As artificial intelligence(AI)technology has continued to develop,its efficient data processing and pattern recognition capabilities have significantly improved the precision and speed of decision-making processes,and...As artificial intelligence(AI)technology has continued to develop,its efficient data processing and pattern recognition capabilities have significantly improved the precision and speed of decision-making processes,and it has been widely applied across various fields.In the field of astronomy,AI techniques have demonstrated unique advantages,particularly in the identification of pulsars and their candidates.AI is able to address the challenges of pulsar celestial body identification and classification because of its accuracy and efficiency.This paper systematically surveys commonly used AI models for pulsar candidate identification,analyzing and discussing the typical applications of machine learning,artificial neural networks,convolutional neural networks,and generative adversarial networks in candidate identification.Furthermore,it explores how th.e introduction of AI techniques not only enhances the efficiency and accuracy of pulsar identification but also provides new perspectives and tools for pulsar survey data processing,thus playing a significant role in advancing pulsar research and the field of astronomy.展开更多
To address the issues of low accuracy and high computational complexity in traditional channelization techniques for ultra-wideband signals,this paper proposes a novel rationally oversampled channelization method to e...To address the issues of low accuracy and high computational complexity in traditional channelization techniques for ultra-wideband signals,this paper proposes a novel rationally oversampled channelization method to enhance the accuracy and efficiency of signal processing.The proposed method is evaluated by implementing and comparing critically sampled and integer oversampled channelization algorithms.A detailed analysis of the impact of different oversampling factors and filter orders on performance is provided.The validity of the proposed algorithm is verified using baseband data from pulsar J0437−4715 observed by the Parkes telescope,demonstrating its effectiveness and correctness.展开更多
Astronomical spectroscopy is crucial for exploring the physical properties,chemical composition,and kinematic behavior of celestial objects.With continuous advancements in observational technology,astronomical spectro...Astronomical spectroscopy is crucial for exploring the physical properties,chemical composition,and kinematic behavior of celestial objects.With continuous advancements in observational technology,astronomical spectroscopy faces the dual challenges of rapidly expanding data volumes and relatively lagging data processing capabilities.In this context,the rise of artificial intelligence technologies offers an innovative solution to address these challenges.This paper analyzes the latest developments in the application of machine learning for astronomical spectral data mining and discusses future research directions in AI-based spectral studies.However,the application of machine learning technologies presents several challenges.The high complexity of models often comes with insufficient interpretability,complicating scientific understanding.Moreover,the large-scale computational demands place higher requirements on hardware resources,leading to a significant increase in computational costs.AI-based astronomical spectroscopy research should advance in the following key directions.First,develop efficient data augmentation techniques to enhance model generalization capabilities.Second,explore more interpretable model designs to ensure the reliability and transparency of scientific conclusions.Third,optimize computational efficiency and reduce the threshold for deep-learning applications through collaborative innovations in algorithms and hardware.Furthermore,promoting the integration of cross-band data processing is essential to achieve seamless integration and comprehensive analysis of multi-source data,providing richer,multidimensional information to uncover the mysteries of the universe.展开更多
Recently, the layered transition metal dichalcogenide 1 T MoTe2 has attracted considerable attention due to its non-saturating magnetoresistance, type-II Weyl semimetal properties, superconductivity, and potential can...Recently, the layered transition metal dichalcogenide 1 T MoTe2 has attracted considerable attention due to its non-saturating magnetoresistance, type-II Weyl semimetal properties, superconductivity, and potential candidate for twodimensional（2 D） topological insulator in the single-and few-layer limit. Here in this work, we perform systematic transport measurements on thin flakes of MoTe2 prepared by mechanical exfoliation. We find that MoTe2 flakes are superconducting and have an onset superconducting transition temperature Tc up to 5.3 K, which significantly exceeds that of its bulk counterpart. The in-plane upper critical field(Hc2||) is much higher than the Pauli paramagnetic limit, implying that the MoTe2 flakes have Zeeman-protected Ising superconductivity. Furthermore, the Tc and Hc2|| can be tuned by up to 320 mK and 400 mT by applying a gate voltage. Our result indicates that MoTe2 flake is a good candidate for studying exotic superconductivity with nontrivial topological properties.展开更多
Artificial Intelligence(AI)is an interdisciplinary research field with widespread applications.It aims at developing theoretical,methodological,technological,and applied systems that simulate,enhance,and assist human ...Artificial Intelligence(AI)is an interdisciplinary research field with widespread applications.It aims at developing theoretical,methodological,technological,and applied systems that simulate,enhance,and assist human intelligence.Recently,notable accomplishments of artificial intelligence technology have been achieved in astronomical data processing,establishing this technology as central to numerous astronomical research areas such as radio astronomy,stellar and galactic(Milky Way)studies,exoplanets surveys,cosmology,and solar physics.This article systematically reviews representative applications of artificial intelligence technology to astronomical data processing,with comprehensive description of specific cases:pulsar candidate identification,fast radio burst detection,gravitational wave detection,spectral classification,and radio frequency interference mitigation.Furthermore,it discusses possible future applications to provide perspectives for astronomical research in the artificial intelligence era.展开更多
The radio telescope possesses high sensitivity and strong signal collection capabilities.While receiving celestial radiation signals,it also captures Radio Frequency Interferences(RFIs)introduced by human activities.R...The radio telescope possesses high sensitivity and strong signal collection capabilities.While receiving celestial radiation signals,it also captures Radio Frequency Interferences(RFIs)introduced by human activities.RFI,as signals originating from sources other than the astronomical targets,significantly impacts the quality of astronomical data.This paper presents an RFI fast mitigation algorithm based on block Least Mean Square(LMS)algorithm.It enhances the traditional adaptive LMS filter by grouping L adjacent time-sampled points into one block and applying the same filter coefficients for filtering within each block.This transformation reduces multiplication calculations and enhances algorithm efficiency by leveraging the time-domain convolution theorem.The algorithm is tested using baseband data from the Parkes 64 m radio telescope's pulsar observations and simulated data.The results confirm the algorithm's effectiveness,as the pulsar profile after RFI mitigation closely matches the original pulsar profile.展开更多
We propose a multi-source radio frequency interference(RFI)mitigation method based on a reference antenna array to address the challenge of RFI from multiple directions in radio observation equipment.It introduces a s...We propose a multi-source radio frequency interference(RFI)mitigation method based on a reference antenna array to address the challenge of RFI from multiple directions in radio observation equipment.It introduces a sampling point correction technique using a multi-channel parallel cross-correlation computation method,enhancing the effectiveness of frequency domain adaptive RFI fast mitigation algorithms.The design implements an RFI component detection method based on cross-correlation coefficient thresholds to effectively reduce new interference frequency components introduced by the reference antenna array.Simulated RFI signals and baseband signals of pulsar J0332+5434 observed by the Nanshan 26 m Radio Telescope(NSRT)were used to test the algorithm proposed in this paper.Simulation results demonstrate that the simulated radio telescope signals after RFI mitigation closely match the original pulsar data in profile and phase,confirming the effectiveness of the proposed method.展开更多
For real-time processing of ultra-wide bandwidth low-frequency pulsar baseband data,we designed and implemented an ultra-wide bandwidth low-frequency pulsar data processing pipeline(UWLPIPE)based on the shared ringbuf...For real-time processing of ultra-wide bandwidth low-frequency pulsar baseband data,we designed and implemented an ultra-wide bandwidth low-frequency pulsar data processing pipeline(UWLPIPE)based on the shared ringbuffer and GPU parallel technology.UWLPIPE runs on the GPU cluster and can simultaneously receive multiple 128 MHz dual-polarization VDIF data packets preprocessed by the front-end FPGA.After aligning the dual-polarization data,multiple 128M subband data are packaged into PSRDADA baseband data or multi-channel coherent dispersion filterbank data,and multiple subband filterbank data can be spliced into wideband data after time alignment.We used the Nanshan 26 m radio telescope with the L-band receiver at964~1732 MHz to observe multiple pulsars.Finally,we processed the data using DSPSR software,and the results showed that each subband could correctly fold out the pulse profile,and the wideband pulse profile accumulated by multiple subbands could be correctly aligned.展开更多
Cross-matching is a key technique to achieve fusion of multi-band astronomical catalogs. Due to different equipment such as various astronomical telescopes, the existence of measurement errors, and proper motions of t...Cross-matching is a key technique to achieve fusion of multi-band astronomical catalogs. Due to different equipment such as various astronomical telescopes, the existence of measurement errors, and proper motions of the celestial bodies, the same celestial object will have different positions in different catalogs, making it difficult to integrate multi-band or full-band astronomical data. In this study, we propose an online cross-matching method based on pseudo-spherical indexing techniques and develop a service combining with high performance computing system(Taurus) to improve cross-matching efficiency, which is designed for the Data Center of Xinjiang Astronomical Observatory. Specifically, we use Quad Tree Cube to divide the spherical blocks of the celestial object and map the 2D space composed of R.A. and decl. to 1D space and achieve correspondence between real celestial objects and spherical patches. Finally, we verify the performance of the service using Gaia 3 and PPMXL catalogs. Meanwhile, we send the matching results to VO tools-Topcat and Aladin respectively to get visual results. The experimental results show that the service effectively solves the speed bottleneck problem of crossmatching caused by frequent I/O, and significantly improves the retrieval and matching speed of massive astronomical data.展开更多
To address the problem of real-time processing of ultra-wide bandwidth pulsar baseband data,we designed and implemented a pulsar baseband data processing algorithm(PSRDP)based on GPU parallel computing technology.PSRD...To address the problem of real-time processing of ultra-wide bandwidth pulsar baseband data,we designed and implemented a pulsar baseband data processing algorithm(PSRDP)based on GPU parallel computing technology.PSRDP can perform operations such as baseband data unpacking,channel separation,coherent dedispersion,Stokes detection,phase and folding period prediction,and folding integration in GPU clusters.We tested the algorithm using the J0437-4715 pulsar baseband data generated by the CASPSR and Medusa backends of the Parkes,and the J0332+5434 pulsar baseband data generated by the self-developed backend of the Nan Shan Radio Telescope.We obtained the pulse profiles of each baseband data.Through experimental analysis,we have found that the pulse profiles generated by the PSRDP algorithm in this paper are essentially consistent with the processing results of Digital Signal Processing Software for Pulsar Astronomy(DSPSR),which verified the effectiveness of the PSRDP algorithm.Furthermore,using the same baseband data,we compared the processing speed of PSRDP with DSPSR,and the results showed that PSRDP was not slower than DSPSR in terms of speed.The theoretical and technical experience gained from the PSRDP algorithm research in this article lays a technical foundation for the real-time processing of QTT(Qi Tai radio Telescope)ultra-wide bandwidth pulsar baseband data.展开更多
Objective:To evaluate the clinical therapeutic effect on mammary hyperplasia of electroacupuncture(EA)combined with scraping therapy.Methods:A total of 54 patients with mammary hyperplasia were adopted EA combined wit...Objective:To evaluate the clinical therapeutic effect on mammary hyperplasia of electroacupuncture(EA)combined with scraping therapy.Methods:A total of 54 patients with mammary hyperplasia were adopted EA combined with scraping therapy.Two groups of acupoints were selected.One group is Wuyi(屋翳ST15),Danzhong(膻中CV17)and Hegu(合谷LI4),EA was applied to these acupoints.Anothor group is Tianzong(天宗SI11),Jianjing(肩井GB21)and Ganshu(肝俞BL18),scraping therapy was applied to these points.Other acupoints were accompanied to.Ten times of treatments were as one course,at the interval of 1 week among the treatment courses.Totally,3 courses were required.Before and after treatment,the score of the symptoms of mammary hyperplasia,the grade and score of breast lumps and the levels of follicle-stimulating hormone(FSH),luteinizing hormone(LH)and estradiol(E2)were evaluated in the patients.Results:Compared with the scores before treatment,the scores of the symptoms of mammary hyperplasia and breast lumps were all reduced in the patients,indicating the statistical significant differences(all P<0.05).Compared with the levels before treatment,the levels of FSH,LH and E2 were all reduced in the patients,indicating the statistical significant differences(all P<0.05).The total effective rate was 92.59%after treatment.Conclusion:Electroacupuncture combined with scraping therapy achieves a satisfactory clinical effect on mammary hyperplasia.展开更多
Novel double hydrophilic block copolymers with amine pendant chains were synthesized by polymerization of 4-vinyl benzylamine hydrochloric salt using 4,4′-azo-bis[4-cyanopentanoate poly（ethylene glycol） ester] as m...Novel double hydrophilic block copolymers with amine pendant chains were synthesized by polymerization of 4-vinyl benzylamine hydrochloric salt using 4,4′-azo-bis[4-cyanopentanoate poly（ethylene glycol） ester] as macroazoinitiator. The structures of the copolymers were characterized by ^1H NMR, FTIR spectra and acid-base titration, GPC-MALS techniques.展开更多
The synergistic effect of H_3PMo_(12)O_(40) or H_3PW_(12)O_(40) polyoxometalate solution(POM) and TiO_2 to catalyze formic acid oxidation was investigated. Under UV irradiation, hole and electron were photogenerated b...The synergistic effect of H_3PMo_(12)O_(40) or H_3PW_(12)O_(40) polyoxometalate solution(POM) and TiO_2 to catalyze formic acid oxidation was investigated. Under UV irradiation, hole and electron were photogenerated by TiO_2. Formic acid was oxided by the photogenerated hole and photogenerated electron was transferred to reduce polyoxometalate. With this design, formic acid can be converted into electricity in the fuel cell and hydrogen can be generated in the electrolysis cell without noble metal catalyst. Unlike other noble metal catalysts applied in the fuel cells and electrolysis cell, POM and TiO_2 are stable and low cost. The maximum output power density of liquid formic acid fuel cell after 12 h UV irradiation is 5.21 mW/cm^2 for phosphmolybdic acid and 22.81 m W/cm^2 for phosphotungstic acid respectively. The applied potential for the hydrogen evolution is as low as 0.8 V for phosphmolybdic acid and 0.6 V for phosphotungstic acid.展开更多
基金supported by the National Key R&D Program of China(2021YFC2203502 and 2022YFF0711502)the National Natural Science Foundation of China(NSFC)(12173077)+4 种基金the Tianshan Talent Project of Xinjiang Uygur Autonomous Region(2022TSYCCX0095 and 2023TSYCCX0112)the Scientific Instrument Developing Project of the Chinese Academy of Sciences(PTYQ2022YZZD01)China National Astronomical Data Center(NADC)the Operation,Maintenance and Upgrading Fund for Astronomical Telescopes and Facility Instruments,budgeted from the Ministry of Finance of China(MOF)and administrated by the Chinese Academy of Sciences(CAS)Natural Science Foundation of Xinjiang Uygur Autonomous Region(2022D01A360)。
文摘As artificial intelligence(AI)technology has continued to develop,its efficient data processing and pattern recognition capabilities have significantly improved the precision and speed of decision-making processes,and it has been widely applied across various fields.In the field of astronomy,AI techniques have demonstrated unique advantages,particularly in the identification of pulsars and their candidates.AI is able to address the challenges of pulsar celestial body identification and classification because of its accuracy and efficiency.This paper systematically surveys commonly used AI models for pulsar candidate identification,analyzing and discussing the typical applications of machine learning,artificial neural networks,convolutional neural networks,and generative adversarial networks in candidate identification.Furthermore,it explores how th.e introduction of AI techniques not only enhances the efficiency and accuracy of pulsar identification but also provides new perspectives and tools for pulsar survey data processing,thus playing a significant role in advancing pulsar research and the field of astronomy.
基金supported by the National Key R&D Program of China Nos.2021YFC2203502 and 2022YFF0711502the National Natural Science Foundation of China(NSFC)(12173077)+5 种基金the Chinese Academy of Sciences(CAS)“Light of West China”Program(No.xbzg-zdsys-202410)the Tianshan Talent Project of Xinjiang Uygur Autonomous Region(2022TSYCCX0095 and 2023TSYCCX0112)the Scientific Instrument Developing Project of the Chinese Academy of Sciences,grant No.PTYQ2022YZZD01China National Astronomical Data Center(NADC)the Operation,Maintenance and Upgrading Fund for Astronomical Telescopes and Facility Instruments,budgeted from the Ministry of Finance of China(MOF)and administrated by the Chinese Academy of Sciences(CAS)Natural Science Foundation of Xinjiang Uygur Autonomous Region(2022D01A360).
文摘To address the issues of low accuracy and high computational complexity in traditional channelization techniques for ultra-wideband signals,this paper proposes a novel rationally oversampled channelization method to enhance the accuracy and efficiency of signal processing.The proposed method is evaluated by implementing and comparing critically sampled and integer oversampled channelization algorithms.A detailed analysis of the impact of different oversampling factors and filter orders on performance is provided.The validity of the proposed algorithm is verified using baseband data from pulsar J0437−4715 observed by the Parkes telescope,demonstrating its effectiveness and correctness.
基金supported by the National Key R&D Program of China(2021YFC2203502 and 2022YFF0711502)the National Natural Science Foundation of China(NSFC)(12173077)+4 种基金the Tianshan Talent Project of Xinjiang Uygur Autonomous Region(2022TSYCCX0095 and 2023TSYCCX0112)the Scientific Instrument Developing Project of the Chinese Academy of Sciences(PTYQ2022YZZD01)China National Astronomical Data Center(NADC)the Operation,Maintenance and Upgrading Fund for Astronomical Telescopes and Facility Instruments,budgeted from the Ministry of Finance of China(MOF)and administrated by the Chinese Academy of SciencesNatural Science Foundation of Xinjiang Uygur Autonomous Region(2022D01A360).
文摘Astronomical spectroscopy is crucial for exploring the physical properties,chemical composition,and kinematic behavior of celestial objects.With continuous advancements in observational technology,astronomical spectroscopy faces the dual challenges of rapidly expanding data volumes and relatively lagging data processing capabilities.In this context,the rise of artificial intelligence technologies offers an innovative solution to address these challenges.This paper analyzes the latest developments in the application of machine learning for astronomical spectral data mining and discusses future research directions in AI-based spectral studies.However,the application of machine learning technologies presents several challenges.The high complexity of models often comes with insufficient interpretability,complicating scientific understanding.Moreover,the large-scale computational demands place higher requirements on hardware resources,leading to a significant increase in computational costs.AI-based astronomical spectroscopy research should advance in the following key directions.First,develop efficient data augmentation techniques to enhance model generalization capabilities.Second,explore more interpretable model designs to ensure the reliability and transparency of scientific conclusions.Third,optimize computational efficiency and reduce the threshold for deep-learning applications through collaborative innovations in algorithms and hardware.Furthermore,promoting the integration of cross-band data processing is essential to achieve seamless integration and comprehensive analysis of multi-source data,providing richer,multidimensional information to uncover the mysteries of the universe.
基金Project supported by the Guangdong Innovative and Entrepreneurial Research Team Program,China(Grant No.2016ZT06D348)the National Natural Science Foundation of China(Grant No.11874193)the Shenzhen Fundamental Subject Research Program,China(Grant Nos.JCYJ20170817110751776 and JCYJ20170307105434022)
文摘Recently, the layered transition metal dichalcogenide 1 T MoTe2 has attracted considerable attention due to its non-saturating magnetoresistance, type-II Weyl semimetal properties, superconductivity, and potential candidate for twodimensional（2 D） topological insulator in the single-and few-layer limit. Here in this work, we perform systematic transport measurements on thin flakes of MoTe2 prepared by mechanical exfoliation. We find that MoTe2 flakes are superconducting and have an onset superconducting transition temperature Tc up to 5.3 K, which significantly exceeds that of its bulk counterpart. The in-plane upper critical field(Hc2||) is much higher than the Pauli paramagnetic limit, implying that the MoTe2 flakes have Zeeman-protected Ising superconductivity. Furthermore, the Tc and Hc2|| can be tuned by up to 320 mK and 400 mT by applying a gate voltage. Our result indicates that MoTe2 flake is a good candidate for studying exotic superconductivity with nontrivial topological properties.
基金This work is supported by National Key R&D Program of China No.2021YFC2203502 and 2022YFF0711502the National Natural Science Foundation of China(NSFC)(12173077 and 12003062)+5 种基金the Tianshan Innovation Team Plan of Xinjiang Uygur Autonomous Region(2022D14020)the Tianshan Talent Project of Xinjiang Uygur Autonomous Region(2022TSYCCX0095)the Scientific Instrument Developing Project of the Chinese Academy of Sciences,Grant No.PTYQ2022YZZD01China National Astronomical Data Center(NADC)the Operation,Maintenance and Upgrading Fund for Astronomical Telescopes and Facility Instruments,budgeted from the Ministry of Finance of China(MOF)and administrated by the Chinese Academy of Sciences(CAS)Natural Science Foundation of Xinjiang Uygur Autonomous Region(2022D01A360).
文摘Artificial Intelligence(AI)is an interdisciplinary research field with widespread applications.It aims at developing theoretical,methodological,technological,and applied systems that simulate,enhance,and assist human intelligence.Recently,notable accomplishments of artificial intelligence technology have been achieved in astronomical data processing,establishing this technology as central to numerous astronomical research areas such as radio astronomy,stellar and galactic(Milky Way)studies,exoplanets surveys,cosmology,and solar physics.This article systematically reviews representative applications of artificial intelligence technology to astronomical data processing,with comprehensive description of specific cases:pulsar candidate identification,fast radio burst detection,gravitational wave detection,spectral classification,and radio frequency interference mitigation.Furthermore,it discusses possible future applications to provide perspectives for astronomical research in the artificial intelligence era.
基金supported by the National Key R&D Program of China(Nos.2021YFC2203502 and 2022YFF0711502)the National Natural Science Foundation of China(NSFC)(12173077 and 12073067)+7 种基金the Tianshan Innovation Team Plan of Xinjiang Uygur Autonomous Region(2022D14020)the Tianshan Talent Project of Xinjiang Uygur Autonomous Region(2022TSYCCX0095)the Scientific Instrument Developing Project of the Chinese Academy of Sciences(grant No.PTYQ2022YZZD01)China National Astronomical Data Center(NADC)the Operation,Maintenance and Upgrading Fund for Astronomical Telescopes and Facility Instruments,budgeted from the Ministry of Finance of China(MOF)and administrated by the Chinese Academy of Sciences(CAS)Natural Science Foundation of Xinjiang Uygur AutonomousRegion(2022D01A360)the CAS“Light of West China”program under No.2022-XBQNXZ-012supported by Astronomical Big Data Joint Research Center,cofounded by National Astronomical Observatories,Chinese Academy of Sciences。
文摘The radio telescope possesses high sensitivity and strong signal collection capabilities.While receiving celestial radiation signals,it also captures Radio Frequency Interferences(RFIs)introduced by human activities.RFI,as signals originating from sources other than the astronomical targets,significantly impacts the quality of astronomical data.This paper presents an RFI fast mitigation algorithm based on block Least Mean Square(LMS)algorithm.It enhances the traditional adaptive LMS filter by grouping L adjacent time-sampled points into one block and applying the same filter coefficients for filtering within each block.This transformation reduces multiplication calculations and enhances algorithm efficiency by leveraging the time-domain convolution theorem.The algorithm is tested using baseband data from the Parkes 64 m radio telescope's pulsar observations and simulated data.The results confirm the algorithm's effectiveness,as the pulsar profile after RFI mitigation closely matches the original pulsar profile.
基金supported by the National Key R&D Program of China Nos.2021YFC2203502 and 2022YFF0711502the National Natural Science Foundation of China(NSFC,grant Nos.12173077,12073067)+4 种基金the Tianshan Talent Project of Xinjiang Uygur Autonomous Region(2022TSYCCX0095 and2023TSYCCX0112)the Scientific Instrument Developing Project of the Chinese Academy of Sciences,grant No.PTYQ2022YZZD01China National Astronomical Data Center(NADC)the Operation,Maintenance and Upgrading Fund for Astronomical Telescopes and Facility Instruments,budgeted from the Ministry of Finance of China(MOF)and administrated by the Chinese Academy of Sciences(CAS)Natural Science Foundation of Xinjiang Uygur Autonomous Region(2022D01A360)。
文摘We propose a multi-source radio frequency interference(RFI)mitigation method based on a reference antenna array to address the challenge of RFI from multiple directions in radio observation equipment.It introduces a sampling point correction technique using a multi-channel parallel cross-correlation computation method,enhancing the effectiveness of frequency domain adaptive RFI fast mitigation algorithms.The design implements an RFI component detection method based on cross-correlation coefficient thresholds to effectively reduce new interference frequency components introduced by the reference antenna array.Simulated RFI signals and baseband signals of pulsar J0332+5434 observed by the Nanshan 26 m Radio Telescope(NSRT)were used to test the algorithm proposed in this paper.Simulation results demonstrate that the simulated radio telescope signals after RFI mitigation closely match the original pulsar data in profile and phase,confirming the effectiveness of the proposed method.
基金supported by the National Key R&D Program of China Nos.2021YFC2203502 and 2022YFF0711502the National Natural Science Foundation of China(NSFC)(12173077)+4 种基金the Tianshan Talent Project of Xinjiang Uygur Autonomous Region(2022TSYCCX0095 and2023TSYCCX0112)the Scientific Instrument Developing Project of the Chinese Academy of Sciences,grant No.PTYQ2022YZZD01China National Astronomical Data Center(NADC)the Operation,Maintenance and Upgrading Fund for Astronomical Telescopes and Facility Instruments,budgeted from the Ministry of Finance of China(MOF)and administrated by the Chinese Academy of Sciences(CAS)Natural Science Foundation of Xinjiang Uygur Autonomous Region(2022D01A360)。
文摘For real-time processing of ultra-wide bandwidth low-frequency pulsar baseband data,we designed and implemented an ultra-wide bandwidth low-frequency pulsar data processing pipeline(UWLPIPE)based on the shared ringbuffer and GPU parallel technology.UWLPIPE runs on the GPU cluster and can simultaneously receive multiple 128 MHz dual-polarization VDIF data packets preprocessed by the front-end FPGA.After aligning the dual-polarization data,multiple 128M subband data are packaged into PSRDADA baseband data or multi-channel coherent dispersion filterbank data,and multiple subband filterbank data can be spliced into wideband data after time alignment.We used the Nanshan 26 m radio telescope with the L-band receiver at964~1732 MHz to observe multiple pulsars.Finally,we processed the data using DSPSR software,and the results showed that each subband could correctly fold out the pulse profile,and the wideband pulse profile accumulated by multiple subbands could be correctly aligned.
基金supported by the National Key R&D Program of China (Nos. 2022YFF0711502 and 2021YFC2203502)the National Natural Science Foundation of China (NSFC)(12173077 and 12003062)+6 种基金the Tianshan Innovation Team Plan of Xinjiang Uygur Autonomous Region (2022D14020)the Tianshan Talent Project of Xinjiang Uygur Autonomous Region(2022TSYCCX0095)the Scientific Instrument Developing Project of the Chinese Academy of Sciences (grant No. PTYQ2022YZZD01)China National Astronomical Data Center (NADC)the Operation,Maintenance and Upgrading Fund for Astronomical Telescopes and Facility Instruments,budgeted from the Ministry of Finance of China (MOF)and administrated by the Chinese Academy of Sciences (CAS)Natural Science Foundation of Xinjiang Uygur Autonomous Region (2022D01A360)supported by Astronomical Big Data Joint Research Center,co-founded by National Astronomical Observatories,Chinese Academy of Sciences。
文摘Cross-matching is a key technique to achieve fusion of multi-band astronomical catalogs. Due to different equipment such as various astronomical telescopes, the existence of measurement errors, and proper motions of the celestial bodies, the same celestial object will have different positions in different catalogs, making it difficult to integrate multi-band or full-band astronomical data. In this study, we propose an online cross-matching method based on pseudo-spherical indexing techniques and develop a service combining with high performance computing system(Taurus) to improve cross-matching efficiency, which is designed for the Data Center of Xinjiang Astronomical Observatory. Specifically, we use Quad Tree Cube to divide the spherical blocks of the celestial object and map the 2D space composed of R.A. and decl. to 1D space and achieve correspondence between real celestial objects and spherical patches. Finally, we verify the performance of the service using Gaia 3 and PPMXL catalogs. Meanwhile, we send the matching results to VO tools-Topcat and Aladin respectively to get visual results. The experimental results show that the service effectively solves the speed bottleneck problem of crossmatching caused by frequent I/O, and significantly improves the retrieval and matching speed of massive astronomical data.
基金supported by the National Key R&D Program of China Nos.2021YFC2203502 and 2022YFF0711502the National Natural Science Foundation of China(NSFC)(12173077 and 12003062)+5 种基金the Tianshan Innovation Team Plan of Xinjiang Uygur Autonomous Region(2022D14020)the Tianshan Talent Project of Xinjiang Uygur Autonomous Region(2022TSYCCX0095)the Scientific Instrument Developing Project of the Chinese Academy of Sciences,grant No.PTYQ2022YZZD01China National Astronomical Data Center(NADC)the Operation,Maintenance and Upgrading Fund for Astronomical Telescopes and Facility Instruments,budgeted from the Ministry of Finance of China(MOF)and administrated by the Chinese Academy of Sciences(CAS)Natural Science Foundation of Xinjiang Uygur Autonomous Region(2022D01A360)。
文摘To address the problem of real-time processing of ultra-wide bandwidth pulsar baseband data,we designed and implemented a pulsar baseband data processing algorithm(PSRDP)based on GPU parallel computing technology.PSRDP can perform operations such as baseband data unpacking,channel separation,coherent dedispersion,Stokes detection,phase and folding period prediction,and folding integration in GPU clusters.We tested the algorithm using the J0437-4715 pulsar baseband data generated by the CASPSR and Medusa backends of the Parkes,and the J0332+5434 pulsar baseband data generated by the self-developed backend of the Nan Shan Radio Telescope.We obtained the pulse profiles of each baseband data.Through experimental analysis,we have found that the pulse profiles generated by the PSRDP algorithm in this paper are essentially consistent with the processing results of Digital Signal Processing Software for Pulsar Astronomy(DSPSR),which verified the effectiveness of the PSRDP algorithm.Furthermore,using the same baseband data,we compared the processing speed of PSRDP with DSPSR,and the results showed that PSRDP was not slower than DSPSR in terms of speed.The theoretical and technical experience gained from the PSRDP algorithm research in this article lays a technical foundation for the real-time processing of QTT(Qi Tai radio Telescope)ultra-wide bandwidth pulsar baseband data.
文摘Objective:To evaluate the clinical therapeutic effect on mammary hyperplasia of electroacupuncture(EA)combined with scraping therapy.Methods:A total of 54 patients with mammary hyperplasia were adopted EA combined with scraping therapy.Two groups of acupoints were selected.One group is Wuyi(屋翳ST15),Danzhong(膻中CV17)and Hegu(合谷LI4),EA was applied to these acupoints.Anothor group is Tianzong(天宗SI11),Jianjing(肩井GB21)and Ganshu(肝俞BL18),scraping therapy was applied to these points.Other acupoints were accompanied to.Ten times of treatments were as one course,at the interval of 1 week among the treatment courses.Totally,3 courses were required.Before and after treatment,the score of the symptoms of mammary hyperplasia,the grade and score of breast lumps and the levels of follicle-stimulating hormone(FSH),luteinizing hormone(LH)and estradiol(E2)were evaluated in the patients.Results:Compared with the scores before treatment,the scores of the symptoms of mammary hyperplasia and breast lumps were all reduced in the patients,indicating the statistical significant differences(all P<0.05).Compared with the levels before treatment,the levels of FSH,LH and E2 were all reduced in the patients,indicating the statistical significant differences(all P<0.05).The total effective rate was 92.59%after treatment.Conclusion:Electroacupuncture combined with scraping therapy achieves a satisfactory clinical effect on mammary hyperplasia.
文摘Novel double hydrophilic block copolymers with amine pendant chains were synthesized by polymerization of 4-vinyl benzylamine hydrochloric salt using 4,4′-azo-bis[4-cyanopentanoate poly（ethylene glycol） ester] as macroazoinitiator. The structures of the copolymers were characterized by ^1H NMR, FTIR spectra and acid-base titration, GPC-MALS techniques.
文摘The synergistic effect of H_3PMo_(12)O_(40) or H_3PW_(12)O_(40) polyoxometalate solution(POM) and TiO_2 to catalyze formic acid oxidation was investigated. Under UV irradiation, hole and electron were photogenerated by TiO_2. Formic acid was oxided by the photogenerated hole and photogenerated electron was transferred to reduce polyoxometalate. With this design, formic acid can be converted into electricity in the fuel cell and hydrogen can be generated in the electrolysis cell without noble metal catalyst. Unlike other noble metal catalysts applied in the fuel cells and electrolysis cell, POM and TiO_2 are stable and low cost. The maximum output power density of liquid formic acid fuel cell after 12 h UV irradiation is 5.21 mW/cm^2 for phosphmolybdic acid and 22.81 m W/cm^2 for phosphotungstic acid respectively. The applied potential for the hydrogen evolution is as low as 0.8 V for phosphmolybdic acid and 0.6 V for phosphotungstic acid.
