α-Trifluoromethyl ketones are a class of useful compounds with versatile applications.Their synthetic application via the transformation of the C—F bonds is of particular interest by allowing the synthesis of organi...α-Trifluoromethyl ketones are a class of useful compounds with versatile applications.Their synthetic application via the transformation of the C—F bonds is of particular interest by allowing the synthesis of organic compounds with diverse structures.Herein,the advances in the research areas ofα-trifluoromethyl ketone synthesis and their defluorination reactions are reviewed.Discussion on the mechanisms of the typical reactions has also been provided,in hope of affording some guides to the chemistry ofα-trifluoromethyl ketones in the synthetic methods toward themselves and their derivatives.展开更多
With the increasing complexity of the current electromagnetic environment,excessive microwave radi-ation not only does harm to human health but also forms various electromagnetic interference to so-phisticated electro...With the increasing complexity of the current electromagnetic environment,excessive microwave radi-ation not only does harm to human health but also forms various electromagnetic interference to so-phisticated electronic instruments.Therefore,the design and preparation of electromagnetic absorbing composites represent an efficient approach to mitigate the current hazards of electromagnetic radiation.However,traditional electromagnetic absorbers are difficult to satisfy the demands of actual utilization in the face of new challenges,and emerging absorbents have garnered increasing attention due to their structure and performance-based advantages.In this review,several emerging composites of Mxene-based,biochar-based,chiral,and heat-resisting are discussed in detail,including their synthetic strategy,structural superiority and regulation method,and final optimization of electromagnetic absorption ca-pacity.These insights provide a comprehensive reference for the future development of new-generation electromagnetic-wave absorption composites.Moreover,the potential development directions of these emerging absorbers have been proposed as well.展开更多
This study examines the evolving use of synthetic chemicals in intensive agriculture over the past decade.It highlights the negative impacts of chemical inputs on soil health and ecosystem integrity and recommends kno...This study examines the evolving use of synthetic chemicals in intensive agriculture over the past decade.It highlights the negative impacts of chemical inputs on soil health and ecosystem integrity and recommends knowledge-sharing platforms,soil protection laws,and collaborative efforts between regulatory agencies and agricultural experts.The study emphasizes the need for a balanced approach that includes natural methods alongside synthetic chemicals,particularly herbicides.Ten years ago,farmers primarily used urea,DAP,and potassium for nutrients.However,increased awareness,market forces,and government subsidies have led to a significant rise in herbicide use as a cost-effective weed management strategy.Over the past decade,synthetic fertilizer use for cotton cultivation has increased by 80%,leading to deteriorating soil quality.Paddy cultivation has decreased by 23%,while cotton cultivation has increased by 20.4%due to higher economic incentives.Currently,89.1%of farmers use herbicides,compared to 97.2%who did not a decade ago.Insecticide use has also surged,with 97.8%of farmers applying 1.5 liters or more per acre.The excessive use of chemicals threatens soil fertility and disrupts the ecosystem’s balance.This article explores the reasons behind the adoption of chemical-intensive farming practices and offers insights into farmers’decision-making processes.The careful use of synthetic chemicals is essential to safeguard soil health and maintain ecological balance.展开更多
Epigenetics-mediated breeding(epibreeding)involves engineering crop traits and stress responses through the targeted manipulation of key epigenetic features to enhance agricultural productivity.While conventional bree...Epigenetics-mediated breeding(epibreeding)involves engineering crop traits and stress responses through the targeted manipulation of key epigenetic features to enhance agricultural productivity.While conventional breeding methods raise concerns about reduced genetic diversity,epibreeding propels crop improvement through epigenetic variations that regulate gene expression,ultimately impacting crop yield.Epigenetic regulation in crops encompasses various modes,including histone modification,DNA modification,RNA modification,non-coding RNA,and chromatin remodeling.This review summarizes the epigenetic mechanisms underlying major agronomic traits in maize and identifies candidate epigenetic landmarks in the maize breeding process.We propose a valuable strategy for improving maize yield through epibreeding,combining CRISPR/Cas-based epigenome editing technology and Synthetic Epigenetics(SynEpi).Finally,we discuss the challenges and opportunities associated with maize trait improvement through epibreeding.展开更多
Plant synthetic biology has emerged as a transformative field in agriculture,offering innovative solutions to enhance food security,provide resilience to climate change,and transition to sustainable farming practices....Plant synthetic biology has emerged as a transformative field in agriculture,offering innovative solutions to enhance food security,provide resilience to climate change,and transition to sustainable farming practices.By integrating advanced genetic tools,computational modeling,and systems biology,researchers can precisely modify plant genomes to enhance traits such as yield,stress tolerance,and nutrient use efficiency.The ability to design plants with specific characteristics tailored to diverse environmental conditions and agricultural needs holds great potential to address global food security challenges.Here,we highlight recent advancements and applications of plant synthetic biology in agriculture,focusing on key areas such as photosynthetic efficiency,nitrogen fixation,drought tolerance,pathogen resistance,nutrient use efficiency,biofortification,climate resilience,microbiology engineering,synthetic plant genomes,and the integration of artificial intelligence with synthetic biology.These innovations aim to maximize resource use efficiency,reduce reliance on external inputs,and mitigate environmental impacts associated with conventional agricultural practices.Despite challenges related to regulatory approval and public acceptance,the integration of synthetic biology in agriculture holds immense promise for creating more resilient and sustainable agricultural systems,contributing to global food security and environmental sustainability.Rigorous multi-field testing of these approaches will undoubtedly be required to ensure reproducibility.展开更多
Active landslides pose a significant threat globally,endangering lives and property.Effective monitoring and forecasting of displacements are essential for the timely warnings and mitigation of these events.Interferom...Active landslides pose a significant threat globally,endangering lives and property.Effective monitoring and forecasting of displacements are essential for the timely warnings and mitigation of these events.Interferometric synthetic aperture radar(InSAR)stands out as an efficient and prevalent tool for monitoring landslide deformation and offers new prospects for displacement prediction.However,challenges such as inherent limitation of satellite viewing geometry,long revisit cycles,and limited data volume hinder its application in displacement forecasting,notably for landslides with near-north-south deformation less detectable by InSAR.To address these issues,we propose a novel strategy for predicting three-dimensional(3D)landslide displacement,integrating InSAR and global navigation satellite system(GNSS)measurements with machine learning(ML).This framework first synergizes InSAR line-of-sight(LOS)results with GNSS horizontal data to reconstruct 3D displacement time series.It then employs ML models to capture complex nonlinear relationships between external triggers,landslide evolutionary states,and 3D displacements,thus enabling accurate future deformation predictions.Utilizing four advanced ML algorithms,i.e.random forest(RF),support vector machine(SVM),long short-term memory(LSTM),and gated recurrent unit(GRU),with Bayesian optimization(BO)for hyperparameter tuning,we applied this innovative approach to the north-facing,slow-moving Xinpu landslide in the Three Gorges Reservoir Area(TGRA)of China.Leveraging over 6.5 years of Sentinel-1 satellite data and GNSS measurements,our framework demonstrates satisfactory and robust prediction performance,with an average root mean square deviation(RMSD)of 9.62 mm and a correlation coefficient(CC)of 0.996.This study presents a promising strategy for 3D displacement prediction,illustrating the efficacy of integrating InSAR monitoring with ML forecasting in enhancing landslide early warning capabilities.展开更多
In recent years,with the development of synthetic aperture radar(SAR)technology and the widespread application of deep learning,lightweight detection of SAR images has emerged as a research direction.The ultimate goal...In recent years,with the development of synthetic aperture radar(SAR)technology and the widespread application of deep learning,lightweight detection of SAR images has emerged as a research direction.The ultimate goal is to reduce computational and storage requirements while ensuring detection accuracy and reliability,making it an ideal choice for achieving rapid response and efficient processing.In this regard,a lightweight SAR ship target detection algorithm based on YOLOv8 was proposed in this study.Firstly,the C2f-Sc module was designed by fusing the C2f in the backbone network with the ScConv to reduce spatial redundancy and channel redundancy between features in convolutional neural networks.At the same time,the Ghost module was introduced into the neck network to effectively reduce model parameters and computational complexity.A relatively lightweight EMA attention mechanism was added to the neck network to promote the effective fusion of features at different levels.Experimental results showed that the Parameters and GFLOPs of the improved model are reduced by 8.5%and 7.0%when mAP@0.5 and mAP@0.5:0.95 are increased by 0.7%and 1.8%,respectively.It makes the model lightweight and improves the detection accuracy,which has certain application value.展开更多
The use of synthetic biology technology to develop cosmetic ingredients is attracting widespread attention due to its effectiveness,safety,and environmental friendliness.This article explains the concept of synthetic ...The use of synthetic biology technology to develop cosmetic ingredients is attracting widespread attention due to its effectiveness,safety,and environmental friendliness.This article explains the concept of synthetic biology and its key technologies and current status in the production of cosmetic ingredients.It also briefly analyzes the regulatory approaches to synthetic biology-based cosmetic ingredients in different countries and regions,providing guidance for the management of this field in China.The goal is to ensure product safety,enhance consumer trust,and promote the healthy development of the industry.展开更多
There is a growing body of clinical research on the utility of synthetic data derivatives,an emerging research tool in medicine.In nephrology,clinicians can use machine learning and artificial intelligence as powerful...There is a growing body of clinical research on the utility of synthetic data derivatives,an emerging research tool in medicine.In nephrology,clinicians can use machine learning and artificial intelligence as powerful aids in their clinical decision-making while also preserving patient privacy.This is especially important given the epidemiology of chronic kidney disease,renal oncology,and hypertension worldwide.However,there remains a need to create a framework for guidance regarding how to better utilize synthetic data as a practical application in this research.展开更多
Aiming at the dynamic stall problem that restricts the improvement of aircraft maneuverability,a new dynamic stall control method based on leading-edge Dual Synthetic Jets(DSJ)is proposed in this paper.The aerodynamic...Aiming at the dynamic stall problem that restricts the improvement of aircraft maneuverability,a new dynamic stall control method based on leading-edge Dual Synthetic Jets(DSJ)is proposed in this paper.The aerodynamic control characteristics and flow field evolution process of steady jet,Synthetic Jet(SJ)and DSJ in dynamic stall flow field are analyzed in detail,and the corresponding control mechanism is revealed.The strong"wall attachment effect"and quasisteady"characteristics of DSJ are found.The results show that the leading-edge jet technology can improve the dynamic stall flow field environment.For the whole pitching process,the average lift coefficients of steady jet,SJ and DSJ increased by 3.65%,10.51%and 14.62%respectively,and the average drag coefficients decreased by 9.58%,29.9%and 32.0%respectively.In the downward phase,the average lift coefficient increased by 16.31%,26.72%and 35.88%respectively,and the average drag coefficient decreased by 26.21%,50.46%and 54.28%respectively.Due to its strong"wall attachment effect"and"quasi-steady"characteristics,DSJ exhibits optimal control effect,showing its application potential in dynamic stall control.展开更多
The central Chinese province emerges as a key player in China-African trade and investment cooperation The fourth China-Africa Economic and Trade Expo(CAETE)was a prime opportunity for Citygreen Sports,a Chinese suppl...The central Chinese province emerges as a key player in China-African trade and investment cooperation The fourth China-Africa Economic and Trade Expo(CAETE)was a prime opportunity for Citygreen Sports,a Chinese supplier of synthetic turf,to boost its visibility.“Africa is one of our main markets.The expo allows us to showcase our products to African customers and engage directly with government representatives to discuss potential projects,”Wu Huan,regional director for international affairs at the group,told ChinAfrica.Based in Shishou,Hubei Province,the company notably supplied the synthetic turf for Ethiopia’s national stadium,the country’s only FIFA-certified field.展开更多
Imbalanced multiclass datasets pose challenges for machine learning algorithms.They often contain minority classes that are important for accurate predictions.However,when the data is sparsely distributed and overlaps...Imbalanced multiclass datasets pose challenges for machine learning algorithms.They often contain minority classes that are important for accurate predictions.However,when the data is sparsely distributed and overlaps with data points fromother classes,it introduces noise.As a result,existing resamplingmethods may fail to preserve the original data patterns,further disrupting data quality and reducingmodel performance.This paper introduces Neighbor Displacement-based Enhanced Synthetic Oversampling(NDESO),a hybridmethod that integrates a data displacement strategy with a resampling technique to achieve data balance.It begins by computing the average distance of noisy data points to their neighbors and adjusting their positions toward the center before applying random oversampling.Extensive evaluations compare 14 alternatives on nine classifiers across synthetic and 20 real-world datasetswith varying imbalance ratios.This evaluation was structured into two distinct test groups.First,the effects of k-neighbor variations and distance metrics are evaluated,followed by a comparison of resampled data distributions against alternatives,and finally,determining the most suitable oversampling technique for data balancing.Second,the overall performance of the NDESO algorithm was assessed,focusing on G-mean and statistical significance.The results demonstrate that our method is robust to a wide range of variations in these parameters and the overall performance achieves an average G-mean score of 0.90,which is among the highest.Additionally,it attains the lowest mean rank of 2.88,indicating statistically significant improvements over existing approaches.This advantage underscores its potential for effectively handling data imbalance in practical scenarios.展开更多
3-Deoxy-D-manno–oct-2-ulosonic acid(Kdo)is widely distributed in bacteria,and the synthesis of Kdocontaining oligosaccharides is important for the development of novel antibiotics and immunological agents.We have rec...3-Deoxy-D-manno–oct-2-ulosonic acid(Kdo)is widely distributed in bacteria,and the synthesis of Kdocontaining oligosaccharides is important for the development of novel antibiotics and immunological agents.We have recently developed a strategy to achieveα-stereocontrolled glycosylation using a C3-p-tolylthio-substituted Kdo phosphite donor.The wide substrate scope and high reactivity of the donors enabled the efficient synthesis of a series of Kdo-containing glycosides with completeα-stereoselectivity and without the formation of 2,3-ene byproducts.In this study,we improved the method by replacing the leaving group diethyl phosphite with fluoride,which enhanced the stability of the donor and led to cleaner reaction.Furthermore,the substrate range was expanded by synthesizing a series of Kdo O/C/S/Nglycosides,which also opened up a new avenue for the synthesis of CMP-Kdo synthase inhibitors.展开更多
MAX series materials,as non-van der Waals layered multi-element compounds,contribute remarkable regulated properties and functional dimension,combining the features of metal and ceramic materials due to their inherent...MAX series materials,as non-van der Waals layered multi-element compounds,contribute remarkable regulated properties and functional dimension,combining the features of metal and ceramic materials due to their inherently laminated crystal structure that Mn+1Xn slabs are intercalated with A element layers.Oriented to the functional requirements of information,intelligence,electrification,and aerospace in the new era,how to accelerate MAX series materials into new quality productive forces?The systematic enhancement of knowledge about MAX series materials is intrinsic to understanding its low-dimensional geometric structure characteristics,and physical and chemical properties,revealing the correlation of composition,structure,and function and further realizing rational design based on simulation and prediction.Diversity also brings complexity to MAX materials research.This review provides substantial tabular information on(Ⅰ)MAX’s research timeline from 1960 to the present,(Ⅱ)structure diversity and classification convention,(Ⅲ)synthesis route exploration,(Ⅳ)prediction based on theory and machine learning,(Ⅴ)properties,and(Ⅵ)functional applications.Herein,the researchers can quickly locate research content and recognize connections and differences of MAX series materials.In addition,the research challenges for the future development of MAX series materials are highlighted.展开更多
Plant cell wall(CW)-like soft materials,referred to as artificial CWs,are composites of assembled polymers containing micro-/nanoparticles or fibers/fibrils that are designed to mimic the composition,structure,and mec...Plant cell wall(CW)-like soft materials,referred to as artificial CWs,are composites of assembled polymers containing micro-/nanoparticles or fibers/fibrils that are designed to mimic the composition,structure,and mechanics of plant CWs.CW-like materials have recently emerged to test hypotheses pertaining to the intricate structure–property relationships of native plant CWs or to fabricate functional materials.Here,research on plant CWs and CW-like materials is reviewed by distilling key studies on biomimetic composites primarily composed of plant polysaccharides,including cellulose,pectin,and hemicellulose,as well as organic polymers like lignin.Micro-and nanofabrication of plant CW-like composites,characterization techniques,and in silico studies are reviewed,with a brief overview of current and potential applications.Micro-/nanofabrication approaches include bacterial growth and impregnation,layer-by-layer assembly,film casting,3-dimensional templating microcapsules,and particle coating.Various characterization techniques are necessary for the comprehensive mechanical,chemical,morphological,and structural analyses of plant CWs and CW-like materials.CW-like materials demonstrate versatility in real-life applications,including biomass conversion,pulp and paper,food science,construction,catalysis,and reaction engineering.This review seeks to facilitate the rational design and thorough characterization of plant CW-mimetic materials,with the goal of advancing the development of innovative soft materials and elucidating the complex structure–property relationships inherent in native CWs.展开更多
Artemisia annua,known for its malarial properties,has been central to Madagascar's agricultural economy and traditional healing cultures for centuries.As demand for artemisinin-based treatments for malaria has con...Artemisia annua,known for its malarial properties,has been central to Madagascar's agricultural economy and traditional healing cultures for centuries.As demand for artemisinin-based treatments for malaria has continued to grow globally,Madagascar has emerged as a key supplier of Artemisia annua for global pharmaceutical markets,reinforcing the plant’s national significance.This paper explores the growth and evolution of Artemisia annua cultivation in the country,focusing especially on the recent introduction of synthetic artemisinin and the subsequent cultural,economic,and environmental impacts.It examines the challenges faced by Malagasy farmers and local healers with particular focus on issues such as artemisinin resistance,commercial exploitation,and the growing tension between traditional knowledge and modern biotechnology.Ultimately,this paper explores the complexities of balancing economic development,cultural preservation,and global health needs,offering insight into the broader implications for sustainable pharmaceutical sourcing and the future of traditional medicine in an increasingly globalized world.展开更多
The earthquake early warning(EEW)system provides advance notice of potentially damaging ground shaking.In EEW,early estimation of magnitude is crucial for timely rescue operations.A set of thirty-four features is extr...The earthquake early warning(EEW)system provides advance notice of potentially damaging ground shaking.In EEW,early estimation of magnitude is crucial for timely rescue operations.A set of thirty-four features is extracted using the primary wave earthquake precursor signal and site-specific information.In Japan's earthquake magnitude dataset,there is a chance of a high imbalance concerning the earthquakes above strong impact.This imbalance causes a high prediction error while training advanced machine learning or deep learning models.In this work,Conditional Tabular Generative Adversarial Networks(CTGAN),a deep machine learning tool,is utilized to learn the characteristics of the first arrival of earthquake P-waves and generate a synthetic dataset based on this information.The result obtained using actual and mixed(synthetic and actual)datasets will be used for training the stacked ensemble magnitude prediction model,MagPred,designed specifically for this study.There are 13295,3989,and1710 records designated for training,testing,and validation.The mean absolute error of the test dataset for single station magnitude detection using early three,four,and five seconds of P wave are 0.41,0.40,and 0.38 MJMA.The study demonstrates that the Generative Adversarial Networks(GANs)can provide a good result for single-station magnitude prediction.The study can be effective where less seismic data is available.The study shows that the machine learning method yields better magnitude detection results compared with the several regression models.The multi-station magnitude prediction study has been conducted on prominent Osaka,Off Fukushima,and Kumamoto earthquakes.Furthermore,to validate the performance of the model,an inter-region study has been performed on the earthquakes of the India or Nepal region.The study demonstrates that GANs can discover effective magnitude estimation compared with non-GAN-based methods.This has a high potential for wide application in earthquake early warning systems.展开更多
Planar chiral cyclophanes are a type of structurally intriguing organic molecules,which have found increasingly applications in the field of biologically active compounds,asymmetric catalysis,and optically pure materi...Planar chiral cyclophanes are a type of structurally intriguing organic molecules,which have found increasingly applications in the field of biologically active compounds,asymmetric catalysis,and optically pure materials.As such,significant efforts in the development of new methods to build up enantioenriched cyclophanes in a precise manner have attracted increased attention in recent years.Among the plethora of reported synthetic strategies,catalytic enantioselective method has emerged as one of the most straightforward and efficient ways to deliver optically pure planar chiral cyclophanes.In this review,the recent progress in catalytic enantioselective reactions for the synthesis of planar chiral cyclophanes will be discussed,which would stimulate the research interest of chemists for the discovery of novel asymmetric strategies for the preparation of valuable and previously difficult-to-access chiral molecules.展开更多
One-carbon(C1)compounds,such as CO_(2),methane,and methanol,are emerging as promising feedstocks for next-generation biomanufacturing due to their abundance and low cost.In recent years,there has been growing interest...One-carbon(C1)compounds,such as CO_(2),methane,and methanol,are emerging as promising feedstocks for next-generation biomanufacturing due to their abundance and low cost.In recent years,there has been growing interest in harnessing microorganisms to convert these carbon sources into valuable natural products(NPs),which offers great potential for sustainable development.This review systematically outlines recent advancements in biocatalysts,synthetic biology,and process optimization aimed at improving the feasibility and scalability of producing C1-based NPs.Current challenges and insights into NPs biomanufacturing from C1 compounds are thoroughly examined in the areas of multi-gene editing,metabolic regulation,and synthetic microbial consortium.With ongoing progress in biosynthetic tools and fermentation techniques,C1-based biomanufacturing is becoming a versatile and sustainable platform for generating diverse value-added products.展开更多
文摘α-Trifluoromethyl ketones are a class of useful compounds with versatile applications.Their synthetic application via the transformation of the C—F bonds is of particular interest by allowing the synthesis of organic compounds with diverse structures.Herein,the advances in the research areas ofα-trifluoromethyl ketone synthesis and their defluorination reactions are reviewed.Discussion on the mechanisms of the typical reactions has also been provided,in hope of affording some guides to the chemistry ofα-trifluoromethyl ketones in the synthetic methods toward themselves and their derivatives.
基金supported by the Surface Project of Local De-velopment in Science and Technology Guided by Central Govern-ment(No.2021ZYD0041)the National Natural Science Founda-tion of China(Nos.52377026 and 52301192)+3 种基金the Natural Science Foundation of Shandong Province(No.ZR2019YQ24)the Taishan Scholars and Young Experts Program of Shandong Province(No.tsqn202103057)the Special Financial of Shandong Province(Struc-tural Design of High-efficiency Electromagnetic Wave-absorbing Composite Materials and Construction of Shandong Provincial Tal-ent Teams)the“Sanqin Scholars”Innovation Teams Project of Shaanxi Province(Clean Energy Materials and High-Performance Devices Innovation Team of Shaanxi Dongling Smelting Co.,Ltd.).
文摘With the increasing complexity of the current electromagnetic environment,excessive microwave radi-ation not only does harm to human health but also forms various electromagnetic interference to so-phisticated electronic instruments.Therefore,the design and preparation of electromagnetic absorbing composites represent an efficient approach to mitigate the current hazards of electromagnetic radiation.However,traditional electromagnetic absorbers are difficult to satisfy the demands of actual utilization in the face of new challenges,and emerging absorbents have garnered increasing attention due to their structure and performance-based advantages.In this review,several emerging composites of Mxene-based,biochar-based,chiral,and heat-resisting are discussed in detail,including their synthetic strategy,structural superiority and regulation method,and final optimization of electromagnetic absorption ca-pacity.These insights provide a comprehensive reference for the future development of new-generation electromagnetic-wave absorption composites.Moreover,the potential development directions of these emerging absorbers have been proposed as well.
文摘This study examines the evolving use of synthetic chemicals in intensive agriculture over the past decade.It highlights the negative impacts of chemical inputs on soil health and ecosystem integrity and recommends knowledge-sharing platforms,soil protection laws,and collaborative efforts between regulatory agencies and agricultural experts.The study emphasizes the need for a balanced approach that includes natural methods alongside synthetic chemicals,particularly herbicides.Ten years ago,farmers primarily used urea,DAP,and potassium for nutrients.However,increased awareness,market forces,and government subsidies have led to a significant rise in herbicide use as a cost-effective weed management strategy.Over the past decade,synthetic fertilizer use for cotton cultivation has increased by 80%,leading to deteriorating soil quality.Paddy cultivation has decreased by 23%,while cotton cultivation has increased by 20.4%due to higher economic incentives.Currently,89.1%of farmers use herbicides,compared to 97.2%who did not a decade ago.Insecticide use has also surged,with 97.8%of farmers applying 1.5 liters or more per acre.The excessive use of chemicals threatens soil fertility and disrupts the ecosystem’s balance.This article explores the reasons behind the adoption of chemical-intensive farming practices and offers insights into farmers’decision-making processes.The careful use of synthetic chemicals is essential to safeguard soil health and maintain ecological balance.
基金supported by funding from the National Key R&D Program of China(2023ZD0407304)the Sci-Tech Innovation 2030 Agenda(2022ZD0115703)Fundamental Research Funds for Central Non-Profit of Chinese Academy of Agricultural Sciences(Y2023PT20).
文摘Epigenetics-mediated breeding(epibreeding)involves engineering crop traits and stress responses through the targeted manipulation of key epigenetic features to enhance agricultural productivity.While conventional breeding methods raise concerns about reduced genetic diversity,epibreeding propels crop improvement through epigenetic variations that regulate gene expression,ultimately impacting crop yield.Epigenetic regulation in crops encompasses various modes,including histone modification,DNA modification,RNA modification,non-coding RNA,and chromatin remodeling.This review summarizes the epigenetic mechanisms underlying major agronomic traits in maize and identifies candidate epigenetic landmarks in the maize breeding process.We propose a valuable strategy for improving maize yield through epibreeding,combining CRISPR/Cas-based epigenome editing technology and Synthetic Epigenetics(SynEpi).Finally,we discuss the challenges and opportunities associated with maize trait improvement through epibreeding.
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences(Category B,XDB1090000).
文摘Plant synthetic biology has emerged as a transformative field in agriculture,offering innovative solutions to enhance food security,provide resilience to climate change,and transition to sustainable farming practices.By integrating advanced genetic tools,computational modeling,and systems biology,researchers can precisely modify plant genomes to enhance traits such as yield,stress tolerance,and nutrient use efficiency.The ability to design plants with specific characteristics tailored to diverse environmental conditions and agricultural needs holds great potential to address global food security challenges.Here,we highlight recent advancements and applications of plant synthetic biology in agriculture,focusing on key areas such as photosynthetic efficiency,nitrogen fixation,drought tolerance,pathogen resistance,nutrient use efficiency,biofortification,climate resilience,microbiology engineering,synthetic plant genomes,and the integration of artificial intelligence with synthetic biology.These innovations aim to maximize resource use efficiency,reduce reliance on external inputs,and mitigate environmental impacts associated with conventional agricultural practices.Despite challenges related to regulatory approval and public acceptance,the integration of synthetic biology in agriculture holds immense promise for creating more resilient and sustainable agricultural systems,contributing to global food security and environmental sustainability.Rigorous multi-field testing of these approaches will undoubtedly be required to ensure reproducibility.
基金jointly supported by the International Research Center of Big Data for Sustainable Development Goals(Grant No.CBAS2022GSP02)the National Natural Science Foundation of China(Grant Nos.42072320 and 42372264).
文摘Active landslides pose a significant threat globally,endangering lives and property.Effective monitoring and forecasting of displacements are essential for the timely warnings and mitigation of these events.Interferometric synthetic aperture radar(InSAR)stands out as an efficient and prevalent tool for monitoring landslide deformation and offers new prospects for displacement prediction.However,challenges such as inherent limitation of satellite viewing geometry,long revisit cycles,and limited data volume hinder its application in displacement forecasting,notably for landslides with near-north-south deformation less detectable by InSAR.To address these issues,we propose a novel strategy for predicting three-dimensional(3D)landslide displacement,integrating InSAR and global navigation satellite system(GNSS)measurements with machine learning(ML).This framework first synergizes InSAR line-of-sight(LOS)results with GNSS horizontal data to reconstruct 3D displacement time series.It then employs ML models to capture complex nonlinear relationships between external triggers,landslide evolutionary states,and 3D displacements,thus enabling accurate future deformation predictions.Utilizing four advanced ML algorithms,i.e.random forest(RF),support vector machine(SVM),long short-term memory(LSTM),and gated recurrent unit(GRU),with Bayesian optimization(BO)for hyperparameter tuning,we applied this innovative approach to the north-facing,slow-moving Xinpu landslide in the Three Gorges Reservoir Area(TGRA)of China.Leveraging over 6.5 years of Sentinel-1 satellite data and GNSS measurements,our framework demonstrates satisfactory and robust prediction performance,with an average root mean square deviation(RMSD)of 9.62 mm and a correlation coefficient(CC)of 0.996.This study presents a promising strategy for 3D displacement prediction,illustrating the efficacy of integrating InSAR monitoring with ML forecasting in enhancing landslide early warning capabilities.
文摘In recent years,with the development of synthetic aperture radar(SAR)technology and the widespread application of deep learning,lightweight detection of SAR images has emerged as a research direction.The ultimate goal is to reduce computational and storage requirements while ensuring detection accuracy and reliability,making it an ideal choice for achieving rapid response and efficient processing.In this regard,a lightweight SAR ship target detection algorithm based on YOLOv8 was proposed in this study.Firstly,the C2f-Sc module was designed by fusing the C2f in the backbone network with the ScConv to reduce spatial redundancy and channel redundancy between features in convolutional neural networks.At the same time,the Ghost module was introduced into the neck network to effectively reduce model parameters and computational complexity.A relatively lightweight EMA attention mechanism was added to the neck network to promote the effective fusion of features at different levels.Experimental results showed that the Parameters and GFLOPs of the improved model are reduced by 8.5%and 7.0%when mAP@0.5 and mAP@0.5:0.95 are increased by 0.7%and 1.8%,respectively.It makes the model lightweight and improves the detection accuracy,which has certain application value.
文摘The use of synthetic biology technology to develop cosmetic ingredients is attracting widespread attention due to its effectiveness,safety,and environmental friendliness.This article explains the concept of synthetic biology and its key technologies and current status in the production of cosmetic ingredients.It also briefly analyzes the regulatory approaches to synthetic biology-based cosmetic ingredients in different countries and regions,providing guidance for the management of this field in China.The goal is to ensure product safety,enhance consumer trust,and promote the healthy development of the industry.
文摘There is a growing body of clinical research on the utility of synthetic data derivatives,an emerging research tool in medicine.In nephrology,clinicians can use machine learning and artificial intelligence as powerful aids in their clinical decision-making while also preserving patient privacy.This is especially important given the epidemiology of chronic kidney disease,renal oncology,and hypertension worldwide.However,there remains a need to create a framework for guidance regarding how to better utilize synthetic data as a practical application in this research.
基金supported by the National Natural Science Foundation of China(Nos.52075538,92271110)Hunan Provincial Natural Science Foundation,China(No.2023JJ30622)the National Science and Technology Major Project,China(Nos.J2019-II-0016-0037,J2019-III-0010-0054).
文摘Aiming at the dynamic stall problem that restricts the improvement of aircraft maneuverability,a new dynamic stall control method based on leading-edge Dual Synthetic Jets(DSJ)is proposed in this paper.The aerodynamic control characteristics and flow field evolution process of steady jet,Synthetic Jet(SJ)and DSJ in dynamic stall flow field are analyzed in detail,and the corresponding control mechanism is revealed.The strong"wall attachment effect"and quasisteady"characteristics of DSJ are found.The results show that the leading-edge jet technology can improve the dynamic stall flow field environment.For the whole pitching process,the average lift coefficients of steady jet,SJ and DSJ increased by 3.65%,10.51%and 14.62%respectively,and the average drag coefficients decreased by 9.58%,29.9%and 32.0%respectively.In the downward phase,the average lift coefficient increased by 16.31%,26.72%and 35.88%respectively,and the average drag coefficient decreased by 26.21%,50.46%and 54.28%respectively.Due to its strong"wall attachment effect"and"quasi-steady"characteristics,DSJ exhibits optimal control effect,showing its application potential in dynamic stall control.
文摘The central Chinese province emerges as a key player in China-African trade and investment cooperation The fourth China-Africa Economic and Trade Expo(CAETE)was a prime opportunity for Citygreen Sports,a Chinese supplier of synthetic turf,to boost its visibility.“Africa is one of our main markets.The expo allows us to showcase our products to African customers and engage directly with government representatives to discuss potential projects,”Wu Huan,regional director for international affairs at the group,told ChinAfrica.Based in Shishou,Hubei Province,the company notably supplied the synthetic turf for Ethiopia’s national stadium,the country’s only FIFA-certified field.
文摘Imbalanced multiclass datasets pose challenges for machine learning algorithms.They often contain minority classes that are important for accurate predictions.However,when the data is sparsely distributed and overlaps with data points fromother classes,it introduces noise.As a result,existing resamplingmethods may fail to preserve the original data patterns,further disrupting data quality and reducingmodel performance.This paper introduces Neighbor Displacement-based Enhanced Synthetic Oversampling(NDESO),a hybridmethod that integrates a data displacement strategy with a resampling technique to achieve data balance.It begins by computing the average distance of noisy data points to their neighbors and adjusting their positions toward the center before applying random oversampling.Extensive evaluations compare 14 alternatives on nine classifiers across synthetic and 20 real-world datasetswith varying imbalance ratios.This evaluation was structured into two distinct test groups.First,the effects of k-neighbor variations and distance metrics are evaluated,followed by a comparison of resampled data distributions against alternatives,and finally,determining the most suitable oversampling technique for data balancing.Second,the overall performance of the NDESO algorithm was assessed,focusing on G-mean and statistical significance.The results demonstrate that our method is robust to a wide range of variations in these parameters and the overall performance achieves an average G-mean score of 0.90,which is among the highest.Additionally,it attains the lowest mean rank of 2.88,indicating statistically significant improvements over existing approaches.This advantage underscores its potential for effectively handling data imbalance in practical scenarios.
基金supported by the National Key R&D Program of China(Nos.2022YFF1203005,2022YFC2303700)supported by the National Natural Science Foundation of China(Nos.81930097,82151223).
文摘3-Deoxy-D-manno–oct-2-ulosonic acid(Kdo)is widely distributed in bacteria,and the synthesis of Kdocontaining oligosaccharides is important for the development of novel antibiotics and immunological agents.We have recently developed a strategy to achieveα-stereocontrolled glycosylation using a C3-p-tolylthio-substituted Kdo phosphite donor.The wide substrate scope and high reactivity of the donors enabled the efficient synthesis of a series of Kdo-containing glycosides with completeα-stereoselectivity and without the formation of 2,3-ene byproducts.In this study,we improved the method by replacing the leaving group diethyl phosphite with fluoride,which enhanced the stability of the donor and led to cleaner reaction.Furthermore,the substrate range was expanded by synthesizing a series of Kdo O/C/S/Nglycosides,which also opened up a new avenue for the synthesis of CMP-Kdo synthase inhibitors.
基金financial support by the Development Plan of Science and Technology of Jilin Province(No.YDZJ202201ZYTS305)the Natural Science Foundation of Jilin Province(No.YDZJ202401316ZYTS)the Innovation Laboratory Development Program of Education Department of Jilin Province and Industry and Information Technology Department of Jilin Province,China(The Joint Laboratory of MAX/MXene Materials).
文摘MAX series materials,as non-van der Waals layered multi-element compounds,contribute remarkable regulated properties and functional dimension,combining the features of metal and ceramic materials due to their inherently laminated crystal structure that Mn+1Xn slabs are intercalated with A element layers.Oriented to the functional requirements of information,intelligence,electrification,and aerospace in the new era,how to accelerate MAX series materials into new quality productive forces?The systematic enhancement of knowledge about MAX series materials is intrinsic to understanding its low-dimensional geometric structure characteristics,and physical and chemical properties,revealing the correlation of composition,structure,and function and further realizing rational design based on simulation and prediction.Diversity also brings complexity to MAX materials research.This review provides substantial tabular information on(Ⅰ)MAX’s research timeline from 1960 to the present,(Ⅱ)structure diversity and classification convention,(Ⅲ)synthesis route exploration,(Ⅳ)prediction based on theory and machine learning,(Ⅴ)properties,and(Ⅵ)functional applications.Herein,the researchers can quickly locate research content and recognize connections and differences of MAX series materials.In addition,the research challenges for the future development of MAX series materials are highlighted.
基金supported as part of The Center for LignoCellulose Structure and Formation,an Energy Frontier Research Center funded by the U.S.Department of Energy,Office of Science,Basic Energy Sciences under Award#DE-SC0001090support from the Huck Institutes of the Life Sciences at Penn State University through the Patricia and Stephen Benkovic Research Initiativesupported by the Center for Engineering Mechano Biology(CEMB),an NSF Science and Technology Center,under grant agreement CMMI:15-48571。
文摘Plant cell wall(CW)-like soft materials,referred to as artificial CWs,are composites of assembled polymers containing micro-/nanoparticles or fibers/fibrils that are designed to mimic the composition,structure,and mechanics of plant CWs.CW-like materials have recently emerged to test hypotheses pertaining to the intricate structure–property relationships of native plant CWs or to fabricate functional materials.Here,research on plant CWs and CW-like materials is reviewed by distilling key studies on biomimetic composites primarily composed of plant polysaccharides,including cellulose,pectin,and hemicellulose,as well as organic polymers like lignin.Micro-and nanofabrication of plant CW-like composites,characterization techniques,and in silico studies are reviewed,with a brief overview of current and potential applications.Micro-/nanofabrication approaches include bacterial growth and impregnation,layer-by-layer assembly,film casting,3-dimensional templating microcapsules,and particle coating.Various characterization techniques are necessary for the comprehensive mechanical,chemical,morphological,and structural analyses of plant CWs and CW-like materials.CW-like materials demonstrate versatility in real-life applications,including biomass conversion,pulp and paper,food science,construction,catalysis,and reaction engineering.This review seeks to facilitate the rational design and thorough characterization of plant CW-mimetic materials,with the goal of advancing the development of innovative soft materials and elucidating the complex structure–property relationships inherent in native CWs.
文摘Artemisia annua,known for its malarial properties,has been central to Madagascar's agricultural economy and traditional healing cultures for centuries.As demand for artemisinin-based treatments for malaria has continued to grow globally,Madagascar has emerged as a key supplier of Artemisia annua for global pharmaceutical markets,reinforcing the plant’s national significance.This paper explores the growth and evolution of Artemisia annua cultivation in the country,focusing especially on the recent introduction of synthetic artemisinin and the subsequent cultural,economic,and environmental impacts.It examines the challenges faced by Malagasy farmers and local healers with particular focus on issues such as artemisinin resistance,commercial exploitation,and the growing tension between traditional knowledge and modern biotechnology.Ultimately,this paper explores the complexities of balancing economic development,cultural preservation,and global health needs,offering insight into the broader implications for sustainable pharmaceutical sourcing and the future of traditional medicine in an increasingly globalized world.
基金related to grant PM-31-22-626-414 from the Prime Minister's Research Fellows(PMRF)of the Indian Institute of Technology Roorkee。
文摘The earthquake early warning(EEW)system provides advance notice of potentially damaging ground shaking.In EEW,early estimation of magnitude is crucial for timely rescue operations.A set of thirty-four features is extracted using the primary wave earthquake precursor signal and site-specific information.In Japan's earthquake magnitude dataset,there is a chance of a high imbalance concerning the earthquakes above strong impact.This imbalance causes a high prediction error while training advanced machine learning or deep learning models.In this work,Conditional Tabular Generative Adversarial Networks(CTGAN),a deep machine learning tool,is utilized to learn the characteristics of the first arrival of earthquake P-waves and generate a synthetic dataset based on this information.The result obtained using actual and mixed(synthetic and actual)datasets will be used for training the stacked ensemble magnitude prediction model,MagPred,designed specifically for this study.There are 13295,3989,and1710 records designated for training,testing,and validation.The mean absolute error of the test dataset for single station magnitude detection using early three,four,and five seconds of P wave are 0.41,0.40,and 0.38 MJMA.The study demonstrates that the Generative Adversarial Networks(GANs)can provide a good result for single-station magnitude prediction.The study can be effective where less seismic data is available.The study shows that the machine learning method yields better magnitude detection results compared with the several regression models.The multi-station magnitude prediction study has been conducted on prominent Osaka,Off Fukushima,and Kumamoto earthquakes.Furthermore,to validate the performance of the model,an inter-region study has been performed on the earthquakes of the India or Nepal region.The study demonstrates that GANs can discover effective magnitude estimation compared with non-GAN-based methods.This has a high potential for wide application in earthquake early warning systems.
基金financial support provided by Huanghuai University and Hangzhou Medical College.
文摘Planar chiral cyclophanes are a type of structurally intriguing organic molecules,which have found increasingly applications in the field of biologically active compounds,asymmetric catalysis,and optically pure materials.As such,significant efforts in the development of new methods to build up enantioenriched cyclophanes in a precise manner have attracted increased attention in recent years.Among the plethora of reported synthetic strategies,catalytic enantioselective method has emerged as one of the most straightforward and efficient ways to deliver optically pure planar chiral cyclophanes.In this review,the recent progress in catalytic enantioselective reactions for the synthesis of planar chiral cyclophanes will be discussed,which would stimulate the research interest of chemists for the discovery of novel asymmetric strategies for the preparation of valuable and previously difficult-to-access chiral molecules.
基金supported by the Science Fund for Distinguished Young Scholars of Shaanxi Province(2022JC-09)the China Postdoctoral Science Foundation(2023M732780)+1 种基金the Higher Education Institution Academic Discipline Innovation and Talent Introduction Plan(B23025)the Youth Innovation Team of Shaanxi Universities.
文摘One-carbon(C1)compounds,such as CO_(2),methane,and methanol,are emerging as promising feedstocks for next-generation biomanufacturing due to their abundance and low cost.In recent years,there has been growing interest in harnessing microorganisms to convert these carbon sources into valuable natural products(NPs),which offers great potential for sustainable development.This review systematically outlines recent advancements in biocatalysts,synthetic biology,and process optimization aimed at improving the feasibility and scalability of producing C1-based NPs.Current challenges and insights into NPs biomanufacturing from C1 compounds are thoroughly examined in the areas of multi-gene editing,metabolic regulation,and synthetic microbial consortium.With ongoing progress in biosynthetic tools and fermentation techniques,C1-based biomanufacturing is becoming a versatile and sustainable platform for generating diverse value-added products.
