This paper presents the development of a single-shot, partially spatially coherent quantitative differential phase contrast microscopy (Q-DPCM) system. The optical scheme comprises a polarizer, lenses, calcite beam displacer, and analyzer, which can be seamlessly integrated to an existing bright-field microscopy system, transforming it into a Q-DPCM system. It utilizes a partially spatially coherent ...

Talking upper-body synthesis is a promising task due to its versatile potential for video creation and consists of animating the body and face from a source image with the motion from a given driving video. However, prior synthesis approaches fall short in addressing this task and have been either limited to animating heads of a target person only, or have animated the upper body but neglected the ...

Group robustness strategies aim to mitigate learned biases in deep learning models that arise from spurious correlations present in their training datasets. However, most existing methods rely on the access to the label distribution of the groups, which is time-consuming and expensive to obtain. As a result, unsupervised group robustness strategies are sought. Based on the insight that a trained ...

Extreme precipitation events can cause severe floods that pose significant risks to human lives, properties, and ecosystems. Therefore, understanding how climate change may affect the characteristics of these events is crucial for developing effective adaptation and mitigation strategies. In this study, we investigated the effect of climate change on the extreme characteristics through the concept ...

The recent development of self-explainable deep learning approaches has focused on integrating well-defined explainability principles into learning process, with the goal of achieving these principles through optimization. In this work, we propose DIB-X, a self-explainable deep learning approach for image data, which adheres to the principles of minimal, sufficient, and interactive explanations. The ...

We address the challenge of minimizing "true risk" in multi-node distributed learning.\footnote{We use the term node to refer to a client, FPGA, APU, CPU, GPU, or worker.} These systems are frequently exposed to both inter-node and intra-node "label shifts", which present a critical obstacle to effectively optimizing model performance while ensuring that data remains confined to each node. To tackle ...

Atherogenesis is associated with elevated plasma levels of oxidized low-density lipoproteins (oxLDL). In vivo, oxLDL causes liver endothelial swelling, and disrupts liver sinusoidal endothelial cell (LSECs) fenestrations. We mapped the nanoscale kinetics of these changes in vitro in isolated rat LSECs challenged with oxLDL and monitored viability with endocytosis and cytotoxicity assays. OxLDL ...

In a world more and more dependent on new and effective energy sources, the introduction of fusion power could prove invaluable. Magnetic confinement of plasma has proved to be difficult, and the curvature of the magnetic field lines in tokamaks give rise to charge polarization at the boundary of the fusion devices leading to cross-field transport. Experiments has shown that the dominating transport ...

Amidst the intensifying extreme rainfall patterns due to climate change, global early warning systems for mass movements (e.g. landslides, avalanches) need to provide not only the coarsely aggregated danger reports, but also the necessary fine details to understand its potential implications on critical infrastructures such as transportation systems. In this study, we introduce a novel ‘intergraph’ ...

Land surface temperature (LST) serves as an important climate variable which is relevant to a number of studies related to energy and water exchanges, vegetation growth and urban heat island effects. Although LST can be derived from satellite observations, these approaches rely on cloud‐free acquisitions. This represents a significant obstacle in regions which are prone to cloud cover. In this ...