Synthetic speech detection is an essential task in the field of voice security,aimed at identifying deceptive voice attacks generated by text-to-speech(TTS)systems or voice conversion(VC)systems.In this paper,we propo...Synthetic speech detection is an essential task in the field of voice security,aimed at identifying deceptive voice attacks generated by text-to-speech(TTS)systems or voice conversion(VC)systems.In this paper,we propose a synthetic speech detection model called TFTransformer,which integrates both local and global features to enhance detection capabilities by effectively modeling local and global dependencies.Structurally,the model is divided into two main components:a front-end and a back-end.The front-end of the model uses a combination of SincLayer and two-dimensional(2D)convolution to extract high-level feature maps(HFM)containing local dependency of the input speech signals.The back-end uses time-frequency Transformer module to process these feature maps and further capture global dependency.Furthermore,we propose TFTransformer-SE,which incorporates a channel attention mechanism within the 2D convolutional blocks.This enhancement aims to more effectively capture local dependencies,thereby improving the model’s performance.The experiments were conducted on the ASVspoof 2021 LA dataset,and the results showed that the model achieved an equal error rate(EER)of 3.37%without data augmentation.Additionally,we evaluated the model using the ASVspoof 2019 LA dataset,achieving an EER of 0.84%,also without data augmentation.This demonstrates that combining local and global dependencies in the time-frequency domain can significantly improve detection accuracy.展开更多
A trace analytical method based on solid-phase extraction gas chromatography-tandem mass spectrometry(SPE–GC–MS/MS)was developed for the rapid detection of 256 semi-volatile organic compounds(SVOCs),including 25 pol...A trace analytical method based on solid-phase extraction gas chromatography-tandem mass spectrometry(SPE–GC–MS/MS)was developed for the rapid detection of 256 semi-volatile organic compounds(SVOCs),including 25 polycyclic aromatic hydrocarbons(PAHs),70 polychlorinated biphenyls(PCBs),123 pesticides,20 phthalate esters(PAEs),4 organophosphate esters(OPEs),9 synthetic musks(SMs),and 5 UV filters(UVs)in water.No-tably,this method provided a decent linearity of calibration standards(R^(2)>0.999),excellent method limits of quantification(MLOQs)(0.12–11.41 ng/L),satisfactory matrix spiking recovery rates(60.4%–126%),and high precision(intra-day relative standard deviations(RSDs):1.0%–10.0%,inter-day RSDs:3.0%–15.0%,and inter-week RSDs:3.4%–15.7%),making it suitable for trace-level studies.Statistical analysis revealed that SVOCs with higher volatility exhibited enhanced recovery rates.Validation of the methodology involved analyzing SVOCs in real spring water and river water samples.Twenty-seven SVOCs were detected in spring water and 58 in river water,with an average concentration of 631.73 and 16,095 ng/L,respectively.Among the detected SVOCs,PAEs constituted the predominant proportion.This study underscored the presence of SVOCs contamination specifi-cally within the spring water,although SVOCs concentrations in river water were significantly greater than those found in spring water.In summary,this sensitive method based on SPE–GC–MS/MS was successfully developed and validated for the rapid analysis of a diverse array of 256 SVOCs at trace levels in water,including not only the traditional highly valued PAHs,PCBs,pesticides,and PAEs,but also the emerging OPEs,UVs,and SMs.展开更多
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
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
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
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
Synthetic phenolic antioxidants(SPAs)are widely used in diverse industries due to their exceptional antioxidant characteristics.However,human exposure to SPAs may cause health problems.In this study,226 dust samples w...Synthetic phenolic antioxidants(SPAs)are widely used in diverse industries due to their exceptional antioxidant characteristics.However,human exposure to SPAs may cause health problems.In this study,226 dust samples were collected from 10 provinces in China,and six SPAs(three parent SPAs and their three transformation products)were analyzed.The concentrations of6SPAs(the sum of six target compounds)ranged from 15.4 to 3210 ng/g(geometric mean(GM):169 ng/g).The highest concentration of6SPAswas found in Sichuan Province(GM:349 ng/g),which was approximately 4 times higher than that in Hubei Province(81.6 ng/g)(p<0.05).The concentrations of butylated hydroxytoluene(BHT),2,2'-methylene bis(4-methyl-6–tert-butylphenol)(AO2246),2,6-di–tert–butyl–1,4-benzoquinone(BHT-Q),2,6-di–tert–butyl–4-(hydroxymethyl)phenol(BHT-OH),and ∑_(p)-SPAs were substantially higher in dust from urban areas than rural areas(p<0.05).AO2246 concentration in dust from homes(GM:0.400 ng/g)was about 4 times higher than that in workplaces(0.116 ng/g)(p<0.01).Significantly higherp-SPAs concentrations were found in dust from homes(GM:17.5 ng/g)than workplaces(11.4 ng/g)(p<0.01).The estimated daily intakes(EDIs)of ∑_(6)SPAs exposed through dust ingestion were 0.582,0.342,0.197,0.076,and 0.080 ng/kg bw/day in different age groups,and exposed through dermal contact was 0.358,0.252,0.174,0.167,and 0.177 ng/kg bw/day.EDIs showed that the exposure risks of SPAs decreased with age.This is the first work to determine SPAs in dust from10 provinces in China and investigate the spatial distribution of SPAs in those regions.展开更多
Synthetic aperture radar(SAR)aboard SEASAT was first launched in 1978.At the beginning of the 21st century,the Chinese remote sensing community recognized the urgent need to develop domestic SAR capabilities.Unlike sc...Synthetic aperture radar(SAR)aboard SEASAT was first launched in 1978.At the beginning of the 21st century,the Chinese remote sensing community recognized the urgent need to develop domestic SAR capabilities.Unlike scatterometers and al-timeters,space-borne SAR offers high-resolution images of the ocean,regardless of weather conditions or time of day.SAR imagery provides rich information about the sea surface,capturing complicated dynamic processes in the upper layers of the ocean,particular-ly in relation to tropical cyclones.Over the past four decades,the advantages of SAR have been increasingly recognized,leading to notable marine applications,especially in the development of algorithms for retrieving wind and wave data from SAR images.This study reviews the history,progress,and future outlook of SAR-based monitoring of sea surface wind and waves.In particular,the ap-plicability of various SAR wind and wave algorithms is systematically investigated,with a particular focus on their performance un-der extreme sea conditions.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
An efficient and practical synthetic process for Daprodustat was developed.Starting with N,N'-dicyclohexylcarbodiimide(DCC)and malonic acid,the key intermediate 1,3-dicyclohexylpyrimidine-2,4,6(1H,3H,5H)-trione wa...An efficient and practical synthetic process for Daprodustat was developed.Starting with N,N'-dicyclohexylcarbodiimide(DCC)and malonic acid,the key intermediate 1,3-dicyclohexylpyrimidine-2,4,6(1H,3H,5H)-trione was synthesized via condensation reaction with 91%yield.Subsequent activation of this intermediate by 1,1'-carbonyldiimidazole(CDI),followed by a one-pot reaction with glycine ethyl ester hydrochloride,directly afforded Daprodustat in 92%yield with>99.8%HPLC purity.The process achieved an overall yield of 84%upon validation at 62-gram scale.Structural confirmation of the key intermediate was accomplished through nuclear magnetic resonance(NMR)spectroscopy and high-resolution mass spectrometry(HRMS).Compared with existing methods,this streamlined protocol demonstrates advantages including simplified operation,reduced reaction time,and lower production costs,offering significant potential for industrial-scale synthesis of Daprodustat.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
I.The Fentanyl Crisis in the U.S.The development and spread of the fentanyl crisis in the U.S.Recent years have seen a deteriorating narcotics situation in the U.S.and serious social problems arising therefrom.From 19...I.The Fentanyl Crisis in the U.S.The development and spread of the fentanyl crisis in the U.S.Recent years have seen a deteriorating narcotics situation in the U.S.and serious social problems arising therefrom.From 1999 to 2012,deaths from synthetic opioids(mainly fentanylrelated substances)overdose in the U.S.increased by 8%annually.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
Skeletal editing has emerged as a powerful tool in organic chemistry,enabling the simplification of synthetic routes to complex molecules[1].Indoles,electron-rich nitrogen-containing building blocks,represent privileg...Skeletal editing has emerged as a powerful tool in organic chemistry,enabling the simplification of synthetic routes to complex molecules[1].Indoles,electron-rich nitrogen-containing building blocks,represent privileged scaffolds prevalent in pharmaceuticals,natural products,and bioactive compounds.The application of skeletal editing strategies to modify such structures is highly valuable and in growing demand.Leveraging the electronrich nature of indoles at C2 and C3,single-carbon atom insertion using cationic carbyne equivalents offers an efficient approach for indole ring expansion to quinoline(Scheme 1a).However,existing methods predominantly rely on halocarbene precursors,which restricts the functional groups of ring-expanded products to halogen[2],alkyl,aryl,heteroaryl and ester moieties[3].This limitation hinders their utility in late-stage skeletal modifications of complex targets.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
基金supported by project ZR2022MF330 supported by Shandong Provincial Natural Science Foundationthe National Natural Science Foundation of China under Grant No.61701286.
文摘Synthetic speech detection is an essential task in the field of voice security,aimed at identifying deceptive voice attacks generated by text-to-speech(TTS)systems or voice conversion(VC)systems.In this paper,we propose a synthetic speech detection model called TFTransformer,which integrates both local and global features to enhance detection capabilities by effectively modeling local and global dependencies.Structurally,the model is divided into two main components:a front-end and a back-end.The front-end of the model uses a combination of SincLayer and two-dimensional(2D)convolution to extract high-level feature maps(HFM)containing local dependency of the input speech signals.The back-end uses time-frequency Transformer module to process these feature maps and further capture global dependency.Furthermore,we propose TFTransformer-SE,which incorporates a channel attention mechanism within the 2D convolutional blocks.This enhancement aims to more effectively capture local dependencies,thereby improving the model’s performance.The experiments were conducted on the ASVspoof 2021 LA dataset,and the results showed that the model achieved an equal error rate(EER)of 3.37%without data augmentation.Additionally,we evaluated the model using the ASVspoof 2019 LA dataset,achieving an EER of 0.84%,also without data augmentation.This demonstrates that combining local and global dependencies in the time-frequency domain can significantly improve detection accuracy.
基金supported by the National Natural Science Foundation of China(No.51939009)Shenzhen Science and Technology Program(Nos.JCYJ20241202125905008 and GXWD20201231165807007-20200810165349001).
文摘A trace analytical method based on solid-phase extraction gas chromatography-tandem mass spectrometry(SPE–GC–MS/MS)was developed for the rapid detection of 256 semi-volatile organic compounds(SVOCs),including 25 polycyclic aromatic hydrocarbons(PAHs),70 polychlorinated biphenyls(PCBs),123 pesticides,20 phthalate esters(PAEs),4 organophosphate esters(OPEs),9 synthetic musks(SMs),and 5 UV filters(UVs)in water.No-tably,this method provided a decent linearity of calibration standards(R^(2)>0.999),excellent method limits of quantification(MLOQs)(0.12–11.41 ng/L),satisfactory matrix spiking recovery rates(60.4%–126%),and high precision(intra-day relative standard deviations(RSDs):1.0%–10.0%,inter-day RSDs:3.0%–15.0%,and inter-week RSDs:3.4%–15.7%),making it suitable for trace-level studies.Statistical analysis revealed that SVOCs with higher volatility exhibited enhanced recovery rates.Validation of the methodology involved analyzing SVOCs in real spring water and river water samples.Twenty-seven SVOCs were detected in spring water and 58 in river water,with an average concentration of 631.73 and 16,095 ng/L,respectively.Among the detected SVOCs,PAEs constituted the predominant proportion.This study underscored the presence of SVOCs contamination specifi-cally within the spring water,although SVOCs concentrations in river water were significantly greater than those found in spring water.In summary,this sensitive method based on SPE–GC–MS/MS was successfully developed and validated for the rapid analysis of a diverse array of 256 SVOCs at trace levels in water,including not only the traditional highly valued PAHs,PCBs,pesticides,and PAEs,but also the emerging OPEs,UVs,and SMs.
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.
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.
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 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supported by the National Key Research and Development Program of China(No.2023YFC3706602)the National Natural Science Foundation of China(Nos.22225605 and 22193051)the Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDB0750200).
文摘Synthetic phenolic antioxidants(SPAs)are widely used in diverse industries due to their exceptional antioxidant characteristics.However,human exposure to SPAs may cause health problems.In this study,226 dust samples were collected from 10 provinces in China,and six SPAs(three parent SPAs and their three transformation products)were analyzed.The concentrations of6SPAs(the sum of six target compounds)ranged from 15.4 to 3210 ng/g(geometric mean(GM):169 ng/g).The highest concentration of6SPAswas found in Sichuan Province(GM:349 ng/g),which was approximately 4 times higher than that in Hubei Province(81.6 ng/g)(p<0.05).The concentrations of butylated hydroxytoluene(BHT),2,2'-methylene bis(4-methyl-6–tert-butylphenol)(AO2246),2,6-di–tert–butyl–1,4-benzoquinone(BHT-Q),2,6-di–tert–butyl–4-(hydroxymethyl)phenol(BHT-OH),and ∑_(p)-SPAs were substantially higher in dust from urban areas than rural areas(p<0.05).AO2246 concentration in dust from homes(GM:0.400 ng/g)was about 4 times higher than that in workplaces(0.116 ng/g)(p<0.01).Significantly higherp-SPAs concentrations were found in dust from homes(GM:17.5 ng/g)than workplaces(11.4 ng/g)(p<0.01).The estimated daily intakes(EDIs)of ∑_(6)SPAs exposed through dust ingestion were 0.582,0.342,0.197,0.076,and 0.080 ng/kg bw/day in different age groups,and exposed through dermal contact was 0.358,0.252,0.174,0.167,and 0.177 ng/kg bw/day.EDIs showed that the exposure risks of SPAs decreased with age.This is the first work to determine SPAs in dust from10 provinces in China and investigate the spatial distribution of SPAs in those regions.
基金supported by the National Nat-ural Science Foundation of China(No.42376174)the Natural Science Foundation of Shanghai(No.23ZR 1426900).
文摘Synthetic aperture radar(SAR)aboard SEASAT was first launched in 1978.At the beginning of the 21st century,the Chinese remote sensing community recognized the urgent need to develop domestic SAR capabilities.Unlike scatterometers and al-timeters,space-borne SAR offers high-resolution images of the ocean,regardless of weather conditions or time of day.SAR imagery provides rich information about the sea surface,capturing complicated dynamic processes in the upper layers of the ocean,particular-ly in relation to tropical cyclones.Over the past four decades,the advantages of SAR have been increasingly recognized,leading to notable marine applications,especially in the development of algorithms for retrieving wind and wave data from SAR images.This study reviews the history,progress,and future outlook of SAR-based monitoring of sea surface wind and waves.In particular,the ap-plicability of various SAR wind and wave algorithms is systematically investigated,with a particular focus on their performance un-der extreme sea conditions.
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An efficient and practical synthetic process for Daprodustat was developed.Starting with N,N'-dicyclohexylcarbodiimide(DCC)and malonic acid,the key intermediate 1,3-dicyclohexylpyrimidine-2,4,6(1H,3H,5H)-trione was synthesized via condensation reaction with 91%yield.Subsequent activation of this intermediate by 1,1'-carbonyldiimidazole(CDI),followed by a one-pot reaction with glycine ethyl ester hydrochloride,directly afforded Daprodustat in 92%yield with>99.8%HPLC purity.The process achieved an overall yield of 84%upon validation at 62-gram scale.Structural confirmation of the key intermediate was accomplished through nuclear magnetic resonance(NMR)spectroscopy and high-resolution mass spectrometry(HRMS).Compared with existing methods,this streamlined protocol demonstrates advantages including simplified operation,reduced reaction time,and lower production costs,offering significant potential for industrial-scale synthesis of Daprodustat.
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I.The Fentanyl Crisis in the U.S.The development and spread of the fentanyl crisis in the U.S.Recent years have seen a deteriorating narcotics situation in the U.S.and serious social problems arising therefrom.From 1999 to 2012,deaths from synthetic opioids(mainly fentanylrelated substances)overdose in the U.S.increased by 8%annually.
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Skeletal editing has emerged as a powerful tool in organic chemistry,enabling the simplification of synthetic routes to complex molecules[1].Indoles,electron-rich nitrogen-containing building blocks,represent privileged scaffolds prevalent in pharmaceuticals,natural products,and bioactive compounds.The application of skeletal editing strategies to modify such structures is highly valuable and in growing demand.Leveraging the electronrich nature of indoles at C2 and C3,single-carbon atom insertion using cationic carbyne equivalents offers an efficient approach for indole ring expansion to quinoline(Scheme 1a).However,existing methods predominantly rely on halocarbene precursors,which restricts the functional groups of ring-expanded products to halogen[2],alkyl,aryl,heteroaryl and ester moieties[3].This limitation hinders their utility in late-stage skeletal modifications of complex targets.
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.
