Background Quantifying the potential benefits of advanced footwear technology(AFT)track shoes(i.e.,“spikes”)in middle-distance events is challenging,because repeated maximal effort trials(as in sprinting)or aerobic ...Background Quantifying the potential benefits of advanced footwear technology(AFT)track shoes(i.e.,“spikes”)in middle-distance events is challenging,because repeated maximal effort trials(as in sprinting)or aerobic running economy trials(as in long-distance running)are not feasible.Methods We introduce a novel approach to assess the benefits of AFT spikes,consisting of a series of 200-m runs at self-perceived middle-distance race pace with 10 min recovery,and conduct 4 experiments to evaluate its validity,sensitivity,reproducibility,and utility.Results In Experiment 1,participants ran 1.2%slower in spikes with 200 g added mass vs.control spikes,which is exactly equal to the known effects of shoe mass on running performance.In Experiment 2,participants ran significantly faster in AFT prototype spikes vs.traditional spikes.In Experiment 3,we compared 2 other AFT prototype spikes against traditional spikes on 3 separate days.Group-level results were consistent across days,but our data indicates that at least 2 separate sessions are needed to evaluate individual responses.In Experiment 4,participants ran significantly faster in 2 AFT spike models vs.traditional spikes(2.1%and 1.6%).Speed was similar between a third AFT spike model and the traditional spikes.These speed results were mirrored by changes in step length as participants took significantly longer steps in the 2 faster AFT spike models(2.3%and 1.9%),while step length was similar between the other spikes.Conclusion Our novel,interval-based approach is a valid and reliable method for quantifying differences between spikes at middle-distance running intensity.展开更多
Grain yield variation has been associated to variation in grain number per unit area(GN).It has been shown in the last about 40 years that GN is linearly associated to the spike dry weight(SDW)at anthesis in wheat,fac...Grain yield variation has been associated to variation in grain number per unit area(GN).It has been shown in the last about 40 years that GN is linearly associated to the spike dry weight(SDW)at anthesis in wheat,fact that has been useful to understand mechanistically potential grain yield.Fruiting efficiency(FE,grains per gram of spike dry weight),the slope between GN and SDW relationship,has been proposed as a possible trait to improve wheat yield potential.The linear relationship between GN and SDW implies a constant increase in GN per unit increase in spike growth and,then a constant FE.However,there are empirical and theoretical elements suggesting that this relationship would not be linear.In this study,we hypothesised and showed that the linearity of the relationship between GN and SDW would be non-linear for extreme values of SDW,implying that the FE would be noticeably reduced at these extreme cases of dry matter allocation to the juvenile spikes.These results have implications for both,genetic and management improvements in grain yield.展开更多
Spiking Neural Network(SNN)inspired by the biological triggering mechanism of neurons to provide a novel solution for plant disease detection,offering enhanced performance and efficiency in contrast to Artificial Neur...Spiking Neural Network(SNN)inspired by the biological triggering mechanism of neurons to provide a novel solution for plant disease detection,offering enhanced performance and efficiency in contrast to Artificial Neural Networks(ANN).Unlike conventional ANNs,which process static images without fully capturing the inherent temporal dynamics,our approach represents the first implementation of SNNs tailored explicitly for agricultural disease classification,integrating an encoding method to convert static RGB plant images into temporally encoded spike trains.Additionally,while Bernoulli trials and standard deep learning architectures likeConvolutionalNeuralNetworks(CNNs)and Fully Connected Neural Networks(FCNNs)have been used extensively,our work is the first to integrate these trials within an SNN framework specifically for agricultural applications.This integration not only refines spike regulation and reduces computational overhead by 30%but also delivers superior accuracy(93.4%)in plant disease classification,marking a significant advancement in precision agriculture that has not been previously explored.Our approach uniquely transforms static plant leaf images into time-dependent representations,leveraging SNNs’intrinsic temporal processing capabilities.This approach aligns with the inherent ability of SNNs to capture dynamic,timedependent patterns,making them more suitable for detecting disease activations in plants than conventional ANNs that treat inputs as static entities.Unlike prior works,our hybrid encoding scheme dynamically adapts to pixel intensity variations(via threshold),enabling robust feature extraction under diverse agricultural conditions.The dual-stage preprocessing customizes the SNN’s behavior in two ways:the encoding threshold is derived from pixel distributions in diseased regions,and Bernoulli trials selectively reduce redundant spikes to ensure energy efficiency on low-power devices.We used a comprehensive dataset of 87,000 RGB images of plant leaves,which included 38 distinct classes of healthy and unhealthy leaves.To train and evaluate three distinct neural network architectures,DeepSNN,SimpleCNN,and SimpleFCNN,the dataset was rigorously preprocessed,including stochastic rotation,horizontal flip,resizing,and normalization.Moreover,by integrating Bernoulli trials to regulate spike generation,ourmethod focuses on extracting themost relevant featureswhile reducingcomputational overhead.Using a comprehensivedatasetof87,000RGB images across 38 classes,we rigorously preprocessed the data and evaluated three architectures:DeepSNN,SimpleCNN,and SimpleFCNN.The results demonstrate that DeepSNN outperforms the other models,achieving superior accuracy,efficient feature extraction,and robust spike management,thereby establishing the potential of SNNs for real-time,energy-efficient agricultural applications.展开更多
Epileptic seizures are known for their unpredictable nature.However,recent research provides that the transition to seizure event is not random but the result of evidence accumulations.Therefore,a reliable method capa...Epileptic seizures are known for their unpredictable nature.However,recent research provides that the transition to seizure event is not random but the result of evidence accumulations.Therefore,a reliable method capable to detect these indications can predict seizures and improve the life quality of epileptic patients.Seizures periods are generally characterized by epileptiform discharges with different changes including spike rate variation according to the shapes,spikes,and the amplitude.In this study,spike rate is used as the indicator to anticipate seizures in electroencephalogram(EEG) signal.Spikes detection step is used in EEG signal during interictal,preictal,and ictal periods followed by a mean filter to smooth the spike number.The maximum spike rate in interictal periods is used as an indicator to predict seizures.When the spike number in the preictal period exceeds the threshold,an alarm is triggered.Using the CHB-MIT database,the proposed approach has ensured92% accuracy in seizure prediction for all patients.展开更多
BACKGROUND Epilepsy is a syndrome characterized by transient,rigid,paroxysmal,and repetitive central nervous system dysfunction.Prevention,control,and improvement of cognitive and behavioral dysfunction are of great s...BACKGROUND Epilepsy is a syndrome characterized by transient,rigid,paroxysmal,and repetitive central nervous system dysfunction.Prevention,control,and improvement of cognitive and behavioral dysfunction are of great significance for improving the patients’intellectual development and quality of life.Electroencephalograms(EEG)can predict an accelerated decline in cognitive function.AIM To determine the clinical and EEG characteristics and treatment results of benign epilepsy in spiking children.METHODS A total of 106 cases of benign epilepsy in children with myocardial spines treated at our hospital from January 2017 to January 2020 were selected.Differences in clinical data and EGG characteristics between treatment-effective/-ineffective patients were analyzed,and children’s intellectual development before and after treatment evaluated using the Gesell Development Diagnostic Scale.RESULTS EEG showed that the discharge proportion in the awake and sleep periods was 66.04%,and the peak/peak discharge was mainly single-sided,accounting for 81.13%,while the discharge generalization accounted for 31.13%.There was no significant difference in any of these variables between sexes and ages(P>0.05).The proportion of patients with early onset(<5 years old)and seizure frequency>3 times/half a year was 40.00%and 60.00%,respectively;the incidence rate and seizure frequency in the younger age group(<5 years old)were significantly higher than those in the treatment-effective group(P<0.05),while the discharge index was significantly lower than that in the treatment-effective group(P<0.05).The discharge index was negatively correlated with fine motor skill and language development(r=-0.274 and-0.247,respectively;P<0.05),but not with the rest(P>0.05).Logistic regression analysis showed that low age onset(<5 years old)and seizure frequency were the factors affecting ineffective-treatment of benign epilepsy in children(odds ratio=11.304 and 5.784,respectively;P<0.05).The discharge index of the responsive group after treatment was significantly lower than that of the unresponsive group(P<0.05).However,there was no significant difference between groups after treatment in gross and fine motor skills,adaptability,language,and personal social development(P>0.05).CONCLUSION The EEG of children with benign epilepsy due to spinal wave in central time zone has characteristic changes,and the therapeutic effect is influenced by age of onset and attack frequency.展开更多
Fusarium head blight (FHB) caused by Fusarium graminearum is a devastating disease that results in extensive yield losses to wheat and barley. A green fluorescent protein (GFP) expressing plasmid pRP22-GFP was constru...Fusarium head blight (FHB) caused by Fusarium graminearum is a devastating disease that results in extensive yield losses to wheat and barley. A green fluorescent protein (GFP) expressing plasmid pRP22-GFP was constructed for monitoring the colonization of two biocontrol agents, Brevibacillus brevis ZJY-1 and Bacillus subtilis ZJY-116, on the spikes of barley and their effect on suppression of FHB. Survival and colonization of the Brevibacillus brevis ZJY-1 and Bacillus subtilis ZJY-116 strains on spikes of barley were observed by tracking the bacterial transformants with GFP expression. Our field study revealed that plasmid pRP22-GFP was stably maintained in the bacterial strains without selective pressure. The retrieved GFP-tagged strains showed that the bacterial population fluctuation accorded with that of the rain events. Furthermore, both biocontrol strains gave significant protection against FHB on spikes of barley in fields. The greater suppression of barley FHB disease was resulted from the treat-ment of barley spikes with biocontrol agents before inoculation with F. graminearum.展开更多
This paper investigates the finite-thickness effect of two superimposed fluids on bubbles and spikes in Richtmyer–Meshkov instability(RMI) for arbitrary Atwood numbers by using the method of the small parameter expan...This paper investigates the finite-thickness effect of two superimposed fluids on bubbles and spikes in Richtmyer–Meshkov instability(RMI) for arbitrary Atwood numbers by using the method of the small parameter expansion up to the second order. When the thickness of the two fluids tends to be infinity, our results can reproduce the classical results where RMI happens at the interface separating two semi-infinity-thickness fluids of different densities. It is found that the thickness has a large influence on the amplitude evolution of bubbles and spikes compared with those in classical RMI. Based on the thickness relationship of the two fluids, the thickness effect on bubbles and spikes for four cases is discussed. The thickness encourages(or reduces)the growth of bubbles or spikes, depending on not only Atwood number, but also the relationship of the thickness ratio of the heavy and light fluids, which is explicitly determined in this paper.展开更多
Data processing for seismic network is very complex and fussy,because a lot of data is recorded in seismicnetwork every day,which make it impossible to process these data all by manual work.Therefore,seismic datashoul...Data processing for seismic network is very complex and fussy,because a lot of data is recorded in seismicnetwork every day,which make it impossible to process these data all by manual work.Therefore,seismic datashould be processed automatically to produce a initial results about events detection and location.Afterwards,these results are reviewed and modified by analyst.In automatic processing data quality checking is important.There are three main problem data that exist in real seismic records,which include:spike,repeated data and展开更多
This paper presents a spikes removing methodology for ultrasonic rangefinders with an application to a quadrotor unmanned aerial vehicle. Ultrasonic sensors suffer from spikes in distance measurements due to specular ...This paper presents a spikes removing methodology for ultrasonic rangefinders with an application to a quadrotor unmanned aerial vehicle. Ultrasonic sensors suffer from spikes in distance measurements due to specular reflectance and acoustic noise. Removing these spikes is necessary for improving the hovering performance of the quadrotor. The spikes removing algorithm is based on the discrete wavelet transform. The algorithm is implemented in simulation to study the effect of the altitude measurement spikes on the control performance of the quadrotor with and without the algorithm. The algorithm is also implemented digitally on ultrasonic measurements from a real flight. Results show that the method is capable of rejecting the spikes in the measurements efficiently leaving the altitude control signal unaffected.展开更多
The characteristics of the millisecond spikes with short durations and weak flux densities which were observed with high time resolution (1 ms) during a great type Ⅳ solar radio burst of 1990 July 30 are introduced. ...The characteristics of the millisecond spikes with short durations and weak flux densities which were observed with high time resolution (1 ms) during a great type Ⅳ solar radio burst of 1990 July 30 are introduced. The time profiles of the spikes are statistically analyzed and the parameters of the spike source are also estimated.展开更多
Tangrams奖前身为亚洲营销实效和策略奖,如今为亚洲顶尖创意奖(Spikes Asia Awards)下设的一个主要奖项,包括实效类、媒介策略类、数字策略类、大数据和分析以及电子商务类几个类别。作为亚太区最大规模的策略和实效类奖项,Tangrams表...Tangrams奖前身为亚洲营销实效和策略奖,如今为亚洲顶尖创意奖(Spikes Asia Awards)下设的一个主要奖项,包括实效类、媒介策略类、数字策略类、大数据和分析以及电子商务类几个类别。作为亚太区最大规模的策略和实效类奖项,Tangrams表彰的是活动作品中所展现的先进营销实效思维,以及最出色的有效品牌构建和稳健的商业转化结果,在创意卓越之外,又为行业提供了营销策略和实效方面的基准。展开更多
We review examples of placement of select Cenozoic Global Boundary Stratotype Sections and Points(GSSP=“golden spikes”)from a geochemical and magnetostratigraphic perspective.Though biostratigraphy is the sine qua n...We review examples of placement of select Cenozoic Global Boundary Stratotype Sections and Points(GSSP=“golden spikes”)from a geochemical and magnetostratigraphic perspective.Though biostratigraphy is the sine qua non for placing modern chronologic tools(high-resolution radiometric dates,magnetochronology,and astrochronology)into proper stratigraphic context,its use as the primary correlation tool for GSSP is less desirable than using magnetostratigraphic or chemostratigraphic markers.Here,we advocate for defining of GSSPs at lithologic levels that are globally correlatable using magnetic reversals and/or abrupt geochemical changes,and the avoidance of biostratigraphic datum levels(that are necessarily biogeographically restricted)as primary criterion for correlation.展开更多
When a mass spreads in a turbulent flow, areas with obviously high concentration of the mass compared with surrounding areas are formed by organized structures of turbulence. In this study, we extract the high concent...When a mass spreads in a turbulent flow, areas with obviously high concentration of the mass compared with surrounding areas are formed by organized structures of turbulence. In this study, we extract the high concentration areas and investigate their diffusion process. For this purpose, a combination of Planar Laser Induced Fluorescence (PLIF) and Particle Image Velocimetry (PIV) techniques was employed to obtain simultaneously the two fields of the concentration of injected dye and of the velocity in a water turbulent channel flow. With focusing on a quasi-homogeneous turbulence in the channel central region, a series of PLIF and PIV images were acquired at several different downstream positions. We applied a conditional sampling technique to the PLIF images to extract the high concentration areas, or spikes, and calculated the conditional-averaged statistics of the extracted areas such as length scale, mean concentration, and turbulent diffusion coefficient. We found that the averaged length scale was constant with downstream distance from the diffusion source and was smaller than integral scale of the turbulent eddies. The spanwise distribution of the mean concentration was basically Gaussian, and the spanwise width of the spikes increased linearly with downstream distance from the diffusion source. Moreover, the turbulent diffusion coefficient was found to increase in proportion to the spanwise distance from the source. These results reveal aspects different from those of regular mass diffusion and let us conclude that the diffusion process of the spikes differs from that of regular mass diffusion.展开更多
In recent years, blind source separation （BSS） by independent component analysis （ICA） has been drawing much attention because of its potential applications in signal processing such as in speech recognition syste...In recent years, blind source separation （BSS） by independent component analysis （ICA） has been drawing much attention because of its potential applications in signal processing such as in speech recognition systems, telecommunication and medical signal processing. In this paper, two algorithms of independent component analysis （fixed-point IC,4 and natural gradient-flexible ICA） are adopted to extract human epileptic feature spikes from interferential signals. Experiment results show that epileptic spikes can be extracted from noise successfully. The kurtosis of the epileptic component signal separated is much better than that of other noisy signals. It shows that ICA is an effective tool to extract epileptic spikes from patients＇ electroencephalogram EEG and shows promising application to assist physicians to diagnose epilepsy and estimate the epileptogenic region in clinic.展开更多
基金partly supported by a research contract from PUMA SE with the University of Massachusetts,Amherst.
文摘Background Quantifying the potential benefits of advanced footwear technology(AFT)track shoes(i.e.,“spikes”)in middle-distance events is challenging,because repeated maximal effort trials(as in sprinting)or aerobic running economy trials(as in long-distance running)are not feasible.Methods We introduce a novel approach to assess the benefits of AFT spikes,consisting of a series of 200-m runs at self-perceived middle-distance race pace with 10 min recovery,and conduct 4 experiments to evaluate its validity,sensitivity,reproducibility,and utility.Results In Experiment 1,participants ran 1.2%slower in spikes with 200 g added mass vs.control spikes,which is exactly equal to the known effects of shoe mass on running performance.In Experiment 2,participants ran significantly faster in AFT prototype spikes vs.traditional spikes.In Experiment 3,we compared 2 other AFT prototype spikes against traditional spikes on 3 separate days.Group-level results were consistent across days,but our data indicates that at least 2 separate sessions are needed to evaluate individual responses.In Experiment 4,participants ran significantly faster in 2 AFT spike models vs.traditional spikes(2.1%and 1.6%).Speed was similar between a third AFT spike model and the traditional spikes.These speed results were mirrored by changes in step length as participants took significantly longer steps in the 2 faster AFT spike models(2.3%and 1.9%),while step length was similar between the other spikes.Conclusion Our novel,interval-based approach is a valid and reliable method for quantifying differences between spikes at middle-distance running intensity.
基金mainly funded by the State Research Agency of Spain through the Competitive Project PID2021-127415OB-I00 on "Spike fertility in wheat" with some contribution from an AGROTECNIO Seed-funding on "Analysing the physiology of spike density to provide support to selection in breeding programs"RAS did part of the work in this project during a research stay at the Crop Physiology Lab of the University of Lleida co-funded by AUIP (Postgraduate Iberoamerican University Association) grants+1 种基金core funds Crop Physiology Lab of the Ud L. CSC held a Maria Zambrano’s fellowship from the University of Lleida funded by the Spanish Ministry of Universities and the European Social Fund and is a member of CONICET (the Scientific Research Council of Argentina)INTA (the National Institute of Agriculture Technology of Argentina)
文摘Grain yield variation has been associated to variation in grain number per unit area(GN).It has been shown in the last about 40 years that GN is linearly associated to the spike dry weight(SDW)at anthesis in wheat,fact that has been useful to understand mechanistically potential grain yield.Fruiting efficiency(FE,grains per gram of spike dry weight),the slope between GN and SDW relationship,has been proposed as a possible trait to improve wheat yield potential.The linear relationship between GN and SDW implies a constant increase in GN per unit increase in spike growth and,then a constant FE.However,there are empirical and theoretical elements suggesting that this relationship would not be linear.In this study,we hypothesised and showed that the linearity of the relationship between GN and SDW would be non-linear for extreme values of SDW,implying that the FE would be noticeably reduced at these extreme cases of dry matter allocation to the juvenile spikes.These results have implications for both,genetic and management improvements in grain yield.
基金supported in part by the Basic Science Research Program through the National Research Foundation of Korea(NRF),funded by the Ministry of Education(NRF-2021R1A6A1A03039493).
文摘Spiking Neural Network(SNN)inspired by the biological triggering mechanism of neurons to provide a novel solution for plant disease detection,offering enhanced performance and efficiency in contrast to Artificial Neural Networks(ANN).Unlike conventional ANNs,which process static images without fully capturing the inherent temporal dynamics,our approach represents the first implementation of SNNs tailored explicitly for agricultural disease classification,integrating an encoding method to convert static RGB plant images into temporally encoded spike trains.Additionally,while Bernoulli trials and standard deep learning architectures likeConvolutionalNeuralNetworks(CNNs)and Fully Connected Neural Networks(FCNNs)have been used extensively,our work is the first to integrate these trials within an SNN framework specifically for agricultural applications.This integration not only refines spike regulation and reduces computational overhead by 30%but also delivers superior accuracy(93.4%)in plant disease classification,marking a significant advancement in precision agriculture that has not been previously explored.Our approach uniquely transforms static plant leaf images into time-dependent representations,leveraging SNNs’intrinsic temporal processing capabilities.This approach aligns with the inherent ability of SNNs to capture dynamic,timedependent patterns,making them more suitable for detecting disease activations in plants than conventional ANNs that treat inputs as static entities.Unlike prior works,our hybrid encoding scheme dynamically adapts to pixel intensity variations(via threshold),enabling robust feature extraction under diverse agricultural conditions.The dual-stage preprocessing customizes the SNN’s behavior in two ways:the encoding threshold is derived from pixel distributions in diseased regions,and Bernoulli trials selectively reduce redundant spikes to ensure energy efficiency on low-power devices.We used a comprehensive dataset of 87,000 RGB images of plant leaves,which included 38 distinct classes of healthy and unhealthy leaves.To train and evaluate three distinct neural network architectures,DeepSNN,SimpleCNN,and SimpleFCNN,the dataset was rigorously preprocessed,including stochastic rotation,horizontal flip,resizing,and normalization.Moreover,by integrating Bernoulli trials to regulate spike generation,ourmethod focuses on extracting themost relevant featureswhile reducingcomputational overhead.Using a comprehensivedatasetof87,000RGB images across 38 classes,we rigorously preprocessed the data and evaluated three architectures:DeepSNN,SimpleCNN,and SimpleFCNN.The results demonstrate that DeepSNN outperforms the other models,achieving superior accuracy,efficient feature extraction,and robust spike management,thereby establishing the potential of SNNs for real-time,energy-efficient agricultural applications.
文摘Epileptic seizures are known for their unpredictable nature.However,recent research provides that the transition to seizure event is not random but the result of evidence accumulations.Therefore,a reliable method capable to detect these indications can predict seizures and improve the life quality of epileptic patients.Seizures periods are generally characterized by epileptiform discharges with different changes including spike rate variation according to the shapes,spikes,and the amplitude.In this study,spike rate is used as the indicator to anticipate seizures in electroencephalogram(EEG) signal.Spikes detection step is used in EEG signal during interictal,preictal,and ictal periods followed by a mean filter to smooth the spike number.The maximum spike rate in interictal periods is used as an indicator to predict seizures.When the spike number in the preictal period exceeds the threshold,an alarm is triggered.Using the CHB-MIT database,the proposed approach has ensured92% accuracy in seizure prediction for all patients.
文摘BACKGROUND Epilepsy is a syndrome characterized by transient,rigid,paroxysmal,and repetitive central nervous system dysfunction.Prevention,control,and improvement of cognitive and behavioral dysfunction are of great significance for improving the patients’intellectual development and quality of life.Electroencephalograms(EEG)can predict an accelerated decline in cognitive function.AIM To determine the clinical and EEG characteristics and treatment results of benign epilepsy in spiking children.METHODS A total of 106 cases of benign epilepsy in children with myocardial spines treated at our hospital from January 2017 to January 2020 were selected.Differences in clinical data and EGG characteristics between treatment-effective/-ineffective patients were analyzed,and children’s intellectual development before and after treatment evaluated using the Gesell Development Diagnostic Scale.RESULTS EEG showed that the discharge proportion in the awake and sleep periods was 66.04%,and the peak/peak discharge was mainly single-sided,accounting for 81.13%,while the discharge generalization accounted for 31.13%.There was no significant difference in any of these variables between sexes and ages(P>0.05).The proportion of patients with early onset(<5 years old)and seizure frequency>3 times/half a year was 40.00%and 60.00%,respectively;the incidence rate and seizure frequency in the younger age group(<5 years old)were significantly higher than those in the treatment-effective group(P<0.05),while the discharge index was significantly lower than that in the treatment-effective group(P<0.05).The discharge index was negatively correlated with fine motor skill and language development(r=-0.274 and-0.247,respectively;P<0.05),but not with the rest(P>0.05).Logistic regression analysis showed that low age onset(<5 years old)and seizure frequency were the factors affecting ineffective-treatment of benign epilepsy in children(odds ratio=11.304 and 5.784,respectively;P<0.05).The discharge index of the responsive group after treatment was significantly lower than that of the unresponsive group(P<0.05).However,there was no significant difference between groups after treatment in gross and fine motor skills,adaptability,language,and personal social development(P>0.05).CONCLUSION The EEG of children with benign epilepsy due to spinal wave in central time zone has characteristic changes,and the therapeutic effect is influenced by age of onset and attack frequency.
基金Project supported by the National Natural Science Foundation of China (No. 30230250)Science and Technology Committee of Zhejiang Province (No. 2003C22029), China
文摘Fusarium head blight (FHB) caused by Fusarium graminearum is a devastating disease that results in extensive yield losses to wheat and barley. A green fluorescent protein (GFP) expressing plasmid pRP22-GFP was constructed for monitoring the colonization of two biocontrol agents, Brevibacillus brevis ZJY-1 and Bacillus subtilis ZJY-116, on the spikes of barley and their effect on suppression of FHB. Survival and colonization of the Brevibacillus brevis ZJY-1 and Bacillus subtilis ZJY-116 strains on spikes of barley were observed by tracking the bacterial transformants with GFP expression. Our field study revealed that plasmid pRP22-GFP was stably maintained in the bacterial strains without selective pressure. The retrieved GFP-tagged strains showed that the bacterial population fluctuation accorded with that of the rain events. Furthermore, both biocontrol strains gave significant protection against FHB on spikes of barley in fields. The greater suppression of barley FHB disease was resulted from the treat-ment of barley spikes with biocontrol agents before inoculation with F. graminearum.
基金supported by National Natural Science Foundation of China (Nos. U1530261,91852203,and 11472278)the Innovation Fund of Fundamental Technology Institute of All Value In Creation (No. JCY2015A005)+2 种基金the Natural Science Foundation of Sichuan Province (Nos. 18ZA0260,and 2018JY0454)the Natural Science Foundation of Mianyang Normal University (Nos. HX2017007,MYSY2017JC06 and MYSY2018T004)the National High-Tech Inertial Confinement Fusion Committee
文摘This paper investigates the finite-thickness effect of two superimposed fluids on bubbles and spikes in Richtmyer–Meshkov instability(RMI) for arbitrary Atwood numbers by using the method of the small parameter expansion up to the second order. When the thickness of the two fluids tends to be infinity, our results can reproduce the classical results where RMI happens at the interface separating two semi-infinity-thickness fluids of different densities. It is found that the thickness has a large influence on the amplitude evolution of bubbles and spikes compared with those in classical RMI. Based on the thickness relationship of the two fluids, the thickness effect on bubbles and spikes for four cases is discussed. The thickness encourages(or reduces)the growth of bubbles or spikes, depending on not only Atwood number, but also the relationship of the thickness ratio of the heavy and light fluids, which is explicitly determined in this paper.
基金National Natural Science Foundation of China (60172026).
文摘Data processing for seismic network is very complex and fussy,because a lot of data is recorded in seismicnetwork every day,which make it impossible to process these data all by manual work.Therefore,seismic datashould be processed automatically to produce a initial results about events detection and location.Afterwards,these results are reviewed and modified by analyst.In automatic processing data quality checking is important.There are three main problem data that exist in real seismic records,which include:spike,repeated data and
文摘This paper presents a spikes removing methodology for ultrasonic rangefinders with an application to a quadrotor unmanned aerial vehicle. Ultrasonic sensors suffer from spikes in distance measurements due to specular reflectance and acoustic noise. Removing these spikes is necessary for improving the hovering performance of the quadrotor. The spikes removing algorithm is based on the discrete wavelet transform. The algorithm is implemented in simulation to study the effect of the altitude measurement spikes on the control performance of the quadrotor with and without the algorithm. The algorithm is also implemented digitally on ultrasonic measurements from a real flight. Results show that the method is capable of rejecting the spikes in the measurements efficiently leaving the altitude control signal unaffected.
文摘The characteristics of the millisecond spikes with short durations and weak flux densities which were observed with high time resolution (1 ms) during a great type Ⅳ solar radio burst of 1990 July 30 are introduced. The time profiles of the spikes are statistically analyzed and the parameters of the spike source are also estimated.
文摘Tangrams奖前身为亚洲营销实效和策略奖,如今为亚洲顶尖创意奖(Spikes Asia Awards)下设的一个主要奖项,包括实效类、媒介策略类、数字策略类、大数据和分析以及电子商务类几个类别。作为亚太区最大规模的策略和实效类奖项,Tangrams表彰的是活动作品中所展现的先进营销实效思维,以及最出色的有效品牌构建和稳健的商业转化结果,在创意卓越之外,又为行业提供了营销策略和实效方面的基准。
文摘We review examples of placement of select Cenozoic Global Boundary Stratotype Sections and Points(GSSP=“golden spikes”)from a geochemical and magnetostratigraphic perspective.Though biostratigraphy is the sine qua non for placing modern chronologic tools(high-resolution radiometric dates,magnetochronology,and astrochronology)into proper stratigraphic context,its use as the primary correlation tool for GSSP is less desirable than using magnetostratigraphic or chemostratigraphic markers.Here,we advocate for defining of GSSPs at lithologic levels that are globally correlatable using magnetic reversals and/or abrupt geochemical changes,and the avoidance of biostratigraphic datum levels(that are necessarily biogeographically restricted)as primary criterion for correlation.
文摘When a mass spreads in a turbulent flow, areas with obviously high concentration of the mass compared with surrounding areas are formed by organized structures of turbulence. In this study, we extract the high concentration areas and investigate their diffusion process. For this purpose, a combination of Planar Laser Induced Fluorescence (PLIF) and Particle Image Velocimetry (PIV) techniques was employed to obtain simultaneously the two fields of the concentration of injected dye and of the velocity in a water turbulent channel flow. With focusing on a quasi-homogeneous turbulence in the channel central region, a series of PLIF and PIV images were acquired at several different downstream positions. We applied a conditional sampling technique to the PLIF images to extract the high concentration areas, or spikes, and calculated the conditional-averaged statistics of the extracted areas such as length scale, mean concentration, and turbulent diffusion coefficient. We found that the averaged length scale was constant with downstream distance from the diffusion source and was smaller than integral scale of the turbulent eddies. The spanwise distribution of the mean concentration was basically Gaussian, and the spanwise width of the spikes increased linearly with downstream distance from the diffusion source. Moreover, the turbulent diffusion coefficient was found to increase in proportion to the spanwise distance from the source. These results reveal aspects different from those of regular mass diffusion and let us conclude that the diffusion process of the spikes differs from that of regular mass diffusion.
基金973 Project (No. 2003CB71606) and National Natural Science Foundation of China (No.30400105, 90208003)
文摘In recent years, blind source separation （BSS） by independent component analysis （ICA） has been drawing much attention because of its potential applications in signal processing such as in speech recognition systems, telecommunication and medical signal processing. In this paper, two algorithms of independent component analysis （fixed-point IC,4 and natural gradient-flexible ICA） are adopted to extract human epileptic feature spikes from interferential signals. Experiment results show that epileptic spikes can be extracted from noise successfully. The kurtosis of the epileptic component signal separated is much better than that of other noisy signals. It shows that ICA is an effective tool to extract epileptic spikes from patients＇ electroencephalogram EEG and shows promising application to assist physicians to diagnose epilepsy and estimate the epileptogenic region in clinic.
