High qualityβ-Ga_(2)O_(3)single crystal nanobelts with length of 2−3 mm and width from tens of microns to 132μm were synthesized by carbothermal reduction method.Based on the grown nanobelt with the length of 600μm...High qualityβ-Ga_(2)O_(3)single crystal nanobelts with length of 2−3 mm and width from tens of microns to 132μm were synthesized by carbothermal reduction method.Based on the grown nanobelt with the length of 600μm,the dual-Schottky-junctions coupling device(DSCD)was fabricated.Due to the electrically floating Ga_(2)O_(3)nanobelt region coupling with the double Schottky-junctions,the current I_(S2)increases firstly and rapidly reaches into saturation as increase the voltage V_(S2).The saturation current is about 10 pA,which is two orders of magnitude lower than that of a single Schottky-junction.In the case of solar-blind ultraviolet(UV)light irradiation,the photogenerated electrons further aggravate the coupling physical mechanism in device.I_(S2)increases as the intensity of UV light increases.Under the UV light of 1820μW/cm^(2),I_(S2)quickly enters the saturation state.At V_(S2)=10 V,photo-to-dark current ratio(PDCR)of the device reaches more than 104,the external quantum efficiency(EQE)is 1.6×10^(3)%,and the detectivity(D*)is 7.5×10^(12)Jones.In addition,the device has a very short rise and decay times of 25−54 ms under different positive and negative bias.DSCD shows unique electrical and optical control characteristics,which will open a new way for the application of nanobelt-based devices.展开更多
In the original publication the third author name is published incorrectly as“Hayatdavoodi Masoud”.The correct author name should be read as“Masoud Hayatdavoodi”.The correct author name is available in this correc...In the original publication the third author name is published incorrectly as“Hayatdavoodi Masoud”.The correct author name should be read as“Masoud Hayatdavoodi”.The correct author name is available in this correction.展开更多
This study employs the generalized method of moments(GMM)and panel vector autoregression(PVAR)models for a multi-factor quantitative dissection of China’s poverty reduction process across multiple stages,using provin...This study employs the generalized method of moments(GMM)and panel vector autoregression(PVAR)models for a multi-factor quantitative dissection of China’s poverty reduction process across multiple stages,using provincial panel data from 2000 to 2019.According to our research,economic growth and social development are the key drivers of poverty reduction in China,but the trickle-down effect of economic growth is diminishing and marketization is having a lesser pro-poor effect.Public expenditure has failed to provide social protection and income redistribution benefits due to issues such as targeting error and elite capture.Increasing the efficiency of the poverty reduction system calls for adaptive adjustments.Finally,this study highlights China’s poverty reduction experiences and analyzes current challenges,which serve as inspiration for consolidating poverty-reduction achievements,combating relative poverty,and attaining countryside vitalization.展开更多
At present,studies on large-amplitude internal solitary waves mostly adopt strong stratification models,such as the twoand three-layer Miyata–Choi–Camassa(MCC)internal wave models,which omit the pycnocline or treat ...At present,studies on large-amplitude internal solitary waves mostly adopt strong stratification models,such as the twoand three-layer Miyata–Choi–Camassa(MCC)internal wave models,which omit the pycnocline or treat it as another fluid layer with a constant density.Because the pycnocline exists in real oceans and cannot be omitted sometimes,the computational error of a large-amplitude internal solitary wave within the pycnocline introduced by the strong stratification approximation is unclear.In this study,the two-and three-layer MCC internal wave models are used to calculate the wave profile and wave speed of large-amplitude internal solitary waves.By comparing these results with the results provided by the Dubreil–Jacotin–Long(DJL)equation,which accurately describes large-amplitude internal solitary waves in a continuous density stratification,the computational errors of large-amplitude internal solitary waves at different pycnocline depths introduced by the strong stratification approximation are assessed.Although the pycnocline thicknesses are relatively large(accounting for 8%–10%of the total water depth),the error is much smaller under the three-layer approximation than under the two-layer approximation.展开更多
Quantum computers promise to solve finite-temperature properties of quantum many-body systems,which is generally challenging for classical computers due to high computational complexities.Here,we report experimental p...Quantum computers promise to solve finite-temperature properties of quantum many-body systems,which is generally challenging for classical computers due to high computational complexities.Here,we report experimental preparations of Gibbs states and excited states of Heisenberg X X and X X Z models by using a 5-qubit programmable superconducting processor.In the experiments,we apply a hybrid quantum–classical algorithm to generate finite temperature states with classical probability models and variational quantum circuits.We reveal that the Hamiltonians can be fully diagonalized with optimized quantum circuits,which enable us to prepare excited states at arbitrary energy density.We demonstrate that the approach has a self-verifying feature and can estimate fundamental thermal observables with a small statistical error.Based on numerical results,we further show that the time complexity of our approach scales polynomially in the number of qubits,revealing its potential in solving large-scale problems.展开更多
Recurrence is the key factor affecting the prognosis of osteosarcoma.Currently,there is a lack of clinically useful tools to predict osteosarcoma recurrence.The application of pathological images for artificial intell...Recurrence is the key factor affecting the prognosis of osteosarcoma.Currently,there is a lack of clinically useful tools to predict osteosarcoma recurrence.The application of pathological images for artificial intelligence‐assisted accurate prediction of tumour out-comes is increasing.Thus,the present study constructed a quantitative histological image classifier with tumour nuclear features to predict osteosarcoma outcomes using haema-toxylin and eosin(H&E)‐stained whole‐slide images(WSIs)from 150 osteosarcoma patients.We first segmented eight distinct tissues in osteosarcoma H&E‐stained WSIs,with an average accuracy of 90.63%on the testing set.The tumour areas were auto-matically and accurately acquired,facilitating the tumour cell nuclear feature extraction process.Based on six selected tumour nuclear features,we developed an osteosarcoma histological image classifier(OSHIC)to predict the recurrence and survival of osteo-sarcoma following standard treatment.The quantitative OSHIC derived from tumour nuclear features independently predicted the recurrence and survival of osteosarcoma patients,thereby contributing to precision oncology.Moreover,we developed a fully automated workflow to extract quantitative image features,evaluate the diagnostic values of feature sets and build classifiers to predict osteosarcoma outcomes.Thus,the present study provides a novel tool for predicting osteosarcoma outcomes,which has a broad application prospect in clinical practice.展开更多
基金supported by Natural Science Basic Research Program in Shaanxi Province of China(No.2023-JCYB-574)National Natural Science Foundation of China(No.62204203).
文摘High qualityβ-Ga_(2)O_(3)single crystal nanobelts with length of 2−3 mm and width from tens of microns to 132μm were synthesized by carbothermal reduction method.Based on the grown nanobelt with the length of 600μm,the dual-Schottky-junctions coupling device(DSCD)was fabricated.Due to the electrically floating Ga_(2)O_(3)nanobelt region coupling with the double Schottky-junctions,the current I_(S2)increases firstly and rapidly reaches into saturation as increase the voltage V_(S2).The saturation current is about 10 pA,which is two orders of magnitude lower than that of a single Schottky-junction.In the case of solar-blind ultraviolet(UV)light irradiation,the photogenerated electrons further aggravate the coupling physical mechanism in device.I_(S2)increases as the intensity of UV light increases.Under the UV light of 1820μW/cm^(2),I_(S2)quickly enters the saturation state.At V_(S2)=10 V,photo-to-dark current ratio(PDCR)of the device reaches more than 104,the external quantum efficiency(EQE)is 1.6×10^(3)%,and the detectivity(D*)is 7.5×10^(12)Jones.In addition,the device has a very short rise and decay times of 25−54 ms under different positive and negative bias.DSCD shows unique electrical and optical control characteristics,which will open a new way for the application of nanobelt-based devices.
文摘In the original publication the third author name is published incorrectly as“Hayatdavoodi Masoud”.The correct author name should be read as“Masoud Hayatdavoodi”.The correct author name is available in this correction.
基金Key Project of the National Social Science Foundation of China(NSSFC)“Study on the Theory and Practice of Inclusive Green Growth(19ZDA048)General Project of the China Postdoctoral Science Fund“Study on the Impact and Mechanism of Talent Dividend on High Quality Development of Manufacturing Industry from the Perspective of Common Prosperity”(2023M733865).
文摘This study employs the generalized method of moments(GMM)and panel vector autoregression(PVAR)models for a multi-factor quantitative dissection of China’s poverty reduction process across multiple stages,using provincial panel data from 2000 to 2019.According to our research,economic growth and social development are the key drivers of poverty reduction in China,but the trickle-down effect of economic growth is diminishing and marketization is having a lesser pro-poor effect.Public expenditure has failed to provide social protection and income redistribution benefits due to issues such as targeting error and elite capture.Increasing the efficiency of the poverty reduction system calls for adaptive adjustments.Finally,this study highlights China’s poverty reduction experiences and analyzes current challenges,which serve as inspiration for consolidating poverty-reduction achievements,combating relative poverty,and attaining countryside vitalization.
基金the Fundamental Research Funds for the Central Universities (No. 3072022FSC0101)the National Natural Science Foundation of China (Nos. 12202114, 52261135547)+4 种基金the China Postdoctoral Science Foundation (No. 2022M710932)the State Key Laboratory of Coastal and Offshore EngineeringDalian University of Technology (No. LP2202)the Qingdao Postdoctoral Application Projectthe Heilongjiang Touyan Innovation Team Program
文摘At present,studies on large-amplitude internal solitary waves mostly adopt strong stratification models,such as the twoand three-layer Miyata–Choi–Camassa(MCC)internal wave models,which omit the pycnocline or treat it as another fluid layer with a constant density.Because the pycnocline exists in real oceans and cannot be omitted sometimes,the computational error of a large-amplitude internal solitary wave within the pycnocline introduced by the strong stratification approximation is unclear.In this study,the two-and three-layer MCC internal wave models are used to calculate the wave profile and wave speed of large-amplitude internal solitary waves.By comparing these results with the results provided by the Dubreil–Jacotin–Long(DJL)equation,which accurately describes large-amplitude internal solitary waves in a continuous density stratification,the computational errors of large-amplitude internal solitary waves at different pycnocline depths introduced by the strong stratification approximation are assessed.Although the pycnocline thicknesses are relatively large(accounting for 8%–10%of the total water depth),the error is much smaller under the three-layer approximation than under the two-layer approximation.
基金Project supported by the State Key Development Program for Basic Research of China(Grant No.2017YFA0304300)the National Natural Science Foundation of China(Grant Nos.11934018,11747601,and 11975294)+4 种基金Strategic Priority Research Program of Chinese Academy of Sciences(Grant No.XDB28000000)Scientific Instrument Developing Project of Chinese Academy of Sciences(Grant No.YJKYYQ20200041)Beijing Natural Science Foundation(Grant No.Z200009)the Key-Area Research and Development Program of Guangdong Province,China(Grant No.2020B0303030001)Chinese Academy of Sciences(Grant No.QYZDB-SSW-SYS032)。
文摘Quantum computers promise to solve finite-temperature properties of quantum many-body systems,which is generally challenging for classical computers due to high computational complexities.Here,we report experimental preparations of Gibbs states and excited states of Heisenberg X X and X X Z models by using a 5-qubit programmable superconducting processor.In the experiments,we apply a hybrid quantum–classical algorithm to generate finite temperature states with classical probability models and variational quantum circuits.We reveal that the Hamiltonians can be fully diagonalized with optimized quantum circuits,which enable us to prepare excited states at arbitrary energy density.We demonstrate that the approach has a self-verifying feature and can estimate fundamental thermal observables with a small statistical error.Based on numerical results,we further show that the time complexity of our approach scales polynomially in the number of qubits,revealing its potential in solving large-scale problems.
基金supported by the China Postdoctoral Science Foundation(2021M692792)National Natural Science Foun-dation of China(82103499,81872173,82072959,U1809205,61771249,91959207,81871352)+2 种基金Natural Science Foundation of Jiangsu Province of China(BK20181411)Natural Science Foundation of Zhejiang Province(LD21H160002)Med-ical and Health Science and Technology Plan of Department of Health of Zhejiang Province(WKJ‐ZJ‐1821).
文摘Recurrence is the key factor affecting the prognosis of osteosarcoma.Currently,there is a lack of clinically useful tools to predict osteosarcoma recurrence.The application of pathological images for artificial intelligence‐assisted accurate prediction of tumour out-comes is increasing.Thus,the present study constructed a quantitative histological image classifier with tumour nuclear features to predict osteosarcoma outcomes using haema-toxylin and eosin(H&E)‐stained whole‐slide images(WSIs)from 150 osteosarcoma patients.We first segmented eight distinct tissues in osteosarcoma H&E‐stained WSIs,with an average accuracy of 90.63%on the testing set.The tumour areas were auto-matically and accurately acquired,facilitating the tumour cell nuclear feature extraction process.Based on six selected tumour nuclear features,we developed an osteosarcoma histological image classifier(OSHIC)to predict the recurrence and survival of osteo-sarcoma following standard treatment.The quantitative OSHIC derived from tumour nuclear features independently predicted the recurrence and survival of osteosarcoma patients,thereby contributing to precision oncology.Moreover,we developed a fully automated workflow to extract quantitative image features,evaluate the diagnostic values of feature sets and build classifiers to predict osteosarcoma outcomes.Thus,the present study provides a novel tool for predicting osteosarcoma outcomes,which has a broad application prospect in clinical practice.
