With the continuous development of the mining industry,the number of abandoned mines is increasing,which brings many impacts on the geology and ecological environment around the mines.It is urgent to attach great impo...With the continuous development of the mining industry,the number of abandoned mines is increasing,which brings many impacts on the geology and ecological environment around the mines.It is urgent to attach great importance to the ecological management and environmental restoration of abandoned mines.The long-term traditional development path of rural areas,following the model of“pollution first,treatment later,”fails to meet the needs of sustainable development.The contradiction between mine economic development and ecological environment degradation is becoming increasingly prominent,which urgently needs to be solved.Under the guidance of the Party and the state,in order to implement the relevant policies of“green mountains and clear waters are gold and silver mountains,”we emphasize rural green development,and the transformation of rural green development path is imperative.This paper takes Datu Mine in Xinhe Village,Dadukou District,Chongqing as the research object,combines rural ecological development as the research basis,and innovatively integrates the“educational research”model,aiming to provide practical strategies for the sustainable development of rural landscapes in abandoned mines.展开更多
We use the Fe Kα emission in X-rays from non-equilibrium ionizing plasmas as a probe to explore the dust in supernova remnants(SNRs). We applied our model to Cassiopeia A(Cas A), a well-studied SNR with plenty of obs...We use the Fe Kα emission in X-rays from non-equilibrium ionizing plasmas as a probe to explore the dust in supernova remnants(SNRs). We applied our model to Cassiopeia A(Cas A), a well-studied SNR with plenty of observational data as a test. We use Chandra Advanced CCD Imaging Spectrometer 980 ks data of Cas A, and AtomDB v3.0.9, an atomic database for X-ray plasma spectral modeling, to fit 248 spectra. A two-temperature model is adopted to describe the physical conditions of shocked ejecta and iron-rich plasma. We measure the Fe Kα flux ratio and the centroid difference of the dust and gas contributions. We find strong 6.4 keV line emission components, which indicates that iron-rich dust can survive within Cas A's shocked ejecta. We also find that the Fe Kα complex demonstrates an apparent double-hump structure in some Fe–K rich regions, which may be caused by both dust and multi-ejecta structure in Cas A. The results of Fe Kα structures are consistent with our model for a dust cloud embedded in multi-phase ejecta and suggest the presence of both dust sputtering and drag effects in those regions. It is currently still limited by the low spatial and spectrum resolution for the current X-ray detectors, but should be more useful when the new generation, high-resolution X-ray telescopes come into service.展开更多
Objective To map the research hotspots,developmental trends,and existing challenges in the integration of artificial intelligence(AI)with multi-omics in traditional Chinese medicine(TCM)through comprehensive bibliomet...Objective To map the research hotspots,developmental trends,and existing challenges in the integration of artificial intelligence(AI)with multi-omics in traditional Chinese medicine(TCM)through comprehensive bibliometric analysis.Methods China National Knowledge Infrastructure(CNKI),Wanfang Data,China Science and Technology Journal Database(VIP),Chaoxing Journal Database,PubMed,and Web of Science were searched to collect literature on the theme of AI in TCM multi-omics research from the inception of each database to December 31,2024.Eligible records were required to simultaneously address AI,TCM,and multi-omics.Quantitative and visual analyses of publication growth,core authorship networks,institutional collaboration patterns,and keyword co-occurrence were performed using Microsoft Excel 2021,NoteExpress v4.0.0,and Cite-Space 6.3.R1.AI application modes in TCM multi-omics research were also categorized and summarized.Results A total of 1106 articles were enrolled(932 Chinese and 174 English).Publication output has increased continuously since 2010 and accelerated after 2016.Region-specific collaboration clusters were identified,dominated by Beijing University of Chinese Medicine,China Academy of Chinese Medical Sciences,Shanghai University of Traditional Chinese Medicine,and Nanjing University of Chinese Medicine.Keyword co-occurrence analysis revealed that current AI applications predominantly centered on metabolomics and algorithms such as cluster analysis and data mining.Research foci mainly ranked as follows:single herbs,herbal formulae,and disease-syndrome differentiation.Conclusion Machine learning methods are the predominant integrative modality of AI in the realm of TCM multi-omics research at present,utilized for processing omics data and uncovering latent patterns therein.The domain of TCM,in addition to investigating omics information procured through high-throughput technologies,also integrates data on traditional Chinese medicinal substances and clinical phenotypes,progressing towards joint analysis of multi-omics,high-dimensionality of data,and multi-modality of information.Deep learning approaches represent an emerging trend in the field.展开更多
Since the new era in China,the long-term traditional rural development path,characterized by the“pollute first,treat later”model,has proven insufficient to meet the needs of sustainable development.The growing contr...Since the new era in China,the long-term traditional rural development path,characterized by the“pollute first,treat later”model,has proven insufficient to meet the needs of sustainable development.The growing contradiction between rural economic development and ecological environmental degradation urgently needs to be addressed.Under the guidance of the Party and the state,there is a strong emphasis on green rural development,making the transformation of the rural green development path imperative.This paper takes rural ecological development as the research basis and innovatively integrates the“educational research”model,aiming to provide practical strategies for the sustainable development of abandoned mine rural landscapes.Taking Datukuang in Xinhe Village,Dadukou District,Chongqing as an example,this project breaks through the technical path dependence of traditional engineering restoration,creatively implants research function modules such as natural education,geological science popularization,and ecological experience,transforming the abandoned mine pit into a composite ecological education demonstration base integrating environmental restoration,science popularization education,and cultural tourism experience.It has opened up a new paradigm for rural revitalization with“mine restoration+research economy”,providing an innovative practice sample for solving the transformation dilemma of resource-based villages.展开更多
Premenstrual dysphoric disorder(PMDD) affects nearly 5% of women of reproductive age. Symptomatic heterogeneity, together with largely unknown genetics, has greatly hindered its effective treatment. In the present stu...Premenstrual dysphoric disorder(PMDD) affects nearly 5% of women of reproductive age. Symptomatic heterogeneity, together with largely unknown genetics, has greatly hindered its effective treatment. In the present study, analysis of genomic sequencing-based copy number variations(CNVs) called from 100 kb white blood cell DNA sequence windows by means of semisupervized clustering led to the segregation of patient genomes into the D and V groups, which correlated with the depression and invasion clinical types,respectively, with 89.0% consistency. Application of diagnostic CNV features selected using the correlation-based machine learning method enabled the classification of the CNVs obtained into the D group, V group, total patient group, and control group with an average accuracy of 83.0%. The power of the diagnostic CNV features was 0.98 on average, suggesting that these CNV features could be used for the molecular diagnosis of the major clinical types of PMDD. This demonstrated concordance between the CNV profiles and clinical types of PMDD supported the validity of symptom-based diagnosis of PMDD for differentiating between its two major clinical types, as well as the predominantly genetic nature of PMDD with a host of overlaps between multiple susceptibility genes/pathways and the diagnostic CNV features as indicators of involvement in PMDD etiology.展开更多
基金National Innovation Training Project“Landscape Design of Educational Research Base Based on Mine Ecological Restoration:Taking the Restoration of Datu Mine in Xinhe Village,Dadukou District as an Example”(202312608002X)Chongqing Institute of Engineering Innovation Training Project“Yitian Xuegu”Innovative Design Research on Rural Education Practice Base in Longhe Town,Fengdu CountyChongqing Institute of Engineering School-Level Topic“Research on Urban Waterfront Landscape Design Based on the Concept of River Ecological Restoration:Taking the Section of Huaxi River in Chongqing Institute of Engineering as an Example”(2022xskz02)。
文摘With the continuous development of the mining industry,the number of abandoned mines is increasing,which brings many impacts on the geology and ecological environment around the mines.It is urgent to attach great importance to the ecological management and environmental restoration of abandoned mines.The long-term traditional development path of rural areas,following the model of“pollution first,treatment later,”fails to meet the needs of sustainable development.The contradiction between mine economic development and ecological environment degradation is becoming increasingly prominent,which urgently needs to be solved.Under the guidance of the Party and the state,in order to implement the relevant policies of“green mountains and clear waters are gold and silver mountains,”we emphasize rural green development,and the transformation of rural green development path is imperative.This paper takes Datu Mine in Xinhe Village,Dadukou District,Chongqing as the research object,combines rural ecological development as the research basis,and innovatively integrates the“educational research”model,aiming to provide practical strategies for the sustainable development of rural landscapes in abandoned mines.
基金supported by a GRF grant of the Hong Kong Government under HKU 17304524.
文摘We use the Fe Kα emission in X-rays from non-equilibrium ionizing plasmas as a probe to explore the dust in supernova remnants(SNRs). We applied our model to Cassiopeia A(Cas A), a well-studied SNR with plenty of observational data as a test. We use Chandra Advanced CCD Imaging Spectrometer 980 ks data of Cas A, and AtomDB v3.0.9, an atomic database for X-ray plasma spectral modeling, to fit 248 spectra. A two-temperature model is adopted to describe the physical conditions of shocked ejecta and iron-rich plasma. We measure the Fe Kα flux ratio and the centroid difference of the dust and gas contributions. We find strong 6.4 keV line emission components, which indicates that iron-rich dust can survive within Cas A's shocked ejecta. We also find that the Fe Kα complex demonstrates an apparent double-hump structure in some Fe–K rich regions, which may be caused by both dust and multi-ejecta structure in Cas A. The results of Fe Kα structures are consistent with our model for a dust cloud embedded in multi-phase ejecta and suggest the presence of both dust sputtering and drag effects in those regions. It is currently still limited by the low spatial and spectrum resolution for the current X-ray detectors, but should be more useful when the new generation, high-resolution X-ray telescopes come into service.
基金General Project of Scientific Research of Hunan Provincial Education Department (22C0191)General Project of University-level Scientific Research of Hunan University of Chinese Medicine (Z2023XJYB21)Hunan Provincial Degree and Graduate Education Reform Research Project(2024JGYB157)。
文摘Objective To map the research hotspots,developmental trends,and existing challenges in the integration of artificial intelligence(AI)with multi-omics in traditional Chinese medicine(TCM)through comprehensive bibliometric analysis.Methods China National Knowledge Infrastructure(CNKI),Wanfang Data,China Science and Technology Journal Database(VIP),Chaoxing Journal Database,PubMed,and Web of Science were searched to collect literature on the theme of AI in TCM multi-omics research from the inception of each database to December 31,2024.Eligible records were required to simultaneously address AI,TCM,and multi-omics.Quantitative and visual analyses of publication growth,core authorship networks,institutional collaboration patterns,and keyword co-occurrence were performed using Microsoft Excel 2021,NoteExpress v4.0.0,and Cite-Space 6.3.R1.AI application modes in TCM multi-omics research were also categorized and summarized.Results A total of 1106 articles were enrolled(932 Chinese and 174 English).Publication output has increased continuously since 2010 and accelerated after 2016.Region-specific collaboration clusters were identified,dominated by Beijing University of Chinese Medicine,China Academy of Chinese Medical Sciences,Shanghai University of Traditional Chinese Medicine,and Nanjing University of Chinese Medicine.Keyword co-occurrence analysis revealed that current AI applications predominantly centered on metabolomics and algorithms such as cluster analysis and data mining.Research foci mainly ranked as follows:single herbs,herbal formulae,and disease-syndrome differentiation.Conclusion Machine learning methods are the predominant integrative modality of AI in the realm of TCM multi-omics research at present,utilized for processing omics data and uncovering latent patterns therein.The domain of TCM,in addition to investigating omics information procured through high-throughput technologies,also integrates data on traditional Chinese medicinal substances and clinical phenotypes,progressing towards joint analysis of multi-omics,high-dimensionality of data,and multi-modality of information.Deep learning approaches represent an emerging trend in the field.
基金National Innovation Training Project-Landscape Design of Educational Research Base Based on Mine Ecological Restoration(Project No.:202312608002X)Chongqing Engineering College School-level Project:Research on Urban Waterside Landscape Design Based on the Concept of River Ecological Restoration-Taking the Section of Chongqing Engineering College of Huaxi River as an Example(Project No.:2022xskz02)Chongqing Engineering College Innovation Training Project:Innovative Design Research of“Yitian Xuegu”Fengdu County Longhe Town Rural Education Practice Base(Project No.:CXCY2024011)。
文摘Since the new era in China,the long-term traditional rural development path,characterized by the“pollute first,treat later”model,has proven insufficient to meet the needs of sustainable development.The growing contradiction between rural economic development and ecological environmental degradation urgently needs to be addressed.Under the guidance of the Party and the state,there is a strong emphasis on green rural development,making the transformation of the rural green development path imperative.This paper takes rural ecological development as the research basis and innovatively integrates the“educational research”model,aiming to provide practical strategies for the sustainable development of abandoned mine rural landscapes.Taking Datukuang in Xinhe Village,Dadukou District,Chongqing as an example,this project breaks through the technical path dependence of traditional engineering restoration,creatively implants research function modules such as natural education,geological science popularization,and ecological experience,transforming the abandoned mine pit into a composite ecological education demonstration base integrating environmental restoration,science popularization education,and cultural tourism experience.It has opened up a new paradigm for rural revitalization with“mine restoration+research economy”,providing an innovative practice sample for solving the transformation dilemma of resource-based villages.
基金supported by grants to HX from University Grants Council(SRF116SC01UROP18SC06+10 种基金UROP20SC07)Innovation and Technology Commission(ITS/085/10ITS113/15FPITCPD/17-9ITT/023/17GPITT/026/18GP)of Hong Kong SARShenzhen Municipal Council of Science and Technology,Guangdong(JCYJ20170818113656988)Guangdong Province Basic and Applied Basic Research Fund(2021A1515011169)Shandong Province First Class Disciple Development Grant and Tai-Shan Scholar Program,Shandongand Ministry of Science and Technology(National Science and Technology Major Project,No.2017ZX09301064,2017ZX09301064004)People’s Republic of China,as well as grants from National Natural Science Foundation of China to M.Q.(8157151623)and J.W.(81603510)。
文摘Premenstrual dysphoric disorder(PMDD) affects nearly 5% of women of reproductive age. Symptomatic heterogeneity, together with largely unknown genetics, has greatly hindered its effective treatment. In the present study, analysis of genomic sequencing-based copy number variations(CNVs) called from 100 kb white blood cell DNA sequence windows by means of semisupervized clustering led to the segregation of patient genomes into the D and V groups, which correlated with the depression and invasion clinical types,respectively, with 89.0% consistency. Application of diagnostic CNV features selected using the correlation-based machine learning method enabled the classification of the CNVs obtained into the D group, V group, total patient group, and control group with an average accuracy of 83.0%. The power of the diagnostic CNV features was 0.98 on average, suggesting that these CNV features could be used for the molecular diagnosis of the major clinical types of PMDD. This demonstrated concordance between the CNV profiles and clinical types of PMDD supported the validity of symptom-based diagnosis of PMDD for differentiating between its two major clinical types, as well as the predominantly genetic nature of PMDD with a host of overlaps between multiple susceptibility genes/pathways and the diagnostic CNV features as indicators of involvement in PMDD etiology.
