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Polyelectrolyte nanoparticles derived from durian seed gum modified with chitosan for selective targeting in cancer cells

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International Journal of Biological Macromolecules 2025年 315卷 144625页

作者： Putro, Jindrayani Nyoo Bintang Ilhami, Fasih Cheng, Chih-Chia Imanuela, Keziah Janice Mangindaan, Dave Irawaty, Wenny Rahmawati, Astrid Shimomura, Osamu Ismadji, Suryadi Chemical Engineering Master Program Faculty of Engineering Widya Mandala Surabaya Catholic University Kalijudan 37 Surabaya60114 Indonesia Collaborative Research Center for Sustainable and Zero Waste Industries Jl. Kalijudan 37 East Java Surabaya60114 Indonesia Department of Natural Science Faculty of Mathematics and Natural Science Universitas Negeri Surabaya Surabaya60231 Indonesia Graduate Institute of Applied Science and Technology National Taiwan University of Science and Technology Taipei10607 Taiwan Department of Chemical Engineering Widya Mandala Surabaya Catholic University Kalijudan 37 Surabaya60114 Indonesia Professional Engineer Program Department Faculty of Engineering Bina Nusantara University K.H. Syahdan No. 9 Jakarta11480 Indonesia Waste-Food-Environmental Nexus Research Interest Group Bina Nusantara University K.H. Syahdan No. 9 Jakarta11480 Indonesia Department of Applied Chemistry Osaka Institute of Technology 5-16-1 Omiya Ashahi-ku Osaka535-8585 Japan

The synthesis of natural polysaccharides from durian seed gum-modified chitosan as complex nanoparticles was successfully developed. The complex formation of nanoparticles was confirmed by 1H NMR, indicating the interpenetrating polymer network between the durian seed gum and chitosan. The material's physical properties were analyzed using ZETA potential, SEM, FTIR, swelling assay, and spectrofluorometer. The material showed a pH-responsive behavior as evidenced by the swelling assay, in which the complex nanoparticle has a smaller swelling index in pH 5.5 and 7.4 than pH 2.1. The stability of the material was tested by checking the hydrodynamic diameter, which resulted in the modification of chitosan having higher kinetic stability than the durian seed gum under a diameter smaller than 1 μm. The chitosan-modified durian seed gum's hemolytic activity indicates blood compatibility with 4 % hemolytic activity under high nanoparticle concentration (400 μg/mL). More importantly, the cytotoxicity test of complex nanoparticles showed biocompatibility with NIH/3 T3 cells, whereas complex nanoparticles exhibited high toxicity towards HeLa cells. Moreover, complex nanoparticles showed strong intracellular blue fluorescence with selective activity towards cancer cells. Hence, this newly developed green synthesis of polyelectrolyte nanoparticles derived from durian seed gum modified with chitosan improved selectivity and intracellular fluorescence in tracking cancer cells. © 2025 Elsevier B.V.

关键词： Chitosan

Utilizing probabilistic entanglement between sensors in quantum networks

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arXiv 2024年

作者： Van Milligen, Emily A. Gagatsos, Christos N. Kaur, Eneet Towsley, Don Guha, Saikat Department of Physics The University of Arizona 1630 East University Boulevard TucsonAZ85721 United States Department of Electrical and Computer Engineering The University of Arizona 1630 East University Boulevard TucsonAZ85721 United States Wyant College of Optical Sciences The University of Arizona 1630 East University Boulevard TucsonAZ85721 United States Program in Applied Mathematics The University of Arizona TucsonAZ85721 United States Cisco Quantum Lab Los Angeles United States College of Computer Science University of Massachusetts AmherstMA United States

One of the most promising applications of quantum networks is entanglement assisted sensing. The field of quantum metrology exploits quantum correlations to improve the precision bound for applications such as precision timekeeping, field sensing, and biological imaging. When measuring multiple spatially distributed parameters, current literature focuses on quantum entanglement in the discrete variable case—and quantum squeezing in the continuous variable case distributed amongst all of the sensors in a given network. However, it can be difficult to ensure all sensors pre-share entanglement of sufficiently high fidelity. This work probes the space between fully entangled and fully classical sensing networks by modeling a star network with probabilistic entanglement generation that is attempting to estimate the average of local parameters. The quantum Fisher information is used to determine which protocols best utilize entanglement as a resource for different network conditions. It is shown that without entanglement distillation there is a threshold fidelity below which classical sensing is preferable. For a network with a given number of sensors and links characterized by a certain initial fidelity and probability of success, this work outlines when and how to use entanglement, when to store it, and when it needs to be distilled. © 2024, CC BY.

关键词： Quantum entanglement

Structural Properties of Hyperuniform Networks

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arXiv 2024年

作者： Newby, Eli Shi, Wenlong Jiao, Yang Albert, Reka Torquato, Salvatore Department of Physics Pennsylvania State University University ParkPA16802 United States Materials Science and Engineering Arizona State University TempeAZ85287 United States Department of Physics Arizona State University TempeAZ85287 United States Department of Chemistry Princeton University PrincetonNJ08544 United States Department of Physics Princeton University PrincetonNJ08544 United States Princeton Institute of Materials Princeton University PrincetonNJ08544 United States Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States

Disordered hyperuniform many-particle systems are recently discovered exotic states of matter, characterized by a complete suppression of normalized infinite-wavelength density fluctuations, as in perfect crystals, and lack of conventional long-range order, as in liquids and glasses. In this work, we begin a program to quantify the structural properties of nonhyperuniform and hyperuniform networks. In particular, large two-dimensional (2D) Voronoi networks (graphs) containing approximately 10,000 nodes are created from a variety of different point configurations, including the antihyperuniform hyperplane intersection process (HIP), nonhyperuniform Poisson process, nonhyperuniform random sequential addition (RSA) saturated packing, and both non-stealthy and stealthy hyperuniform point processes. We carry out an extensive study of the Voronoi-cell area distribution of each of the networks through determining multiple metrics that characterize the distribution, including their higher-cumulants (i.e., skewness 1 and excess kurtosis 2). We show that the HIP distribution is far from Gaussian, as evidenced by a high skewness (γ1 = 3.16) and large positive excess kurtosis (γ2 = 16.2). The Poisson (with γ1 = 1.07 and γ2 = 1.79) and non-stealthy hyperuniform (with γ1 = 0.257 and γ2 = 0.0217) distributions are Gaussian-like distributions, since they exhibit a small but positive skewness and excess kurtosis. The RSA (with γ1 = 0.450 and γ2 = -0.0384) and the highest stealthy hyperuniform distributions (with γ1 = 0.0272 and γ2 = -0.0626) are also non-Gaussian because of their low skewness and negative excess kurtosis, which is diametrically opposite non-Gaussian behavior of the HIP. The fact that the cell-area distributions of large, finite-sized RSA and stealthy hyperuniform networks (e.g., with N ≈ 10, 000 nodes) are narrower, have larger peaks, and smaller tails than a Gaussian distribution implies that in the thermodynamic limit the distributions should exhibit compact suppo

关键词： Gaussian distribution

Constraining f(R) models with cosmic chronometers and the HII galaxy Hubble diagram

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arXiv 2022年

作者： Sultana, Joseph Yennapureddy, Manoj K. Melia, Fulvio Kazanas, Demosthenes Department of Mathematics Faculty of Science University of Malta MSD Msida2080 Malta Department of Physics The University of Arizona TucsonAZ85721 United States Department of Physics The Applied Math Program Department of Astronomy The University of Arizona TucsonAZ85721 United States Astrophysics Science Division NASA/Goddard Space Flight Center GreenbeltMD20771 United States

We consider several well-known f(R) cosmological models and constrain their parameters, namely the deviation parameter b and the cosmological parameters Ωm and h. We first obtain analytical approximations for the Hubble rate H(z) and the luminosity distance dL(z) in terms of these parameters, and then test these against the observational expansion rate derived from cosmic chronometers and the distance modulus in the HII galaxy Hubble diagram, obtained in a model-independent way using Gaussian Processes (GP). We first optimize the models based solely on the cosmic chronometers and then repeat this process with a joint analysis using both the cosmic chronometers and HII galaxies. Copyright © 2022, The Authors. All rights reserved.

关键词： Chronometers

Drone-borne calibration pulser for radio observatories detecting ultra-high-energy cosmic rays and neutrinos 38

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Drone-borne calibration pulser for radio observatories detec...

38th International Cosmic Ray Conference, ICRC 2023

作者： Nam, J. Kuo, C.-Y. Shin, B.K. Chen, P. Chen, Y. Hsu, S.-Y. Huang, J.-J. Huang, M.-H.A. Leung, C.H. Liu, T.-C. Wang, S.-H. Wang, M.-Z. Wang, Y.-H. Besson, D. Novikov, A. Hornhuber, C. Young, R. Department of Physics National Taiwan University Taipei Taiwan Leung Center for Cosmology and Particle Astrophysics National Taiwan University Taipei Taiwan Ulsan National Institute of Science and Technology Ulsan Korea Republic of Department of Energy and Resources National United University Miaoli Taiwan Department of Electrophysics National Yang Ming Chiao Tung University Hsinchu300 Taiwan Department of applied physics National PingTung university PingTung900 Taiwan Chung Cheng Institute of Technology National Defense University TaoYuan335 Taiwan Undergraduate Degree Program of Systems Engineering and Technology National Yang Ming Chiao Tung University Hsinchu300 Taiwan Department of Physics and Astronomy University of Kansas Lawrence United States Instrumentation Design Lab University of Kansas Lawrence United States Moscow Russia Institute of Astronomy and Astrophysics Academia Sinica Astronomy-Mathematics Building No. 1 Sec. 4 Roosevelt Rd. Taipei Taiwan

We report on the development of a drone-borne calibration pulser (cal-pulser) for radio observatories detecting ultra-high energy (UHE) cosmic rays and neutrinos. This system allows us to calibrate the radio detector in its field of view regardless of the accessibility of the site. The system is compact and sufficiently lightweight to be attached to a commercial drone. It consists of a solid-state high-power pulse generator, a programmable attenuator, a transmitting antenna, and a differential GPS (D-GPS) module. The drone, with the ∼1.3 kg payload, has a typical flight time of around 25 minutes, corresponding to a maximum flight distance of around 10 km. After developing the first version of the system in 2019, it successfully demonstrated its calibration performance with the TAROGE stations in Taiwan and the TAROGE-M station in Mt. Melbourne, Antarctica. In 2022, the system was upgraded with a dual-band D-GPS for more reliable operation and more accurate determination of the coordinates of the cal-pulser. In addition to the cal-pulser, we investigated aerial photogrammetry using the built-in camera and the D-GPS, which is an efficient method to determine the coordinates of the detector. For objects within 10 m of the drone, an accuracy of a few millimeter was achieved. These drone-borne cal-pulser and the photogrammetry have become essential calibration procedures in the TAROGE-M experiment. We suggest these approaches may find application in many other radio experiments that detect UHE cosmic rays and neutrinos, such as ARIANNA, BEACON, GRAND, as well as IceCube-Gen2. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Cosmic rays

Ultradense Sphere Packings Derived From Disordered Stealthy Hyperuniform Ground States

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arXiv 2025年

作者： Kim, Jaeuk Torquato, Salvatore Princeton Materials Institute Department of Physics Department of Chemistry Princeton University PrincetonNJ08544 United States Department of Chemistry Department of Physics Princeton Materials Institute Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States

Disordered stealthy hyperuniform (SHU) packings are an emerging class of exotic amorphous two-phase materials endowed with novel optical, transport, and mechanical properties. Such packings of identical spheres have been created from SHU ground-state point patterns via a modified collective-coordinate optimization scheme that includes a soft-core repulsion, besides the standard "stealthy" pair potential. To explore maximal ranges of the packing fraction , we investigate the distributions of minimum pair distances as well as nearest-neighbor distances of ensembles of SHU point patterns without and with soft-core repulsions in the first three space dimensions as a function of the stealthiness parameter χ and number of particles N within a hypercubic simulation box under periodic boundary conditions. Within the disordered regime (χ max(χ, d), decrease to zero on average as N increases if there are no soft-core repulsions. By contrast, the inclusion of soft-core repulsions results in very large max(χ, d) independent of N, reaching up to max(χ, d) = 1.0, 0.86, 0.63 in the zero-χ limit and decreasing to max(χ, d) = 1.0, 0.67, 0.47 at χ = 0.45 for d = 1, 2, 3, respectively. We obtain explicit formulas for max(χ, d) as functions of χ and N for a given value of d in both cases with and without soft-core repulsions. In two and three dimensions, our soft-core SHU ground-state packings for small χ become configurationally very close to the corresponding jammed hard-particle packings created by fast compression algorithms, as measured by their pair statistics. As χ increases beyond 0.20, the packings form fewer contacts and linear polymer-like chains as χ tends to 1/2. The resulting structure factors S(k) and pair correlation functions g2(r) reveal that soft-core repulsions significantly alter the short- and intermediate-range correlations in the SHU ground states. We show that the degree of large-scale order of the soft-core SHU ground states increases as χ increases from 0 to

关键词： Digital arithmetic

Variational methods and deep Ritz method for active elastic solids

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arXiv 2022年

作者： Wang, Haiqin Zou, Boyi Su, Jian Wang, Dong Xu, Xinpeng Physics Program Guangdong Technion - Israel Institute of Technology 241 Daxue Road Guangdong Shantou515063 China Technion - Israel Institute of Technology Haifa32000 Israel School of Science and Engineering The Chinese University of Hong Kong Guangdong Shenzhen518172 China Shenzhen International Center for Industrial and Applied Mathematics Shenzhen Research Institute of Big Data Guangdong Shenzhen518172 China

Variational methods have been widely used in soft matter physics for both static and dynamic problems. These methods are mostly based on two variational principles: the variational principle of minimum free energy (MFEVP) and Onsager's variational principle (OVP). Our interests lie in the applications of these variational methods to active matter physics. In our former work [Soft Matter, 2021, 17, 3634], we have explored the applications of OVP-based variational methods for the modeling of active matter dynamics. In the present work, we explore variational (or energy) methods that are based on MFEVP for static problems in active elastic solids. We show that MFEVP can be used not only to derive equilibrium equations, but also to develop approximate solution methods, such as Ritz method, for active solid statics. Moreover, the power of Ritz-type method can be further enhanced using deep learning methods if we use deep neural networks to construct the trial functions of the variational problems. We then apply these variational methods and the deep Ritz method to study the spontaneous bending and contraction of a thin active circular plate that is induced by internal asymmetric active contraction. The circular plate is found to be bent towards its contracting side. The study of such a simple toy system gives implications for understanding the morphogenesis of solid-like confluent cell monolayers. In addition, we introduce a so-called activogravity length to characterize the importance of gravitational forces relative to internal active contraction in driving the bending of the active plate. When the lateral plate dimension is larger than the activogravity length (about 100 micron), gravitational forces become important. Such gravitaxis behaviors at multicellular scales may play significant roles in the morphogenesis and in the up-down symmetry broken during tissue development. © 2022, CC BY-NC-ND.

关键词： Deep neural networks

Enhanced Gaussian Process Regression for Diagnosing Wind Energy Conversion Systems

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IFAC-PapersOnLine 2022年第6期55卷 673-678页

作者： Majdi Mansouri Radhia Fezai Mohamed Trabelsi Hajji Mansour Hazem Nounou Mohamed Nounou Department of Mathematics and Sciences Prince Sultan University Riyadh 11586 Saudi Arabia Research Laboratory of Automation Signal Processing and Image National Engineering School of Monastir 5019 Tunisia Electronic and Communications Engineering Department Kuwait College of Science and Technology P. O. Box 27235 Kuwait Higher Institute of Applied Sciences and Technology of Kasserine Kairouan University Tunisia Chemical Engineering Program Texas A&M University at Qatar Doha Qatar

Fault detection and diagnosis techniques are increasingly important to ensure robust and resource efficient operation of Wind Energy Conversion (WEC) systems. In this context, this paper presents a Reduced Enhanced Gaussian Process Regression (REGPR)-based Random Forest (RF) technique (REGPR-RF) to identify and diagnose faults occurring in a nonlinear WEC systems. The proposed technique uses REGPR technique for features extraction and selection from raw sensor data. Then, these selected features are fed to RF classifier to reliably detect and classify faults. The use of REGPR to learn features avoid the dimension problems and improves the classification performance significantly with a small number of training data. The results obtained by REGPR-RF are compared to those obtained with other conventional classifiers (Support Vector Machines (SVM), Naive Bayes (NB), ...). The results show that the developed REGPR-RF technique achieve higher accuracy (99.99%) with small data sets.

关键词： Gaussian Process Regression (GPR) Noise-Signal-Dependence Random Forest (RF) Feature Extraction Selection Fault Detection Diagnosis (FDD) Wind Energy Conversion (WEC) Systems

Convergence analysis of machine learning algorithms for the numerical solution of mean field control and games: I the Ergodic case.

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arXiv 2019年

作者： Carmona, René Laurière, Mathieu Program in Applied and Computational Mathematics and Orfe

We propose two algorithms for the solution of the optimal control of ergodic McKean-Vlasov dynamics. Both algorithms are based on approximations of the theoretical solutions by neural networks, the latter being characterized by their architecture and a set of parameters. This allows the use of modern machine learning tools, and efficient implementations of stochastic gradient *** first algorithm is based on the idiosyncrasies of the ergodic optimal control problem. We provide a mathematical proof of the convergence of the approximation scheme, and we analyze rigorously the approximation by controlling the different sources of error. The second method is an adaptation of the deep Galerkin method to the system of partial differential equations issued from the optimality condition. We demonstrate the efficiency of these algorithms on several numerical examples, some of them being chosen to show that our algorithms succeed where existing ones failed. We also argue that both methods can easily be applied to problems in dimensions larger than what can be found in the existing literature. Finally, we illustrate the fact that, although the first algorithm is specifically designed for mean field control problems, the second one is more general and can also be applied to the partial differential equation systems arising in the theory of mean field games. Copyright © 2019, The Authors. All rights reserved.

关键词： Machine learning