@article{BaerenzungHolschneiderWichtetal.2018, author = {B{\"a}renzung, Julien and Holschneider, Matthias and Wicht, Johannes and Sanchez, Sabrina and Lesur, Vincent}, title = {Modeling and predicting the short-term evolution of the geomagnetic field}, series = {Journal of geophysical research : Solid earth}, volume = {123}, journal = {Journal of geophysical research : Solid earth}, number = {6}, publisher = {American Geophysical Union}, address = {Washington}, issn = {2169-9313}, doi = {10.1029/2017JB015115}, pages = {4539 -- 4560}, year = {2018}, abstract = {We propose a reduced dynamical system describing the coupled evolution of fluid flow and magnetic field at the top of the Earth's core between the years 1900 and 2014. The flow evolution is modeled with a first-order autoregressive process, while the magnetic field obeys the classical frozen flux equation. An ensemble Kalman filter algorithm serves to constrain the dynamics with the geomagnetic field and its secular variation given by the COV-OBS.x1 model. Using a large ensemble with 40,000 members provides meaningful statistics including reliable error estimates. The model highlights two distinct flow scales. Slowly varying large-scale elements include the already documented eccentric gyre. Localized short-lived structures include distinctly ageostophic features like the high-latitude polar jet on the Northern Hemisphere. Comparisons with independent observations of the length-of-day variations not only validate the flow estimates but also suggest an acceleration of the geostrophic flows over the last century. Hindcasting tests show that our model outperforms simpler predictions bases (linear extrapolation and stationary flow). The predictability limit, of about 2,000 years for the magnetic dipole component, is mostly determined by the random fast varying dynamics of the flow and much less by the geomagnetic data quality or lack of small-scale information.}, language = {en} } @article{ChristakoudiTsilidisMulleretal.2020, author = {Christakoudi, Sofa and Tsilidis, Konstantinos K. and Muller, David C. and Freisling, Heinz and Weiderpass, Elisabete and Overvad, Kim and S{\"o}derberg, Stefan and H{\"a}ggstr{\"o}m, Christel and Pischon, Tobias and Dahm, Christina C. and Zhang, Jie and Tj{\o}nneland, Anne and Schulze, Matthias Bernd}, title = {A Body Shape Index (ABSI) achieves better mortality risk stratification than alternative indices of abdominal obesity: results from a large European cohort}, series = {Scientific Reports}, volume = {10}, journal = {Scientific Reports}, number = {1}, publisher = {Springer Nature}, address = {Berlin}, pages = {15}, year = {2020}, abstract = {Abdominal and general adiposity are independently associated with mortality, but there is no consensus on how best to assess abdominal adiposity. We compared the ability of alternative waist indices to complement body mass index (BMI) when assessing all-cause mortality. We used data from 352,985 participants in the European Prospective Investigation into Cancer and Nutrition (EPIC) and Cox proportional hazards models adjusted for other risk factors. During a mean follow-up of 16.1 years, 38,178 participants died. Combining in one model BMI and a strongly correlated waist index altered the association patterns with mortality, to a predominantly negative association for BMI and a stronger positive association for the waist index, while combining BMI with the uncorrelated A Body Shape Index (ABSI) preserved the association patterns. Sex-specific cohort-wide quartiles of waist indices correlated with BMI could not separate high-risk from low-risk individuals within underweight (BMI<18.5 kg/m(2)) or obese (BMI30 kg/m(2)) categories, while the highest quartile of ABSI separated 18-39\% of the individuals within each BMI category, which had 22-55\% higher risk of death. In conclusion, only a waist index independent of BMI by design, such as ABSI, complements BMI and enables efficient risk stratification, which could facilitate personalisation of screening, treatment and monitoring.}, language = {en} } @misc{ChristakoudiTsilidisMulleretal.2020, author = {Christakoudi, Sofa and Tsilidis, Konstantinos K. and Muller, David C. and Freisling, Heinz and Weiderpass, Elisabete and Overvad, Kim and S{\"o}derberg, Stefan and H{\"a}ggstr{\"o}m, Christel and Pischon, Tobias and Dahm, Christina C. and Zhang, Jie and Tj{\o}nneland, Anne and Schulze, Matthias Bernd}, title = {A Body Shape Index (ABSI) achieves better mortality risk stratification than alternative indices of abdominal obesity: results from a large European cohort}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {1}, issn = {1866-8372}, doi = {10.25932/publishup-52582}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-525827}, pages = {17}, year = {2020}, abstract = {Abdominal and general adiposity are independently associated with mortality, but there is no consensus on how best to assess abdominal adiposity. We compared the ability of alternative waist indices to complement body mass index (BMI) when assessing all-cause mortality. We used data from 352,985 participants in the European Prospective Investigation into Cancer and Nutrition (EPIC) and Cox proportional hazards models adjusted for other risk factors. During a mean follow-up of 16.1 years, 38,178 participants died. Combining in one model BMI and a strongly correlated waist index altered the association patterns with mortality, to a predominantly negative association for BMI and a stronger positive association for the waist index, while combining BMI with the uncorrelated A Body Shape Index (ABSI) preserved the association patterns. Sex-specific cohort-wide quartiles of waist indices correlated with BMI could not separate high-risk from low-risk individuals within underweight (BMI<18.5 kg/m(2)) or obese (BMI30 kg/m(2)) categories, while the highest quartile of ABSI separated 18-39\% of the individuals within each BMI category, which had 22-55\% higher risk of death. In conclusion, only a waist index independent of BMI by design, such as ABSI, complements BMI and enables efficient risk stratification, which could facilitate personalisation of screening, treatment and monitoring.}, language = {en} } @misc{CiemerRehmKurthsetal.2020, author = {Ciemer, Catrin and Rehm, Lars and Kurths, J{\"u}rgen and Donner, Reik Volker and Winkelmann, Ricarda and Boers, Niklas}, title = {An early-warning indicator for Amazon droughts exclusively based on tropical Atlantic sea surface temperatures}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {9}, issn = {1866-8372}, doi = {10.25932/publishup-52586}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-525863}, pages = {12}, year = {2020}, abstract = {Droughts in tropical South America have an imminent and severe impact on the Amazon rainforest and affect the livelihoods of millions of people. Extremely dry conditions in Amazonia have been previously linked to sea surface temperature (SST) anomalies in the adjacent tropical oceans. Although the sources and impacts of such droughts have been widely studied, establishing reliable multi-year lead statistical forecasts of their occurrence is still an ongoing challenge. Here, we further investigate the relationship between SST and rainfall anomalies using a complex network approach. We identify four ocean regions which exhibit the strongest overall SST correlations with central Amazon rainfall, including two particularly prominent regions in the northern and southern tropical Atlantic. Based on the time-dependent correlation between SST anomalies in these two regions alone, we establish a new early-warning method for droughts in the central Amazon basin and demonstrate its robustness in hindcasting past major drought events with lead-times up to 18 months.}, language = {en} } @article{CiemerRehmKurthsetal.2020, author = {Ciemer, Catrin and Rehm, Lars and Kurths, J{\"u}rgen and Donner, Reik Volker and Winkelmann, Ricarda and Boers, Niklas}, title = {An early-warning indicator for Amazon droughts exclusively based on tropical Atlantic sea surface temperatures}, series = {Environmental Research Letters}, volume = {15}, journal = {Environmental Research Letters}, number = {9}, publisher = {IOP - Institute of Physics Publishing}, address = {Bristol}, pages = {10}, year = {2020}, abstract = {Droughts in tropical South America have an imminent and severe impact on the Amazon rainforest and affect the livelihoods of millions of people. Extremely dry conditions in Amazonia have been previously linked to sea surface temperature (SST) anomalies in the adjacent tropical oceans. Although the sources and impacts of such droughts have been widely studied, establishing reliable multi-year lead statistical forecasts of their occurrence is still an ongoing challenge. Here, we further investigate the relationship between SST and rainfall anomalies using a complex network approach. We identify four ocean regions which exhibit the strongest overall SST correlations with central Amazon rainfall, including two particularly prominent regions in the northern and southern tropical Atlantic. Based on the time-dependent correlation between SST anomalies in these two regions alone, we establish a new early-warning method for droughts in the central Amazon basin and demonstrate its robustness in hindcasting past major drought events with lead-times up to 18 months.}, language = {en} } @phdthesis{Elsaid2022, author = {Elsaid, Mohamed Esameldin Mohamed}, title = {Virtual machines live migration cost modeling and prediction}, doi = {10.25932/publishup-54001}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-540013}, school = {Universit{\"a}t Potsdam}, pages = {xiv, 107}, year = {2022}, abstract = {Dynamic resource management is an essential requirement for private and public cloud computing environments. With dynamic resource management, the physical resources assignment to the cloud virtual resources depends on the actual need of the applications or the running services, which enhances the cloud physical resources utilization and reduces the offered services cost. In addition, the virtual resources can be moved across different physical resources in the cloud environment without an obvious impact on the running applications or services production. This means that the availability of the running services and applications in the cloud is independent on the hardware resources including the servers, switches and storage failures. This increases the reliability of using cloud services compared to the classical data-centers environments. In this thesis we briefly discuss the dynamic resource management topic and then deeply focus on live migration as the definition of the compute resource dynamic management. Live migration is a commonly used and an essential feature in cloud and virtual data-centers environments. Cloud computing load balance, power saving and fault tolerance features are all dependent on live migration to optimize the virtual and physical resources usage. As we will discuss in this thesis, live migration shows many benefits to cloud and virtual data-centers environments, however the cost of live migration can not be ignored. Live migration cost includes the migration time, downtime, network overhead, power consumption increases and CPU overhead. IT admins run virtual machines live migrations without an idea about the migration cost. So, resources bottlenecks, higher migration cost and migration failures might happen. The first problem that we discuss in this thesis is how to model the cost of the virtual machines live migration. Secondly, we investigate how to make use of machine learning techniques to help the cloud admins getting an estimation of this cost before initiating the migration for one of multiple virtual machines. Also, we discuss the optimal timing for a specific virtual machine before live migration to another server. Finally, we propose practical solutions that can be used by the cloud admins to be integrated with the cloud administration portals to answer the raised research questions above. Our research methodology to achieve the project objectives is to propose empirical models based on using VMware test-beds with different benchmarks tools. Then we make use of the machine learning techniques to propose a prediction approach for virtual machines live migration cost. Timing optimization for live migration is also proposed in this thesis based on using the cost prediction and data-centers network utilization prediction. Live migration with persistent memory clusters is also discussed at the end of the thesis. The cost prediction and timing optimization techniques proposed in this thesis could be practically integrated with VMware vSphere cluster portal such that the IT admins can now use the cost prediction feature and timing optimization option before proceeding with a virtual machine live migration. Testing results show that our proposed approach for VMs live migration cost prediction shows acceptable results with less than 20\% prediction error and can be easily implemented and integrated with VMware vSphere as an example of a commonly used resource management portal for virtual data-centers and private cloud environments. The results show that using our proposed VMs migration timing optimization technique also could save up to 51\% of migration time of the VMs migration time for memory intensive workloads and up to 27\% of the migration time for network intensive workloads. This timing optimization technique can be useful for network admins to save migration time with utilizing higher network rate and higher probability of success. At the end of this thesis, we discuss the persistent memory technology as a new trend in servers memory technology. Persistent memory modes of operation and configurations are discussed in detail to explain how live migration works between servers with different memory configuration set up. Then, we build a VMware cluster with persistent memory inside server and also with DRAM only servers to show the live migration cost difference between the VMs with DRAM only versus the VMs with persistent memory inside.}, language = {en} } @phdthesis{GamezLopez2006, author = {G{\´a}mez L{\´o}pez, Antonio Juan}, title = {Application of nonlinear dimensionality reduction to climate data for prediction}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-10956}, school = {Universit{\"a}t Potsdam}, year = {2006}, abstract = {This Thesis was devoted to the study of the coupled system composed by El Ni{\~n}o/Southern Oscillation and the Annual Cycle. More precisely, the work was focused on two main problems: 1. How to separate both oscillations into an affordable model for understanding the behaviour of the whole system. 2. How to model the system in order to achieve a better understanding of the interaction, as well as to predict future states of the system. We focused our efforts in the Sea Surface Temperature equations, considering that atmospheric effects were secondary to the ocean dynamics. The results found may be summarised as follows: 1. Linear methods are not suitable for characterising the dimensionality of the sea surface temperature in the tropical Pacific Ocean. Therefore they do not help to separate the oscillations by themselves. Instead, nonlinear methods of dimensionality reduction are proven to be better in defining a lower limit for the dimensionality of the system as well as in explaining the statistical results in a more physical way [1]. In particular, Isomap, a nonlinear modification of Multidimensional Scaling methods, provides a physically appealing method of decomposing the data, as it substitutes the euclidean distances in the manifold by an approximation of the geodesic distances. We expect that this method could be successfully applied to other oscillatory extended systems and, in particular, to meteorological systems. 2. A three dimensional dynamical system could be modeled, using a backfitting algorithm, for describing the dynamics of the sea surface temperature in the tropical Pacific Ocean. We observed that, although there were few data points available, we could predict future behaviours of the coupled ENSO-Annual Cycle system with an accuracy of less than six months, although the constructed system presented several drawbacks: few data points to input in the backfitting algorithm, untrained model, lack of forcing with external data and simplification using a close system. Anyway, ensemble prediction techniques showed that the prediction skills of the three dimensional time series were as good as those found in much more complex models. This suggests that the climatological system in the tropics is mainly explained by ocean dynamics, while the atmosphere plays a secondary role in the physics of the process. Relevant predictions for short lead times can be made using a low dimensional system, despite its simplicity. The analysis of the SST data suggests that nonlinear interaction between the oscillations is small, and that noise plays a secondary role in the fundamental dynamics of the oscillations [2]. A global view of the work shows a general procedure to face modeling of climatological systems. First, we should find a suitable method of either linear or nonlinear dimensionality reduction. Then, low dimensional time series could be extracted out of the method applied. Finally, a low dimensional model could be found using a backfitting algorithm in order to predict future states of the system.}, subject = {Nichtlineare Dynamik}, language = {en} } @phdthesis{Haider2013, author = {Haider, Peter}, title = {Prediction with Mixture Models}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-69617}, school = {Universit{\"a}t Potsdam}, year = {2013}, abstract = {Learning a model for the relationship between the attributes and the annotated labels of data examples serves two purposes. Firstly, it enables the prediction of the label for examples without annotation. Secondly, the parameters of the model can provide useful insights into the structure of the data. If the data has an inherent partitioned structure, it is natural to mirror this structure in the model. Such mixture models predict by combining the individual predictions generated by the mixture components which correspond to the partitions in the data. Often the partitioned structure is latent, and has to be inferred when learning the mixture model. Directly evaluating the accuracy of the inferred partition structure is, in many cases, impossible because the ground truth cannot be obtained for comparison. However it can be assessed indirectly by measuring the prediction accuracy of the mixture model that arises from it. This thesis addresses the interplay between the improvement of predictive accuracy by uncovering latent cluster structure in data, and further addresses the validation of the estimated structure by measuring the accuracy of the resulting predictive model. In the application of filtering unsolicited emails, the emails in the training set are latently clustered into advertisement campaigns. Uncovering this latent structure allows filtering of future emails with very low false positive rates. In order to model the cluster structure, a Bayesian clustering model for dependent binary features is developed in this thesis. Knowing the clustering of emails into campaigns can also aid in uncovering which emails have been sent on behalf of the same network of captured hosts, so-called botnets. This association of emails to networks is another layer of latent clustering. Uncovering this latent structure allows service providers to further increase the accuracy of email filtering and to effectively defend against distributed denial-of-service attacks. To this end, a discriminative clustering model is derived in this thesis that is based on the graph of observed emails. The partitionings inferred using this model are evaluated through their capacity to predict the campaigns of new emails. Furthermore, when classifying the content of emails, statistical information about the sending server can be valuable. Learning a model that is able to make use of it requires training data that includes server statistics. In order to also use training data where the server statistics are missing, a model that is a mixture over potentially all substitutions thereof is developed. Another application is to predict the navigation behavior of the users of a website. Here, there is no a priori partitioning of the users into clusters, but to understand different usage scenarios and design different layouts for them, imposing a partitioning is necessary. The presented approach simultaneously optimizes the discriminative as well as the predictive power of the clusters. Each model is evaluated on real-world data and compared to baseline methods. The results show that explicitly modeling the assumptions about the latent cluster structure leads to improved predictions compared to the baselines. It is beneficial to incorporate a small number of hyperparameters that can be tuned to yield the best predictions in cases where the prediction accuracy can not be optimized directly.}, language = {en} } @article{HartmannEhlertFritz2019, author = {Hartmann, Julia and Ehlert, Antje and Fritz, Annemarie}, title = {Welche Rolle spielen sprachliche Parameter f{\"u}r die Entwicklung integrierter verbal-numerischer Konzepte im vierten Lebensjahr?}, series = {Fr{\"u}he Bildung : interdisziplin{\"a}re Zeitschrift f{\"u}r Forschung, Ausbildung und Praxis}, volume = {8}, journal = {Fr{\"u}he Bildung : interdisziplin{\"a}re Zeitschrift f{\"u}r Forschung, Ausbildung und Praxis}, number = {1}, publisher = {Hogrefe}, address = {G{\"o}ttingen}, issn = {2191-9186}, doi = {10.1026/2191-9186/a000410}, pages = {44 -- 52}, year = {2019}, abstract = {Der Beitrag untersucht, ob und zu welchen Anteilen fr{\"u}he sprachliche Kompetenzen numerische Kompetenzen vorhersagen. An 72 dreij{\"a}hrigen Kindern wurden numerische, verbal produktive und rezeptive sowie grammatische Leistungen zwei Mal im Abstand von drei Monaten erhoben. Mithilfe von Strukturgleichungsmodellen kann gezeigt werden, dass sprachliche und numerische Leistungen in diesem Alter noch wenig distinkt sind. F{\"u}r die numerischen Kompetenzen findet sich bereits in diesem Alter eine hohe interindividuelle Entwicklungsstabilit{\"a}t. Ein bedeutsamer Einfluss sprachlicher Kompetenz auf den Zuwachs mathematischer Kompetenz im vierten Lebensjahr konnte nicht nachgewiesen werden. Wir diskutieren die Ergebnisse vor dem Hintergrund der aktuellen Thesen zum Zusammenhang von Sprache und Numerik in der Entwicklung.}, language = {de} } @misc{HischeLarhlimiSchwarzetal.2012, author = {Hische, Manuela and Larhlimi, Abdelhalim and Schwarz, Franziska and Fischer-Rosinsk{\´y}, Antje and Bobbert, Thomas and Assmann, Anke and Catchpole, Gareth S. and Pfeiffer, Andreas F. H. and Willmitzer, Lothar and Selbig, Joachim and Spranger, Joachim}, title = {A distinct metabolic signature predictsdevelopment of fasting plasma glucose}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch Naturwissenschaftliche Reihe}, number = {850}, issn = {1866-8372}, doi = {10.25932/publishup-42740}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-427400}, pages = {12}, year = {2012}, abstract = {Background High blood glucose and diabetes are amongst the conditions causing the greatest losses in years of healthy life worldwide. Therefore, numerous studies aim to identify reliable risk markers for development of impaired glucose metabolism and type 2 diabetes. However, the molecular basis of impaired glucose metabolism is so far insufficiently understood. The development of so called 'omics' approaches in the recent years promises to identify molecular markers and to further understand the molecular basis of impaired glucose metabolism and type 2 diabetes. Although univariate statistical approaches are often applied, we demonstrate here that the application of multivariate statistical approaches is highly recommended to fully capture the complexity of data gained using high-throughput methods. Methods We took blood plasma samples from 172 subjects who participated in the prospective Metabolic Syndrome Berlin Potsdam follow-up study (MESY-BEPO Follow-up). We analysed these samples using Gas Chromatography coupled with Mass Spectrometry (GC-MS), and measured 286 metabolites. Furthermore, fasting glucose levels were measured using standard methods at baseline, and after an average of six years. We did correlation analysis and built linear regression models as well as Random Forest regression models to identify metabolites that predict the development of fasting glucose in our cohort. Results We found a metabolic pattern consisting of nine metabolites that predicted fasting glucose development with an accuracy of 0.47 in tenfold cross-validation using Random Forest regression. We also showed that adding established risk markers did not improve the model accuracy. However, external validation is eventually desirable. Although not all metabolites belonging to the final pattern are identified yet, the pattern directs attention to amino acid metabolism, energy metabolism and redox homeostasis. Conclusions We demonstrate that metabolites identified using a high-throughput method (GC-MS) perform well in predicting the development of fasting plasma glucose over several years. Notably, not single, but a complex pattern of metabolites propels the prediction and therefore reflects the complexity of the underlying molecular mechanisms. This result could only be captured by application of multivariate statistical approaches. Therefore, we highly recommend the usage of statistical methods that seize the complexity of the information given by high-throughput methods.}, language = {en} } @phdthesis{Jaeger2015, author = {J{\"a}ger, Lena Ann}, title = {Working memory and prediction in human sentence parsing}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-82517}, school = {Universit{\"a}t Potsdam}, pages = {xi, 144}, year = {2015}, abstract = {This dissertation investigates the working memory mechanism subserving human sentence processing and its relative contribution to processing difficulty as compared to syntactic prediction. Within the last decades, evidence for a content-addressable memory system underlying human cognition in general has accumulated (e.g., Anderson et al., 2004). In sentence processing research, it has been proposed that this general content-addressable architecture is also used for language processing (e.g., McElree, 2000). Although there is a growing body of evidence from various kinds of linguistic dependencies that is consistent with a general content-addressable memory subserving sentence processing (e.g., McElree et al., 2003; VanDyke2006), the case of reflexive-antecedent dependencies has challenged this view. It has been proposed that in the processing of reflexive-antecedent dependencies, a syntactic-structure based memory access is used rather than cue-based retrieval within a content-addressable framework (e.g., Sturt, 2003). Two eye-tracking experiments on Chinese reflexives were designed to tease apart accounts assuming a syntactic-structure based memory access mechanism from cue-based retrieval (implemented in ACT-R as proposed by Lewis and Vasishth (2005). In both experiments, interference effects were observed from noun phrases which syntactically do not qualify as the reflexive's antecedent but match the animacy requirement the reflexive imposes on its antecedent. These results are interpreted as evidence against a purely syntactic-structure based memory access. However, the exact pattern of effects observed in the data is only partially compatible with the Lewis and Vasishth cue-based parsing model. Therefore, an extension of the Lewis and Vasishth model is proposed. Two principles are added to the original model, namely 'cue confusion' and 'distractor prominence'. Although interference effects are generally interpreted in favor of a content-addressable memory architecture, an alternative explanation for interference effects in reflexive processing has been proposed which, crucially, might reconcile interference effects with a structure-based account. It has been argued that interference effects do not necessarily reflect cue-based retrieval interference in a content-addressable memory but might equally well be accounted for by interference effects which have already occurred at the moment of encoding the antecedent in memory (Dillon, 2011). Three experiments (eye-tracking and self-paced reading) on German reflexives and Swedish possessives were designed to tease apart cue-based retrieval interference from encoding interference. The results of all three experiments suggest that there is no evidence that encoding interference affects the retrieval of a reflexive's antecedent. Taken together, these findings suggest that the processing of reflexives can be explained with the same cue-based retrieval mechanism that has been invoked to explain syntactic dependency resolution in a range of other structures. This supports the view that the language processing system is located within a general cognitive architecture, with a general-purpose content-addressable working memory system operating on linguistic expressions. Finally, two experiments (self-paced reading and eye-tracking) using Chinese relative clauses were conducted to determine the relative contribution to sentence processing difficulty of working-memory processes as compared to syntactic prediction during incremental parsing. Chinese has the cross-linguistically rare property of being a language with subject-verb-object word order and pre-nominal relative clauses. This property leads to opposing predictions of expectation-based accounts and memory-based accounts with respect to the relative processing difficulty of subject vs. object relatives. Previous studies showed contradictory results, which has been attributed to different kinds local ambiguities confounding the materials (Lin and Bever, 2011). The two experiments presented are the first to compare Chinese relatives clauses in syntactically unambiguous contexts. The results of both experiments were consistent with the predictions of the expectation-based account of sentence processing but not with the memory-based account. From these findings, I conclude that any theory of human sentence processing needs to take into account the power of predictive processes unfolding in the human mind.}, language = {en} } @misc{KaminskiSchlagenhaufRappetal.2018, author = {Kaminski, Jakob A. and Schlagenhauf, Florian and Rapp, Michael Armin and Awasthi, Swapnil and Ruggeri, Barbara and Deserno, Lorenz and Banaschewski, Tobias and Bokde, Arun L. W. and Bromberg, Uli and B{\"u}chel, Christian and Quinlan, Erin Burke and Desrivi{\`e}res, Sylvane and Flor, Herta and Frouin, Vincent and Garavan, Hugh and Gowland, Penny and Ittermann, Bernd and Martinot, Jean-Luc and Paill{\`e}re Martinot, Marie-Laure and Nees, Frauke and Papadopoulos Orfanos, Dimitri and Paus, Tom{\´a}š and Poustka, Luise and Smolka, Michael N. and Fr{\"o}hner, Juliane H. and Walter, Henrik and Whelan, Robert and Ripke, Stephan and Schumann, Gunter and Heinz, Andreas}, title = {Epigenetic variance in dopamine D2 receptor}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {950}, issn = {1866-8372}, doi = {10.25932/publishup-42568}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-425687}, pages = {13}, year = {2018}, abstract = {Genetic and environmental factors both contribute to cognitive test performance. A substantial increase in average intelligence test results in the second half of the previous century within one generation is unlikely to be explained by genetic changes. One possible explanation for the strong malleability of cognitive performance measure is that environmental factors modify gene expression via epigenetic mechanisms. Epigenetic factors may help to understand the recent observations of an association between dopamine-dependent encoding of reward prediction errors and cognitive capacity, which was modulated by adverse life events. The possible manifestation of malleable biomarkers contributing to variance in cognitive test performance, and thus possibly contributing to the "missing heritability" between estimates from twin studies and variance explained by genetic markers, is still unclear. Here we show in 1475 healthy adolescents from the IMaging and GENetics (IMAGEN) sample that general IQ (gIQ) is associated with (1) polygenic scores for intelligence, (2) epigenetic modification of DRD2 gene, (3) gray matter density in striatum, and (4) functional striatal activation elicited by temporarily surprising reward-predicting cues. Comparing the relative importance for the prediction of gIQ in an overlapping subsample, our results demonstrate neurobiological correlates of the malleability of gIQ and point to equal importance of genetic variance, epigenetic modification of DRD2 receptor gene, as well as functional striatal activation, known to influence dopamine neurotransmission. Peripheral epigenetic markers are in need of confirmation in the central nervous system and should be tested in longitudinal settings specifically assessing individual and environmental factors that modify epigenetic structure.}, language = {en} } @misc{KisslingDormannGroeneveldetal.2012, author = {Kissling, W. D. and Dormann, Carsten F. and Groeneveld, Juergen and Hickler, Thomas and K{\"u}hn, Ingolf and McInerny, Greg J. and Montoya, Jose M. and R{\"o}mermann, Christine and Schiffers, Katja and Schurr, Frank Martin and Singer, Alexander and Svenning, Jens-Christian and Zimmermann, Niklaus E. and O'Hara, Robert B.}, title = {Towards novel approaches to modelling biotic interactions in multispecies assemblages at large spatial extents}, series = {Journal of biogeography}, volume = {39}, journal = {Journal of biogeography}, number = {12}, publisher = {Wiley-Blackwell}, address = {Hoboken}, issn = {0305-0270}, doi = {10.1111/j.1365-2699.2011.02663.x}, pages = {2163 -- 2178}, year = {2012}, abstract = {Aim Biotic interactions within guilds or across trophic levels have widely been ignored in species distribution models (SDMs). This synthesis outlines the development of species interaction distribution models (SIDMs), which aim to incorporate multispecies interactions at large spatial extents using interaction matrices. Location Local to global. Methods We review recent approaches for extending classical SDMs to incorporate biotic interactions, and identify some methodological and conceptual limitations. To illustrate possible directions for conceptual advancement we explore three principal ways of modelling multispecies interactions using interaction matrices: simple qualitative linkages between species, quantitative interaction coefficients reflecting interaction strengths, and interactions mediated by interaction currencies. We explain methodological advancements for static interaction data and multispecies time series, and outline methods to reduce complexity when modelling multispecies interactions. Results Classical SDMs ignore biotic interactions and recent SDM extensions only include the unidirectional influence of one or a few species. However, novel methods using error matrices in multivariate regression models allow interactions between multiple species to be modelled explicitly with spatial co-occurrence data. If time series are available, multivariate versions of population dynamic models can be applied that account for the effects and relative importance of species interactions and environmental drivers. These methods need to be extended by incorporating the non-stationarity in interaction coefficients across space and time, and are challenged by the limited empirical knowledge on spatio-temporal variation in the existence and strength of species interactions. Model complexity may be reduced by: (1) using prior ecological knowledge to set a subset of interaction coefficients to zero, (2) modelling guilds and functional groups rather than individual species, and (3) modelling interaction currencies and species effect and response traits. Main conclusions There is great potential for developing novel approaches that incorporate multispecies interactions into the projection of species distributions and community structure at large spatial extents. Progress can be made by: (1) developing statistical models with interaction matrices for multispecies co-occurrence datasets across large-scale environmental gradients, (2) testing the potential and limitations of methods for complexity reduction, and (3) sampling and monitoring comprehensive spatio-temporal data on biotic interactions in multispecies communities.}, language = {en} } @misc{Korup2020, author = {Korup, Oliver}, title = {Bayesian geomorphology}, series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {1}, issn = {1866-8372}, doi = {10.25932/publishup-53989}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-539892}, pages = {24}, year = {2020}, abstract = {The rapidly growing amount and diversity of data are confronting us more than ever with the need to make informed predictions under uncertainty. The adverse impacts of climate change and natural hazards also motivate our search for reliable predictions. The range of statistical techniques that geomorphologists use to tackle this challenge has been growing, but rarely involves Bayesian methods. Instead, many geomorphic models rely on estimated averages that largely miss out on the variability of form and process. Yet seemingly fixed estimates of channel heads, sediment rating curves or glacier equilibrium lines, for example, are all prone to uncertainties. Neighbouring scientific disciplines such as physics, hydrology or ecology have readily embraced Bayesian methods to fully capture and better explain such uncertainties, as the necessary computational tools have advanced greatly. The aim of this article is to introduce the Bayesian toolkit to scientists concerned with Earth surface processes and landforms, and to show how geomorphic models might benefit from probabilistic concepts. I briefly review the use of Bayesian reasoning in geomorphology, and outline the corresponding variants of regression and classification in several worked examples.}, language = {en} } @article{Korup2020, author = {Korup, Oliver}, title = {Bayesian geomorphology}, series = {Earth surface processes and landforms : the journal of the British Geomorphological Research Group}, volume = {46}, journal = {Earth surface processes and landforms : the journal of the British Geomorphological Research Group}, number = {1}, publisher = {Wiley}, address = {Hoboken}, issn = {0197-9337}, doi = {10.1002/esp.4995}, pages = {151 -- 172}, year = {2020}, abstract = {The rapidly growing amount and diversity of data are confronting us more than ever with the need to make informed predictions under uncertainty. The adverse impacts of climate change and natural hazards also motivate our search for reliable predictions. The range of statistical techniques that geomorphologists use to tackle this challenge has been growing, but rarely involves Bayesian methods. Instead, many geomorphic models rely on estimated averages that largely miss out on the variability of form and process. Yet seemingly fixed estimates of channel heads, sediment rating curves or glacier equilibrium lines, for example, are all prone to uncertainties. Neighbouring scientific disciplines such as physics, hydrology or ecology have readily embraced Bayesian methods to fully capture and better explain such uncertainties, as the necessary computational tools have advanced greatly. The aim of this article is to introduce the Bayesian toolkit to scientists concerned with Earth surface processes and landforms, and to show how geomorphic models might benefit from probabilistic concepts. I briefly review the use of Bayesian reasoning in geomorphology, and outline the corresponding variants of regression and classification in several worked examples.}, language = {en} } @article{MooijTrolleJeppesenetal.2010, author = {Mooij, Wolf M. and Trolle, Dennis and Jeppesen, Erik and Arhonditsis, George B. and Belolipetsky, Pavel V. and Chitamwebwa, Deonatus B. R. and Degermendzhy, Andrey G. and DeAngelis, Donald L. and Domis, Lisette Nicole de Senerpont and Downing, Andrea S. and Elliott, J. Alex and Fragoso Jr, Carlos Ruberto and Gaedke, Ursula and Genova, Svetlana N. and Gulati, Ramesh D. and H{\aa}kanson, Lars and Hamilton, David P. and Hipsey, Matthew R. and 't Hoen, Jochem and H{\"u}lsmann, Stephan and Los, F. Hans and Makler-Pick, Vardit and Petzoldt, Thomas and Prokopkin, Igor G. and Rinke, Karsten and Schep, Sebastiaan A. and Tominaga, Koji and Van Dam, Anne A. and Van Nes, Egbert H. and Wells, Scott A. and Janse, Jan H.}, title = {Challenges and opportunities for integrating lake ecosystem modelling approaches}, series = {Aquatic ecology}, volume = {44}, journal = {Aquatic ecology}, publisher = {Springer Science + Business Media B.V.}, address = {Dordrecht}, issn = {1573-5125}, doi = {10.1007/s10452-010-9339-3}, pages = {633 -- 667}, year = {2010}, abstract = {A large number and wide variety of lake ecosystem models have been developed and published during the past four decades. We identify two challenges for making further progress in this field. One such challenge is to avoid developing more models largely following the concept of others ('reinventing the wheel'). The other challenge is to avoid focusing on only one type of model, while ignoring new and diverse approaches that have become available ('having tunnel vision'). In this paper, we aim at improving the awareness of existing models and knowledge of concurrent approaches in lake ecosystem modelling, without covering all possible model tools and avenues. First, we present a broad variety of modelling approaches. To illustrate these approaches, we give brief descriptions of rather arbitrarily selected sets of specific models. We deal with static models (steady state and regression models), complex dynamic models (CAEDYM, CE-QUAL-W2, Delft 3D-ECO, LakeMab, LakeWeb, MyLake, PCLake, PROTECH, SALMO), structurally dynamic models and minimal dynamic models. We also discuss a group of approaches that could all be classified as individual based: super-individual models (Piscator, Charisma), physiologically structured models, stage-structured models and traitbased models. We briefly mention genetic algorithms, neural networks, Kalman filters and fuzzy logic. Thereafter, we zoom in, as an in-depth example, on the multi-decadal development and application of the lake ecosystem model PCLake and related models (PCLake Metamodel, Lake Shira Model, IPH-TRIM3D-PCLake). In the discussion, we argue that while the historical development of each approach and model is understandable given its 'leading principle', there are many opportunities for combining approaches. We take the point of view that a single 'right' approach does not exist and should not be strived for. Instead, multiple modelling approaches, applied concurrently to a given problem, can help develop an integrative view on the functioning of lake ecosystems. We end with a set of specific recommendations that may be of help in the further development of lake ecosystem models.}, language = {en} } @misc{MooijTrolleJeppesenetal.2010, author = {Mooij, Wolf M. and Trolle, Dennis and Jeppesen, Erik and Arhonditsis, George B. and Belolipetsky, Pavel V. and Chitamwebwa, Deonatus B. R. and Degermendzhy, Andrey G. and DeAngelis, Donald L. and Domis, Lisette Nicole de Senerpont and Downing, Andrea S. and Elliott, J. Alex and Fragoso Jr., Carlos Ruberto and Gaedke, Ursula and Genova, Svetlana N. and Gulati, Ramesh D. and H{\aa}kanson, Lars and Hamilton, David P. and Hipsey, Matthew R. and 't Hoen, Jochem and H{\"u}lsmann, Stephan and Los, F. Hans and Makler-Pick, Vardit and Petzoldt, Thomas and Prokopkin, Igor G. and Rinke, Karsten and Schep, Sebastiaan A. and Tominaga, Koji and Van Dam, Anne A. and Van Nes, Egbert H. and Wells, Scott A. and Janse, Jan H.}, title = {Challenges and opportunities for integrating lake ecosystem modelling approaches}, series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {1326}, issn = {1866-8372}, doi = {10.25932/publishup-42983}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-429839}, pages = {35}, year = {2010}, abstract = {A large number and wide variety of lake ecosystem models have been developed and published during the past four decades. We identify two challenges for making further progress in this field. One such challenge is to avoid developing more models largely following the concept of others ('reinventing the wheel'). The other challenge is to avoid focusing on only one type of model, while ignoring new and diverse approaches that have become available ('having tunnel vision'). In this paper, we aim at improving the awareness of existing models and knowledge of concurrent approaches in lake ecosystem modelling, without covering all possible model tools and avenues. First, we present a broad variety of modelling approaches. To illustrate these approaches, we give brief descriptions of rather arbitrarily selected sets of specific models. We deal with static models (steady state and regression models), complex dynamic models (CAEDYM, CE-QUAL-W2, Delft 3D-ECO, LakeMab, LakeWeb, MyLake, PCLake, PROTECH, SALMO), structurally dynamic models and minimal dynamic models. We also discuss a group of approaches that could all be classified as individual based: super-individual models (Piscator, Charisma), physiologically structured models, stage-structured models and traitbased models. We briefly mention genetic algorithms, neural networks, Kalman filters and fuzzy logic. Thereafter, we zoom in, as an in-depth example, on the multi-decadal development and application of the lake ecosystem model PCLake and related models (PCLake Metamodel, Lake Shira Model, IPH-TRIM3D-PCLake). In the discussion, we argue that while the historical development of each approach and model is understandable given its 'leading principle', there are many opportunities for combining approaches. We take the point of view that a single 'right' approach does not exist and should not be strived for. Instead, multiple modelling approaches, applied concurrently to a given problem, can help develop an integrative view on the functioning of lake ecosystems. We end with a set of specific recommendations that may be of help in the further development of lake ecosystem models.}, language = {en} } @misc{ProtGentileAndersonetal.2013, author = {Prot, Sara and Gentile, Douglas A. and Anderson, Craig A. and Suzuki, Kanae and Swing, Edward and Lim, Kam Ming and Horiuchi, Yukiko and Jelic, Margareta and Krah{\´e}, Barbara and Liuqing, Wei and Liau, Albert K. and Khoo, Angeline and Petrescu, Poesis Diana and Sakamoto, Akira and Tajima, Sachi and Toma, Roxana Andreea and Warburton, Wayne and Zhang, Xuemin and Lam, Ben Chun Pan}, title = {Long-term relations among prosocial-media use, empathy, and prosocial behavior}, series = {Postprints der Universit{\"a}t Potsdam : Humanwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Humanwissenschaftliche Reihe}, number = {389}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-404136}, pages = {11}, year = {2013}, abstract = {Despite recent growth of research on the effects of prosocial media, processes underlying these effects are not well understood. Two studies explored theoretically relevant mediators and moderators of the effects of prosocial media on helping. Study 1 examined associations among prosocial- and violent-media use, empathy, and helping in samples from seven countries. Prosocial-media use was positively associated with helping. This effect was mediated by empathy and was similar across cultures. Study 2 explored longitudinal relations among prosocial-video-game use, violent-video-game use, empathy, and helping in a large sample of Singaporean children and adolescents measured three times across 2 years. Path analyses showed significant longitudinal effects of prosocial- and violent-video-game use on prosocial behavior through empathy. Latent-growth-curve modeling for the 2-year period revealed that change in video-game use significantly affected change in helping, and that this relationship was mediated by change in empathy.}, language = {en} } @article{ProtGentileAndersonetal.2014, author = {Prot, Sara and Gentile, Douglas A. and Anderson, Craig A. and Suzuki, Kanae and Swing, Edward and Lim, Kam Ming and Horiuchi, Yukiko and Jelic, Margareta and Krah{\´e}, Barbara and Wei Liuqing, and Liau, Albert K. and Khoo, Angeline and Petrescu, Poesis Diana and Sakamoto, Akira and Tajima, Sachi and Toma, Roxana Andreea and Warburton, Wayne and Zhang, Xuemin and Lam, Ben Chun Pan}, title = {Long-term relations among prosocial-media use, empathy, and prosocial behavior}, series = {Psychological science : research, theory, \& application in psychology and related sciences}, volume = {25}, journal = {Psychological science : research, theory, \& application in psychology and related sciences}, number = {2}, publisher = {Sage Publ.}, address = {Thousand Oaks}, issn = {0956-7976}, doi = {10.1177/0956797613503854}, pages = {358 -- 368}, year = {2014}, abstract = {Despite recent growth of research on the effects of prosocial media, processes underlying these effects are not well understood. Two studies explored theoretically relevant mediators and moderators of the effects of prosocial media on helping. Study 1 examined associations among prosocial- and violent-media use, empathy, and helping in samples from seven countries. Prosocial-media use was positively associated with helping. This effect was mediated by empathy and was similar across cultures. Study 2 explored longitudinal relations among prosocial-video-game use, violent-video-game use, empathy, and helping in a large sample of Singaporean children and adolescents measured three times across 2 years. Path analyses showed significant longitudinal effects of prosocial- and violent-video-game use on prosocial behavior through empathy. Latent-growth-curve modeling for the 2-year period revealed that change in video-game use significantly affected change in helping, and that this relationship was mediated by change in empathy.}, language = {en} } @phdthesis{Quade2018, author = {Quade, Markus}, title = {Symbolic regression for identification, prediction, and control of dynamical systems}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-419790}, school = {Universit{\"a}t Potsdam}, pages = {xiii, 134}, year = {2018}, abstract = {In the present work, we use symbolic regression for automated modeling of dynamical systems. Symbolic regression is a powerful and general method suitable for data-driven identification of mathematical expressions. In particular, the structure and parameters of those expressions are identified simultaneously. We consider two main variants of symbolic regression: sparse regression-based and genetic programming-based symbolic regression. Both are applied to identification, prediction and control of dynamical systems. We introduce a new methodology for the data-driven identification of nonlinear dynamics for systems undergoing abrupt changes. Building on a sparse regression algorithm derived earlier, the model after the change is defined as a minimum update with respect to a reference model of the system identified prior to the change. The technique is successfully exemplified on the chaotic Lorenz system and the van der Pol oscillator. Issues such as computational complexity, robustness against noise and requirements with respect to data volume are investigated. We show how symbolic regression can be used for time series prediction. Again, issues such as robustness against noise and convergence rate are investigated us- ing the harmonic oscillator as a toy problem. In combination with embedding, we demonstrate the prediction of a propagating front in coupled FitzHugh-Nagumo oscillators. Additionally, we show how we can enhance numerical weather predictions to commercially forecast power production of green energy power plants. We employ symbolic regression for synchronization control in coupled van der Pol oscillators. Different coupling topologies are investigated. We address issues such as plausibility and stability of the control laws found. The toolkit has been made open source and is used in turbulence control applications. Genetic programming based symbolic regression is very versatile and can be adapted to many optimization problems. The heuristic-based algorithm allows for cost efficient optimization of complex tasks. We emphasize the ability of symbolic regression to yield white-box models. In contrast to black-box models, such models are accessible and interpretable which allows the usage of established tool chains.}, language = {en} } @article{Rabovsky2020, author = {Rabovsky, Milena}, title = {Change in a probabilistic representation of meaning can account for N400 effects on articles}, series = {Neuropsychologia : an international journal in behavioural and cognitive neuroscience}, volume = {143}, journal = {Neuropsychologia : an international journal in behavioural and cognitive neuroscience}, publisher = {Elsevier}, address = {Oxford}, issn = {0028-3932}, doi = {10.1016/j.neuropsychologia.2020.107466}, pages = {7}, year = {2020}, abstract = {Increased N400 amplitudes on indefinite articles (a/an) incompatible with expected nouns have been initially taken as strong evidence for probabilistic pre-activation of phonological word forms, and recently been intensely debated because they have been difficult to replicate. Here, these effects are simulated using a neural network model of sentence comprehension that we previously used to simulate a broad range of empirical N400 effects. The model produces the effects when the cue validity of the articles concerning upcoming noun meaning in the learning environment is high, but fails to produce the effects when the cue validity of the articles is low due to adjectives presented between articles and nouns during training. These simulations provide insight into one of the factors potentially contributing to the small size of the effects in empirical studies and generate predictions for cross-linguistic differences in article induced N400 effects based on articles' cue validity. The model accounts for article induced N400 effects without assuming pre-activation of word forms, and instead simulates these effects as the stimulus-induced change in a probabilistic representation of meaning corresponding to an implicit semantic prediction error.}, language = {en} } @article{Rabovsky2020, author = {Rabovsky, Milena}, title = {Change in a probabilistic representation of meaning can account for N400 effects on articles: a neural network model}, series = {Neuropsychologia}, volume = {143}, journal = {Neuropsychologia}, publisher = {Elsevier}, address = {Amsterdam}, pages = {7}, year = {2020}, abstract = {Increased N400 amplitudes on indefinite articles (a/an) incompatible with expected nouns have been initially taken as strong evidence for probabilistic pre-activation of phonological word forms, and recently been intensely debated because they have been difficult to replicate. Here, these effects are simulated using a neural network model of sentence comprehension that we previously used to simulate a broad range of empirical N400 effects. The model produces the effects when the cue validity of the articles concerning upcoming noun meaning in the learning environment is high, but fails to produce the effects when the cue validity of the articles is low due to adjectives presented between articles and nouns during training. These simulations provide insight into one of the factors potentially contributing to the small size of the effects in empirical studies and generate predictions for cross-linguistic differences in article induced N400 effects based on articles' cue validity. The model accounts for article induced N400 effects without assuming pre-activation of word forms, and instead simulates these effects as the stimulus-induced change in a probabilistic representation of meaning corresponding to an implicit semantic prediction error.}, language = {en} } @misc{Rabovsky2020, author = {Rabovsky, Milena}, title = {Change in a probabilistic representation of meaning can account for N400 effects on articles: a neural network model}, series = {Postprints der Universit{\"a}t Potsdam : Humanwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Humanwissenschaftliche Reihe}, issn = {1866-8364}, doi = {10.25932/publishup-52698}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-526988}, pages = {9}, year = {2020}, abstract = {Increased N400 amplitudes on indefinite articles (a/an) incompatible with expected nouns have been initially taken as strong evidence for probabilistic pre-activation of phonological word forms, and recently been intensely debated because they have been difficult to replicate. Here, these effects are simulated using a neural network model of sentence comprehension that we previously used to simulate a broad range of empirical N400 effects. The model produces the effects when the cue validity of the articles concerning upcoming noun meaning in the learning environment is high, but fails to produce the effects when the cue validity of the articles is low due to adjectives presented between articles and nouns during training. These simulations provide insight into one of the factors potentially contributing to the small size of the effects in empirical studies and generate predictions for cross-linguistic differences in article induced N400 effects based on articles' cue validity. The model accounts for article induced N400 effects without assuming pre-activation of word forms, and instead simulates these effects as the stimulus-induced change in a probabilistic representation of meaning corresponding to an implicit semantic prediction error.}, language = {en} } @article{ReibisKuehlSalzwedeletal.2017, author = {Reibis, Rona Katharina and K{\"u}hl, Uwe and Salzwedel, Annett and Rasawieh, Mortesa and Eichler, Sarah and Wegscheider, Karl and V{\"o}ller, Heinz}, title = {Return to work in heart failure patients with suspected viral myocarditis}, series = {SAGE Open Medicine}, volume = {5}, journal = {SAGE Open Medicine}, publisher = {Sage}, address = {Thousand Oaks, Calif.}, issn = {2050-3121}, doi = {10.1177/2050312117744978}, year = {2017}, abstract = {Background: Endomyocardial biopsy is considered as the gold standard in patients with suspected myocarditis. We aimed to evaluate the impact of bioptic findings on prediction of successful return to work. Methods: In 1153 patients (48.9 ± 12.4 years, 66.2\% male), who were hospitalized due to symptoms of left heart failure between 2005 and 2012, an endomyocardial biopsy was performed. Routine clinical and laboratory data, sociodemographic parameters, and noninvasive and invasive cardiac variables including endomyocardial biopsy were registered. Data were linked with return to work data from the German statutory pension insurance program and analyzed by Cox regression. Results: A total of 220 patients had a complete data set of hospital and insurance information. Three quarters of patients were virus-positive (54.2\% parvovirus B19, other or mixed infection 16.7\%). Mean invasive left ventricular ejection fraction was 47.1\% ± 18.6\% (left ventricular ejection fraction <45\% in 46.3\%). Return to work was achieved after a mean interval of 168.8 ± 347.7 days in 220 patients (after 6, 12, and 24 months in 61.3\%, 72.2\%, and 76.4\%). In multivariate regression analysis, only age (per 10 years, hazard ratio, 1.27; 95\% confidence interval, 1.10-1.46; p = 0.001) and left ventricular ejection fraction (per 5\% increase, hazard ratio, 1.07; 95\% confidence interval, 1.03-1.12; p = 0.002) were associated with increased, elevated work intensity (heavy vs light, congestive heart failure, 0.58; 95\% confidence interval, 0.34-0.99; p < 0.049) with decreased probability of return to work. None of the endomyocardial biopsy-derived parameters was significantly associated with return to work in the total group as well as in the subgroup of patients with biopsy-proven myocarditis. Conclusion: Added to established predictors, bioptic data demonstrated no additional impact for return to work probability. Thus, socio-medical evaluation of patients with suspected myocarditis furthermore remains an individually oriented process based primarily on clinical and functional parameters.}, language = {en} } @misc{ReibisKuehlSalzwedeletal.2018, author = {Reibis, Rona Katharina and K{\"u}hl, Uwe and Salzwedel, Annett and Rasawieh, Mortesa and Eichler, Sarah and Wegscheider, Karl and V{\"o}ller, Heinz}, title = {Return to work in heart failure patients with suspected viral myocarditis}, series = {Postprints der Universit{\"a}t Potsdam : Humanwissenschaftliche Reihe}, volume = {5}, journal = {Postprints der Universit{\"a}t Potsdam : Humanwissenschaftliche Reihe}, number = {378}, issn = {1866-8364}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-407637}, year = {2018}, abstract = {Background: Endomyocardial biopsy is considered as the gold standard in patients with suspected myocarditis. We aimed to evaluate the impact of bioptic findings on prediction of successful return to work. Methods: In 1153 patients (48.9 ± 12.4 years, 66.2\% male), who were hospitalized due to symptoms of left heart failure between 2005 and 2012, an endomyocardial biopsy was performed. Routine clinical and laboratory data, sociodemographic parameters, and noninvasive and invasive cardiac variables including endomyocardial biopsy were registered. Data were linked with return to work data from the German statutory pension insurance program and analyzed by Cox regression. Results: A total of 220 patients had a complete data set of hospital and insurance information. Three quarters of patients were virus-positive (54.2\% parvovirus B19, other or mixed infection 16.7\%). Mean invasive left ventricular ejection fraction was 47.1\% ± 18.6\% (left ventricular ejection fraction <45\% in 46.3\%). Return to work was achieved after a mean interval of 168.8 ± 347.7 days in 220 patients (after 6, 12, and 24 months in 61.3\%, 72.2\%, and 76.4\%). In multivariate regression analysis, only age (per 10 years, hazard ratio, 1.27; 95\% confidence interval, 1.10-1.46; p = 0.001) and left ventricular ejection fraction (per 5\% increase, hazard ratio, 1.07; 95\% confidence interval, 1.03-1.12; p = 0.002) were associated with increased, elevated work intensity (heavy vs light, congestive heart failure, 0.58; 95\% confidence interval, 0.34-0.99; p < 0.049) with decreased probability of return to work. None of the endomyocardial biopsy-derived parameters was significantly associated with return to work in the total group as well as in the subgroup of patients with biopsy-proven myocarditis. Conclusion: Added to established predictors, bioptic data demonstrated no additional impact for return to work probability. Thus, socio-medical evaluation of patients with suspected myocarditis furthermore remains an individually oriented process based primarily on clinical and functional parameters.}, language = {en} } @phdthesis{RoggeSolti2014, author = {Rogge-Solti, Andreas}, title = {Probabilistic Estimation of Unobserved Process Events}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-70426}, school = {Universit{\"a}t Potsdam}, year = {2014}, abstract = {Organizations try to gain competitive advantages, and to increase customer satisfaction. To ensure the quality and efficiency of their business processes, they perform business process management. An important part of process management that happens on the daily operational level is process controlling. A prerequisite of controlling is process monitoring, i.e., keeping track of the performed activities in running process instances. Only by process monitoring can business analysts detect delays and react to deviations from the expected or guaranteed performance of a process instance. To enable monitoring, process events need to be collected from the process environment. When a business process is orchestrated by a process execution engine, monitoring is available for all orchestrated process activities. Many business processes, however, do not lend themselves to automatic orchestration, e.g., because of required freedom of action. This situation is often encountered in hospitals, where most business processes are manually enacted. Hence, in practice it is often inefficient or infeasible to document and monitor every process activity. Additionally, manual process execution and documentation is prone to errors, e.g., documentation of activities can be forgotten. Thus, organizations face the challenge of process events that occur, but are not observed by the monitoring environment. These unobserved process events can serve as basis for operational process decisions, even without exact knowledge of when they happened or when they will happen. An exemplary decision is whether to invest more resources to manage timely completion of a case, anticipating that the process end event will occur too late. This thesis offers means to reason about unobserved process events in a probabilistic way. We address decisive questions of process managers (e.g., "when will the case be finished?", or "when did we perform the activity that we forgot to document?") in this thesis. As main contribution, we introduce an advanced probabilistic model to business process management that is based on a stochastic variant of Petri nets. We present a holistic approach to use the model effectively along the business process lifecycle. Therefore, we provide techniques to discover such models from historical observations, to predict the termination time of processes, and to ensure quality by missing data management. We propose mechanisms to optimize configuration for monitoring and prediction, i.e., to offer guidance in selecting important activities to monitor. An implementation is provided as a proof of concept. For evaluation, we compare the accuracy of the approach with that of state-of-the-art approaches using real process data of a hospital. Additionally, we show its more general applicability in other domains by applying the approach on process data from logistics and finance.}, language = {en} } @inproceedings{RudianHaasePinkwart2022, author = {Rudian, Sylvio Leo and Haase, Jennifer and Pinkwart, Niels}, title = {Predicting creativity in online courses}, series = {2022 International Conference on Advanced Learning Technologies (ICALT)}, booktitle = {2022 International Conference on Advanced Learning Technologies (ICALT)}, publisher = {IEEE}, address = {Piscataway, NJ}, isbn = {978-1-6654-9519-6}, doi = {10.1109/ICALT55010.2022.00056}, pages = {164 -- 168}, year = {2022}, abstract = {Many prediction tasks can be done based on users' trace data. This paper explores divergent and convergent thinking as person-related attributes and predicts them based on features gathered in an online course. We use the logfile data of a short Moodle course, combined with an image test (IMT), the Alternate Uses Task (AUT), the Remote Associates Test (RAT), and creative self-efficacy (CSE). Our results show that originality and elaboration metrics can be predicted with an accuracy of ~.7 in cross-validation, whereby predicting fluency and RAT scores perform worst. CSE items can be predicted with an accuracy of ~.45. The best performing model is a Random Forest Tree, where the features were reduced using a Linear Discriminant Analysis in advance. The promising results can help to adjust online courses to the learners' needs based on their creative performances.}, language = {en} } @article{RyngajlloChildsLohseetal.2011, author = {Ryngajllo, Malgorzata and Childs, Liam H. and Lohse, Marc and Giorgi, Federico M. and Lude, Anja and Selbig, Joachim and Usadel, Bj{\"o}rn}, title = {SLocX predicting subcellular localization of Arabidopsis proteins leveraging gene expression data}, series = {Frontiers in plant science}, volume = {2}, journal = {Frontiers in plant science}, publisher = {Frontiers Research Foundation}, address = {Lausanne}, issn = {1664-462X}, doi = {10.3389/fpls.2011.00043}, pages = {19}, year = {2011}, abstract = {Despite the growing volume of experimentally validated knowledge about the subcellular localization of plant proteins, a well performing in silico prediction tool is still a necessity. Existing tools, which employ information derived from protein sequence alone, offer limited accuracy and/or rely on full sequence availability. We explored whether gene expression profiling data can be harnessed to enhance prediction performance. To achieve this, we trained several support vector machines to predict the subcellular localization of Arabidopsis thaliana proteins using sequence derived information, expression behavior, or a combination of these data and compared their predictive performance through a cross-validation test. We show that gene expression carries information about the subcellular localization not available in sequence information, yielding dramatic benefits for plastid localization prediction, and some notable improvements for other compartments such as the mito-chondrion, the Golgi, and the plasma membrane. Based on these results, we constructed a novel subcellular localization prediction engine, SLocX, combining gene expression profiling data with protein sequence-based information. We then validated the results of this engine using an independent test set of annotated proteins and a transient expression of GFP fusion proteins. Here, we present the prediction framework and a website of predicted localizations for Arabidopsis. The relatively good accuracy of our prediction engine, even in cases where only partial protein sequence is available (e.g., in sequences lacking the N-terminal region), offers a promising opportunity for similar application to non-sequenced or poorly annotated plant species. Although the prediction scope of our method is currently limited by the availability of expression information on the ATH1 array, we believe that the advances in measuring gene expression technology will make our method applicable for all Arabidopsis proteins.}, language = {en} } @inproceedings{RuedianHaasePinkwart2021, author = {R{\"u}dian, Sylvio Leo and Haase, Jennifer and Pinkwart, Niels}, title = {The relation of convergent thinking and trace data in an online course}, series = {Die 19. Fachtagung Bildungstechnologien (DELFI) / Lecture Notes in Informatics (LNI)}, booktitle = {Die 19. Fachtagung Bildungstechnologien (DELFI) / Lecture Notes in Informatics (LNI)}, publisher = {Gesellschaft f{\"u}r Informatik}, address = {Bonn}, pages = {181 -- 186}, year = {2021}, abstract = {Many prediction tasks can be done based on users' trace data. In this paper, we explored convergent thinking as a personality-related attribute and its relation to features gathered in interactive and non-interactive tasks of an online course. This is an under-utilized attribute that could be used for adapting online courses according to the creativity level to enhance the motivation of learners. Therefore, we used the logfile data of a 60 minutes Moodle course with N=128 learners, combined with the Remote Associates Test (RAT). We explored the trace data and found a weak correlation between interactive tasks and the RAT score, which was the highest considering the overall dataset. We trained a Random Forest Regressor to predict convergent thinking based on the trace data and analyzed the feature importance. The result has shown that the interactive tasks have the highest importance in prediction, but the accuracy is very low. We discuss the potential for personalizing online courses and address further steps to improve the applicability.}, language = {en} } @phdthesis{Schlenter2019, author = {Schlenter, Judith}, title = {Predictive language processing in late bilinguals}, doi = {10.25932/publishup-43249}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-432498}, school = {Universit{\"a}t Potsdam}, pages = {251}, year = {2019}, abstract = {The current thesis examined how second language (L2) speakers of German predict upcoming input during language processing. Early research has shown that the predictive abilities of L2 speakers relative to L1 speakers are limited, resulting in the proposal of the Reduced Ability to Generate Expectations (RAGE) hypothesis. Considering that prediction is assumed to facilitate language processing in L1 speakers and probably plays a role in language learning, the assumption that L1/L2 differences can be explained in terms of different processing mechanisms is a particularly interesting approach. However, results from more recent studies on the predictive processing abilities of L2 speakers have indicated that the claim of the RAGE hypothesis is too broad and that prediction in L2 speakers could be selectively limited. In the current thesis, the RAGE hypothesis was systematically put to the test. In this thesis, German L1 and highly proficient late L2 learners of German with Russian as L1 were tested on their predictive use of one or more information sources that exist as cues to sentence interpretation in both languages, to test for selective limits. The results showed that, in line with previous findings, L2 speakers can use the lexical-semantics of verbs to predict the upcoming noun. Here the level of prediction was more systematically controlled for than in previous studies by using verbs that restrict the selection of upcoming nouns to the semantic category animate or inanimate. Hence, prediction in L2 processing is possible. At the same time, this experiment showed that the L2 group was slower/less certain than the L1 group. Unlike previous studies, the experiment on case marking demonstrated that L2 speakers can use this morphosyntactic cue for prediction. Here, the use of case marking was tested by manipulating the word order (Dat > Acc vs. Acc > Dat) in double object constructions after a ditransitive verb. Both the L1 and the L2 group showed a difference between the two word order conditions that emerged within the critical time window for an anticipatory effect, indicating their sensitivity towards case. However, the results for the post-critical time window pointed to a higher uncertainty in the L2 group, who needed more time to integrate incoming information and were more affected by the word order variation than the L1 group, indicating that they relied more on surface-level information. A different cue weighting was also found in the experiment testing whether participants predict upcoming reference based on implicit causality information. Here, an additional child L1 group was tested, who had a lower memory capacity than the adult L2 group, as confirmed by a digit span task conducted with both learner groups. Whereas the children were only slightly delayed compared to the adult L1 group and showed the same effect of condition, the L2 speakers showed an over-reliance on surface-level information (first-mention/subjecthood). Hence, the pattern observed resulted more likely from L1/L2 differences than from resource deficits. The reviewed studies and the experiments conducted show that L2 prediction is affected by a range of factors. While some of the factors can be attributed to more individual differences (e.g., language similarity, slower processing) and can be interpreted by L2 processing accounts assuming that L1 and L2 processing are basically the same, certain limits are better explained by accounts that assume more substantial L1/L2 differences. Crucially, the experimental results demonstrate that the RAGE hypothesis should be refined: Although prediction as a fast-operating mechanism is likely to be affected in L2 speakers, there is no indication that prediction is the dominant source of L1/L2 differences. The results rather demonstrate that L2 speakers show a different weighting of cues and rely more on semantic and surface-level information to predict as well as to integrate incoming information.}, language = {en} } @article{SchoknechtRoehmSchlesewskyetal.2022, author = {Schoknecht, Pia and Roehm, Dietmar and Schlesewsky, Matthias and Bornkessel-Schlesewsky, Ina}, title = {The interaction of predictive processing and similarity-based retrieval interference}, series = {Language, cognition and neuroscience}, volume = {37}, journal = {Language, cognition and neuroscience}, number = {7}, publisher = {Routledge, Taylor \& Francis Group}, address = {Abingdon}, issn = {2327-3798}, doi = {10.1080/23273798.2022.2026421}, pages = {883 -- 901}, year = {2022}, abstract = {Language processing requires memory retrieval to integrate current input with previous context and making predictions about upcoming input. We propose that prediction and retrieval are two sides of the same coin, i.e. functionally the same, as they both activate memory representations. Under this assumption, memory retrieval and prediction should interact: Retrieval interference can only occur at a word that triggers retrieval and a fully predicted word would not do that. The present study investigated the proposed interaction with event-related potentials (ERPs) during the processing of sentence pairs in German. Predictability was measured via cloze probability. Memory retrieval was manipulated via the position of a distractor inducing proactive or retroactive similarity-based interference. Linear mixed model analyses provided evidence for the hypothesised interaction in a broadly distributed negativity, which we discuss in relation to the interference ERP literature. Our finding supports the proposal that memory retrieval and prediction are functionally the same.}, language = {en} } @misc{SeibertMerzApel2017, author = {Seibert, Mathias and Merz, Bruno and Apel, Heiko}, title = {Seasonal forecasting of hydrological drought in the Limpopo Basin}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch Naturwissenschaftliche Reihe}, number = {626}, doi = {10.25932/publishup-41844}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-418442}, pages = {1611 -- 1629}, year = {2017}, abstract = {The Limpopo Basin in southern Africa is prone to droughts which affect the livelihood of millions of people in South Africa, Botswana, Zimbabwe and Mozambique. Seasonal drought early warning is thus vital for the whole region. In this study, the predictability of hydrological droughts during the main runoff period from December to May is assessed using statistical approaches. Three methods (multiple linear models, artificial neural networks, random forest regression trees) are compared in terms of their ability to forecast streamflow with up to 12 months of lead time. The following four main findings result from the study. 1. There are stations in the basin at which standardised streamflow is predictable with lead times up to 12 months. The results show high inter-station differences of forecast skill but reach a coefficient of determination as high as 0.73 (cross validated). 2. A large range of potential predictors is considered in this study, comprising well-established climate indices, customised teleconnection indices derived from sea surface temperatures and antecedent streamflow as a proxy of catchment conditions. El Nino and customised indices, representing sea surface temperature in the Atlantic and Indian oceans, prove to be important teleconnection predictors for the region. Antecedent streamflow is a strong predictor in small catchments (with median 42\% explained variance), whereas teleconnections exert a stronger influence in large catchments. 3. Multiple linear models show the best forecast skill in this study and the greatest robustness compared to artificial neural networks and random forest regression trees, despite their capabilities to represent nonlinear relationships. 4. Employed in early warning, the models can be used to forecast a specific drought level. Even if the coefficient of determination is low, the forecast models have a skill better than a climatological forecast, which is shown by analysis of receiver operating characteristics (ROCs). Seasonal statistical forecasts in the Limpopo show promising results, and thus it is recommended to employ them as complementary to existing forecasts in order to strengthen preparedness for droughts.}, language = {en} } @article{SprinzdeMesquitaKallbekkenetal.2016, author = {Sprinz, Detlef F. and de Mesquita, Bruce Bueno and Kallbekken, Steffen and Stokman, Frans and Saelen, Hakon and Thomson, Robert}, title = {Predicting Paris: Multi-Method Approaches to Forecast the Outcomes of Global Climate Negotiations}, series = {Politics and Governance}, volume = {4}, journal = {Politics and Governance}, publisher = {Cogitatio Press}, address = {Lisbon}, issn = {2183-2463}, doi = {10.17645/pag.v4i3.654}, pages = {172 -- 187}, year = {2016}, abstract = {We examine the negotiations held under the auspices of the United Nations Framework Convention of Climate Change in Paris, December 2015. Prior to these negotiations, there was considerable uncertainty about whether an agreement would be reached, particularly given that the world's leaders failed to do so in the 2009 negotiations held in Copenhagen. Amid this uncertainty, we applied three different methods to predict the outcomes: an expert survey and two negotiation simulation models, namely the Exchange Model and the Predictioneer's Game. After the event, these predictions were assessed against the coded texts that were agreed in Paris. The evidence suggests that combining experts' predictions to reach a collective expert prediction makes for significantly more accurate predictions than individual experts' predictions. The differences in the performance between the two different negotiation simulation models were not statistically significant.}, language = {en} } @article{StadlerOttSpringeretal.2012, author = {Stadler, Waltraud and Ott, Derek V. M. and Springer, Anne and Schubotz, Ricarda I. and Sch{\"u}tz-Bosbach, Simone and Prinz, Wolfgang}, title = {Repetitive TMS suggests a role of the human dorsal premotor cortex in action prediction}, series = {Frontiers in human neuroscienc}, volume = {6}, journal = {Frontiers in human neuroscienc}, number = {2}, publisher = {Frontiers Research Foundation}, address = {Lausanne}, issn = {1662-5161}, doi = {10.3389/fnhum.2012.00020}, pages = {11}, year = {2012}, abstract = {Predicting the actions of other individuals is crucial for our daily interactions. Recent evidence suggests that the prediction of object-directed arm and full-body actions employs the dorsal premotor cortex (PMd). Thus, the neural substrate involved in action control may also be essential for action prediction. Here, we aimed to address this issue and hypothesized that disrupting the PMd impairs action prediction. Using fMRI-guided coil navigation, rTMS (five pulses, 10Hz) was applied over the left PMd and over the vertex (control region) while participants observed everyday actions in video clips that were transiently occluded for 1s. The participants detected manipulations in the time course of occluded actions, which required them to internally predict the actions during occlusion. To differentiate between functional roles that the PMd could play in prediction, rTMS was either delivered at occluder-onset (TMS-early), affecting the initiation of action prediction, or 300 ms later during occlusion(TMS-late), affecting the maintenance of anongoing prediction. TMS-early over the left PMd produced more prediction errors than TMS-early over the vertex. TMS-late had no effect on prediction performance, suggesting that the left PMd might be involved particularly during the initiation of internally guided action prediction but may play a subordinate role in maintaining ongoing prediction. These findings open a new perspective on the role of the left PMd in action prediction which is in line with its functions in action control and in cognitive tasks. In the discussion, there levance of the left PMd for integrating external action parameters with the observer's motor repertoire is emphasized. Overall, the results are in line with the notion that premotor functions are employed in both action control and action observation.}, language = {en} } @article{StillmanRailsbackGiskeetal.2015, author = {Stillman, Richard A. and Railsback, Steven Floyd and Giske, Jarl and Berger, Uta and Grimm, Volker}, title = {Making Predictions in a Changing World: The Benefits of Individual-Based Ecology}, series = {Bioscience}, volume = {65}, journal = {Bioscience}, number = {2}, publisher = {Oxford Univ. Press}, address = {Oxford}, issn = {0006-3568}, doi = {10.1093/biosci/biu192}, pages = {140 -- 150}, year = {2015}, abstract = {Ecologists urgently need a better ability to predict how environmental change affects biodiversity. We examine individual-based ecology (IBE), a research paradigm that promises better a predictive ability by using individual-based models (IBMs) to represent ecological dynamics as arising from how individuals interact with their environment and with each other. A key advantage of IBMs is that the basis for predictions-fitness maximization by individual organisms-is more general and reliable than the empirical relationships that other models depend on. Case studies illustrate the usefulness and predictive success of long-term IBE programs. The pioneering programs had three phases: conceptualization, implementation, and diversification. Continued validation of models runs throughout these phases. The breakthroughs that make IBE more productive include standards for describing and validating IBMs, improved and standardized theory for individual traits and behavior, software tools, and generalized instead of system-specific IBMs. We provide guidelines for pursuing IBE and a vision for future IBE research.}, language = {en} } @phdthesis{Stone2020, author = {Stone, Kate}, title = {Predicting long-distance lexical content in German verb-particle constructions}, doi = {10.25932/publishup-47679}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-476798}, school = {Universit{\"a}t Potsdam}, year = {2020}, abstract = {A large body of research now supports the presence of both syntactic and lexical predictions in sentence processing. Lexical predictions, in particular, are considered to indicate a deep level of predictive processing that extends past the structural features of a necessary word (e.g. noun), right down to the phonological features of the lexical identity of a specific word (e.g. /kite/; DeLong et al., 2005). However, evidence for lexical predictions typically focuses on predictions in very local environments, such as the adjacent word or words (DeLong et al., 2005; Van Berkum et al., 2005; Wicha et al., 2004). Predictions in such local environments may be indistinguishable from lexical priming, which is transient and uncontrolled, and as such may prime lexical items that are not compatible with the context (e.g. Kukona et al., 2014). Predictive processing has been argued to be a controlled process, with top-down information guiding preactivation of plausible upcoming lexical items (Kuperberg \& Jaeger, 2016). One way to distinguish lexical priming from prediction is to demonstrate that preactivated lexical content can be maintained over longer distances. In this dissertation, separable German particle verbs are used to demonstrate that preactivation of lexical items can be maintained over multi-word distances. A self-paced reading time and an eye tracking experiment provide some support for the idea that particle preactivation triggered by a verb and its context can be observed by holding the sentence context constant and manipulating the predictabilty of the particle. Although evidence of an effect of particle predictability was only seen in eye tracking, this is consistent with previous evidence suggesting that predictive processing facilitates only some eye tracking measures to which the self-paced reading modality may not be sensitive (Staub, 2015; Rayner1998). Interestingly, manipulating the distance between the verb and the particle did not affect reading times, suggesting that the surprisal-predicted faster reading times at long distance may only occur when the additional distance is created by information that adds information about the lexical identity of a distant element (Levy, 2008; Grodner \& Gibson, 2005). Furthermore, the results provide support for models proposing that temporal decay is not major influence on word processing (Lewandowsky et al., 2009; Vasishth et al., 2019). In the third and fourth experiments, event-related potentials were used as a method for detecting specific lexical predictions. In the initial ERP experiment, we found some support for the presence of lexical predictions when the sentence context constrained the number of plausible particles to a single particle. This was suggested by a frontal post-N400 positivity (PNP) that was elicited when a lexical prediction had been violated, but not to violations when more than one particle had been plausible. The results of this study were highly consistent with previous research suggesting that the PNP might be a much sought-after ERP marker of prediction failure (DeLong et al., 2011; DeLong et al., 2014; Van Petten \& Luka, 2012; Thornhill \& Van Petten, 2012; Kuperberg et al., 2019). However, a second experiment in a larger sample experiment failed to replicate the effect, but did suggest the relationship of the PNP to predictive processing may not yet be fully understood. Evidence for long-distance lexical predictions was inconclusive. The conclusion drawn from the four experiments is that preactivation of the lexical entries of plausible upcoming particles did occur and was maintained over long distances. The facilitatory effect of this preactivation at the particle site therefore did not appear to be the result of transient lexical priming. However, the question of whether this preactivation can also lead to lexical predictions of a specific particle remains unanswered. Of particular interest to future research on predictive processing is further characterisation of the PNP. Implications for models of sentence processing may be the inclusion of long-distance lexical predictions, or the possibility that preactivation of lexical material can facilitate reading times and ERP amplitude without commitment to a specific lexical item.}, language = {en} } @article{StoneVerissimoSchadetal.2021, author = {Stone, Kate and Verissimo, Joao and Schad, Daniel J. and Oltrogge, Elise and Vasishth, Shravan and Lago, Sol}, title = {The interaction of grammatically distinct agreement dependencies in predictive processing}, series = {Language, cognition and neuroscience}, volume = {36}, journal = {Language, cognition and neuroscience}, number = {9}, publisher = {Routledge, Taylor \& Francis Group}, address = {Abingdon}, issn = {2327-3798}, doi = {10.1080/23273798.2021.1921816}, pages = {1159 -- 1179}, year = {2021}, abstract = {Previous research has found that comprehenders sometimes predict information that is grammatically unlicensed by sentence constraints. An open question is why such grammatically unlicensed predictions occur. We examined the possibility that unlicensed predictions arise in situations of information conflict, for instance when comprehenders try to predict upcoming words while simultaneously building dependencies with previously encountered elements in memory. German possessive pronouns are a good testing ground for this hypothesis because they encode two grammatically distinct agreement dependencies: a retrospective one between the possessive and its previously mentioned referent, and a prospective one between the possessive and its following nominal head. In two visual world eye-tracking experiments, we estimated the onset of predictive effects in participants' fixations. The results showed that the retrospective dependency affected resolution of the prospective dependency by shifting the onset of predictive effects. We attribute this effect to an interaction between predictive and memory retrieval processes.}, language = {en} } @article{VaidChanChaudharyetal.2021, author = {Vaid, Akhil and Chan, Lili and Chaudhary, Kumardeep and Jaladanki, Suraj K. and Paranjpe, Ishan and Russak, Adam J. and Kia, Arash and Timsina, Prem and Levin, Matthew A. and He, John Cijiang and B{\"o}ttinger, Erwin and Charney, Alexander W. and Fayad, Zahi A. and Coca, Steven G. and Glicksberg, Benjamin S. and Nadkarni, Girish N.}, title = {Predictive approaches for acute dialysis requirement and death in COVID-19}, series = {Clinical journal of the American Society of Nephrology : CJASN}, volume = {16}, journal = {Clinical journal of the American Society of Nephrology : CJASN}, number = {8}, publisher = {American Society of Nephrology}, address = {Washington}, organization = {MSCIC}, issn = {1555-9041}, doi = {10.2215/CJN.17311120}, pages = {1158 -- 1168}, year = {2021}, abstract = {Background and objectives AKI treated with dialysis initiation is a common complication of coronavirus disease 2019 (COVID-19) among hospitalized patients. However, dialysis supplies and personnel are often limited. Design, setting, participants, \& measurements Using data from adult patients hospitalized with COVID-19 from five hospitals from theMount Sinai Health System who were admitted between March 10 and December 26, 2020, we developed and validated several models (logistic regression, Least Absolute Shrinkage and Selection Operator (LASSO), random forest, and eXtreme GradientBoosting [XGBoost; with and without imputation]) for predicting treatment with dialysis or death at various time horizons (1, 3, 5, and 7 days) after hospital admission. Patients admitted to theMount Sinai Hospital were used for internal validation, whereas the other hospitals formed part of the external validation cohort. Features included demographics, comorbidities, and laboratory and vital signs within 12 hours of hospital admission. Results A total of 6093 patients (2442 in training and 3651 in external validation) were included in the final cohort. Of the different modeling approaches used, XGBoost without imputation had the highest area under the receiver operating characteristic (AUROC) curve on internal validation (range of 0.93-0.98) and area under the precisionrecall curve (AUPRC; range of 0.78-0.82) for all time points. XGBoost without imputation also had the highest test parameters on external validation (AUROC range of 0.85-0.87, and AUPRC range of 0.27-0.54) across all time windows. XGBoost without imputation outperformed all models with higher precision and recall (mean difference in AUROC of 0.04; mean difference in AUPRC of 0.15). Features of creatinine, BUN, and red cell distribution width were major drivers of the model's prediction. Conclusions An XGBoost model without imputation for prediction of a composite outcome of either death or dialysis in patients positive for COVID-19 had the best performance, as compared with standard and other machine learning models.}, language = {en} } @article{VaidSomaniRussaketal.2020, author = {Vaid, Akhil and Somani, Sulaiman and Russak, Adam J. and De Freitas, Jessica K. and Chaudhry, Fayzan F. and Paranjpe, Ishan and Johnson, Kipp W. and Lee, Samuel J. and Miotto, Riccardo and Richter, Felix and Zhao, Shan and Beckmann, Noam D. and Naik, Nidhi and Kia, Arash and Timsina, Prem and Lala, Anuradha and Paranjpe, Manish and Golden, Eddye and Danieletto, Matteo and Singh, Manbir and Meyer, Dara and O'Reilly, Paul F. and Huckins, Laura and Kovatch, Patricia and Finkelstein, Joseph and Freeman, Robert M. and Argulian, Edgar and Kasarskis, Andrew and Percha, Bethany and Aberg, Judith A. and Bagiella, Emilia and Horowitz, Carol R. and Murphy, Barbara and Nestler, Eric J. and Schadt, Eric E. and Cho, Judy H. and Cordon-Cardo, Carlos and Fuster, Valentin and Charney, Dennis S. and Reich, David L. and B{\"o}ttinger, Erwin and Levin, Matthew A. and Narula, Jagat and Fayad, Zahi A. and Just, Allan C. and Charney, Alexander W. and Nadkarni, Girish N. and Glicksberg, Benjamin S.}, title = {Machine learning to predict mortality and critical events in a cohort of patients with COVID-19 in New York City: model development and validation}, series = {Journal of medical internet research : international scientific journal for medical research, information and communication on the internet ; JMIR}, volume = {22}, journal = {Journal of medical internet research : international scientific journal for medical research, information and communication on the internet ; JMIR}, number = {11}, publisher = {Healthcare World}, address = {Richmond, Va.}, issn = {1439-4456}, doi = {10.2196/24018}, pages = {19}, year = {2020}, abstract = {Background: COVID-19 has infected millions of people worldwide and is responsible for several hundred thousand fatalities. The COVID-19 pandemic has necessitated thoughtful resource allocation and early identification of high-risk patients. However, effective methods to meet these needs are lacking. Objective: The aims of this study were to analyze the electronic health records (EHRs) of patients who tested positive for COVID-19 and were admitted to hospitals in the Mount Sinai Health System in New York City; to develop machine learning models for making predictions about the hospital course of the patients over clinically meaningful time horizons based on patient characteristics at admission; and to assess the performance of these models at multiple hospitals and time points. Methods: We used Extreme Gradient Boosting (XGBoost) and baseline comparator models to predict in-hospital mortality and critical events at time windows of 3, 5, 7, and 10 days from admission. Our study population included harmonized EHR data from five hospitals in New York City for 4098 COVID-19-positive patients admitted from March 15 to May 22, 2020. The models were first trained on patients from a single hospital (n=1514) before or on May 1, externally validated on patients from four other hospitals (n=2201) before or on May 1, and prospectively validated on all patients after May 1 (n=383). Finally, we established model interpretability to identify and rank variables that drive model predictions. Results: Upon cross-validation, the XGBoost classifier outperformed baseline models, with an area under the receiver operating characteristic curve (AUC-ROC) for mortality of 0.89 at 3 days, 0.85 at 5 and 7 days, and 0.84 at 10 days. XGBoost also performed well for critical event prediction, with an AUC-ROC of 0.80 at 3 days, 0.79 at 5 days, 0.80 at 7 days, and 0.81 at 10 days. In external validation, XGBoost achieved an AUC-ROC of 0.88 at 3 days, 0.86 at 5 days, 0.86 at 7 days, and 0.84 at 10 days for mortality prediction. Similarly, the unimputed XGBoost model achieved an AUC-ROC of 0.78 at 3 days, 0.79 at 5 days, 0.80 at 7 days, and 0.81 at 10 days. Trends in performance on prospective validation sets were similar. At 7 days, acute kidney injury on admission, elevated LDH, tachypnea, and hyperglycemia were the strongest drivers of critical event prediction, while higher age, anion gap, and C-reactive protein were the strongest drivers of mortality prediction. Conclusions: We externally and prospectively trained and validated machine learning models for mortality and critical events for patients with COVID-19 at different time horizons. These models identified at-risk patients and uncovered underlying relationships that predicted outcomes.}, language = {en} } @phdthesis{Zurell2011, author = {Zurell, Damaris}, title = {Integrating dynamic and statistical modelling approaches in order to improve predictions for scenarios of environmental change}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-56845}, school = {Universit{\"a}t Potsdam}, year = {2011}, abstract = {Species respond to environmental change by dynamically adjusting their geographical ranges. Robust predictions of these changes are prerequisites to inform dynamic and sustainable conservation strategies. Correlative species distribution models (SDMs) relate species' occurrence records to prevailing environmental factors to describe the environmental niche. They have been widely applied in global change context as they have comparably low data requirements and allow for rapid assessments of potential future species' distributions. However, due to their static nature, transient responses to environmental change are essentially ignored in SDMs. Furthermore, neither dispersal nor demographic processes and biotic interactions are explicitly incorporated. Therefore, it has often been suggested to link statistical and mechanistic modelling approaches in order to make more realistic predictions of species' distributions for scenarios of environmental change. In this thesis, I present two different ways of such linkage. (i) Mechanistic modelling can act as virtual playground for testing statistical models and allows extensive exploration of specific questions. I promote this 'virtual ecologist' approach as a powerful evaluation framework for testing sampling protocols, analyses and modelling tools. Also, I employ such an approach to systematically assess the effects of transient dynamics and ecological properties and processes on the prediction accuracy of SDMs for climate change projections. That way, relevant mechanisms are identified that shape the species' response to altered environmental conditions and which should hence be considered when trying to project species' distribution through time. (ii) I supplement SDM projections of potential future habitat for black grouse in Switzerland with an individual-based population model. By explicitly considering complex interactions between habitat availability and demographic processes, this allows for a more direct assessment of expected population response to environmental change and associated extinction risks. However, predictions were highly variable across simulations emphasising the need for principal evaluation tools like sensitivity analysis to assess uncertainty and robustness in dynamic range predictions. Furthermore, I identify data coverage of the environmental niche as a likely cause for contrasted range predictions between SDM algorithms. SDMs may fail to make reliable predictions for truncated and edge niches, meaning that portions of the niche are not represented in the data or niche edges coincide with data limits. Overall, my thesis contributes to an improved understanding of uncertainty factors in predictions of range dynamics and presents ways how to deal with these. Finally I provide preliminary guidelines for predictive modelling of dynamic species' response to environmental change, identify key challenges for future research and discuss emerging developments.}, language = {en} } @article{ZoellerBenZion2014, author = {Z{\"o}ller, Gert and Ben-Zion, Yehuda}, title = {Large earthquake hazard of the San Jacinto fault zone, CA, from long record of simulated seismicity assimilating the available instrumental and paleoseismic data}, series = {Pure and applied geophysics}, volume = {171}, journal = {Pure and applied geophysics}, number = {11}, publisher = {Springer}, address = {Basel}, issn = {0033-4553}, doi = {10.1007/s00024-014-0783-1}, pages = {2955 -- 2965}, year = {2014}, abstract = {We investigate spatio-temporal properties of earthquake patterns in the San Jacinto fault zone (SJFZ), California, between Cajon Pass and the Superstition Hill Fault, using a long record of simulated seismicity constrained by available seismological and geological data. The model provides an effective realization of a large segmented strike-slip fault zone in a 3D elastic half-space, with heterogeneous distribution of static friction chosen to represent several clear step-overs at the surface. The simulated synthetic catalog reproduces well the basic statistical features of the instrumental seismicity recorded at the SJFZ area since 1981. The model also produces events larger than those included in the short instrumental record, consistent with paleo-earthquakes documented at sites along the SJFZ for the last 1,400 years. The general agreement between the synthetic and observed data allows us to address with the long-simulated seismicity questions related to large earthquakes and expected seismic hazard. The interaction between m a parts per thousand yen 7 events on different sections of the SJFZ is found to be close to random. The hazard associated with m a parts per thousand yen 7 events on the SJFZ increases significantly if the long record of simulated seismicity is taken into account. The model simulations indicate that the recent increased number of observed intermediate SJFZ earthquakes is a robust statistical feature heralding the occurrence of m a parts per thousand yen 7 earthquakes. The hypocenters of the m a parts per thousand yen 5 events in the simulation results move progressively towards the hypocenter of the upcoming m a parts per thousand yen 7 earthquake.}, language = {en} } @article{ZoellerHainzlTilmannetal.2020, author = {Z{\"o}ller, Gert and Hainzl, Sebastian and Tilmann, Frederik and Woith, Heiko and Dahm, Torsten}, title = {Comment on: Wikelski, Martin; M{\"u}ller, Uschi; Scocco, Paola; Catorci, Andrea; Desinov, Lev V.; Belyaev, Mikhail Y.; Keim, Daniel A.; Pohlmeier, Winfried; Fechteler, Gerhard; Mai, Martin P. : Potential short-term earthquake forecasting by farm animal monitoring. - Ethology. - 126 (2020), 9. - S. 931 - 941. -ISSN 0179-1613. - eISSN 1439-0310. - doi 10.1111/eth.13078}, series = {Ethology}, volume = {127}, journal = {Ethology}, number = {3}, publisher = {Wiley}, address = {Hoboken}, issn = {0179-1613}, doi = {10.1111/eth.13105}, pages = {302 -- 306}, year = {2020}, abstract = {Based on an analysis of continuous monitoring of farm animal behavior in the region of the 2016 M6.6 Norcia earthquake in Italy, Wikelski et al., 2020; (Seismol Res Lett, 89, 2020, 1238) conclude that animal activity can be anticipated with subsequent seismic activity and that this finding might help to design a "short-term earthquake forecasting method." We show that this result is based on an incomplete analysis and misleading interpretations. Applying state-of-the-art methods of statistics, we demonstrate that the proposed anticipatory patterns cannot be distinguished from random patterns, and consequently, the observed anomalies in animal activity do not have any forecasting power.}, language = {en} }