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Machine learning for predicting the outcome of terminal ballistics events

Defence Technology（防务技术） 2024年第1期31卷 14-26页

作者： Shannon Ryan Neeraj Mohan Sushma Arun Kumar AV Julian Berk Tahrima Hashem Santu Rana Svetha Venkatesh Applied Artificial intelligence Institute(A2I2) Deakin University75 Pigdons RdWaurn PondsVIC3216Australia

Machine learning(ML) is well suited for the prediction of high-complexity,high-dimensional problems such as those encountered in terminal *** evaluate the performance of four popular ML-based regression models,extreme gradient boosting(XGBoost),artificial neural network(ANN),support vector regression(SVR),and Gaussian process regression(GP),on two common terminal ballistics’ problems:(a)predicting the V50ballistic limit of monolithic metallic armour impacted by small and medium calibre projectiles and fragments,and(b) predicting the depth to which a projectile will penetrate a target of semi-infinite *** achieve this we utilise two datasets,each consisting of approximately 1000samples,collated from public release *** demonstrate that all four model types provide similarly excellent agreement when interpolating within the training data and diverge when extrapolating outside this *** extrapolation is not advisable for ML-based regression models,for applications such as lethality/survivability analysis,such capability is *** circumvent this,we implement expert knowledge and physics-based models via enforced monotonicity,as a Gaussian prior mean,and through a modified loss *** physics-informed models demonstrate improved performance over both classical physics-based models and the basic ML regression models,providing an ability to accurately fit experimental data when it is available and then revert to the physics-based model when *** resulting models demonstrate high levels of predictive accuracy over a very wide range of projectile types,target materials and thicknesses,and impact conditions significantly more diverse than that achievable from any existing analytical *** with numerical analysis tools such as finite element solvers the ML models run orders of magnitude *** provide some general guidelines throughout for the development,application,and reporting of ML models in terminal ballist

关键词： Machine learning Artificial intelligence Physics-informed machine learning Terminal ballistics Armour

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通智测试——基于动态具身物理社会交互环境的通用人工智能测试

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Engineering 2024年第3期34卷 12-22页

作者： Yujia Peng Jiaheng Han Zhenliang Zhang Lifeng Fan Tengyu Liu Siyuan Qi Xue Feng Yuxi Ma Yizhou Wang Song-Chun Zhu National Key Laboratory of General Artificial intelligence Beijing Institute for General Artificial IntelligenceBeijing 100086China Institute for Artificial intelligence Peking UniversityBeijing 100871China Beijing Key Laboratory of Behavior and Mental Health School of Psychological and Cognitive SciencesPeking UniversityBeijing 100871China School of intelligence Science and Technology Peking UniversityBeijing 100871China School of Computer Science Peking UniversityBeijing 100871China

The release of the generative pre-trained transformer(GPT)series has brought artificial general intelligence(AGI)to the forefront of the artificial intelligence(AI)field once ***,the questions of how to define and evaluate AGI remain *** perspective article proposes that the evaluation of AGI should be rooted in dynamic embodied physical and social interactions(DEPSI).More specifically,we propose five critical characteristics to be considered as AGI benchmarks and suggest the Tong test as an AGI evaluation *** Tong test describes a value-and ability-oriented testing system that delineates five levels of AGI milestones through a virtual environment with DEPSI,allowing for infinite task *** contrast the Tong test with classical AI testing systems in terms of various aspects and propose a systematic evaluation system to promote standardized,quantitative,and objective benchmarks and evaluation of AGI.

关键词： Artificial general intelligence Artificial intelligence benchmark Artificial intelligence evaluation Embodied artificial intelligence Value alignment Turing test Causality

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Multi-step state-based opacity for unambiguous weighted machines

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Science China(Information Sciences) 2024年

作者： Zhipeng ZHANG Chengyi XIA Guoyuan QI Jun FU School of Artificial intelligence Tiangong University School of Control Science and Engineering Tiangong University State Key Laboratory of Synthetical Automation for Process Industries Northeastern University

Opacity is a central concept in the issue of privacy security and has been studied extensively in fields such as finite automata, probabilistic automata, and stochastic automata. Here, we investigate the problem of validating multi-step opaque properties through unambiguous weighted machines from the perspective of cyber-physical systems. First, the notion of multi-step state-based opacity for unambiguous weighted machines is presented and defined. It includes two variants of delays with a finite K and infinite steps. Subsequently, the weighted state estimate with K (infinite)-step delay is established by abstracting the possible state set that the system could have through these weighted observations. Meanwhile, to keep the observable weighted sequence consistent between the bidirectional observers, the unobserved weights of the reverse weighted machine are assumed to be reserved. Subsequently, the existence conditions are developed, and the corresponding algorithms, termed the weighted bidirectional observer, are generalized to verify these properties. Finally, several numerical examples are illustrated to demonstrate the effectiveness of the proposed method. Taken together, the current approach will be conducive to a deep understanding of the security and privacy of cyber-physical systems.

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Direct synthesis of unnatural amino acids and modifications of peptides via LADA strategy

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Chinese Chemical Letters 2024年第1期35卷 237-242页

作者： Yunqi Liu Junliang Zhou Zhankui Sun Shanghai Frontiers Science Center for Drug Target Identification and Drug Delivery School of Pharmaceutical SciencesShanghai Jiao Tong UniversityShanghai 200240China Shanghai Key Laboratory for Molecular Engineering of Chiral Drugs Pharm-X CenterSchool of Pharmaceutical SciencesShanghai Jiao Tong UniversityShanghai 200240China AI pharma Center Zhangjiang Institute for Advanced StudyShanghai Jiao Tong UniversityShanghai 201203China Shanghai Artificial intelligence Laboratory Shanghai 200232China

Unnatural amino acids(UAAs)have broad applications in pharmaceutical sciences and biological *** synthetic methods for UAAs mainly rely on asymmetric catalysis and often require several *** is a lack of direct and simple *** address this challenge,we designed the LADA(labeling-activation-desulfurization-addition)strategy:selective labeling and activation of cysteine residues,the photocatalytic desulfurization and the subsequent radical addition to *** composed of two steps,it is one-pot synthesis and has advantages such as high functional group tolerance,biocompatible reaction condition,and retained *** highly efficient strategy was successfully applied in the direct synthesis of unnatural amino acids and modifications of peptides with more than 50 examples.

关键词： Unnatural amino acids Peptide modifications Desulfurization Cysteine Radical addition

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Existence of long-range magnetic order in Heisenberg spin nanoribbons with edge modification

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Communications in Theoretical Physics 2024年第7期76卷 134-144页

作者： Da-cheng Ma Ling-yi Cui Chu-xiao Sun Xiao-dan Chi Zheng-Nan XianYu An Du College of Science Northeastern UniversityShenyang 110819China Department of Basic Science Dalian Naval AcademyDalian 116018China Department of Physics College of SciencesShenyang University of Chemical TechnologyShenyang 110142China National Frontiers Science Center for Industrial intelligence and Systems Optimization Northeastern UniversityChina Key Laboratory of Data Analytics and Optimization for Smart Industry(Northeastern University) Ministry of EducationChina

Long-range magnetic order appears on a side decorated Heisenberg spin nanoribbon at nonzero temperature,although no spontaneous magnetization exists in a one-or two-dimensional isotropic Heisenberg model at any nonzero temperature according to the Mermin-Wagner *** use of the spin Green's function method,we calculated the magnetizations of Heisenberg nanoribbons decorated by side spins with single-ion anisotropy and found that the system exhibits a nonzero transition temperature,whether the decorated edge spins of the system link together or separate from each *** the width of the nanoribbon achieves infinite limit,the transition temperatures of the system tend to the same finite constant eventually whether one edge or both edges are decorated by side spins in the *** results reveal that the magnetism of a low-dimensional spin system is different from that of a threedimensional spin *** the single-ion anisotropy of edge spins in a Heisenberg spin nanoribbon can be modulated by an electric field experimentally,various useful long-range magnetic orders of the system can be *** work can provide a detailed theoretical basis for designing and fabricating next-generation low-dimensional magnetic random-access memory.

关键词： Nanoribbon magnetic anisotropy long-range magnetic order Heisenberg model transition temperature

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Exploration on learning molecular docking with deep learning models

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Quantitative Biology 2023年第3期11卷 320-331页

作者： Qin Xie Wei Ma Jianhang Zhang Shiliang Li Xiaobing Deng Youjun Xu Weilin Zhang infinite intelligence pharma Beijing 100083China Shanghai Key Laboratory of New Drug Design State Key Laboratory of Bioreactor EngineeringSchool of PharmacyEast China University of Science and TechnologyShanghai 200237China College of Chemistry and Molecular Engineering Peking UniversityBeijing 100871China

Background:Molecular docking-based virtual screening(VS)aims to choose ligands with potential pharmacological activities from millions or even billions of *** process could significantly cut down the number of compounds that need to be experimentally ***,during the docking calculation,many molecules have low affinity for a particular protein target,which waste a lot of computational ***:We implemented a fast and practical molecular screening approach called DL-DockVS(deep learning dock virtual screening)by using deep learning models(regression and classification models)to learn the outcomes of pipelined docking programs ***:In this study,we showed that this approach could successfully weed out compounds with poor docking scores while keeping compounds with potentially high docking scores against 10 DUD-E protein targets.A self-built dataset of about 1.9 million molecules was used to further verify DL-DockVS,yielding good results in terms of recall rate,active compounds enrichment factor and runtime ***:We comprehensively evaluate the practicality and effectiveness of DL-DockVS against 10 protein *** to the improvements of runtime and maintained success rate,it would be a useful and promising approach to screen ultra-large compound libraries in the age of big *** is also very convenient for researchers to make a well-trained model of one specific target for predicting other chemical libraries and high docking-score molecules without docking computation again.

关键词： molecular docking ultra-large virtual screening deep learning

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Sodium metals for single emitter strong coupling:Alternative plasmonic candidates beyond noble metals

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Science China(Physics,Mechanics & Astronomy) 2024年第8期67卷 106-117页

作者： Yi Zhang Shuying Chen Yuning Han Xiulai Xu Lin Zhou National Laboratory of Solid State Microstructures Collaborative Innovation Center of Advanced MicrostructuresJiangsu Key Laboratory of Artificial Functional MaterialsCollege of Engineering and Applied SciencesNanjing UniversityNanjing 210008China School of Information and Electronic Engineering(Sussex Artificial intelligence Institute) Zhejiang Gongshang UniversityHangzhou 310018China Department of Physics&Astronomy University College LondonLondon WC1E 6BTUK State Key Laboratory for Mesoscopic Physics and Frontiers Science Center for Nano-optoelectronics School of PhysicsPeking UniversityBeijing 100871China

This work provides a theoretical investigation into the strong coupling between a single quantum emitter(QE)and the surface plasmons of sodium metals in two representative plasmonic systems,i.e.,the semi-infinite metal-dielectric interface and the metal nanoparticles(NPs)of monomer/dimer *** both configurations,sodium metals exhibit distinctly stronger coupling strength and lower optical loss in the optical region than their noble metal counterparts,demonstrating the ideal candidate characteristics for single-molecule-level strong couplings with distinctly facile operation *** results provide new insights into extreme light-matter interactions with potential applications in quantum information,optical sensors,quantum chemistry,etc.

关键词： sodium metals plasmonics single quantum emitter strong coupling pseudomode

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基因疗法全球研发进展

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药学进展 2017年第5期41卷 392-397页

作者： BOLITER Natasha Informa pharma intelligence

基因疗法能将基因导入细胞内,用于治疗和预防疾病,被称为医学史上的一大革命。近年来,基因治疗在科研领域取得很多重要进展,多个基因疗法药物已进入临床硏究阶段或已上市,为癌症、罕见病、神经性疾病、心血管疾病等多个领域的疾病治疗... 详细信息

基因疗法能将基因导入细胞内,用于治疗和预防疾病,被称为医学史上的一大革命。近年来,基因治疗在科研领域取得很多重要进展,多个基因疗法药物已进入临床硏究阶段或已上市,为癌症、罕见病、神经性疾病、心血管疾病等多个领域的疾病治疗带来新希望。概述并解析基因疗法药物的全球研发进展,包括总体研发态势、作用靶点、适应证、研发阶段、开发公司及产品管线或临床研究情况等。

关键词：基因疗法上市药物癌症罕见病

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炎症性肠病临床研究多元化发展：突破口在何方？

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药学进展 2017年第3期41卷 230-236页

作者： RUNKEL Laura Informaa pharma intelligence

炎症性肠病（IBD）是一种慢性炎症，影响人类胃肠道健康且容易反复发作。最常见的2种炎症性肠病分别为克罗恩病和溃疡性结肠炎。介绍炎症性肠病治疗药物的研发现状，包括作用机制、试验申办方及产品线临床研究情况等，并对比了制药企业... 详细信息

炎症性肠病（IBD）是一种慢性炎症，影响人类胃肠道健康且容易反复发作。最常见的2种炎症性肠病分别为克罗恩病和溃疡性结肠炎。介绍炎症性肠病治疗药物的研发现状，包括作用机制、试验申办方及产品线临床研究情况等，并对比了制药企业和非商业性研发机构在IBD治疗药物研发策略方面的特点。

关键词：炎症性肠病克罗恩病溃疡性结肠炎临床研究

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在处于平稳期的自身免疫疾病和炎症药物市场中保持领先地位的策略

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药学进展 2017年第4期41卷 313-317页

作者： SPICER Pamela Informa pharma intelligence

受仿制药影响,自身免疫疾病和炎症药物市场波动明显。通过对比正在进行和计划启动的临床试验与已经完成或终止的临床试验,可以了解制药企业在这一领域的进退。对产品管线和研发项目的深入研究可进一步洞悉这一领域的主要制药企业所采用... 详细信息

受仿制药影响,自身免疫疾病和炎症药物市场波动明显。通过对比正在进行和计划启动的临床试验与已经完成或终止的临床试验,可以了解制药企业在这一领域的进退。对产品管线和研发项目的深入研究可进一步洞悉这一领域的主要制药企业所采用的战略措施。来自Trialtrove的报告深入分析临床研究动向、战略措施以及自身免疫疾病和炎症药物领域的制药公司如何应对多变的研发计划。

关键词：自身免疫疾病炎症临床试验

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