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Acta Metallurgica Sinica(English Letters) 2015年第11期28卷 1382-1386页

作者： Nai-Kun Sun zeng-xin ren Jie Guo Sheng-Jie Du Ping-Zhan Si School of Science Shenyang Ligong University College of Materials Science and Engineering China Jiliang University

Nitrogenation of La0.5Pr0.5Fe11.4Si1.6 with a particle size of 100-150 μm was performed in a high-purity N2 atmosphere of 40 MPa. La0.5Pr0.5Fe11.4Si1.6N0.3 nitrogenated at 480 ℃ exhibits an increase in the Curie temperature Tc from 187 to 195 K. Moreover, for a field change from 0 to 1.5 T, the maximum hysteresis loss at Tc is remarkably reduced from 53 to 3 J kg^-1 and a large magnetic-entropy change ASm of over 10 J kg^-1 K^-1 is maintained. For a La0.5Pr0.5- Fe11.4Si1.6N1.2 sample, nitrogenated at 550 ℃, the XRD pattern clearly exhibits two 1：13 phases and, accordingly, the thermal magnetic curves exhibit two transitions, at 210 and at 295 K. The two transitions lead, for a field change of 5 T, to a ASm larger than 2 J kg^-1 K^-1 over a large temperature range from 200 to 310 K with a maximum value of 5.3 J kg^-1 K^-1 at 225 K. Upon further increase in the nitrogenation temperature to 650 ℃, the amount of the nitrogen- poor phase strongly decreases and a large amount of α-Fe precipitates, resulting in a large reduction in the MCE.

关键词： Metals and alloys Magnetocaloric effect Magnetic hysteresis

Preparation and study of novel mid-to-low-temperature phase-change molten salts

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Science China Technological Sciences 2025年

作者： Chenxing ren Yifan WANG xin HE Chenghang ZHENG Xiang GAO State Key Laboratory of Clean Energy Utilization Zhejiang University Institute of Carbon Neutrality Zhejiang University Baima Lake Laboratory Zhejiang University

Molten salts is a promising medium for heat storage and heat transfer due to their advantages of low cost, low steam pressure, high energy storage density and wide temperature range. In this paper, a new phase change mixture of molten salts with KNO3, NaNO3, ZnCl2, NaF, Na2CO3, NaCl, and MgO as materials has been prepared through a plenty of experiments. The experimental results show that the melting point of some molten salts can be reduced to 202.9°C, and the decomposition temperature can reach 701.3°C. In addition, its thermophysical properties, including specific heat, viscosity and thermal stability, were measured and analyzed. The average specific heat of some molten salts is as high as 2.53 J/（g K）, and the average thermal conductivity is as high as 0.77 W/（m K）. In the 4-day short-term thermal stability test, the fluctuation of each parameter is minimal, and the overall thermal physical property is relatively stable. Compared with the traditional phase change molten salt, the new hybrid molten salt has a significantly lower melting point, a further improvement in the decomposition temperature, specific heat and other comprehensive thermophysical properties, and a better overall economy, which has important application value in heat transfer and energy storage.

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Induced pluripotent stem cell-related approaches to generate dopaminergic neurons for Parkinson's disease

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Neural Regeneration Research 2025年第11期20卷 3193-3206页

作者： Ling-Xiao Yi Hui ren Woon Genevieve Saw Li zeng Eng King Tan Zhi Dong Zhou National Neuroscience Institute Singapore Nanyang Technology University Singapore Department of Neurology Singapore General HospitalSingapore Signature Research Program in Neuroscience and Behavioral Disorders Duke-NUS Medical SchoolSingapore

The progressive loss of dopaminergic neurons in affected patient brains is one of the pathological features of Parkinson's disease,the second most common human neurodegenerative *** the detailed pathogenesis accounting for dopaminergic neuron degeneration in Parkinson's disease is still unclear,the advancement of stem cell approaches has shown promise for Parkinson's disease research and *** induced pluripotent stem cells have been commonly used to generate dopaminergic neurons,which has provided valuable insights to improve our understanding of Parkinson's disease pathogenesis and contributed to anti-Parkinson's disease *** current review discusses the practical approaches and potential applications of induced pluripotent stem cell techniques for generating and differentiating dopaminergic neurons from induced pluripotent stem *** benefits of induced pluripotent stem cell-based research are *** dopaminergic neuron differentiation protocols from induced pluripotent stem cells are *** emerging three-dimension-based brain organoid models compared with conventional two-dimensional cell culture are ***,limitations,challenges,and future directions of induced pluripotent stem cell–based approaches are analyzed and proposed,which will be significant to the future application of induced pluripotent stem cell-related techniques for Parkinson's disease.

关键词： dopaminergic neurons induced pluripotent stem cells Parkinson's disease stem cell approaches

Early identification of stroke through deep learning with multi-modal human speech and movement data

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Neural Regeneration Research 2025年第1期20卷 234-241页

作者： Zijun Ou Haitao Wang Bin Zhang Haobang Liang Bei Hu Longlong ren Yanjuan Liu Yuhu Zhang Chengbo Dai Hejun Wu Weifeng Li xin Li School of Computer Science and Engineering Sun Yat-sen UniversityGuangzhouGuangdong ProvinceChina Department of Neurology Guangdong Neuroscience InstituteGuangdong Provincial People’s Hospital(Guangdong Academy of Medical Sciences)Southern Medical UniversityGuangzhouGuangdong ProvinceChina Department of Emergency Medicine Guangdong Provincial People’s Hospital(Guangdong Academy of Medical Sciences)Southern Medical UniversityGuangzhouGuangdong ProvinceChina

Early identification and treatment of stroke can greatly improve patient outcomes and quality of *** clinical tests such as the Cincinnati Pre-hospital Stroke Scale(CPSS)and the Face Arm Speech Test(FAST)are commonly used for stroke screening,accurate administration is dependent on specialized *** this study,we proposed a novel multimodal deep learning approach,based on the FAST,for assessing suspected stroke patients exhibiting symptoms such as limb weakness,facial paresis,and speech disorders in acute *** collected a dataset comprising videos and audio recordings of emergency room patients performing designated limb movements,facial expressions,and speech tests based on the *** compared the constructed deep learning model,which was designed to process multi-modal datasets,with six prior models that achieved good action classification performance,including the I3D,SlowFast,X3D,TPN,TimeSformer,and *** found that the findings of our deep learning model had a higher clinical value compared with the other ***,the multi-modal model outperformed its single-module variants,highlighting the benefit of utilizing multiple types of patient data,such as action videos and speech *** results indicate that a multi-modal deep learning model combined with the FAST could greatly improve the accuracy and sensitivity of early stroke identification of stroke,thus providing a practical and powerful tool for assessing stroke patients in an emergency clinical setting.

关键词： artificial intelligence deep learning diagnosis early detection FAST screening stroke

Tailoring Light–Matter Interactions in Overcoupled Resonator for Biomolecule Recognition and Detection

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Nano-Micro Letters 2025年第1期17卷 262-280页

作者： Dongxiao Li Hong Zhou Zhihao ren Cheng Xu Chengkuo Lee Department of Electrical and Computer Engineering National University of SingaporeSingapore 117583Singapore Center for Intelligent Sensors and MEMS(CISM) National University of SingaporeSingapore 117608Singapore

Plasmonic nanoantennas provide unique opportunities for precise control of light–matter coupling in surface-enhanced infrared absorption(SEIRA)spectroscopy,but most of the resonant systems realized so far suffer from the obstacles of low sensitivity,narrow bandwidth,and asymmetric Fano resonance ***,we demonstrated an overcoupled resonator with a high plasmon-molecule coupling coefficient(μ)(OC-Hμresonator)by precisely controlling the radiation loss channel,the resonator-oscillator coupling channel,and the frequency detuning *** observed a strong dependence of the sensing performance on the coupling state,and demonstrated that OC-Hμresonator has excellent sensing properties of ultra-sensitive(7.25%nm^(−1)),ultra-broadband(3–10μm),and immune asymmetric Fano *** characteristics represent a breakthrough in SEIRA technology and lay the foundation for specific recognition of biomolecules,trace detection,and protein secondary structure analysis using a single array(array size is 100×100μm^(2)).In addition,with the assistance of machine learning,mixture classification,concentration prediction and spectral reconstruction were achieved with the highest accuracy of 100%.Finally,we demonstrated the potential of OC-Hμresonator for SARS-CoV-2 *** findings will promote the wider application of SEIRA technology,while providing new ideas for other enhanced spectroscopy technologies,quantum photonics and studying light–matter interactions.

关键词： Plasmonic nanoantennas Light-matter interaction Surface-enhanced infrared absorption Overcoupled Biosensing

Optimizing the key parameter to accelerate the recovery of AMOC under a rapid increase of greenhouse gas forcing

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Atmospheric and Oceanic Science Letters 2025年第1期18卷 39-45页

作者： Haolan ren Fei Zheng Tingwei Cao Qiang Wang International Center for Climate and Environment Science(ICCES) Institute of Atmospheric PhysicsChinese Academy of SciencesBeijingChina University of Chinese Academy of Sciences BeijingChina College of Oceanography Hohai UniversityNanjingChina CAS Key Laboratory of Ocean Circulation and Waves Institute of OceanologyChinese Academy of Sciences and Pilot National Laboratory for Marine Science and Technology(Qingdao)QingdaoChina

Atlantic Meridional Overturning Circulation(AMOC)plays a central role in long-term climate variations through its heat and freshwater transports,which can collapse under a rapid increase of greenhouse gas forcing in climate *** studies have suggested that the deviation of model parameters is one of the major factors in inducing inaccurate AMOC *** this work,with a low-resolution earth system model,the authors try to explore whether a reasonable adjustment of the key model parameter can help to re-establish the AMOC after its *** a new optimization strategy,the extra freshwater flux(FWF)parameter is determined to be the dominant one affecting the AMOC’s *** traditional ensemble optimal interpolation(EnOI)data assimilation and new machine learning methods are adopted to optimize the FWF parameter in an abrupt 4×CO_(2) forcing experiment to improve the adaptability of model parameters and accelerate the recovery of *** results show that,under an abrupt 4×CO_(2) forcing in millennial simulations,the AMOC will first collapse and then re-establish by the default FWF parameter ***,during the parameter adjustment process,the saltier and colder sea water over the North Atlantic region are the dominant factors in usefully improving the adaptability of the FWF parameter and accelerating the recovery of AMOC,according to their physical relationship with FWF on the interdecadal timescale.

关键词： Recovery of AMOC 4×CO_(2)forcing Key parameter Parameter estimation Data assimilation Machine learning

Iron-handling solute carrier SLC22A17 as a blood-brain barrier target after stroke

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Neural Regeneration Research 2025年第11期20卷 3207-3208页

作者： Xueqi ren Wenlu Li Key Laboratory of Neuropharmacology and Translational Medicine of Zhejiang Province School of Pharmaceutical SciencesZhejiang Chinese Medical UniversityHangzhouZhejiang ProvinceChina Neuroprotection Research Laboratories Departments of Radiology and NeurologyMassachusetts General HospitalHarvard Medical SchoolBostonMAUSA

The pathophysiology of ischemic stroke is complex and multifactorial,involving various forms of cell death such as apoptosis,autophagy,and necrosis.A recent study suggests that oxidative and inflammatory stress can induce ferroptosis,a specialized form of cell death characterized by the accumulation of lipid peroxides dependent on intracellular iron overload(Li and Jia,2023).

关键词： death specialized barrier

Bearing Fault Diagnosis Based on the Markov Transition Field and SE-IShufflenetV2 Model

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Structural Durability & Health Monitoring 2025年第1期19卷 125-144页

作者： Chaozhi Cai Tiexin Xu Jianhua ren Yingfang Xue School of Mechanical and Equipment Engineering Hebei University of EngineeringHandan056038China

A bearing fault diagnosis method based on the Markov transitionﬁeld(MTF)and SEnet(SE)-IShufﬂenetV2 model is proposed in this paper due to the problems of complex working conditions,low fault diagnosis accuracy,and poor generalization of rolling ***,MTF is used to encode one-dimensional time series vibration sig-nals and convert them into time-dependent and unique two-dimensional feature ***,the generated two-dimensional dataset is fed into the SE-IShufﬂenetV2 model for training to achieve fault feature extraction and classiﬁ*** paper selects the bearing fault datasets from Case Western Reserve University and Paderborn University to experimentally verify the effectiveness and superiority of the proposed *** generalization performance of the proposed method is tested under the variable load condition and different signal-to-noise ratios(SNRs).The experimental results show that the average accuracy of the proposed method under different working conditions is 99.2%without adding *** accuracy under different working conditions from 0 to 1 HP is 100%.When the SNR is 0 dB,the average accuracy of the proposed method can still reach 98.7%under varying working ***,the bearing fault diagnosis method proposed in this paper is characterized by high accuracy,strong anti-noise ability,and ***,the proposed method can also overcome the inﬂuence of variable working conditions on diagnosis accuracy,providing method support for the accurate diagnosis of bearing faults under strong noise and variable working conditions.

关键词： Bearings Markov transitionﬁeld SE-IShufﬂenetV2

Stochastic Augmented-Based Dual-Teaching for Semi-Supervised Medical Image Segmentation

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Computers, Materials & Continua 2025年第1期82卷 543-560页

作者： Hengyang Liu Yang Yuan Pengcheng ren Chengyun Song Fen Luo School of Computer Science and Engineering Chongqing University of TechnologyChongqing400054China College of Artificial Intelligence Chongqing Technology and Business UniversityChongqing400067China

Existing semi-supervisedmedical image segmentation algorithms use copy-paste data augmentation to correct the labeled-unlabeled data distribution ***,current copy-paste methods have three limitations:(1)training the model solely with copy-paste mixed pictures from labeled and unlabeled input loses a lot of labeled information;(2)low-quality pseudo-labels can cause confirmation bias in pseudo-supervised learning on unlabeled data;(3)the segmentation performance in low-contrast and local regions is less than *** design a Stochastic Augmentation-Based Dual-Teaching Auxiliary Training Strategy(SADT),which enhances feature diversity and learns high-quality features to overcome these *** be more precise,SADT trains the Student Network by using pseudo-label-based training from Teacher Network 1 and supervised learning with labeled data,which prevents the loss of rare labeled *** introduce a bi-directional copy-pastemask with progressive high-entropy filtering to reduce data distribution disparities and mitigate confirmation bias in *** the mixed images,Deep-Shallow Spatial Contrastive Learning(DSSCL)is proposed in the feature spaces of Teacher Network 2 and the Student Network to improve the segmentation capabilities in low-contrast and local *** this procedure,the features retrieved by the Student Network are subjected to a random feature perturbation *** two openly available datasets,extensive trials show that our proposed SADT performs much better than the state-ofthe-art semi-supervised medical segmentation *** only 10%of the labeled data for training,SADT was able to acquire a Dice score of 90.10%on the ACDC(Automatic Cardiac Diagnosis Challenge)dataset.

关键词： Semi-supervised medical image segmentation contrastive learning stochastic augmented

Morphological Mechanism and Experimental Verification of Self-healing of Basalt-fiber Modified Water-soaked Asphalt

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Journal of Wuhan University of Technology(Materials Science) 2025年第1期40卷 171-186页

作者： XIAO Minmin DONG Jinyong LI Chunyan GUO Xu ren Jianguo School of Urban Construction and Safety Engineering Shanghai Institute of TechnologyShanghai 201418China

This study investigates the mechanism of action of representative molecules of basalt fibers on the healing of water-soaked *** parameters,morphological characteristics,interfacial healing energy,and interfacial healing strength were analyzed using molecular dynamics and macroscopic tests under different time,temperature,and water conditions to evaluate the specific states and critical conditions involved in *** results indicate that basalt-fiber molecules can induce rearrangement and a combination of water-soaked asphalt at the healing *** groups with different bonding states increase the interfacial adsorption capacity of water-soaked *** interaction between basalt fiber molecules and water molecules leads to a"hoop"phenomenon,while aromatics-2 molecules exhibit a"ring band aggregation"*** former reduces the miscibility of water and asphalt molecules,while the latter causes slow diffusion of the ***,a micro-macro dual-scale comparison of interfacial healing strength was conducted at temperatures of 297.15 and 312.15 K to identify the strength transition point and critical temperature of 299.4 K during the self-healing process of basalt-fiber modified water-soaked asphalt.

关键词： water-soaked asphalt basalt-fibers self-healing properties moisture status molecular characterization