Alcohol oxidation is a widely used green chemical reaction.The reaction process produces flammable and explosive hydrogen,so the design of the reactor must meet stringent safety requirements.Based on the limited exper...Alcohol oxidation is a widely used green chemical reaction.The reaction process produces flammable and explosive hydrogen,so the design of the reactor must meet stringent safety requirements.Based on the limited experimental data,utilizing the traditional numerical method of computational fluid dynamics(CFD)to simulate the gas-liquid two-phase flow reactor can mitigate the risk of danger under varying working conditions.However,the calculation process is highly time-consuming.Therefore,by integrating process simulation,computational fluid dynamics,and deep learning technologies,an intelligent hybrid chemical model based on machine learning was proposed to expedite CFD calculations,enhance the prediction of flow fields,conversion rates,and concentrations inside the reactor,and offer insights for designing and optimizing the reactor for the alcohol oxidation system.The results show that the hybrid model based on the long and short-term memory neural network achieves 99.8%accuracy in conversion rate prediction and 99.9%accuracy in product concentration prediction.Through validation,the hybrid model is accelerated by about 360 times compared with instrumental analysis in conversion rate prediction and about 45 times compared with CFD calculation in concentration distribution prediction.This hybrid model can quickly predict the conversion rate and product concentration distribution in the gas-liquid two-phase flow reactor and provide a model reference for fast prediction and accurate control in the actual chemical production process.展开更多
Objective Chronic obstructive pulmonary disease(COPD)is a major health concern in northwest China;however,the impact of particulate matter(PM)exposure during sand-dust storms(SDS)remains poorly understood.Therefore,th...Objective Chronic obstructive pulmonary disease(COPD)is a major health concern in northwest China;however,the impact of particulate matter(PM)exposure during sand-dust storms(SDS)remains poorly understood.Therefore,this study aimed to investigate the association between PM exposure on SDS days and COPD hospitalization risk in arid regions.Methods Data on daily COPD hospitalizations were collected from 323 hospitals from 2018 to 2022,along with the corresponding air pollutant and meteorological data for each city in Gansu Province.Employing a space-time-stratified case-crossover design and conditional Poisson regression,we analyzed 265,379 COPD hospitalizations.Results PM exposure during SDS days significantly increased COPD hospitalization risk[relative risk(RR)for PM2.5,lag 3:1.028,95%confidence interval(CI):1.021–1.034],particularly among men and the elderly,and during the cold season.The burden of PM exposure on COPD hospitalization was substantially high in Northwest China,especially in the arid and semi-arid regions.Conclusion Our findings revealed a positive correlation between PM exposure during SDS episodes and elevated hospitalization rates for COPD in arid and semi-arid zones in China.This highlights the urgency of developing region-specific public health strategies to address adverse respiratory outcomes associated with SDS-related air quality deterioration.展开更多
The effects of microstructure inhomogeneity on the mechanical properties of different zones in TA15 electron beam welded joints were investigated using a micromechanics-based finite element method.Considering the inde...The effects of microstructure inhomogeneity on the mechanical properties of different zones in TA15 electron beam welded joints were investigated using a micromechanics-based finite element method.Considering the indentation size effect,the mechanical properties for constituent phases of the base metal(BM) and heat affected zone(HAZ) were determined by the instrumented nano-indentation test.The macroscopic mechanical properties of BM and HAZ obtained from the tensile test agree well with the numerical results.The incompatible deformation between the constituent phases tends to localize along the softer primary phase a where failure usually initiates in form of localized plastic strain.Compared with the BM,the mechanical properties of constituent phases in the HAZ differ substantially,leading to more serious strain localization behavior.展开更多
For the stress-constrained topology optimization of a turbine disk under centrifugal loads,the jagged boundaries of the mesh and the gray densities on the solid/void interfaces could make the calculated stress field i...For the stress-constrained topology optimization of a turbine disk under centrifugal loads,the jagged boundaries of the mesh and the gray densities on the solid/void interfaces could make the calculated stress field inconsistent with the actual value.It may result in overestimating the maximum stress and thus affect the effectiveness of stress constraints.This paper proposes a new method for predicting the maximum stress to overcome the difficulty.In the process,a predicted density is newly defined to obtain stable boundaries with thin layers of gray elements,a transition factor is innovatively proposed to evaluate the effects of intermediate-density elements,two different stiffness penalty schemes are flexibly used to calculate the elastic modulus of elements,and a linear stress penalty is further adopted to relax the stress field of the structure.The proposed approach for predicting the maximum stress value is verified by the analysis of a structure with smooth boundaries and the topology optimization of a turbine disk.An updating scheme of the stress constraint in the topology optimization is also developed using the predicted maximum stress.Some key ingredients affecting the optimization results are discussed in detail.The results prove the effectiveness and efficacy of the proposed maximum stress prediction and developed stress constraint methods.展开更多
Diabetes is a pervasive and serious global health issue.According to the International Diabetes Federation report,463 million adults worldwide were living with diabetes in 2019,and this number is projected to reach 70...Diabetes is a pervasive and serious global health issue.According to the International Diabetes Federation report,463 million adults worldwide were living with diabetes in 2019,and this number is projected to reach 700 million in 2045^([1]).展开更多
The dielectric effect is receiving increasing interest in the study of resistivity logging. Several recent findings have proven that the dielectric effect can cause negative imaginary signals on the array induction lo...The dielectric effect is receiving increasing interest in the study of resistivity logging. Several recent findings have proven that the dielectric effect can cause negative imaginary signals on the array induction logging. However, very few researches discuss the dielectric effect on the triaxial induction logging which is a novel technology in solving anisotropy problem. In this paper, we investigate the effect of large dielectric constants on a basic triaxial induction tool in a 1-D homogenous earth formation. The simulation model is derived from Maxwell equation and calculated by wave number integration. Sufficient simulations have been done. We performed an asymptotic analysis of the dielectric effect within the low-freq limit, yielding interesting observations on the dielectric effect with respect to frequency, spacing, and anisotropy. Those findings provide important and useful guidance for researchers to study on the dielectric effect on the triaxial induction logging.展开更多
The development of heterogeneous catalysts with well-defined uniform isolated or multiple active sites is of great importance for understanding catalytic performances and studying reaction mechanisms.Herein,we present...The development of heterogeneous catalysts with well-defined uniform isolated or multiple active sites is of great importance for understanding catalytic performances and studying reaction mechanisms.Herein,we present a CoCu dual-atom catalyst(CoCu-DAC)where bonded Co-Cu dual-atom sites are embedded in N-doped carbon matrix with a well-defined Co(OH)CuN_(6)structure.The CoCu-DAC exhibits higher catalytic activity and selectivity than the Co single-atom catalyst(Co-SAC)and Cu single-atom catalyst(CuSAC)counterparts in the catalytic oxidative esterification of alcohols and a variety of methyl and alkyl esters have been successfully synthesized.Kinetic studies reveal that the activation energy(29.7 kJ mol^(-1))over CoCu-DAC is much lower than that over Co-SAC(38.4 kJ mol^(-1))and density functional theory(DFT)studies disclose that two different mechanisms are regulated over CoCu-DAC and Co-SAC/Cu-SAC in three-step esterification of alcohols.The bonded Co-Cu and adjacent N species efficiently catalyze the elementary reactions of alcohol dehydrogenation,O2activation and ester formation,respectively.The stepwise alkoxy pathway(O-H and C-H scissions)is preferred for both alcohol dehydrogenation and ester formation over CoCu-DAC,while the progressive hydroxylalkyl pathway(C-H and O-H scissions)for alcohol dehydrogenation and simultaneous hemiacetal dehydrogenation are favored over Co-SAC and Cu-SAC.Characteristic peaks in the Fourier transform infrared spectroscopy analysis may confirm the formation of the metal-C intermediate and the hydroxylalkyl pathway over Co-SAC.展开更多
The plateau region is conventionally regarded as a“clean land”with minimal environmental pollution,leading to scarce research on the distribution of emerging pollutants such as per-and polyfluoroalkyl substances(PFA...The plateau region is conventionally regarded as a“clean land”with minimal environmental pollution,leading to scarce research on the distribution of emerging pollutants such as per-and polyfluoroalkyl substances(PFAS)and their effects on the health of plateau inhabitants.To understand that,we studied participants from two representative towns in Gannan Tibetan Autonomous Prefecture,Gansu Province,China.Lung function parameters(FVC%,FEV1%,and FEV1/FVC)were measured,while PFAS concentrations in urine and indoor dust were analyzed using liquid chromatography-tandem mass spectrometry(LC-MS/MS).We measured the levels of 8-hydroxy-2′-deoxyguanosine(8-OHdG),8-epiprostaglandin F2α(8-epi-PGF2α),and malondialdehyde(MDA)in urine.The results demonstrated a preponderance of short-chain PFAS in urine,with PFBS,PFPeA,and PFBA showing the highest detection rates.PFBA had the highest median concentration at 0.47 ng/mL.Similarly,in indoor dust,PFBA was the most frequently detected,followed by PFOA,with median concentrations of 0.56 and 0.44 ng/g,respectively.Multiple PFAS compounds showed significant inverse correlations with FVC%and FEV1%.PFAS exposure was associated with elevated oxidative stress biomarker levels(8-OHdG,8-epi-PGF2α,and MDA),and their synergistic interaction aggravated the decline in lung function.This research provides valuable evidence of PFAS exposure patterns in the plateau population,highlighting the dominance of short-chain PFAS compounds and the concerning link between PFAS exposure and impaired lung function.展开更多
Most of our learning comes from other people or from our own experience. For instance, when a taxi driver is seeking passengers on an unknown road in a large city, what should the driver do？ Alternatives include crui...Most of our learning comes from other people or from our own experience. For instance, when a taxi driver is seeking passengers on an unknown road in a large city, what should the driver do？ Alternatives include cruising around the road or waiting for a time period at the roadside in the hopes of finding a passenger or just leaving for another road enroute to a destination he knows （e.g., hotel taxi rank）？ This is an interesting problem that arises everyday in cities all over the world. There could be different answers to the question poised above, but one fundamental problem is how the driver learns about the likelihood of finding passengers on a road that is new to him （as he has not picked up or dropped off passengers there before）. Our observation from large scale taxi driver trace data is that a driver not only learns from his own experience but through interactions with other drivers. In this paper, we first formally define this problem as socialized information learning （SIL）, second we propose a framework including a series of models to study how a taxi driver gathers and learns information in an uncertain environment through the use of his social network. Finally, the large scale real life data and empirical experiments confirm that our models are much more effective, efficient and scalable that prior work on this problem.展开更多
With advancements in agricultural technology,the full mechanization of rice straw wheat planting has been achieved.However,issues such as missed seeding,uneven row spacing,and poor uniformity of row replenishment ofte...With advancements in agricultural technology,the full mechanization of rice straw wheat planting has been achieved.However,issues such as missed seeding,uneven row spacing,and poor uniformity of row replenishment often arise due to wheel slippage in wheeled wheat seeders.These problems manual replanting after emergence,reducing efficiency and increasing labor costs.To address these challenges,a speed-adaptive wheat seeding control system based on speed radar was developed.This system comprises a pneumatic wheat seeding device,an automatic speed-following control system,a human-machine interface,and a stepper motor.Leveraging an embedded controller,the system dynamically adjusts motor speed based on real-time forward speed to ensure precise seeding.Using fuzzy PID control,the system dynamically adjusts motor speed,achieving row spacing consistency below 3.9%and seeding stability within 1.3%,even at varying speeds.This system addresses critical challenges in precision agriculture,enhancing planting efficiency and reducing labor costs.This innovation enhances planting efficiency,reduces labor costs,and ensures adaptability to varying tractor speeds,meeting the precision requirements of wheat planting.展开更多
Direct synthesis of high-value-added chemicals from low-carbon molecules is of great research importance.The C(sp^(3))–H bonds in alkanes exhibit a high bond dissociation energy and a very low polarity;consequently,a...Direct synthesis of high-value-added chemicals from low-carbon molecules is of great research importance.The C(sp^(3))–H bonds in alkanes exhibit a high bond dissociation energy and a very low polarity;consequently,achieving highly selective synthesis of esters through alkoxy carbonylation in heterogeneous catalysis is a particularly challenging process.Herein,we describe the immobilization of a single-atom palladium catalyst supported by porous organic polymers for highly selective ester formation in cycloalkane carbonylation,which achieves a selectivity as high as 82% and a benzyl alcohol conversion of up to 96%.Various catalytic characterization methods,including XRD,XPS,TEM,SEM,and FTIR,indicate that palladium species are uniformly distributed in the polymer.This work suggests a promising method for the design of hybrid catalytic systems and offers meaningful insights into the development of bifunctional catalysts for selective alkoxy carbonylation.展开更多
This study investigated the combined effects of fine particulate matter(PM_(2.5))exposure and ambient oxygen(O_(2))availability on peripheral artery disease(PAD)hospitalizations in Gansu Province,China,from 2018 to 20...This study investigated the combined effects of fine particulate matter(PM_(2.5))exposure and ambient oxygen(O_(2))availability on peripheral artery disease(PAD)hospitalizations in Gansu Province,China,from 2018 to 2022(N=38,514).A time-series case-crossover design with conditional logistic regression assessed short-term exposure to daily PM_(2.5) and its major chemical components(black carbon[BC],organic carbon[OC],sulfate[SO_(4)^(2-)],nitrate[NO_(3)^(-)],ammonium[NH_(4)^(+)],and chloride[Cl^(-)]).Atmospheric O_(2) levels were estimated based on altitude,temperature,and humidity.Short-term exposure to PM_(2.5) was associated with an increased risk of PAD hospitalization,notably at lag 1(odds ratio[OR]=1.003;95% confidence interval[CI]:1.002-1.004).Carbonaceous pollutants exhibited delayed effects,with peak associations at lag 6 for BC(OR=1.069;95%CI:1.035-1.105)and OC(OR=1.028;95%CI:1.011-1.050),per 1μg/m^(3) increase.Secondary inorganic aerosols showed acute effects at lag 1:Cl-(OR=1.107;95%CI:1.063-1.150),NH_(4)^(+)(OR=1.040;95%CI:1.022-1.060),SO_(4)^(2-)(OR=1.025;95%CI:1.015-1.036),and NO3-(OR=1.030;95%CI:1.018-1.042),per 1μg/m3 increase.Nonlinear exposure-response curves revealed a stronger PAD risk under lower O_(2) conditions(<18%).The PM_(2.5)-related risk was amplified in high-altitude residents(>1500 m),older adults(>60 years),females,emergency admissions,and during the cold season.These findings suggest that ambient PM_(2.5) and lower O_(2) levels interact synergistically to elevate PAD hospitalization risk,emphasizing the urgent need for region-specific air quality controls and targeted health protection strategies.展开更多
A gradual increase in avian influenza outbreaks has been found in recent years.It is highly possible to trigger the next human pandemic due to the characteristics of antigenic drift and antigenic shift in avian influe...A gradual increase in avian influenza outbreaks has been found in recent years.It is highly possible to trigger the next human pandemic due to the characteristics of antigenic drift and antigenic shift in avian influenza virus(AIV).Although great improvements in understanding influenza viruses and the associated diseases have been unraveled,our knowledge of how these viruses impact the gut microbiome of both poultry and humans,as well as the underlying mechanisms,is still improving.The“One Health”approach shows better vitality in monitoring and mitigating the risk of avian influenza,which requires a multi-sectoral effort and highlights the interconnection of human health with environmental sustainability and animal health.Therefore,monitoring the gut microbiome may serve as a sentinel for protecting the common health of the environment,animals,and humans.This review summarizes the interactions between AIV infection and the gut microbiome of poultry and humans and their potential mechanisms.With the presented suggestions,we hope to address the current major challenges in the surveillance and prevention of microbiome-related avian influenza with the“One Health”approach.展开更多
The traditional recognition algorithm is prone to miss detection targets in the complex tea garden environment,and it is difficult to satisfy the requirement for tea bud recognition accuracy and efficiency.In this stu...The traditional recognition algorithm is prone to miss detection targets in the complex tea garden environment,and it is difficult to satisfy the requirement for tea bud recognition accuracy and efficiency.In this study,the YOLOv7 model was developed to improve tea bud recognition accuracy for some extreme tea garden scenarios.In the improved model,a lightweight MobileNetV3 network is adopted to replace the original backbone network,which reduces the size of the model and improves detection efficiency.The convolutional block attention module is introduced to enhance the attention to the features of small and occluded tea buds,suppressing the interference of the complex tea garden environment on tea bud recognition and strengthening the feature extraction capability of the recognition model.Moreover,to further improve recognition accuracy for dense and occlusive scenarios,the soft non-maximum suppression strategy is integrated into the recognition model.Experimental results show that the improved YOLOv7 model has the precision,recall,and mean average precision(mAP)values of 88.3%,87.4%,and 88.5%,respectively.Compared with the Faster R-CNN,SSD,and original YOLOv7 algorithms,the mAP of the improved YOLOv7 model is increased by 7.4,7.9,and 3.9 percentage points,respectively,and its recognition speed is also promoted by 94.9%,46.2%,and 16.9%.The proposed model can rapidly and accurately identify the tea buds in multiple complex tea garden scenarios-such as dense distribution,being close to the background color,and mutual occlusion-with high generalization and robustness,which can provide theoretical and technical support for the recognition of tea-picking robots.展开更多
基金the support from the National Natural Science Foundation of China(22478429)the Special Project Fund of Taishan-Scholars(tsqn202408101)+3 种基金the Natural Science Foundation of Shandong Province(ZR2023YQ009)CNPC Innovation Found(2024DQ02-0504)Fundamental Research Funds for the Central Universities,Ocean University of China(202364004)the State Key Laboratory of Heavy Oil Processing(SKLHOP202403003)。
文摘Alcohol oxidation is a widely used green chemical reaction.The reaction process produces flammable and explosive hydrogen,so the design of the reactor must meet stringent safety requirements.Based on the limited experimental data,utilizing the traditional numerical method of computational fluid dynamics(CFD)to simulate the gas-liquid two-phase flow reactor can mitigate the risk of danger under varying working conditions.However,the calculation process is highly time-consuming.Therefore,by integrating process simulation,computational fluid dynamics,and deep learning technologies,an intelligent hybrid chemical model based on machine learning was proposed to expedite CFD calculations,enhance the prediction of flow fields,conversion rates,and concentrations inside the reactor,and offer insights for designing and optimizing the reactor for the alcohol oxidation system.The results show that the hybrid model based on the long and short-term memory neural network achieves 99.8%accuracy in conversion rate prediction and 99.9%accuracy in product concentration prediction.Through validation,the hybrid model is accelerated by about 360 times compared with instrumental analysis in conversion rate prediction and about 45 times compared with CFD calculation in concentration distribution prediction.This hybrid model can quickly predict the conversion rate and product concentration distribution in the gas-liquid two-phase flow reactor and provide a model reference for fast prediction and accurate control in the actual chemical production process.
基金supported by the Innovative Talent Project of Lanzhou City,Lanzhou Science and Technology Bureau(2022-RC-42)the Fundamental Research Funds for the Central Universities,Lanzhou University,China(lzujbky-2021-ey07,lzujbky-2024-it59,lzujbky-2025-it29)the Gansu Province Postgraduate Innovation Star Program(2025CXZX-018).
文摘Objective Chronic obstructive pulmonary disease(COPD)is a major health concern in northwest China;however,the impact of particulate matter(PM)exposure during sand-dust storms(SDS)remains poorly understood.Therefore,this study aimed to investigate the association between PM exposure on SDS days and COPD hospitalization risk in arid regions.Methods Data on daily COPD hospitalizations were collected from 323 hospitals from 2018 to 2022,along with the corresponding air pollutant and meteorological data for each city in Gansu Province.Employing a space-time-stratified case-crossover design and conditional Poisson regression,we analyzed 265,379 COPD hospitalizations.Results PM exposure during SDS days significantly increased COPD hospitalization risk[relative risk(RR)for PM2.5,lag 3:1.028,95%confidence interval(CI):1.021–1.034],particularly among men and the elderly,and during the cold season.The burden of PM exposure on COPD hospitalization was substantially high in Northwest China,especially in the arid and semi-arid regions.Conclusion Our findings revealed a positive correlation between PM exposure during SDS episodes and elevated hospitalization rates for COPD in arid and semi-arid zones in China.This highlights the urgency of developing region-specific public health strategies to address adverse respiratory outcomes associated with SDS-related air quality deterioration.
基金Project(51875402)supported by the National Natural Science Foundation of China
文摘The effects of microstructure inhomogeneity on the mechanical properties of different zones in TA15 electron beam welded joints were investigated using a micromechanics-based finite element method.Considering the indentation size effect,the mechanical properties for constituent phases of the base metal(BM) and heat affected zone(HAZ) were determined by the instrumented nano-indentation test.The macroscopic mechanical properties of BM and HAZ obtained from the tensile test agree well with the numerical results.The incompatible deformation between the constituent phases tends to localize along the softer primary phase a where failure usually initiates in form of localized plastic strain.Compared with the BM,the mechanical properties of constituent phases in the HAZ differ substantially,leading to more serious strain localization behavior.
基金co-supported by the National Natural Science Foundation of China(Nos.52005421 and 12102375)the Natural Science Foundation of Fujian Province of China(No.2020J05020)+2 种基金the National Science and Technology Major Project,China(No.J2019-I-0013-0013)the Fundamental Research Funds for the Central Universities,China(No.20720210090)the project funded by the China Postdoctoral Science Foundation(Nos.2020M682584 and 2021T140634).
文摘For the stress-constrained topology optimization of a turbine disk under centrifugal loads,the jagged boundaries of the mesh and the gray densities on the solid/void interfaces could make the calculated stress field inconsistent with the actual value.It may result in overestimating the maximum stress and thus affect the effectiveness of stress constraints.This paper proposes a new method for predicting the maximum stress to overcome the difficulty.In the process,a predicted density is newly defined to obtain stable boundaries with thin layers of gray elements,a transition factor is innovatively proposed to evaluate the effects of intermediate-density elements,two different stiffness penalty schemes are flexibly used to calculate the elastic modulus of elements,and a linear stress penalty is further adopted to relax the stress field of the structure.The proposed approach for predicting the maximum stress value is verified by the analysis of a structure with smooth boundaries and the topology optimization of a turbine disk.An updating scheme of the stress constraint in the topology optimization is also developed using the predicted maximum stress.Some key ingredients affecting the optimization results are discussed in detail.The results prove the effectiveness and efficacy of the proposed maximum stress prediction and developed stress constraint methods.
基金The Central Universities,Lanzhou University,China [lzujbky-2021-ey07]the innovative talent project of Lanzhou city[Lanzhou science and technology bureau, 2022-RC-42 to BL]Gansu Province Young Doctoral Fund Project [2021QB005]
文摘Diabetes is a pervasive and serious global health issue.According to the International Diabetes Federation report,463 million adults worldwide were living with diabetes in 2019,and this number is projected to reach 700 million in 2045^([1]).
文摘The dielectric effect is receiving increasing interest in the study of resistivity logging. Several recent findings have proven that the dielectric effect can cause negative imaginary signals on the array induction logging. However, very few researches discuss the dielectric effect on the triaxial induction logging which is a novel technology in solving anisotropy problem. In this paper, we investigate the effect of large dielectric constants on a basic triaxial induction tool in a 1-D homogenous earth formation. The simulation model is derived from Maxwell equation and calculated by wave number integration. Sufficient simulations have been done. We performed an asymptotic analysis of the dielectric effect within the low-freq limit, yielding interesting observations on the dielectric effect with respect to frequency, spacing, and anisotropy. Those findings provide important and useful guidance for researchers to study on the dielectric effect on the triaxial induction logging.
基金supported by the National Natural Science Foundation of China(22372180 and 22202216)the Natural Science Foundation of Gansu Province and the Major Project of Gansu Province(21JR7RA096 and 21ZD4WA021)+2 种基金the Youth Innovation Promotion Association(2023441)Lanzhou Institute of Chemical Physics(LICP)Cooperation Foundation for Young Scholars(HZJJ21-06)Key Program of the Lanzhou Institute of Chemical Physics(KJZLZD-2)。
文摘The development of heterogeneous catalysts with well-defined uniform isolated or multiple active sites is of great importance for understanding catalytic performances and studying reaction mechanisms.Herein,we present a CoCu dual-atom catalyst(CoCu-DAC)where bonded Co-Cu dual-atom sites are embedded in N-doped carbon matrix with a well-defined Co(OH)CuN_(6)structure.The CoCu-DAC exhibits higher catalytic activity and selectivity than the Co single-atom catalyst(Co-SAC)and Cu single-atom catalyst(CuSAC)counterparts in the catalytic oxidative esterification of alcohols and a variety of methyl and alkyl esters have been successfully synthesized.Kinetic studies reveal that the activation energy(29.7 kJ mol^(-1))over CoCu-DAC is much lower than that over Co-SAC(38.4 kJ mol^(-1))and density functional theory(DFT)studies disclose that two different mechanisms are regulated over CoCu-DAC and Co-SAC/Cu-SAC in three-step esterification of alcohols.The bonded Co-Cu and adjacent N species efficiently catalyze the elementary reactions of alcohol dehydrogenation,O2activation and ester formation,respectively.The stepwise alkoxy pathway(O-H and C-H scissions)is preferred for both alcohol dehydrogenation and ester formation over CoCu-DAC,while the progressive hydroxylalkyl pathway(C-H and O-H scissions)for alcohol dehydrogenation and simultaneous hemiacetal dehydrogenation are favored over Co-SAC and Cu-SAC.Characteristic peaks in the Fourier transform infrared spectroscopy analysis may confirm the formation of the metal-C intermediate and the hydroxylalkyl pathway over Co-SAC.
基金supported by the Innovation and Entrepreneurship Talent Project of Lanzhou(2022-RC-42)a major Project of the Key R&D Programme of Ningxia Hui Autonomous Region(2022BEG02027)the Fundamental Research Funds for the Central Universities,Lanzhou University,China(lzujbky-2021-ey07).
文摘The plateau region is conventionally regarded as a“clean land”with minimal environmental pollution,leading to scarce research on the distribution of emerging pollutants such as per-and polyfluoroalkyl substances(PFAS)and their effects on the health of plateau inhabitants.To understand that,we studied participants from two representative towns in Gannan Tibetan Autonomous Prefecture,Gansu Province,China.Lung function parameters(FVC%,FEV1%,and FEV1/FVC)were measured,while PFAS concentrations in urine and indoor dust were analyzed using liquid chromatography-tandem mass spectrometry(LC-MS/MS).We measured the levels of 8-hydroxy-2′-deoxyguanosine(8-OHdG),8-epiprostaglandin F2α(8-epi-PGF2α),and malondialdehyde(MDA)in urine.The results demonstrated a preponderance of short-chain PFAS in urine,with PFBS,PFPeA,and PFBA showing the highest detection rates.PFBA had the highest median concentration at 0.47 ng/mL.Similarly,in indoor dust,PFBA was the most frequently detected,followed by PFOA,with median concentrations of 0.56 and 0.44 ng/g,respectively.Multiple PFAS compounds showed significant inverse correlations with FVC%and FEV1%.PFAS exposure was associated with elevated oxidative stress biomarker levels(8-OHdG,8-epi-PGF2α,and MDA),and their synergistic interaction aggravated the decline in lung function.This research provides valuable evidence of PFAS exposure patterns in the plateau population,highlighting the dominance of short-chain PFAS compounds and the concerning link between PFAS exposure and impaired lung function.
基金This research was supported by the T-SET Univer- sity Transportation Center sponsored by the US Department of Transporta- tion （DTRT12-G-UTCll）, and Huawei Corporation （YBCB2009041-27）, and the Singapore National Research Foundation under its International Re- search Centre @ Singapore Funding Initiative and administered by the IDM Programme Office. This research was supported in part by the National Basic Research Program of China （973 Program） （2012CB316400）, in part by the National Natural Science Foundation of China （Grant No. 61303160）, and in part by China Postdoctoral Science Foundation （2013M530739）.
文摘Most of our learning comes from other people or from our own experience. For instance, when a taxi driver is seeking passengers on an unknown road in a large city, what should the driver do？ Alternatives include cruising around the road or waiting for a time period at the roadside in the hopes of finding a passenger or just leaving for another road enroute to a destination he knows （e.g., hotel taxi rank）？ This is an interesting problem that arises everyday in cities all over the world. There could be different answers to the question poised above, but one fundamental problem is how the driver learns about the likelihood of finding passengers on a road that is new to him （as he has not picked up or dropped off passengers there before）. Our observation from large scale taxi driver trace data is that a driver not only learns from his own experience but through interactions with other drivers. In this paper, we first formally define this problem as socialized information learning （SIL）, second we propose a framework including a series of models to study how a taxi driver gathers and learns information in an uncertain environment through the use of his social network. Finally, the large scale real life data and empirical experiments confirm that our models are much more effective, efficient and scalable that prior work on this problem.
基金supported by the National Key Research and Development Program Sub-Theme Project of China(Grant No:2023YFD1901004)the Anhui Province Key Research and Development Program(Grant No:2023n06020046).
文摘With advancements in agricultural technology,the full mechanization of rice straw wheat planting has been achieved.However,issues such as missed seeding,uneven row spacing,and poor uniformity of row replenishment often arise due to wheel slippage in wheeled wheat seeders.These problems manual replanting after emergence,reducing efficiency and increasing labor costs.To address these challenges,a speed-adaptive wheat seeding control system based on speed radar was developed.This system comprises a pneumatic wheat seeding device,an automatic speed-following control system,a human-machine interface,and a stepper motor.Leveraging an embedded controller,the system dynamically adjusts motor speed based on real-time forward speed to ensure precise seeding.Using fuzzy PID control,the system dynamically adjusts motor speed,achieving row spacing consistency below 3.9%and seeding stability within 1.3%,even at varying speeds.This system addresses critical challenges in precision agriculture,enhancing planting efficiency and reducing labor costs.This innovation enhances planting efficiency,reduces labor costs,and ensures adaptability to varying tractor speeds,meeting the precision requirements of wheat planting.
基金supported by the National Natural Science Foundation of China (U22A20393,22202216)the Lanzhou Institute of Chemical Physics (E40199SR)。
文摘Direct synthesis of high-value-added chemicals from low-carbon molecules is of great research importance.The C(sp^(3))–H bonds in alkanes exhibit a high bond dissociation energy and a very low polarity;consequently,achieving highly selective synthesis of esters through alkoxy carbonylation in heterogeneous catalysis is a particularly challenging process.Herein,we describe the immobilization of a single-atom palladium catalyst supported by porous organic polymers for highly selective ester formation in cycloalkane carbonylation,which achieves a selectivity as high as 82% and a benzyl alcohol conversion of up to 96%.Various catalytic characterization methods,including XRD,XPS,TEM,SEM,and FTIR,indicate that palladium species are uniformly distributed in the polymer.This work suggests a promising method for the design of hybrid catalytic systems and offers meaningful insights into the development of bifunctional catalysts for selective alkoxy carbonylation.
基金supported by Key R&D Program Special of Gansu Province(25YFFA031)the National Natural Science Foundation of China(42275189)+1 种基金Fundamental Research Funds for the Central Universities,Lanzhou University,China(lzujbky-2025-it29)the Postgraduate Innovation Star Program in Gansu Province(2025CXZX-018).
文摘This study investigated the combined effects of fine particulate matter(PM_(2.5))exposure and ambient oxygen(O_(2))availability on peripheral artery disease(PAD)hospitalizations in Gansu Province,China,from 2018 to 2022(N=38,514).A time-series case-crossover design with conditional logistic regression assessed short-term exposure to daily PM_(2.5) and its major chemical components(black carbon[BC],organic carbon[OC],sulfate[SO_(4)^(2-)],nitrate[NO_(3)^(-)],ammonium[NH_(4)^(+)],and chloride[Cl^(-)]).Atmospheric O_(2) levels were estimated based on altitude,temperature,and humidity.Short-term exposure to PM_(2.5) was associated with an increased risk of PAD hospitalization,notably at lag 1(odds ratio[OR]=1.003;95% confidence interval[CI]:1.002-1.004).Carbonaceous pollutants exhibited delayed effects,with peak associations at lag 6 for BC(OR=1.069;95%CI:1.035-1.105)and OC(OR=1.028;95%CI:1.011-1.050),per 1μg/m^(3) increase.Secondary inorganic aerosols showed acute effects at lag 1:Cl-(OR=1.107;95%CI:1.063-1.150),NH_(4)^(+)(OR=1.040;95%CI:1.022-1.060),SO_(4)^(2-)(OR=1.025;95%CI:1.015-1.036),and NO3-(OR=1.030;95%CI:1.018-1.042),per 1μg/m3 increase.Nonlinear exposure-response curves revealed a stronger PAD risk under lower O_(2) conditions(<18%).The PM_(2.5)-related risk was amplified in high-altitude residents(>1500 m),older adults(>60 years),females,emergency admissions,and during the cold season.These findings suggest that ambient PM_(2.5) and lower O_(2) levels interact synergistically to elevate PAD hospitalization risk,emphasizing the urgent need for region-specific air quality controls and targeted health protection strategies.
基金supported by grants from the Central Universities,Lanzhou University,China(lzujbky-2021-ey07)the scientific research project of Lanzhou City(2022-RC-42).
文摘A gradual increase in avian influenza outbreaks has been found in recent years.It is highly possible to trigger the next human pandemic due to the characteristics of antigenic drift and antigenic shift in avian influenza virus(AIV).Although great improvements in understanding influenza viruses and the associated diseases have been unraveled,our knowledge of how these viruses impact the gut microbiome of both poultry and humans,as well as the underlying mechanisms,is still improving.The“One Health”approach shows better vitality in monitoring and mitigating the risk of avian influenza,which requires a multi-sectoral effort and highlights the interconnection of human health with environmental sustainability and animal health.Therefore,monitoring the gut microbiome may serve as a sentinel for protecting the common health of the environment,animals,and humans.This review summarizes the interactions between AIV infection and the gut microbiome of poultry and humans and their potential mechanisms.With the presented suggestions,we hope to address the current major challenges in the surveillance and prevention of microbiome-related avian influenza with the“One Health”approach.
基金financially supported by State Key Laboratory of Tea Biology and Resource Utilization(Grant No.SKLTOF20230123).
文摘The traditional recognition algorithm is prone to miss detection targets in the complex tea garden environment,and it is difficult to satisfy the requirement for tea bud recognition accuracy and efficiency.In this study,the YOLOv7 model was developed to improve tea bud recognition accuracy for some extreme tea garden scenarios.In the improved model,a lightweight MobileNetV3 network is adopted to replace the original backbone network,which reduces the size of the model and improves detection efficiency.The convolutional block attention module is introduced to enhance the attention to the features of small and occluded tea buds,suppressing the interference of the complex tea garden environment on tea bud recognition and strengthening the feature extraction capability of the recognition model.Moreover,to further improve recognition accuracy for dense and occlusive scenarios,the soft non-maximum suppression strategy is integrated into the recognition model.Experimental results show that the improved YOLOv7 model has the precision,recall,and mean average precision(mAP)values of 88.3%,87.4%,and 88.5%,respectively.Compared with the Faster R-CNN,SSD,and original YOLOv7 algorithms,the mAP of the improved YOLOv7 model is increased by 7.4,7.9,and 3.9 percentage points,respectively,and its recognition speed is also promoted by 94.9%,46.2%,and 16.9%.The proposed model can rapidly and accurately identify the tea buds in multiple complex tea garden scenarios-such as dense distribution,being close to the background color,and mutual occlusion-with high generalization and robustness,which can provide theoretical and technical support for the recognition of tea-picking robots.
