The high porosity and tunable chemical functionality of metal-organic frameworks(MOFs)make it a promising catalyst design platform.High-throughput screening of catalytic performance is feasible since the large MOF str...The high porosity and tunable chemical functionality of metal-organic frameworks(MOFs)make it a promising catalyst design platform.High-throughput screening of catalytic performance is feasible since the large MOF structure database is available.In this study,we report a machine learning model for high-throughput screening of MOF catalysts for the CO_(2) cycloaddition reaction.The descriptors for model training were judiciously chosen according to the reaction mechanism,which leads to high accuracy up to 97%for the 75%quantile of the training set as the classification criterion.The feature contribution was further evaluated with SHAP and PDP analysis to provide a certain physical understanding.12,415 hypothetical MOF structures and 100 reported MOFs were evaluated under 100℃ and 1 bar within one day using the model,and 239 potentially efficient catalysts were discovered.Among them,MOF-76(Y)achieved the top performance experimentally among reported MOFs,in good agreement with the prediction.展开更多
The capture of CO_(2)from CO_(2)/H_(2)gas mixtures in syngas is a crucial issue for hydrogen production from steam methane reforming in industry,as the presence of CO_(2)directly affects the purity of H_(2).A combinat...The capture of CO_(2)from CO_(2)/H_(2)gas mixtures in syngas is a crucial issue for hydrogen production from steam methane reforming in industry,as the presence of CO_(2)directly affects the purity of H_(2).A combination of a high-throughput screening method and grand canonical Monte Carlo simulation was utilized to evaluate and screen 1725 metal–organic frameworks(MOFs)in detail as a means of determining their adsorption performance for CO_(2)/H_(2)gas mixtures.The adsorption and separation performance of double-linker MOFs was comprehensively evaluated using eight evaluation indicators,namely,the largest cavity diameter,accessible surface area,pore occupied accessible volume,porosity,adsorption selectivity,working capacity,adsorbent performance score and percent regeneration.Six optimal performance frameworks were screened to further study their single-component adsorption and binary competitive adsorption of CO_(2)/H_(2)respectively.The CO_(2)adsorption selectivity at different CO_(2)/H_(2)feed ratios was also evaluated,which indicated their excellent adsorption and separation performance.The microscopic adsorption mechanisms for CO_(2)and H_(2)at the molecular level were investigated by analyzing the radial distribution function and density distribution.This study may provide directional guidance and reference for subsequent experiments on the adsorption and separation of CO_(2)/H_(2).展开更多
Alzheimer's disease(AD)is a common cause of dementia,characterised by cerebral amyloid-βdeposition,pathological tau and neurodegeneration.The prodromal stage of AD(pAD)refers to patients with mild cognitive impai...Alzheimer's disease(AD)is a common cause of dementia,characterised by cerebral amyloid-βdeposition,pathological tau and neurodegeneration.The prodromal stage of AD(pAD)refers to patients with mild cognitive impairment(MCl)and evidence of AD's pathology.At this stage,disease-modifying interventions should be used to prevent the progression to dementia.Given the inherent heterogeneity of MCl,more specific biomarkers are needed to elucidate the underlying AD's pathology.Although the uses of cerebrospinal fluid and positron emission tomography are widely accepted methods for detecting AD's pathology,their clinical applications are limited by their high costs and invasiveness,particularly in low-income areas in China.Therefore,to improve the early detection of Alzheimer's disease(AD)pathology through cost-effective screening methods,a panel of 45neurologists,psychiatrists andgerontologistswas invited to establish a formal consensus on the screening of pAD in China.The supportive evidence and grades of recommendations are based on a systematic literature review andfocus group discussion.National meetings were held to allow participants to review,vote and provide their expert opinions to reach a consensus.A majority(two-thirds)decision was used for questions for which consensus could not be reached.Recommended screening methods are presented in this publication,including neuropsychological assessment,peripheral biomarkers and brain imaging.In addition,a general workflow for Screening pAD in China is established,which will help clinicians identify individuals at high risk and determine therapeutic targets.展开更多
Metal halide perovskites,particularly the quasi-two-dimensional perovskite subclass,have exhibited considerable potential for next-generation electroluminescent materials for lighting and display.Nevertheless,the pres...Metal halide perovskites,particularly the quasi-two-dimensional perovskite subclass,have exhibited considerable potential for next-generation electroluminescent materials for lighting and display.Nevertheless,the presence of defects within these perovskites has a substantial influence on the emission efficiency and durability of the devices.In this study,we revealed a synergistic passivation mechanism on perovskite films by using a dual-functional compound of potassium bromide.The dual functional potassium bromide on the one hand can passivate the defects of halide vacancies with bromine anions and,on the other hand,can screen the charged defects at the grain boundaries with potassium cations.This approach effectively reduces the probability of carriers quenching resulting from charged defects capture and consequently enhances the radiative recombination efficiency of perovskite thin films,leading to a significant enhancement of photoluminescence quantum yield to near-unity values(95%).Meanwhile,the potassium bromide treatment promoted the growth of homogeneous and smooth film,facilitating the charge carrier injection in the devices.Consequently,the perovskite light-emitting diodes based on this strategy achieve a maximum external quantum efficiency of~21%and maximum luminance of~60,000 cd m^(-2).This work provides a deeper insight into the passivation mechanism of ionic compound additives in perovskite with the solution method.展开更多
As an independent sand control unit or a common protective shell of a high-quality screen,the punching screen is the outermost sand retaining unit of the sand control pipe which is used in geothermal well or oil and g...As an independent sand control unit or a common protective shell of a high-quality screen,the punching screen is the outermost sand retaining unit of the sand control pipe which is used in geothermal well or oil and gas well.However,most screens only consider the influence of the internal sand retaining medium parameters in the sand control performance design while ignoring the influence of the plugging of the punching screen on the overall sand retaining performance of the screen.To explore the clogging mechanism of the punching screen,this paper established the clogging mechanism calculation model of a single punching screen sand control unit by using the computational fluid mechanics-discrete element method(CFD-DEM)combined method.According to the combined motion of particles and fluids,the influence of the internal flow state on particle motion and accumulation was analyzed.The results showed that(1)the clogging process of the punching sand control unit is divided into three stages:initial clogging,aggravation of clogging and stability of clogging.In the initial stage of blockage,coarse particles form a loose bridge structure,and blockage often occurs preferentially at the streamline gathering place below chamfering inside the sand control unit.In the stage of blockage intensification,the particle mass develops into a relatively complete sand bridge,which develops from both ends of the opening to the center of the opening.In the stable plugging stage,the sand deposits show a“fan shape”and form a“V-shaped”gully inside the punching slot element.(2)Under a certain reservoir particle-size distribution,The slit length and opening height have a large influence on the permeability and blockage rate,while the slit width size has little influence on the permeability and blockage rate.The microscopic clogging mechanism and its law of the punching screen prevention unit are proposed in this study,which has some field guidance significance for the design of punching screen and sand prevention selection.展开更多
Photocatalysis,a critical strategy for harvesting sunlight to address energy demand and environmental concerns,is underpinned by the discovery of high-performance photocatalysts,thereby how to design photocatalysts is...Photocatalysis,a critical strategy for harvesting sunlight to address energy demand and environmental concerns,is underpinned by the discovery of high-performance photocatalysts,thereby how to design photocatalysts is now generating widespread interest in boosting the conversion effi-ciency of solar energy.In the past decade,computational technologies and theoretical simulations have led to a major leap in the development of high-throughput computational screening strategies for novel high-efficiency photocatalysts.In this viewpoint,we started with introducing the challenges of photocatalysis from the view of experimental practice,especially the inefficiency of the traditional“trial and error”method.Sub-sequently,a cross-sectional comparison between experimental and high-throughput computational screening for photocatalysis is presented and discussed in detail.On the basis of the current experimental progress in photocatalysis,we also exemplified the various challenges associated with high-throughput computational screening strategies.Finally,we offered a preferred high-throughput computational screening procedure for pho-tocatalysts from an experimental practice perspective(model construction and screening,standardized experiments,assessment and revision),with the aim of a better correlation of high-throughput simulations and experimental practices,motivating to search for better descriptors.展开更多
Alpha-lactalbumin(α-LA)is a major whey protein found in breast milk and plays a crucial role in the growth and development of infants.In this study,Bacillus subtilis RIK1285 harboring AprE signal peptide(SP)was selec...Alpha-lactalbumin(α-LA)is a major whey protein found in breast milk and plays a crucial role in the growth and development of infants.In this study,Bacillus subtilis RIK1285 harboring AprE signal peptide(SP)was selected as the original strain for the production ofα-LA.It was found thatα-LA was identified in the pellet after ultrasonic disruption and centrifugation instead of in the fermentation supernatant.The original strain most likely only producedα-LA intracellular,but not extracellular.To improve the expression and secretion ofα-LA in RIK1285,a library of 173 homologous SPs from the B.subtilis 168 genome was fused with target LALBA gene in the pBE-S vector and expressed extracellularly in RIK1285.SP YjcN was determined to be the best signal peptide.Bands in supernatant were observed by sodium dodecyl sulfate-polyacrylamide gel electrophoresis and purified by nickel column to calculate the highest yield signal peptide.In addition,different promoters(P_(aprE),P_(43),and P_(glv))were compared and applied.The results indicated that the strain RIK1285-pBE-P_(glv)-YjcN-LALBA had the highestα-LA yield,reaching 122.04μg/mL.This study demonstrates successful expression and secretion of humanα-LA in B.subtilis and establishes a foundation for simulating breast milk for infant formulas and developing bioengineered milk.展开更多
The traditional nutritional and medical hemp(Cannabis sativa L.)seed protein were explored for the discovery and directional preparation of new xanthine oxidase inhibitory(XOI)peptides by structure-based virtual scree...The traditional nutritional and medical hemp(Cannabis sativa L.)seed protein were explored for the discovery and directional preparation of new xanthine oxidase inhibitory(XOI)peptides by structure-based virtual screening,compound synthesis,in vitro bioassay and proteolysis.Six subtypes of hemp seed edestin and albumin were in silico hydrolyzed by 29 proteases,and 192 encrypted bioactive peptides were screened out.Six peptides showed to be XOI peptides,of which four(about 67%)were released by elastase hydrolysis.The peptide DDNPRRFY displayed the highest XOI activity(IC50=(2.10±0.06)mg/mL),acting as a mixed inhibitor.The pancreatic elastase directionally prepared XOI hemp seed protein hydrolysates,from which 6 high-abundance XOI peptides encrypted 3 virtually-screened ones including the DDNPRRFY.The novel outstanding hemp seed protein-derived XOI peptides and their virtual screening and directed preparation methods provide a promising and applicable approach to conveniently and efficiently explore food-derived bioactive peptides.展开更多
When seismic waves propagate through the geological formation,there is a significant loss of energy and a decrease in imaging resolution,because of the viscoacoustic properties of subsurface medium.This profoundly imp...When seismic waves propagate through the geological formation,there is a significant loss of energy and a decrease in imaging resolution,because of the viscoacoustic properties of subsurface medium.This profoundly impacts seismic wavefield propagation,imaging and interpretation.To accurately image the true structure of subsurface medium,the consensus among geophysicists is to no longer treat subsurface medium as ideal homogeneous medium,but rather to incorporate the viscoacoustic properties of subsurface medium.Based on the generalized screen propagator using conventional acoustic wave equation(acoustic GSP),our developed method introduces viscoacoustic compensation strategy,and derives a one-way wave generalized screen propagator based on time-fractional viscoacoustic wave equation(viscoacoustic GSP).In numerical experiments,we conducted tests on two-dimensional multi-layer model and the Marmousi model.When comparing with the acoustic GSP using the acoustic data,we found that the imaging results of the viscoacoustic GSP using the viscoacoustic data showed a significant attenuation compensation effect,and achieved imaging results for both algorithms were essentially consistent.However,the imaging results of acoustic GSP using viscoacoustic data showed significant attenuation effects,especially for deep subsurface imaging.This indicates that we have proposed an effective method to compensate the attenuated seismic wavefield.Our application on a set of real seismic data demonstrated that the imaging performance of our proposed method in local areas surpassed that of the conventional acoustic GSP.This suggests that our proposed method holds practical value and can more accurately image real subsurface structures while enhancing imaging resolution compared with the conventional acoustic GSP.Finally,with respect to computational efficiency,we gathered statistics on running time to compare our proposed method with conventional Q-RTM,and it is evident that our method exhibits higher computational efficiency.In summary,our proposed viscoacoustic GSP method takes into account the true properties of the medium,still achieves migration results comparable to conventional acoustic GSP.展开更多
Dual-atom catalysts(DACs)have emerged as potential catalysts for effective electroreduction of CO_(2)due to their high atom utilization efficiency and multiple active sites.However,the screening of DACs remains a chal...Dual-atom catalysts(DACs)have emerged as potential catalysts for effective electroreduction of CO_(2)due to their high atom utilization efficiency and multiple active sites.However,the screening of DACs remains a challenge due to the large number of possible combinations,making exhaustive experimental or computational screening a daunting task.In this study,a density functional theory(DFT)-based machine learning(ML)-accelerated(DFT-ML)hybrid approach was developed to test a set of 406 dual transition metal catalysts on N-doped graphene(NG)for the electroreduction of CO_(2)to HCOOH.The results showed that the ML algorithms can successfully capture the relationship between the descriptors of the DACs(inputs)and the limiting potential for HCOOH generation(output).Of the four ML algorithms studied in this work,the feedforward neural network model achieved the highest prediction accuracy(the highest correlation coefficient(R^(2))of 0.960 and the lowest root mean square error(RMSE)of 0.319 eV on the test set)and the predicted results were verified by DFT calculations with an average absolute error of 0.14 eV.The DFT-ML approach identified Co-Co-NG and Ir-Fe-NG as the most active and stable electrocatalysts for the electrochemical reduction of CO_(2)to HCOOH.The DFT-ML hybrid approach exhibits exceptional prediction accuracy while enabling a significant reduction in screening time by an impressive 64%compared to conventional DFT-only calculations.These results demonstrate the immense potential of using ML methods to accelerate the screening and rational design of efficient catalysts for various energy and environmental applications.展开更多
In this paper,we introduce the censored composite conditional quantile coefficient(cC-CQC)to rank the relative importance of each predictor in high-dimensional censored regression.The cCCQC takes advantage of all usef...In this paper,we introduce the censored composite conditional quantile coefficient(cC-CQC)to rank the relative importance of each predictor in high-dimensional censored regression.The cCCQC takes advantage of all useful information across quantiles and can detect nonlinear effects including interactions and heterogeneity,effectively.Furthermore,the proposed screening method based on cCCQC is robust to the existence of outliers and enjoys the sure screening property.Simulation results demonstrate that the proposed method performs competitively on survival datasets of high-dimensional predictors,particularly when the variables are highly correlated.展开更多
基金financial support from the National Key Research and Development Program of China(2021YFB 3501501)the National Natural Science Foundation of China(No.22225803,22038001,22108007 and 22278011)+1 种基金Beijing Natural Science Foundation(No.Z230023)Beijing Science and Technology Commission(No.Z211100004321001).
文摘The high porosity and tunable chemical functionality of metal-organic frameworks(MOFs)make it a promising catalyst design platform.High-throughput screening of catalytic performance is feasible since the large MOF structure database is available.In this study,we report a machine learning model for high-throughput screening of MOF catalysts for the CO_(2) cycloaddition reaction.The descriptors for model training were judiciously chosen according to the reaction mechanism,which leads to high accuracy up to 97%for the 75%quantile of the training set as the classification criterion.The feature contribution was further evaluated with SHAP and PDP analysis to provide a certain physical understanding.12,415 hypothetical MOF structures and 100 reported MOFs were evaluated under 100℃ and 1 bar within one day using the model,and 239 potentially efficient catalysts were discovered.Among them,MOF-76(Y)achieved the top performance experimentally among reported MOFs,in good agreement with the prediction.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.11304079,11404094,and 11504088)Science and Technology Research Project of Henan Science and Technology Department(Grant No.182102410076)。
文摘The capture of CO_(2)from CO_(2)/H_(2)gas mixtures in syngas is a crucial issue for hydrogen production from steam methane reforming in industry,as the presence of CO_(2)directly affects the purity of H_(2).A combination of a high-throughput screening method and grand canonical Monte Carlo simulation was utilized to evaluate and screen 1725 metal–organic frameworks(MOFs)in detail as a means of determining their adsorption performance for CO_(2)/H_(2)gas mixtures.The adsorption and separation performance of double-linker MOFs was comprehensively evaluated using eight evaluation indicators,namely,the largest cavity diameter,accessible surface area,pore occupied accessible volume,porosity,adsorption selectivity,working capacity,adsorbent performance score and percent regeneration.Six optimal performance frameworks were screened to further study their single-component adsorption and binary competitive adsorption of CO_(2)/H_(2)respectively.The CO_(2)adsorption selectivity at different CO_(2)/H_(2)feed ratios was also evaluated,which indicated their excellent adsorption and separation performance.The microscopic adsorption mechanisms for CO_(2)and H_(2)at the molecular level were investigated by analyzing the radial distribution function and density distribution.This study may provide directional guidance and reference for subsequent experiments on the adsorption and separation of CO_(2)/H_(2).
基金the National Natural Science Foundation of China(82171198,U20A20354)the Sci-Tech Innovation 2030 Agenda of China(2022ZD0211603).
文摘Alzheimer's disease(AD)is a common cause of dementia,characterised by cerebral amyloid-βdeposition,pathological tau and neurodegeneration.The prodromal stage of AD(pAD)refers to patients with mild cognitive impairment(MCl)and evidence of AD's pathology.At this stage,disease-modifying interventions should be used to prevent the progression to dementia.Given the inherent heterogeneity of MCl,more specific biomarkers are needed to elucidate the underlying AD's pathology.Although the uses of cerebrospinal fluid and positron emission tomography are widely accepted methods for detecting AD's pathology,their clinical applications are limited by their high costs and invasiveness,particularly in low-income areas in China.Therefore,to improve the early detection of Alzheimer's disease(AD)pathology through cost-effective screening methods,a panel of 45neurologists,psychiatrists andgerontologistswas invited to establish a formal consensus on the screening of pAD in China.The supportive evidence and grades of recommendations are based on a systematic literature review andfocus group discussion.National meetings were held to allow participants to review,vote and provide their expert opinions to reach a consensus.A majority(two-thirds)decision was used for questions for which consensus could not be reached.Recommended screening methods are presented in this publication,including neuropsychological assessment,peripheral biomarkers and brain imaging.In addition,a general workflow for Screening pAD in China is established,which will help clinicians identify individuals at high risk and determine therapeutic targets.
基金supported by the Science and Technology Development Fund,Macao SAR(File no.FDCT-0082/2021/A2,0010/2022/AMJ,006/2022/ALC)UM's research fund(File no.MYRG2022-00241-IAPME,MYRGCRG2022-00009-FHS)+2 种基金the research fund from Wuyi University(EF38/IAPME-XGC/2022/WYU)the Natural Science Foundation of China(61935017,62175268)Science,Technology and Innovation Commission of Shenzhen Municipality(Project Nos.JCYJ20220530113015035,JCYJ20210324120204011,and KQTD2015071710313656).
文摘Metal halide perovskites,particularly the quasi-two-dimensional perovskite subclass,have exhibited considerable potential for next-generation electroluminescent materials for lighting and display.Nevertheless,the presence of defects within these perovskites has a substantial influence on the emission efficiency and durability of the devices.In this study,we revealed a synergistic passivation mechanism on perovskite films by using a dual-functional compound of potassium bromide.The dual functional potassium bromide on the one hand can passivate the defects of halide vacancies with bromine anions and,on the other hand,can screen the charged defects at the grain boundaries with potassium cations.This approach effectively reduces the probability of carriers quenching resulting from charged defects capture and consequently enhances the radiative recombination efficiency of perovskite thin films,leading to a significant enhancement of photoluminescence quantum yield to near-unity values(95%).Meanwhile,the potassium bromide treatment promoted the growth of homogeneous and smooth film,facilitating the charge carrier injection in the devices.Consequently,the perovskite light-emitting diodes based on this strategy achieve a maximum external quantum efficiency of~21%and maximum luminance of~60,000 cd m^(-2).This work provides a deeper insight into the passivation mechanism of ionic compound additives in perovskite with the solution method.
文摘As an independent sand control unit or a common protective shell of a high-quality screen,the punching screen is the outermost sand retaining unit of the sand control pipe which is used in geothermal well or oil and gas well.However,most screens only consider the influence of the internal sand retaining medium parameters in the sand control performance design while ignoring the influence of the plugging of the punching screen on the overall sand retaining performance of the screen.To explore the clogging mechanism of the punching screen,this paper established the clogging mechanism calculation model of a single punching screen sand control unit by using the computational fluid mechanics-discrete element method(CFD-DEM)combined method.According to the combined motion of particles and fluids,the influence of the internal flow state on particle motion and accumulation was analyzed.The results showed that(1)the clogging process of the punching sand control unit is divided into three stages:initial clogging,aggravation of clogging and stability of clogging.In the initial stage of blockage,coarse particles form a loose bridge structure,and blockage often occurs preferentially at the streamline gathering place below chamfering inside the sand control unit.In the stage of blockage intensification,the particle mass develops into a relatively complete sand bridge,which develops from both ends of the opening to the center of the opening.In the stable plugging stage,the sand deposits show a“fan shape”and form a“V-shaped”gully inside the punching slot element.(2)Under a certain reservoir particle-size distribution,The slit length and opening height have a large influence on the permeability and blockage rate,while the slit width size has little influence on the permeability and blockage rate.The microscopic clogging mechanism and its law of the punching screen prevention unit are proposed in this study,which has some field guidance significance for the design of punching screen and sand prevention selection.
基金The authors are grateful for financial support from the National Key Projects for Fundamental Research and Development of China(2021YFA1500803)the National Natural Science Foundation of China(51825205,52120105002,22102202,22088102,U22A20391)+1 种基金the DNL Cooperation Fund,CAS(DNL202016)the CAS Project for Young Scientists in Basic Research(YSBR-004).
文摘Photocatalysis,a critical strategy for harvesting sunlight to address energy demand and environmental concerns,is underpinned by the discovery of high-performance photocatalysts,thereby how to design photocatalysts is now generating widespread interest in boosting the conversion effi-ciency of solar energy.In the past decade,computational technologies and theoretical simulations have led to a major leap in the development of high-throughput computational screening strategies for novel high-efficiency photocatalysts.In this viewpoint,we started with introducing the challenges of photocatalysis from the view of experimental practice,especially the inefficiency of the traditional“trial and error”method.Sub-sequently,a cross-sectional comparison between experimental and high-throughput computational screening for photocatalysis is presented and discussed in detail.On the basis of the current experimental progress in photocatalysis,we also exemplified the various challenges associated with high-throughput computational screening strategies.Finally,we offered a preferred high-throughput computational screening procedure for pho-tocatalysts from an experimental practice perspective(model construction and screening,standardized experiments,assessment and revision),with the aim of a better correlation of high-throughput simulations and experimental practices,motivating to search for better descriptors.
基金This work was funded by National Natural Science Foundation of China(32272279)the Key R&D project of Qingdao Science and Technology Plan(22-3-3-hygg-29-hy).
文摘Alpha-lactalbumin(α-LA)is a major whey protein found in breast milk and plays a crucial role in the growth and development of infants.In this study,Bacillus subtilis RIK1285 harboring AprE signal peptide(SP)was selected as the original strain for the production ofα-LA.It was found thatα-LA was identified in the pellet after ultrasonic disruption and centrifugation instead of in the fermentation supernatant.The original strain most likely only producedα-LA intracellular,but not extracellular.To improve the expression and secretion ofα-LA in RIK1285,a library of 173 homologous SPs from the B.subtilis 168 genome was fused with target LALBA gene in the pBE-S vector and expressed extracellularly in RIK1285.SP YjcN was determined to be the best signal peptide.Bands in supernatant were observed by sodium dodecyl sulfate-polyacrylamide gel electrophoresis and purified by nickel column to calculate the highest yield signal peptide.In addition,different promoters(P_(aprE),P_(43),and P_(glv))were compared and applied.The results indicated that the strain RIK1285-pBE-P_(glv)-YjcN-LALBA had the highestα-LA yield,reaching 122.04μg/mL.This study demonstrates successful expression and secretion of humanα-LA in B.subtilis and establishes a foundation for simulating breast milk for infant formulas and developing bioengineered milk.
基金funded by National Natural Science Foundation of China(21868003)Bama County Program for Talents in Science and Technology(BaRenKe20210045).
文摘The traditional nutritional and medical hemp(Cannabis sativa L.)seed protein were explored for the discovery and directional preparation of new xanthine oxidase inhibitory(XOI)peptides by structure-based virtual screening,compound synthesis,in vitro bioassay and proteolysis.Six subtypes of hemp seed edestin and albumin were in silico hydrolyzed by 29 proteases,and 192 encrypted bioactive peptides were screened out.Six peptides showed to be XOI peptides,of which four(about 67%)were released by elastase hydrolysis.The peptide DDNPRRFY displayed the highest XOI activity(IC50=(2.10±0.06)mg/mL),acting as a mixed inhibitor.The pancreatic elastase directionally prepared XOI hemp seed protein hydrolysates,from which 6 high-abundance XOI peptides encrypted 3 virtually-screened ones including the DDNPRRFY.The novel outstanding hemp seed protein-derived XOI peptides and their virtual screening and directed preparation methods provide a promising and applicable approach to conveniently and efficiently explore food-derived bioactive peptides.
基金financially supported by the National Natural Science Foundation of China (grant Nos.42004103,42374149)Sichuan Science and Technology Program (grant No.2023NSFSC0257)CNPC Innovation Found (2022DQ02-0306)。
文摘When seismic waves propagate through the geological formation,there is a significant loss of energy and a decrease in imaging resolution,because of the viscoacoustic properties of subsurface medium.This profoundly impacts seismic wavefield propagation,imaging and interpretation.To accurately image the true structure of subsurface medium,the consensus among geophysicists is to no longer treat subsurface medium as ideal homogeneous medium,but rather to incorporate the viscoacoustic properties of subsurface medium.Based on the generalized screen propagator using conventional acoustic wave equation(acoustic GSP),our developed method introduces viscoacoustic compensation strategy,and derives a one-way wave generalized screen propagator based on time-fractional viscoacoustic wave equation(viscoacoustic GSP).In numerical experiments,we conducted tests on two-dimensional multi-layer model and the Marmousi model.When comparing with the acoustic GSP using the acoustic data,we found that the imaging results of the viscoacoustic GSP using the viscoacoustic data showed a significant attenuation compensation effect,and achieved imaging results for both algorithms were essentially consistent.However,the imaging results of acoustic GSP using viscoacoustic data showed significant attenuation effects,especially for deep subsurface imaging.This indicates that we have proposed an effective method to compensate the attenuated seismic wavefield.Our application on a set of real seismic data demonstrated that the imaging performance of our proposed method in local areas surpassed that of the conventional acoustic GSP.This suggests that our proposed method holds practical value and can more accurately image real subsurface structures while enhancing imaging resolution compared with the conventional acoustic GSP.Finally,with respect to computational efficiency,we gathered statistics on running time to compare our proposed method with conventional Q-RTM,and it is evident that our method exhibits higher computational efficiency.In summary,our proposed viscoacoustic GSP method takes into account the true properties of the medium,still achieves migration results comparable to conventional acoustic GSP.
基金partially sponsored by the Development and Reform Commission of Ningbo Municipality(Ningbo Municipal Engineering Research Centre for Solid Carbonaceous Wastes Processing and Utilization Technologies)the National Natural Science Foundation Youth Science Fund Project(52203300),the National Natural Science Foundation of China(22308195)+4 种基金the Natural Science Foundation of Shandong Province(ZR2023QB237)Ningbo Science and Technologies Innovation 2025 Major Special Project(2018B10027)The Zhejiang Provincial Department of Science and Technology is acknowledged for sponsorship under its Provincial Key Laboratory Program(2020E10018)Ningbo Bureau of Science and Technology is also thanked for its support to the Key Laboratory of Clean Energy Conversion TechnologiesThe University of Nottingham Ningbo China provides the first author with a full scholarship。
文摘Dual-atom catalysts(DACs)have emerged as potential catalysts for effective electroreduction of CO_(2)due to their high atom utilization efficiency and multiple active sites.However,the screening of DACs remains a challenge due to the large number of possible combinations,making exhaustive experimental or computational screening a daunting task.In this study,a density functional theory(DFT)-based machine learning(ML)-accelerated(DFT-ML)hybrid approach was developed to test a set of 406 dual transition metal catalysts on N-doped graphene(NG)for the electroreduction of CO_(2)to HCOOH.The results showed that the ML algorithms can successfully capture the relationship between the descriptors of the DACs(inputs)and the limiting potential for HCOOH generation(output).Of the four ML algorithms studied in this work,the feedforward neural network model achieved the highest prediction accuracy(the highest correlation coefficient(R^(2))of 0.960 and the lowest root mean square error(RMSE)of 0.319 eV on the test set)and the predicted results were verified by DFT calculations with an average absolute error of 0.14 eV.The DFT-ML approach identified Co-Co-NG and Ir-Fe-NG as the most active and stable electrocatalysts for the electrochemical reduction of CO_(2)to HCOOH.The DFT-ML hybrid approach exhibits exceptional prediction accuracy while enabling a significant reduction in screening time by an impressive 64%compared to conventional DFT-only calculations.These results demonstrate the immense potential of using ML methods to accelerate the screening and rational design of efficient catalysts for various energy and environmental applications.
基金Outstanding Youth Foundation of Hunan Provincial Department of Education(Grant No.22B0911)。
文摘In this paper,we introduce the censored composite conditional quantile coefficient(cC-CQC)to rank the relative importance of each predictor in high-dimensional censored regression.The cCCQC takes advantage of all useful information across quantiles and can detect nonlinear effects including interactions and heterogeneity,effectively.Furthermore,the proposed screening method based on cCCQC is robust to the existence of outliers and enjoys the sure screening property.Simulation results demonstrate that the proposed method performs competitively on survival datasets of high-dimensional predictors,particularly when the variables are highly correlated.
