We characterize the properties of the asymptotic stage of modulational instability arising from localized perturbations of a constant background, including the number and location of the individual peaks in the oscillation region. We show that, for long times, the solution tends to an ensemble of classical (i.e., sech-shaped) solitons of the focusing nonlinear Schrödinger equation (as opposed to the various breatherlike solutions of the same equation with a nonzero background). We also confirm the robustness of the theoretical results by comparing the analytical predictions with careful numerical simulations with a variety of initial conditions, which confirm that the evolution of modulationally unstable media in the presence of localized initial perturbations is indeed described by the same asymptotic state.
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http://dx.doi.org/10.1103/PhysRevE.94.060201 | DOI Listing |
Unlabelled: The gut microbiota influences systemic immunity and the function of distal tissues, including the brain, liver, skin, lung, and muscle. However, the role of the gut microbiota in the foreign body response (FBR) and fibrosis around medical implants is largely unexplored. To investigate this connection, we perturbed the homeostasis of the murine gut microbiota via enterotoxigenic (ETBF) infection and implanted the synthetic polymer polycaprolactone (PCL) into a distal muscle injury.
View Article and Find Full Text PDFACS Cent Sci
January 2025
The Rosalind Franklin Institute, Harwell Science & Innovation Campus, Harwell OX11 0FA, U.K.
Protein N-glycosylation is a cotranslational modification that takes place in the endoplasmic reticulum (ER). Disruption of this process can result in accumulation of misfolded proteins, known as ER stress. In response, the unfolded protein response (UPR) restores proteostasis or responds by controlling cellular fate, including increased expression of activating transcription factor 4 (ATF4) that can lead to apoptosis.
View Article and Find Full Text PDFNeural Comput Appl
December 2022
Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, USA.
Artificial neural networks (ANNs) are one of the most promising tools in the quest to develop general artificial intelligence. Their design was inspired by how neurons in natural brains connect and process, the only other substrate to harbor intelligence. Compared to biological brains that are sparsely connected and that form sparsely distributed representations, ANNs instead process information by connecting all nodes of one layer to all nodes of the next.
View Article and Find Full Text PDFInt J Mol Sci
January 2025
Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry RAS, 117997 Moscow, Russia.
Alzheimer's disease (AD) pathogenesis is correlated with the membrane content of various lipid species, including cholesterol, whose interactions with amyloid precursor protein (APP) have been extensively explored. Amyloid-β peptides triggering AD are products of APP cleavage by secretases, which differ depending on the APP and secretase location relative to ordered or disordered membrane microdomains. We used high-resolution NMR to probe the interactions of the cholesterol analog with APP transmembrane domain in two membrane-mimicking systems resembling ordered or perturbed lipid environments (bicelles/micelles).
View Article and Find Full Text PDFBiomimetics (Basel)
January 2025
Technology Research and Development Centre, Xuelong Group Co., Ltd., Ningbo 315899, China.
To address the challenges of slow convergence speed, poor convergence precision, and getting stuck in local optima for unmanned aerial vehicle (UAV) three-dimensional path planning, this paper proposes a path planning method based on an Improved Human Evolution Optimization Algorithm (IHEOA). First, a mathematical model is used to construct a three-dimensional terrain environment, and a multi-constraint path cost model is established, framing path planning as a multidimensional function optimization problem. Second, recognizing the sensitivity of population diversity to Logistic Chaotic Mapping in a traditional Human Evolution Optimization Algorithm (HEOA), an opposition-based learning strategy is employed to uniformly initialize the population distribution, thereby enhancing the algorithm's global optimization capability.
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