Results 81 to 90 of about 2,388,151 (359)

3D Neuro-electronic interface devices for neuromuscular control: Design studies and realisation steps [PDF]

open access: yes, 1995
In order to design the shape and dimensions of new 3D multi-microelectrode information transducers properly, i. e. adapted to the scale of information delivery to and from peripheral nerve fibres, a number of studies were, and still are, being performed ...
Frieswijk, Theo A.   +4 more
core   +2 more sources

Electrochemical polymerization of conducting polymers in living neural tissue [PDF]

open access: yesJournal of Neural Engineering, 2007
A number of biomedical devices require extended electrical communication with surrounding tissue. Significant improvements in device performance would be achieved if it were possible to maintain communication with target cells despite the reactive, insulating scar tissue that forms at the device-tissue interface.
David C. Martin   +2 more
openaire   +3 more sources

Autophagy in cancer and protein conformational disorders

open access: yesFEBS Letters, EarlyView.
Autophagy plays a crucial role in numerous biological processes, including protein and organelle quality control, development, immunity, and metabolism. Hence, dysregulation or mutations in autophagy‐related genes have been implicated in a wide range of human diseases.
Sergio Attanasio
wiley   +1 more source

Hopping Conductivity of a Nearly-1d Fractal: a Model for Conducting Polymers [PDF]

open access: yes, 1998
We suggest treating a conducting network of oriented polymer chains as an anisotropic fractal whose dimensionality D=1+\epsilon is close to one. Percolation on such a fractal is studied within the real space renormalization group of Migdal and Kadanoff.
arxiv   +1 more source

Conductivity Imaging from Internal Measurements with Mixed Least-Squares Deep Neural Networks [PDF]

open access: yesarXiv, 2023
In this work we develop a novel approach using deep neural networks to reconstruct the conductivity distribution in elliptic problems from one measurement of the solution over the whole domain. The approach is based on a mixed reformulation of the governing equation and utilizes the standard least-squares objective, with deep neural networks as ansatz ...
arxiv  

Scaling Properties of Conductance at Integer Quantum Hall Plateau Transitions [PDF]

open access: yesPhys. Rev. B 58, R3576 (1998), 1998
We investigate the scaling properties of zero temperature conductances at integer quantum Hall plateau transitions in the lowest Landau band of a two-dimensional tight-binding model. Scaling is obeyed for all energy and system sizes with critical exponent nu =7/3 .
arxiv   +1 more source

Liquid Metal Enabled Droplet Circuits

open access: yes, 2018
Conventional electrical circuits are generally rigid in their components and working styles which are not flexible and stretchable. From an alternative, liquid metal based soft electronics is offering important opportunities for innovating modern ...
Liu, Jing, Ren, Yi
core   +1 more source

A mechanism for achieving zero-lag long-range synchronization of neural activity [PDF]

open access: yes, 2009
Poster presentation: How can two distant neural assemblies synchronize their firings at zero-lag even in the presence of non-negligible delays in the transfer of information between them?
Fischer, Ingo   +4 more
core   +1 more source

Unlocking the potential of tumor‐derived DNA in urine for cancer detection: methodological challenges and opportunities

open access: yesMolecular Oncology, EarlyView.
Urine is a rich source of biomarkers for cancer detection. Tumor‐derived material is released into the bloodstream and transported to the urine. Urine can easily be collected from individuals, allowing non‐invasive cancer detection. This review discusses the rationale behind urine‐based cancer detection and its potential for cancer diagnostics ...
Birgit M. M. Wever   +1 more
wiley   +1 more source

Physics informed neural network for charged particles surrounded by conductive boundaries [PDF]

open access: yesarXiv, 2023
In this paper, we developed a new PINN-based model to predict the potential of point-charged particles surrounded by conductive walls. As a result of the proposed physics-informed neural network model, the mean square error and R2 score are less than 7% and more than 90% for the corresponding example simulation, respectively. Results have been compared
arxiv  

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