Microengineered devices enable long-term imaging of the ventral nerve cord in behaving adult Drosophila

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This work proposes a transfer learning-based encoder-decoder framework to predict the relationship between loading conditions and residual stiffness in carbon fiber reinforced composites and adhesives. The encoder, built from a Convolutional Neural Network ...

In face of cumulating evidence about the impact of human-induced environmental changes on mental health and behavior, our understanding of the main effects and interactions between environmental factors – i.e., the exposome and the brain – is still limited ...

Functional connectivity (FC) between brain regions as manifested via fMRI entails signatures that can be used to differentiate individuals and decode cognitive tasks. In this work, we use methods from graph structure inference to estimate FC, which is in c ...

Deep neural networks provide magnificent results for vision tasks. However, their complex structures and numerous parameters make them computationally and memory-wise intensive. Execution of these models on resource-constrained, camera-equipped devices suc ...

Buildings play a pivotal role in the ongoing worldwide energy transition, accounting for 30% of the global energy consumption. With traditional engineering solutions reaching their limits to tackle such large-scale problems, data-driven methods and Machine ...

Cervical spinal cord injury (SCI) leads to permanent impairment of arm and hand functions. Here we conducted a prospective, single-arm, multicenter, open-label, non-significant risk trial that evaluated the safety and efficacy of ARCEX Therapy to improve a ...

The monumental progress in the development of machine learning models has led to a plethora of applications with transformative effects in engineering and science. This has also turned the attention of the research community towards the pursuit of construc ...

In this work, we present for the first time a method for detecting label errors in image datasets with semantic segmentation, i.e., pixel-wise class labels. Annotation acquisition for semantic segmentation datasets is time-consuming and requires plenty of ...

Herringbone grooved journal bearings (HGJBs) are widely used in micro-turbocompressor applications due to their high load-carrying capacity, low friction, and oil-free solution. However, the performance of these bearings is sensitive to manufacturing devia ...

Different types of mental rotation tests have been used extensively in psychology to understand human visual reasoning and perception. Understanding what an object or visual scene would look like from another viewpoint is a challenging problem that is made ...

The Laser Power Bed Fusion (LPBF) process is of high interest to many industries, such as motors and vehicles, robotics, biomedical applications, aerospace, and others. LPBF workpieces can indeed achieve near full density and high resistance. However, a la ...

Neural functions operate in tightly controlled conditions that are mediated by multiple electrical and chemical phenomena. Brain disorders such as Parkinson's Disease and Alzheimer's Disease perturb these conditions and cause a loss of neurons, which impai ...

State-of-the-art methods for self-supervised sequential action alignment rely on deep networks that find correspon- dences across videos in time. They either learn frame-to- frame mapping across sequences, which does not leverage temporal information, or a ...

The growing popularity of edgeAI requires novel solutions to support the deployment of compute-intense algorithms in embedded devices. In this article, we advocate for a holistic approach, where application-level transformations are jointly conceived with ...

Microengineered devices enable long-term imaging of the ventral nerve cord in behaving adult Drosophila

Chat with Graph Search

Transfer learning-based approach for evaluating residual stiffness in carbon fiber reinforced composites and adhesives

Large-scale georeferenced neuroimaging and psychometry data link the urban environmental exposome with brain health

Joint Subject-Identification and Task-Decoding From Inferred Functional Brain Graphs Via a Multi-Task Neural Network

Smart Edge for Hierarchical Vision Systems

Fusing Pre-existing Knowledge and Machine Learning for Enhanced Building Thermal Modeling and Control

Non-invasive spinal cord electrical stimulation for arm and hand function in chronic tetraplegia: a safety and efficacy trial

Probabilistic methods for neural combinatorial optimization

Automated Detection of Label Errors in Semantic Segmentation Datasets via Deep Learning and Uncertainty Quantification

Robust Design of Herringbone Grooved Journal Bearings using Multi-Objective Optimization with Artificial Neural Networks

Visual question answering from another perspective: CLEVR mental rotation tests *

Acoustic emission for the prediction of processing regimes in Laser Powder Bed Fusion, and the generation of processing maps

A neural probe to sample brain fluid in nanoliter volumes for quantitative molecular studies

Learning to Align Sequential Actions in the Wild

A hardware/software co-design vision for deep learning at the edge

Editorial: Computational Neuroimage Analysis Tools for Brain (Diseases) Biomarkers