Accurate identification and effective support of key blocks are crucial for ensuring the stability and safety of rock slopes.The number of structural planes and rock blocks were reduced in previous studies.This impair...Accurate identification and effective support of key blocks are crucial for ensuring the stability and safety of rock slopes.The number of structural planes and rock blocks were reduced in previous studies.This impairs the ability to characterize complex rock slopes accurately and inhibits the identification of key blocks.In this paper,a knowledge-data dually driven paradigm for accurate identification of key blocks in complex rock slopes is proposed.Our basic idea is to integrate key block theory into data-driven models based on finely characterizing structural features to identify key blocks in complex rock slopes accurately.The proposed novel paradigm consists of(1)representing rock slopes as graph-structured data based on complex systems theory,(2)identifying key nodes in the graph-structured data using graph deep learning,and(3)mapping the key nodes of graph-structured data to corresponding key blocks in the rock slope.Verification experiments and real-case applications are conducted by the proposed method.The verification results demonstrate excellent model performance,strong generalization capability,and effective classification results.Moreover,the real case application is conducted on the northern slope of the Yanqianshan Iron Mine.The results show that the proposed method can accurately identify key blocks in complex rock slopes,which can provide a decision-making basis and rational recommendations for effective support and instability prevention of rock slopes,thereby ensuring the stability of rock engineering and the safety of life and property.展开更多
The identification of key nodes plays an important role in improving the robustness of the transportation network.For different types of transportation networks,the effect of the same identification method may be diff...The identification of key nodes plays an important role in improving the robustness of the transportation network.For different types of transportation networks,the effect of the same identification method may be different.It is of practical significance to study the key nodes identification methods corresponding to various types of transportation networks.Based on the knowledge of complex networks,the metro networks and the bus networks are selected as the objects,and the key nodes are identified by the node degree identification method,the neighbor node degree identification method,the weighted k-shell degree neighborhood identification method(KSD),the degree k-shell identification method(DKS),and the degree k-shell neighborhood identification method(DKSN).Take the network efficiency and the largest connected subgraph as the effective indicators.The results show that the KSD identification method that comprehensively considers the elements has the best recognition effect and has certain practical significance.展开更多
Radio Frequency Identification(RFID)technology has been widely used to identify missing items.In many applications,rapidly pinpointing key tags that are attached to favorable or valuable items is critical.To realize t...Radio Frequency Identification(RFID)technology has been widely used to identify missing items.In many applications,rapidly pinpointing key tags that are attached to favorable or valuable items is critical.To realize this goal,interference from ordinary tags should be avoided,while key tags should be efficiently verified.Despite many previous studies,how to rapidly and dynamically filter out ordinary tags when the ratio of ordinary tags changes has not been addressed.Moreover,how to efficiently verify missing key tags in groups rather than one by one has not been explored,especially with varying missing rates.In this paper,we propose an Efficient and Robust missing Key tag Identification(ERKI)protocol that consists of a filtering mechanism and a verification mechanism.Specifically,the filtering mechanism adopts the Bloom filter to quickly filter out ordinary tags and uses the labeling vector to optimize the Bloom filter's performance when the key tag ratio is high.Furthermore,the verification mechanism can dynamically verify key tags according to the missing rates,in which an appropriate number of key tags is mapped to a slot and verified at once.Moreover,we theoretically analyze the parameters of the ERKI protocol to minimize its execution time.Extensive numerical results show that ERKI can accelerate the execution time by more than 2.14compared with state-of-the-art solutions.展开更多
As the scale of the power system continues to expand,the environment for power operations becomes more and more complex.Existing risk management and control methods for power operations can only set the same risk dete...As the scale of the power system continues to expand,the environment for power operations becomes more and more complex.Existing risk management and control methods for power operations can only set the same risk detection standard and conduct the risk detection for any scenario indiscriminately.Therefore,more reliable and accurate security control methods are urgently needed.In order to improve the accuracy and reliability of the operation risk management and control method,this paper proposes a method for identifying the key links in the whole process of electric power operation based on the spatiotemporal hybrid convolutional neural network.To provide early warning and control of targeted risks,first,the video stream is framed adaptively according to the pixel changes in the video stream.Then,the optimized MobileNet is used to extract the feature map of the video stream,which contains both time-series and static spatial scene information.The feature maps are combined and non-linearly mapped to realize the identification of dynamic operating scenes.Finally,training samples and test samples are produced by using the whole process image of a power company in Xinjiang as a case study,and the proposed algorithm is compared with the unimproved MobileNet.The experimental results demonstrated that the method proposed in this paper can accurately identify the type and start and end time of each operation link in the whole process of electric power operation,and has good real-time performance.The average accuracy of the algorithm can reach 87.8%,and the frame rate is 61 frames/s,which is of great significance for improving the reliability and accuracy of security control methods.展开更多
The thermal-induced error is a very important sour ce of machining errors of machine tools. To compensate the thermal-induced machin ing errors, a relationship model between the thermal field and deformations was need...The thermal-induced error is a very important sour ce of machining errors of machine tools. To compensate the thermal-induced machin ing errors, a relationship model between the thermal field and deformations was needed. The relationship can be deduced by virtual of FEM (Finite Element Method ), ANN (Artificial Neural Network) or MRA (Multiple Regression Analysis). MR A is on the basis of a total understanding of the temperature distribution of th e machine tool. Although the more the temperatures measured are, the more accura te the MRA is, too more temperatures will hinder the analysis calculation. So it is necessary to identify the key temperatures of the machine tool. The selectio n of key temperatures decides the efficiency and precision of MRA. Because of th e complexities and multi-input and multi-output structure of the relationships , the exact quantitative portions as well as the unclear portions must be taken into consideration together to improve the identification of key temperatures. I n this paper, a fuzzy cluster analysis was used to select the key temperatures. The substance of identifying the key temperatures is to group all temperatures b y their relativity, and then to select a temperature from each group as the repr esentation. A fuzzy cluster analysis can uncover the relationships between t he thermal field and deformations more truly and thoroughly. A fuzzy cluster ana lysis is the cluster analysis based on fuzzy sets. Given U={u i|i=0,...,N}, in which u i is the temperature measured, a fuzzy matrix R can be obta ined. The transfer close package t(R) can be deduced from R. A fuzzy clu ster of U then conducts on the basis of t(R). Based on the fuzzy cluster analysis discussed above, this paper identified the k ey temperatures of a horizontal machining center. The number of the temperatures measured was reduced to 4 from 32, and then the multiple regression relationshi p models between the 4 temperatures and the thermal deformations of the spindle were drawn. The remnant errors between the regression models and measured deform ations reached a satisfying low level. At the same time, the decreasing of tempe rature variable number improved the efficiency of measure and analysis greatly.展开更多
Twenty-eight candidate genes provided by other sub-projects were used to produce transgenic cotton plants.There were over 1000 individuals,and some of them were generation T2 or T3.All
Abstract Phyllochaetopterus species are widely distributed on the coast of China. Here, Phyllochaetopterus hainanensis n. sp., a new species collected from Hainan Island （China）, is reported. It is characterized by ...Abstract Phyllochaetopterus species are widely distributed on the coast of China. Here, Phyllochaetopterus hainanensis n. sp., a new species collected from Hainan Island （China）, is reported. It is characterized by having a V-shaped peristomium, two eyespots covered by a pair of large curved peristomial notopodia （cirri located beneath the palps）, 13-14 chaetigers in the anterior body region, with three enlarged modified chaetae on the fourth notopodium, and more than five chaetigers in the middle body region. The modified chaeta has a slightly inflated head with an obliquely truncate end. The new species resembles Phyllochaetopterus socialis Clapar6de, 1869, but differs in the shape of peristomial notopodia and peristomium. Twelve species of Phyllochaetopterus have been described from the Pacific Ocean, including the new species described here. An identification key to the known Pacific species is provided together with a brief discussion of the taxonomic value of the eyespots for the genus.展开更多
The identity of Rostraria bierii,originally described as a larval amphinomid from Cape Setozaki,Pacific coast of Japan,is investigated.Based on the original description and illustrations,reinterpretations conclude the...The identity of Rostraria bierii,originally described as a larval amphinomid from Cape Setozaki,Pacific coast of Japan,is investigated.Based on the original description and illustrations,reinterpretations conclude the“larva”to represent a partial juvenile or adult magelonid specimen,broken after the first chaetiger.The original figures are compared with several known magelonid species to justify the new placement.The authors suggest the supposed amphinomid larva is a Magelonidae taxon inquirendum.The identity of the species is discussed in line with the current knowledge of the Magelonidae in the western Pacific and a key to all known species within the region is provided to aid identifications.Current gaps in our taxonomic knowledge of the Magelonidae of the western Pacific are highlighted and discussed.展开更多
Understanding intricate interactions between natural–social factors and ecosystem service synergies and trade-offs(ESS/EST)can be valuable for promoting the sustainable development of multiple ecosystem services(ESs)...Understanding intricate interactions between natural–social factors and ecosystem service synergies and trade-offs(ESS/EST)can be valuable for promoting the sustainable development of multiple ecosystem services(ESs).Taking Beijing as the study area,this study was conducted from the perspective of ecosystem service bundles(ESBs).First,based on the identification of key ecological risks,the supply of 5 ESs was quantified.Then,3 ESBs were identified through the cluster analysis of the ESs.We explored the synergies and trade-offs between ES pairs in different ESBs and quantified their strengths.By further exploring the influence of natural–social factors on ESS/EST,we developed targeted management policies in different ESBs to improve management efficiency.At the township scale,Beijing is divided into 3 ESBs.Marked differences in the ESS/EST were found among each bundle,indicating the necessity of zonal management.The results showed that landscape composition was the dominant factor affecting ESS in ESB3 and EST in ESB2,human activities had the greatest influence on ESS in ESB2,while biophysical indicators had the highest degree of contribution to ESS and EST in ESB1 and EST in ESB3.These results support the formulation of sustainable management strategies.The results of the study emphasize the importance of considering ESS/EST and their natural–social factors in different ESBs when formulating effective policies,which can provide useful guidance for sustainable urban planning and development and can be further applied to metropolitan areas around the world.展开更多
This study describes a classification methodology based on support vector machines(SVMs),which offer superior classification performance for fault diagnosis in chemical process engineering.The method incorporates an e...This study describes a classification methodology based on support vector machines(SVMs),which offer superior classification performance for fault diagnosis in chemical process engineering.The method incorporates an efficient parameter tuning procedure(based on minimization of radius/margin bound for SVM's leave-one-out errors)into a multi-class classification strategy using a fuzzy decision factor,which is named fuzzy support vector machine(FSVM).The datasets generated from the Tennessee Eastman process(TEP)simulator were used to evaluate the clas-sification performance.To decrease the negative influence of the auto-correlated and irrelevant variables,a key vari-able identification procedure using recursive feature elimination,based on the SVM is implemented,with time lags incorporated,before every classifier is trained,and the number of relatively important variables to every classifier is basically determined by 10-fold cross-validation.Performance comparisons are implemented among several kinds of multi-class decision machines,by which the effectiveness of the proposed approach is proved.展开更多
The authors present a combined morphological and molecular approach of the genus Cantharellus in Africa.Morphological descriptions and detailed illustrations are provided for five new species from the Zambezian savann...The authors present a combined morphological and molecular approach of the genus Cantharellus in Africa.Morphological descriptions and detailed illustrations are provided for five new species from the Zambezian savannah woodlands in tropical Africa:C.afrocibarius,C.gracilis,C.humidicolus,C.miomboensis and C.tanzanicus.A maximum likelihood analysis of tef-1 sequences obtained for 83 collections of Cantharellus that are representative of all major groups in world wide Cantharellus,places a total of 13 African chanterelles,including the five newly described taxa.The recognition of a separate genus Afrocantharellus is rejected.An identification key based on the re-examination of all existing type material is provided for all presently known African Cantharellus.展开更多
Orphan crops hold significant potential for global food security,particularly in addressing climate change,population growth,and demands for nutritional diversity.This review comprehensively summarizes recent advances...Orphan crops hold significant potential for global food security,particularly in addressing climate change,population growth,and demands for nutritional diversity.This review comprehensively summarizes recent advances in genomic research and genetic improvement of orphan crops,exploring how enhanced yield,stress resilience,and nutritional value can address global food challenges.Studies reveal that orphan crops possess rich genetic diversity,enabling the identification and optimization of key genes through genome sequencing,gene editing(e.g.,CRISPR/Cas9),and conventional breeding to improve critical agronomic traits.The paper synthesizes the characteristics of genetic resources,progress in traditional breeding,discovery of advantageous genes,and improvement strategies in the whole-genome era,while also analyzing their linkages to human health and current challenges.The research underscores that the development and utilization of orphan crops offer innovative strategies for achieving sustainable agriculture and'Zero Hunger'posed by the United Nations,despite remaining hurdles such as insufficient research investment and limited market adoption.展开更多
This revision of Cantharellus in Madagascar deals with species that are associated with strictly endemic host trees and shrubs.Based on morphological differences and molecular sequence data of the tef-1 gene,five new ...This revision of Cantharellus in Madagascar deals with species that are associated with strictly endemic host trees and shrubs.Based on morphological differences and molecular sequence data of the tef-1 gene,five new species are proposed(C.albidolutescens,C.ambohitantelyensis,C.ibityensis,C.paucifurcatus and C.sebosus),as well as one new subspecies,C.subincarnatus ssp.rubrosalmoneus,whereas C.decolorans and C.platyphyllus ssp.bojeriensis are epitypified.A key is provided to all Cantharellus that grow with native vegetation in Madagascar.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.42277161,42230709).
文摘Accurate identification and effective support of key blocks are crucial for ensuring the stability and safety of rock slopes.The number of structural planes and rock blocks were reduced in previous studies.This impairs the ability to characterize complex rock slopes accurately and inhibits the identification of key blocks.In this paper,a knowledge-data dually driven paradigm for accurate identification of key blocks in complex rock slopes is proposed.Our basic idea is to integrate key block theory into data-driven models based on finely characterizing structural features to identify key blocks in complex rock slopes accurately.The proposed novel paradigm consists of(1)representing rock slopes as graph-structured data based on complex systems theory,(2)identifying key nodes in the graph-structured data using graph deep learning,and(3)mapping the key nodes of graph-structured data to corresponding key blocks in the rock slope.Verification experiments and real-case applications are conducted by the proposed method.The verification results demonstrate excellent model performance,strong generalization capability,and effective classification results.Moreover,the real case application is conducted on the northern slope of the Yanqianshan Iron Mine.The results show that the proposed method can accurately identify key blocks in complex rock slopes,which can provide a decision-making basis and rational recommendations for effective support and instability prevention of rock slopes,thereby ensuring the stability of rock engineering and the safety of life and property.
基金supported by the National Natural Science Foundation of China(Grant No.61961019)the Youth Key Project of the Natural Science Foundation of Jiangxi Province of China(Grant No.20202ACBL212003).
文摘The identification of key nodes plays an important role in improving the robustness of the transportation network.For different types of transportation networks,the effect of the same identification method may be different.It is of practical significance to study the key nodes identification methods corresponding to various types of transportation networks.Based on the knowledge of complex networks,the metro networks and the bus networks are selected as the objects,and the key nodes are identified by the node degree identification method,the neighbor node degree identification method,the weighted k-shell degree neighborhood identification method(KSD),the degree k-shell identification method(DKS),and the degree k-shell neighborhood identification method(DKSN).Take the network efficiency and the largest connected subgraph as the effective indicators.The results show that the KSD identification method that comprehensively considers the elements has the best recognition effect and has certain practical significance.
基金This work was supported in part by the National Natural Science Foundation of China under project contracts No.61971113 and 61901095in part by National Key R&D Program under project contract No.2018AAA0103203+5 种基金in part by Guangdong Provincial Research and Development Plan in Key Areas under project contract No.2019B010141001 and 2019B010142001in part by Sichuan Provincial Science and Technology Planning Program under project contracts No.2020YFG0039,No.2021YFG0013 and No.2021YFH0133in part by Ministry of Education China Mobile Fund Program under project contract No.MCM20180104in part by Yibin Science and Technology Program-Key Projects under project contract No.2018ZSF001 and 2019GY001in part by Central University Business Fee Program under project contract No.A03019023801224the Central Universities under Grant ZYGX2019Z022.
文摘Radio Frequency Identification(RFID)technology has been widely used to identify missing items.In many applications,rapidly pinpointing key tags that are attached to favorable or valuable items is critical.To realize this goal,interference from ordinary tags should be avoided,while key tags should be efficiently verified.Despite many previous studies,how to rapidly and dynamically filter out ordinary tags when the ratio of ordinary tags changes has not been addressed.Moreover,how to efficiently verify missing key tags in groups rather than one by one has not been explored,especially with varying missing rates.In this paper,we propose an Efficient and Robust missing Key tag Identification(ERKI)protocol that consists of a filtering mechanism and a verification mechanism.Specifically,the filtering mechanism adopts the Bloom filter to quickly filter out ordinary tags and uses the labeling vector to optimize the Bloom filter's performance when the key tag ratio is high.Furthermore,the verification mechanism can dynamically verify key tags according to the missing rates,in which an appropriate number of key tags is mapped to a slot and verified at once.Moreover,we theoretically analyze the parameters of the ERKI protocol to minimize its execution time.Extensive numerical results show that ERKI can accelerate the execution time by more than 2.14compared with state-of-the-art solutions.
基金This paper is supported by the Science and technology projects of Yunnan Province(Grant No.202202AD080004).
文摘As the scale of the power system continues to expand,the environment for power operations becomes more and more complex.Existing risk management and control methods for power operations can only set the same risk detection standard and conduct the risk detection for any scenario indiscriminately.Therefore,more reliable and accurate security control methods are urgently needed.In order to improve the accuracy and reliability of the operation risk management and control method,this paper proposes a method for identifying the key links in the whole process of electric power operation based on the spatiotemporal hybrid convolutional neural network.To provide early warning and control of targeted risks,first,the video stream is framed adaptively according to the pixel changes in the video stream.Then,the optimized MobileNet is used to extract the feature map of the video stream,which contains both time-series and static spatial scene information.The feature maps are combined and non-linearly mapped to realize the identification of dynamic operating scenes.Finally,training samples and test samples are produced by using the whole process image of a power company in Xinjiang as a case study,and the proposed algorithm is compared with the unimproved MobileNet.The experimental results demonstrated that the method proposed in this paper can accurately identify the type and start and end time of each operation link in the whole process of electric power operation,and has good real-time performance.The average accuracy of the algorithm can reach 87.8%,and the frame rate is 61 frames/s,which is of great significance for improving the reliability and accuracy of security control methods.
文摘The thermal-induced error is a very important sour ce of machining errors of machine tools. To compensate the thermal-induced machin ing errors, a relationship model between the thermal field and deformations was needed. The relationship can be deduced by virtual of FEM (Finite Element Method ), ANN (Artificial Neural Network) or MRA (Multiple Regression Analysis). MR A is on the basis of a total understanding of the temperature distribution of th e machine tool. Although the more the temperatures measured are, the more accura te the MRA is, too more temperatures will hinder the analysis calculation. So it is necessary to identify the key temperatures of the machine tool. The selectio n of key temperatures decides the efficiency and precision of MRA. Because of th e complexities and multi-input and multi-output structure of the relationships , the exact quantitative portions as well as the unclear portions must be taken into consideration together to improve the identification of key temperatures. I n this paper, a fuzzy cluster analysis was used to select the key temperatures. The substance of identifying the key temperatures is to group all temperatures b y their relativity, and then to select a temperature from each group as the repr esentation. A fuzzy cluster analysis can uncover the relationships between t he thermal field and deformations more truly and thoroughly. A fuzzy cluster ana lysis is the cluster analysis based on fuzzy sets. Given U={u i|i=0,...,N}, in which u i is the temperature measured, a fuzzy matrix R can be obta ined. The transfer close package t(R) can be deduced from R. A fuzzy clu ster of U then conducts on the basis of t(R). Based on the fuzzy cluster analysis discussed above, this paper identified the k ey temperatures of a horizontal machining center. The number of the temperatures measured was reduced to 4 from 32, and then the multiple regression relationshi p models between the 4 temperatures and the thermal deformations of the spindle were drawn. The remnant errors between the regression models and measured deform ations reached a satisfying low level. At the same time, the decreasing of tempe rature variable number improved the efficiency of measure and analysis greatly.
文摘Twenty-eight candidate genes provided by other sub-projects were used to produce transgenic cotton plants.There were over 1000 individuals,and some of them were generation T2 or T3.All
基金Supported by the Ocean Public Welfare Scientific Research Project(No.201105012)
文摘Abstract Phyllochaetopterus species are widely distributed on the coast of China. Here, Phyllochaetopterus hainanensis n. sp., a new species collected from Hainan Island （China）, is reported. It is characterized by having a V-shaped peristomium, two eyespots covered by a pair of large curved peristomial notopodia （cirri located beneath the palps）, 13-14 chaetigers in the anterior body region, with three enlarged modified chaetae on the fourth notopodium, and more than five chaetigers in the middle body region. The modified chaeta has a slightly inflated head with an obliquely truncate end. The new species resembles Phyllochaetopterus socialis Clapar6de, 1869, but differs in the shape of peristomial notopodia and peristomium. Twelve species of Phyllochaetopterus have been described from the Pacific Ocean, including the new species described here. An identification key to the known Pacific species is provided together with a brief discussion of the taxonomic value of the eyespots for the genus.
文摘The identity of Rostraria bierii,originally described as a larval amphinomid from Cape Setozaki,Pacific coast of Japan,is investigated.Based on the original description and illustrations,reinterpretations conclude the“larva”to represent a partial juvenile or adult magelonid specimen,broken after the first chaetiger.The original figures are compared with several known magelonid species to justify the new placement.The authors suggest the supposed amphinomid larva is a Magelonidae taxon inquirendum.The identity of the species is discussed in line with the current knowledge of the Magelonidae in the western Pacific and a key to all known species within the region is provided to aid identifications.Current gaps in our taxonomic knowledge of the Magelonidae of the western Pacific are highlighted and discussed.
基金supported by the Key Project of the State Forestry and Grassland Administration of China(2023132050)the Major Project of Teaching Reform of Beijing Forestry University 2023 (BJFU2023JYZD002)
文摘Understanding intricate interactions between natural–social factors and ecosystem service synergies and trade-offs(ESS/EST)can be valuable for promoting the sustainable development of multiple ecosystem services(ESs).Taking Beijing as the study area,this study was conducted from the perspective of ecosystem service bundles(ESBs).First,based on the identification of key ecological risks,the supply of 5 ESs was quantified.Then,3 ESBs were identified through the cluster analysis of the ESs.We explored the synergies and trade-offs between ES pairs in different ESBs and quantified their strengths.By further exploring the influence of natural–social factors on ESS/EST,we developed targeted management policies in different ESBs to improve management efficiency.At the township scale,Beijing is divided into 3 ESBs.Marked differences in the ESS/EST were found among each bundle,indicating the necessity of zonal management.The results showed that landscape composition was the dominant factor affecting ESS in ESB3 and EST in ESB2,human activities had the greatest influence on ESS in ESB2,while biophysical indicators had the highest degree of contribution to ESS and EST in ESB1 and EST in ESB3.These results support the formulation of sustainable management strategies.The results of the study emphasize the importance of considering ESS/EST and their natural–social factors in different ESBs when formulating effective policies,which can provide useful guidance for sustainable urban planning and development and can be further applied to metropolitan areas around the world.
基金Supported by the Special Funds for Major State Basic Research Program of China (973 Program,No.2002CB312200)the Na-tional Natural Science Foundation of China (No.60574019,No.60474045)+1 种基金the Key Technologies R&D Program of Zhejiang Province (No.2005C21087)the Academician Foundation of Zhejiang Province (No.2005A1001-13).
文摘This study describes a classification methodology based on support vector machines(SVMs),which offer superior classification performance for fault diagnosis in chemical process engineering.The method incorporates an efficient parameter tuning procedure(based on minimization of radius/margin bound for SVM's leave-one-out errors)into a multi-class classification strategy using a fuzzy decision factor,which is named fuzzy support vector machine(FSVM).The datasets generated from the Tennessee Eastman process(TEP)simulator were used to evaluate the clas-sification performance.To decrease the negative influence of the auto-correlated and irrelevant variables,a key vari-able identification procedure using recursive feature elimination,based on the SVM is implemented,with time lags incorporated,before every classifier is trained,and the number of relatively important variables to every classifier is basically determined by 10-fold cross-validation.Performance comparisons are implemented among several kinds of multi-class decision machines,by which the effectiveness of the proposed approach is proved.
基金the staff members of AMU in Dar-es-Salaam for logistic support and field assistancefinanced by SIDA/SAREC under the«Propagation and phytochemical studies of endangered or economically important plants and fungi of Tanzania»projectstudy was performed by C.Cruaud at the Genoscope or“Consortium National de Recherche en Génomique”near Paris(France)as part of the agreement n°2005/67 on the project“Macrophylogeny of life”between the Genoscope and the“service de systématique moléculaire”(CNRS IFR 101)of the Muséum National d’Histoire Naturelle and receives continuing support from the ATM-project“Barcode of life”(Dirs.L.Legall and S.Samadi).
文摘The authors present a combined morphological and molecular approach of the genus Cantharellus in Africa.Morphological descriptions and detailed illustrations are provided for five new species from the Zambezian savannah woodlands in tropical Africa:C.afrocibarius,C.gracilis,C.humidicolus,C.miomboensis and C.tanzanicus.A maximum likelihood analysis of tef-1 sequences obtained for 83 collections of Cantharellus that are representative of all major groups in world wide Cantharellus,places a total of 13 African chanterelles,including the five newly described taxa.The recognition of a separate genus Afrocantharellus is rejected.An identification key based on the re-examination of all existing type material is provided for all presently known African Cantharellus.
文摘Orphan crops hold significant potential for global food security,particularly in addressing climate change,population growth,and demands for nutritional diversity.This review comprehensively summarizes recent advances in genomic research and genetic improvement of orphan crops,exploring how enhanced yield,stress resilience,and nutritional value can address global food challenges.Studies reveal that orphan crops possess rich genetic diversity,enabling the identification and optimization of key genes through genome sequencing,gene editing(e.g.,CRISPR/Cas9),and conventional breeding to improve critical agronomic traits.The paper synthesizes the characteristics of genetic resources,progress in traditional breeding,discovery of advantageous genes,and improvement strategies in the whole-genome era,while also analyzing their linkages to human health and current challenges.The research underscores that the development and utilization of orphan crops offer innovative strategies for achieving sustainable agriculture and'Zero Hunger'posed by the United Nations,despite remaining hurdles such as insufficient research investment and limited market adoption.
文摘This revision of Cantharellus in Madagascar deals with species that are associated with strictly endemic host trees and shrubs.Based on morphological differences and molecular sequence data of the tef-1 gene,five new species are proposed(C.albidolutescens,C.ambohitantelyensis,C.ibityensis,C.paucifurcatus and C.sebosus),as well as one new subspecies,C.subincarnatus ssp.rubrosalmoneus,whereas C.decolorans and C.platyphyllus ssp.bojeriensis are epitypified.A key is provided to all Cantharellus that grow with native vegetation in Madagascar.
