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The ability to respond appropriately to employees' work-related well-being requires leaders to pay attention to their employees' well-being in the first place. We propose that leaders' stress mindset, that is, the belief that stress is enhancing versus debilitating, may bias their perception of employees' well-being. We further propose that this judgment then influences leaders' intention to engage in or refrain from health-oriented leadership behavior, to express higher performance expectations, or to promote their employees. We expect this process to be stronger if leaders strongly identify with their team, increasing their perceived similarity with their employees. In three experiments (N1 = 198, N2 = 292, N3 = 250), we tested the effect of participants' stress mindset on their intention to show certain leadership behaviors, mediated by their perception of employee well-being (emotional exhaustion, somatic symptoms, work engagement) and moderated by their team identification. Our findings largely support the association between stress mindset and the perception of well-being. The results for the proposed mediation and the moderating function of identification were mixed. Overall, the results emphasize the critical role of leaders' stress mindset and may, thus, improve health promotion in organizations by helping leaders to adequately recognize employees' well-being and respond appropriately.
In the nineteenth century, two Neolithic axe-heads were reported from the Michelsberg enclosure system at Kapellenberg. The recent identification of an unusually large tumulus, from which the axe-heads were almost certainly once recovered, reveals that socio-political hierarchisation, linked to the emergence of high-ranking elites in Brittany and the Paris Basin during the fifth millennium cal BC, may have extended into Central Europe.
The human brain achieves visual object recognition through multiple stages of nonlinear transformations operating at a millisecond scale. To predict and explain these rapid transformations, computational neuroscientists employ machine learning modeling techniques. However, state-of-the-art models require massive amounts of data to properly train, and to the present day there is a lack of vast brain datasets which extensively sample the temporal dynamics of visual object recognition. Here we collected a large and rich dataset of high temporal resolution EEG responses to images of objects on a natural background. This dataset includes 10 participants, each with 82,160 trials spanning 16,740 image conditions. Through computational modeling we established the quality of this dataset in five ways. First, we trained linearizing encoding models that successfully synthesized the EEG responses to arbitrary images. Second, we correctly identified the recorded EEG data image conditions in a zero-shot fashion, using EEG synthesized responses to hundreds of thousands of candidate image conditions. Third, we show that both the high number of conditions as well as the trial repetitions of the EEG dataset contribute to the trained models’ prediction accuracy. Fourth, we built encoding models whose predictions well generalize to novel participants. Fifth, we demonstrate full end-to-end training of randomly initialized DNNs that output M/EEG responses for arbitrary input images. We release this dataset as a tool to foster research in visual neuroscience and computer vision.
The human brain achieves visual object recognition through multiple stages of linear and nonlinear transformations operating at a millisecond scale. To predict and explain these rapid transformations, computational neuroscientists employ machine learning modeling techniques. However, state-of-the-art models require massive amounts of data to properly train, and to the present day there is a lack of vast brain datasets which extensively sample the temporal dynamics of visual object recognition. Here we collected a large and rich dataset of high temporal resolution EEG responses to images of objects on a natural background. This dataset includes 10 participants, each with 82,160 trials spanning 16,740 image conditions. Through computational modeling we established the quality of this dataset in five ways. First, we trained linearizing encoding models that successfully synthesized the EEG responses to arbitrary images. Second, we correctly identified the recorded EEG data image conditions in a zero-shot fashion, using EEG synthesized responses to hundreds of thousands of candidate image conditions. Third, we show that both the high number of conditions as well as the trial repetitions of the EEG dataset contribute to the trained models’ prediction accuracy. Fourth, we built encoding models whose predictions well generalize to novel participants. Fifth, we demonstrate full end-to-end training of randomly initialized DNNs that output EEG responses for arbitrary input images. We release this dataset as a tool to foster research in visual neuroscience and computer vision.
Spin waves in yttrium-iron garnet has been the subject of research for decades. Recently the report of Bose-Einstein condensation at room temperature has brought these experiments back into focus. Due to the small mass of quasiparticles compared to atoms for example, the condensation temperature can be much higher. With spin-wave quasiparticles, so-called magnons, even room temperature can be reached by externally injecting magnons. But also possible applications in information technologies are of interest. Using excitations as carriers for information instead of charges delivers a much more efficient way of processing data. Basic logical operations have already been realized. Finally the wavelength of spin waves which can be decreased to nanoscale, gives the opportunity to further miniaturize devices for receiving signals for example in smartphones.
For all of these purposes the magnon system is driven far out of equilibrium. In order to get a better fundamental understanding, we concentrate in the main part of this thesis on the nonequilibrium aspect of magnon experiments and investigate their thermalization process. In this context we develop formalisms which are of general interest and which can be adopted to many different kinds of systems.
A milestone in describing gases out of equilibrium was the Boltzmann equation discovered by Ludwig Boltzmann in 1872. In this thesis extensions to the Boltzmann equation with improved approximations are derived. For the application to yttrium-iron garnet we describe the thermalization process after magnons were excited by an external microwave field.
First we consider the Bose-Einstein condensation phenomena. A special property of thin films of yttrium-iron garnet is that the dispersion of magnons has its minimum at finite wave vectors which leads to an interesting behavior of the condensate. We investigate the spatial structure of the condensate using the Gross-Pitaevskii equation and find that the magnons can not condensate only at the energy minimum but that also higher Fourier modes have to be occupied macroscopically. In principle this can lead to a localization on a lattice in real space.
Next we use functional renormalization group methods to go beyond the perturbation theory expressions in the Boltzmann equation. It is a difficult task to find a suitable cutoff scheme which fits to the constraints of nonequilibrium, namely causality and the fluctuation-dissipation theorem when approaching equilibrium. Therefore the cutoff scheme we developed for bosons in the context of our considerations is of general interest for the functional renormalization group. In certain approximations we obtain a system of differential equations which have a similar transition rate structure to the Boltzmann equation. We consider a model of two kinds of free bosons of which one type of boson acts as a thermal bath to the other one. Taking a suitable initial state we can use our formalism to describe the dynamics of magnons such that an enhanced occupation of the ground state is achieved. Numerical results are in good agreement with experimental data.
Finally we extend our model to consider also the pumping process and the decrease of the magnon particle number till thermal equilibrium is reached again. Additional terms which explicitly break the U(1)-symmetry make it necessary to also extend the theory from which a kinetic equation can be deduced. These extensions are complicated and we therefore restrict ourselves to perturbation theory only. Because of the weak interactions in yttrium-iron garnet this provides already good results.
Background: The aim of this pilot study was to analyze postures during the work of neurologists with respect to their occupational activities.
Methods: A total data material of 64.8 h (3885.74 min) of nine (three m/six f) neurologists (assistant physicians) was collected. Kinematic data were collected using the CUELA system (electro-goniometry). In addition, the occupational tasks performed on-site were subject to a detailed objective activity analysis. All activities were assigned to the categories "Office activities" (I), "Measures on patients" (II) and "Other activities" (III). The angle values of each body region (evaluation parameters) were evaluated according to ergonomic ISO standards.
Results: Only 3.4% of the working hours were spent with (II), while 50.8% of time was spent with (I) and 45.8% with (III). All tasks of category (II) revealed an increased ergonomic risk to the head, neck, trunk and back areas. During category (I) especially neck and back movements in the sagittal plane showed higher ergonomic risk levels.
Conclusion: Despite frequently performed awkward body positions in (II), the ergonomic risk is considered as rather low, since the percentage time share totaled only 3.4%. As a result, "Office activities" have been detected as high predictor to cause stress load on the musculoskeletal system in the daily work of neurologists.
By running a temperature series of molecular dynamics (MD) simulations starting from the known low-temperature phase, the experimentally observed phase transition in a `jumping crystal' was captured, thereby providing a prediction of the unknown crystal structure of the high-temperature phase and clarifying the phase-transition mechanism. The phase transition is accompanied by a discontinuity in two of the unit-cell parameters. The structure of the high-temperature phase is very similar to that of the low-temperature phase. The anisotropic displacement parameters calculated from the MD simulations readily identified libration as the driving force behind the phase transition. Both the predicted crystal structure and the phase-transition mechanism were verified experimentally using TLS (translation, libration, screw) refinement against X-ray powder diffraction data.
Motivated by recent reports of a quantum-disordered ground state in the triangular lattice compound NaRuO2, we derive a jeff = 1/2 magnetic model for this system by means of first-principles calculations. The pseudospin Hamiltonian is dominated by bond-dependent off-diagonal Γ interactions, complemented by a ferromagnetic Heisenberg exchange and a notably antiferromagnetic Kitaev term. In addition to bilinear interactions, we find a sizable four-spin ring exchange contribution with a strongly anisotropic character, which has been so far overlooked when modeling Kitaev materials. The analysis of the magnetic model, based on the minimization of the classical energy and exact diagonalization of the quantum Hamiltonian, points toward the existence of a rather robust easy-plane ferromagnetic order, which cannot be easily destabilized by physically relevant perturbations.
Background: Novel microscopic techniques which bypass the resolution limit in light microscopy are becoming routinely established today. The higher spatial resolution of super-resolution microscopy techniques demands for precise correction of drift, spectral and spatial offset of images recorded at different axial planes.
Methods: We employ a hydrophilic gel matrix for super-resolution microscopy of cellular structures. The matrix allows distributing fiducial markers in 3D, and using these for drift correction and multi-channel registration. We demonstrate single-molecule super-resolution microscopy with photoswitchable fluorophores at different axial planes. We calculate a correction matrix for each spectral channel, correct for drift, spectral and spatial offset in 3D.
Results and discussion: We demonstrate single-molecule super-resolution microscopy with photoswitchable fluorophores in a hydrophilic gel matrix. We distribute multi-color fiducial markers in the gel matrix and correct for drift and register multiple imaging channels. We perform two-color super-resolution imaging of click-labeled DNA and histone H2B in different axial planes, and demonstrate the quality of drift correction and channel registration quantitatively. This approach delivers robust microscopic data which is a prerequisite for data interpretation.
For genus g=2i≥4 and the length g−1 partition μ=(4,2,…,2,−2,…,−2) of 0, we compute the first coefficients of the class of D¯¯¯¯(μ) in PicQ(R¯¯¯¯g), where D(μ) is the divisor consisting of pairs [C,η]∈Rg with η≅OC(2x1+x2+⋯+xi−1−xi−⋯−x2i−1) for some points x1,…,x2i−1 on C. We further provide several enumerative results that will be used for this computation.
For genus g=2i≥4 and the length g−1 partition μ=(4,2,…,2,−2,…,−2) of 0, we compute the first coefficients of the class of D¯¯¯¯(μ) in PicQ(R¯¯¯¯g), where D(μ) is the divisor consisting of pairs [C,η]∈Rg with η≅OC(2x1+x2+⋯+xi−1−xi−⋯−x2i−1) for some points x1,…,x2i−1 on C. We further provide several enumerative results that will be used for this computation.
For genus g=2i≥4 and the length g−1 partition μ=(4,2,…,2,−2,…,−2) of 0, we compute the first coefficients of the class of D¯¯¯¯(μ) in PicQ(R¯¯¯¯g), where D(μ) is the divisor consisting of pairs [C,η]∈Rg with η≅OC(2x1+x2+⋯+xi−1−xi−⋯−x2i−1) for some points x1,…,x2i−1 on C. We further provide several enumerative results that will be used for this computation.
For genus g=2i≥4 and the length g−1 partition μ=(4,2,…,2,−2,…,−2) of 0, we compute the first coefficients of the class of D¯¯¯¯(μ) in PicQ(R¯¯¯¯g), where D(μ) is the divisor consisting of pairs [C,η]∈Rg with η≅OC(2x1+x2+⋯+xi−1−xi−⋯−x2i−1) for some points x1,…,x2i−1 on C. We further provide several enumerative results that will be used for this computation.
Background & Aims: Elimination of chronic HBV/HDV infection remains a major global health challenge. Targeting excessive hepatitis B surface antigen (HBsAg) release may provide an interesting window of opportunity to break immune tolerance and to achieve a functional cure using additional antivirals.
Methods: We evaluated a HBsAg-specific human monoclonal antibody, as part of either a prophylactic or therapeutic strategy, against HBV/HDV infection in cell culture models and in human-liver chimeric mice. To assess prophylactic efficacy, mice were passively immunized prior to infection with HBV or HBV/HDV (coinfection and superinfection setting). Therapeutic efficacy was assessed in HBV and HBV/HDV-coinfected mice receiving 4 weeks of treatment. Viral parameters (HBV DNA, HDV RNA and HBsAg) were assessed in mouse plasma.
Results: The antibody could effectively prevent HBV/HDV infection in a dose-dependent manner with IC50 values of ∼3.5 ng/ml. Passive immunization showed complete protection of mice from both HBV and HBV/HDV coinfection. Moreover, HDV superinfection was either completely prevented or at least attenuated in HBV-infected mice. Finally, antibody treatment in mice with established HBV/HDV infection resulted in a significant decline in viremia and a concomitant drop in on-treatment HBsAg, with a moderate viral rebound following treatment cessation.
Conclusion: We present data on a valuable antibody candidate that could complement other antivirals in strategies aimed at achieving functional cure of chronic HBV and HDV infection.
Impact and implications: Patients chronically infected with HBV may eventually develop liver cancer and are at great risk of being superinfected with HDV, which worsens and accelerates disease progression. Unfortunately, current treatments can rarely eliminate both viruses from chronically infected patients. In this study, we present data on a novel antibody that is able to prevent chronic HBV/HDV infection in a mouse model with a humanized liver. Moreover, antibody treatment of HBV/HDV-infected mice strongly diminishes viral loads during therapy. This antibody is a valuable candidate for further clinical development.
We provide a Hopf boundary lemma for the regional fractional Laplacian (−Δ)sΩ, with Ω ⊂ RN a bounded open set. More precisely, given u a pointwise or weak super-solution of the equation (−Δ)s u = c(x)u in Ω, we show that the ratio u(x)∕(dist(x, 𝜕Ω))2s−1 is strictly Ω positive as x approaches the boundary 𝜕Ω of Ω. We also prove a strong maximum principle for distributional super-solutions.
Breast cancer is fast becoming the leading cause of oncologic morbidity and mortality among women worldwide. Demographic changes in Asia, Southeast Asia, and South America will further accelerate this trend. Different specialties are involved in the treatment of breast cancer patients: gynecology, surgery, pathology, hematology/oncology, radiology, radiation oncology, and nuclear medicine. Optimal results are seen in countries providing standardized breast cancer care in certified breast centers. The present article provides an overview of current state-of-the-art treatment strategies and explains the contributions of different specialties to optimal and individualized care for breast cancer patients. Breast cancer will be one of the most important health issues facing physicians involved with women’s health and a basic understanding of current treatment objectives will be essential medical knowledge for everyone taking care of female patients.
The geminal frustrated Lewis pair tBu2PCH2B(Fxyl)2 (1; Fxyl=3,5-(CF3)2C6H3) is accessible in 65 % yield from tBu2PCH2Li and (Fxyl)2BF. According to NMR spectroscopy and X-ray crystallography, 1 is monomeric both in solution and in the solid state. The intramolecular P⋅⋅⋅B distance of 2.900(5) Å and the full planarity of the borane site exclude any significant P/B interaction. Compound 1 readily activates a broad variety of substrates including H2, EtMe2SiH, CO2/CS2, Ph2CO, and H3CCN. Terminal alkynes react with heterolysis of the C−H bond. Haloboranes give cyclic adducts with strong P−BX3 and weak R3B−X bonds. Unprecedented transformations leading to zwitterionic XP/BCX3 adducts occur on treatment of 1 with CCl4 or CBr4 in Et2O. In less polar solvents (C6H6, n-pentane), XP/BCX3 adduct formation is accompanied by the generation of significant amounts of XP/BX adducts. FLP 1 catalyzes the hydrogenation of PhCH=NtBu and the hydrosilylation of Ph2CO with EtMe2SiH.
MicroRNAs (miRNAs) are critical post-transcriptional regulators in many biological processes. They act by guiding RNA-induced silencing complexes to miRNA response elements (MREs) in target mRNAs, inducing translational inhibition and/or mRNA degradation. Functional MREs are expected to predominantly occur in the 3' untranslated region and involve perfect base-pairing of the miRNA seed. Here, we generate a high-resolution map of miR-181a/b-1 (miR-181) MREs to define the targeting rules of miR-181 in developing murine T-cells. By combining a multi-omics approach with computational high-resolution analyses, we uncover novel miR-181 targets and demonstrate that miR-181 acts predominantly through RNA destabilization. Importantly, we discover an alternative seed match and identify a distinct set of targets with repeat elements in the coding sequence which are targeted by miR-181 and mediate translational inhibition. In conclusion, deep profiling of MREs in primary cells is critical to expand physiologically relevant targetomes and establish context-dependent miRNA targeting rules.