The rapid advancement of artificial intelligence(AI)has significantly increased the computational load on data centers.AI-related computational activities consume considerable electricity and result in substantial car...The rapid advancement of artificial intelligence(AI)has significantly increased the computational load on data centers.AI-related computational activities consume considerable electricity and result in substantial carbon emissions.To mitigate these emissions,future data centers should be strategically planned and operated to fully utilize renewable energy resources while meeting growing computational demands.This paper aims to investigate how much carbon emission reduction can be achieved by using a carbonoriented demand response to guide the optimal planning and operation of data centers.A carbon-oriented data center planning model is proposed that considers the carbon-oriented demand response of the AI load.In the planning model,future operation simulations comprehensively coordinate the temporal‒spatial flexibility of computational loads and the quality of service(QoS).An empirical study based on the proposed models is conducted on real-world data from China.The results from the empirical analysis show that newly constructed data centers are recommended to be built in Gansu Province,Ningxia Hui Autonomous Region,Sichuan Province,Inner Mongolia Autonomous Region,and Qinghai Province,accounting for 57%of the total national increase in server capacity.33%of the computational load from Eastern China should be transferred to the West,which could reduce the overall load carbon emissions by 26%.展开更多
Countries around the world have been making efforts to reduce pollutant emissions. However, the response of global black carbon(BC) aging to emission changes remains unclear. Using the Community Atmosphere Model versi...Countries around the world have been making efforts to reduce pollutant emissions. However, the response of global black carbon(BC) aging to emission changes remains unclear. Using the Community Atmosphere Model version 6 with a machine-learning-integrated four-mode version of the Modal Aerosol Module, we quantify global BC aging responses to emission reductions for 2011–2018 and for 2050 and 2100 under carbon neutrality. During 2011–18, global trends in BC aging degree(mass ratio of coatings to BC, R_(BC)) exhibited marked regional disparities, with a significant increase in China(5.4% yr^(-1)), which contrasts with minimal changes in the USA, Europe, and India. The divergence is attributed to opposing trends in secondary organic aerosol(SOA) and sulfate coatings, driven by regional changes in the emission ratios of corresponding coating precursors to BC(volatile organic compounds-VOCs/BC and SO_(2)/BC). Projections under carbon neutrality reveal that R_(BC) will increase globally by 47%(118%) in 2050(2100), with strong convergent increases expected across major source regions. The R_(BC) increase, primarily driven by enhanced SOA coatings due to sharper BC reductions relative to VOCs, will enhance the global BC mass absorption cross-section(MAC) by 11%(17%) in 2050(2100).Consequently, although the global BC burden will decline sharply by 60%(76%), the enhanced MAC partially offsets the magnitude of the decline in the BC direct radiative effect, resulting in the moderation of global BC DRE decreases to 88%(92%) of the BC burden reductions in 2050(2100). This study highlights the globally enhanced BC aging and light absorption capacity under carbon neutrality, thereby partly offsetting the impact of BC direct emission reductions on future changes in BC radiative effects globally.展开更多
In order to explore the reduction pathways of zinc oxide in LiCl molten salt and the optimal process,experiments were conducted in an alumina crucible using metallic lithium as the reducing agent and lithium chloride ...In order to explore the reduction pathways of zinc oxide in LiCl molten salt and the optimal process,experiments were conducted in an alumina crucible using metallic lithium as the reducing agent and lithium chloride molten salt as the reaction medium at 923 K.The study assessed the effects of lithium thermochemical reduction and electrolytic reduction of ZnO.The volatilization behavior of metal oxides in molten salts,the equivalent of a reducing agent,reduction time,amount of molten salt,stirring time,and the method of reduction feed were investigated for their impacts on the reduction yield and product composition.X-ray powder diffraction(XRD)analysis of the products showed that lithium reduction of ZnO not only produced metallic Zn but also formed a LiZn alloy.Electrolytic reduction can be used to obtain the metallic Zn product by controlling the potential below-2.2 V(vs Ag/Ag^(+)).Moreover,sintered oxides and higher electrode potentials could enhance the efficiency of electrolysis.Under the optimal reaction conditions determined experimentally,the lithium reduction experiment achieved a yield of 77.2%after a 12-h test,and the electrolytic reduction reached a yield of 85.4%after a 6-h test.展开更多
In the past decade,financial institutions have invested significant efforts in the development of accurate analytical credit scoring models.The evidence suggests that even small improvements in the accuracy of existin...In the past decade,financial institutions have invested significant efforts in the development of accurate analytical credit scoring models.The evidence suggests that even small improvements in the accuracy of existing credit-scoring models may optimize profits while effectively managing risk exposure.Despite continuing efforts,the majority of existing credit scoring models still include some judgment-based assumptions that are sometimes supported by the significant findings of previous studies but are not validated using the institution’s internal data.We argue that current studies related to the development of credit scoring models have largely ignored recent developments in statistical methods for sufficient dimension reduction.To contribute to the field of financial innovation,this study proposes a Dimension Reduction Assisted Credit Scoring(DRA-CS)method via distance covariance-based sufficient dimension reduction(DCOV-SDR)in Majorization-Minimization(MM)algorithm.First,in the presence of a large number of variables,the DRA-CS method results in greater dimension reduction and better prediction accuracy than the other methods used for dimension reduction.Second,when the DRA-CS method is employed with logistic regression,it outperforms existing methods based on different variable selection techniques.This study argues that the DRA-CS method should be used by financial institutions as a financial innovation tool to analyze high-dimensional customer datasets and improve the accuracy of existing credit scoring methods.展开更多
A method for the rapid reduction of acyl chlorides to aldehydes was developed using pinacolborane(HBpin)as the reducing agent.The method exhibits excellent generality for both aromatic and aliphatic substrates,affordi...A method for the rapid reduction of acyl chlorides to aldehydes was developed using pinacolborane(HBpin)as the reducing agent.The method exhibits excellent generality for both aromatic and aliphatic substrates,affording aldehydes in isolated yields of up to 88%with broad functional group tolerance,including cyano,halogen,alkenyl,ketone,and ester groups.Moreover,the method enables gram-scale aldehyde synthesis and shows high efficiency in reducing in situ generated acyl chlorides,thereby enhancing its synthetic practicality.展开更多
The proliferation of high-dimensional data and the widespread use of complex models present central challenges in contemporary statistics and data science.Dimension reduction and model checking,as two foundational pil...The proliferation of high-dimensional data and the widespread use of complex models present central challenges in contemporary statistics and data science.Dimension reduction and model checking,as two foundational pillars supporting scientific inference and data-driven decisionmaking,have evolved through the collective wisdom of generations of statisticians.This special issue,titled"Recent Developments in Dimension Reduction and Model Checking for regressions",not only aims to showcase cutting-edge advances in the field but also carries a distinct sense of academic homage to honor the groundbreaking and enduring contributions of Professor Lixing Zhu,a leading scholar whose work has profoundly shaped both areas.展开更多
The carbon emission trading policy is a key policy for China to achieve its dual carbon goals.This paper aims to examine the emission-reduction effects,transmission mechanisms,and carbon-market efficiency of China’s ...The carbon emission trading policy is a key policy for China to achieve its dual carbon goals.This paper aims to examine the emission-reduction effects,transmission mechanisms,and carbon-market efficiency of China’s carbon-emission trading policy from 2012 to 2023.We adopt the difference-in-differences(DID)model to analyze the effects of policy on emissions,and the empirical results from the DID model confirm that the pilot carbon emission trading policy has significantly reduced carbon emission intensity in pilot areas.Then we use the mediation model to study the transmission mechanism of the pilot carbon emission trading policy,and the mediation analysis demonstrates that the pilot carbon emission trading policy achieves emission abatement through four parallel transmission channels:scientific innovation,energy conservation,clean energy substitution,and industrial structure upgrading.Data envelopment analysis evaluates the carbon market efficiency of China.The result shows that the average carbon market efficiency of pilot areas has improved steadily,particularly from 2012 to 2023,especially in Beijing,Hubei,and Guangdong.Moreover,the efficiency of the national carbon market has shown an upward trend since its 2021 launch;it remains lower than the pilot average,constrained primarily by limited sectoral coverage,which impacts scale efficiency.展开更多
BFOSC and YFOSC are the most frequently used instruments in the Xinglong 2.16 m telescope and Lijiang 2.4 m telescope,respectively.We developed a software package named“BYSpec”(BFOSC and YFOSC Spectra Reduction Pack...BFOSC and YFOSC are the most frequently used instruments in the Xinglong 2.16 m telescope and Lijiang 2.4 m telescope,respectively.We developed a software package named“BYSpec”(BFOSC and YFOSC Spectra Reduction Package)dedicated to automatically reducing the long-slit and echelle spectra obtained by these two instruments.The package supports bias and flat-fielding correction,order location,background subtraction,automatic wavelength calibration,and absolute flux calibration.The optimal extraction method maximizes the signal-to-noise ratio and removes most of the cosmic rays imprinted in the spectra.A comparison with the 1D spectra reduced with IRAF verifies the reliability of the results.This open-source software is publicly available to the community.展开更多
This paper presents an efficient model reduction technique for linear time-varying systems based on shifted Legendre polynomials.The approach constructs approximate low-rank decomposition factors of finite-time Gramia...This paper presents an efficient model reduction technique for linear time-varying systems based on shifted Legendre polynomials.The approach constructs approximate low-rank decomposition factors of finite-time Gramians directly from the expansion coefficients of impulse responses.Leveraging these factors,we develop two model reduction algorithms that integrate the low-rank square root method with dominant subspace projection.Our method is computationally efficient and flexible,requiring only a few matrix-vector operations and a singular value decomposition of a low-dimensional matrix,thereby avoiding the need to solve differential Lyapunov equations.Numerical experiments confirm the effectiveness of the proposed approach.展开更多
Earthquakes are highly destructive spatio-temporal phenomena whose analysis is essential for disaster preparedness and risk mitigation.Modern seismological research produces vast volumes of heterogeneous data from sei...Earthquakes are highly destructive spatio-temporal phenomena whose analysis is essential for disaster preparedness and risk mitigation.Modern seismological research produces vast volumes of heterogeneous data from seismic networks,satellite observations,and geospatial repositories,creating the need for scalable infrastructures capable of integrating and analyzing such data to support intelligent decision-making.Data warehousing technologies provide a robust foundation for this purpose;however,existing earthquake-oriented data warehouses remain limited,often relying on simplified schemas,domain-specific analytics,or cataloguing efforts.This paper presents the design and implementation of a spatio-temporal data warehouse for seismic activity.The framework integrates spatial and temporal dimensions in a unified schema and introduces a novel array-based approach for managing many-to-many relationships between facts and dimensions without intermediate bridge tables.A comparative evaluation against a conventional bridge-table schema demonstrates that the array-based design improves fact-centric query performance,while the bridge-table schema remains advantageous for dimension-centric queries.To reconcile these trade-offs,a hybrid schema is proposed that retains both representations,ensuring balanced efficiency across heterogeneous workloads.The proposed framework demonstrates how spatio-temporal data warehousing can address schema complexity,improve query performance,and support multidimensional visualization.In doing so,it provides a foundation for integrating seismic analysis into broader big data-driven intelligent decision systems for disaster resilience,risk mitigation,and emergency management.展开更多
This paper reports the preparation of three di‑iron complexes containing a thiazole moiety.Esterification of complex[Fe_(2)(CO)_(6)(μ‑SCH_(2)CH(CH_(2)OH)S)](1)with 4‑methylthiazole‑5‑carboxylic acid gave the correspo...This paper reports the preparation of three di‑iron complexes containing a thiazole moiety.Esterification of complex[Fe_(2)(CO)_(6)(μ‑SCH_(2)CH(CH_(2)OH)S)](1)with 4‑methylthiazole‑5‑carboxylic acid gave the corresponding ester[Fe_(2)(CO)_(6)(μ‑tedt)](2),where tedt=SCH_(2)CH(CH_(2)OOC(5‑C_(3)HNSCH_(3)))S.Further reactions of complex 2 with tri(ptolyl)phosphine(tp)or tris(4‑fluorophenyl)phosphine(fp)gave the phosphine‑substituted derivatives[Fe_(2)(CO)_(5)(tp)(μ‑tedt)](3)and[Fe_(2)(CO)_(5)(fp)(μ‑tedt)](4).The structures of the newly prepared complexes were elucidated by elemental analysis,NMR,IR,and X‑ray photoelectron spectroscopy.Moreover,single‑crystal X‑ray diffraction analysis confirmed their molecular structures,showing that they contain a di‑iron core ligated by a bridged dithiolate bearing a thiazole moiety and terminal carbonyls.The electrochemical and electrocatalytic proton reduction were probed by cyclic voltammetry,revealing that three complexes can catalyze the reduction of protons to H_(2) under the electrochemical conditions.For comparison,complex 4 possessed the best efficiency with a turnover frequency of 23.5 s^(-1)at 10 mmol·L^(-1)HOAc concentration.In addition,the fungicidal activity of these complexes was also investigated in this study.CCDC:2477511,2;2477512,3;2477513,4.展开更多
Experts and officials shared their insights on poverty reduction cooperation and sustainable development during the 2025 International Seminar on Global Poverty Reduction Partnerships.
Hexavalent chromium(Cr(Ⅵ)) is an extremely toxic pollutant in aqueous environment.Chemical reduction is the most employed method in decontamination of Cr(Ⅵ).However,the chemical reduction was usually conducted in ac...Hexavalent chromium(Cr(Ⅵ)) is an extremely toxic pollutant in aqueous environment.Chemical reduction is the most employed method in decontamination of Cr(Ⅵ).However,the chemical reduction was usually conducted in acidic media,resulting in considerable waste of acid reagents and the following neutralizing agents.In this study,kinetics and mechanisms of Cr(Ⅵ) reduction by sulfite in alkaline conditions(pH:7-10) were investigated.It reveals that Cr(Ⅵ) reduction follows pseudo-zero-order kinetics,where the rate constants increased markedly with an in situ irradiation of Far-UVC(UV_(222)).Decreasing pH levels slightly favored the reduction.Iodide ion displayed a notable accelerating effect,which not only save the energy input but also minimize the reductant usage.Chloride,sulfate,and carbonate ions exhibit little effect on the reduction,whereas nitrate and nitrite ions,dissolved oxygen as well as Cu(Ⅱ) suppressed the reduction significantly,implying that hydrated electrons produced by UV222 played the most important role in the reaction.Compared to the UV254/sulfite/iodide process,UV222/sulfite/iodide demonstrates clear advantages in the reduction kinetics and the sulfite utilization efficiency,underscoring its potential for effective Cr(Ⅵ) remediation in various environmental settings.展开更多
This work contributes to the theoretical foundation for pricing in data markets and offers practical insights for managing digital data exchanges in the era of big data.We propose a structured pricing model for data e...This work contributes to the theoretical foundation for pricing in data markets and offers practical insights for managing digital data exchanges in the era of big data.We propose a structured pricing model for data exchanges transitioning from quasi-public to marketoriented operations.To address the complex dynamics among data exchanges,suppliers,and consumers,the authors develop a threestage Stackelberg game framework.In this model,the data exchange acts as a leader setting transaction commission rates,suppliers are intermediate leaders determining unit prices,and consumers are followers making purchasing decisions.Two pricing strategies are examined:the Independent Pricing Approach(IPA)and the novel Perfectly Competitive Pricing Approach(PCPA),which accounts for competition among data providers.Using backward induction,the study derives subgame-perfect equilibria and proves the existence and uniqueness of Stackelberg equilibria under both approaches.Extensive numerical simulations are carried out in the model,demonstrating that PCPA enhances data demander utility,encourages supplier competition,increases transaction volume,and improves the overall profitability and sustainability of data exchanges.Social welfare analysis further confirms PCPA’s superiority in promoting efficient and fair data markets.展开更多
Objective: To investigate the therapeutic advantages of closed reduction and Kirschner wire fixation versus open reduction and plate fixation in patients with hand surgery fractures. Methods: The sample was collected ...Objective: To investigate the therapeutic advantages of closed reduction and Kirschner wire fixation versus open reduction and plate fixation in patients with hand surgery fractures. Methods: The sample was collected from May 2021 to May 2025, consisting of 80 patients with hand surgery fractures. These patients were randomly divided into two groups using the red and blue ball method: the plate fixation group (40 cases, treated with open reduction and plate fixation) and the Kirschner wire fixation group (40 cases, treated with closed reduction and Kirschner wire fixation). The therapeutic effects between the two groups were randomly compared. Results: The Kirschner wire fixation group outperformed the plate fixation group in all indicators except for hand function scores (p < 0.05). There was no statistically significant difference in hand function scores between the two groups (p > 0.05). Conclusion: Compared with open reduction and plate fixation, closed reduction and Kirschner wire fixation for patients with hand surgery fractures achieves a more pronounced therapeutic effect, with advantages such as less trauma, shorter operation time, less bleeding, and a lower incidence of complications. It is suitable for hand surgery fractures with good stability. Open reduction and plate internal fixation have greater advantages in complex fractures and cases requiring high stability, and are worthy of promotion and application.展开更多
Ovarian cancer(OC)is one of the leading causes of death related to gynecological cancer,with the main difficulty of its early diagnosis and a heterogeneous nature of tumor biomarkers.Machine learning(ML)has the potent...Ovarian cancer(OC)is one of the leading causes of death related to gynecological cancer,with the main difficulty of its early diagnosis and a heterogeneous nature of tumor biomarkers.Machine learning(ML)has the potential to process complex datasets and support decision-making in OC diagnosis.Nevertheless,traditional ML models tend to be biased,overfitting,noisy,and less generalized.Moreover,their black-box nature reduces interpretability and limits their practical clinical applicability.In this study,we introduce an explainable ensemble learning(EL)model,TreeX-Stack,based on a stacking architecture that employs tree-based learners such as Decision Tree(DT),Random Forest(RF),Gradient Boosting(GB),and Extreme Gradient Boosting(XGBoost)as base learners,and Logistic Regression(LR)as the meta-learner to enhance ovarian cancer(OC)diagnosis.Local Interpretable ModelAgnostic Explanations(LIME)are used to explain individual predictions,making the model outputs more clinically interpretable and applicable.The model is trained on the dataset that includes demographic information,blood test,general chemistry,and tumor markers.Extensive preprocessing includes handling missing data using iterative imputation with Bayesian Ridge and addressing multicollinearity by removing features with correlation coefficients above 0.7.Relevant features are then selected using the Boruta feature selection method.To obtain robust and unbiased performance estimates during hyperparameter tuning,nested cross-validation(CV)with grid search is employed,and all experiments are repeated five times to ensure statistical reliability.TreeX-Stack demonstrates excellent diagnostic performance,achieving an accuracy of 0.9027,a precision of 0.8673,a recall of 0.9391,and an F1-score of 0.9012.Feature-importance analyses using LIME and permutation importance highlight Human Epididymis Protein 4(HE4)as the most significant biomarker for OC.The combination of high predictive performance and interpretability makes TreeX-Stack a reliable tool for clinical decision support in OC diagnosis.展开更多
Accurately assessing the relationship between tree growth and climatic factors is of great importance in dendrochronology.This study evaluated the consistency between alternative climate datasets(including station and...Accurately assessing the relationship between tree growth and climatic factors is of great importance in dendrochronology.This study evaluated the consistency between alternative climate datasets(including station and gridded data)and actual climate data(fixed-point observations near the sampling sites),in northeastern China’s warm temperate zone and analyzed differences in their correlations with tree-ring width index.The results were:(1)Gridded temperature data,as well as precipitation and relative humidity data from the Huailai meteorological station,was more consistent with the actual climate data;in contrast,gridded soil moisture content data showed significant discrepancies.(2)Horizontal distance had a greater impact on the representativeness of actual climate conditions than vertical elevation differences.(3)Differences in consistency between alternative and actual climate data also affected their correlations with tree-ring width indices.In some growing season months,correlation coefficients,both in magnitude and sign,differed significantly from those based on actual data.The selection of different alternative climate datasets can lead to biased results in assessing forest responses to climate change,which is detrimental to the management of forest ecosystems in harsh environments.Therefore,the scientific and rational selection of alternative climate data is essential for dendroecological and climatological research.展开更多
To address the severe challenges of PM_(2.5) and ozone co-control during the"14^(th) Five-Year Plan"period and to enhance the precision and intelligence level of air environment governance,it is imperative t...To address the severe challenges of PM_(2.5) and ozone co-control during the"14^(th) Five-Year Plan"period and to enhance the precision and intelligence level of air environment governance,it is imperative to build an efficient comprehensive management platform for regional air quality.In this paper,the specific practice in Zibo City,Shandong Province is as an example to systematically analyze the top-level design,technical implementation,and innovative application of a comprehensive management platform for regional air quality integrating"perception monitoring,data fusion,research judgment of early warnings,analysis of sources,collaborative dispatching,and evaluation assessment".Through the construction of an"sky-air-ground"integrated three-dimensional monitoring network,the platform integrates multi-source heterogeneous environmental data,and employs big data,cloud computing,artificial intelligence,CALPUFF/CMAQ,and other numerical model technologies to achieve comprehensive perception,precise prediction,intelligent source tracing,and closed-loop management of air pollution.The platform innovatively establishes a full-process closed-loop management mechanism of"data-early warning-disposition-evaluation",and achieves a fundamental transformation from passive response to active anticipation and from experience-based judgment to data driving in environmental supervision.The application results show that this platform significantly improves the scientific decision-making ability and collaborative execution efficiency of air pollution governance in Zibo City,providing a replicable and scalable comprehensive solution for similar industrial cities to achieve the continuous improvement of air quality.展开更多
tRNA-derived small RNAs(tsRNAs),as a class of regulatory small noncoding RNA,have been implicated in a wide variety of human diseases.Large amounts of tsRNA–disease associations have been identified in recent years f...tRNA-derived small RNAs(tsRNAs),as a class of regulatory small noncoding RNA,have been implicated in a wide variety of human diseases.Large amounts of tsRNA–disease associations have been identified in recent years from accumulating studies.However,repositories for cataloging the detailed information on tsRNA–disease associations are scarce.In this study,we provide a tsRNADisease database by integrating experimentally and computationally supported tsRNA–disease associations from manual curation of literatures and other related resources.tsRNADisease contains 5571 manually curated associations between 4759 tsRNAs and 166 diseases with experimental evidence from 346 studies.In addition,it also contains 5013 predicted associations between 1297 tsRNAs and 111 diseases.tsRNADisease provides a user-friendly interface to browse,retrieve,and download data conveniently.This database can improve our understanding of tsRNA deregulation in diseases and serve as a valuable resource for investigating the mechanism of disease-related tsRNAs.tsRNADisease is freely available at http://www.compgenelab.info/tsRNADisease.展开更多
Electrochemical nitrate reduction reaction(NO_(3)RR)is a sustainable strategy to treat wastewater and produce ammonia.However,it is still a challenge to prepare electrocatalysts with high activity and selectivity.Here...Electrochemical nitrate reduction reaction(NO_(3)RR)is a sustainable strategy to treat wastewater and produce ammonia.However,it is still a challenge to prepare electrocatalysts with high activity and selectivity.Herein,the CuO_(x) nanowires supported Ru nanoclusters(Ru-CuO_(x))were fabricated via a three-step procedure for efficient nitrate conversion and highly selective ammonia generation.The prepared RuCuO_(x) shows a high ammonia yield rate of 2286.5μg h^(-1) cm^(-2) at-0.7 V vs.RHE and Faradaic efficiency(FE)of 80.1%at-0.4 V vs.RHE.Additionally,the nitrate conversion rate exceeds 90%at the potential range from-0.2 to-0.7 V vs.RHE,and the ammonia selectivity can reach 97.7%at-0.7 V vs.RHE in100 mg L^(-1) NaNO_(3) solution.The systematic characterizations clarify that the introduction of Ru not only regulates the electronic structure of CuO_(x) and accelerates the reconstruction of CuO_(x) to Cu but also promotes H2O dissociation to generate active hydrogen.Moreover.in-situ Raman spectroscopy reveals that the formed Ru-Cu is considered the actual active species during the NO_(3)RR.Density functional theory(DFT)calculations further prove that the obtained Ru-Cu facilitates the adsorption of nitrate and lowers the Gibbs free energy of the rate-determining step,thus improving the NO_(3)RR performance.展开更多
基金supported by the Scientific&Technical Project of the State Grid(5700--202490228A--1--1-ZN).
文摘The rapid advancement of artificial intelligence(AI)has significantly increased the computational load on data centers.AI-related computational activities consume considerable electricity and result in substantial carbon emissions.To mitigate these emissions,future data centers should be strategically planned and operated to fully utilize renewable energy resources while meeting growing computational demands.This paper aims to investigate how much carbon emission reduction can be achieved by using a carbonoriented demand response to guide the optimal planning and operation of data centers.A carbon-oriented data center planning model is proposed that considers the carbon-oriented demand response of the AI load.In the planning model,future operation simulations comprehensively coordinate the temporal‒spatial flexibility of computational loads and the quality of service(QoS).An empirical study based on the proposed models is conducted on real-world data from China.The results from the empirical analysis show that newly constructed data centers are recommended to be built in Gansu Province,Ningxia Hui Autonomous Region,Sichuan Province,Inner Mongolia Autonomous Region,and Qinghai Province,accounting for 57%of the total national increase in server capacity.33%of the computational load from Eastern China should be transferred to the West,which could reduce the overall load carbon emissions by 26%.
基金supported by the National Natural Science Foundation of China (42505149,41925023,U2342223,42105069,and 91744208)the China Postdoctoral Science Foundation (2025M770303)+1 种基金the Fundamental Research Funds for the Central Universities (14380230)the Jiangsu Funding Program for Excellent Postdoctoral Talent,and Jiangsu Collaborative Innovation Center of Climate Change。
文摘Countries around the world have been making efforts to reduce pollutant emissions. However, the response of global black carbon(BC) aging to emission changes remains unclear. Using the Community Atmosphere Model version 6 with a machine-learning-integrated four-mode version of the Modal Aerosol Module, we quantify global BC aging responses to emission reductions for 2011–2018 and for 2050 and 2100 under carbon neutrality. During 2011–18, global trends in BC aging degree(mass ratio of coatings to BC, R_(BC)) exhibited marked regional disparities, with a significant increase in China(5.4% yr^(-1)), which contrasts with minimal changes in the USA, Europe, and India. The divergence is attributed to opposing trends in secondary organic aerosol(SOA) and sulfate coatings, driven by regional changes in the emission ratios of corresponding coating precursors to BC(volatile organic compounds-VOCs/BC and SO_(2)/BC). Projections under carbon neutrality reveal that R_(BC) will increase globally by 47%(118%) in 2050(2100), with strong convergent increases expected across major source regions. The R_(BC) increase, primarily driven by enhanced SOA coatings due to sharper BC reductions relative to VOCs, will enhance the global BC mass absorption cross-section(MAC) by 11%(17%) in 2050(2100).Consequently, although the global BC burden will decline sharply by 60%(76%), the enhanced MAC partially offsets the magnitude of the decline in the BC direct radiative effect, resulting in the moderation of global BC DRE decreases to 88%(92%) of the BC burden reductions in 2050(2100). This study highlights the globally enhanced BC aging and light absorption capacity under carbon neutrality, thereby partly offsetting the impact of BC direct emission reductions on future changes in BC radiative effects globally.
文摘In order to explore the reduction pathways of zinc oxide in LiCl molten salt and the optimal process,experiments were conducted in an alumina crucible using metallic lithium as the reducing agent and lithium chloride molten salt as the reaction medium at 923 K.The study assessed the effects of lithium thermochemical reduction and electrolytic reduction of ZnO.The volatilization behavior of metal oxides in molten salts,the equivalent of a reducing agent,reduction time,amount of molten salt,stirring time,and the method of reduction feed were investigated for their impacts on the reduction yield and product composition.X-ray powder diffraction(XRD)analysis of the products showed that lithium reduction of ZnO not only produced metallic Zn but also formed a LiZn alloy.Electrolytic reduction can be used to obtain the metallic Zn product by controlling the potential below-2.2 V(vs Ag/Ag^(+)).Moreover,sintered oxides and higher electrode potentials could enhance the efficiency of electrolysis.Under the optimal reaction conditions determined experimentally,the lithium reduction experiment achieved a yield of 77.2%after a 12-h test,and the electrolytic reduction reached a yield of 85.4%after a 6-h test.
文摘In the past decade,financial institutions have invested significant efforts in the development of accurate analytical credit scoring models.The evidence suggests that even small improvements in the accuracy of existing credit-scoring models may optimize profits while effectively managing risk exposure.Despite continuing efforts,the majority of existing credit scoring models still include some judgment-based assumptions that are sometimes supported by the significant findings of previous studies but are not validated using the institution’s internal data.We argue that current studies related to the development of credit scoring models have largely ignored recent developments in statistical methods for sufficient dimension reduction.To contribute to the field of financial innovation,this study proposes a Dimension Reduction Assisted Credit Scoring(DRA-CS)method via distance covariance-based sufficient dimension reduction(DCOV-SDR)in Majorization-Minimization(MM)algorithm.First,in the presence of a large number of variables,the DRA-CS method results in greater dimension reduction and better prediction accuracy than the other methods used for dimension reduction.Second,when the DRA-CS method is employed with logistic regression,it outperforms existing methods based on different variable selection techniques.This study argues that the DRA-CS method should be used by financial institutions as a financial innovation tool to analyze high-dimensional customer datasets and improve the accuracy of existing credit scoring methods.
文摘A method for the rapid reduction of acyl chlorides to aldehydes was developed using pinacolborane(HBpin)as the reducing agent.The method exhibits excellent generality for both aromatic and aliphatic substrates,affording aldehydes in isolated yields of up to 88%with broad functional group tolerance,including cyano,halogen,alkenyl,ketone,and ester groups.Moreover,the method enables gram-scale aldehyde synthesis and shows high efficiency in reducing in situ generated acyl chlorides,thereby enhancing its synthetic practicality.
文摘The proliferation of high-dimensional data and the widespread use of complex models present central challenges in contemporary statistics and data science.Dimension reduction and model checking,as two foundational pillars supporting scientific inference and data-driven decisionmaking,have evolved through the collective wisdom of generations of statisticians.This special issue,titled"Recent Developments in Dimension Reduction and Model Checking for regressions",not only aims to showcase cutting-edge advances in the field but also carries a distinct sense of academic homage to honor the groundbreaking and enduring contributions of Professor Lixing Zhu,a leading scholar whose work has profoundly shaped both areas.
基金supported by the National Social Science Fund of China under Grant 25CJL064.
文摘The carbon emission trading policy is a key policy for China to achieve its dual carbon goals.This paper aims to examine the emission-reduction effects,transmission mechanisms,and carbon-market efficiency of China’s carbon-emission trading policy from 2012 to 2023.We adopt the difference-in-differences(DID)model to analyze the effects of policy on emissions,and the empirical results from the DID model confirm that the pilot carbon emission trading policy has significantly reduced carbon emission intensity in pilot areas.Then we use the mediation model to study the transmission mechanism of the pilot carbon emission trading policy,and the mediation analysis demonstrates that the pilot carbon emission trading policy achieves emission abatement through four parallel transmission channels:scientific innovation,energy conservation,clean energy substitution,and industrial structure upgrading.Data envelopment analysis evaluates the carbon market efficiency of China.The result shows that the average carbon market efficiency of pilot areas has improved steadily,particularly from 2012 to 2023,especially in Beijing,Hubei,and Guangdong.Moreover,the efficiency of the national carbon market has shown an upward trend since its 2021 launch;it remains lower than the pilot average,constrained primarily by limited sectoral coverage,which impacts scale efficiency.
基金supported by the National Natural Science Foundation of China under grant No.U2031144partially supported by the Open Project Program of the Key Laboratory of Optical Astronomy,National Astronomical Observatories,Chinese Academy of Sciences+5 种基金supported by the National Key R&D Program of China with No.2021YFA1600404the National Natural Science Foundation of China(12173082)the Yunnan Fundamental Research Projects(grant 202201AT070069)the Top-notch Young Talents Program of Yunnan Provincethe Light of West China Program provided by the Chinese Academy of Sciencesthe International Centre of Supernovae,Yunnan Key Laboratory(No.202302AN360001)。
文摘BFOSC and YFOSC are the most frequently used instruments in the Xinglong 2.16 m telescope and Lijiang 2.4 m telescope,respectively.We developed a software package named“BYSpec”(BFOSC and YFOSC Spectra Reduction Package)dedicated to automatically reducing the long-slit and echelle spectra obtained by these two instruments.The package supports bias and flat-fielding correction,order location,background subtraction,automatic wavelength calibration,and absolute flux calibration.The optimal extraction method maximizes the signal-to-noise ratio and removes most of the cosmic rays imprinted in the spectra.A comparison with the 1D spectra reduced with IRAF verifies the reliability of the results.This open-source software is publicly available to the community.
文摘This paper presents an efficient model reduction technique for linear time-varying systems based on shifted Legendre polynomials.The approach constructs approximate low-rank decomposition factors of finite-time Gramians directly from the expansion coefficients of impulse responses.Leveraging these factors,we develop two model reduction algorithms that integrate the low-rank square root method with dominant subspace projection.Our method is computationally efficient and flexible,requiring only a few matrix-vector operations and a singular value decomposition of a low-dimensional matrix,thereby avoiding the need to solve differential Lyapunov equations.Numerical experiments confirm the effectiveness of the proposed approach.
文摘Earthquakes are highly destructive spatio-temporal phenomena whose analysis is essential for disaster preparedness and risk mitigation.Modern seismological research produces vast volumes of heterogeneous data from seismic networks,satellite observations,and geospatial repositories,creating the need for scalable infrastructures capable of integrating and analyzing such data to support intelligent decision-making.Data warehousing technologies provide a robust foundation for this purpose;however,existing earthquake-oriented data warehouses remain limited,often relying on simplified schemas,domain-specific analytics,or cataloguing efforts.This paper presents the design and implementation of a spatio-temporal data warehouse for seismic activity.The framework integrates spatial and temporal dimensions in a unified schema and introduces a novel array-based approach for managing many-to-many relationships between facts and dimensions without intermediate bridge tables.A comparative evaluation against a conventional bridge-table schema demonstrates that the array-based design improves fact-centric query performance,while the bridge-table schema remains advantageous for dimension-centric queries.To reconcile these trade-offs,a hybrid schema is proposed that retains both representations,ensuring balanced efficiency across heterogeneous workloads.The proposed framework demonstrates how spatio-temporal data warehousing can address schema complexity,improve query performance,and support multidimensional visualization.In doing so,it provides a foundation for integrating seismic analysis into broader big data-driven intelligent decision systems for disaster resilience,risk mitigation,and emergency management.
文摘This paper reports the preparation of three di‑iron complexes containing a thiazole moiety.Esterification of complex[Fe_(2)(CO)_(6)(μ‑SCH_(2)CH(CH_(2)OH)S)](1)with 4‑methylthiazole‑5‑carboxylic acid gave the corresponding ester[Fe_(2)(CO)_(6)(μ‑tedt)](2),where tedt=SCH_(2)CH(CH_(2)OOC(5‑C_(3)HNSCH_(3)))S.Further reactions of complex 2 with tri(ptolyl)phosphine(tp)or tris(4‑fluorophenyl)phosphine(fp)gave the phosphine‑substituted derivatives[Fe_(2)(CO)_(5)(tp)(μ‑tedt)](3)and[Fe_(2)(CO)_(5)(fp)(μ‑tedt)](4).The structures of the newly prepared complexes were elucidated by elemental analysis,NMR,IR,and X‑ray photoelectron spectroscopy.Moreover,single‑crystal X‑ray diffraction analysis confirmed their molecular structures,showing that they contain a di‑iron core ligated by a bridged dithiolate bearing a thiazole moiety and terminal carbonyls.The electrochemical and electrocatalytic proton reduction were probed by cyclic voltammetry,revealing that three complexes can catalyze the reduction of protons to H_(2) under the electrochemical conditions.For comparison,complex 4 possessed the best efficiency with a turnover frequency of 23.5 s^(-1)at 10 mmol·L^(-1)HOAc concentration.In addition,the fungicidal activity of these complexes was also investigated in this study.CCDC:2477511,2;2477512,3;2477513,4.
文摘Experts and officials shared their insights on poverty reduction cooperation and sustainable development during the 2025 International Seminar on Global Poverty Reduction Partnerships.
基金supported by the National Key R&D Program of China(No.2023YFE0112100)the Science and Technology Planning Project of Fujian Province(No.2023Y4015)the Marine and Fishery Devel-opment Special Fund of Xiamen(No.23YYST064QCB36).
文摘Hexavalent chromium(Cr(Ⅵ)) is an extremely toxic pollutant in aqueous environment.Chemical reduction is the most employed method in decontamination of Cr(Ⅵ).However,the chemical reduction was usually conducted in acidic media,resulting in considerable waste of acid reagents and the following neutralizing agents.In this study,kinetics and mechanisms of Cr(Ⅵ) reduction by sulfite in alkaline conditions(pH:7-10) were investigated.It reveals that Cr(Ⅵ) reduction follows pseudo-zero-order kinetics,where the rate constants increased markedly with an in situ irradiation of Far-UVC(UV_(222)).Decreasing pH levels slightly favored the reduction.Iodide ion displayed a notable accelerating effect,which not only save the energy input but also minimize the reductant usage.Chloride,sulfate,and carbonate ions exhibit little effect on the reduction,whereas nitrate and nitrite ions,dissolved oxygen as well as Cu(Ⅱ) suppressed the reduction significantly,implying that hydrated electrons produced by UV222 played the most important role in the reaction.Compared to the UV254/sulfite/iodide process,UV222/sulfite/iodide demonstrates clear advantages in the reduction kinetics and the sulfite utilization efficiency,underscoring its potential for effective Cr(Ⅵ) remediation in various environmental settings.
基金supported by the National Natural Science Foundation of China[grant numbers 12171158,12371474 and 12571510]Fundamental Research Funds for the Central Universities[grant number 2025ECNU-WLJC006].
文摘This work contributes to the theoretical foundation for pricing in data markets and offers practical insights for managing digital data exchanges in the era of big data.We propose a structured pricing model for data exchanges transitioning from quasi-public to marketoriented operations.To address the complex dynamics among data exchanges,suppliers,and consumers,the authors develop a threestage Stackelberg game framework.In this model,the data exchange acts as a leader setting transaction commission rates,suppliers are intermediate leaders determining unit prices,and consumers are followers making purchasing decisions.Two pricing strategies are examined:the Independent Pricing Approach(IPA)and the novel Perfectly Competitive Pricing Approach(PCPA),which accounts for competition among data providers.Using backward induction,the study derives subgame-perfect equilibria and proves the existence and uniqueness of Stackelberg equilibria under both approaches.Extensive numerical simulations are carried out in the model,demonstrating that PCPA enhances data demander utility,encourages supplier competition,increases transaction volume,and improves the overall profitability and sustainability of data exchanges.Social welfare analysis further confirms PCPA’s superiority in promoting efficient and fair data markets.
文摘Objective: To investigate the therapeutic advantages of closed reduction and Kirschner wire fixation versus open reduction and plate fixation in patients with hand surgery fractures. Methods: The sample was collected from May 2021 to May 2025, consisting of 80 patients with hand surgery fractures. These patients were randomly divided into two groups using the red and blue ball method: the plate fixation group (40 cases, treated with open reduction and plate fixation) and the Kirschner wire fixation group (40 cases, treated with closed reduction and Kirschner wire fixation). The therapeutic effects between the two groups were randomly compared. Results: The Kirschner wire fixation group outperformed the plate fixation group in all indicators except for hand function scores (p < 0.05). There was no statistically significant difference in hand function scores between the two groups (p > 0.05). Conclusion: Compared with open reduction and plate fixation, closed reduction and Kirschner wire fixation for patients with hand surgery fractures achieves a more pronounced therapeutic effect, with advantages such as less trauma, shorter operation time, less bleeding, and a lower incidence of complications. It is suitable for hand surgery fractures with good stability. Open reduction and plate internal fixation have greater advantages in complex fractures and cases requiring high stability, and are worthy of promotion and application.
基金supported and funded by the Deanship of Scientific Research at Imam Mohammad Ibn Saud Islamic University(IMSIU)under the grant number IMSIU-DDRSP2601.
文摘Ovarian cancer(OC)is one of the leading causes of death related to gynecological cancer,with the main difficulty of its early diagnosis and a heterogeneous nature of tumor biomarkers.Machine learning(ML)has the potential to process complex datasets and support decision-making in OC diagnosis.Nevertheless,traditional ML models tend to be biased,overfitting,noisy,and less generalized.Moreover,their black-box nature reduces interpretability and limits their practical clinical applicability.In this study,we introduce an explainable ensemble learning(EL)model,TreeX-Stack,based on a stacking architecture that employs tree-based learners such as Decision Tree(DT),Random Forest(RF),Gradient Boosting(GB),and Extreme Gradient Boosting(XGBoost)as base learners,and Logistic Regression(LR)as the meta-learner to enhance ovarian cancer(OC)diagnosis.Local Interpretable ModelAgnostic Explanations(LIME)are used to explain individual predictions,making the model outputs more clinically interpretable and applicable.The model is trained on the dataset that includes demographic information,blood test,general chemistry,and tumor markers.Extensive preprocessing includes handling missing data using iterative imputation with Bayesian Ridge and addressing multicollinearity by removing features with correlation coefficients above 0.7.Relevant features are then selected using the Boruta feature selection method.To obtain robust and unbiased performance estimates during hyperparameter tuning,nested cross-validation(CV)with grid search is employed,and all experiments are repeated five times to ensure statistical reliability.TreeX-Stack demonstrates excellent diagnostic performance,achieving an accuracy of 0.9027,a precision of 0.8673,a recall of 0.9391,and an F1-score of 0.9012.Feature-importance analyses using LIME and permutation importance highlight Human Epididymis Protein 4(HE4)as the most significant biomarker for OC.The combination of high predictive performance and interpretability makes TreeX-Stack a reliable tool for clinical decision support in OC diagnosis.
基金supported by the International Partnership program of the Chinese Academy of Sciences(170GJHZ2023074GC)National Natural Science Foundation of China(42425706 and 42488201)+1 种基金National Key Research and Development Program of China(2024YFF0807902)Beijing Natural Science Foundation(8242041),and China Postdoctoral Science Foundation(2025M770353).
文摘Accurately assessing the relationship between tree growth and climatic factors is of great importance in dendrochronology.This study evaluated the consistency between alternative climate datasets(including station and gridded data)and actual climate data(fixed-point observations near the sampling sites),in northeastern China’s warm temperate zone and analyzed differences in their correlations with tree-ring width index.The results were:(1)Gridded temperature data,as well as precipitation and relative humidity data from the Huailai meteorological station,was more consistent with the actual climate data;in contrast,gridded soil moisture content data showed significant discrepancies.(2)Horizontal distance had a greater impact on the representativeness of actual climate conditions than vertical elevation differences.(3)Differences in consistency between alternative and actual climate data also affected their correlations with tree-ring width indices.In some growing season months,correlation coefficients,both in magnitude and sign,differed significantly from those based on actual data.The selection of different alternative climate datasets can lead to biased results in assessing forest responses to climate change,which is detrimental to the management of forest ecosystems in harsh environments.Therefore,the scientific and rational selection of alternative climate data is essential for dendroecological and climatological research.
文摘To address the severe challenges of PM_(2.5) and ozone co-control during the"14^(th) Five-Year Plan"period and to enhance the precision and intelligence level of air environment governance,it is imperative to build an efficient comprehensive management platform for regional air quality.In this paper,the specific practice in Zibo City,Shandong Province is as an example to systematically analyze the top-level design,technical implementation,and innovative application of a comprehensive management platform for regional air quality integrating"perception monitoring,data fusion,research judgment of early warnings,analysis of sources,collaborative dispatching,and evaluation assessment".Through the construction of an"sky-air-ground"integrated three-dimensional monitoring network,the platform integrates multi-source heterogeneous environmental data,and employs big data,cloud computing,artificial intelligence,CALPUFF/CMAQ,and other numerical model technologies to achieve comprehensive perception,precise prediction,intelligent source tracing,and closed-loop management of air pollution.The platform innovatively establishes a full-process closed-loop management mechanism of"data-early warning-disposition-evaluation",and achieves a fundamental transformation from passive response to active anticipation and from experience-based judgment to data driving in environmental supervision.The application results show that this platform significantly improves the scientific decision-making ability and collaborative execution efficiency of air pollution governance in Zibo City,providing a replicable and scalable comprehensive solution for similar industrial cities to achieve the continuous improvement of air quality.
基金supported by the National Natural Science Foundation of China(91959106)the Foundation of the Shanghai Municipal Education Commission(24RGZNC02)+4 种基金Shanghai Key Laboratory of Intelligent Information Processing,Fudan University(IIPL-2025-RD3-02)Key University Science Research Project of Anhui Province(2023AH030108)Climbing Peak Training Program for Innovative Technology team of Yijishan Hospital,Wannan Medical College(PF201904)Peak Training Program for Scientific Research of Yijishan Hospital,Wannan Medical College(GF2019G15)the talent project of the First Affiliated Hospital of Wannan Medical College(Yijishan Hospital of Wannan Medical College)(YR202422).
文摘tRNA-derived small RNAs(tsRNAs),as a class of regulatory small noncoding RNA,have been implicated in a wide variety of human diseases.Large amounts of tsRNA–disease associations have been identified in recent years from accumulating studies.However,repositories for cataloging the detailed information on tsRNA–disease associations are scarce.In this study,we provide a tsRNADisease database by integrating experimentally and computationally supported tsRNA–disease associations from manual curation of literatures and other related resources.tsRNADisease contains 5571 manually curated associations between 4759 tsRNAs and 166 diseases with experimental evidence from 346 studies.In addition,it also contains 5013 predicted associations between 1297 tsRNAs and 111 diseases.tsRNADisease provides a user-friendly interface to browse,retrieve,and download data conveniently.This database can improve our understanding of tsRNA deregulation in diseases and serve as a valuable resource for investigating the mechanism of disease-related tsRNAs.tsRNADisease is freely available at http://www.compgenelab.info/tsRNADisease.
基金the Natural Science Foundation of China(Grant No.NSFC-22072062,22202098)the Science and Technology Project of China Northern Rare Earth(BFXT-2023-D-0048 and BFXT-2022-D-0078)。
文摘Electrochemical nitrate reduction reaction(NO_(3)RR)is a sustainable strategy to treat wastewater and produce ammonia.However,it is still a challenge to prepare electrocatalysts with high activity and selectivity.Herein,the CuO_(x) nanowires supported Ru nanoclusters(Ru-CuO_(x))were fabricated via a three-step procedure for efficient nitrate conversion and highly selective ammonia generation.The prepared RuCuO_(x) shows a high ammonia yield rate of 2286.5μg h^(-1) cm^(-2) at-0.7 V vs.RHE and Faradaic efficiency(FE)of 80.1%at-0.4 V vs.RHE.Additionally,the nitrate conversion rate exceeds 90%at the potential range from-0.2 to-0.7 V vs.RHE,and the ammonia selectivity can reach 97.7%at-0.7 V vs.RHE in100 mg L^(-1) NaNO_(3) solution.The systematic characterizations clarify that the introduction of Ru not only regulates the electronic structure of CuO_(x) and accelerates the reconstruction of CuO_(x) to Cu but also promotes H2O dissociation to generate active hydrogen.Moreover.in-situ Raman spectroscopy reveals that the formed Ru-Cu is considered the actual active species during the NO_(3)RR.Density functional theory(DFT)calculations further prove that the obtained Ru-Cu facilitates the adsorption of nitrate and lowers the Gibbs free energy of the rate-determining step,thus improving the NO_(3)RR performance.
