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We propose a multivariate dynamic intensity peaks-over-threshold model to capture extreme events in a multivariate time series of returns. The random occurrence of extreme events exceeding a threshold is modeled by means of a multivariate dynamic intensity model allowing for feedback effects between the individual processes. We propose alternative specifications of the multivariate intensity process using autoregressive conditional intensity and Hawkes-type specifications. Likewise, temporal clustering of the size of exceedances is captured by an autoregressive multiplicative error model based on a generalized Pareto distribution. We allow for spillovers between both the intensity processes and the process of marks. The model is applied to jointly model extreme returns in the daily returns of three major stock indexes. We find strong empirical support for a temporal clustering of both the occurrence of extremes and the size of exceedances. Moreover, significant feedback effects between both types of processes are observed. Backtesting Value-at-Risk (VaR) and Expected Shortfall (ES) forecasts show that the proposed model does not only produce a good in-sample fit but also reliable out-of-sample predictions. We show that the inclusion of temporal clustering of the size of exceedances and feedback with the intensity thereof results in better forecasts of VaR and ES.
We provide elementary algorithms for two preservation theorems for first-order sentences (FO) on the class ℭd of all finite structures of degree at most d: For each FO-sentence that is preserved under extensions (homomorphisms) on ℭd, a ℭd-equivalent existential (existential-positive) FO-sentence can be constructed in 5-fold (4-fold) exponential time. This is complemented by lower bounds showing that a 3-fold exponential blow-up of the computed existential (existential-positive) sentence is unavoidable. Both algorithms can be extended (while maintaining the upper and lower bounds on their time complexity) to input first-order sentences with modulo m counting quantifiers (FO+MODm). Furthermore, we show that for an input FO-formula, a ℭd-equivalent Feferman-Vaught decomposition can be computed in 3-fold exponential time. We also provide a matching lower bound
Background: Alzheimer’s Disease (AD) is the most common form of dementia and one of the major diseases of old age, causing the impairment of cognitive functions. This disease does not only confront society with financial issues, but also puts severe stress on individuals suffering from AD and their relatives alike. One of the possible symptoms, commonly described in AD, is the impairment of learning as well as the recognition of face-name associations. Beginning at age 60, the chance to develop AD grows exponentially with increasing age, making age a major risk factor. Additionally, the e4 allele of the apolipoprotein E (APOE) polymorphism has been associated with the risk of developing AD when compared to the more common e3 allele. While strong evidence shows a stronger decline in cognitive function with rising age for e4 carriers, some studies demonstrated better cognitive function in e4 carriers at a young age.
This led to the postulation of the hypothesis of antagonistic pleiotropy of the APOE gene, wherein the e4 allele may benefit cognitive function in young carriers, yet leads to a faster decline at a later point in life, encouraging the development of cognitive dysfunction such as AD. Several functional magnetic resonance imaging (fMRI) studies, examining functional activation patterns, found APOE-related differences in key areas of episodic memory, such as the hippocampus, where e4 carriers show aberrant activation similar to AD patients. However, associative memory (encoding and retrieval of face name pairs) has not been well examined for APOE-related differences. Interaction effects of age and the APOE genotype, such as those postulated by the hypothesis of antagonistic pleiotropy, have not been addressed in face-name association tasks either.
Leading Question: Is it possible to detect interaction effects between age and APOE genotype on cognitive performance or neuronal activation patterns in healthy young and old participants during an fMRI face-name association task, supporting the hypothesis of antagonistic pleiotropy of the APOE genotype?
Methods: Participants were stratied by age, and APOE e4 carriers were randomly matched with homozygous e3 carriers. Neuropsychological examination (CVLT and CERAD) was administered. Participants underwent structural MRI analysis via voxelbased morphometry (VBM) as well as fMRI imaging during a face-name association task.
Results: Apart from strong age-related effects in cognitive function detected during neuropsychological testing, the behavioral data from the face-name association task as well as the structural MRI analysis did not show an association with the APOE genotype. Nevertheless, analysis of functional MRI data showed age- as well as APOE-dependent effects on activation patterns for the encoding and retrieval of face-name pairs, in absence of differences in cognitive performance. Further analysis showed eight clusters of significant age X APOE genotype interactions in areas previously associated with working and visual associative memory, including the fusiform gyri bilaterally. These interactions show different patterns, whereas a relative hypoactivation of young e4 carriers together with a hyperactivation of old e4 carriers is the most prominent.
Conclusions: With regard to the leading question, this study successfully found age X APOE interactions in a face-name pair retrieval task, although no interaction effects were present in the encoding task, structural analysis, or cognitive performance. The agemediated effect of the APOE e4 allele on functional activation patterns may be explained by the compensatory hypothesis, describing a relative hyperactivation of old e4 carriers as compensatory, and interpreting a relative hypoactivation of younger e4 participants as reduced effort to achieve the same cognitive performance as non carriers.
These findings present further evidence of an antagonistic pleiotropy of the APOE genotype, showing age-dependent effects of the e4 allele even in healthy carriers. Nevertheless, previously described differences in cognitive performance and brain structure, even in young participants, were not found. On the contrary, functional MRI analysis showed APOE-related differences in young and old participants, suggesting that this modality may be more sensitive in detecting APOE-mediated changes. Among the clusters, demonstrating an interaction effect, the fusiform gyri were most prominent, which might be due to its important role in visual associative memory. As previous studies indicate an early and strong involvement of this area due to AD pathology, this interaction effect of age and APOE genotype in healthy participants underlines the importance of this region in the development of AD, and should be the focus of further research. However, this research is also required to determine, how exactly the APOE genotype influences brain function in healthy humans, and to clarify its relationship to pathological processes facilitating the development of AD.
Even in the absence of sensory stimulation the brain is spontaneously active. This background “noise” seems to be the dominant cause of the notoriously high trial-to-trial variability of neural recordings. Recent experimental observations have extended our knowledge of trial-to-trial variability and spontaneous activity in several directions: 1. Trial-to-trial variability systematically decreases following the onset of a sensory stimulus or the start of a motor act. 2. Spontaneous activity states in sensory cortex outline the region of evoked sensory responses. 3. Across development, spontaneous activity aligns itself with typical evoked activity patterns. 4. The spontaneous brain activity prior to the presentation of an ambiguous stimulus predicts how the stimulus will be interpreted. At present it is unclear how these observations relate to each other and how they arise in cortical circuits. Here we demonstrate that all of these phenomena can be accounted for by a deterministic self-organizing recurrent neural network model (SORN), which learns a predictive model of its sensory environment. The SORN comprises recurrently coupled populations of excitatory and inhibitory threshold units and learns via a combination of spike-timing dependent plasticity (STDP) and homeostatic plasticity mechanisms. Similar to balanced network architectures, units in the network show irregular activity and variable responses to inputs. Additionally, however, the SORN exhibits sequence learning abilities matching recent findings from visual cortex and the network's spontaneous activity reproduces the experimental findings mentioned above. Intriguingly, the network's behaviour is reminiscent of sampling-based probabilistic inference, suggesting that correlates of sampling-based inference can develop from the interaction of STDP and homeostasis in deterministic networks. We conclude that key observations on spontaneous brain activity and the variability of neural responses can be accounted for by a simple deterministic recurrent neural network which learns a predictive model of its sensory environment via a combination of generic neural plasticity mechanisms.
Immunohistochemical assessment of phosphorylated mTORC1-pathway proteins in human brain tumors
(2015)
Background: Current pathological diagnostics include the analysis of (epi-)genetic alterations as well as oncogenic pathways. Deregulated mammalian target of rapamycin complex 1 (mTORC1) signaling has been implicated in a variety of cancers including malignant gliomas and is considered a promising target in cancer treatment. Monitoring of mTORC1 activity before and during inhibitor therapy is essential. The aim of our study is to provide a recommendation and report on pitfalls in the use of phospho-specific antibodies against mTORC1-targets phospho-RPS6 (Ser235/236; Ser240/244) and phospho-4EBP1 (Thr37/46) in formalin fixed, paraffin embedded material.
Methods and findings: Primary, established cell lines and brain tumor tissue from routine diagnostics were assessed by immunocyto-, immunohistochemistry, immunofluorescent stainings and immunoblotting. For validation of results, immunoblotting experiments were performed. mTORC-pathway activation was pharmacologically inhibited by torin2 and rapamycin. Torin2 treatment led to a strong reduction of signal intensity and frequency of all tested antibodies. In contrast phospho-4EBP1 did not show considerable reduction in staining intensity after rapamycin treatment, while immunocytochemistry with both phospho-RPS6-specific antibodies showed a reduced signal compared to controls. Staining intensity of both phospho-RPS6-specific antibodies did not show considerable decrease in stability in a timeline from 0–230 minutes without tissue fixation, however we observed a strong decrease of staining intensity in phospho-4EBP1 after 30 minutes. Detection of phospho-signals was strongly dependent on tissue size and fixation gradient. mTORC1-signaling was significantly induced in glioblastomas although not restricted to cancer cells but also detectable in non-neoplastic cells.
Conclusion: Here we provide a recommendation for phospho-specific immunohistochemistry for patient-orientated therapy decisions and monitoring treatment response.
Simple cells in primary visual cortex were famously found to respond to low-level image components such as edges. Sparse coding and independent component analysis (ICA) emerged as the standard computational models for simple cell coding because they linked their receptive fields to the statistics of visual stimuli. However, a salient feature of image statistics, occlusions of image components, is not considered by these models. Here we ask if occlusions have an effect on the predicted shapes of simple cell receptive fields. We use a comparative approach to answer this question and investigate two models for simple cells: a standard linear model and an occlusive model. For both models we simultaneously estimate optimal receptive fields, sparsity and stimulus noise. The two models are identical except for their component superposition assumption. We find the image encoding and receptive fields predicted by the models to differ significantly. While both models predict many Gabor-like fields, the occlusive model predicts a much sparser encoding and high percentages of ‘globular’ receptive fields. This relatively new center-surround type of simple cell response is observed since reverse correlation is used in experimental studies. While high percentages of ‘globular’ fields can be obtained using specific choices of sparsity and overcompleteness in linear sparse coding, no or only low proportions are reported in the vast majority of studies on linear models (including all ICA models). Likewise, for the here investigated linear model and optimal sparsity, only low proportions of ‘globular’ fields are observed. In comparison, the occlusive model robustly infers high proportions and can match the experimentally observed high proportions of ‘globular’ fields well. Our computational study, therefore, suggests that ‘globular’ fields may be evidence for an optimal encoding of visual occlusions in primary visual cortex.
Aim: We investigated the long-term impact of adjunctive systemic antibiotics on periodontal disease progression. Periodontal therapy is frequently supplemented by systemic antibiotics, although its impact on the course of disease is still unclear.
Material & Methods: This prospective, randomized, double-blind, placebo-controlled multi-centre trial comprising patients suffering from moderate to severe periodontitis evaluated the impact of rational adjunctive use of systemic amoxicillin 500 mg plus metronidazole 400 mg (3x/day, 7 days) on attachment loss. The primary outcome was the percentage of sites showing further attachment loss (PSAL) ≥1.3 mm after the 27.5 months observation period. Standardized therapy comprised mechanical debridement in conjunction with antibiotics or placebo administration, and maintenance therapy at 3 months intervals.
Results: From 506 participating patients, 406 were included in the intention to treat analysis. Median PSAL observed in placebo group was 7.8% compared to 5.3% in antibiotics group (Q25 4.7%/Q75 14.1%; Q25 3.1%/Q75 9.9%; p < 0.001 respectively).
Conclusions: Both treatments were effective in preventing disease progression. Compared to placebo, the prescription of empiric adjunctive systemic antibiotics showed a small absolute, although statistically significant, additional reduction in further attachment loss. Therapists should consider the patient's overall risk for periodontal disease when deciding for or against adjunctive antibiotics prescription.
When markets are incomplete, social security can partially insure against idiosyncratic and aggregate risks. We incorporate both risks into an analytically tractable model with two overlapping generations. We derive the equilibrium dynamics in closed form and show that joint presence of both risks leads to over-proportional risk exposure for households. This implies that the whole benefit from insurance through social security is greater than the sum of the benefits from insurance against each of the two risks in isolation. We measure this through interaction effects which appear even though the two risks are orthogonal by construction. While the interactions unambiguously increase the welfare benefits from insurance, they can in- or decrease the welfare costs from crowding out of capital formation. The net effect depends on the relative strengths of the opposing forces.
Aus der Redaktion
(2015)
»Arsen und Spitzenforschung« : Ausstellung zu Paul Ehrlichs 100. Todestag im Historischen Museum
(2015)
This paper studies a dynamic stochastic general equilibrium model involving climate change. Our model allows for damages on economic growth resulting from global warming. In the calibration, we capture effects from climate change and feedback effects on the temperature dynamics. We solve for the optimal state-dependent abatement policy. In our simulations, the costs of this policy measured in terms of lost GDP growth are moderate. On the other hand, postponing abatement action could reduce the probability that the climate can be stabilized. For instance, waiting for 10 years reduces this probability from 60% to 30%. Waiting for another 10 years leads to a probability that is less than 10%. Finally, doing nothing opens the risk that temperatures might explode and economic growth decreases significantly.
This paper studies the life cycle consumption-investment-insurance problem of a family. The wage earner faces the risk of a health shock that significantly increases his probability of dying. The family can buy long-term life insurance that can only be revised at significant costs, which makes insurance decisions sticky. Furthermore, a revision is only possible as long as the insured person is healthy. A second important feature of our model is that the labor income of the wage earner is unspanned. We document that the combination of unspanned labor income and the stickiness of insurance decisions reduces the long-term insurance demand significantly. This is because an income shock induces the need to reduce the insurance coverage, since premia become less affordable. Since such a reduction is costly and families anticipate these potential costs, they buy less protection at all ages. In particular, young families stay away from long-term life insurance markets altogether. Our results are robust to adding short-term life insurance, annuities and health insurance.
The involvement of the ubiquitin-proteasome system (UPS) in the course of various age-associated neurodegenerative diseases is well established. The single RING finger type E3 ubiquitin-protein ligase PARK2 is mutated in a Parkinson’s disease (PD) variant and was found to interact with ATXN2, a protein where polyglutamine expansions cause Spinocerebellar ataxia type 2 (SCA2) or increase the risk for Levodopa-responsive PD and for the motor neuron disease Amyotrophic lateral sclerosis (ALS). We previously reported evidence for a transcriptional induction of the multi-subunit RING finger Skp1/Cul/F-box (SCF) type E3 ubiquitin-protein ligase complex component FBXW8 in global microarray profiling of ATXN2-expansion mouse cerebellum and demonstrated its role for ATXN2 degradation in vitro. Now, we documented co-localization in vitro and co-immunoprecipitations both in vitro and in vivo, which indicate associations of FBXW8 with ATXN2 and PARK2. Both FBXW8 and PARK2 proteins are driven into insolubility by expanded ATXN2. Whereas the FBXW8 transcript upregulation by ATXN2- expansion was confirmed also in qPCR of skin fibroblasts and blood samples of SCA2 patients, a FBXW8 expression dysregulation was not observed in ATXN2-deficient mice, nor was a PARK2 transcript dysregulation observed in any samples. Jointly, all available data suggest that the degradation of wildtype and mutant ATXN2 is dependent on FBXW8, and that ATXN2 accumulation selectively modulates FBXW8 levels, while PARK2 might act indirectly through FBXW8. The effects of ATXN2-expansions on FBXW8 expression in peripheral tissues like blood may become useful for clinical diagnostics