Developing machine learning frameworks with predictive power,interpretability,and transferability is crucial,yet it faces challenges in the field of electrocatalysis.To achieve this,we employed rigorous feature engine...Developing machine learning frameworks with predictive power,interpretability,and transferability is crucial,yet it faces challenges in the field of electrocatalysis.To achieve this,we employed rigorous feature engineering to establish a finely tuned gradient boosting regressor(GBR)model,which adeptly captures the physical complexity from feature space to target variables.We demonstrated that environmental electron effects and atomic number significantly govern the success of the mapping process via global and local explanations.The finely tuned GBR model exhibits exceptional robustness in predicting CO adsorption energies(R_(ave)^(2)=0.937,RMSE=0.153 eV).Moreover,the model demonstrated remarkable transfer learning ability,showing excellent predictive power for OH,NO,and N_(2) adsorption.Importantly,the GBR model exhibits exceptional predictive capability across an extensive search space,thereby demonstrating profound adaptability and versatility.Our research framework significantly enhances the interpretability and transferability of machine learning in electrocatalysis,offering vital insights for further advancements.展开更多
Transfer-based Adversarial Attacks(TAAs)can deceive a victim model even without prior knowledge.This is achieved by leveraging the property of adversarial examples.That is,when generated from a surrogate model,they re...Transfer-based Adversarial Attacks(TAAs)can deceive a victim model even without prior knowledge.This is achieved by leveraging the property of adversarial examples.That is,when generated from a surrogate model,they retain their features if applied to other models due to their good transferability.However,adversarial examples often exhibit overfitting,as they are tailored to exploit the particular architecture and feature representation of source models.Consequently,when attempting black-box transfer attacks on different target models,their effectiveness is decreased.To solve this problem,this study proposes an approach based on a Regularized Constrained Feature Layer(RCFL).The proposed method first uses regularization constraints to attenuate the initial examples of low-frequency components.Perturbations are then added to a pre-specified layer of the source model using the back-propagation technique,in order to modify the original adversarial examples.Afterward,a regularized loss function is used to enhance the black-box transferability between different target models.The proposed method is finally tested on the ImageNet,CIFAR-100,and Stanford Car datasets with various target models,The obtained results demonstrate that it achieves a significantly higher transfer-based adversarial attack success rate compared with baseline techniques.展开更多
Artificial intelligence has potential for forecasting reactor conditions in the nuclear industry.Owing to economic and security concerns,a common method is to train data generated by simulators.However,achieving a sat...Artificial intelligence has potential for forecasting reactor conditions in the nuclear industry.Owing to economic and security concerns,a common method is to train data generated by simulators.However,achieving a satisfactory performance in practical applications is difficult because simulators imperfectly emulate reality.To bridge this gap,we propose a novel framework called simulation-to-reality domain adaptation(SRDA)for forecasting the operating parameters of nuclear reactors.The SRDA model employs a transformer-based feature extractor to capture dynamic characteristics and temporal dependencies.A parameter predictor with an improved logarithmic loss function is specifically designed to adapt to varying reactor powers.To fuse prior reactor knowledge from simulations with reality,the domain discriminator utilizes an adversarial strategy to ensure the learning of deep domain-invariant features,and the multiple kernel maximum mean discrepancy minimizes their discrepancies.Experiments on neutron fluxes and temperatures from a pressurized water reactor illustrate that the SRDA model surpasses various advanced methods in terms of predictive performance.This study is the first to use domain adaptation for real-world reactor prediction and presents a feasible solution for enhancing the transferability and generalizability of simulated data.展开更多
[Objective] The research aimed to study the transferability of Camellia sinensis EST-SSRs in Theaceae plant.[Method] Seven pairs of EST-SSRs primers which derived from Camellia sinensis EST sequence were used to ampli...[Objective] The research aimed to study the transferability of Camellia sinensis EST-SSRs in Theaceae plant.[Method] Seven pairs of EST-SSRs primers which derived from Camellia sinensis EST sequence were used to amplify the nineteen materials of Theaceae plant.[Result] Five pairs in the seven pairs of EST-SSRs primers could effectively amplify the nineteen tested varieties,and the transferability rate was 71.43%.The amplification rate of Camellia retiacalate FengShanCha,Camellia japouica CaiXia and Camellia retiacalate JuBan was the highest.The amplification rate of Camellia synaptica Sealy and Adinandra sagonica var.wallichiana（oc）Ming was the lowest.Moreover,four pairs in the five pairs of primers which could effectively amplify showed the rich polymorphism whose difference was obvious in the tested materials.[Conclusion] SSR primers which were developed from Camellia sinensis genome had the higher transferability in the different genus and species of Theaceae plant,could be used in the comparative genome research and analysis mark research of Theaceae plant.展开更多
Simple sequence repeat （SSR） or microsatellite marker is a valuable tool for several purposes, such as mapping, fingerprinting, and breeding. In the present study, an intersimple sequence repeat （ISSR）-PCR techniq...Simple sequence repeat （SSR） or microsatellite marker is a valuable tool for several purposes, such as mapping, fingerprinting, and breeding. In the present study, an intersimple sequence repeat （ISSR）-PCR technique was applied for developing SSR markers in non-heading Chinese cabbage （Brassica rapa）. A total of 190 SSRs were obtained. Among these, AG or CT （54.7%） was the most frequent repeat, followed by AC or GT （31.6%） of the microsatellites. The average number of the SSRs length array was 16 and 10 times, respectively. Based on the determined SSR sequences, 143 SSR primer pairs were designed to evaluate their transferabilities among the related species of Brassica. The number of alleles produced per marker averaged 2.91, and the polymorphism information content （PIC） value ranged from 0 to 0.863 with an average of 0.540. Monomorphism was observed in 16 primer pairs. The transferability percentage in CC genome was higher than in BB genome. More loci occurred in the BBCC genome. This result supported the hypothesis that BB genome was divergent from A and C genomes, and AA and CC genomes were relatively close. The polymorphic primers can be exploited for further evolution, fingerprinting, and variety identification.展开更多
Currently development of new marker types has shifted from anonymous DNA fragments to gene-based markers. Simple Sequence Repeats (SSRs) are useful DNA markers in plant genetic research including in peanut. However, d...Currently development of new marker types has shifted from anonymous DNA fragments to gene-based markers. Simple Sequence Repeats (SSRs) are useful DNA markers in plant genetic research including in peanut. However, de novo development of SSRs is expensive and time consuming. Gene-based DNA markers are transferable among related species owing to the conserved nature of genes. In this study transferability of sorghum EST-SSR (SbEST-SSR) markers to peanut was prospected. A set of 411 SbEST-SSR primer pairs were used to amplify peanut genomic DNA extracted from cultivated peanut where 39% of them successfully amplified. A comparison of amplification patterns between sorghum and peanut showed similar banding pattern with majority of transferable SbEST-SSRs. Among these transferable SSR markers, 14% have detected polymorphism among 4 resistant and 4 susceptible peanut lines for rust and late leaf spot diseases. These transferable markers will benefit peanut genome research by not only providing additional DNA markers for population genetic analyses, but also allowing comparative mapping to be possible between peanut and sorghum—a possible monocot-dicot comparison.展开更多
We characterized 14 anonymous nuclear loci from Pinus thunbergii Parl., an important pine species native to Japan. One hundred and twenty-six single nucleotide polymorphisms （SNPs） were identified from these loci, g...We characterized 14 anonymous nuclear loci from Pinus thunbergii Parl., an important pine species native to Japan. One hundred and twenty-six single nucleotide polymorphisms （SNPs） were identified from these loci, giving a frequency of 1 SNP per 51 bp. Nucleotide di- versity （0） ranged from 1.06 × 10^-3 to 11.87 × 10^-3, with all average of 4.99 × 10^-3. Only one locus （mK45） deviated significantly from the Hardy-Weinberg equilibrium. Thirteen of 14 loci were applicable in other pine species. These loci will be useful for nucleotide variation studies and will provide material for SNP-based marker development in P. thun- bergii and related species.展开更多
Glacier mass balance, the difference between accumulation and ablation at the glacier surface, is the direct reflection of the local climate regime. Under global warming, the simulation of glacier mass balance at the ...Glacier mass balance, the difference between accumulation and ablation at the glacier surface, is the direct reflection of the local climate regime. Under global warming, the simulation of glacier mass balance at the regional scale has attracted increasing interests. This study selects Urumqi Glacier No. 1 as the testbed for examining the transferability in space and time of two commonly used glacier mass balance simulation models: i.e., the Degree-Day Model(DDM) and the simplified Energy Balance Model(s EBM). Four experiments were carried out for assessing both models’ temporal and spatial transferability. The results show that the spatial transferability of both the DDM and s EBM is strong, whereas the temporal transferability of the DDM is relatively weak. For all four experiments, the overall simulation effect of the s EBM is better than that of the DDM. At the zone around Equilibrium Line Altitude(ELA), the DDM performed better than the s EBM.Also, the accuracy of parameters, including the lapse rate of air temperature and vertical gradient of precipitation at the glacier surface, is of great significance for improving the spatial transferability of both models.展开更多
The current adversarial attacks against deep learning models have achieved incredible success in the white-box scenario.However,they often exhibit weak transferability in the black-box scenario,especially when attacki...The current adversarial attacks against deep learning models have achieved incredible success in the white-box scenario.However,they often exhibit weak transferability in the black-box scenario,especially when attacking those with defense mechanisms.In this work,we propose a new transfer-based blackbox attack called the channel decomposition attack method(CDAM).It can attack multiple black-box models by enhancing the transferability of the adversarial examples.On the one hand,it tunes the gradient and stabilizes the update direction by decomposing the channels of the input example and calculating the aggregate gradient.On the other hand,it helps to escape from local optima by initializing the data point with random noise.Besides,it could combine with other transfer-based attacks flexibly.Extensive experiments on the standard ImageNet dataset show that our method could significantly improve the transferability of adversarial attacks.Compared with the state-of-the-art method,our approach improves the average success rate from 88.2%to 96.6%when attacking three adversarially trained black-box models,demonstrating the remaining shortcomings of existing deep learning models.展开更多
Transferability of five nuclear microsatellite markers (Jc-16, Jc-31, Jc-32, Jc-35 and Jc-37) that were originally developed for J. communis was tested to J. procera. Jc-31 & Jc-37 showed successful amplifications...Transferability of five nuclear microsatellite markers (Jc-16, Jc-31, Jc-32, Jc-35 and Jc-37) that were originally developed for J. communis was tested to J. procera. Jc-31 & Jc-37 showed successful amplifications and polymorphism in J. procera. Jc-35 which had been reported as polymorphic in J. communis was monomorphic in J. procera while the primer pair for Jc-32 failed to record any amplification. The remaining one primer pair (Jc-16) showed double loci ampli-fication in both J. procera and the control J. communis suggesting further examination of the primer pair and its binding sites. Genetic variation of six Ethiopian J. procera populations: Chilimo, Goba, Menagesha-Suba, Wef-Washa, Yabelo and Ziquala was assessed based on the two polymorphic loci (Jc-31 & Jc-37) in 20 - 24 individuals of each population. From these two loci, a total of 41 alleles could be retrieved. Two populations that are located south east of the Great Rift Valley together harboured 75% of private alleles signifying their deviant geo-ecological zones and suggesting special consideration for conservation. Chilimo, which is at the western margin of Juniper habitat in Ethiopian central highlands scored the highest fixation (FIS = 0.584) entailing lower immigrant genes and hence higher inbreeding. The AMOVA revealed that 97% of the variation resided within the?population while still among population variation was significant展开更多
The rapid development of foundation potentials(FPs)in machine learning interatomic potentials demonstrates the possibility for generalizable learning of the universal potential energy surface.The accuracy of FPs can b...The rapid development of foundation potentials(FPs)in machine learning interatomic potentials demonstrates the possibility for generalizable learning of the universal potential energy surface.The accuracy of FPs can be further improved by bridging the model from lower-fidelity datasets to highfidelity ones.In this work,we analyze the challenge of this transfer learning(TL)problem within the CHGNet framework.We show that significant energy scale shifts and poor correlations between GGA and r^(2)SCAN hinder cross-functional transferability.By benchmarking different TL approaches on the MP-r^(2)SCAN dataset,we demonstrate the importance of elemental energy referencing in the TL of FPs.By comparing the scaling law with and without the pre-training on a low-fidelity dataset,we show that significant data efficiency can still be achieved through TL,even with a target dataset of sub-million structures.We highlight the importance of proper TL and multi-fidelity learning in creating nextgeneration FPs on high-fidelity data.展开更多
Leaf spectroscopy,combined with partial least squares regression(PLSR),is recognized as an efficient and precise tool for measuring plant leaf traits.However,the feasibility of developing a generalizable model remains...Leaf spectroscopy,combined with partial least squares regression(PLSR),is recognized as an efficient and precise tool for measuring plant leaf traits.However,the feasibility of developing a generalizable model remains unclear,primarily due to limited understanding of PLSR model transferability.Here,we collected six key leaf traits along with paired leaf reflectance spectra from 1967 samples of 349 tree species in eight forest sites across China.Using this dataset,we explored the transferability of PLSR models,factors affecting model transferability,and the feasibility of developing generalizable PLSR models for leaf trait prediction.Overall,PLSR models trained at a specific study site demonstrate limited transferability to other study sites.Dissimilarities in plant evolutionary history and environmental conditions between study sites are the primary factors influencing the transferability of PLSR models.Incorporating training data from diverse evolutionary histories and environmental conditions can improve the transferability of PLSR models,achieving accuracy equivalent to that of site-specific models.Our findings provide guidelines for the use of spectroscopy in leaf trait prediction and underscore the urgent need for collaborative efforts to build an open database of leaf traits and reflectance spectra,thereby promoting the development of universal PLSR models for plant leaf trait prediction.展开更多
Safety performance functions(SPFs),or crash-prediction models,have played an important role in identifying the factors contributing to crashes,predicting crash counts and identifying hotspots.Since a great deal of tim...Safety performance functions(SPFs),or crash-prediction models,have played an important role in identifying the factors contributing to crashes,predicting crash counts and identifying hotspots.Since a great deal of time and effort is needed to estimate an SPF,previous studies have sought to determine the transferability of particular SPFs;that is,the extent to which they can be applied to data from other regions.Although many efforts have been made to examine micro-level SPF transferability,few studies have focused on macro-level SPF transferability.There has been little transferability analysis of macro-level SPFs in the international context,especially between western countries.This study therefore evaluates the transferability of SPFs for several states in the USA(Illinois,Florida and Colorado)and for Italy.The SPFs were developed using data from counties in the United States and provincias in Italy,and the results revealed multiple common significant variables between the two countries.Transferability indexes were then calculated between the SPFs.These showed that the Italy SPFs for total crashes and bicycle crashes were transferable to US data after calibration factors were applied,whereas the US SPFs for total and bicycle crashes,with the exception of the Colorado SPF,could not be transferred to the Italian data.On the other hand,none of the pedestrian SPFs developed was transferable to other countries.This paper provides insights into the applicability of macro-level SPFs between the USA and Italy,and shows a good potential for international SPF transferability.Nevertheless,further investigation is needed of SPF transferability between a wider range of countries.展开更多
Fluorescent probes based on intramolecular charge transfer(ICT) have obvious advantages for accurate quantitative analysis.To obtain high-performance ratiometric probes requires distinct photophysical properties durin...Fluorescent probes based on intramolecular charge transfer(ICT) have obvious advantages for accurate quantitative analysis.To obtain high-performance ratiometric probes requires distinct photophysical properties during recognition reaction process,which is closely related to their ICT characteristics.1,8-Naphthalimide is known as a typical fluorophore with desirable ICT property when functionalized with an electron-donating moiety at the para-position of the naphthalene chromophore.Although the photophysical properties of para-substituted 1,8-naphthalimide have been well studied,its meta-substituted counterpart has not been fully evaluated since the meta-position is conventionally thought to be weakly conjugated.Herein,combined experimental and theoretical studies are performed which consistently indicate that stronger charge transfer(CT) is exhibited by the meta-amino substituted 1,8-naphthalimide(m-NH_(2)) compared to the para-amino substituted one(p-NH_(2)).The ratiometric response of fluorescence with significant changes in wavelength and intensity upon acetylation(m-NAc and p-NAc) can be attributed to the larger ICT and stronger-NH_(2) vibrations.This observation is further demonstrated by deuterium oxide experiments,viscosity experiments and quantum chemical calculations.The practical application of meta-amino-1,8-naphthalimide ICT-based probes is also confirmed.This research is expected to bring an in-depth understanding of π-conjugated systems with ICT characteristics,and facilitates the design of sensitive ICT fluorescent probes with meta-amino substitution.展开更多
It is of great significance to study the indicators of university patents’transferability for improving the efficiency of the University Technology Transfer Office and promoting university patent transfer.Based on th...It is of great significance to study the indicators of university patents’transferability for improving the efficiency of the University Technology Transfer Office and promoting university patent transfer.Based on the in-depth analysis of the existing research,this paper finds that patent quality is the inherent decisive factor of patent transferability.Combining with the evaluation indexes of patent quality and the bibliometrics characteristics of university patents,9 indicators are proposed to indicate the transferability of university patents.Based on the patent transfer data of 35 Chinese universities,this paper analyzes and verifies the potential indicators of patent transfer using the binary logistic regression method.The results show that the number of inventors and the number of non-patent document citations positively predict the transferability of university patents,while the examination duration negatively predicts transferability.The effects of other indicators on transferability need to be discussed considering the actual situation and specific technology fields.展开更多
This study examined the influence of spatial resolution on model parameterization,output,and the parameter transferability between different resolutions using the Storm Water Management Model.High-resolution models,in...This study examined the influence of spatial resolution on model parameterization,output,and the parameter transferability between different resolutions using the Storm Water Management Model.High-resolution models,in which most subcatchrnents were homogeneous,and high-resolution-based low-resolution models (in 3 scenarios)were constructed for a highly urbanized catchment in Beijing.The results indicated that the parameterization and simulation results were affected by both spatial resolution and rainfall characteristics.The simulated peak inflow and total runoff volume were sensitive to the spatial resolution,but did not show a consistent tendency.High-resolution models performed very well for both calibration and validation events in terms of three indexes:1)the Nash-Sutcliffe efficiency, 2)the peak flow error,and 3)the volume error;indication of the advantage of using these models.The parameters obtained from high-resolution models could be directly used in the low-resolution models and performed well in the simulation of heavy rain and torrential rain and in the study area where sub-area routing is insignificant.Alternatively,sub-area routing should be considered and estimated approximately.The successful scale conversion from high spatial resolution to low spatial resolution is of great significance for the hydrological simulation of ungauged large areas.展开更多
This study investigates catalytic tar cracking over semi-coke catalysts,addressing reaction kinetics challenges by integrating experimental data with a COMSOL Multiphysics model.A multi-physics framework combines cata...This study investigates catalytic tar cracking over semi-coke catalysts,addressing reaction kinetics challenges by integrating experimental data with a COMSOL Multiphysics model.A multi-physics framework combines catalysis,carbon deposition,and self-consumption to analyze toluene(tar model compound)removal.The model evaluates intrinsic catalytic activity,porosity evolution,and porous media flow,revealing that toluene conversion is governed by diffusion/convective mass transfer,homogeneous reactions,and surface reactions influenced by dynamic carbon deposition/removal.Increasing temperature from 973 to 1173 K enhances gas-film heat and mass transfer coefficient,accelerating tar cracking rates and extending catalyst lifetime.Elevated temperatures improve gas-solid phase heat/mass transfer,promoting efficient tar removal during syngas purification.The results highlight the interplay between reaction kinetics,carbon deposition dynamics,and transport phenomena in optimizing semi-coke catalyst performance under high-temperature conditions.展开更多
Coiled tube heat exchangers are widely preferred in shell structures due to their superior heat transfer performance,driven by favorable flow characteristics.This study investigates the effect of modifying coil and sh...Coiled tube heat exchangers are widely preferred in shell structures due to their superior heat transfer performance,driven by favorable flow characteristics.This study investigates the effect of modifying coil and shell configurations on heat transfer efficiency.Two key enhancements were examined:adding fins to the outer coil surface and integrating longitudinal slots within a hollowed shell.These modifications promote turbulence and extend heat transfer duration,thereby improving performance.However,they also introduce challenges,including increased pressure loss andmanufacturing complexity.Numerical simulationswere conducted usingANSYS Fluent 2024R1 under identical boundary conditions.With a fixed cold-side flow rate of 3 L/min,the input temperatures for the hot and cold fluids were 333.15 and 291.65 K,respectively.The hot-side flow rate varied between 2 and 6 L/min.Simulation outcomes were reported for the objectives of the study that included the improvement in heat exchangers’heat transfer enhancement.As it was indicated in the study outcomes,the average heat transfer rate increased by 15.56%,the overall heat transfer coefficient enhanced by about 29.51%,and the convective heat transfer coefficient improved by about 75.96%compared to the conventional shell-and-coil tube heat exchanger model.However,the modified technique resulted in a significant pressure drop.展开更多
A visible-light-induced synergistic hydrogen atom transfer(HAT)and proton transfer(PT)catalysis was developed for the defluorinative carboxylation of α-CF_(2)R-substituted alkenes.This system affords a variety of γ,...A visible-light-induced synergistic hydrogen atom transfer(HAT)and proton transfer(PT)catalysis was developed for the defluorinative carboxylation of α-CF_(2)R-substituted alkenes.This system affords a variety of γ,γ-difluoro-and γ-monofluoro-vinylacetic acids without stepwise acidification,exhibiting good functional group tolerance,broad scope,and facile scalability.Mechanism studies support that thiol plays the role of the hydrogen relay,which s a hydrogen atom through HAT and then outputs a proton via PT.This strategy also takes full advantage of formate for photocatalytic carboxylation reaction in a step-and atomeconomical way.展开更多
Adding subtle perturbations to an image can cause the classification model to misclassify,and such images are called adversarial examples.Adversar-ial examples threaten the safe use of deep neural networks,but when com...Adding subtle perturbations to an image can cause the classification model to misclassify,and such images are called adversarial examples.Adversar-ial examples threaten the safe use of deep neural networks,but when combined with reversible data hiding(RDH)technology,they can protect images from being correctly identified by unauthorized models and recover the image lossless under authorized models.Based on this,the reversible adversarial example(RAE)is ris-ing.However,existing RAE technology focuses on feasibility,attack success rate and image quality,but ignores transferability and time complexity.In this paper,we optimize the data hiding structure and combine data augmentation technology,whichflips the input image in probability to avoid overfitting phenomenon on the dataset.On the premise of maintaining a high success rate of white-box attacks and the image’s visual quality,the proposed method improves the transferability of reversible adversarial examples by approximately 16%and reduces the com-putational cost by approximately 43%compared to the state-of-the-art method.In addition,the appropriateflip probability can be selected for different application scenarios.展开更多
基金supported by the Research Grants Council of Hong Kong(CityU 11305919 and 11308620)and NSFC/RGC Joint Research Scheme N_CityU104/19Hong Kong Research Grant Council Collaborative Research Fund:C1002-21G and C1017-22Gsupported by the Hong Kong Research Grant Council Collaborative Research Fund:C6021-19E.
文摘Developing machine learning frameworks with predictive power,interpretability,and transferability is crucial,yet it faces challenges in the field of electrocatalysis.To achieve this,we employed rigorous feature engineering to establish a finely tuned gradient boosting regressor(GBR)model,which adeptly captures the physical complexity from feature space to target variables.We demonstrated that environmental electron effects and atomic number significantly govern the success of the mapping process via global and local explanations.The finely tuned GBR model exhibits exceptional robustness in predicting CO adsorption energies(R_(ave)^(2)=0.937,RMSE=0.153 eV).Moreover,the model demonstrated remarkable transfer learning ability,showing excellent predictive power for OH,NO,and N_(2) adsorption.Importantly,the GBR model exhibits exceptional predictive capability across an extensive search space,thereby demonstrating profound adaptability and versatility.Our research framework significantly enhances the interpretability and transferability of machine learning in electrocatalysis,offering vital insights for further advancements.
基金supported by the Intelligent Policing Key Laboratory of Sichuan Province(No.ZNJW2022KFZD002)This work was supported by the Scientific and Technological Research Program of Chongqing Municipal Education Commission(Grant Nos.KJQN202302403,KJQN202303111).
文摘Transfer-based Adversarial Attacks(TAAs)can deceive a victim model even without prior knowledge.This is achieved by leveraging the property of adversarial examples.That is,when generated from a surrogate model,they retain their features if applied to other models due to their good transferability.However,adversarial examples often exhibit overfitting,as they are tailored to exploit the particular architecture and feature representation of source models.Consequently,when attempting black-box transfer attacks on different target models,their effectiveness is decreased.To solve this problem,this study proposes an approach based on a Regularized Constrained Feature Layer(RCFL).The proposed method first uses regularization constraints to attenuate the initial examples of low-frequency components.Perturbations are then added to a pre-specified layer of the source model using the back-propagation technique,in order to modify the original adversarial examples.Afterward,a regularized loss function is used to enhance the black-box transferability between different target models.The proposed method is finally tested on the ImageNet,CIFAR-100,and Stanford Car datasets with various target models,The obtained results demonstrate that it achieves a significantly higher transfer-based adversarial attack success rate compared with baseline techniques.
基金supported by the Industry-University Cooperation Project in Fujian Province University(No.2023H6006)the State Key Laboratory of Reliability and Intelligence of Electrical Equipment(No.EERI-KF20200005)。
文摘Artificial intelligence has potential for forecasting reactor conditions in the nuclear industry.Owing to economic and security concerns,a common method is to train data generated by simulators.However,achieving a satisfactory performance in practical applications is difficult because simulators imperfectly emulate reality.To bridge this gap,we propose a novel framework called simulation-to-reality domain adaptation(SRDA)for forecasting the operating parameters of nuclear reactors.The SRDA model employs a transformer-based feature extractor to capture dynamic characteristics and temporal dependencies.A parameter predictor with an improved logarithmic loss function is specifically designed to adapt to varying reactor powers.To fuse prior reactor knowledge from simulations with reality,the domain discriminator utilizes an adversarial strategy to ensure the learning of deep domain-invariant features,and the multiple kernel maximum mean discrepancy minimizes their discrepancies.Experiments on neutron fluxes and temperatures from a pressurized water reactor illustrate that the SRDA model surpasses various advanced methods in terms of predictive performance.This study is the first to use domain adaptation for real-world reactor prediction and presents a feasible solution for enhancing the transferability and generalizability of simulated data.
基金Supported by"Provincial and Ministerial Key Discipline,Provincial Key Laboratory of University and School Laboratory Sharing Platform" ItemSouthwest Forestry University Key Fund Item(110909)~~
文摘[Objective] The research aimed to study the transferability of Camellia sinensis EST-SSRs in Theaceae plant.[Method] Seven pairs of EST-SSRs primers which derived from Camellia sinensis EST sequence were used to amplify the nineteen materials of Theaceae plant.[Result] Five pairs in the seven pairs of EST-SSRs primers could effectively amplify the nineteen tested varieties,and the transferability rate was 71.43%.The amplification rate of Camellia retiacalate FengShanCha,Camellia japouica CaiXia and Camellia retiacalate JuBan was the highest.The amplification rate of Camellia synaptica Sealy and Adinandra sagonica var.wallichiana（oc）Ming was the lowest.Moreover,four pairs in the five pairs of primers which could effectively amplify showed the rich polymorphism whose difference was obvious in the tested materials.[Conclusion] SSR primers which were developed from Camellia sinensis genome had the higher transferability in the different genus and species of Theaceae plant,could be used in the comparative genome research and analysis mark research of Theaceae plant.
文摘Simple sequence repeat （SSR） or microsatellite marker is a valuable tool for several purposes, such as mapping, fingerprinting, and breeding. In the present study, an intersimple sequence repeat （ISSR）-PCR technique was applied for developing SSR markers in non-heading Chinese cabbage （Brassica rapa）. A total of 190 SSRs were obtained. Among these, AG or CT （54.7%） was the most frequent repeat, followed by AC or GT （31.6%） of the microsatellites. The average number of the SSRs length array was 16 and 10 times, respectively. Based on the determined SSR sequences, 143 SSR primer pairs were designed to evaluate their transferabilities among the related species of Brassica. The number of alleles produced per marker averaged 2.91, and the polymorphism information content （PIC） value ranged from 0 to 0.863 with an average of 0.540. Monomorphism was observed in 16 primer pairs. The transferability percentage in CC genome was higher than in BB genome. More loci occurred in the BBCC genome. This result supported the hypothesis that BB genome was divergent from A and C genomes, and AA and CC genomes were relatively close. The polymorphic primers can be exploited for further evolution, fingerprinting, and variety identification.
文摘Currently development of new marker types has shifted from anonymous DNA fragments to gene-based markers. Simple Sequence Repeats (SSRs) are useful DNA markers in plant genetic research including in peanut. However, de novo development of SSRs is expensive and time consuming. Gene-based DNA markers are transferable among related species owing to the conserved nature of genes. In this study transferability of sorghum EST-SSR (SbEST-SSR) markers to peanut was prospected. A set of 411 SbEST-SSR primer pairs were used to amplify peanut genomic DNA extracted from cultivated peanut where 39% of them successfully amplified. A comparison of amplification patterns between sorghum and peanut showed similar banding pattern with majority of transferable SbEST-SSRs. Among these transferable SSR markers, 14% have detected polymorphism among 4 resistant and 4 susceptible peanut lines for rust and late leaf spot diseases. These transferable markers will benefit peanut genome research by not only providing additional DNA markers for population genetic analyses, but also allowing comparative mapping to be possible between peanut and sorghum—a possible monocot-dicot comparison.
文摘We characterized 14 anonymous nuclear loci from Pinus thunbergii Parl., an important pine species native to Japan. One hundred and twenty-six single nucleotide polymorphisms （SNPs） were identified from these loci, giving a frequency of 1 SNP per 51 bp. Nucleotide di- versity （0） ranged from 1.06 × 10^-3 to 11.87 × 10^-3, with all average of 4.99 × 10^-3. Only one locus （mK45） deviated significantly from the Hardy-Weinberg equilibrium. Thirteen of 14 loci were applicable in other pine species. These loci will be useful for nucleotide variation studies and will provide material for SNP-based marker development in P. thun- bergii and related species.
基金supported by the Key Research Program of Frontier Sciences of Chinese Academy of Sciences(Grant No.QYZDB-SSW-SYS024)National Natural Science Foundation of China(Grant Nos.41771081 and 41761134093).
文摘Glacier mass balance, the difference between accumulation and ablation at the glacier surface, is the direct reflection of the local climate regime. Under global warming, the simulation of glacier mass balance at the regional scale has attracted increasing interests. This study selects Urumqi Glacier No. 1 as the testbed for examining the transferability in space and time of two commonly used glacier mass balance simulation models: i.e., the Degree-Day Model(DDM) and the simplified Energy Balance Model(s EBM). Four experiments were carried out for assessing both models’ temporal and spatial transferability. The results show that the spatial transferability of both the DDM and s EBM is strong, whereas the temporal transferability of the DDM is relatively weak. For all four experiments, the overall simulation effect of the s EBM is better than that of the DDM. At the zone around Equilibrium Line Altitude(ELA), the DDM performed better than the s EBM.Also, the accuracy of parameters, including the lapse rate of air temperature and vertical gradient of precipitation at the glacier surface, is of great significance for improving the spatial transferability of both models.
基金This work was supported by Sichuan Science and Technology Program[No.2022YFG0315,2022YFG0174]Sichuan Gas Turbine Research Institute stability support project of China Aero Engine Group Co.,Ltd.[GJCZ-2019-71]Key project of Chengdu[No.2019-YF09-00044-CG].
文摘The current adversarial attacks against deep learning models have achieved incredible success in the white-box scenario.However,they often exhibit weak transferability in the black-box scenario,especially when attacking those with defense mechanisms.In this work,we propose a new transfer-based blackbox attack called the channel decomposition attack method(CDAM).It can attack multiple black-box models by enhancing the transferability of the adversarial examples.On the one hand,it tunes the gradient and stabilizes the update direction by decomposing the channels of the input example and calculating the aggregate gradient.On the other hand,it helps to escape from local optima by initializing the data point with random noise.Besides,it could combine with other transfer-based attacks flexibly.Extensive experiments on the standard ImageNet dataset show that our method could significantly improve the transferability of adversarial attacks.Compared with the state-of-the-art method,our approach improves the average success rate from 88.2%to 96.6%when attacking three adversarially trained black-box models,demonstrating the remaining shortcomings of existing deep learning models.
基金The German Academic Exchange Service(DAAD)is appreciated for financial support to the first author
文摘Transferability of five nuclear microsatellite markers (Jc-16, Jc-31, Jc-32, Jc-35 and Jc-37) that were originally developed for J. communis was tested to J. procera. Jc-31 & Jc-37 showed successful amplifications and polymorphism in J. procera. Jc-35 which had been reported as polymorphic in J. communis was monomorphic in J. procera while the primer pair for Jc-32 failed to record any amplification. The remaining one primer pair (Jc-16) showed double loci ampli-fication in both J. procera and the control J. communis suggesting further examination of the primer pair and its binding sites. Genetic variation of six Ethiopian J. procera populations: Chilimo, Goba, Menagesha-Suba, Wef-Washa, Yabelo and Ziquala was assessed based on the two polymorphic loci (Jc-31 & Jc-37) in 20 - 24 individuals of each population. From these two loci, a total of 41 alleles could be retrieved. Two populations that are located south east of the Great Rift Valley together harboured 75% of private alleles signifying their deviant geo-ecological zones and suggesting special consideration for conservation. Chilimo, which is at the western margin of Juniper habitat in Ethiopian central highlands scored the highest fixation (FIS = 0.584) entailing lower immigrant genes and hence higher inbreeding. The AMOVA revealed that 97% of the variation resided within the?population while still among population variation was significant
基金funded by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, Materials Sciences and Engineering Division under Contract No. DE-AC0205CH11231 (Materials Project program KC23MP)The work was also supported by the computational resources provided by the Extreme Science and Engineering Discovery Environment (XSEDE), supported by National Science Foundation grant number ACI1053575the National Energy Research Scientific Computing Center (NERSC), a U.S. Department of Energy Office of Science User Facility located at Lawrence Berkeley National Laboratory, and the Swift Cluster resource provided by the National Renewable Energy Laboratory (NREL). The authors thank Luca Binci and Lauren N. Walters for valuable discussions.
文摘The rapid development of foundation potentials(FPs)in machine learning interatomic potentials demonstrates the possibility for generalizable learning of the universal potential energy surface.The accuracy of FPs can be further improved by bridging the model from lower-fidelity datasets to highfidelity ones.In this work,we analyze the challenge of this transfer learning(TL)problem within the CHGNet framework.We show that significant energy scale shifts and poor correlations between GGA and r^(2)SCAN hinder cross-functional transferability.By benchmarking different TL approaches on the MP-r^(2)SCAN dataset,we demonstrate the importance of elemental energy referencing in the TL of FPs.By comparing the scaling law with and without the pre-training on a low-fidelity dataset,we show that significant data efficiency can still be achieved through TL,even with a target dataset of sub-million structures.We highlight the importance of proper TL and multi-fidelity learning in creating nextgeneration FPs on high-fidelity data.
基金This study was supported by the National Natural Science Foundation of China grants 32422059 and 32271640the National Key R&D Program of China grants 2022YFF0803100 and 2022YFD2200101the Innovation and Technology Fund(funding support to State Key Laboratories in Hong Kong of Agrobiotechnology).
文摘Leaf spectroscopy,combined with partial least squares regression(PLSR),is recognized as an efficient and precise tool for measuring plant leaf traits.However,the feasibility of developing a generalizable model remains unclear,primarily due to limited understanding of PLSR model transferability.Here,we collected six key leaf traits along with paired leaf reflectance spectra from 1967 samples of 349 tree species in eight forest sites across China.Using this dataset,we explored the transferability of PLSR models,factors affecting model transferability,and the feasibility of developing generalizable PLSR models for leaf trait prediction.Overall,PLSR models trained at a specific study site demonstrate limited transferability to other study sites.Dissimilarities in plant evolutionary history and environmental conditions between study sites are the primary factors influencing the transferability of PLSR models.Incorporating training data from diverse evolutionary histories and environmental conditions can improve the transferability of PLSR models,achieving accuracy equivalent to that of site-specific models.Our findings provide guidelines for the use of spectroscopy in leaf trait prediction and underscore the urgent need for collaborative efforts to build an open database of leaf traits and reflectance spectra,thereby promoting the development of universal PLSR models for plant leaf trait prediction.
文摘Safety performance functions(SPFs),or crash-prediction models,have played an important role in identifying the factors contributing to crashes,predicting crash counts and identifying hotspots.Since a great deal of time and effort is needed to estimate an SPF,previous studies have sought to determine the transferability of particular SPFs;that is,the extent to which they can be applied to data from other regions.Although many efforts have been made to examine micro-level SPF transferability,few studies have focused on macro-level SPF transferability.There has been little transferability analysis of macro-level SPFs in the international context,especially between western countries.This study therefore evaluates the transferability of SPFs for several states in the USA(Illinois,Florida and Colorado)and for Italy.The SPFs were developed using data from counties in the United States and provincias in Italy,and the results revealed multiple common significant variables between the two countries.Transferability indexes were then calculated between the SPFs.These showed that the Italy SPFs for total crashes and bicycle crashes were transferable to US data after calibration factors were applied,whereas the US SPFs for total and bicycle crashes,with the exception of the Colorado SPF,could not be transferred to the Italian data.On the other hand,none of the pedestrian SPFs developed was transferable to other countries.This paper provides insights into the applicability of macro-level SPFs between the USA and Italy,and shows a good potential for international SPF transferability.Nevertheless,further investigation is needed of SPF transferability between a wider range of countries.
基金financially supported by National Key Research and Development Programs (Nos.2022YFD1700403 and 2023YFD1700303)National Natural Science Foundation of China (Nos.12274128 and 12250003)+2 种基金Shanghai Rising-Star Program (No.21QA1402600)the support of NYU-ECNU Center for Computational Chemistry at NYU Shanghaithe University of Bath and the Open Research Fund of the School of Chemistry and Chemical Engineering,Henan Normal University (No.2020ZD01) for support。
文摘Fluorescent probes based on intramolecular charge transfer(ICT) have obvious advantages for accurate quantitative analysis.To obtain high-performance ratiometric probes requires distinct photophysical properties during recognition reaction process,which is closely related to their ICT characteristics.1,8-Naphthalimide is known as a typical fluorophore with desirable ICT property when functionalized with an electron-donating moiety at the para-position of the naphthalene chromophore.Although the photophysical properties of para-substituted 1,8-naphthalimide have been well studied,its meta-substituted counterpart has not been fully evaluated since the meta-position is conventionally thought to be weakly conjugated.Herein,combined experimental and theoretical studies are performed which consistently indicate that stronger charge transfer(CT) is exhibited by the meta-amino substituted 1,8-naphthalimide(m-NH_(2)) compared to the para-amino substituted one(p-NH_(2)).The ratiometric response of fluorescence with significant changes in wavelength and intensity upon acetylation(m-NAc and p-NAc) can be attributed to the larger ICT and stronger-NH_(2) vibrations.This observation is further demonstrated by deuterium oxide experiments,viscosity experiments and quantum chemical calculations.The practical application of meta-amino-1,8-naphthalimide ICT-based probes is also confirmed.This research is expected to bring an in-depth understanding of π-conjugated systems with ICT characteristics,and facilitates the design of sensitive ICT fluorescent probes with meta-amino substitution.
基金supported by the National Social Science Foundation of China,A Restudy of patent Citation Relationship and its Evaluation Significance from the Perspective of Innovation Economics(Grant No.20XTQ008)。
文摘It is of great significance to study the indicators of university patents’transferability for improving the efficiency of the University Technology Transfer Office and promoting university patent transfer.Based on the in-depth analysis of the existing research,this paper finds that patent quality is the inherent decisive factor of patent transferability.Combining with the evaluation indexes of patent quality and the bibliometrics characteristics of university patents,9 indicators are proposed to indicate the transferability of university patents.Based on the patent transfer data of 35 Chinese universities,this paper analyzes and verifies the potential indicators of patent transfer using the binary logistic regression method.The results show that the number of inventors and the number of non-patent document citations positively predict the transferability of university patents,while the examination duration negatively predicts transferability.The effects of other indicators on transferability need to be discussed considering the actual situation and specific technology fields.
基金the State Key Program of the National Natural Science Foundation of China (Grant No.41530635)the Fund for Innovative Research Group of the National Natural Science Foundation of China (Grant No.51421065)Open Research Fund Program of Key Laboratory of Urban Storm Water System and Water Environment, Ministry of Education.
文摘This study examined the influence of spatial resolution on model parameterization,output,and the parameter transferability between different resolutions using the Storm Water Management Model.High-resolution models,in which most subcatchrnents were homogeneous,and high-resolution-based low-resolution models (in 3 scenarios)were constructed for a highly urbanized catchment in Beijing.The results indicated that the parameterization and simulation results were affected by both spatial resolution and rainfall characteristics.The simulated peak inflow and total runoff volume were sensitive to the spatial resolution,but did not show a consistent tendency.High-resolution models performed very well for both calibration and validation events in terms of three indexes:1)the Nash-Sutcliffe efficiency, 2)the peak flow error,and 3)the volume error;indication of the advantage of using these models.The parameters obtained from high-resolution models could be directly used in the low-resolution models and performed well in the simulation of heavy rain and torrential rain and in the study area where sub-area routing is insignificant.Alternatively,sub-area routing should be considered and estimated approximately.The successful scale conversion from high spatial resolution to low spatial resolution is of great significance for the hydrological simulation of ungauged large areas.
基金the National Key Research and Development Program of China(2022YFE0208400)the Shanxi Province Key Research and Development Program(202202090301002)the Natural Science Foundation of Shanxi Province,China(202103021224096).
文摘This study investigates catalytic tar cracking over semi-coke catalysts,addressing reaction kinetics challenges by integrating experimental data with a COMSOL Multiphysics model.A multi-physics framework combines catalysis,carbon deposition,and self-consumption to analyze toluene(tar model compound)removal.The model evaluates intrinsic catalytic activity,porosity evolution,and porous media flow,revealing that toluene conversion is governed by diffusion/convective mass transfer,homogeneous reactions,and surface reactions influenced by dynamic carbon deposition/removal.Increasing temperature from 973 to 1173 K enhances gas-film heat and mass transfer coefficient,accelerating tar cracking rates and extending catalyst lifetime.Elevated temperatures improve gas-solid phase heat/mass transfer,promoting efficient tar removal during syngas purification.The results highlight the interplay between reaction kinetics,carbon deposition dynamics,and transport phenomena in optimizing semi-coke catalyst performance under high-temperature conditions.
文摘Coiled tube heat exchangers are widely preferred in shell structures due to their superior heat transfer performance,driven by favorable flow characteristics.This study investigates the effect of modifying coil and shell configurations on heat transfer efficiency.Two key enhancements were examined:adding fins to the outer coil surface and integrating longitudinal slots within a hollowed shell.These modifications promote turbulence and extend heat transfer duration,thereby improving performance.However,they also introduce challenges,including increased pressure loss andmanufacturing complexity.Numerical simulationswere conducted usingANSYS Fluent 2024R1 under identical boundary conditions.With a fixed cold-side flow rate of 3 L/min,the input temperatures for the hot and cold fluids were 333.15 and 291.65 K,respectively.The hot-side flow rate varied between 2 and 6 L/min.Simulation outcomes were reported for the objectives of the study that included the improvement in heat exchangers’heat transfer enhancement.As it was indicated in the study outcomes,the average heat transfer rate increased by 15.56%,the overall heat transfer coefficient enhanced by about 29.51%,and the convective heat transfer coefficient improved by about 75.96%compared to the conventional shell-and-coil tube heat exchanger model.However,the modified technique resulted in a significant pressure drop.
基金supported by the National Natural Science Foundation of China (22472031,U24A20567,22032002)the 111 Project。
文摘A visible-light-induced synergistic hydrogen atom transfer(HAT)and proton transfer(PT)catalysis was developed for the defluorinative carboxylation of α-CF_(2)R-substituted alkenes.This system affords a variety of γ,γ-difluoro-and γ-monofluoro-vinylacetic acids without stepwise acidification,exhibiting good functional group tolerance,broad scope,and facile scalability.Mechanism studies support that thiol plays the role of the hydrogen relay,which s a hydrogen atom through HAT and then outputs a proton via PT.This strategy also takes full advantage of formate for photocatalytic carboxylation reaction in a step-and atomeconomical way.
基金This research work is partly supported by the National Natural Science Foundation of China(62172001)the Provincial Colleges Quality Project of Anhui Province(2020xsxxkc047)the National Undergraduate Innovation and Entrepreneurship Training Program(202210357077).
文摘Adding subtle perturbations to an image can cause the classification model to misclassify,and such images are called adversarial examples.Adversar-ial examples threaten the safe use of deep neural networks,but when combined with reversible data hiding(RDH)technology,they can protect images from being correctly identified by unauthorized models and recover the image lossless under authorized models.Based on this,the reversible adversarial example(RAE)is ris-ing.However,existing RAE technology focuses on feasibility,attack success rate and image quality,but ignores transferability and time complexity.In this paper,we optimize the data hiding structure and combine data augmentation technology,whichflips the input image in probability to avoid overfitting phenomenon on the dataset.On the premise of maintaining a high success rate of white-box attacks and the image’s visual quality,the proposed method improves the transferability of reversible adversarial examples by approximately 16%and reduces the com-putational cost by approximately 43%compared to the state-of-the-art method.In addition,the appropriateflip probability can be selected for different application scenarios.
