@phdthesis{Schmidt2019,
  author    = {Schmidt, Martin},
  title     = {Fragmentation of landscapes: modelling ecosystem services of transition zones},
  doi       = {10.25932/publishup-44294},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-442942},
  school      = {Universit{\"a}t Potsdam},
  pages     = {XV, 103},
  year      = {2019},
  abstract  = {For millennia, humans have affected landscapes all over the world. Due to horizontal expansion, agriculture plays a major role in the process of fragmentation. This process is caused by a substitution of natural habitats by agricultural land leading to agricultural landscapes. These landscapes are characterized by an alternation of agriculture and other land use like forests. In addition, there are landscape elements of natural origin like small water bodies. Areas of different land use are beside each other like patches, or fragments. They are physically distinguishable which makes them look like a patchwork from an aerial perspective. These fragments are each an own ecosystem with conditions and properties that differ from their adjacent fragments. As open systems, they are in exchange of information, matter and energy across their boundaries. These boundary areas are called transition zones. Here, the habitat properties and environmental conditions are altered compared to the interior of the fragments. This changes the abundance and the composition of species in the transition zones, which in turn has a feedback effect on the environmental conditions. The literature mainly offers information and insights on species abundance and composition in forested transition zones. Abiotic effects, the gradual changes in energy and matter, received less attention. In addition, little is known about non-forested transition zones. For example, the effects on agricultural yield in transition zones of an altered microclimate, matter dynamics or different light regimes are hardly researched or understood. The processes in transition zones are closely connected with altered provisioning and regulating ecosystem services. To disentangle the mechanisms and to upscale the effects, models can be used. My thesis provides insights into these topics: literature was reviewed and a conceptual framework for the quantitative description of gradients of matter and energy in transition zones was introduced. The results of measurements of environmental gradients like microclimate, aboveground biomass and soil carbon and nitrogen content are presented that span from within the forest into arable land. Both the measurements and the literature review could not validate a transition zone of 100 m for abiotic effects. Although this value is often reported and used in the literature, it is likely to be smaller. Further, the measurements suggest that on the one hand trees in transition zones are smaller compared to those in the interior of the fragments, while on the other hand less biomass was measured in the arable lands' transition zone. These results support the hypothesis that less carbon is stored in the aboveground biomass in transition zones. The soil at the edge (zero line) between adjacent forest and arable land contains more nitrogen and carbon content compared to the interior of the fragments. One-year measurements in the transition zone also provided evidence that microclimate is different compared to the fragments' interior. To predict the possible yield decreases that transition zones might cause, a modelling approach was developed. Using a small virtual landscape, I modelled the effect of a forest fragment shading the adjacent arable land and the effects of this on yield using the MONICA crop growth model. In the transition zone yield was less compared to the interior due to shading. The results of the simulations were upscaled to the landscape level and exemplarily calculated for the arable land of a whole region in Brandenburg, Germany. The major findings of my thesis are: (1) Transition zones are likely to be much smaller than assumed in the scientific literature; (2) transition zones aren't solely a phenomenon of forested ecosystems, but significantly extend into arable land as well; (3) empirical and modelling results show that transition zones encompass biotic and abiotic changes that are likely to be important to a variety of agricultural landscape ecosystem services.},
  language  = {en}
}
@phdthesis{Burmester2019,
  author    = {Burmester, Juliane},
  title     = {Linguistic and visual salience in sentence comprehension},
  doi       = {10.25932/publishup-44315},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-443155},
  school      = {Universit{\"a}t Potsdam},
  pages     = {XI, 165},
  year      = {2019},
  abstract  = {Interlocutors typically link their utterances to the discourse environment and enrich communication by linguistic (e.g., information packaging) and extra-linguistic (e.g., eye gaze, gestures) means to optimize information transfer. Psycholinguistic studies underline that ‒for meaning computation‒ listeners profit from linguistic and visual cues that draw their focus of attention to salient information. This dissertation is the first work that examines how linguistic compared to visual salience cues influence sentence comprehension using the very same experimental paradigms and materials, that is, German subject-before-object (SO) and object-before-subject (OS) sentences, across the two cue modalities. Linguistic salience was induced by indicating a referent as the aboutness topic. Visual salience was induced by implicit (i.e., unconscious) or explicit (i.e., shared) manipulations of listeners' attention to a depicted referent. In Study 1, a selective, facilitative impact of linguistic salience on the context-sensitive OS word order was found using offline comprehensibility judgments. More precisely, during online sentence processing, this impact was characterized by a reduced sentence-initial Late positivity which reflects reduced processing costs for updating the current mental representation of discourse. This facilitative impact of linguistic salience was not replicated by means of an implicit visual cue (Study 2) shown to modulate word order preferences during sentence production. However, a gaze shift to a depicted referent as an indicator of shared attention eased sentence-initial processing similar to linguistic salience as revealed by reduced reading times (Study 3). Yet, this cue did not modulate the strong subject-antecedent preference during later pronoun resolution like linguistic salience. Taken together, these findings suggest a significant impact of linguistic and visual salience cues on sentence comprehension, which substantiates that both the information delivered via language and via the visual environment is integrated into the mental representation of the discourse; but, the way how salience is induced is crucial to its impact.},
  language  = {en}
}
@phdthesis{Hoang2019,
  author    = {Hoang, Yen},
  title     = {De novo binning strategy to analyze and visualize multi-dimensional cytometric data},
  doi       = {10.25932/publishup-44307},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-443078},
  school      = {Universit{\"a}t Potsdam},
  pages     = {vii, 81, xxxii},
  year      = {2019},
  abstract  = {Since half a century, cytometry has been a major scientific discipline in the field of cytomics - the study of system's biology at single cell level. It enables the investigation of physiological processes, functional characteristics and rare events with proteins by analysing multiple parameters on an individual cell basis. In the last decade, mass cytometry has been established which increased the parallel measurement to up to 50 proteins. This has shifted the analysis strategy from conventional consecutive manual gates towards multi-dimensional data processing. Novel algorithms have been developed to tackle these high-dimensional protein combinations in the data. They are mainly based on clustering or non-linear dimension reduction techniques, or both, often combined with an upstream downsampling procedure. However, these tools have obstacles either in comprehensible interpretability, reproducibility, computational complexity or in comparability between samples and groups. To address this bottleneck, a reproducible, semi-automated cytometric data mining workflow PRI (pattern recognition of immune cells) is proposed which combines three main steps: i) data preparation and storage; ii) bin-based combinatorial variable engineering of three protein markers, the so called triploTs, and subsequent sectioning of these triploTs in four parts; and iii) deployment of a data-driven supervised learning algorithm, the cross-validated elastic-net regularized logistic regression, with these triploT sections as input variables. As a result, the selected variables from the models are ranked by their prevalence, which potentially have discriminative value. The purpose is to significantly facilitate the identification of meaningful subpopulations, which are most distinguish between two groups. The proposed workflow PRI is exemplified by a recently published public mass cytometry data set. The authors found a T cell subpopulation which is discriminative between effective and ineffective treatment of breast carcinomas in mice. With PRI, that subpopulation was not only validated, but was further narrowed down as a particular Th1 cell population. Moreover, additional insights of combinatorial protein expressions are revealed in a traceable manner. An essential element in the workflow is the reproducible variable engineering. These variables serve as basis for a clearly interpretable visualization, for a structured variable exploration and as input layers in neural network constructs. PRI facilitates the determination of marker levels in a semi-continuous manner. Jointly with the combinatorial display, it allows a straightforward observation of correlating patterns, and thus, the dominant expressed markers and cell hierarchies. Furthermore, it enables the identification and complex characterization of discriminating subpopulations due to its reproducible and pseudo-multi-parametric pattern presentation. This endorses its applicability as a tool for unbiased investigations on cell subsets within multi-dimensional cytometric data sets.},
  language  = {en}
}
@phdthesis{Qin2019,
  author    = {Qin, Qing},
  title     = {Chemical functionalization of porous carbon-based materials to enable novel modes for efficient electrochemical N2 fixation},
  doi       = {10.25932/publishup-44339},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-443397},
  school      = {Universit{\"a}t Potsdam},
  pages     = {146},
  year      = {2019},
  abstract  = {The central motivation of the thesis was to provide possible solutions and concepts to improve the performance (e.g. activity and selectivity) of electrochemical N2 reduction reaction (NRR). Given that porous carbon-based materials usually exhibit a broad range of structural properties, they could be promising NRR catalysts. Therefore, the advanced design of novel porous carbon-based materials and the investigation of their application in electrocatalytic NRR including the particular reaction mechanisms are the most crucial points to be addressed. In this regard, three main topics were investigated. All of them are related to the functionalization of porous carbon for electrochemical NRR or other electrocatalytic reactions. In chapter 3, a novel C-TixOy/C nanocomposite has been described that has been obtained via simple pyrolysis of MIL-125(Ti). A novel mode for N2 activation is achieved by doping carbon atoms from nearby porous carbon into the anion lattice of TixOy. By comparing the NRR performance of M-Ts and by carrying out DFT calculations, it is found that the existence of (O-)Ti-C bonds in C-doped TixOy can largely improve the ability to activate and reduce N2 as compared to unoccupied OVs in TiO2. The strategy of rationally doping heteroatoms into the anion lattice of transition metal oxides to create active centers may open many new opportunities beyond the use of noble metal-based catalysts also for other reactions that require the activation of small molecules as well. In chapter 4, a novel catalyst construction composed of Au single atoms decorated on the surface of NDPCs was reported. The introduction of Au single atoms leads to active reaction sites, which are stabilized by the N species present in NDPCs. Thus, the interaction within as-prepared AuSAs-NDPCs catalysts enabled promising performance for electrochemical NRR. For the reaction mechanism, Au single sites and N or C species can act as Frustrated Lewis pairs (FLPs) to enhance the electron donation and back-donation process to activate N2 molecules. This work provides new opportunities for catalyst design in order to achieve efficient N2 fixation at ambient conditions by utilizing recycled electric energy. The last topic described in chapter 5 mainly focused on the synthesis of dual heteroatom-doped porous carbon from simple precursors. The introduction of N and B heteroatoms leads to the construction of N-B motives and Frustrated Lewis pairs in a microporous architecture which is also rich in point defects. This can improve the strength of adsorption of different reactants (N2 and HMF) and thus their activation. As a result, BNC-2 exhibits a desirable electrochemical NRR and HMF oxidation performance. Gas adsorption experiments have been used as a simple tool to elucidate the relationship between the structure and catalytic activity. This work provides novel and deep insights into the rational design and the origin of activity in metal-free electrocatalysts and enables a physically viable discussion of the active motives, as well as the search for their further applications. Throughout this thesis, the ubiquitous problems of low selectivity and activity of electrochemical NRR are tackled by designing porous carbon-based catalysts with high efficiency and exploring their catalytic mechanisms. The structure-performance relationships and mechanisms of activation of the relatively inert N2 molecules are revealed by either experimental results or DFT calculations. These fundamental understandings pave way for a future optimal design and targeted promotion of NRR catalysts with porous carbon-based structure, as well as study of new N2 activation modes.},
  language  = {en}
}
@phdthesis{Fuhr2019,
  author    = {Fuhr, Antonie},
  title     = {Eine Hypothese {\"u}ber die Grundlagen von Moral und einige Implikationen},
  doi       = {10.25932/publishup-44309},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-443091},
  school      = {Universit{\"a}t Potsdam},
  pages     = {172},
  year      = {2019},
  abstract  = {In der Dissertationsarbeit mit dem Titel „Eine Hypothese {\"u}ber die Grundlagen von Moral und einige Implikationen" unternimmt die Autorin den Versuch, die anthropologischen Pr{\"a}missen moralischen Handelns herauszuarbeiten. Es wird eine Hypothese aufgestellt und erl{\"a}utert, die behauptet, dass moralisches Handeln nur dann verst{\"a}ndlich wird, wenn der Handelnde erstens die F{\"a}higkeit der Phantasie aufweist, zweitens auf Erfahrungen (mittels seines Ged{\"a}chtnisses) zugreifen kann und durch Konversation mit anderen Personen interagierte und interagiert, denn nur auf der Basis dieser drei Grundlagen von Moral k{\"o}nnen sich diejenigen F{\"a}higkeiten ent¬wickeln, die als Voraussetzungen moralischen Handeln gesehen werden m{\"u}ssen: Selbstbewusstsein, Freiheit, die Entwicklung eines Wir-Gef{\"u}hls, die Genese eines moralischen Ideals und die F{\"a}higkeit, sich im Entscheiden und Handeln nach diesem Ideal richten zu k{\"o}nnen. Außerdem werden in dieser Dissertation einige Implikationen dieser Hypothese auf individueller und zwischenmenschlicher Ebene diskutiert.},
  language  = {de}
}
@phdthesis{Rezaei2019,
  author    = {Rezaei, Mina},
  title     = {Deep representation learning from imbalanced medical imaging},
  doi       = {10.25932/publishup-44275},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-442759},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xxviii, 160},
  year      = {2019},
  abstract  = {Medical imaging plays an important role in disease diagnosis, treatment planning, and clinical monitoring. One of the major challenges in medical image analysis is imbalanced training data, in which the class of interest is much rarer than the other classes. Canonical machine learning algorithms suppose that the number of samples from different classes in the training dataset is roughly similar or balance. Training a machine learning model on an imbalanced dataset can introduce unique challenges to the learning problem. A model learned from imbalanced training data is biased towards the high-frequency samples. The predicted results of such networks have low sensitivity and high precision. In medical applications, the cost of misclassification of the minority class could be more than the cost of misclassification of the majority class. For example, the risk of not detecting a tumor could be much higher than referring to a healthy subject to a doctor. The current Ph.D. thesis introduces several deep learning-based approaches for handling class imbalanced problems for learning multi-task such as disease classification and semantic segmentation. At the data-level, the objective is to balance the data distribution through re-sampling the data space: we propose novel approaches to correct internal bias towards fewer frequency samples. These approaches include patient-wise batch sampling, complimentary labels, supervised and unsupervised minority oversampling using generative adversarial networks for all. On the other hand, at algorithm-level, we modify the learning algorithm to alleviate the bias towards majority classes. In this regard, we propose different generative adversarial networks for cost-sensitive learning, ensemble learning, and mutual learning to deal with highly imbalanced imaging data. We show evidence that the proposed approaches are applicable to different types of medical images of varied sizes on different applications of routine clinical tasks, such as disease classification and semantic segmentation. Our various implemented algorithms have shown outstanding results on different medical imaging challenges.},
  language  = {en}
}
@phdthesis{Mandal2019,
  author    = {Mandal, Sankalita},
  title     = {Event handling in business processes},
  doi       = {10.25932/publishup-44170},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-441700},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xix, 151},
  year      = {2019},
  abstract  = {Business process management (BPM) deals with modeling, executing, monitoring, analyzing, and improving business processes. During execution, the process communicates with its environment to get relevant contextual information represented as events. Recent development of big data and the Internet of Things (IoT) enables sources like smart devices and sensors to generate tons of events which can be filtered, grouped, and composed to trigger and drive business processes. The industry standard Business Process Model and Notation (BPMN) provides several event constructs to capture the interaction possibilities between a process and its environment, e.g., to instantiate a process, to abort an ongoing activity in an exceptional situation, to take decisions based on the information carried by the events, as well as to choose among the alternative paths for further process execution. The specifications of such interactions are termed as event handling. However, in a distributed setup, the event sources are most often unaware of the status of process execution and therefore, an event is produced irrespective of the process being ready to consume it. BPMN semantics does not support such scenarios and thus increases the chance of processes getting delayed or getting in a deadlock by missing out on event occurrences which might still be relevant. The work in this thesis reviews the challenges and shortcomings of integrating real-world events into business processes, especially the subscription management. The basic integration is achieved with an architecture consisting of a process modeler, a process engine, and an event processing platform. Further, points of subscription and unsubscription along the process execution timeline are defined for different BPMN event constructs. Semantic and temporal dependencies among event subscription, event occurrence, event consumption and event unsubscription are considered. To this end, an event buffer with policies for updating the buffer, retrieving the most suitable event for the current process instance, and reusing the event has been discussed that supports issuing of early subscription. The Petri net mapping of the event handling model provides our approach with a translation of semantics from a business process perspective. Two applications based on this formal foundation are presented to support the significance of different event handling configurations on correct process execution and reachability of a process path. Prototype implementations of the approaches show that realizing flexible event handling is feasible with minor extensions of off-the-shelf process engines and event platforms.},
  language  = {en}
}
@phdthesis{AppiahDwomoh2019,
  author    = {Appiah-Dwomoh, Edem Korkor},
  title     = {Postural control and back pain in adolescent athletes},
  doi       = {10.25932/publishup-44269},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-442692},
  school      = {Universit{\"a}t Potsdam},
  pages     = {VI, 77, X},
  year      = {2019},
  abstract  = {Back pain is a problem in adolescent athletes affecting postural control which is an important requirement for physical and daily activities whether under static or dynamic conditions. One leg stance and star excursion balance postural control tests are effective in measuring static and dynamic postural control respectively. These tests have been used in individuals with back pain, athletes and non-athletes without first establishing their reliabilities. In addition to this, there is no published literature investigating dynamic posture in adolescent athletes with back pain using the star excursion balance test. Therefore, the aim of the thesis was to assess deficit in postural control in adolescent athletes with and without back pain using static (one leg stance test) and dynamic postural (SEBT) control tests. Adolescent athletes with and without back pain participated in the study. Static and dynamic postural control tests were performed using one leg stance and SEBT respectively. The reproducibility of both tests was established. Afterwards, it was determined whether there was an association between static and dynamic posture using the measure of displacement of the centre pressure and reach distance respectively. Finally, it was investigated whether there was a difference in postural control in adolescent athletes with and without back pain using the one leg stance test and the SEBT. Fair to excellent reliabilities was recorded for the static (one leg stance) and dynamic (star excursion balance) postural control tests in the subjects of interest. No association was found between variables of the static and dynamic tests for the adolescent athletes with and without back pain. Also, no statistically significant difference was obtained between adolescent athletics with and without back pain using the static and dynamic postural control test. One leg stance test and SEBT can be used as measures of postural control in adolescent athletes with and without back pain. Although static and dynamic postural control might be related, adolescent athletes with and without back pain might be using different mechanisms in controlling their static and dynamic posture. Consequently, static and dynamic postural control in adolescent athletes with back pain was not different from those without back pain. These outcome measures might not be challenging enough to detect deficit in postural control in our study group of interest.},
  language  = {en}
}
@phdthesis{Willig2019,
  author    = {Willig, Lisa},
  title     = {Ultrafast magneto-optical studies of remagnetisation dynamics in transition metals},
  doi       = {10.25932/publishup-44194},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-441942},
  school      = {Universit{\"a}t Potsdam},
  pages     = {XIV, 113, XVII},
  year      = {2019},
  abstract  = {Ultrafast magnetisation dynamics have been investigated intensely for two decades. The recovery process after demagnetisation, however, was rarely studied experimentally and discussed in detail. The focus of this work lies on the investigation of the magnetisation on long timescales after laser excitation. It combines two ultrafast time resolved methods to study the relaxation of the magnetic and lattice system after excitation with a high fluence ultrashort laser pulse. The magnetic system is investigated by time resolved measurements of the magneto-optical Kerr effect. The experimental setup has been implemented in the scope of this work. The lattice dynamics were obtained with ultrafast X-ray diffraction. The combination of both techniques leads to a better understanding of the mechanisms involved in magnetisation recovery from a non-equilibrium condition. Three different groups of samples are investigated in this work: Thin Nickel layers capped with nonmagnetic materials, a continuous sample of the ordered L10 phase of Iron Platinum and a sample consisting of Iron Platinum nanoparticles embedded in a carbon matrix. The study of the remagnetisation reveals a general trend for all of the samples: The remagnetisation process can be described by two time dependences. A first exponential recovery that slows down with an increasing amount of energy absorbed in the system until an approximately linear time dependence is observed. This is followed by a second exponential recovery. In case of low fluence excitation, the first recovery is faster than the second. With increasing fluence the first recovery is slowed down and can be described as a linear function. If the pump-induced temperature increase in the sample is sufficiently high, a phase transition to a paramagnetic state is observed. In the remagnetisation process, the transition into the ferromagnetic state is characterised by a distinct transition between the linear and exponential recovery. From the combination of the transient lattice temperature Tp(t) obtained from ultrafast X-ray measurements and magnetisation M(t) gained from magneto-optical measurements we construct the transient magnetisation versus temperature relations M(Tp). If the lattice temperature remains below the Curie temperature the remagnetisation curve M(Tp) is linear and stays below the M(T) curve in equilibrium in the continuous transition metal layers. When the sample is heated above phase transition, the remagnetisation converges towards the static temperature dependence. For the granular Iron Platinum sample the M(Tp) curves for different fluences coincide, i.e. the remagnetisation follows a similar path irrespective of the initial laser-induced temperature jump.},
  language  = {en}
}
@phdthesis{Amirkhanyan2019,
  author    = {Amirkhanyan, Aragats},
  title     = {Methods and frameworks for GeoSpatioTemporal data analytics},
  doi       = {10.25932/publishup-44168},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-441685},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xxiv, 133},
  year      = {2019},
  abstract  = {In the era of social networks, internet of things and location-based services, many online services produce a huge amount of data that have valuable objective information, such as geographic coordinates and date time. These characteristics (parameters) in the combination with a textual parameter bring the challenge for the discovery of geospatiotemporal knowledge. This challenge requires efficient methods for clustering and pattern mining in spatial, temporal and textual spaces. In this thesis, we address the challenge of providing methods and frameworks for geospatiotemporal data analytics. As an initial step, we address the challenges of geospatial data processing: data gathering, normalization, geolocation, and storage. That initial step is the basement to tackle the next challenge -- geospatial clustering challenge. The first step of this challenge is to design the method for online clustering of georeferenced data. This algorithm can be used as a server-side clustering algorithm for online maps that visualize massive georeferenced data. As the second step, we develop the extension of this method that considers, additionally, the temporal aspect of data. For that, we propose the density and intensity-based geospatiotemporal clustering algorithm with fixed distance and time radius. Each version of the clustering algorithm has its own use case that we show in the thesis. In the next chapter of the thesis, we look at the spatiotemporal analytics from the perspective of the sequential rule mining challenge. We design and implement the framework that transfers data into textual geospatiotemporal data - data that contain geographic coordinates, time and textual parameters. By this way, we address the challenge of applying pattern/rule mining algorithms in geospatiotemporal space. As the applicable use case study, we propose spatiotemporal crime analytics -- discovery spatiotemporal patterns of crimes in publicly available crime data. The second part of the thesis, we dedicate to the application part and use case studies. We design and implement the application that uses the proposed clustering algorithms to discover knowledge in data. Jointly with the application, we propose the use case studies for analysis of georeferenced data in terms of situational and public safety awareness.},
  language  = {en}
}