The stability of solutions to evolution equations with respect to small stochastic perturbations is considered. The stability of a stochastic dynamical system is characterized by the local stability index. The limit of this index with respect to infinite time describes the asymptotic stability of a stochastic dynamical system. Another limit of the stability index is given by the vanishing intensity of stochastic perturbations. A dynamical system is stochastically unstable when these two limits do not commute with each other. Several examples illustrate the thesis that there always exist such stochastic perturbations that render a given dynamical system stochastically unstable. The stochastic instability of quasi-isolated systems is responsible for the irreversibility of time arrow.
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http://dx.doi.org/10.1103/PhysRevE.65.056118 | DOI Listing |
Protein Sci
February 2025
Department of Biochemistry and Molecular Biology, The University of Chicago, Chicago, Illinois, USA.
We have developed a portfolio of antibody-based modules that can be prefabricated as standalone units and snapped together in plug-and-play fashion to create uniquely powerful multifunctional assemblies. The basic building blocks are derived from multiple pairs of native and modified Fab scaffolds and protein G (PG) variants engineered by phage display to introduce high pair-wise specificity. The variety of possible Fab-PG pairings provides a highly orthogonal system that can be exploited to perform challenging cell biology operations in a straightforward manner.
View Article and Find Full Text PDFProtein Sci
February 2025
IRR Chemistry Hub, Institute for Regeneration and Repair, The University of Edinburgh, Edinburgh, UK.
Super-resolution microscopy has revolutionized biological imaging, enabling the visualization of structures at the nanometer length scale. Its application in live cells, however, has remained challenging. To address this, we adapted LIVE-PAINT, an approach we established in yeast, for application in live mammalian cells.
View Article and Find Full Text PDFBiomark Res
January 2025
BK21 FOUR KNU Convergence Educational Program of Biomedical Sciences for Creative Future Talents, Department of Biomedical Sciences, School of Medicine, Kyungpook National University, Daegu, 41944, Korea.
Macrophages are pivotal in the body's defense and response to inflammation. They are present in significant numbers and are widely implicated in various diseases, including cancer. While molecular and histological techniques have advanced our understanding of macrophage biology, their precise function within the cancerous microenvironments remains underexplored.
View Article and Find Full Text PDFOphthalmic Physiol Opt
January 2025
Vision and Hearing Sciences Research Centre, Anglia Ruskin University, Cambridge, UK.
Purpose: Wearable electronic low vision enhancement systems (wEVES) improve visual function but are not widely adopted by people with vision impairment. Here, qualitative research methods were used to investigate the usefulness of wEVES for people with age-related macular degeneration (AMD) after an extended home trial.
Methods: Following a 12-week non-masked randomised crossover trial, semi-structured interviews were completed with 34 participants with AMD, 64.
Sci Rep
January 2025
Department of Computer Science and Engineering, E.G.S. Pillay Engineering College, Nagapattinam, 611002, Tamil Nadu, India.
In response to the pressing need for the detection of Monkeypox caused by the Monkeypox virus (MPXV), this study introduces the Enhanced Spatial-Awareness Capsule Network (ESACN), a Capsule Network architecture designed for the precise multi-class classification of dermatological images. Addressing the shortcomings of traditional Machine Learning and Deep Learning models, our ESACN model utilizes the dynamic routing and spatial hierarchy capabilities of CapsNets to differentiate complex patterns such as those seen in monkeypox, chickenpox, measles, and normal skin presentations. CapsNets' inherent ability to recognize and process crucial spatial relationships within images outperforms conventional CNNs, particularly in tasks that require the distinction of visually similar classes.
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