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This study presents an augmented hybrid approach for improving the diagnosis of malignant skin lesions by combining convolutional neural network (CNN) predictions with selective human interventions based on prediction confidence. The algorithm retains high ...

Genome-wide chromatin conformation capture assays provide formidable insights into the spatial organization of genomes. However, due to the complexity of the data structure, their integration in multi-omics workflows remains challenging. We present data st ...

This study integrates deep learning and geospatial analysis to enhance soil loss estimation in the Moulouya Watershed, a region prone to erosion due to diverse topography and climatic conditions. Traditional models like the Universal Soil Loss Equation (US ...

Geometric properties of lattice quantum gravity in two dimensions are studied numerically via Monte Carlo on Euclidean Dynamical Triangulations. A new computational method is proposed to simulate gravity coupled with fermions, which allows the study of int ...

Correlative light and electron microscopy (CLEM) combines light microscopy, for identifying a target via genetic labels, dyes, antibodies and morphological features, with electron microscopy, for analyzing high-resolution subcellular ultrastructures. Here, ...

Background and Objective: Computational models of the cardiovascular system allow for a detailed and quantitative investigation of both physiological and pathological conditions, thanks to their ability to combine clinical-possibly patient-specific-data wi ...

Monitoring of cardiac output (CO) is a mainstay of hemodynamic management in the acutely or critically ill patient. Invasive determination of CO using thermodilution, albeit regarded as the gold standard, is cumbersome and bears risks inherent to catheteri ...

Fluorescence confocal laser-scanning microscopy (LSM) is one of the most popular tools for life science research. This popularity is expected to grow thanks to single-photon array detectors tailored for LSM. These detectors offer unique single-photon spati ...

SARS-CoV-2, the causative agent of COVID-19, is predominantly transmitted by respiratory aerosol and contaminated surfaces. Recent studies demonstrated that aerosols can become acidic, and acidification has been proposed as decontamination method. Here, we ...

Human babies have a natural desire to interact with new toys and objects, through which they learn how the world around them works, e.g., that glass shatters when dropped, but a rubber ball does not. When their predictions are proven incorrect, such as whe ...

Estimating ecosystem-atmosphere fluxes such as evapotranspiration (ET) in a robust manner and at a global scale remains a challenge. Methods based on machine learning (ML) have shown promising results in achieving such upscaling, providing a complementary ...

We present a combination technique based on mixed differences of both spatial approximations and quadrature formulae for the stochastic variables to solve efficiently a class of optimal control problems (OCPs) constrained by random partial differential equ ...

This paper introduces a novel architecture for Quantum Graph Neural Networks, which is significantly different from previous approaches found in the literature. The proposed approach produces similar outcomes with respect to previous models but with fewer ...

We report the development of a continuous-wave and pulsed X-band electron spin resonance (ESR) spectrometer for the study of spins on ordered surfaces down to cryogenic temperatures. The spectrometer operates in ultra-high vacuum and utilizes a half-wavele ...

The optimistic gradient method is useful in addressing minimax optimization problems. Motivated by the observation that the conventional stochastic version suffers from the need for a large batch size on the order of O(ϵ-2) to achieve an ϵ-stationary solut ...

EncodingActs investigates how computational methods can facilitate the transmission of multifaceted knowledge within intangible cultural heritage (ICH). ICH, characterized by living, tacit, yet complex epistemic systems, is conventionally viewed as challen ...

To retrieve Surface Solar Radiation (SSR) from satellite images, a baseline reflectance of the observed ground in clear-sky conditions, also called background reflectance, is necessary to distinguish atmospheric absorption and scattering effects from surfa ...

Interferometric scattering (iSCAT) microscopy enables the label-free observation of biomolecules. Consequently, single-particle imaging and tracking with the iSCAT-based method known as mass photometry (MP) is a growing area of study. However, establishing ...

Super-resolution microscopy (SRM) has undeniable potential for scientific discovery, yet still presents many challenges that hinder its widespread adoption, including technical trade-offs between resolution, speed and photodamage, as well as limitations in ...

The application of computational biology in drug development for membrane protein targets has experienced a boost from recent developments in deep learning-driven structure prediction, increased speed and resolution of structure elucidation, machine learni ...

Live-cell imaging powered by computation

Chat with Graph Search

Enhancing skin lesion classification: a CNN approach with human baseline comparison

Orchestrating chromosome conformation capture analysis with Bioconductor

Application of Deep Learning and Geospatial Analysis in Soil Loss Risk in the Moulouya Watershed, Morocco

Hausdorff dimension of fermions on a random lattice

Correlative light and electron microscopy for human brain and other biological models

The role of computational methods in cardiovascular medicine: a narrative review

Machine learning-enabled estimation of cardiac output from peripheral waveforms is independent of blood pressure measurement location in an in silico population

Compact and effective photon-resolved image scanning microscope

Inactivation of SARS-CoV-2 at acidic pH is driven by partial unfolding of spike

Seeking the new, learning from the unexpected: Computational models of surprise and novelty in the brain

On the added value of sequential deep learning for the upscaling of evapotranspiration

A Combination Technique for Optimal Control Problems Constrained by Random PDEs

A Study on Quantum Graph Neural Networks Applied to Molecular Physics

A continuous-wave and pulsed X-band electron spin resonance spectrometer operating in ultra-high vacuum for the study of low dimensional spin ensembles

Diffusion Stochastic Optimization for Min-Max Problems

EncodingActs: Modeling, Representing and Transmitting Embodied Knowledge in Traditional Martial Arts

Retrieval of Surface Solar Radiation through Implicit Albedo Recovery from Temporal Context

Surface passivation and functionalisation for mass photometry

Resolution in super-resolution microscopy – facts, artifacts, technological advancements and biological applications

Computational drug development for membrane protein targets