Directional three-dimensional carbon-based foams are emerging as highly attractive candidates for promising electromagnetic wave absorbing materials(EWAMs)thanks to their unique architecture,but their construction usu...Directional three-dimensional carbon-based foams are emerging as highly attractive candidates for promising electromagnetic wave absorbing materials(EWAMs)thanks to their unique architecture,but their construction usually involves complex procedures and extremely depends on unidirectional freezing technique.Herein,we propose a groundbreaking approach that leverages the assemblies of salting-out protein induced by ammonium metatungstate(AM)as the precursor,and then acquire directional three-dimensional carbon-based foams through simple pyrolysis.The electrostatic interaction between AM and protein ensures well dispersion of WC_(1−x)nanoparticles on carbon frameworks.The content of WC_(1−x)nanoparticles can be rationally regulated by AM dosage,and it also affects the electromagnetic(EM)properties of final carbon-based foams.The optimized foam exhibits exceptional EM absorption performance,achieving a remarkable minimum reflection loss of−72.0 dB and an effective absorption bandwidth of 6.3 GHz when EM wave propagates parallel to the directional pores.Such performance benefits from the synergistic effects of macroporous architecture and compositional design.Although there is a directional dependence of EM absorption,radar stealth simulation demonstrates that these foams can still promise considerable reduction in radar cross section with the change of incident angle.Moreover,COMSOL simulation further identifies their good performance in preventing EM interference among different electronic components.展开更多
【目的】通过EMS诱变创制抗草甘膦小麦新种质,以应对麦田杂草危害。通过大田筛选获得抗性突变株,明确5-烯醇丙酮莽草酸-3-磷酸合酶(EPSPS)基因突变特征及适宜施药条件,为培育抗草甘膦小麦品种提供可行途径。【方法】用EMS诱变处理刚萌...【目的】通过EMS诱变创制抗草甘膦小麦新种质,以应对麦田杂草危害。通过大田筛选获得抗性突变株,明确5-烯醇丙酮莽草酸-3-磷酸合酶(EPSPS)基因突变特征及适宜施药条件,为培育抗草甘膦小麦品种提供可行途径。【方法】用EMS诱变处理刚萌发的镇麦9号种子,创制突变群体,运用草甘膦对大田M2、M3代群体进行多轮筛选,获得抗性突变株。结合产量和抗性表型,采用系选方法筛选出GR1、GR19和GR23等优良突变系。通过PCR方法和测序确定EPSPS基因突变位点,并利用RT-qPCR技术分析TaEPSPS-4A、TaEPSPS-7A和TaEPSPS-7D的表达水平。最后,通过设置不同剂量和生育期的田间药效试验,系统评估草甘膦使用效果,明确其适宜施用剂量和安全使用时期。【结果】经诱变的M2群体抗性突变频率为6.53×10-6,在M3代成功筛选出43株能够耐受4×推荐剂量草甘膦的突变株。测序分析表明,在抗性系GR1和GR19中,分别在TaEPSPS-7D检测到5和3个突变位点,而在GR23中则在TaEPSPS-4A检测到5个突变位点。表达分析表明,草甘膦处理后3个突变系中多数同源基因的表达水平显著下降,且该现象与基因是否发生抗性突变无关。大田药效试验证实,各剂量草甘膦处理对杂草的株防效均达100%,显著优于异丙隆;随着草甘膦剂量的增加,小麦苗高和鲜重呈下降趋势,但多数未达显著水平,表明其对生长无显著不利影响。产量分析显示,经1×和2×剂量处理后,减产不显著,而4×和8×剂量处理后,分别显著减产3.04%和4.63%。不同生育期施药试验进一步表明,苗期至拔节期喷施2×剂量草甘膦对植株生长无显著影响,但孕穗期施药则导致株高、鲜重和籽粒产量显著下降,减产达6.48%。【结论】结合EMS诱变与大田筛选创制抗草甘膦小麦新种质,可抗4×推荐剂量,EPSPS酶非活性中心的多个点突变增强了草甘膦抗性而不减产量,在生产上应用这类抗草甘膦品种时,防除杂草适期为小麦返青期(3月上旬),用41%草甘膦840—1680 g ae·hm-2,兑水450L·hm-2,选择无雨天气进行杂草茎叶喷雾处理。展开更多
Soybean(Glycine max L.)is a globally vital crop for oil production and food security.High-quality genomic resources are instrumental for both functional genomics and breeding.Here,we report a near-complete,high-qualit...Soybean(Glycine max L.)is a globally vital crop for oil production and food security.High-quality genomic resources are instrumental for both functional genomics and breeding.Here,we report a near-complete,high-quality genome assembly of the elite cultivar Tianlong 1(TL1),featuring fully resolved telomeres and centromeres,as well as a gap-free assembly of 14 of its 20 chromosomes.On the basis of the genome assembly,we generate an ethyl methanesulfonate(EMS)-mutagenized population comprising 2555 M7 plants.Whole-genome resequencing of 288 EMS mutants uncovers 1,163,869 high-confidence single-nucleotide polymorphisms(SNPs)and 542,709 insertions/deletions(InDels),achieving 91.89%coverage of predicted protein-coding genes.Phenotypic screening demonstrates robust genotype–phenotype associations,with two nonsynonymous mutants displaying pronounced defects in seed and leaf development.Collectively,the chromosome-scale TL1 genome assembly and the extensively characterized mutant population establish valuable resources for functional genomics and precision breeding in soybean and related legume species.展开更多
Internet of Things(IoTs)devices are bringing about a revolutionary change our society by enabling connectivity regardless of time and location.However,The extensive deployment of these devices also makes them attracti...Internet of Things(IoTs)devices are bringing about a revolutionary change our society by enabling connectivity regardless of time and location.However,The extensive deployment of these devices also makes them attractive victims for themalicious actions of adversaries.Within the spectrumof existing threats,Side-ChannelAttacks(SCAs)have established themselves as an effective way to compromise cryptographic implementations.These attacks exploit unintended,unintended physical leakage that occurs during the cryptographic execution of devices,bypassing the theoretical strength of the crypto design.In recent times,the advancement of deep learning has provided SCAs with a powerful ally.Well-trained deep-learningmodels demonstrate an exceptional capacity to identify correlations between side-channel measurements and sensitive data,thereby significantly enhancing such attacks.To further understand the security threats posed by deep-learning SCAs and to aid in formulating robust countermeasures in the future,this paper undertakes an exhaustive investigation of leading-edge SCAs targeting Advanced Encryption Standard(AES)implementations.The study specifically focuses on attacks that exploit power consumption and electromagnetic(EM)emissions as primary leakage sources,systematically evaluating the extent to which diverse deep learning techniques enhance SCAs acrossmultiple critical dimensions.These dimensions include:(i)the characteristics of publicly available datasets derived from various hardware and software platforms;(ii)the formalization of leakage models tailored to different attack scenarios;(iii)the architectural suitability and performance of state-of-the-art deep learning models.Furthermore,the survey provides a systematic synthesis of current research findings,identifies significant unresolved issues in the existing literature and suggests promising directions for future work,including cross-device attack transferability and the impact of quantum-classical hybrid computing on side-channel security.展开更多
As the healthcare system advances and expands in its services,the challenges of remaining efficient become more important.Emergency medical services(EMS)are vital cornerstones of communities.In many countries,EMS is a...As the healthcare system advances and expands in its services,the challenges of remaining efficient become more important.Emergency medical services(EMS)are vital cornerstones of communities.In many countries,EMS is available for every individual,regardless of their social or insurance status,via a toll-free telephone number.Understanding the risk factors for busy days in EMSs might be helpful for improving the allocation of resources,which is the key to better care for all patients in the prehospital setting.[1]An important factor influencing ambulance call volume could be the interplay of public behavior and weather.展开更多
基金financially supported by the National Natural Science Foundation of China(Nos.22475057 and No.52373262).
文摘Directional three-dimensional carbon-based foams are emerging as highly attractive candidates for promising electromagnetic wave absorbing materials(EWAMs)thanks to their unique architecture,but their construction usually involves complex procedures and extremely depends on unidirectional freezing technique.Herein,we propose a groundbreaking approach that leverages the assemblies of salting-out protein induced by ammonium metatungstate(AM)as the precursor,and then acquire directional three-dimensional carbon-based foams through simple pyrolysis.The electrostatic interaction between AM and protein ensures well dispersion of WC_(1−x)nanoparticles on carbon frameworks.The content of WC_(1−x)nanoparticles can be rationally regulated by AM dosage,and it also affects the electromagnetic(EM)properties of final carbon-based foams.The optimized foam exhibits exceptional EM absorption performance,achieving a remarkable minimum reflection loss of−72.0 dB and an effective absorption bandwidth of 6.3 GHz when EM wave propagates parallel to the directional pores.Such performance benefits from the synergistic effects of macroporous architecture and compositional design.Although there is a directional dependence of EM absorption,radar stealth simulation demonstrates that these foams can still promise considerable reduction in radar cross section with the change of incident angle.Moreover,COMSOL simulation further identifies their good performance in preventing EM interference among different electronic components.
文摘【目的】通过EMS诱变创制抗草甘膦小麦新种质,以应对麦田杂草危害。通过大田筛选获得抗性突变株,明确5-烯醇丙酮莽草酸-3-磷酸合酶(EPSPS)基因突变特征及适宜施药条件,为培育抗草甘膦小麦品种提供可行途径。【方法】用EMS诱变处理刚萌发的镇麦9号种子,创制突变群体,运用草甘膦对大田M2、M3代群体进行多轮筛选,获得抗性突变株。结合产量和抗性表型,采用系选方法筛选出GR1、GR19和GR23等优良突变系。通过PCR方法和测序确定EPSPS基因突变位点,并利用RT-qPCR技术分析TaEPSPS-4A、TaEPSPS-7A和TaEPSPS-7D的表达水平。最后,通过设置不同剂量和生育期的田间药效试验,系统评估草甘膦使用效果,明确其适宜施用剂量和安全使用时期。【结果】经诱变的M2群体抗性突变频率为6.53×10-6,在M3代成功筛选出43株能够耐受4×推荐剂量草甘膦的突变株。测序分析表明,在抗性系GR1和GR19中,分别在TaEPSPS-7D检测到5和3个突变位点,而在GR23中则在TaEPSPS-4A检测到5个突变位点。表达分析表明,草甘膦处理后3个突变系中多数同源基因的表达水平显著下降,且该现象与基因是否发生抗性突变无关。大田药效试验证实,各剂量草甘膦处理对杂草的株防效均达100%,显著优于异丙隆;随着草甘膦剂量的增加,小麦苗高和鲜重呈下降趋势,但多数未达显著水平,表明其对生长无显著不利影响。产量分析显示,经1×和2×剂量处理后,减产不显著,而4×和8×剂量处理后,分别显著减产3.04%和4.63%。不同生育期施药试验进一步表明,苗期至拔节期喷施2×剂量草甘膦对植株生长无显著影响,但孕穗期施药则导致株高、鲜重和籽粒产量显著下降,减产达6.48%。【结论】结合EMS诱变与大田筛选创制抗草甘膦小麦新种质,可抗4×推荐剂量,EPSPS酶非活性中心的多个点突变增强了草甘膦抗性而不减产量,在生产上应用这类抗草甘膦品种时,防除杂草适期为小麦返青期(3月上旬),用41%草甘膦840—1680 g ae·hm-2,兑水450L·hm-2,选择无雨天气进行杂草茎叶喷雾处理。
基金supported by the National Natural Science Foundation of China(31970344)Joint Funds of the Natural Science Foundation of Hainan Province,China(2021JJLH0065).
文摘Soybean(Glycine max L.)is a globally vital crop for oil production and food security.High-quality genomic resources are instrumental for both functional genomics and breeding.Here,we report a near-complete,high-quality genome assembly of the elite cultivar Tianlong 1(TL1),featuring fully resolved telomeres and centromeres,as well as a gap-free assembly of 14 of its 20 chromosomes.On the basis of the genome assembly,we generate an ethyl methanesulfonate(EMS)-mutagenized population comprising 2555 M7 plants.Whole-genome resequencing of 288 EMS mutants uncovers 1,163,869 high-confidence single-nucleotide polymorphisms(SNPs)and 542,709 insertions/deletions(InDels),achieving 91.89%coverage of predicted protein-coding genes.Phenotypic screening demonstrates robust genotype–phenotype associations,with two nonsynonymous mutants displaying pronounced defects in seed and leaf development.Collectively,the chromosome-scale TL1 genome assembly and the extensively characterized mutant population establish valuable resources for functional genomics and precision breeding in soybean and related legume species.
基金The Key R&D Program of Hunan Province(Grant No.2025AQ2024)of the Department of Science and Technology of Hunan Province.Distinguished Young Scientists Fund(Grant No.24B0446)of Hunan Education Department.
文摘Internet of Things(IoTs)devices are bringing about a revolutionary change our society by enabling connectivity regardless of time and location.However,The extensive deployment of these devices also makes them attractive victims for themalicious actions of adversaries.Within the spectrumof existing threats,Side-ChannelAttacks(SCAs)have established themselves as an effective way to compromise cryptographic implementations.These attacks exploit unintended,unintended physical leakage that occurs during the cryptographic execution of devices,bypassing the theoretical strength of the crypto design.In recent times,the advancement of deep learning has provided SCAs with a powerful ally.Well-trained deep-learningmodels demonstrate an exceptional capacity to identify correlations between side-channel measurements and sensitive data,thereby significantly enhancing such attacks.To further understand the security threats posed by deep-learning SCAs and to aid in formulating robust countermeasures in the future,this paper undertakes an exhaustive investigation of leading-edge SCAs targeting Advanced Encryption Standard(AES)implementations.The study specifically focuses on attacks that exploit power consumption and electromagnetic(EM)emissions as primary leakage sources,systematically evaluating the extent to which diverse deep learning techniques enhance SCAs acrossmultiple critical dimensions.These dimensions include:(i)the characteristics of publicly available datasets derived from various hardware and software platforms;(ii)the formalization of leakage models tailored to different attack scenarios;(iii)the architectural suitability and performance of state-of-the-art deep learning models.Furthermore,the survey provides a systematic synthesis of current research findings,identifies significant unresolved issues in the existing literature and suggests promising directions for future work,including cross-device attack transferability and the impact of quantum-classical hybrid computing on side-channel security.
文摘As the healthcare system advances and expands in its services,the challenges of remaining efficient become more important.Emergency medical services(EMS)are vital cornerstones of communities.In many countries,EMS is available for every individual,regardless of their social or insurance status,via a toll-free telephone number.Understanding the risk factors for busy days in EMSs might be helpful for improving the allocation of resources,which is the key to better care for all patients in the prehospital setting.[1]An important factor influencing ambulance call volume could be the interplay of public behavior and weather.
