Related papers: Mapping cellular magnesium using X-ray microfluore…
Understanding and accurately predicting hydrogen diffusion in materials is challenging due to the complex interactions between hydrogen defects and the crystal lattice. These interactions span large length and time scales, making them…
Since the invention of the atomic force microscope (AFM) in 1986, there has been a drive to apply this scanning probe technique or a form of this technique to various disciplines in nanoscale science. Magnetic force microscopy (MFM) is a…
In this paper we report on the gas-phase abundance of singly-ionized magnesium (Mg II) in 44 lines of sight, using data from the Hubble Space Telescope (HST). We measure Mg II column densities by analyzing medium- and high-resolution…
We present the abundances of magnesium (Mg) and silicon (Si) for 314 dwarf stars with spectral types in the interval K7.0-M5.5 (Teff range ~4200-3050 K) observed with the CARMENES high-resolution spectrograph at the 3.5 m telescope at the…
Extracting reliable and quantitative microstructure information of living tissue by non-invasive imaging is an outstanding challenge for understanding disease mechanisms and allowing early stage diagnosis of pathologies. Magnetic Resonance…
Diffusive motion of regulatory enzymes on biopolymers with eventual capture at a reaction site is a common feature in cell biology. Using a lattice gas model we study the impact of diffusion and capture for a microtubule polymerase and a…
A novel non-invasive microscopy technique for imaging and sizing of folded DNA molecules with the use of photovoltaic tweezers and phase-sensitive detection is elaborated and realized. This novel method is compared with the state-of-the-art…
Cells and tissues are constantly exposed to various chemical and physical signals that intricately regulate various physiological and pathological processes. This study explores the integration of two biophysical methods, Traction Force…
We present a new annotated microscopic cellular image dataset to improve the effectiveness of machine learning methods for cellular image analysis. Cell counting is an important step in cell analysis. Typically, domain experts manually…
Fluorescence microscopy allows for a detailed inspection of cells, cellular networks, and anatomical landmarks by staining with a variety of carefully-selected markers visualized as color channels. Quantitative characterization of…
The X-shooter Spectral Library (XSL) is a large empirical stellar library used as a benchmark for the development of stellar population models. The inclusion of $\alpha$-elements abundances is crucial to disentangling the chemical evolution…
Real-world applications may be affected by outlying values. In the model-based clustering literature, several methodologies have been proposed to detect units that deviate from the majority of the data (rowwise outliers) and trim them from…
We present a novel experimental setup in which magnetic and optical tweezers are combined for torque and force transduction onto single filamentous molecules in a transverse configuration to allow simultaneous mechanical measurement and…
MPC (Magneto-Photonic Crystal) Optimisation is a feature-rich Windows software application designed to enable researchers to analyze the optical and magneto-optical spectral properties of multilayers containing gyrotropic constituents. A…
Magnetic properties of thin (Ga,Mn)As layers improve during annealing by out-diffusion of interstitial Mn ions to a free surface. Out-diffused Mn atoms participate in the growth of a Mn-rich surface layer and a saturation of this layer…
It is demonstrated that the use of a Micrometric Thin $^{39}$K vapor Cell (MTC) and Saturated Absorption spectroscopy (SA) allows to form narrow atomic lines in transmission spectrum without unwanted Cross-Over (CO) resonances. Another…
Fluorescence imaging is the most widely used method for unveiling the molecular composition of biological specimens. However, the weak optical emission of fluorescent probes and the tradeoff between imaging speed and sensitivity is…
Real-time monitoring of dynamic biological processes in the body is critical to understanding disease progression and treatment response. This data, for instance, can help address the lower than 50% response rates to cancer immunotherapy.…
We propose an approach for exploiting machine learning to approximate electronic fields in crystalline solids subjected to deformation. Strain engineering is emerging as a widely used method for tuning the properties of materials, and this…
In digital pathology, both detection and classification of cells are important for automatic diagnostic and prognostic tasks. Classifying cells into subtypes, such as tumor cells, lymphocytes or stromal cells is particularly challenging.…