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Published in 2025 at "Nature Communications"
DOI: 10.1038/s41467-024-55478-2
Abstract: Interventional embolization has been widely used as a clinical cancer therapy, which deactivates the tumors by occluding their blood supply vessels. However, conventional methods lack active control over the embolic particles, thus having a limited…
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Keywords:
embolic particle;
via shape;
vessel;
networks via ... See more keywords
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Published in 2025 at "Green Chemistry Letters and Reviews"
DOI: 10.1080/17518253.2024.2441229
Abstract: ABSTRACT In this study, colloidal films of polystyrene micro particles were transformed into porous films with 3D networks via photo sintering. The wavelength of the irradiation light was the same as the absorption wavelength of…
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Keywords:
crystallization;
networks via;
coated porous;
photo sintering ... See more keywords
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Published in 2021 at "Journal of the Royal Society Interface"
DOI: 10.1098/rsif.2020.0985
Abstract: One of the main objectives of synthetic biology is the development of molecular controllers that can manipulate the dynamics of a given biochemical network that is at most partially known. When integrated into smaller compartments,…
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Keywords:
control biochemical;
robust control;
networks via;
biochemical reaction ... See more keywords
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Published in 2024 at "Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences"
DOI: 10.1098/rspa.2024.0774
Abstract: We use simple martingale methods to construct a large deviation theory of spin systems with pairwise interactions. As an application, we show that the fully connected case obeys a universal scaling limit that is just…
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Keywords:
scaling limits;
martingale methods;
spin networks;
networks via ... See more keywords
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Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3207197
Abstract: For having an in-depth study and analysis of various network’s structural properties such as interconnection, extensibility, availability, centralization, vulnerability and reliability, we require distance based graph theoretic parameters. Numerous parameters like distance based dimensions help…
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Keywords:
networks via;
fractional dimensions;
symmetric networks;
study convexo ... See more keywords
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Published in 2023 at "IEEE Access"
DOI: 10.1109/access.2023.3263210
Abstract: We analyze the data-dependent capacity of neural networks and assess anomalies in inputs from the perspective of networks during inference. The notion of data-dependent capacity allows for analyzing the knowledge base of a model populated…
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Keywords:
networks via;
neural networks;
via gradient;
probing purview ... See more keywords
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Published in 2025 at "Journal of Lightwave Technology"
DOI: 10.1109/jlt.2025.3621466
Abstract: An analytical model that utilizes the minimum mean square error (MMSE) equalization matrix is proposed to accurately estimate mode-dependent loss (MDL)-induced signal-to-noise ratio (SNR) penalties with substantially reduced computational cost. The method achieves an estimation…
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Keywords:
accurate qot;
prediction sdm;
qot prediction;
sdm networks ... See more keywords
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Published in 2023 at "IEEE Communications Letters"
DOI: 10.1109/lcomm.2022.3232148
Abstract: By flexibly manipulating the radio propagation environment, reconfigurable intelligent surface (RIS) is a promising technique for future wireless communications. However, the single-side coverage and double-fading attenuation faced by conventional RISs largely restrict their applications. To…
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Keywords:
networks via;
multi functional;
surface;
noma networks ... See more keywords
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Published in 2018 at "IEEE Control Systems Letters"
DOI: 10.1109/lcsys.2018.2821240
Abstract: Controllability is one of the most important properties of a Boolean control network (BCN). Essentially there are two kinds of controls: 1) networked inputs and 2) free logical inputs. This letter considers controllability of BCNs…
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Keywords:
via mixed;
networks via;
mixed controls;
boolean networks ... See more keywords
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Published in 2022 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2022.3165618
Abstract: Deep graph networks (DGNs) are a family of machine learning models for structured data which are finding heavy application in life sciences (drug repurposing, molecular property predictions) and on social network data (recommendation systems). The…
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Keywords:
deep graph;
via input;
networks via;
explaining deep ... See more keywords
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Published in 2024 at "Applied Sciences"
DOI: 10.3390/app14177962
Abstract: We consider authenticating multicast messages in the case of extremely narrow communication channels, such as underwater acoustic communication, with devices such as mobile sensors creating a self-organizing autonomous network. Channel characteristics in this scenario prevent…
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Keywords:
tiny networks;
via extremely;
multicast;
networks via ... See more keywords