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Efficient scheme for remote preparation of arbitrary n-qubit equatorial states

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Chinese Physics B 2020年第4期29卷 160-164页

作者： Xin-Wei Zha Min-Rui Wang ruo-xu jiang School of Science Xi'an University of Posts and TelecommunicationsXi'an 710121China

Recently,a scheme for deterministic remote preparation of arbitrary multi-qubit equatorial states was proposed by Wei et al.[Quantum ***.1770(2018)].It is worth mentioning that the construction of mutual orthogonal measurement basis plays a key role in quantum remote state *** this paper,a simple and feasible remote preparation of arbitrary n-qubit equatorial states scheme is *** our scheme,the success probability will reach ***,there are no coefficient constraint and auxiliary qubits in this *** means that the success probabilities are independent of the coefficients of the entangled *** advantage of our scheme is that the mutual orthogonal measurement basis is *** accomplish the quantum remote state preparation(RSP)schemes,some new sets of mutually orthogonal measurement basis are introduced.

关键词： mutual orthogonal measurement basis remote state preparation equatorial states success probability

Constructing a Maximally Entangled Seven-Qubit State via Orthogonal Arrays

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Chinese Physics Letters 2020年第9期37卷 6-9页

作者： Xin-Wei Zha Min-Rui Wang ruo-xu jiang School of Science Xi'an University of Posts and TelecommunicationsXi'an 710121China

Huber et al.[***.118(2017)200502]have proved that a seven-qubit state whose three-body marginal states are all maximally mixed does not ***,we propose a method to build a maximally entangled state based on orthogonal arrays to construct maximally entangled seven-qubit *** this method,we not only determine that a seven-qubit state whose three-body marginals are all maximally mixed does not exist,but also find the condition for maximally entangled seven-qubit *** consider thatπME=19/140 is a condition for maximally entangled seven-qubit ***,we derive three forms of maximally entangled seven-qubit states via orthogonal arrays.

关键词： states. maximal states

Multi-model ensemble learning for battery state-of-health estimation:Recent advances and perspectives

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Journal of Energy Chemistry 2025年第1期100卷 739-759页

作者： Chuanping Lin Jun xu Delong jiang Jiayang Hou Ying Liang Zhongyue Zou xuesong Mei State Key Laboratory for Manufacturing Systems Engineering Xi'an Jiaotong University Shaanxi Key Laboratory of Intelligent Robots School of Mechanical Engineering Xi'an Jiaotong University Department of Electrical Engineering and Automation Luoyang Institute of Science and Technology School of Mechanical Engineering Hangzhou Dianzi University

The burgeoning market for lithium-ion batteries has stimulated a growing need for more reliable battery performance monitoring. Accurate state-of-health(SOH) estimation is critical for ensuring battery operational performance. Despite numerous data-driven methods reported in existing research for battery SOH estimation, these methods often exhibit inconsistent performance across different application scenarios. To address this issue and overcome the performance limitations of individual data-driven models,integrating multiple models for SOH estimation has received considerable attention. Ensemble learning(EL) typically leverages the strengths of multiple base models to achieve more robust and accurate outputs. However, the lack of a clear review of current research hinders the further development of ensemble methods in SOH estimation. Therefore, this paper comprehensively reviews multi-model ensemble learning methods for battery SOH estimation. First, existing ensemble methods are systematically categorized into 6 classes based on their combination strategies. Different realizations and underlying connections are meticulously analyzed for each category of EL methods, highlighting distinctions, innovations, and typical applications. Subsequently, these ensemble methods are comprehensively compared in terms of base models, combination strategies, and publication trends. Evaluations across 6 dimensions underscore the outstanding performance of stacking-based ensemble methods. Following this, these ensemble methods are further inspected from the perspectives of weighted ensemble and diversity, aiming to inspire potential approaches for enhancing ensemble performance. Moreover, addressing challenges such as base model selection, measuring model robustness and uncertainty, and interpretability of ensemble models in practical applications is emphasized. Finally, future research prospects are outlined, specifically noting that deep learning ensemble is poised to advance ens

关键词： Lithium-ion battery State-of-health estimation Data-driven Machine learning Ensemble learning Ensemble diversity

Non-coding RNAs in acute ischemic stroke:from brain to periphery

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Neural Regeneration Research 2025年第1期20卷 116-129页

作者： Shuo Li Zhaohan xu Shiyao Zhang Huiling Sun Xiaodan Qin Lin Zhu Teng jiang Junshan Zhou Fuling Yan Qiwen Deng Department of Neurology Nanjing First HospitalNanjing Medical UniversityNanjingJiangsu ProvinceChina Department of Neurology Zhongda HospitalSchool of MedicineSoutheast UniversityNanjingJiangsu ProvinceChina General Clinical Research Center Nanjing First HospitalNanjing Medical UniversityNanjingJiangsu ProvinceChina

Acute ischemic stroke is a clinical emergency and a condition with high morbidity,mortality,and *** predictive,diagnostic,and prognostic biomarkers and effective therapeutic targets for acute ischemic stroke remain *** innovations in high-throughput gene sequencing analysis,many aberrantly expressed non-coding RNAs(ncRNAs)in the brain and peripheral blood after acute ischemic stroke have been found in clinical samples and experimental *** expressed ncRNAs in the post-stroke brain were demonstrated to play vital roles in pathological processes,leading to neuroprotection or deterioration,thus ncRNAs can serve as therapeutic targets in acute ischemic ***,distinctly expressed ncRNAs in the peripheral blood can be used as biomarkers for acute ischemic stroke prediction,diagnosis,and *** particular,ncRNAs in peripheral immune cells were recently shown to be involved in the peripheral and brain immune response after acute ischemic *** this review,we consolidate the latest progress of research into the roles of ncRNAs(microRNAs,long ncRNAs,and circular RNAs)in the pathological processes of acute ischemic stroke–induced brain damage,as well as the potential of these ncRNAs to act as biomarkers for acute ischemic stroke prediction,diagnosis,and *** from this review will provide novel ideas for the clinical application of ncRNAs in acute ischemic stroke.

关键词： acute ischemic stroke apoptosis blood–brain barrier damage circular RNAs excitatory toxicity long non-coding RNAs microRNAs neuroinflammation non-coding RNAs oxidative stress

Impacts of the annual cycle of background SST in the tropical Pacific on the phase and amplitude of ENSO

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Atmospheric and Oceanic Science Letters 2025年第1期18卷 12-17页

作者： Song jiang Congwen Zhu Ning jiang State Key Laboratory of Severe Weather(LASW) Chinese Academy of Meteorological SciencesBeijingChina College of Earth and Planetary Sciences University of Chinese Academy of SciencesBeijingChina

The dominant annual cycle of sea surface temperature(SST)in the tropical Pacific exhibits an antisymmetric mode,which explains 83.4%total variance,and serves as a background of El Niño-Southern Oscillation(ENSO).However,there is no consensus yet on its anomalous impacts on the phase and amplitude of *** on data during 1982-2022,results show that anomalies of the antisymmetric mode can affect the evolution of ENSO on the interannual scale via Bjerknes feedback,in which the positive(negative)phase of the antisymmetric mode can strengthen El Niño(La Niña)in boreal winter via an earlier(delayed)seasonal cycle transition and larger(smaller)annual *** magnitude of the SST anomalies in the equatorial eastern Pacific can reach more than±0.3◦C,regulated by the changes in the antisymmetric mode based on random sensitivity *** reveal the spatial pattern of the annual cycle associated with the seasonal phase-locking of ENSO evolution and provide new insight into the impact of the annual cycle of background SST on ENSO,which possibly carries important implications for forecasting ENSO.

关键词： Annual cycle SST anomaly Antisymmetric mode ENSO

Solar flare forecasting based on a Fusion Model

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Earth and Planetary Physics 2025年第1期9卷 171-181页

作者： YiYang Li ShiYong Huang SiBo xu ZhiGang Yuan Kui jiang QiYang Xiong RenTong Lin School of Earth and Space Science Technology Hubei Luojia LaboratoryWuhan UniversityWuhan 430072China

Solar flare prediction is an important subject in the field of space *** learning technology has greatly promoted the development of this *** this study,we propose a novel solar flare forecasting model integrating Deep Residual Network(ResNet)and Support Vector Machine(SVM)for both≥C-class(C,M,and X classes)and≥M-class(M and X classes)*** collected samples of magnetograms from May 1,2010 to September 13,2018 from Space-weather Helioseismic and Magnetic Imager(HMI)Active Region Patches and then used a cross-validation method to obtain seven independent data *** then utilized five metrics to evaluate our fusion model,based on intermediate-output extracted by ResNet and SVM using the Gaussian kernel *** results show that the primary metric true skill statistics(TSS)achieves a value of 0.708±0.027 for≥C-class prediction,and of 0.758±0.042 for≥M-class prediction;these values indicate that our approach performs significantly better than those of previous *** metrics of our fusion model’s performance on the seven datasets indicate that the model is quite stable and robust,suggesting that fusion models that integrate an excellent baseline network with SVM can achieve improved performance in solar flare ***,we also discuss the performance impact of architectural innovation in our fusion model.

关键词： solar flare pace weather deep learning Fusion Model

Peripheral blood RNA biomarkers can predict lesion severity in degenerative cervical myelopathy

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Neural Regeneration Research 2025年第6期20卷 1764-1775页

作者： Zhenzhong Zheng Jialin Chen Jinghong xu Bin jiang Lei Li Yawei Li Yuliang Dai Bing Wang Department of Spine Surgery The Second Xiangya Hospital of Central South UniversityChangshaHunan ProvinceChina

Degenerative cervical myelopathy is a common cause of spinal cord injury,with longer symptom duration and higher myelopathy severity indicating a worse *** numerous studies have investigated serological biomarkers for acute spinal cord injury,few studies have explored such biomarkers for diagnosing degenerative cervical *** study involved 30 patients with degenerative cervical myelopathy(51.3±7.3 years old,12 women and 18 men),seven healthy controls(25.7±1.7 years old,one woman and six men),and nine patients with cervical spondylotic radiculopathy(51.9±8.6 years old,three women and six men).Analysis of blood samples from the three groups showed clear differences in transcriptomic *** analysis identified 128 differentially expressed genes that were enriched in patients with neurological *** least absolute shrinkage and selection operator analysis,we constructed a five-gene model(TBCD,TPM2,PNKD,EIF4G2,and AP5Z1)to diagnose degenerative cervical myelopathy with an accuracy of 93.5%.One-gene models(TCAP and SDHA)identified mild and severe degenerative cervical myelopathy with accuracies of 83.3%and 76.7%,*** of two immune cell types(memory B cells and memory-activated CD4^(+)T cells)predicted levels of lesions in degenerative cervical myelopathy with 80%*** results suggest that peripheral blood RNA biomarkers could be used to predict lesion severity in degenerative cervical myelopathy.

关键词： biomarkers candidate genes degenerative cervical myelopathy gene expression analysis immune cell types neurological disabilities peripheral blood RNA profiles spinal cord injury

Preparation of Co/S co-doped carbon catalysts for excellent methylene blue degradation

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International Journal of Minerals,Metallurgy and Materials 2025年第1期32卷 169-181页

作者： Haixu Li Haobo He Tiannan jiang Yunfei Du Zhichen Wu Liang xu Xinjie Wang Xiaoguang Liu Wanhua Yu Wendong xue School of Materials Science and Engineering University of Science and Technology BeijingBeijing 100083China Beijing Jinyu Tongda Refractory Technologies Co. Ltd.Beijing 100085China

S and Co co-doped carbon catalysts were prepared via pyrolysis of MOF-71 and thiourea mixtures at 800℃at a mass ratio of MOF-71 to thiourea of 1:0.1 to effectively activate peroxymonosulfate(PMS)for methylene blue(MB)*** effects of two different mixing routes were identified on the MB degradation ***,the catalyst obtained by the alcohol solvent evaporation(MOF-AEP)mixing route could degrade 95.60%MB(50 mg/L)within 4 min(degradation rate:K=0.78 min^(-1)),which was faster than that derived from the direct grinding method(MOF-DGP,80.97%,K=0.39 min^(-1)).X-ray photoelectron spectroscopy revealed that the Co-S content of MOF-AEP(43.39at%)was less than that of MOF-DGP(54.73at%),and the proportion of C-S-C in MOF-AEP(13.56at%)was higher than that of MOF-DGP(10.67at%).Density functional theory calculations revealed that the adsorption energy of Co for PMS was -2.94 eV when sulfur was doped as C-S-C on the carbon skeleton,which was higher than that when sulfur was doped next to cobalt in the form of Co-S bond(-2.86 eV).Thus,the C-S-C sites might provide more contributions to activate PMS compared with ***,the degradation parameters,including pH and MOF-AEP dosage,were ***,radical quenching experiments and electron paramagnetic resonance(EPR)measurements revealed that ^(1)O_(2)might be the primary catalytic species,whereas·O~(2-)might be the secondary one in degrading MB.

关键词： advanced oxidation process alcohol solvent evaporation hydrogen bond S and Co co-doped carbon catalysts wastewater remediation

Exploration of Gas-Dependent Self-Adaptive Reconstruction Behavior of Cu₂O for Electrochemical CO₂ Conversion to Multi-Carbon Products

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NANO-MICRO LETTERS 2025年第1期17卷 1-17页

作者： Zhang, Chaoran Gu, Yichuan jiang, Qu Sheng, Ziyang Feng, ruohan Wang, Sihong Zhang, Haoyue xu, Qianqing Yuan, Zijian Song, Fang Shanghai Jiao Tong Univ Sch Mat Sci & Engn State Key Lab Met Matrix Composites Shanghai 200240 Peoples R China

Structural reconstruction of electrocatalysts plays a pivotal role in catalytic performances for CO2 reduction reaction (CO2RR), whereas the behavior is by far superficially understood. Here, we report that CO2 accessibility results in a universal self-adaptive structural reconstruction from Cu2O to Cu@CuxO composites, ending with feeding gas-dependent microstructures and catalytic performances. The CO2-rich atmosphere favors reconstruction for CO2RR, whereas the CO2-deficient one prefers that for hydrogen evolution reaction. With the assistance of spectroscopic analysis and theoretical calculations, we uncover a CO2-induced passivation behavior by identifying a reduction-resistant but catalytic active Cu(I)-rich amorphous layer stabilized by *CO intermediates. Additionally, we find extra CO production is indispensable for the robust production of C2H4. An inverse correlation between durability and FECO/FEC2H4 is disclosed, suggesting that the self-stabilization process involving the absorption of *CO intermediates on Cu(I) sites is essential for durable electrolysis. Guided by this insight, we design hollow Cu2O nanospheres for durable and selective CO2RR electrolysis in producing C2H4. Our work recognizes the previously overlooked passivation reconstruction and self-stabilizing behavior and highlights the critical role of the local atmosphere in modulating reconstruction and catalytic processes.

关键词： CO2 reduction reaction Electrocatalysts Cu2O Reconstruction Self-adaptive electrocatalysis