Plant biomass is an important agronomic trait that has been subjected to intense human selection for yield improvement.The underlying mechanism regulating biomass formation is currently gaining increasing attention,bu...Plant biomass is an important agronomic trait that has been subjected to intense human selection for yield improvement.The underlying mechanism regulating biomass formation is currently gaining increasing attention,but it remains unexplored.In this study,we isolated a cucumber(Cucumis sativus L.)minicuke mutant with remarkably reduced biomass.The causative gene was identified as CsNMT1,a homologue of the Arabidopsis thaliana N-myristoyltransferase1.Our clustered regularly interspaced shot palindromic repeat-based genome editing confirmed the key role of CsNMT1 in biomass regulation.Multi-omics analyses integrating metabolomic and transcriptomic analyses revealed the suppression of a very early step of lignin biosynthesis and the corresponding down-regulation of genes involved in lignin biosynthesis in the minicikue mutant,suggesting an unexpected pathway for regulating biomass accumulation through lignin sink strength.Our findings demonstrate the function of NMT1 in regulating plant biomass and its potential application value for biomass improvement in cucurbits.展开更多
Neural machine translation(NMT)has advanced with deep learning and large-scale multilingual models,yet translating lowresource languages often lacks sufficient training data and leads to hallucinations.This often resu...Neural machine translation(NMT)has advanced with deep learning and large-scale multilingual models,yet translating lowresource languages often lacks sufficient training data and leads to hallucinations.This often results in translated content that diverges significantly from the source text.This research proposes a refined Contrastive Decoding(CD)algorithm that dynamically adjusts weights of log probabilities from strong expert and weak amateur models to mitigate hallucinations in lowresource NMT and improve translation quality.Advanced large language NMT models,including ChatGLM and LLaMA,are fine-tuned and implemented for their superior contextual understanding and cross-lingual capabilities.The refined CD algorithm evaluates multiple candidate translations using BLEU score,semantic similarity,and Named Entity Recognition accuracy.Extensive experimental results show substantial improvements in translation quality and a significant reduction in hallucination rates.Fine-tuned models achieve higher evaluation metrics compared to baseline models and state-of-the-art models.An ablation study confirms the contributions of each methodological component and highlights the effectiveness of the refined CD algorithm and advanced models in mitigating hallucinations.Notably,the refined methodology increased the BLEU score by approximately 30%compared to baseline models.展开更多
This study aims to explore the potential and limitations of ChatGPT in translation,focusing on its application in Neural Machine Translation(NMT).By combining theoretical analysis with empirical research,the study eva...This study aims to explore the potential and limitations of ChatGPT in translation,focusing on its application in Neural Machine Translation(NMT).By combining theoretical analysis with empirical research,the study evaluates ChatGPT’s strengths and weaknesses.It reveals ChatGPT’s superior performance in handling technical documents with high translation quality and efficiency.However,its limitations become evident in addressing cultural nuances and emotional expressions,where semantic deviation or cultural loss often occurs.Moreover,ChatGPT struggles with creative translation,failing to convey the artistic style and emotional depth of original texts,such as literary works and advertisements.The study proposes optimized paths for human-machine collaboration,emphasizing the crucial role of human translators in cultural adaptation and quality assurance.It suggests incorporating multimodal data,dynamic feedback mechanisms,and pragmatic reasoning techniques to enhance machine translation capabilities.The findings conclude that while ChatGPT serves as an efficient translation tool,complex tasks require human-machine synergy to achieve high-quality cross-cultural communication.展开更多
In view of the problem that the packet information preempted netw ork resources in the process of transmission in the CAN bus,w hich leads to the low utilization of netw ork resources and the low accuracy of informati...In view of the problem that the packet information preempted netw ork resources in the process of transmission in the CAN bus,w hich leads to the low utilization of netw ork resources and the low accuracy of information transmission. Thus,a hybrid scheduling algorithm NM TS based on CAN bus is proposed,in the NM TS hybrid scheduling algorithm,the dynamic scheduling algorithm EDF is used to schedule hard real-time messages to solve the problem of low utilization of netw ork resources; the static scheduling algorithm RM S is used to schedule soft real-time messages and non real-time messages,so as to solve the problem of low accuracy of information transmission. By using M ATLAB softw are,the CAN netw ork model can be built,the EDF algorithm,RM S algorithm and NM TS algorithm are simulated. The experimental results show that the netw ork resources utilization is 90%,the packet loss rate is 0% of the NM TS algorithm. Therefore,The hybrid scheduling algorithm based on CAN bus NM TS has the characteristics of high netw ork resource utilization and high accuracy of information transmission,w hich w ill be very helpful for further research of CAN bus.展开更多
基金supported by the National Natural Science Foundation of China(32172606 to Dr.Xueyong Yang and 32302543 to Dr.Shuai Wang)the National Key Research and Development Program of China(2021YFF1000100)+1 种基金the Beijing Joint Research Program for Germplasm Innovation and New Variety Breeding(G2022062800303)the Science and Technology Innovation Program of the Chinese Academy of Agricultural Sciences(CAASASTIP)。
文摘Plant biomass is an important agronomic trait that has been subjected to intense human selection for yield improvement.The underlying mechanism regulating biomass formation is currently gaining increasing attention,but it remains unexplored.In this study,we isolated a cucumber(Cucumis sativus L.)minicuke mutant with remarkably reduced biomass.The causative gene was identified as CsNMT1,a homologue of the Arabidopsis thaliana N-myristoyltransferase1.Our clustered regularly interspaced shot palindromic repeat-based genome editing confirmed the key role of CsNMT1 in biomass regulation.Multi-omics analyses integrating metabolomic and transcriptomic analyses revealed the suppression of a very early step of lignin biosynthesis and the corresponding down-regulation of genes involved in lignin biosynthesis in the minicikue mutant,suggesting an unexpected pathway for regulating biomass accumulation through lignin sink strength.Our findings demonstrate the function of NMT1 in regulating plant biomass and its potential application value for biomass improvement in cucurbits.
基金M.Faheem is supported by VTT Technical Research Center of Finland.
文摘Neural machine translation(NMT)has advanced with deep learning and large-scale multilingual models,yet translating lowresource languages often lacks sufficient training data and leads to hallucinations.This often results in translated content that diverges significantly from the source text.This research proposes a refined Contrastive Decoding(CD)algorithm that dynamically adjusts weights of log probabilities from strong expert and weak amateur models to mitigate hallucinations in lowresource NMT and improve translation quality.Advanced large language NMT models,including ChatGLM and LLaMA,are fine-tuned and implemented for their superior contextual understanding and cross-lingual capabilities.The refined CD algorithm evaluates multiple candidate translations using BLEU score,semantic similarity,and Named Entity Recognition accuracy.Extensive experimental results show substantial improvements in translation quality and a significant reduction in hallucination rates.Fine-tuned models achieve higher evaluation metrics compared to baseline models and state-of-the-art models.An ablation study confirms the contributions of each methodological component and highlights the effectiveness of the refined CD algorithm and advanced models in mitigating hallucinations.Notably,the refined methodology increased the BLEU score by approximately 30%compared to baseline models.
文摘This study aims to explore the potential and limitations of ChatGPT in translation,focusing on its application in Neural Machine Translation(NMT).By combining theoretical analysis with empirical research,the study evaluates ChatGPT’s strengths and weaknesses.It reveals ChatGPT’s superior performance in handling technical documents with high translation quality and efficiency.However,its limitations become evident in addressing cultural nuances and emotional expressions,where semantic deviation or cultural loss often occurs.Moreover,ChatGPT struggles with creative translation,failing to convey the artistic style and emotional depth of original texts,such as literary works and advertisements.The study proposes optimized paths for human-machine collaboration,emphasizing the crucial role of human translators in cultural adaptation and quality assurance.It suggests incorporating multimodal data,dynamic feedback mechanisms,and pragmatic reasoning techniques to enhance machine translation capabilities.The findings conclude that while ChatGPT serves as an efficient translation tool,complex tasks require human-machine synergy to achieve high-quality cross-cultural communication.
文摘In view of the problem that the packet information preempted netw ork resources in the process of transmission in the CAN bus,w hich leads to the low utilization of netw ork resources and the low accuracy of information transmission. Thus,a hybrid scheduling algorithm NM TS based on CAN bus is proposed,in the NM TS hybrid scheduling algorithm,the dynamic scheduling algorithm EDF is used to schedule hard real-time messages to solve the problem of low utilization of netw ork resources; the static scheduling algorithm RM S is used to schedule soft real-time messages and non real-time messages,so as to solve the problem of low accuracy of information transmission. By using M ATLAB softw are,the CAN netw ork model can be built,the EDF algorithm,RM S algorithm and NM TS algorithm are simulated. The experimental results show that the netw ork resources utilization is 90%,the packet loss rate is 0% of the NM TS algorithm. Therefore,The hybrid scheduling algorithm based on CAN bus NM TS has the characteristics of high netw ork resource utilization and high accuracy of information transmission,w hich w ill be very helpful for further research of CAN bus.
