Understanding plant community assembly is crucial for effective ecosystem conservation and restoration.The ecological filter framework describes community assembly as a process shaped by dispersal,environmental,and bi...Understanding plant community assembly is crucial for effective ecosystem conservation and restoration.The ecological filter framework describes community assembly as a process shaped by dispersal,environmental,and biotic filters.Additionally,functional traits and phylogenetic relationships are increasingly recognized as important factors influencing species coexistence and community structure.However,both the ecological filter framework and the roles of functional traits and phylogeny in community assembly remain underexplored in the Algerian steppes—particularly in the El Bayadh region,where ongoing vegetation degradation threatens ecosystem stability.This study applied Hierarchical Modeling of Species Communities(HMSC)as an integrative approach to assess how ecological filters influence plant community assembly in the El Bayadh steppe and to evaluate the roles of functional traits and phylogenetic relationships in this process.Environmental data—including soil properties,topography,precipitation,and land use types(grazing and exclosure)—were collected across 50 plots in April and October,2023,along with functional traits from 24 species.These traits include root length,leaf area,specific leaf area,clonality,life history,and seed mass.HMSC results revealed that soil properties and precipitation were the primary drivers of community structure,while sand height and elevation had a moderate influence.In contrast,competition and grazing played relatively minor roles.Species responses to environmental covariates were heterogeneous:soil fertility and texture had mixed effects,benefiting some species while limiting others;sand encroachment and precipitation variability generally had negative impacts,whereas grazing exclusion favored many species.A weak phylogenetic signal was recorded,indicating that community assembly was driven more by environmental filtering than by shared evolutionary history.Functional trait responses to environmental variation reflected plant strategies that balanced resource acquisition and conservation.Specifically,seed mass,leaf area,and root length increased under higher soil moisture and nutrient availability but declined in response to salinity,precipitation variability,and sand height.Clonality and perennial life history traits enhanced the survival of plant species under harsh conditions.Overall,this study provides a holistic understanding of community assembly processes in the El Bayadh steppe and offers valuable insights for ecosystem management and restoration in arid and degraded ecosystem environments.展开更多
The new RE 6 EL from KARL MAYER brings a breath of fresh air to raschel fabric production.Nowadays textile companies increasingly need to produce small production runs and respond to market changes with instantaneous ...The new RE 6 EL from KARL MAYER brings a breath of fresh air to raschel fabric production.Nowadays textile companies increasingly need to produce small production runs and respond to market changes with instantaneous pattern changes in order to operate profitably–meaning they require machines that offer maximum flexibility,reliability and cost efficiency.KARL MAYER understands the challenges of the market and is launching its new RE 6 EL.The Raschel machine offers the core strengths of the classic RSE 6 EL and essentially the same performance parameters,but has been further cost-optimised largely due to local production advantages.This makes the newcomer an efficiency champion in production,especially when it comes to frequent pattern changes.展开更多
This study investigates the distinct impacts of eastern Pacific(EP)and central Pacific(CP)El Niño events on winter shortwave solar radiation(SSR)in southern China,revealing different spatial distributions and und...This study investigates the distinct impacts of eastern Pacific(EP)and central Pacific(CP)El Niño events on winter shortwave solar radiation(SSR)in southern China,revealing different spatial distributions and underlying mechanisms.The results show that,during the developing winter of EP El Niño,significant SSR reductions occur in southwestern China and the east coast of southern China due to a strong,zonally extended Northwest Pacific anticyclone that transports moisture from the tropical Northwest Pacific and North Indian Ocean,while the northeast of southern China experiences a weak increase in SSR.In contrast,during the developing winter of CP El Niño,SSR decreases in the east of southern China with a significant decrease in the lower basin of the Yangtze River but an increase in the west of southern China with a remarkable increase in eastern Yunnan.The pronounced east-west dipole pattern in SSR anomalies is driven by a meridionally elongated Northwest Pacific anticyclone,which enhances northward moisture transport to the east of southern China while leaving western areas drier.Further research reveals that distinct moisture anomalies during the developing winter of EP and CP events result in divergent SSR distributions across southern China,primarily through modulating the total cloud cover.These findings highlight the critical need to differentiate between El Niño types when predicting medium and long-term variability of radiation in southern China.展开更多
Deep learning(DL)has become a crucial technique for predicting the El Niño-Southern Oscillation(ENSO)and evaluating its predictability.While various DL-based models have been developed for ENSO predictions,many f...Deep learning(DL)has become a crucial technique for predicting the El Niño-Southern Oscillation(ENSO)and evaluating its predictability.While various DL-based models have been developed for ENSO predictions,many fail to capture the coherent multivariate evolution within the coupled ocean-atmosphere system of the tropical Pacific.To address this three-dimensional(3D)limitation and represent ENSO-related ocean-atmosphere interactions more accurately,a novel this 3D multivariate prediction model was proposed based on a Transformer architecture,which incorporates a spatiotemporal self-attention mechanism.This model,named 3D-Geoformer,offers several advantages,enabling accurate ENSO predictions up to one and a half years in advance.Furthermore,an integrated gradient method was introduced into the model to identify the sources of predictability for sea surface temperature(SST)variability in the eastern equatorial Pacific.Results reveal that the 3D-Geoformer effectively captures ENSO-related precursors during the evolution of ENSO events,particularly the thermocline feedback processes and ocean temperature anomaly pathways on and off the equator.By extending DL-based ENSO predictions from one-dimensional Niño time series to 3D multivariate fields,the 3D-Geoformer represents a significant advancement in ENSO prediction.This study provides details in the model formulation,analysis procedures,sensitivity experiments,and illustrative examples,offering practical guidance for the application of the model in ENSO research.展开更多
Numerical models are crucial for quantifying the ocean-atmosphere interactions associated with the El Niño-Southern Oscillation(ENSO)phenomenon in the tropical Pacific.Current coupled models often exhibit signifi...Numerical models are crucial for quantifying the ocean-atmosphere interactions associated with the El Niño-Southern Oscillation(ENSO)phenomenon in the tropical Pacific.Current coupled models often exhibit significant biases and inter-model differences in simulating ENSO,underscoring the need for alternative modeling approaches.The Regional Ocean Modeling System(ROMS)is a sophisticated ocean model widely used for regional studies and has been coupled with various atmospheric models.However,its application in simulating ENSO processes on a basin scale in the tropical Pacific has not been explored.For the first time,this study presents the development of a basin-scale hybrid coupled model(HCM)for the tropical Pacific,integrating ROMS with a statistical atmospheric model that captures the interannual relationships between sea surface temperature(SST)and wind stress anomalies.The HCM is evaluated for its capability to simulate the annual mean,seasonal,and interannual variations of the oceanic state in the tropical Pacific.Results demonstrate that the model effectively reproduces the ENSO cycle,with a dominant oscillation period of approximately two years.The ROMS-based HCM developed here offers an efficient and robust tool for investigating climate variability in the tropical Pacific.展开更多
Internet of Things(IoT)refers to the infrastructures that connect smart devices to the Internet,operating autonomously.This connectivitymakes it possible to harvest vast quantities of data,creating new opportunities f...Internet of Things(IoT)refers to the infrastructures that connect smart devices to the Internet,operating autonomously.This connectivitymakes it possible to harvest vast quantities of data,creating new opportunities for the emergence of unprecedented knowledge.To ensure IoT securit,various approaches have been implemented,such as authentication,encoding,as well as devices to guarantee data integrity and availability.Among these approaches,Intrusion Detection Systems(IDS)is an actual security solution,whose performance can be enhanced by integrating various algorithms,including Machine Learning(ML)and Deep Learning(DL),enabling proactive and accurate detection of threats.This study proposes to optimize the performance of network IDS using an ensemble learning method based on a voting classification algorithm.By combining the strengths of three powerful algorithms,Random Forest(RF),K-Nearest Neighbors(KNN),and Support Vector Machine(SVM)to detect both normal behavior and different categories of attack.Our analysis focuses primarily on the NSL-KDD dataset,while also integrating the recent Edge-IIoT dataset,tailored to industrial IoT environments.Experimental results show significant enhancements on the Edge-IIoT and NSL-KDD datasets,reaching accuracy levels between 72%to 99%,with precision between 87%and 99%,while recall values and F1-scores are also between 72%and 99%,for both normal and attack detection.Despite the promising results of this study,it suffers from certain limitations,notably the use of specific datasets and the lack of evaluations in a variety of environments.Future work could include applying this model to various datasets and evaluating more advanced ensemble strategies,with the aim of further enhancing the effectiveness of IDS.展开更多
The Indonesian Throughflow(ITF)plays important roles in global ocean circulation and climate systems.Previous studies suggested the ITF interannual variability is driven by both the El Niño-Southern Oscillation(E...The Indonesian Throughflow(ITF)plays important roles in global ocean circulation and climate systems.Previous studies suggested the ITF interannual variability is driven by both the El Niño-Southern Oscillation(ENSO)and the Indian Ocean Dipole(IOD)events.The detailed processes of ENSO and/or IOD induced anomalies impacting on the ITF,however,are still not clear.In this study,this issue is investigated through causal relation,statistical,and dynamical analyses based on satellite observation.The results show that the driven mechanisms of ENSO on the ITF include two aspects.Firstly,the ENSO related wind field anomalies driven anomalous cyclonic ocean circulation in the western Pacific,and off equatorial upwelling Rossby waves propagating westward to arrive at the western boundary of the Pacific,both tend to induce negative sea surface height anomalies(SSHA)in the western Pacific,favoring ITF reduction since the develop of the El Niño through the following year.Secondly,the ENSO events modulate equatorial Indian Ocean zonal winds through Walker Circulation,which in turn trigger eastward propagating upwelling Kelvin waves and westward propagating downwelling Rossby waves.The Rossby waves are reflected into downwelling Kelvin waves,which then propagate eastward along the equator and the Sumatra-Java coast in the Indian Ocean.As a result,the wave dynamics tend to generate negative(positive)SSHA in the eastern Indian Ocean,and thus enhance(reduce)the ITF transport with time lag of 0-6 months(9-12 months),respectively.Under the IOD condition,the wave dynamics also tend to enhance the ITF in the positive IOD year,and reduce the ITF in the following year.展开更多
Leucogranite,pegmatite,and aplite from selected areas in the Wadi El Gemal area in the southern Eastern Desert of Egypt were investigated geochemically for their petrogenesis.These rocks represent a significant episod...Leucogranite,pegmatite,and aplite from selected areas in the Wadi El Gemal area in the southern Eastern Desert of Egypt were investigated geochemically for their petrogenesis.These rocks represent a significant episode of felsic magmatism during the late stage of the Pan-African orogeny in the evolution of the Arabian–Nubian Shield(ANS)during the Late Neoproterozoic.On a petrographic basis,the leucogranite is sometimes garnetiferous and can be distinguished into monzogranite,syenogranite,and alkali feldspar granite.The analyses of muscovite,biotite,garnet,and apatite reveal the magmatic nature of the studied leucogranite.The investigated leucogranite,pegmatite,and aplite are alkali-calcic,calc-alkaline,and peraluminous.The peraluminous nature of these rocks is evidenced by using the chemical analyses of biotite.These studied rocks show a slight enrichment in light rare-earth elements(LREEs)and large-ion lithophile elements(LILE,especially Rb and Th),with an insignificant depletion of heavy rareearth elements(HREEs).On a geochemical basis,the leucogranite,pegmatite,and aplite in the study area crystallized from multiple-sourced melts that include mafic,metagraywake,and pelitic.They were derived from melts generated at crystallization temperatures around 568-900℃ for leucogranite,553-781℃ for pegmatite,and 639-779℃ for aplite based on the Zr saturation geothermometers,and at a pressure around 0.39-0.48 GPa,i.e.shallow depth intrusions.The studied felsic rocks have strong negative Eu anomalies,which are very consistent with an upper crust composition,indicating fractionation of feldspar cumulates.Also,they show a moderate La/Sm ratio indicating combined magmatic processes represented by partial melting and fractional crystallization.Integration of whole-rock chemical composition and mineral microanalysis suggests that felsic magmatism in the west Wadi El Gemal area produced voluminous masses of syn-to post-collisional granite,pegmatite,and aplite.An evolutionary three-stage model is presented to understand late magmatism in the ANS in terms of a geodynamic model.Such a model discusses the propagation of felsic magmatism in the ANS during syn-collisional to post-collisional stages.展开更多
基金supported by the Foundation of the University of Quebec in Abitibi-Témiscamingue(FUQAT)Quebec Research Fund(FRQ)(2021-SE7-282961)。
文摘Understanding plant community assembly is crucial for effective ecosystem conservation and restoration.The ecological filter framework describes community assembly as a process shaped by dispersal,environmental,and biotic filters.Additionally,functional traits and phylogenetic relationships are increasingly recognized as important factors influencing species coexistence and community structure.However,both the ecological filter framework and the roles of functional traits and phylogeny in community assembly remain underexplored in the Algerian steppes—particularly in the El Bayadh region,where ongoing vegetation degradation threatens ecosystem stability.This study applied Hierarchical Modeling of Species Communities(HMSC)as an integrative approach to assess how ecological filters influence plant community assembly in the El Bayadh steppe and to evaluate the roles of functional traits and phylogenetic relationships in this process.Environmental data—including soil properties,topography,precipitation,and land use types(grazing and exclosure)—were collected across 50 plots in April and October,2023,along with functional traits from 24 species.These traits include root length,leaf area,specific leaf area,clonality,life history,and seed mass.HMSC results revealed that soil properties and precipitation were the primary drivers of community structure,while sand height and elevation had a moderate influence.In contrast,competition and grazing played relatively minor roles.Species responses to environmental covariates were heterogeneous:soil fertility and texture had mixed effects,benefiting some species while limiting others;sand encroachment and precipitation variability generally had negative impacts,whereas grazing exclusion favored many species.A weak phylogenetic signal was recorded,indicating that community assembly was driven more by environmental filtering than by shared evolutionary history.Functional trait responses to environmental variation reflected plant strategies that balanced resource acquisition and conservation.Specifically,seed mass,leaf area,and root length increased under higher soil moisture and nutrient availability but declined in response to salinity,precipitation variability,and sand height.Clonality and perennial life history traits enhanced the survival of plant species under harsh conditions.Overall,this study provides a holistic understanding of community assembly processes in the El Bayadh steppe and offers valuable insights for ecosystem management and restoration in arid and degraded ecosystem environments.
文摘The new RE 6 EL from KARL MAYER brings a breath of fresh air to raschel fabric production.Nowadays textile companies increasingly need to produce small production runs and respond to market changes with instantaneous pattern changes in order to operate profitably–meaning they require machines that offer maximum flexibility,reliability and cost efficiency.KARL MAYER understands the challenges of the market and is launching its new RE 6 EL.The Raschel machine offers the core strengths of the classic RSE 6 EL and essentially the same performance parameters,but has been further cost-optimised largely due to local production advantages.This makes the newcomer an efficiency champion in production,especially when it comes to frequent pattern changes.
基金funded by a Project from China Southern Power Grid Company Ltd.(Nos.ZBKJXM20232481 and ZBKJXM20232482)。
文摘This study investigates the distinct impacts of eastern Pacific(EP)and central Pacific(CP)El Niño events on winter shortwave solar radiation(SSR)in southern China,revealing different spatial distributions and underlying mechanisms.The results show that,during the developing winter of EP El Niño,significant SSR reductions occur in southwestern China and the east coast of southern China due to a strong,zonally extended Northwest Pacific anticyclone that transports moisture from the tropical Northwest Pacific and North Indian Ocean,while the northeast of southern China experiences a weak increase in SSR.In contrast,during the developing winter of CP El Niño,SSR decreases in the east of southern China with a significant decrease in the lower basin of the Yangtze River but an increase in the west of southern China with a remarkable increase in eastern Yunnan.The pronounced east-west dipole pattern in SSR anomalies is driven by a meridionally elongated Northwest Pacific anticyclone,which enhances northward moisture transport to the east of southern China while leaving western areas drier.Further research reveals that distinct moisture anomalies during the developing winter of EP and CP events result in divergent SSR distributions across southern China,primarily through modulating the total cloud cover.These findings highlight the critical need to differentiate between El Niño types when predicting medium and long-term variability of radiation in southern China.
基金Supported by the Laoshan Laboratory(No.LSKJ202202402)the National Natural Science Foundation of China(No.42030410)+2 种基金the Startup Foundation for Introducing Talent of Nanjing University of Information Science&Technology,and Jiangsu Innovation Research Group(No.JSSCTD 202346)supported by the China National Postdoctoral Program for Innovative Talents(No.BX20240169)the China Postdoctoral Science Foundation(No.2141062400101)。
文摘Deep learning(DL)has become a crucial technique for predicting the El Niño-Southern Oscillation(ENSO)and evaluating its predictability.While various DL-based models have been developed for ENSO predictions,many fail to capture the coherent multivariate evolution within the coupled ocean-atmosphere system of the tropical Pacific.To address this three-dimensional(3D)limitation and represent ENSO-related ocean-atmosphere interactions more accurately,a novel this 3D multivariate prediction model was proposed based on a Transformer architecture,which incorporates a spatiotemporal self-attention mechanism.This model,named 3D-Geoformer,offers several advantages,enabling accurate ENSO predictions up to one and a half years in advance.Furthermore,an integrated gradient method was introduced into the model to identify the sources of predictability for sea surface temperature(SST)variability in the eastern equatorial Pacific.Results reveal that the 3D-Geoformer effectively captures ENSO-related precursors during the evolution of ENSO events,particularly the thermocline feedback processes and ocean temperature anomaly pathways on and off the equator.By extending DL-based ENSO predictions from one-dimensional Niño time series to 3D multivariate fields,the 3D-Geoformer represents a significant advancement in ENSO prediction.This study provides details in the model formulation,analysis procedures,sensitivity experiments,and illustrative examples,offering practical guidance for the application of the model in ENSO research.
基金Supported by the Laoshan Laboratory(No.LSKJ 202202404)the Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDB 42000000)+1 种基金the National Natural Science Foundation of China(NSFC)(No.42030410)the Startup Foundation for Introducing Talent of NUIST,and the Jiangsu Innovation Research Group(No.JSSCTD 202346)。
文摘Numerical models are crucial for quantifying the ocean-atmosphere interactions associated with the El Niño-Southern Oscillation(ENSO)phenomenon in the tropical Pacific.Current coupled models often exhibit significant biases and inter-model differences in simulating ENSO,underscoring the need for alternative modeling approaches.The Regional Ocean Modeling System(ROMS)is a sophisticated ocean model widely used for regional studies and has been coupled with various atmospheric models.However,its application in simulating ENSO processes on a basin scale in the tropical Pacific has not been explored.For the first time,this study presents the development of a basin-scale hybrid coupled model(HCM)for the tropical Pacific,integrating ROMS with a statistical atmospheric model that captures the interannual relationships between sea surface temperature(SST)and wind stress anomalies.The HCM is evaluated for its capability to simulate the annual mean,seasonal,and interannual variations of the oceanic state in the tropical Pacific.Results demonstrate that the model effectively reproduces the ENSO cycle,with a dominant oscillation period of approximately two years.The ROMS-based HCM developed here offers an efficient and robust tool for investigating climate variability in the tropical Pacific.
文摘Internet of Things(IoT)refers to the infrastructures that connect smart devices to the Internet,operating autonomously.This connectivitymakes it possible to harvest vast quantities of data,creating new opportunities for the emergence of unprecedented knowledge.To ensure IoT securit,various approaches have been implemented,such as authentication,encoding,as well as devices to guarantee data integrity and availability.Among these approaches,Intrusion Detection Systems(IDS)is an actual security solution,whose performance can be enhanced by integrating various algorithms,including Machine Learning(ML)and Deep Learning(DL),enabling proactive and accurate detection of threats.This study proposes to optimize the performance of network IDS using an ensemble learning method based on a voting classification algorithm.By combining the strengths of three powerful algorithms,Random Forest(RF),K-Nearest Neighbors(KNN),and Support Vector Machine(SVM)to detect both normal behavior and different categories of attack.Our analysis focuses primarily on the NSL-KDD dataset,while also integrating the recent Edge-IIoT dataset,tailored to industrial IoT environments.Experimental results show significant enhancements on the Edge-IIoT and NSL-KDD datasets,reaching accuracy levels between 72%to 99%,with precision between 87%and 99%,while recall values and F1-scores are also between 72%and 99%,for both normal and attack detection.Despite the promising results of this study,it suffers from certain limitations,notably the use of specific datasets and the lack of evaluations in a variety of environments.Future work could include applying this model to various datasets and evaluating more advanced ensemble strategies,with the aim of further enhancing the effectiveness of IDS.
基金The Fund of Laoshan Laboratory under contract No.LSKJ202202700the Basic Scientific Fund for National Public Research Institutes of China under contract No.2024Q02+1 种基金the National Natural Science Foundation of China under contract Nos 42076023 and 42430402the Global Change and Air-Sea InteractionⅡProject under contract No.GASI-01-ATP-STwin.
文摘The Indonesian Throughflow(ITF)plays important roles in global ocean circulation and climate systems.Previous studies suggested the ITF interannual variability is driven by both the El Niño-Southern Oscillation(ENSO)and the Indian Ocean Dipole(IOD)events.The detailed processes of ENSO and/or IOD induced anomalies impacting on the ITF,however,are still not clear.In this study,this issue is investigated through causal relation,statistical,and dynamical analyses based on satellite observation.The results show that the driven mechanisms of ENSO on the ITF include two aspects.Firstly,the ENSO related wind field anomalies driven anomalous cyclonic ocean circulation in the western Pacific,and off equatorial upwelling Rossby waves propagating westward to arrive at the western boundary of the Pacific,both tend to induce negative sea surface height anomalies(SSHA)in the western Pacific,favoring ITF reduction since the develop of the El Niño through the following year.Secondly,the ENSO events modulate equatorial Indian Ocean zonal winds through Walker Circulation,which in turn trigger eastward propagating upwelling Kelvin waves and westward propagating downwelling Rossby waves.The Rossby waves are reflected into downwelling Kelvin waves,which then propagate eastward along the equator and the Sumatra-Java coast in the Indian Ocean.As a result,the wave dynamics tend to generate negative(positive)SSHA in the eastern Indian Ocean,and thus enhance(reduce)the ITF transport with time lag of 0-6 months(9-12 months),respectively.Under the IOD condition,the wave dynamics also tend to enhance the ITF in the positive IOD year,and reduce the ITF in the following year.
基金finational supported by the Foundation of Science,Technology and Innovation Funding Authority(STDF)(Award Number:47106Recipient:Mokhles K K.Azer)。
文摘Leucogranite,pegmatite,and aplite from selected areas in the Wadi El Gemal area in the southern Eastern Desert of Egypt were investigated geochemically for their petrogenesis.These rocks represent a significant episode of felsic magmatism during the late stage of the Pan-African orogeny in the evolution of the Arabian–Nubian Shield(ANS)during the Late Neoproterozoic.On a petrographic basis,the leucogranite is sometimes garnetiferous and can be distinguished into monzogranite,syenogranite,and alkali feldspar granite.The analyses of muscovite,biotite,garnet,and apatite reveal the magmatic nature of the studied leucogranite.The investigated leucogranite,pegmatite,and aplite are alkali-calcic,calc-alkaline,and peraluminous.The peraluminous nature of these rocks is evidenced by using the chemical analyses of biotite.These studied rocks show a slight enrichment in light rare-earth elements(LREEs)and large-ion lithophile elements(LILE,especially Rb and Th),with an insignificant depletion of heavy rareearth elements(HREEs).On a geochemical basis,the leucogranite,pegmatite,and aplite in the study area crystallized from multiple-sourced melts that include mafic,metagraywake,and pelitic.They were derived from melts generated at crystallization temperatures around 568-900℃ for leucogranite,553-781℃ for pegmatite,and 639-779℃ for aplite based on the Zr saturation geothermometers,and at a pressure around 0.39-0.48 GPa,i.e.shallow depth intrusions.The studied felsic rocks have strong negative Eu anomalies,which are very consistent with an upper crust composition,indicating fractionation of feldspar cumulates.Also,they show a moderate La/Sm ratio indicating combined magmatic processes represented by partial melting and fractional crystallization.Integration of whole-rock chemical composition and mineral microanalysis suggests that felsic magmatism in the west Wadi El Gemal area produced voluminous masses of syn-to post-collisional granite,pegmatite,and aplite.An evolutionary three-stage model is presented to understand late magmatism in the ANS in terms of a geodynamic model.Such a model discusses the propagation of felsic magmatism in the ANS during syn-collisional to post-collisional stages.
