Lexical meaning mainly includes rational meaning,grammatical meaning,and coloring meaning.Mastering the coloring meaning of vocabulary is of great significance for foreign students to use Chinese vocabulary correctly....Lexical meaning mainly includes rational meaning,grammatical meaning,and coloring meaning.Mastering the coloring meaning of vocabulary is of great significance for foreign students to use Chinese vocabulary correctly.This study mainly examines the psychological mechanism of Chinese second language learners mastering the coloring meaning of words,examines the psychological characteristics of students mastering the color meaning of words from the perspectives of second language learning theory and cognitive theory,establishes a cognitive schema for coloring meaning learning,and proposes corresponding learning models and teaching strategies.展开更多
A novel visually meaningful image encryption algorithm is proposed based on a hyperchaotic system and compressive sensing(CS), which aims to improve the visual security of steganographic image and decrypted quality. F...A novel visually meaningful image encryption algorithm is proposed based on a hyperchaotic system and compressive sensing(CS), which aims to improve the visual security of steganographic image and decrypted quality. First, a dynamic spiral block scrambling is designed to encrypt the sparse matrix generated by performing discrete wavelet transform(DWT)on the plain image. Then, the encrypted image is compressed and quantified to obtain the noise-like cipher image. Then the cipher image is embedded into the alpha channel of the carrier image in portable network graphics(PNG) format to generate the visually meaningful steganographic image. In our scheme, the hyperchaotic Lorenz system controlled by the hash value of plain image is utilized to construct the scrambling matrix, the measurement matrix and the embedding matrix to achieve higher security. In addition, compared with other existing encryption algorithms, the proposed PNG-based embedding method can blindly extract the cipher image, thus effectively reducing the transmission cost and storage space. Finally, the experimental results indicate that the proposed encryption algorithm has very high visual security.展开更多
This study aims to be the first to use meta-analysis to explore the relationship between meaning in life(MIL)and mental health issues among older adults.A meta-analysis was conducted using six databases,resulting in 1...This study aims to be the first to use meta-analysis to explore the relationship between meaning in life(MIL)and mental health issues among older adults.A meta-analysis was conducted using six databases,resulting in 16 studies with 5,074 participants in total.The“metacor”and“forestplot”packages in R-Studio were used for data analysis.The total effect was calculated using a random-effects model,with I2=86%in the heterogeneity test.The results showed a moderate negative correlation between MIL and mental health issues among older adults,with an average effect of−0.37.Five potential moderating variables were examined:the conceptualization of MIL(value vs.purpose),region(Asian vs.Western countries),residence status(community vs.nursing home vs.hospital),types of mental health issues,and evaluation methods(clinical vs.non-clinical).The first four had no significant moderating effect.The mean correlation coefficients between mental health issues and value/purpose were−0.49/−0.33;the mean correlation coefficients in Asian countries and Western countries were−0.48 and−0.34;the mean correlation coefficients among participants living in community/nursing home/mixed status were−0.33/−0.40/−0.40;the mean correlation coefficients between MIL and depression/others were−0.37/−0.35;however,the negative relationship between MIL and mental health issues was stronger when non-clinical evaluations(self-report only)were used.Specifically,the mean correlation coefficient for non-clinical evaluations was−0.42 and for clinical evaluations was−0.29.This study is the first meta-analysis to identify the negative correlation between older adults’MIL and mental health issues.Significant moderating effects of evaluation methods were found.展开更多
Traditional image encryption algorithms transform a plain image into a noise-like image.To lower the chances for the encrypted image being detected by the attacker during the image transmission,a visually meaningful i...Traditional image encryption algorithms transform a plain image into a noise-like image.To lower the chances for the encrypted image being detected by the attacker during the image transmission,a visually meaningful image encryption scheme is suggested to hide the encrypted image using another carrier image.This paper proposes a visually meaningful encrypted image algorithm that hides a secret image and a digital signature which provides authenticity and confidentiality.The recovered digital signature is used for the purpose of identity authentication while the secret image is encrypted to protect its confidentiality.Least Significant Bit(LSB)method to embed signature on the encrypted image and Lifting Wavelet Transform(LWT)to generate a visually meaningful encrypted image are designed.The proposed algorithm has a keyspace of 139.5-bit,a Normalized Correlation(NC)value of 0.9998 which is closer to 1 and a Peak Signal to Noise Ratio(PSNR)with a value greater than 50 dB.Different analyses are also performed on the proposed algorithm using different images.The experimental results show that the proposed scheme is with high key sensitivity and strong robustness against pepper and salt attack and cropping attack.Moreover,the histogram analysis shows that the original carrier image and the final visual image are very similar.展开更多
Araby is a short story by the famous Irish stream-of-consciousness writer James Joyce.Through a series of images,the novel expresses the theme of the story:the“mental paralysis”of Dubliners and the“spiritual Epiph...Araby is a short story by the famous Irish stream-of-consciousness writer James Joyce.Through a series of images,the novel expresses the theme of the story:the“mental paralysis”of Dubliners and the“spiritual Epiphany”of the little boy,which reflects the spiritual barren of Dubliners at that time.Through the analysis of the symbolic meaning of many images in the work,this paper reveals the social background and religious significance hidden behind the images.展开更多
Cultural-loaded word is one of the most popular topics in translation studies.The theory of spirit transmission and meaning conveyance provides a new way for the translation of cultural-loaded word.Based on the A Happ...Cultural-loaded word is one of the most popular topics in translation studies.The theory of spirit transmission and meaning conveyance provides a new way for the translation of cultural-loaded word.Based on the A Happy Excursion,this paper makes a comparative analysis of the translation strategies of seven English versions.This study will reveal the similarities and differences between Chinese and foreign translators’translation strategies.展开更多
The research examines President Xi’s 2021 New Year speech with research questions centering around its abundant interpersonal meanings.Through qualitative content analysis,the research finds that it is typical for Ch...The research examines President Xi’s 2021 New Year speech with research questions centering around its abundant interpersonal meanings.Through qualitative content analysis,the research finds that it is typical for Chinese president to frequently use judgment and appreciation resources in reviewing the past year.Even in the face of the pandemic and natural disasters,the overall emotions of the speech remain positive,which corresponds to the forward-looking feature of New Year speech.Significance of the study abounds and future research can investigate how COVID-19 impacts the ideologies conveyed through political leaders’speeches through a comparative lens and how to produce more understandings that can help dismantle stereotypes and discrimination hidden in reports about COVID-19 by using Appraisal Theory critically,systematically,and comprehensively.展开更多
工业数据由于技术故障和人为因素通常导致数据异常,现有基于约束的方法因约束阈值设置的过于宽松或严格会导致修复错误,基于统计的方法因平滑修复机制导致对时间步长较远的异常值修复准确度较低.针对上述问题,提出了基于奖励机制的最小...工业数据由于技术故障和人为因素通常导致数据异常,现有基于约束的方法因约束阈值设置的过于宽松或严格会导致修复错误,基于统计的方法因平滑修复机制导致对时间步长较远的异常值修复准确度较低.针对上述问题,提出了基于奖励机制的最小迭代修复和改进WGAN混合模型的时序数据修复方法.首先,在预处理阶段,保留异常数据,进行信息标注等处理,从而充分挖掘异常值与真实值之间的特征约束.其次,在噪声模块提出了近邻参数裁剪规则,用于修正最小迭代修复公式生成的噪声向量.将其传递至模拟分布模块的生成器中,同时设计了一个动态时间注意力网络层,用于提取时序特征权重并与门控循环单元串联组合捕捉不同步长的特征依赖,并引入递归多步预测原理共同提升模型的表达能力;在判别器中设计了Abnormal and Truth奖励机制和Weighted Mean Square Error损失函数共同反向优化生成器修复数据的细节和质量.最后,在公开数据集和真实数据集上的实验结果表明,该方法的修复准确度与模型稳定性显著优于现有方法.展开更多
In 2023,the majority of the Earth witnessed its warmest boreal summer and autumn since 1850.Whether 2023 will indeed turn out to be the warmest year on record and what caused the astonishingly large margin of warming ...In 2023,the majority of the Earth witnessed its warmest boreal summer and autumn since 1850.Whether 2023 will indeed turn out to be the warmest year on record and what caused the astonishingly large margin of warming has become one of the hottest topics in the scientific community and is closely connected to the future development of human society.We analyzed the monthly varying global mean surface temperature(GMST)in 2023 and found that the globe,the land,and the oceans in 2023 all exhibit extraordinary warming,which is distinct from any previous year in recorded history.Based on the GMST statistical ensemble prediction model developed at the Institute of Atmospheric Physics,the GMST in 2023 is predicted to be 1.41℃±0.07℃,which will certainly surpass that in 2016 as the warmest year since 1850,and is approaching the 1.5℃ global warming threshold.Compared to 2022,the GMST in 2023 will increase by 0.24℃,with 88%of the increment contributed by the annual variability as mostly affected by El Niño.Moreover,the multidecadal variability related to the Atlantic Multidecadal Oscillation(AMO)in 2023 also provided an important warming background for sparking the GMST rise.As a result,the GMST in 2023 is projected to be 1.15℃±0.07℃,with only a 0.02℃ increment,if the effects of natural variability—including El Niño and the AMO—are eliminated and only the global warming trend is considered.展开更多
According to the latest version(version 2.0) of the China global Merged Surface Temperature(CMST2.0) dataset, the global mean surface temperature(GMST) in the first half of 2023 reached its third warmest value since t...According to the latest version(version 2.0) of the China global Merged Surface Temperature(CMST2.0) dataset, the global mean surface temperature(GMST) in the first half of 2023 reached its third warmest value since the period of instrumental observation began, being only slightly lower than the values recorded in 2016 and 2020, and historically record-breaking GMST emerged from May to July 2023. Further analysis also indicates that if the surface temperature in the last five months of 2023 approaches the average level of the past five years, the annual average surface temperature anomaly in 2023 of approximately 1.26°C will break the previous highest surface temperature, which was recorded in 2016of approximately 1.25°C(both values relative to the global pre-industrialization period, i.e., the average value from 1850 to1900). With El Ni?o triggering a record-breaking hottest July, record-breaking average annual temperatures will most likely become a reality in 2023.展开更多
Leakages from subsea oil and gas equipment cause substantial economic losses and damage to marine ecosystem,so it is essential to locate the source of the leak.However,due to the complexity and variability of the mari...Leakages from subsea oil and gas equipment cause substantial economic losses and damage to marine ecosystem,so it is essential to locate the source of the leak.However,due to the complexity and variability of the marine environment,the signals collected by hydrophone contain a variety of noises,which makes it challenging to extract useful signals for localization.To solve this problem,a hydrophone denoising algorithm is proposed based on variational modal decomposition(VMD)with grey wolf optimization.First,the average envelope entropy is used as the fitness function of the grey wolf optimizer to find the optimal solution for the parameters K andα.Afterward,the VMD algorithm decomposes the original signal parameters to obtain the intrinsic mode functions(IMFs).Subsequently,the number of interrelationships between each IMF and the original signal was calculated,the threshold value was set,and the noise signal was removed to calculate the time difference using the valid signal obtained by reconstruction.Finally,the arrival time difference is used to locate the origin of the leak.The localization accuracy of the method in finding leaks is investigated experimentally by constructing a simulated leak test rig,and the effectiveness and feasibility of the method are verified.展开更多
In this paper,we investigate spacelike graphs defined over a domain Ω⊂M^(n) in the Lorentz manifold M^(n)×ℝ with the metric−ds^(2)+σ,where M^(n) is a complete Riemannian n-manifold with the metricσ,Ωhas piece...In this paper,we investigate spacelike graphs defined over a domain Ω⊂M^(n) in the Lorentz manifold M^(n)×ℝ with the metric−ds^(2)+σ,where M^(n) is a complete Riemannian n-manifold with the metricσ,Ωhas piecewise smooth boundary,and ℝ denotes the Euclidean 1-space.We prove an interesting stability result for translating spacelike graphs in M^(n)×ℝ under a conformal transformation.展开更多
The purpose of this research work is to investigate the numerical solutions of the fractional dengue transmission model(FDTM)in the presence of Wolbachia using the stochastic-based Levenberg-Marquardt neural network(L...The purpose of this research work is to investigate the numerical solutions of the fractional dengue transmission model(FDTM)in the presence of Wolbachia using the stochastic-based Levenberg-Marquardt neural network(LM-NN)technique.The fractional dengue transmission model(FDTM)consists of 12 compartments.The human population is divided into four compartments;susceptible humans(S_(h)),exposed humans(E_(h)),infectious humans(I_(h)),and recovered humans(R_(h)).Wolbachia-infected and Wolbachia-uninfected mosquito population is also divided into four compartments:aquatic(eggs,larvae,pupae),susceptible,exposed,and infectious.We investigated three different cases of vertical transmission probability(η),namely when Wolbachia-free mosquitoes persist only(η=0.6),when both types of mosquitoes persist(η=0.8),and when Wolbachia-carrying mosquitoes persist only(η=1).The objective of this study is to investigate the effectiveness of Wolbachia in reducing dengue and presenting the numerical results by using the stochastic structure LM-NN approach with 10 hidden layers of neurons for three different cases of the fractional order derivatives(α=0.4,0.6,0.8).LM-NN approach includes a training,validation,and testing procedure to minimize the mean square error(MSE)values using the reference dataset(obtained by solving the model using the Adams-Bashforth-Moulton method(ABM).The distribution of data is 80% data for training,10% for validation,and,10% for testing purpose)results.A comprehensive investigation is accessible to observe the competence,precision,capacity,and efficiency of the suggested LM-NN approach by executing the MSE,state transitions findings,and regression analysis.The effectiveness of the LM-NN approach for solving the FDTM is demonstrated by the overlap of the findings with trustworthy measures,which achieves a precision of up to 10^(-4).展开更多
Landmines continue to pose an ongoing threat in various regions around the world,with countless buried landmines affecting numerous human lives.The detonation of these landmines results in thousands of casualties repo...Landmines continue to pose an ongoing threat in various regions around the world,with countless buried landmines affecting numerous human lives.The detonation of these landmines results in thousands of casualties reported worldwide annually.Therefore,there is a pressing need to employ diverse landmine detection techniques for their removal.One effective approach for landmine detection is UAV(Unmanned Aerial Vehicle)based AirborneMagnetometry,which identifies magnetic anomalies in the local terrestrial magnetic field.It can generate a contour plot or heat map that visually represents the magnetic field strength.Despite the effectiveness of this approach,landmine removal remains a challenging and resource-intensive task,fraughtwith risks.Edge computing,on the other hand,can play a crucial role in critical drone monitoring applications like landmine detection.By processing data locally on a nearby edge server,edge computing can reduce communication latency and bandwidth requirements,allowing real-time analysis of magnetic field data.It enables faster decision-making and more efficient landmine detection,potentially saving lives and minimizing the risks involved in the process.Furthermore,edge computing can provide enhanced security and privacy by keeping sensitive data close to the source,reducing the chances of data exposure during transmission.This paper introduces the MAGnetometry Imaging based Classification System(MAGICS),a fully automated UAV-based system designed for landmine and buried object detection and localization.We have developed an efficient deep learning-based strategy for automatic image classification using magnetometry dataset traces.By simulating the proposal in various network scenarios,we have successfully detected landmine signatures present in themagnetometry images.The trained models exhibit significant performance improvements,achieving a maximum mean average precision value of 97.8%.展开更多
In this study,we aim to assess dynamical downscaling simulations by utilizing a novel bias-corrected global climate model(GCM)data to drive a regional climate model(RCM)over the Asia-western North Pacific region.Three...In this study,we aim to assess dynamical downscaling simulations by utilizing a novel bias-corrected global climate model(GCM)data to drive a regional climate model(RCM)over the Asia-western North Pacific region.Three simulations were conducted with a 25-km grid spacing for the period 1980–2014.The first simulation(WRF_ERA5)was driven by the European Centre for Medium-Range Weather Forecasts Reanalysis 5(ERA5)dataset and served as the validation dataset.The original GCM dataset(MPI-ESM1-2-HR model)was used to drive the second simulation(WRF_GCM),while the third simulation(WRF_GCMbc)was driven by the bias-corrected GCM dataset.The bias-corrected GCM data has an ERA5-based mean and interannual variance and long-term trends derived from the ensemble mean of 18 CMIP6 models.Results demonstrate that the WRF_GCMbc significantly reduced the root-mean-square errors(RMSEs)of the climatological mean of downscaled variables,including temperature,precipitation,snow,wind,relative humidity,and planetary boundary layer height by 50%–90%compared to the WRF_GCM.Similarly,the RMSEs of interannual-tointerdecadal variances of downscaled variables were reduced by 30%–60%.Furthermore,the WRF_GCMbc better captured the annual cycle of the monsoon circulation and intraseasonal and day-to-day variabilities.The leading empirical orthogonal function(EOF)shows a monopole precipitation mode in the WRF_GCM.In contrast,the WRF_GCMbc successfully reproduced the observed tri-pole mode of summer precipitation over eastern China.This improvement could be attributed to a better-simulated location of the western North Pacific subtropical high in the WRF_GCMbc after GCM bias correction.展开更多
文摘Lexical meaning mainly includes rational meaning,grammatical meaning,and coloring meaning.Mastering the coloring meaning of vocabulary is of great significance for foreign students to use Chinese vocabulary correctly.This study mainly examines the psychological mechanism of Chinese second language learners mastering the coloring meaning of words,examines the psychological characteristics of students mastering the color meaning of words from the perspectives of second language learning theory and cognitive theory,establishes a cognitive schema for coloring meaning learning,and proposes corresponding learning models and teaching strategies.
基金supported by the National Natural Science Foundation of China (Grant No. 61672124)the Password Theory Project of the 13th Five-Year Plan National Cryptography Development Fund (Grant No. MMJJ20170203)+3 种基金Liaoning Province Science and Technology Innovation Leading Talents Program Project (Grant No. XLYC1802013)Key R&D Projects of Liaoning Province (Grant No. 2019020105JH2/103)Jinan City ‘20 Universities’ Funding Projects Introducing Innovation Team Program (Grant No. 2019GXRC031)Research Fund of Guangxi Key Lab of Multi-source Information Mining & Security (Grant No. MIMS20-M-02)。
文摘A novel visually meaningful image encryption algorithm is proposed based on a hyperchaotic system and compressive sensing(CS), which aims to improve the visual security of steganographic image and decrypted quality. First, a dynamic spiral block scrambling is designed to encrypt the sparse matrix generated by performing discrete wavelet transform(DWT)on the plain image. Then, the encrypted image is compressed and quantified to obtain the noise-like cipher image. Then the cipher image is embedded into the alpha channel of the carrier image in portable network graphics(PNG) format to generate the visually meaningful steganographic image. In our scheme, the hyperchaotic Lorenz system controlled by the hash value of plain image is utilized to construct the scrambling matrix, the measurement matrix and the embedding matrix to achieve higher security. In addition, compared with other existing encryption algorithms, the proposed PNG-based embedding method can blindly extract the cipher image, thus effectively reducing the transmission cost and storage space. Finally, the experimental results indicate that the proposed encryption algorithm has very high visual security.
基金This research was funded by a research Grant 32171076 from National Social Sciences Foundation of China20BSH139 from National Social Sciences Foundation of China.
文摘This study aims to be the first to use meta-analysis to explore the relationship between meaning in life(MIL)and mental health issues among older adults.A meta-analysis was conducted using six databases,resulting in 16 studies with 5,074 participants in total.The“metacor”and“forestplot”packages in R-Studio were used for data analysis.The total effect was calculated using a random-effects model,with I2=86%in the heterogeneity test.The results showed a moderate negative correlation between MIL and mental health issues among older adults,with an average effect of−0.37.Five potential moderating variables were examined:the conceptualization of MIL(value vs.purpose),region(Asian vs.Western countries),residence status(community vs.nursing home vs.hospital),types of mental health issues,and evaluation methods(clinical vs.non-clinical).The first four had no significant moderating effect.The mean correlation coefficients between mental health issues and value/purpose were−0.49/−0.33;the mean correlation coefficients in Asian countries and Western countries were−0.48 and−0.34;the mean correlation coefficients among participants living in community/nursing home/mixed status were−0.33/−0.40/−0.40;the mean correlation coefficients between MIL and depression/others were−0.37/−0.35;however,the negative relationship between MIL and mental health issues was stronger when non-clinical evaluations(self-report only)were used.Specifically,the mean correlation coefficient for non-clinical evaluations was−0.42 and for clinical evaluations was−0.29.This study is the first meta-analysis to identify the negative correlation between older adults’MIL and mental health issues.Significant moderating effects of evaluation methods were found.
基金supported in part by the National Natural Science Foundation of China (No.61972103)the Natural Science Foundation of Guangdong Province of China (No.2019A1515011361)+2 种基金the Postgraduate Education Innovation Project of Guangdong Ocean University of China (No.202143)the Guangdong Postgraduate Education Innovation Project of China (No.2020JGXM059)the Key Scientific Research Project of Education Department of Guangdong Province of China (2020ZDZX3064).
文摘Traditional image encryption algorithms transform a plain image into a noise-like image.To lower the chances for the encrypted image being detected by the attacker during the image transmission,a visually meaningful image encryption scheme is suggested to hide the encrypted image using another carrier image.This paper proposes a visually meaningful encrypted image algorithm that hides a secret image and a digital signature which provides authenticity and confidentiality.The recovered digital signature is used for the purpose of identity authentication while the secret image is encrypted to protect its confidentiality.Least Significant Bit(LSB)method to embed signature on the encrypted image and Lifting Wavelet Transform(LWT)to generate a visually meaningful encrypted image are designed.The proposed algorithm has a keyspace of 139.5-bit,a Normalized Correlation(NC)value of 0.9998 which is closer to 1 and a Peak Signal to Noise Ratio(PSNR)with a value greater than 50 dB.Different analyses are also performed on the proposed algorithm using different images.The experimental results show that the proposed scheme is with high key sensitivity and strong robustness against pepper and salt attack and cropping attack.Moreover,the histogram analysis shows that the original carrier image and the final visual image are very similar.
文摘Araby is a short story by the famous Irish stream-of-consciousness writer James Joyce.Through a series of images,the novel expresses the theme of the story:the“mental paralysis”of Dubliners and the“spiritual Epiphany”of the little boy,which reflects the spiritual barren of Dubliners at that time.Through the analysis of the symbolic meaning of many images in the work,this paper reveals the social background and religious significance hidden behind the images.
文摘Cultural-loaded word is one of the most popular topics in translation studies.The theory of spirit transmission and meaning conveyance provides a new way for the translation of cultural-loaded word.Based on the A Happy Excursion,this paper makes a comparative analysis of the translation strategies of seven English versions.This study will reveal the similarities and differences between Chinese and foreign translators’translation strategies.
基金Under the major project of the Center for Language Education and Cooperation in 2021“Research on the Construction and Promotion of International Chinese Education Standard System”(21YH04A).
文摘The research examines President Xi’s 2021 New Year speech with research questions centering around its abundant interpersonal meanings.Through qualitative content analysis,the research finds that it is typical for Chinese president to frequently use judgment and appreciation resources in reviewing the past year.Even in the face of the pandemic and natural disasters,the overall emotions of the speech remain positive,which corresponds to the forward-looking feature of New Year speech.Significance of the study abounds and future research can investigate how COVID-19 impacts the ideologies conveyed through political leaders’speeches through a comparative lens and how to produce more understandings that can help dismantle stereotypes and discrimination hidden in reports about COVID-19 by using Appraisal Theory critically,systematically,and comprehensively.
文摘工业数据由于技术故障和人为因素通常导致数据异常,现有基于约束的方法因约束阈值设置的过于宽松或严格会导致修复错误,基于统计的方法因平滑修复机制导致对时间步长较远的异常值修复准确度较低.针对上述问题,提出了基于奖励机制的最小迭代修复和改进WGAN混合模型的时序数据修复方法.首先,在预处理阶段,保留异常数据,进行信息标注等处理,从而充分挖掘异常值与真实值之间的特征约束.其次,在噪声模块提出了近邻参数裁剪规则,用于修正最小迭代修复公式生成的噪声向量.将其传递至模拟分布模块的生成器中,同时设计了一个动态时间注意力网络层,用于提取时序特征权重并与门控循环单元串联组合捕捉不同步长的特征依赖,并引入递归多步预测原理共同提升模型的表达能力;在判别器中设计了Abnormal and Truth奖励机制和Weighted Mean Square Error损失函数共同反向优化生成器修复数据的细节和质量.最后,在公开数据集和真实数据集上的实验结果表明,该方法的修复准确度与模型稳定性显著优于现有方法.
基金supported by the Key Research Program of Frontier Sciences,Chinese Academy of Sciences(Grant No.ZDBS-LY-DQC010)the National Natural Science Foundation of China(Grant No.42175045).
文摘In 2023,the majority of the Earth witnessed its warmest boreal summer and autumn since 1850.Whether 2023 will indeed turn out to be the warmest year on record and what caused the astonishingly large margin of warming has become one of the hottest topics in the scientific community and is closely connected to the future development of human society.We analyzed the monthly varying global mean surface temperature(GMST)in 2023 and found that the globe,the land,and the oceans in 2023 all exhibit extraordinary warming,which is distinct from any previous year in recorded history.Based on the GMST statistical ensemble prediction model developed at the Institute of Atmospheric Physics,the GMST in 2023 is predicted to be 1.41℃±0.07℃,which will certainly surpass that in 2016 as the warmest year since 1850,and is approaching the 1.5℃ global warming threshold.Compared to 2022,the GMST in 2023 will increase by 0.24℃,with 88%of the increment contributed by the annual variability as mostly affected by El Niño.Moreover,the multidecadal variability related to the Atlantic Multidecadal Oscillation(AMO)in 2023 also provided an important warming background for sparking the GMST rise.As a result,the GMST in 2023 is projected to be 1.15℃±0.07℃,with only a 0.02℃ increment,if the effects of natural variability—including El Niño and the AMO—are eliminated and only the global warming trend is considered.
基金support from the National Natural Science Foundation of China (Grant Nos. 41975105 and 42375022)。
文摘According to the latest version(version 2.0) of the China global Merged Surface Temperature(CMST2.0) dataset, the global mean surface temperature(GMST) in the first half of 2023 reached its third warmest value since the period of instrumental observation began, being only slightly lower than the values recorded in 2016 and 2020, and historically record-breaking GMST emerged from May to July 2023. Further analysis also indicates that if the surface temperature in the last five months of 2023 approaches the average level of the past five years, the annual average surface temperature anomaly in 2023 of approximately 1.26°C will break the previous highest surface temperature, which was recorded in 2016of approximately 1.25°C(both values relative to the global pre-industrialization period, i.e., the average value from 1850 to1900). With El Ni?o triggering a record-breaking hottest July, record-breaking average annual temperatures will most likely become a reality in 2023.
基金financially supported by the National Key Research and Development Program of China(Grant No.2022YFC2806102)the National Natural Science Foundation of China(Grant Nos.52171287,52325107)+2 种基金High Tech Ship Research Project of Ministry of Industry and Information Technology(Grant Nos.2023GXB01-05-004-03,GXBZH2022-293)the Science Foundation for Distinguished Young Scholars of Shandong Province(Grant No.ZR2022JQ25)the Taishan Scholars Project(Grant No.tsqn201909063)。
文摘Leakages from subsea oil and gas equipment cause substantial economic losses and damage to marine ecosystem,so it is essential to locate the source of the leak.However,due to the complexity and variability of the marine environment,the signals collected by hydrophone contain a variety of noises,which makes it challenging to extract useful signals for localization.To solve this problem,a hydrophone denoising algorithm is proposed based on variational modal decomposition(VMD)with grey wolf optimization.First,the average envelope entropy is used as the fitness function of the grey wolf optimizer to find the optimal solution for the parameters K andα.Afterward,the VMD algorithm decomposes the original signal parameters to obtain the intrinsic mode functions(IMFs).Subsequently,the number of interrelationships between each IMF and the original signal was calculated,the threshold value was set,and the noise signal was removed to calculate the time difference using the valid signal obtained by reconstruction.Finally,the arrival time difference is used to locate the origin of the leak.The localization accuracy of the method in finding leaks is investigated experimentally by constructing a simulated leak test rig,and the effectiveness and feasibility of the method are verified.
基金supported in part by the NSFC(11801496,11926352)the Fok Ying-Tung Education Foundation(China)the Hubei Key Laboratory of Applied Mathematics(Hubei University).
文摘In this paper,we investigate spacelike graphs defined over a domain Ω⊂M^(n) in the Lorentz manifold M^(n)×ℝ with the metric−ds^(2)+σ,where M^(n) is a complete Riemannian n-manifold with the metricσ,Ωhas piecewise smooth boundary,and ℝ denotes the Euclidean 1-space.We prove an interesting stability result for translating spacelike graphs in M^(n)×ℝ under a conformal transformation.
文摘The purpose of this research work is to investigate the numerical solutions of the fractional dengue transmission model(FDTM)in the presence of Wolbachia using the stochastic-based Levenberg-Marquardt neural network(LM-NN)technique.The fractional dengue transmission model(FDTM)consists of 12 compartments.The human population is divided into four compartments;susceptible humans(S_(h)),exposed humans(E_(h)),infectious humans(I_(h)),and recovered humans(R_(h)).Wolbachia-infected and Wolbachia-uninfected mosquito population is also divided into four compartments:aquatic(eggs,larvae,pupae),susceptible,exposed,and infectious.We investigated three different cases of vertical transmission probability(η),namely when Wolbachia-free mosquitoes persist only(η=0.6),when both types of mosquitoes persist(η=0.8),and when Wolbachia-carrying mosquitoes persist only(η=1).The objective of this study is to investigate the effectiveness of Wolbachia in reducing dengue and presenting the numerical results by using the stochastic structure LM-NN approach with 10 hidden layers of neurons for three different cases of the fractional order derivatives(α=0.4,0.6,0.8).LM-NN approach includes a training,validation,and testing procedure to minimize the mean square error(MSE)values using the reference dataset(obtained by solving the model using the Adams-Bashforth-Moulton method(ABM).The distribution of data is 80% data for training,10% for validation,and,10% for testing purpose)results.A comprehensive investigation is accessible to observe the competence,precision,capacity,and efficiency of the suggested LM-NN approach by executing the MSE,state transitions findings,and regression analysis.The effectiveness of the LM-NN approach for solving the FDTM is demonstrated by the overlap of the findings with trustworthy measures,which achieves a precision of up to 10^(-4).
基金funded by Institutional Fund Projects under Grant No(IFPNC-001-611-2020).
文摘Landmines continue to pose an ongoing threat in various regions around the world,with countless buried landmines affecting numerous human lives.The detonation of these landmines results in thousands of casualties reported worldwide annually.Therefore,there is a pressing need to employ diverse landmine detection techniques for their removal.One effective approach for landmine detection is UAV(Unmanned Aerial Vehicle)based AirborneMagnetometry,which identifies magnetic anomalies in the local terrestrial magnetic field.It can generate a contour plot or heat map that visually represents the magnetic field strength.Despite the effectiveness of this approach,landmine removal remains a challenging and resource-intensive task,fraughtwith risks.Edge computing,on the other hand,can play a crucial role in critical drone monitoring applications like landmine detection.By processing data locally on a nearby edge server,edge computing can reduce communication latency and bandwidth requirements,allowing real-time analysis of magnetic field data.It enables faster decision-making and more efficient landmine detection,potentially saving lives and minimizing the risks involved in the process.Furthermore,edge computing can provide enhanced security and privacy by keeping sensitive data close to the source,reducing the chances of data exposure during transmission.This paper introduces the MAGnetometry Imaging based Classification System(MAGICS),a fully automated UAV-based system designed for landmine and buried object detection and localization.We have developed an efficient deep learning-based strategy for automatic image classification using magnetometry dataset traces.By simulating the proposal in various network scenarios,we have successfully detected landmine signatures present in themagnetometry images.The trained models exhibit significant performance improvements,achieving a maximum mean average precision value of 97.8%.
基金supported jointly by the National Natural Science Foundation of China (Grant No.42075170)the National Key Research and Development Program of China (2022YFF0802503)+2 种基金the Jiangsu Collaborative Innovation Center for Climate Changea Chinese University Direct Grant(Grant No. 4053331)supported by the National Key Scientific and Technological Infrastructure project“Earth System Numerical Simulator Facility”(EarthLab)
文摘In this study,we aim to assess dynamical downscaling simulations by utilizing a novel bias-corrected global climate model(GCM)data to drive a regional climate model(RCM)over the Asia-western North Pacific region.Three simulations were conducted with a 25-km grid spacing for the period 1980–2014.The first simulation(WRF_ERA5)was driven by the European Centre for Medium-Range Weather Forecasts Reanalysis 5(ERA5)dataset and served as the validation dataset.The original GCM dataset(MPI-ESM1-2-HR model)was used to drive the second simulation(WRF_GCM),while the third simulation(WRF_GCMbc)was driven by the bias-corrected GCM dataset.The bias-corrected GCM data has an ERA5-based mean and interannual variance and long-term trends derived from the ensemble mean of 18 CMIP6 models.Results demonstrate that the WRF_GCMbc significantly reduced the root-mean-square errors(RMSEs)of the climatological mean of downscaled variables,including temperature,precipitation,snow,wind,relative humidity,and planetary boundary layer height by 50%–90%compared to the WRF_GCM.Similarly,the RMSEs of interannual-tointerdecadal variances of downscaled variables were reduced by 30%–60%.Furthermore,the WRF_GCMbc better captured the annual cycle of the monsoon circulation and intraseasonal and day-to-day variabilities.The leading empirical orthogonal function(EOF)shows a monopole precipitation mode in the WRF_GCM.In contrast,the WRF_GCMbc successfully reproduced the observed tri-pole mode of summer precipitation over eastern China.This improvement could be attributed to a better-simulated location of the western North Pacific subtropical high in the WRF_GCMbc after GCM bias correction.