegetation was highest during similarity judgments. Overall, preschool children relied less on visual properties than adults, but some properties (e.g., rated depth, shading) were drawn upon similarly strong. In children and infants, depth predicted task performance stronger than shape-related properties. Moreover, children and infants were sensitive to variations in the complexity of low-level visual statistics. These results suggest that classification of visual structures, and attention to particular visual properties is affected by the functional or ecological significance these categories and properties may have for each of the respective age groups.
Based on this, the project highlights the importance of further developmental research on visual categorization with naturalistic, structure-like stimuli. As intended with the current work, this would allow important links between developmental and adult research.
Botulinum neurotoxin (BoNT) is produced by the anaerobic bacterium Clostridium botulinum. It is one of the most potent toxins found in nature and can enter motor neurons (MN) to cleave proteins necessary for neurotransmission, resulting in flaccid paralysis. The toxin has applications in both traditional and esthetic medicine. Since BoNT activity varies between batches despite identical protein concentrations, the activity of each lot must be assessed. The gold standard method is the mouse lethality assay, in which mice are injected with a BoNT dilution series to determine the dose at which half of the animals suffer death from peripheral asphyxia. Ethical concerns surrounding the use of animals in toxicity testing necessitate the creation of alternative model systems to measure the potency of BoNT.
Prerequisites of a successful model are that it is human specific; it monitors the complete toxic pathway of BoNT; and it is highly sensitive, at least in the range of the mouse lethality assay. One model system was developed by our group, in which human SIMA neuroblastoma cells were genetically modified to express a reporter protein (GLuc), which is packaged into neurosecretory vesicles, and which, upon cellular depolarization, can be released – or inhibited by BoNT – simultaneously with neurotransmitters. This assay has great potential, but includes the inherent disadvantages that the GLuc sequence was randomly inserted into the genome and the tumor cells only have limited sensitivity and specificity to BoNT. This project aims to improve these deficits, whereby induced pluripotent stem cells (iPSCs) were genetically modified by the CRISPR/Cas9 method to insert the GLuc sequence into the AAVS1 genomic safe harbor locus, precluding genetic disruption through non-specific integrations. Furthermore, GLuc was modified to associate with signal peptides that direct to the lumen of both large dense core vesicles (LDCV), which transport neuropeptides, and synaptic vesicles (SV), which package neurotransmitters. Finally, the modified iPSCs were differentiated into motor neurons (MNs), the true physiological target of BoNT, and hypothetically the most sensitive and specific cells available for the MoN-Light BoNT assay.
iPSCs were transfected to incorporate one of three constructs to direct GLuc into LDCVs, one construct to direct GLuc into SVs, and one “no tag” GLuc control construct. The LDCV constructs fused GLuc with the signal peptides for proopiomelanocortin (hPOMC-GLuc), chromogranin-A (CgA-GLuc), and secretogranin II (SgII-GLuc), which are all proteins found in the LDCV lumen. The SV construct comprises a VAMP2-GLuc fusion sequence, exploiting the SV membrane-associated protein synaptobrevin (VAMP2). The no tag GLuc expresses GLuc non-specifically throughout the cell and was created to compare the localization of vesicle-directed GLuc.
The clones were characterized to ensure that the GLuc sequence was only incorporated into the AAVS1 safe harbor locus and that the signal peptides directed GLuc to the correct vesicles. The accurate insertion of GLuc was confirmed by PCR with primers flanking the AAVS1 safe harbor locus, capable of simultaneously amplifying wildtype and modified alleles. The PCR amplicons, along with an insert-specific amplicon from candidate clones were Sanger sequenced to confirm the correct genomic region and sequence of the inserted DNA. Off-target integrations were analyzed with the newly developed dc-qcnPCR method, whereby the insert DNA was quantified by qPCR against autosomal and sex-chromosome encoded genes. While the majority of clones had off-target inserts, at least one on-target clone was identified for each construct.
Finally, immunofluorescence was utilized to localize GLuc in the selected clones. In iPSCs, the vesicle-directed GLuc should travel through the Golgi apparatus along the neurosecretory pathway, while the no tag GLuc should not follow this pathway. Initial analyses excluded the CgA-GLuc and SgII-GLuc clones due to poor quality protein visualization. The colocalization of GLuc with the Golgi was analyzed by confocal microscopy and quantified. GLuc was strongly colocalized with the Golgi in the hPOMC-GLuc clone (r = 0.85±0.09), moderately in the VAMP2-GLuc clone (r = 0.65±0.01), and, as expected, only weakly in the no tag GLuc clone (r = 0.44±0.10). Confocal microscopy of differentiated MNs was used to analyze the colocalization of GLuc with proteins associated with LDCVs and SVs, SgII in the hPOMC-GLuc clone (r = 0.85±0.08) and synaptophysin in the VAMP2-GLuc clone (r = 0.65±0.07). GLuc was also expressed in the same cells as the MN-associated protein, Islet1.
A significant portion of GLuc was found in the correct cell type and compartment. However, in the MoN-Light BoNT assay, the hPOMC-GLuc clone could not be provoked to reliably release GLuc upon cellular depolarization. The depolarization protocol for hPOMC-GLuc must be further optimized to produce reliable and specific release of GLuc upon exposure to a stimulus. On the other hand, the VAMP2-GLuc clone could be provoked to release GLuc upon exposure to the muscarinic and nicotinic agonist carbachol. Furthermore, upon simultaneous exposure to the calcium chelator EGTA, the carbachol-provoked release of GLuc could be significantly repressed, indicating the detection of GLuc was likely associated with vesicular fusion at the presynaptic terminal. The application of the VAMP2-GLuc clone in the MoN-Light BoNT assay must still be verified, but the results thus far indicate that this clone could be appropriate for the application of BoNT toxicity assessment.