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IDSSCNN-xgBoost:Improved Dual-Stream Shallow Convolutional Neural Network Based on Extreme Gradient Boosting Algorithm for Micro Expression Recognition

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Computers, Materials & Continua 2025年第1期82卷 729-749页

作者： Adnan Ahmad zhao Li Irfan Tariq Zhengran He School of Information Science and Engineering Southeast UniversityNanjing210016China

Micro-expressions(ME)recognition is a complex task that requires advanced techniques to extract informative features fromfacial *** deep neural networks(DNNs)with convolutional structures have been ***,unlike DNNs,shallow convolutional neural networks often outperform deeper models in mitigating overfitting,particularly with small ***,many of these methods rely on a single feature for recognition,resulting in an insufficient ability to extract highly effective *** address this limitation,in this paper,an Improved Dual-stream Shallow Convolutional Neural Network based on an Extreme Gradient Boosting Algorithm(IDSSCNN-xgBoost)is introduced for ME *** proposed method utilizes a dual-stream architecture where motion vectors(temporal features)are extracted using Optical flow TV-L1 and amplify subtle changes(spatial features)via EulerianVideoMagnification(EVM).These features are processed by IDSSCNN,with an attention mechanism applied to refine the extracted effective *** outputs are then fused,concatenated,and classified using the xgBoost *** comprehensive approach significantly improves recognition accuracy by leveraging the strengths of both temporal and spatial information,supported by the robust classification power of *** proposed method is evaluated on three publicly available ME databases named Chinese Academy of Sciences Micro-expression Database(CASMEII),Spontaneous Micro-Expression Database(SMICHS),and Spontaneous Actions and Micro-Movements(SAMM).Experimental results indicate that the proposed model can achieve outstanding results compared to recent *** accuracy results are 79.01%,69.22%,and 68.99%on CASMEII,SMIC-HS,and SAMM,and the f1-score are 75.47%,68.91%,and 63.84%,*** proposed method has the advantage of operational efficiency and less computational time.

关键词： ME recognition dual stream shallow convolutional neural network euler video magnification TV-L1 xgBoost

Exit options sustain altruistic punishment and decrease the second-order free-riders, but it is not a panacea

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Science China(Information Sciences) 2025年第1期68卷 278-291页

作者： Chen SHEN zhao SONG Lei SHI Jun TANIMOTO Zhen WANG faculty of Engineering Sciences Kyushu University School of Statistics and Mathematics Yunnan University of Finance and Economics School of Computing Engineering and Digital Technologies Teesside University School of Artificial Intelligence OPtics and Electro Nics (iOPEN) Northwestern Polytechnical University

Why do humans punish free riders at their own expense? This behavior represents an evolutionary puzzle in human societies. This study explores the role of exit strategies in fostering altruistic punishment within evolutionary game theory. We extend the traditional prisoner's dilemma model by incorporating exiters, players who opt out for a small payoff while nullifying their opponent's payoff, and altruistic punishers who cooperate and punish non-cooperators. Our findings indicate that in well-mixed populations, exiters destabilize defection but do not promote altruistic punishment. In social networks, however,exiters enable altruistic punishment via cyclic dominance among altruistic punishers, defectors, and exiters. Notably, this cyclic dominance is sensitive to exit payoffs; adjustments can lead to cyclic dominance of non-punishing cooperators, defectors, and exiters, or to a bi-stable state between these two types of cyclic dominance. These results highlight the nuanced impact of exiters on altruistic punishment, emphasizing the need for careful incentivization of exit behavior. While exiters can support altruistic punishment in networked populations, their effectiveness is not a panacea and is highly sensitive to exit payoffs, indicating limits to the voluntary participation mechanism.

关键词： evolutionary game theory altruistic punishment coexistence cyclic dominance bi-stable

COMPrompter: reconceptualized segment anything model with multiprompt network for camouflaged object detection

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Science China(Information Sciences) 2025年第1期68卷 189-203页

作者： xiaoqin ZHANG Zhenni YU Li zhao Deng-Ping fAN Guobao xIAO Zhejiang Province Key Laboratory of Intelligent Informatics for Safety and Emergency Wenzhou University Nankai International Advanced Research Institute (SHENZHEN fUTIAN) College of Computer Science Nankai University School of Computer Science and Technology Tongji University

We rethink the segment anything model(SAM) and propose a novel multiprompt network called COMPrompter for camouflaged object detection(COD). SAM has zero-shot generalization ability beyond other models and can provide an ideal framework for COD. Our network aims to enhance the single prompt strategy in SAM to a multiprompt strategy. To achieve this, we propose an edge gradient extraction module, which generates a mask containing gradient information regarding the boundaries of camouflaged objects. This gradient mask is then used as a novel boundary prompt, enhancing the segmentation process. Thereafter, we design a box-boundary mutual guidance module, which fosters more precise and comprehensive feature extraction via mutual guidance between a boundary prompt and a box prompt. This collaboration enhances the model's ability to accurately detect camouflaged objects. Moreover, we employ the discrete wavelet transform to extract high-frequency features from image embeddings. The high-frequency features serve as a supplementary component to the multiprompt ***, our COMPrompter guides the network to achieve enhanced segmentation results, thereby advancing the development of SAM in terms of COD. Experimental results across COD benchmarks demonstrate that COMPrompter achieves a cutting-edge performance, surpassing the current leading model by an average positive metric of 2.2% in COD10K. In the specific application of COD, the experimental results in polyp segmentation show that our model is superior to top-tier methods as well. The code will be made available at https://***/guobaoxiao/COMPrompter.

关键词： segment anything model camouflaged object detection boundary prompt

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Study on the One-year Accuracy of Pulsar Time-scale

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Research in Astronomy and Astrophysics 2025年第1期25卷 282-296页

作者： Linlin Wang Zhehao Zhang Chengshi zhao Zongke Li Minglei Tong National Time Service Center Chinese Academy of Sciences Key Laboratory of Time Reference and Applications Chinese Academy of Sciences University of Chinese Academy of Sciences

Determining accurate pulsar timing model parameters is essential for establishing TT(PT), a realization of Terrestrial Time (TT) based on a pulsar timescale (PT). This study discusses the impact of different data spans on the accuracy of pulsar timing model parameters when determining pulsar timing model parameters. Using observations of PSR J0437-4715, J1909-3744, J1713+0747, and J1744-1134 from the second data release of the International Pulsar Timing Array (IPTA II, Version A), we compare the accuracy of the timing model parameters determined by these observations with different data spans. The results show for PSR J0437-4715, J1713+0747,and J1909-3744, the amplitude fluctuations of rotational frequency remain within 10-15, 10-14, and 10-14Hz,respectively, when the data spans for determining pulsar timing model parameters exceed 13, 14, and 6 ***, the one-year accuracy of TT(PT) is crucial for its application in timekeeping. By comparing the frequency deviations of TT(PT) relative to TT(BIPM) under both ideal (kr) and actual (kp) conditions across different data spans, we find that when the data span reaches the duration above, the accuracy of TT(PT) surpasses that of TT(TAI) under ideal conditions, slightly inferior under actual conditions. This suggests with improved observational technologies, the accuracy of TT(PT) can be further enhanced.

关键词： (stars:) pulsars: individual (PSRs J1909-3744, J1713+0747, J0437-4715, J1744-1134) methods: data analysis time

Recent Advances in Artificial Sensory Neurons:Biological fundamentals,Devices,Applications,and Challenges

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Nano-Micro Letters 2025年第3期17卷 168-216页

作者： Shuai Zhong Lirou Su Mingkun xu Desmond Loke Bin Yu Yishu Zhang Rong zhao Guangdong Institute of Intelligence Science and Technology HengqinZhuhai 519031People’s Republic of China College of Integrated Circuits Zhejiang UniversityHangzhou 3112000People’s Republic of China ZJU-Hangzhou Global Scientific and Technological Innovation Center Hangzhou 310027People’s Republic of China Department of Science Mathematics and TechnologySingapore University of Technology and DesignSingapore 487372Singapore Department of Precision Instruments Tsinghua UniversityBeijing 100084People’s Republic of China Center for Brain‑Inspired Computing Research Tsinghua UniversityBeijing 100084People’s Republic of China IDG/McGovern Institute for Brain Research Tsinghua UniversityBeijing 100084People’s Republic of China

Spike-based neural networks,which use spikes or action potentialsto represent information,have gained a lot of attention because of their high energyefficiency and low power *** fully leverage its advantages,convertingthe external analog signals to spikes is an essential *** including analog-to-digital converters or ring oscillators,and sensorssuffer from high power and area *** efforts are devoted to constructingartificial sensory neurons based on emerging devices inspired by the biologicalsensory *** can simultaneously perform sensing and spike conversion,overcoming the deficiencies of traditional sensory *** review summarizesand benchmarks the recent progress of artificial sensory *** starts with thepresentation of various mechanisms of biological signal transduction,followed bythe systematic introduction of the emerging devices employed for artificial ***,the implementations with different perceptual capabilitiesare briefly outlined and the key metrics and potential applications are also ***,we highlight the challenges and perspectives for the future development of artificial sensory neurons.

关键词： Artificial intelligence Emerging devices Artificial sensory neurons Spiking neural networks Neuromorphic sensing

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Isospin splitting of the Dirac mass probed using the relativistic Brueckner-Hartree-fock theory

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Nuclear Science and Techniques 2025年第2期36卷 123-130页

作者： Pianpian Qin Qiang zhao Hui Tong Chencan Wang Sibo Wang Department of Physics and Chongqing Key Laboratory for Strongly Coupled Physics Chongqing UniversityChongqing 401331China Center for Exotic Nuclear Studies Institute for Basic ScienceDaejeon 34126Korea Helmholtz-Institut für Strahlen-und Kernphysik and Bethe Center for Theoretical Physics Universität BonnBonn D-53115Germany School of Physics and Astronomy Sun Yat-Sen UniversityZhuhai 519082China

The isospin splitting of the Dirac mass obtained using the relativistic Brueckner-Hartree-fock(RBHf)theory was thor-oughly *** the perspective in the full Dirac space,the long-standing controversy between the momentum-independent approximation(MIA)method and the projection method on the isospin splitting of the Dirac mass in asymmetric nuclear matter was analyzed in *** found that the assumption procedure of the MIA method,which assumes that single-particle potentials are momentum independent,is not a sufficient condition that directly leads to the opposite sign of the isospin splitting of the Dirac mass,whereas the extraction procedure of the MIA method,which extracts single-particle potentials from single-particle potential energy,changes the sign.A formal expression of the Dirac mass was obtained by approximately solving a set of equations involved in the extraction *** opposite isospin splitting of the Dirac mass was mainly caused by the extraction procedure,which forcibly assumed that the momentum dependence of the single-particle potential energy was in a quadratic form,in which the strength was solely determined by a constant scalar *** understanding of the isospin splitting of the Dirac mass from ab initio calculations could enhance our knowledge of neutron-rich systems,such as exotic nuclei and neutron stars.

关键词： Dirac mass Relativistic Brueckner-Hartree-fock theory Single-particle potential Momentum dependence

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Phase-transfer-shuttle generated in situ enables novel SN1-type fluorination of sulfonium ylide with hydrofluoric acid

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Science China Chemistry 2025年第2期68卷 641-648页

作者： Yisa xiao Rui Wang zhaoxuan xu Qunchao zhao Renyi Pang Tao Dong Long Lu Qilong Shen Key Laboratory of fluorine and Nitrogen Chemistry and Advanced Materials Shanghai Institute of Organic ChemistryUniversity of Chinese Academy SciencesChinese Academy of SciencesShanghai 200032China

The development of a nucleophilic fluorination protocol using hydrofluoric acid as the fluoride source represents a long-sought goal in the field of organofluorine *** report herein the realization of such a reaction that employed alkyl-substituted sulfonium ylides as the *** key to the success of the protocol was attributed to two factors:first,as a Brϕnsted base,the ylide was able to be protonated by Hfaq,thus serving as a phase-transfer shuttle generated in situ to bring f−from aqueous phase to the organic phase promoting desolvation of fluoride ***,after protonation,a sulfonium salt,a good leaving group,was generated and subsequent attacked by the fluoride to afford the alkyl *** investigation indicates that the reaction occurs via an SN1 *** of the nature of the cationic intermediate in the reaction,two attractive rearrangement-fluorination approaches including 1,2-aryl migration fluorination and ring-expansion fluorination were disclosed.

关键词： SN1 fluorination hydrofluoric acid sulfonium ylide cation rearrangement

Energy transfer enhanced photocatalytic hydrogen evolution in organic heterostructure nanoparticles via flash nanoprecipitation processing

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Green Energy & Environment 2025年第2期10卷 390-398页

作者： Miaojie Yu Weiwei Zhang xueyan Liu Guohui zhao Jun Du Yongzhen Wu Wei-Hong Zhu Key Laboratory for Advanced Materials and Institute of fine Chemicals Joint International Research Laboratory of Precision Chemistry and Molecular EngineeringFeringa Nobel Prize Scientist Joint Research CenterFrontiers Science Center for Materiobiology and Dynamic ChemistrySchool of Chemistry and Molecular EngineeringEast China University of Science and TechnologyShanghai200237China State Key Laboratory of Molecular Reaction Dynamics Dalian Institute of Chemical PhysicsChinese Academy of SciencesDalianLiaoning116023China

Organic nanophotocatalysts are promising candidates for solar fuels production,but they still face the challenge of unfavorable geminate recombination due to the limited exciton diffusion ***,we introduce a binary nanophotocatalyst fabricated by blending two polymers,PS-PEG5(PS)and PBT-PEG5(PBT),with matched absorption and emission spectra,enabling a f€orster resonance energy transfer(fRET)process for enhanced *** heterostructure nanophotocatalysts are processed using a facile and scalable flash nanoprecipitation(fNP)technique with precious kinetic control over binary nanoparticle *** resulting nanoparticles exhibit an exceptional photocatalytic hydrogen evolution rate up to 65 mmol g^(-1) h^(-1),2.5 times higher than that single component *** through fluorescence spectra and transient absorption spectra confirm the hetero-energy transfer within the binary nanoparticles,which prolongs the excited-state lifetime and extends the namely“effective exciton diffusion length”.Our finding opens new avenues for designing efficient organic photocatalysts by improving exciton migration.

关键词： Polymer photocatalysts Nanoparticles Hydrogen evolution f€orster resonance energy transfer

Deep view of composite SNR CTA1 with LHAASO in γ-rays up to 300 TeV

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Science China(Physics,Mechanics & Astronomy) 2025年

作者： Zhen Cao f.Aharonian Axikegu Y.x.Bai Y.W.Bao D.Bastieri x.J.Bi Y.J.Bi W.Bian A.V.Bukevich Q.Cao W.Y.Cao Zhe Cao J.Chang J.f.Chang A.M.Chen E.S.Chen H.x.Chen Liang Chen Lin Chen Long Chen M.J.Chen M.L.Chen Q.H.Chen S.Chen S.H.Chen S.Z.Chen T.L.Chen Y.Chen N.Cheng Y.D.Cheng M.C.Chu M.Y.Cui S.W.Cui x.H.Cui Y.D.Cui B.Z.Dai H.L.Dai Z.G.Dai Danzengluobu x.Q.Dong K.K.Duan J.H.fan Y.Z.fan J.fang J.H.fang K.fang C.f.feng H.feng L.feng S.H.feng x.T.feng Y.feng Y.L.feng S.Gabici B.Gao C.D.Gao Q.Gao W.Gao W.K.Gao M.M.Ge T.T.Ge L.S.Geng G.Giacinti G.H.Gong Q.B.Gou M.H.Gu f.L.Guo J.Guo x.L.Guo Y.Q.Guo Y.Y.Guo Y.A.Han O.A.Hannuksela M.Hasan H.H.He H.N.He J.Y.He Y.He Y.K.Hor B.W.Hou C.Hou x.Hou H.B.Hu Q.Hu S.C.Hu C.Huang D.H.Huang T.Q.Huang W.J.Huang x.T.Huang x.Y.Huang Y.Huang Y.Y.Huang x.L.Ji H.Y.Jia K.Jia H.B.Jiang K.Jiang x.W.Jiang Z.J.Jiang M.Jin M.M.Kang I.Karpikov D.Khangulyan D.Kuleshov K.Kurinov B.B.Li C.M.Li Cheng Li Cong Li D.Li f.Li H.B.Li H.C.Li Jian Li Jie Li K.Li S.D.Li W.L.Li W.L.Li x.R.Li xin Li Y.Z.Li Zhe Li Zhuo Li E.W.Liang Y.f.Liang S.J.Lin B.Liu C.Liu D.Liu D.B.Liu H.Liu H.D.Liu J.Liu J.L.Liu M.Y.Liu R.Y.Liu S.M.Liu W.Liu Y.Liu Y.N.Liu Q.Luo Y.Luo H.K.Lv B.Q.Ma L.L.Ma x.H.Ma J.R.Mao Z.Min W.Mitthumsiri H.J.Mu Y.C.Nan A.Neronov K.C.Y.Ng L.J.Ou P.Pattarakijwanich Z.Y.Pei J.C.Qi M.Y.Qi B.Q.Qiao J.J.Qin A.Raza D.Ruffolo A.Sáiz M.Saeed D.Semikoz L.Shao O.Shchegolev x.D.Sheng f.W.Shu H.C.Song Yu.V.Stenkin V.Stepanov Y.Su D.x.Sun Q.N.Sun x.N.Sun Z.B.Sun J.Takata P.H.T.Tam Q.W.Tang R.Tang Z.B.Tang W.W.Tian L.H.Wan C.Wang C.B.Wang G.W.Wang H.G.Wang H.H.Wang J.C.Wang Kai Wang Kai Wang L.P.Wang L.Y.Wang P.H.Wang R.Wang W.Wang x.G.Wang x.Y.Wang Y.Wang Y.D.Wang Y.J.Wang Z.H.Wang Z.x.Wang Zhen Wang Zheng Wang D.M.Wei J.J.Wei Y.J.Wei T.Wen C.Y.Wu H.R.Wu Q.W.Wu S.Wu x.f.Wu Y.S.Wu S.Q.xi J.xia G.M.xiang D.x.xiao G.xiao Y.L.xin Y.xing D.R.xiong Z.xiong D.L.xu R.f.xu R.x.xu W.L.xu L.xue D.H.Yan J.Z.Yan T.Yan C.W.Yang C.Y.Yang f.Yang f.f.Yang L.L.Yang M.J.Yang R.Z.Yang W.x.Yang Y.H.Yao Z.G.Yao L.Q.Yin N.Yin x.H.You Z.Y.You Y.H Southwest Jiaotong University School of Astronomy and Space Science Nanjing University Center for Astrophysics Guangzhou University Tsung-Dao Lee Institute & School of Physics and Astronomy Shanghai Jiao Tong University Institute for Nuclear Research of Russian Academy of Sciences Hebei Normal University University of Science and Technology of China LHAASO Collaboration State Key Laboratory of Particle Detection and Electronics Key Laboratory of Dark Matter and Space Astronomy & Key Laboratory of Radio Astronomy Purple Mountain Observatory Chinese Academy of Sciences Research Center for Astronomical Computing Zhejiang Laboratory Key Laboratory for Research in Galaxies and Cosmology Shanghai Astronomical Observatory Chinese Academy of Sciences School of Physics and Astronomy Key Laboratory of Particle Astrophysics & Experimental Physics Division & Computing Center Yunnan University Key Laboratory of Cosmic Rays (Tibet University) Ministry of Education Department of Physics The Chinese University of Hong Kong Key Laboratory of Radio Astronomy and Technology National Astronomical Observatories Chinese Academy of Sciences School of Physics and Astronomy (Zhuhai) & School of Physics (Guangzhou) & Sino-french Institute of Nuclear Engineering and Technology (Zhuhai) Sun Yat-sen University Institute of High Energy Physics Institute of frontier and Interdisciplinary Science Shandong University APC Université Paris Cité CNRS/IN2P3 CEA/IRfU Observatoire de Paris Department of Engineering Physics & Department of Astronomy Tsinghua University School of Physics and Microelectronics Chinese Academy of Sciences Zhengzhou University Yunnan Observatories Chinese Academy of Sciences China Center of Advanced Science and Technology College of Physics Sichuan University School of Physics Peking University Guangxi Key Laboratory for Relativistic Astrophysics School of Physical Science and Technology University of Chinese Academy of Sciences Guangxi University Department of Physics faculty of Science Mahidol University Moscow Institute

The ultra-high-energy（UHE） gamma-ray source 1LHAASO J0007+7303u is positionally associated with the composite SNR CTA1 that is located at high Galactic Latitude b ≈ 10.5°. This provides a rare opportunity to spatially resolve the component of the pulsar wind nebula（PWN） and supernova remnant（SNR） at UHE. This paper conducted a dedicated data analysis of 1LHAASO J0007+7303u using the data collected from December 2019 to July 2023. This source is well detected with significances of 21σ and 17σ at 8-100 TeV and >100 TeV, respectively. The corresponding extensions are determined to be 0.23°±0.03°and 0.17°±0.03°. The emission is proposed to originate from the relativistic electrons accelerated within the PWN of PSR J0007+7303. The energy spectrum is well described by a power-law with an exponential cutoff function dN/dE =（42.4 ± 4.1）(E/（20 TeV）)-2.31±0.11exp(-E/（110±25 TeV）) TeV-1cm-2s-1in the energy range from 8 to 300 TeV, implying a steady-state parent electron spectrum dNe/dEe∝(Ee/（100 TeV）)-3.13±0.16exp[(-Ee/（373±70 TeV）)2] at energies above ≈ 50 TeV. The cutoff energy of the electron spectrum is roughly equal to the expected current maximum energy of particles accelerated at the PWN terminal shock. Combining the x-ray and gamma-ray emission, the current space-averaged magnetic field can be limited to≈ 4.5 μG. To satisfy the multi-wavelength spectrum and the γ-ray extensions, the transport of relativistic particles within the PWN is likely dominated by the advection process under the free-expansion phase assumption.

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