Based on the theory of pattern recognition, the concept of closeness degree between fuzzy sets is brought into the condition assessment of long span bridges. Using the fuzzy analytic hierarchy process （FAHP）, a math...Based on the theory of pattern recognition, the concept of closeness degree between fuzzy sets is brought into the condition assessment of long span bridges. Using the fuzzy analytic hierarchy process （FAHP）, a mathematical model of a multi-objective assessment of a long span suspension bridge is set up. An example is given to show the procedure in the synthetical condition assessment of the Runyang Suspension Bridge, which includes the hierarchical division, the definition of factor weights and fuzzy membership functions, and the calculation of closeness degrees, etc. The assessment combines both the data from the health monitoring system and the manual tests. The classification of evaluation items as well as the calculation of deterministic and nondeterministic items is presented. Compared with the traditional method of point rating, this method can better describe the discreteness of monitoring data and the fuzziness in the condition assessment.展开更多
Now the optimization strategies for power distribution are researched widely, and most of them are aiming to the optimal fuel economy and the driving cycle must be preknown. Thus if the actual driving condition deviat...Now the optimization strategies for power distribution are researched widely, and most of them are aiming to the optimal fuel economy and the driving cycle must be preknown. Thus if the actual driving condition deviates from the scheduled driving cycle, the effect of optimal results will be declined greatly. Therefore, the instantaneous optimization strategy carried out on-line is studied in this paper. The power split path and the transmission efficiency are analyzed based on a special power-split scheme and the efficiency models of the power transmitting components are established. The synthetical efficiency optimization model is established for enhancing the transmission efficiency and the fuel economy. The identification of the synthetical efficiency as the optimization objective and the constrain group are discussed emphatically. The optimization is calculated by the adaptive simulated annealing （ASA） algorithm and realized on-line by the radial basis function （RBF）-based similar models. The optimization for power distribution of the hybrid vehicle in an actual driving condition is carried out and the road test results are presented. The test results indicate that the synthetical efficiency optimization method can enhance the transmission efficiency and the fuel economy of the power-split hybrid electric vehicle （HEV） observably. Compared to the rules-based strategy the optimization strategy is optimal and achieves the approximate global optimization solution for the power distribution. The synthetical efficiency optimization solved by ASA algorithm can give attentions to both optimization quality and calculation efficiency, thus it has good application foreground for the power distribution of power-split HEV.展开更多
Due to the complexity of thickness and shape synthetical adjustment system and the difficulties to build a mathematical model,a thickness and shape synthetical adjustment scheme on DC mill based on dynamic nerve-fuzzy...Due to the complexity of thickness and shape synthetical adjustment system and the difficulties to build a mathematical model,a thickness and shape synthetical adjustment scheme on DC mill based on dynamic nerve-fuzzy control was put forward,and a self-organizing fuzzy control model was established.The structure of the network can be optimized dynamically.In the course of studying,the network can automatically adjust its structure based on the specific questions and make its structure the optimal.The input and output of the network are fuzzy sets,and the trained network can complete the composite relation,the fuzzy inference.For decreasing the off-line training time of BP network,the fuzzy sets are encoded.The simulation results indicate that the self-organizing fuzzy control based on dynamic neural network is better than traditional decoupling PID control.展开更多
Government policy is the key to the development of the individual and private economy (IPE).In the making of a policy, the social consciousness of government officials is one of the important factors to affect the pol...Government policy is the key to the development of the individual and private economy (IPE).In the making of a policy, the social consciousness of government officials is one of the important factors to affect the policy made. Since the social consciousness on the development of IPE varies from person to person, it is conventionally indefinite and fuzzy. This paper applies fuzzy sets to analyse the government officials’ social consciousness on the IPE basis.展开更多
The authors use numerical model integral products in a third level forecast of synthetically multi-level analog forecast technology.This is one of the strongest points of this study,which also includes the re-ducing m...The authors use numerical model integral products in a third level forecast of synthetically multi-level analog forecast technology.This is one of the strongest points of this study,which also includes the re-ducing mean vacant-forecast rate method,which pos-sesses many advantages with regard to filtering the analog term.Moreover,the similitude degree between samples is assessed using a combination of meteorological elements,which works better than that described using a single element in earlier analog forecast studies.Based on these techniques,the authors apply the model output,air sounding,surface observation and weather map data from 1990 to 2002 to perform an analog experiment of the quasi-stationary front rainstorm.The most important re-sults are as follows:(1) The forecast successful index is 0.36,and was improved after the forecast model was re-vised.(2) The forecast precise rate (0.59) and the lost-forecast rate (0.33) are also better than those of other methods.(3) Based on the model output data,the syn-thetically multilevel analog forecast technology can pro-duce more accurate forecasts of a quasi-stationary front rainstorm.(4) Optimal analog elements reveal that trig-gering mechanisms are located in the lower troposphere while upper level systems are more important in main-taining the phase of the rainstorm.These variables should be first taken into account in operational forecasts of the quasi-stationary front rainstorm.(5) In addition,experi-ments reveal that the position of the key zone is mainly decided by the position of the system causing the heavy rainfall.展开更多
Xu deep volcanic gas reservoir is typical of complex lithology, severe inhomogeneity, big difficulty to extract. Pressure sensitivity always exists in gas reservoirs. Prorating production is too high or low, causing p...Xu deep volcanic gas reservoir is typical of complex lithology, severe inhomogeneity, big difficulty to extract. Pressure sensitivity always exists in gas reservoirs. Prorating production is too high or low, causing problems, as for the energy loss, reservoir damage, bottom effusion, thus lowing the gas productivity and affecting development benefit. So it have to research on a new reasonably production proration method considering multi influential factors. It is a reasonably production proration method considering multi influential factors in Xu gas reservoir, with guidelines such as capacity use, pressure draw down, gas recovery rate, water out and throughout water data is reasonably, so we can long term use it to guide gas field exploitation.展开更多
Long Tan Hydroelectric Station is planned to be built in the middle reaches of Hong Shui River between the Guongxi Zhuang Autonomous Region and Guizhou Province where the terrain is complicated and the traffic is unco...Long Tan Hydroelectric Station is planned to be built in the middle reaches of Hong Shui River between the Guongxi Zhuang Autonomous Region and Guizhou Province where the terrain is complicated and the traffic is unconvenient. In order to speed up engineering design, the synthetical remote sensing survey and mapping had been made展开更多
In order to realize the impersonality, justness, impartiality and rationality in the awarding work of science ＆ technology, it is necessary to establish an evaluating model to make the evaluating course numeric as we...In order to realize the impersonality, justness, impartiality and rationality in the awarding work of science ＆ technology, it is necessary to establish an evaluating model to make the evaluating course numeric as well as a complete system of evaluating indexes. The theory of fuzzy mathematics is adopted in this paper to establish a multilevel fuzzy synthetical model to quantitate the evaluating index system for science ＆ technology awarding and to provide the scientific decision-making basis for science ＆ technology awarding.展开更多
Study on the evaluation system for multi-source image fusion is an important and necessary part of image fusion. Qualitative evaluation indexes and quantitative evaluation indexes were studied. A series of new concept...Study on the evaluation system for multi-source image fusion is an important and necessary part of image fusion. Qualitative evaluation indexes and quantitative evaluation indexes were studied. A series of new concepts, such as independent single evaluation index, union single evaluation index, synthetic evaluation index were proposed. Based on these concepts, synthetic evaluation system for digital image fusion was formed. The experiments with the wavelet fusion method, which was applied to fuse the multi-spectral image and panchromatic remote sensing image, the IR image and visible image, the CT and MRI image, and the multi-focus images show that it is an objective, uniform and effective quantitative method for image fusion evaluation.展开更多
An anion-exchange chromatography method combined solid phase extraction （SPE） was developed for the simultaneous analysis of glycolate acid （GL）, monochloroacetic acid （MCA） and dichloroacetic acid （DCA） in sy...An anion-exchange chromatography method combined solid phase extraction （SPE） was developed for the simultaneous analysis of glycolate acid （GL）, monochloroacetic acid （MCA） and dichloroacetic acid （DCA） in synthetical betaine products. The analytes and unknown anionic impurities were well separated on a Metrosep A supp5 anion-exchange column （150 mm×4 mm） with 2.0 mmol/L Na2CO3＋2.0 mmol/L NaHCO3 solution as eluent. Suppressed conductivity detection was used. A strong cation exchange （SCX） solid phase extraction （SPE） cartridge was used to reduce the concentration of matrix betaine and a Cleanert IC-Ag pretreatment cartridge was used to remove high Cl- concentration. The detection limits of GL, MCA and DCA were 0.09, 0.017 and 0.05 μg/L, respectively. The relative standard deviations （RSDs） of the retention times and peak areas were less than 0.09% and 0.49%, respectively. The recoveries of the three analytes were between 90.6% and 100.8%. The analytical results showed that GL and DCA were present in high concentration and no MCA was found when the proposed ion chromatography method was applied to three synthetical betaine samples. The proposed method is simple, sensitive and timesaving, and is also suitable for routine analysis in quality control of synthetical betaine products.展开更多
A growing global population and the increasing prevalence of diet-related health issues such as“hidden hunger”,obesity,hypertension,and diabetes necessitate a fundamental rethinking of crop design and breeding.Synth...A growing global population and the increasing prevalence of diet-related health issues such as“hidden hunger”,obesity,hypertension,and diabetes necessitate a fundamental rethinking of crop design and breeding.Synthetic metabolic engineering offers a method to modify and redesign metabolic pathways to increase the nutritional value of crops.We summarize recent advances in the biofortification of key nutrients including provitamin A,vitamin C,vitamin B9,iron,zinc,anthocyanins,flavonoids,and unsaturated fatty acids.We discuss the potential of multi-gene stacking,gene editing,enzyme engineering,and artificial intelligence in synthetic metabolic engineering.We propose future research directions and potential solutions centered on leveraging AI-driven systems biology,precision gene editing,enzyme engineering,agrobacterium-mediated genotype-independent transformation,and modular metabolic engineering strategies to develop next-generation nutritionally enhanced super crops and transform global food systems.展开更多
In light of the pressing global challenges of climate change,declining crop resilience,and hidden hunger,it is imperative to overcome the limitations of conventional crop breeding to enhance both the nutritional quali...In light of the pressing global challenges of climate change,declining crop resilience,and hidden hunger,it is imperative to overcome the limitations of conventional crop breeding to enhance both the nutritional quality and stress tolerance of crops.Synthetic metabolic engineering presents innovative strategies for the precision modification and de novo design of metabolic pathways.This approach generally encompasses three essential steps:identifying key metabolites through metabolomics,integrating multi-omics technologies to investigate the synthesis and regulation of these metabolites,and utilizing gene editing or de novo design to modify crop metabolic pathways associated with desirable agronomic traits.This review underscores the vital role of plant metabolite diversity in enhancing crop nutritional quality and stress resilience.Integrated multi-omics analyses facilitate the metabolic engineering by identifying key genes,transporters,and transcription factors that regulate metabolite biosynthesis.Precision modification strategies employ genome editing tools to reprogram endogenous metabolic networks,while de novo design reconstructs metabolic pathways through the introduction of exogenous biological elements—thereby both approaches enable the targeted enhancement of desired traits.These strategies have been effectively implemented in major food crops.However,simultaneously enhancing nutritional quality and stress resilience remains challenging due to inherent trade-offs and resource competition in distinct metabolic pathways within plants.Future research should integrate AI-driven predictive models with multi-omics datasets to decipher dynamic metabolic homeostasis and engineer climate-smart crops that maximize yield while preserving quality and environmental adaptability.展开更多
Cotton production faces significant challenges from insect pests,with chemical pesticide use becoming increasingly limited by resistance and environmental concerns.This study explores the potential use of caffeine,a n...Cotton production faces significant challenges from insect pests,with chemical pesticide use becoming increasingly limited by resistance and environmental concerns.This study explores the potential use of caffeine,a natural plant alkaloid,as an environmentally friendly insect resistance strategy in cotton.Exogenous caffeine application demonstrated potent insecticidal effects against cotton bollworm(Helicoverpa armigera)larvae,with concentrations≥2 mg mL−1 causing near-complete feeding cessation and up to 70%larval mortality.Building on this,we engineered transgenic cotton(Gossypium hirsutum cv.Jin668)for heterologous caffeine biosynthesis by introducing three key N-methyltransferase genes(CaXMT1,CaMXMT1,CaDXMT1)by multiple gene transformation.Transgenic lines expressing all three genes showed remarkable caffeine accumulation(up to 3.59 mg g−1 dry weight),whereas two-gene combinations exhibited wild-type-level production.Feeding preference assays revealed that caffeine-enriched cotton strongly deterred feeding by H.armigera.Non-choice feeding trials demonstrated reduced leaf consumption and reduced larval growth in H.armigera fed on caffeine-producing cotton.The study highlights the effectiveness of synthetic biology approaches using the TGSII-UNiE multigene stacking system,despite challenges in transgene stability.This work advances plant-derived insect resistance research and provides a sustainable framework for reducing chemical pesticide reliance in cotton production,while underscoring unique potential of cotton as a synthetic biology platform for secondary metabolite engineering.展开更多
Betalain,an economically valuable water-soluble natural plant pigment,is prized for its strong antioxidant activity,making it popular as a dietary supplement and a visual marker for plant transformation.However,market...Betalain,an economically valuable water-soluble natural plant pigment,is prized for its strong antioxidant activity,making it popular as a dietary supplement and a visual marker for plant transformation.However,market demand significantly outstrips current production capacity.This study reports the development of an efficient push-and-pull multigene strategy based on polycistronic expression and metabolic flux regulation to enhance betalain biosynthesis in transgenic maize(Zea mays L.)endosperm.We engineered a novel enhanced RUBY(eRUBY)system derived from the original polycistronic RUBY construct(CYP76AD1P2ADODA1P2ADOPA5GT unit,abbreviated CDG)by introducing arogenate dehydrogenase(ADHα)to increase the L-tyrosine substrate supply.All the genes were driven by the endosperm-specific promoter.Fusion of ADHαinto a single polycistronic eRUBY construct(CDGA)produced significantly higher betanin(6.88 mg g−1 dry weight)and isobetanin(1.81 mg g−1 dry weight)levels than in CDG+A,which stacked the ADHαcassette independently with CDG.The high betalain accumulation in CDGA lines(which also exhibited higher transgene copy number)resulted in a 2.85–7.58-fold improvement in endosperm antioxidant capacity compared to WT(versus 2.48–2.80-fold in CDG+A).Importantly,transgenic plants maintained a normal phenotype.Transcriptome and metabolome analyses further indicated that metabolism of phenylalanine,alanine,aspartate,and glutamate contributes to betalain production.Hybridization with sweet corn successfully created a high-sugar eRUBY maize variety.Collectively,these results demonstrate the successful development of a novel maize germplasm with significantly enhanced nutritional value through high betalain accumulation.展开更多
Plants produce a vast array of specialized metabolites that serve as essential defenses against herbivores and pathogens.However,the capacity to produce these compounds differs substantially among plant species and is...Plants produce a vast array of specialized metabolites that serve as essential defenses against herbivores and pathogens.However,the capacity to produce these compounds differs substantially among plant species and is frequently diminished during domestication.Advances in synthetic metabolic engineering enable efficient elucidation and engineering of plant specialized metabolic pathways active in crop pest and pathogen resistance.This review summarizes strategies and workflows for selecting defensive metabolic pathways,identifying candidate biosynthetic genes,and rewiring native or introducing heterologous pathways to enhance crop resistance to pests and pathogens.Strategies include weighted gene co-expression network construction,biosynthetic gene cluster scanning,and metabolite genome-wide association studies for pathway discovery,as well as transcriptional reprogramming,enzyme activity optimization,and transporter deployment for pathway engineering.We further discuss challenges in using synthetic metabolic engineering to enhance crop resistance and highlight the potential of artificial intelligence in addressing them.展开更多
Given the broad applicability of carbazole structural moieties in materials science and medicinal chemistry,significant efforts have been devoted to developing efficient synthetic catalytic methodologies to access thi...Given the broad applicability of carbazole structural moieties in materials science and medicinal chemistry,significant efforts have been devoted to developing efficient synthetic catalytic methodologies to access this valuable scaffold.Catalyzed direct Csp^(2)-H functionalization provides an effective and costefficient approach to synthesizing carbazoles from simple and readily available starting materials,ensuring a promising path characterized by excellent atom and step economy.This review highlights the substantial progress made in the last 10 years in advancing catalytic Csp^(2)-H functionalization techniques for synthesizing carbazoles.展开更多
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
1.Introduction Crop breeding is transitioning to engineering by synthetic biology.Conventional breeding,constrained by limited genetic variation and lengthy development cycles,cannot meet the challenges of micronutrie...1.Introduction Crop breeding is transitioning to engineering by synthetic biology.Conventional breeding,constrained by limited genetic variation and lengthy development cycles,cannot meet the challenges of micronutrient malnutrition and yield reductions from climate change with sufficient speed or precision[1].Consequently,agriculture is transitioning from selection-based breeding to designbased engineering.Synthetic biology enables the precision modification of metabolic pathways and the construction of novel trait combinations[1,2].This special issue,Synthetic Biology for Crop Improvement,brings together 26 articles that showcase the field’s transition from laboratory curiosity to field-validated agricultural technology.The collection spans 13 plant species,from staple grains and major industrial crops to horticultural and medicinal plants,demonstrating the universal applicability of metabolic engineering.These studies reveal maturation toward field readiness:independent groups achieving reproducible results in identical pathways,greenhouse concepts advancing to multi-season field trials,and engineered traits delivering measurable agronomic value.This progression answers the central question in crop synthetic biology,shifting the paradigm from asking“can it work?”to demonstrating“how it works,and here are the yields”.This transformation is grounded in understanding and manipulating plant metabolism at molecular resolution[3].展开更多
Bone fractures represent a significant global healthcare burden.Although fractures typically heal on their own,some fail to regenerate properly,leading to nonunion,a condition that causes prolonged disability,morbidit...Bone fractures represent a significant global healthcare burden.Although fractures typically heal on their own,some fail to regenerate properly,leading to nonunion,a condition that causes prolonged disability,morbidity,and mortality.The challenge of treating nonunion fractures is further complicated in patients with underlying bone disorders where systemic and local factors impair bone healing.Traditional treatment approaches,including autografts,allografts,xenografts,and synthetic biomaterials,face limitations such as donor site pain,immune rejection,and insufficient mechanical strength,underscoring the need for alternative strategies.Biologic therapies have emerged as promising tools to enhance bone regeneration by leveraging the body’s natural healing processes.This review explores the critical role of conventional and emerging biologics in fracture healing.We categorize biologic therapies into protein-based treatments,gene and transcript therapies,small molecules,peptides,and cell-based therapies,highlighting their mechanisms of action,advantages,and clinical relevance.Finally,we examine the potential applications of biologics in treating fractures associated with bone disorders such as osteoporosis,osteogenesis imperfecta,rickets,osteomalacia,Paget’s disease,and bone tumors.By integrating biologic therapies with existing biomaterial-based strategies,these innovative approaches have the potential to transform clinical management and improve outcomes for patients with difficult-to-heal fractures.展开更多
基金The National Natural Science Foundation of China(No50608017,50538020)
文摘Based on the theory of pattern recognition, the concept of closeness degree between fuzzy sets is brought into the condition assessment of long span bridges. Using the fuzzy analytic hierarchy process （FAHP）, a mathematical model of a multi-objective assessment of a long span suspension bridge is set up. An example is given to show the procedure in the synthetical condition assessment of the Runyang Suspension Bridge, which includes the hierarchical division, the definition of factor weights and fuzzy membership functions, and the calculation of closeness degrees, etc. The assessment combines both the data from the health monitoring system and the manual tests. The classification of evaluation items as well as the calculation of deterministic and nondeterministic items is presented. Compared with the traditional method of point rating, this method can better describe the discreteness of monitoring data and the fuzziness in the condition assessment.
基金supported by National Natural Science Foundation of China(Grant No.51005017)
文摘Now the optimization strategies for power distribution are researched widely, and most of them are aiming to the optimal fuel economy and the driving cycle must be preknown. Thus if the actual driving condition deviates from the scheduled driving cycle, the effect of optimal results will be declined greatly. Therefore, the instantaneous optimization strategy carried out on-line is studied in this paper. The power split path and the transmission efficiency are analyzed based on a special power-split scheme and the efficiency models of the power transmitting components are established. The synthetical efficiency optimization model is established for enhancing the transmission efficiency and the fuel economy. The identification of the synthetical efficiency as the optimization objective and the constrain group are discussed emphatically. The optimization is calculated by the adaptive simulated annealing （ASA） algorithm and realized on-line by the radial basis function （RBF）-based similar models. The optimization for power distribution of the hybrid vehicle in an actual driving condition is carried out and the road test results are presented. The test results indicate that the synthetical efficiency optimization method can enhance the transmission efficiency and the fuel economy of the power-split hybrid electric vehicle （HEV） observably. Compared to the rules-based strategy the optimization strategy is optimal and achieves the approximate global optimization solution for the power distribution. The synthetical efficiency optimization solved by ASA algorithm can give attentions to both optimization quality and calculation efficiency, thus it has good application foreground for the power distribution of power-split HEV.
文摘Due to the complexity of thickness and shape synthetical adjustment system and the difficulties to build a mathematical model,a thickness and shape synthetical adjustment scheme on DC mill based on dynamic nerve-fuzzy control was put forward,and a self-organizing fuzzy control model was established.The structure of the network can be optimized dynamically.In the course of studying,the network can automatically adjust its structure based on the specific questions and make its structure the optimal.The input and output of the network are fuzzy sets,and the trained network can complete the composite relation,the fuzzy inference.For decreasing the off-line training time of BP network,the fuzzy sets are encoded.The simulation results indicate that the self-organizing fuzzy control based on dynamic neural network is better than traditional decoupling PID control.
文摘Government policy is the key to the development of the individual and private economy (IPE).In the making of a policy, the social consciousness of government officials is one of the important factors to affect the policy made. Since the social consciousness on the development of IPE varies from person to person, it is conventionally indefinite and fuzzy. This paper applies fuzzy sets to analyse the government officials’ social consciousness on the IPE basis.
基金financially supported by the National Basic Research Program of China (Grant No. 2009CB421 401)
文摘The authors use numerical model integral products in a third level forecast of synthetically multi-level analog forecast technology.This is one of the strongest points of this study,which also includes the re-ducing mean vacant-forecast rate method,which pos-sesses many advantages with regard to filtering the analog term.Moreover,the similitude degree between samples is assessed using a combination of meteorological elements,which works better than that described using a single element in earlier analog forecast studies.Based on these techniques,the authors apply the model output,air sounding,surface observation and weather map data from 1990 to 2002 to perform an analog experiment of the quasi-stationary front rainstorm.The most important re-sults are as follows:(1) The forecast successful index is 0.36,and was improved after the forecast model was re-vised.(2) The forecast precise rate (0.59) and the lost-forecast rate (0.33) are also better than those of other methods.(3) Based on the model output data,the syn-thetically multilevel analog forecast technology can pro-duce more accurate forecasts of a quasi-stationary front rainstorm.(4) Optimal analog elements reveal that trig-gering mechanisms are located in the lower troposphere while upper level systems are more important in main-taining the phase of the rainstorm.These variables should be first taken into account in operational forecasts of the quasi-stationary front rainstorm.(5) In addition,experi-ments reveal that the position of the key zone is mainly decided by the position of the system causing the heavy rainfall.
文摘Xu deep volcanic gas reservoir is typical of complex lithology, severe inhomogeneity, big difficulty to extract. Pressure sensitivity always exists in gas reservoirs. Prorating production is too high or low, causing problems, as for the energy loss, reservoir damage, bottom effusion, thus lowing the gas productivity and affecting development benefit. So it have to research on a new reasonably production proration method considering multi influential factors. It is a reasonably production proration method considering multi influential factors in Xu gas reservoir, with guidelines such as capacity use, pressure draw down, gas recovery rate, water out and throughout water data is reasonably, so we can long term use it to guide gas field exploitation.
文摘Long Tan Hydroelectric Station is planned to be built in the middle reaches of Hong Shui River between the Guongxi Zhuang Autonomous Region and Guizhou Province where the terrain is complicated and the traffic is unconvenient. In order to speed up engineering design, the synthetical remote sensing survey and mapping had been made
文摘In order to realize the impersonality, justness, impartiality and rationality in the awarding work of science ＆ technology, it is necessary to establish an evaluating model to make the evaluating course numeric as well as a complete system of evaluating indexes. The theory of fuzzy mathematics is adopted in this paper to establish a multilevel fuzzy synthetical model to quantitate the evaluating index system for science ＆ technology awarding and to provide the scientific decision-making basis for science ＆ technology awarding.
基金National Natural Science Foundation ofChina (No. 60375008) Shanghai EXPOSpecial Project ( No.2004BA908B07 )Shanghai NRC International CooperationProject (No.05SN07118)
文摘Study on the evaluation system for multi-source image fusion is an important and necessary part of image fusion. Qualitative evaluation indexes and quantitative evaluation indexes were studied. A series of new concepts, such as independent single evaluation index, union single evaluation index, synthetic evaluation index were proposed. Based on these concepts, synthetic evaluation system for digital image fusion was formed. The experiments with the wavelet fusion method, which was applied to fuse the multi-spectral image and panchromatic remote sensing image, the IR image and visible image, the CT and MRI image, and the multi-focus images show that it is an objective, uniform and effective quantitative method for image fusion evaluation.
文摘An anion-exchange chromatography method combined solid phase extraction （SPE） was developed for the simultaneous analysis of glycolate acid （GL）, monochloroacetic acid （MCA） and dichloroacetic acid （DCA） in synthetical betaine products. The analytes and unknown anionic impurities were well separated on a Metrosep A supp5 anion-exchange column （150 mm×4 mm） with 2.0 mmol/L Na2CO3＋2.0 mmol/L NaHCO3 solution as eluent. Suppressed conductivity detection was used. A strong cation exchange （SCX） solid phase extraction （SPE） cartridge was used to reduce the concentration of matrix betaine and a Cleanert IC-Ag pretreatment cartridge was used to remove high Cl- concentration. The detection limits of GL, MCA and DCA were 0.09, 0.017 and 0.05 μg/L, respectively. The relative standard deviations （RSDs） of the retention times and peak areas were less than 0.09% and 0.49%, respectively. The recoveries of the three analytes were between 90.6% and 100.8%. The analytical results showed that GL and DCA were present in high concentration and no MCA was found when the proposed ion chromatography method was applied to three synthetical betaine samples. The proposed method is simple, sensitive and timesaving, and is also suitable for routine analysis in quality control of synthetical betaine products.
基金supported by grants from the Guangxi Science and Technology Major Project(GKAA24206023)the Biological Breeding-National Science and Technology Major Project(2024ZD04077)+2 种基金the National Natural Science Foundation of China(32272120)the National Key Research and Development Program of China(2024YFF1000800)the Guangdong Basic Research Center of Excellence for Precise Breeding of Future Crops Major Project(FCBRCE-202502,FCBRCE-202504).
文摘A growing global population and the increasing prevalence of diet-related health issues such as“hidden hunger”,obesity,hypertension,and diabetes necessitate a fundamental rethinking of crop design and breeding.Synthetic metabolic engineering offers a method to modify and redesign metabolic pathways to increase the nutritional value of crops.We summarize recent advances in the biofortification of key nutrients including provitamin A,vitamin C,vitamin B9,iron,zinc,anthocyanins,flavonoids,and unsaturated fatty acids.We discuss the potential of multi-gene stacking,gene editing,enzyme engineering,and artificial intelligence in synthetic metabolic engineering.We propose future research directions and potential solutions centered on leveraging AI-driven systems biology,precision gene editing,enzyme engineering,agrobacterium-mediated genotype-independent transformation,and modular metabolic engineering strategies to develop next-generation nutritionally enhanced super crops and transform global food systems.
基金supported by the Project of Sanya Yazhou Bay Science and Technology City (SKJC-JYRC-2024-26)the National Natural Science Foundation of China (32460072)+4 种基金Hainan Provincial Natural Science Foundation of China (323RC421)the Hainan Province Science and Technology Special Fund (ZDYF2022XDNY144)the Hainan Provincial Academician Innovation Platform Project (HDYSZX-202004)the Collaborative Innovation Center of Nanfan and High-Efficiency Tropical Agriculture, Hainan University (XTCX2022NYB06)Hainan Postdoctoral Research Grant Project
文摘In light of the pressing global challenges of climate change,declining crop resilience,and hidden hunger,it is imperative to overcome the limitations of conventional crop breeding to enhance both the nutritional quality and stress tolerance of crops.Synthetic metabolic engineering presents innovative strategies for the precision modification and de novo design of metabolic pathways.This approach generally encompasses three essential steps:identifying key metabolites through metabolomics,integrating multi-omics technologies to investigate the synthesis and regulation of these metabolites,and utilizing gene editing or de novo design to modify crop metabolic pathways associated with desirable agronomic traits.This review underscores the vital role of plant metabolite diversity in enhancing crop nutritional quality and stress resilience.Integrated multi-omics analyses facilitate the metabolic engineering by identifying key genes,transporters,and transcription factors that regulate metabolite biosynthesis.Precision modification strategies employ genome editing tools to reprogram endogenous metabolic networks,while de novo design reconstructs metabolic pathways through the introduction of exogenous biological elements—thereby both approaches enable the targeted enhancement of desired traits.These strategies have been effectively implemented in major food crops.However,simultaneously enhancing nutritional quality and stress resilience remains challenging due to inherent trade-offs and resource competition in distinct metabolic pathways within plants.Future research should integrate AI-driven predictive models with multi-omics datasets to decipher dynamic metabolic homeostasis and engineer climate-smart crops that maximize yield while preserving quality and environmental adaptability.
基金supported by the National Natural Science Foundation of China (32325039)
文摘Cotton production faces significant challenges from insect pests,with chemical pesticide use becoming increasingly limited by resistance and environmental concerns.This study explores the potential use of caffeine,a natural plant alkaloid,as an environmentally friendly insect resistance strategy in cotton.Exogenous caffeine application demonstrated potent insecticidal effects against cotton bollworm(Helicoverpa armigera)larvae,with concentrations≥2 mg mL−1 causing near-complete feeding cessation and up to 70%larval mortality.Building on this,we engineered transgenic cotton(Gossypium hirsutum cv.Jin668)for heterologous caffeine biosynthesis by introducing three key N-methyltransferase genes(CaXMT1,CaMXMT1,CaDXMT1)by multiple gene transformation.Transgenic lines expressing all three genes showed remarkable caffeine accumulation(up to 3.59 mg g−1 dry weight),whereas two-gene combinations exhibited wild-type-level production.Feeding preference assays revealed that caffeine-enriched cotton strongly deterred feeding by H.armigera.Non-choice feeding trials demonstrated reduced leaf consumption and reduced larval growth in H.armigera fed on caffeine-producing cotton.The study highlights the effectiveness of synthetic biology approaches using the TGSII-UNiE multigene stacking system,despite challenges in transgene stability.This work advances plant-derived insect resistance research and provides a sustainable framework for reducing chemical pesticide reliance in cotton production,while underscoring unique potential of cotton as a synthetic biology platform for secondary metabolite engineering.
基金supported by grants from the Biological Breeding-National Science and Technology Major Project(2024ZD04077)the Invigorate the Seed Industry of Guangdong Province(2024-NPY-00-044)+3 种基金the National Natural Science Foundation of China(32272120)the Guangxi Science and Technology Major Project(GKAA24206023)the National Key Research and Development Program of China(2024YFF1000800)the Guangdong Basic Research Center of Excellence for Precise Breeding of Future Crops Major Project(FCBRCE-202502,FCBRCE-202504).
文摘Betalain,an economically valuable water-soluble natural plant pigment,is prized for its strong antioxidant activity,making it popular as a dietary supplement and a visual marker for plant transformation.However,market demand significantly outstrips current production capacity.This study reports the development of an efficient push-and-pull multigene strategy based on polycistronic expression and metabolic flux regulation to enhance betalain biosynthesis in transgenic maize(Zea mays L.)endosperm.We engineered a novel enhanced RUBY(eRUBY)system derived from the original polycistronic RUBY construct(CYP76AD1P2ADODA1P2ADOPA5GT unit,abbreviated CDG)by introducing arogenate dehydrogenase(ADHα)to increase the L-tyrosine substrate supply.All the genes were driven by the endosperm-specific promoter.Fusion of ADHαinto a single polycistronic eRUBY construct(CDGA)produced significantly higher betanin(6.88 mg g−1 dry weight)and isobetanin(1.81 mg g−1 dry weight)levels than in CDG+A,which stacked the ADHαcassette independently with CDG.The high betalain accumulation in CDGA lines(which also exhibited higher transgene copy number)resulted in a 2.85–7.58-fold improvement in endosperm antioxidant capacity compared to WT(versus 2.48–2.80-fold in CDG+A).Importantly,transgenic plants maintained a normal phenotype.Transcriptome and metabolome analyses further indicated that metabolism of phenylalanine,alanine,aspartate,and glutamate contributes to betalain production.Hybridization with sweet corn successfully created a high-sugar eRUBY maize variety.Collectively,these results demonstrate the successful development of a novel maize germplasm with significantly enhanced nutritional value through high betalain accumulation.
基金supported by the National Natural Science Foundation of China (32402306)the Agricultural Science and Technology Innovation Program of the Chinese Academy of Agricultural Sciences+1 种基金National Key Research and Development Program of China (2022YFE0203300)the China-Uruguay Joint Laboratory on Soybean Research and Innovation
文摘Plants produce a vast array of specialized metabolites that serve as essential defenses against herbivores and pathogens.However,the capacity to produce these compounds differs substantially among plant species and is frequently diminished during domestication.Advances in synthetic metabolic engineering enable efficient elucidation and engineering of plant specialized metabolic pathways active in crop pest and pathogen resistance.This review summarizes strategies and workflows for selecting defensive metabolic pathways,identifying candidate biosynthetic genes,and rewiring native or introducing heterologous pathways to enhance crop resistance to pests and pathogens.Strategies include weighted gene co-expression network construction,biosynthetic gene cluster scanning,and metabolite genome-wide association studies for pathway discovery,as well as transcriptional reprogramming,enzyme activity optimization,and transporter deployment for pathway engineering.We further discuss challenges in using synthetic metabolic engineering to enhance crop resistance and highlight the potential of artificial intelligence in addressing them.
基金support and funding by the European Union-Next Generation EU under the Italian Ministry of University and Research (MUR) National Innovation Ecosystem (No.ECS00000041-VITALITY and also “Ecosistema TECH4YOU-(Spoke 3-Goal 3.5)MUR is thanked for PRIN-PNRR 2022 project "P2022XKWH7-Circular Waste+3 种基金The University of Perugia is acknowledged for financial support to the university project “Fondo Ricerca di Ateneo,edizione 2022”The National Ph D program in Catalysis coordinated by the University of Perugia is also thankedthe financial supports of key research and development and technology transfer projects of Inner Mongolia Autonomous Region (No.2025KJHZ0008)major special projects of science and technology of Ordos (No.2022EEDSKJZDZX003)。
文摘Given the broad applicability of carbazole structural moieties in materials science and medicinal chemistry,significant efforts have been devoted to developing efficient synthetic catalytic methodologies to access this valuable scaffold.Catalyzed direct Csp^(2)-H functionalization provides an effective and costefficient approach to synthesizing carbazoles from simple and readily available starting materials,ensuring a promising path characterized by excellent atom and step economy.This review highlights the substantial progress made in the last 10 years in advancing catalytic Csp^(2)-H functionalization techniques for synthesizing carbazoles.
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1.Introduction Crop breeding is transitioning to engineering by synthetic biology.Conventional breeding,constrained by limited genetic variation and lengthy development cycles,cannot meet the challenges of micronutrient malnutrition and yield reductions from climate change with sufficient speed or precision[1].Consequently,agriculture is transitioning from selection-based breeding to designbased engineering.Synthetic biology enables the precision modification of metabolic pathways and the construction of novel trait combinations[1,2].This special issue,Synthetic Biology for Crop Improvement,brings together 26 articles that showcase the field’s transition from laboratory curiosity to field-validated agricultural technology.The collection spans 13 plant species,from staple grains and major industrial crops to horticultural and medicinal plants,demonstrating the universal applicability of metabolic engineering.These studies reveal maturation toward field readiness:independent groups achieving reproducible results in identical pathways,greenhouse concepts advancing to multi-season field trials,and engineered traits delivering measurable agronomic value.This progression answers the central question in crop synthetic biology,shifting the paradigm from asking“can it work?”to demonstrating“how it works,and here are the yields”.This transformation is grounded in understanding and manipulating plant metabolism at molecular resolution[3].
基金performed as part of the cmRNAbone project funded by the European Union’s Horizon 2020 research and innovation program under the Grant Agreement No 874790。
文摘Bone fractures represent a significant global healthcare burden.Although fractures typically heal on their own,some fail to regenerate properly,leading to nonunion,a condition that causes prolonged disability,morbidity,and mortality.The challenge of treating nonunion fractures is further complicated in patients with underlying bone disorders where systemic and local factors impair bone healing.Traditional treatment approaches,including autografts,allografts,xenografts,and synthetic biomaterials,face limitations such as donor site pain,immune rejection,and insufficient mechanical strength,underscoring the need for alternative strategies.Biologic therapies have emerged as promising tools to enhance bone regeneration by leveraging the body’s natural healing processes.This review explores the critical role of conventional and emerging biologics in fracture healing.We categorize biologic therapies into protein-based treatments,gene and transcript therapies,small molecules,peptides,and cell-based therapies,highlighting their mechanisms of action,advantages,and clinical relevance.Finally,we examine the potential applications of biologics in treating fractures associated with bone disorders such as osteoporosis,osteogenesis imperfecta,rickets,osteomalacia,Paget’s disease,and bone tumors.By integrating biologic therapies with existing biomaterial-based strategies,these innovative approaches have the potential to transform clinical management and improve outcomes for patients with difficult-to-heal fractures.
