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Existence of transmission eigenvalues for biharmonic scattering by a clamped planar region
No full textIn this paper, we study the so-called clamped transmission eigenvalue problem. This is a new transmission eigenvalue problem that is derived from the scattering of an impenetrable clamped obstacle in a thin elastic plate. The scattering problem is modeled by a biharmonic wave operator given by the Kirchhoff-Love infinite plate problem in the frequency domain. These scattering problems have not been studied to the extent of other models. Unlike other transmission eigenvalue problems, the problem studied here is a system of homogeneous PDEs defined in all of . This provides unique analytical and computational difficulties when studying the clamped transmission eigenvalue problem. We are able to prove that there exist infinitely many real clamped transmission eigenvalues. This is done by studying the equivalent variational formulation. We also investigate the relationship of the clamped transmission eigenvalues to the Dirichlet and Neumann eigenvalues of the negative Laplacian for the bounded scattering obstacle
Observing the spatial and temporal evolution of exciton wave functions
No full textExcitons, the correlated electron-hole pairs governing optical and transport properties in organic semiconductors, have long resisted direct experimental access to their full quantum-mechanical wave functions. Here, we use femtosecond time-resolved photoemission orbital tomography (trPOT), combining high-harmonic probe pulses with time- and momentum-resolved photoelectron spectroscopy, to directly image the momentum-space distribution and ultrafast dynamics of excitons in -sexithiophene thin films. We introduce a quantitative model that enables reconstruction of the exciton wave function in real space, including both its spatial extent and its internal phase structure. The reconstructed wave function reveals coherent delocalization across approximately three molecular units and exhibits a characteristic phase modulation, consistent with ab initio calculations within the framework of many-body perturbation theory. Time-resolved measurements further show a \% contraction of the exciton radius within 400 fs, providing direct evidence of self-trapping driven by exciton-phonon coupling. These results establish trPOT as a general and experimentally accessible approach for resolving exciton wave functions -- with spatial, phase, and temporal sensitivity -- in a broad class of molecular and low-dimensional materials
Assessing the Impact of Ground-Based Cloud Observations on Photovoltaic Generation Forecast
No full textThe widespread integration of photovoltaic (PV) systems into modern power grids poses several operational challenges, primarily due to the stochastic nature of weather conditions, which leads to uncertainty in power generation. In this context, accurate forecasting of PV output becomes critical, especially for electricity markets and grid management. This paper investigates the relationship between non-conventional weather variables (i.e., ground-based cloud observations) and PV power generation, and evaluates the impact of incorporating such data into a machine learning model to improve forecasting performance. The analysis is conducted using real power output and ground-based meteorological data collected at Forschungszentrum Jülich, in Germany
Self-Supervised Learning based on Transformed Image Reconstruction for Equivariance-Coherent Feature Representation
No full textThe equivariant behaviour of features is essential in many computer vision tasks, yet popular self-supervised learning (SSL) methods tend to constrain equivariance by design. We propose a self-supervised learning approach where the system learns transformations independently by reconstructing images that have undergone previously unseen transformations. Specifically, the model is tasked to reconstruct intermediate transformed images, e.g. translated or rotated images, without prior knowledge of these transformations. This auxiliary task encourages the model to develop equivariance-coherent features without relying on predefined transformation rules. To this end, we apply transformations to the input image, generating an image pair, and then split the extracted features into two sets per image. One set is used with a usual SSL loss encouraging invariance, the other with our loss based on the auxiliary task to reconstruct the intermediate transformed images. Our loss and the SSL loss are linearly combined with weighted terms. Evaluating on synthetic tasks with natural images, our proposed method strongly outperforms all competitors, regardless of whether they are designed to learn equivariance. Furthermore, when trained alongside augmentation-based methods as the invariance tasks, such as iBOT or DINOv2, we successfully learn a balanced combination of invariant and equivariant features. Our approach performs strong on a rich set of realistic computer vision downstream tasks, almost always improving over all baselines
Organization of the Macaque Monkey Insular Cortex Based on Multimodal Receptor Architectonics
No full textA novel perspective on “Fenton-like” degradation studies on proton exchange membranes
No full textUnderstanding membrane degradation under realistic conditions is critical to improve the lifetime and commercial viability of PEM electrolyzers. This study re-evaluates conventional ex-situ Fenton degradation tests, which simulate long-term radical-driven membrane damage using high concentrations of Fe²⁺ and H₂O₂. This study focuses on evaluating their relevance to in-operando degradation mechanisms and to gain an in-depth understanding of morphological and chemical degradation processes. By combining microscopic, spectroscopic, and electrochemical analyses, it is observed that morphological damage from oxygen evolution, rather than radical-induced chain scission, dominates under “Fenton-like” AST conditions. This challenges current AST design and motivates revised protocols aligned with true PEM electrolyzer operation
Exploring the catalyttic potential of the carboxylic acid reductase from Neurospora crassa for the enzymtic reduction of formic acid to formaldehyde
No full textHow childhood adversities shape minds and lives: An analysis across the affective-to-psychotic spectrum.
No full textAdverse childhood experiences (ACE) contribute significantly to mental disorders. While existing research has primarily focused on specific diagnostic categories, a comprehensive understanding of how childhood trauma interacts with biological factors, symptom severity and functioning requires a broader perspective. Therefore, this study adopted a cross-diagnostic approach to examine the impact of ACE on quality of life (QoL), psychosocial functioning, and symptom burden by analyzing data from the PsyCourse Study, a longitudinal, multicenter research project conducted in Germany and Austria. We used multivariate linear regression models and cluster analysis to evaluate data from 725 participants with affective and psychotic disorders and healthy controls who completed the self-assessed Childhood Trauma Screener (CTS) during the course of the study. The results showed that across diagnoses, QoL was significantly impacted by ACE, particularly emotional neglect. An ablation study revealed that 2.3 % to 6.2 % of the variability in QoL domains could be attributed to ACE. Across diagnoses, symptoms of depression were significantly associated with ACE, especially emotional abuse, but psychotic and manic symptoms were not. Polygenic risk scores (PRS) did not emerge as significant predictors for any examined outcomes. Cluster analysis revealed distinct symptom profiles: Averaged over time, patients with less trauma exposure were rather in the subclinical than in the clinically ill clusters. We conclude that the pervasive influence of ACE on disease severity should be considered when evaluating and treating patients with affective and psychotic disorders