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Effects of wild mango (Spondias pinnata) on quality of salted duck eggs

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AIP Conference Proceedings 2024年第1期3027卷

作者： Muliadi Ramli Rustam Effendi Lia Amalia Nasrullah Idris Saiful Muhammad Rizal Rara Mitaphonna Sarah Aprilia Ulfia Rahmatillah Minati Maisarah Department of Chemistry Universitas Syiah Kuala Faculty of Mathematics and Natural Sciences 23111 Banda AcehAceh Indonesia Department of Physics Universitas Syiah Kuala Faculty of Mathematics and Natural Sciences 23111 Banda Aceh Aceh Indonesia Doctoral Program of Mathematics and Applied Sciences Universitas Syiah Kuala 23111 Banda Aceh Aceh Indonesia

The salted egg has been popular as a rural economic product which are mostly prepared by housewives in Aceh Besar regency. In order to support the rural economic activity, this experiment was designed and focused on utilization of the local fruits, namely wild mango (Spondias pinnata), which is recognized locally as “Kedondong hutan” to preserve quality of the salted egg. This biomass was employed as a green material on salting process of duck eggs. Initially, the pH level of “kedondong hutan” in liquid phase was determined by chemical method and a pH value of around 4.2 was obtained. While a phytochemical analysis of wild mango fruits revealed that it contains terpenoids, phenolic acids, saponins, alkaloids, flavonoids, and phenolic compounds. The oil exudation (OE) content in the salted eggs products was examined using a gravimetric method, and it was found that OE level of the salted eggs produced in Aceh Besar was around 19.83 %. Finally, this research demonstrated that “Kedondong hutan” fruit have a positive impact on preventing microbial growth in the salted duck egg product, thus useful for preserving its quality.

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Biases in inverse Ising estimates of near-critical behavior

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Physical Review E 2023年第1期108卷 014109-014109页

作者： Maximilian B. Kloucek Thomas Machon Shogo Kajimura C. Patrick Royall Naoki Masuda Francesco Turci School of Physics HH Wills Physics Laboratory University of Bristol Tyndall Avenue Bristol BS8 1TL United Kingdom Bristol Centre for Functional Nanomaterials HH Wills Physics Laboratory University of Bristol Tyndall Avenue Bristol BS8 1TL United Kingdom Faculty of Information and Human Sciences Kyoto Institute of Technology Kyoto 606-8585 Japan Gulliver UMR CNRS 7083 ESPCI Paris Université PSL 75005 Paris France Department of Mathematics State University of New York at Buffalo Buffalo New York 14260-2900 USA Computational and Data-Enabled Science and Engineering Program State University of New York at Buffalo Buffalo New York 14260-5030 USA

Inverse Ising inference allows pairwise interactions of complex binary systems to be reconstructed from empirical correlations. Typical estimators used for this inference, such as pseudo-likelihood maximization (PLM), are biased. Using the Sherrington-Kirkpatrick model as a benchmark, we show that these biases are large in critical regimes close to phase boundaries, and they may alter the qualitative interpretation of the inferred model. In particular, we show that the small-sample bias causes models inferred through PLM to appear closer to criticality than one would expect from the data. Data-driven methods to correct this bias are explored and applied to a functional magnetic resonance imaging data set from neuroscience. Our results indicate that additional care should be taken when attributing criticality to real-world data sets.

关键词： Critical phenomena Cortical networks Spin glasses Functional magnetic resonance imaging Ising model

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

Biomedical data and AI

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Science China Life Sciences 2025年第5期68卷 1536-1540页

作者： Hao Xu Shibo Zhou Zefeng Zhu Vincenzo Vitelli Liangyi Chen Ziwei Dai Ning Yang Luhua Lai Shengyong Yang Sergey Ovchinnikov Zhuoran Qiao Sirui Liu Chen Song Jianfeng Pei Han Wen Jianfeng Feng Yaoyao Zhang Zhengwei Xie Yang-Yu Liu Zhiyuan Li Fulai Jin Hao Li Mohammad Lotfollahi Xuegong Zhang Ge Yang Shihua Zhang Ge Gao Pulin Li Qi Liu Jing-Dong Jackie Han Peking-Tsinghua Center for Life Sciences (CLS) Academy for Advanced Interdisciplinary StudiesPeking University Center for Quantitative Biology (CQB) Academy for Advanced Interdisciplinary StudiesPeking University Peking University-Tsinghua University-National Institute of Biological Sciences Joint Graduate Program Academy for Advanced Interdisciplinary StudiesPeking University Department of Physics University of Chicago School of Life Sciences Southern University of Science and Technology Peking University Chengdu Academy for Advanced Interdisciplinary Biotechnologies College of Chemistry and Molecular Engineering Peking University Department of Biotherapy Cancer Center and State Key Laboratory of BiotherapyWest China HospitalSichuan University Department of Biology Massachusetts Institute of Technology Lambic Therapeutics Inc. Changping Laboratory Al for Science Institute Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence Fudan University Department of Obstetrics and Gynecology West China Second University HospitalSichuan University Peking University International Cancer Institute and Peking University-Yunnan Baiyao International Medical Institute and State Key Laboratory of Natural and Biomimetic Drugs Department of Molecular and Cellular PharmacologySchool of Pharmaceutical SciencesPeking University Health Science CenterPeking University Channing Division of Network Medicine Department of MedicineBrigham and Women's Hospital and Harvard Medical School Center for Artificial Intelligence and Modeling the Carl R.Woese Institute for Genomic BiologyUniversity of Illinois Urbana-Champaign Department of Genetics and Genome Sciences School of Medicine and Department of Computer and Data Sciences and Department of Population and Quantitative Health SciencesCase Western Reserve University Department of Biochemistry and Biophysics University of California Sanger Institute Department of Automation Tsinghua University State Key Laboratory of Multimodal Artificial Intelligence Systems I

The development of artificial intelligence(AI) and the mining of biomedical data complement each other. From the direct use of computer vision results to analyze medical images for disease screening, to now integrating biological knowledge into models and even accelerating the development of new AI based on biological discoveries, the boundaries of both are constantly expanding, and their connections are becoming closer.

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Casimir preserving stochastic Lie-Poisson integrators

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arXiv 2021年

作者： Luesink, Erwin Ephrati, Sagy Cifani, Paolo Geurts, Bernard Multiscale Modelling and Simulation Department of Applied Mathematics Faculty EEMCS University of Twente PO Box 217 Enschede7500 AE Netherlands Gran Sasso Science Institute Viale F. Crispi 7 L’Aquila67100 Italy Multiscale Physics Center for Computational Energy Research Department of Applied Physics Eindhoven University of Technology PO Box 513 Eindhoven5600 MB Netherlands

Casimir preserving integrators for stochastic Lie-Poisson equations with Stratonovich noise are developed extending Runge-Kutta Munthe-Kaas methods. The underlying Lie-Poisson structure is preserved along stochastic trajectories. A related stochastic differential equation on the Lie algebra is derived. The solution of this differential equation updates the evolution of the Lie-Poisson dynamics by means of the exponential map. The constructed numerical method conserves Casimir-invariants exactly, which is important for long time integration. This is illustrated numerically for the case of the stochastic heavy top and the stochastic sine-Euler equations. Copyright © 2021, The Authors. All rights reserved.

关键词： Integration

Multiorbital impact on strong-field ionization of HCl molecules

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Physical Review A 2021年第4期104卷 043110-043110页

作者： Shilin Hu Zheng Shu Li Guo Jing Chen Guangdong Provincial Key Laboratory of Quantum Metrology and Sensing and School of Physics and Astronomy Sun Yat-Sen University (Zhuhai Campus) Zhuhai 519082 China Institute of Applied Physics and Computational Mathematics P. O. Box 8090 Beijing 100088 China Department of Physics Shanghai Normal University Shanghai 200234 China Shenzhen Key Laboratory of Ultraintense Laser and Advanced Material Technology Center for Advanced Material Diagnostic Technology and College of Engineering Physics Shenzhen Technology University Shenzhen 518118 China

We have put forward the time-dependent Hartree-Fock approach to investigate ionization dynamics of HCl molecules subjected to strong few-cycle laser pulses, which is based on the finite-element discrete-variable representation in prolate spheroidal coordinates and the Crank-Nicolson method. It is demonstrated that the electron is favored to be freed by the peak electric field pointing towards the H atom for the HCl molecule possessing the bonding length R=2.5 a.u., while the ionization prefers to occur for the maximum electric field pointing from the H nucleus to Cl nucleus with increasing internuclear separations. Analysis indicates that the ionization yield of 5σ electrons becomes significant with respect to that of 2π electrons with stretching bonding lengths, and the relative contributions of the ionization from 5σ and 2π electrons change as a function of internuclear separations, which gives rise to the above distinct oriented ionization of HCl molecules.

关键词： Atomic & molecular processes in external fields Multiphoton or tunneling ionization & excitation Hartree-Fock methods

Towards a mathematical understanding of neural network-based machine learning: What we know and what we don't

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arXiv 2020年

作者： Weinan, E. Ma, Chao Wojtowytsch, Stephan Wu, Lei Department of Mathematics Princeton University United States Program in Applied and Computational Mathematics Princeton University United States Department of Mathematics Stanford University United States Beijing Institute of Big Data Research China

Publisher's Note: “Reacting and non-reacting, three-dimensional shear layers with spanwise stretching” [Phys. Fluids 34, 123602 (2022)]

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physics of Fluids 2023年第1期35卷

作者： Jonathan L. Palafoutas William A. Sirignano 1Program in Applied and Computational Mathematics Princeton University Princeton New Jersey 08540 USA 2Department of Mechanical and Aerospace Engineering University of California Irvine Irvine California 92697 USA

This article was published online on 2 December 2022 with errors throughout the paper. All the derivative terms had the wrong denominator; the denominators were

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Tuning cooperative behavior in games with nonlinear opinion dynamics

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arXiv 2021年

作者： Park, Shinkyu Bizyaeva, Anastasia Kawakatsu, Mari Franci, Alessio Leonard, Naomi Ehrich Computer Electrical and Mathematical Science and Engineering Division Thuwal23955-6900 Saudi Arabia Department of Mechanical and Aerospace Engineering Princeton University PrincetonNJ08544 United States Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States Mathematics Department National Autonomous University of Mexico Mexico City04510 Mexico

We examine the tuning of cooperative behavior in repeated multi-agent games using an analytically tractable, continuous-time, nonlinear model of opinion dynamics. Each modeled agent updates its real-valued opinion about each available strategy in response to payoffs and other agent opinions, as observed over a network. We show how the model provides a principled and systematic means to investigate behavior of agents that select strategies using rationality and reciprocity, key features of human decision-making in social dilemmas. For two-strategy games, we use bifurcation analysis to prove conditions for the bistability of two equilibria and conditions for the first (second) equilibrium to reflect all agents favoring the first (second) strategy. We prove how model parameters, e.g., level of attention to opinions of others (reciprocity), network structure, and payoffs, influence dynamics and, notably, the size of the region of attraction to each stable equilibrium. We provide insights by examining the tuning of the bistability of mutual cooperation and mutual defection and their regions of attraction for the repeated prisoner's dilemma and the repeated multi-agent public goods game. Our results generalize to games with more strategies, heterogeneity, and additional feedback dynamics, such as those designed to elicit cooperation. Copyright © 2021, The Authors. All rights reserved.

关键词： Bifurcation (mathematics)