Organic perovskites are promising semiconductor materials for advanced photoelectric applications.Their fluorescence typically shows a negative temperature coefficient due to bandgap change and structural instability....Organic perovskites are promising semiconductor materials for advanced photoelectric applications.Their fluorescence typically shows a negative temperature coefficient due to bandgap change and structural instability.In this study,a novel perovskite-based composite with positive sensitivity to temperature was designed and obtained based on its inverse temperature crystallization,demonstrating good flexibility and solution processability.The supercritical drying method was used to address the limitations of annealing drying in preparing high-performance perovskite.Optimizing the precursor composition proved to be an effective approach for achieving high fluorescence and structural integrity in the perovskite material.This perovskite-based composite exhibited a positive temperature sensitivity of 28.563%℃^(-1)for intensity change and excellent temperature cycling reversibility in the range of 25-40℃in an ambient environment.This made it suitable for use as a smart window with rapid response.Furthermore,the perovskite composite was found to offer temperature-sensing photoluminescence and flexible processability due to its components of perovskite-based compounds and polyethylene oxide.The organic precursor solvent could be a promising candidate for use as ink to print or write on various substrates for optoelectronic devices responding to temperature.展开更多
Here,we designed asymmetric(m DS)and symmetrical(d DS)chiral V-shaped molecules by linking one or two dansyl groups to trans-1,2-cyclohexane diamine and investigated the solvent-regulated structural transformation and...Here,we designed asymmetric(m DS)and symmetrical(d DS)chiral V-shaped molecules by linking one or two dansyl groups to trans-1,2-cyclohexane diamine and investigated the solvent-regulated structural transformation and inversed circularly polarized luminescence(CPL)in the self-assemblies.Upon increasing water volume fraction(fw)in the mixed solvent of water/acetonitrile,asymmetric mDS selfassembled into hollow nanospheres and microtubes,while solid nanospheres and solid microplates were corresponding to symmetric d DS.During this transformation process,the emission of m DS and d DS was changed from yellow-green to blue and cyan color,which was ascribed to twisted intramolecular charge transfer(TICT)and locally excited(LE)fluorescence of V-shaped DS molecules.The conformation of N,Ndimethyl groups with respect to naphthalene ring also led to the transformation of structures.These tubular and platelike structures had stronger and reversed CPL signals in comparison with spheroidal structures.The chiral information of DS assembly could be effective transferred to achiral Nile red via co-assembly strategy,which endowed Nile red exhibiting inversed induced CPL signal regulated by water fraction.This work provides a method for achieving a variety of self-assembled structures with adjustable chiroptical properties.展开更多
Leaf biochemical properties have been widely assessed using hyperspectral reflectance information by inversion of PROSPECT model or by using hyperspectral indices, but few studies have focused on arid ecosystems. As a...Leaf biochemical properties have been widely assessed using hyperspectral reflectance information by inversion of PROSPECT model or by using hyperspectral indices, but few studies have focused on arid ecosystems. As a dominant species of riparian ecosystems in arid lands, Populus euphratica Oliv. is an unusual tree species with polymorphic leaves along the vertical profile of canopy corresponding to different growth stages. In this study, we evaluated both the inversed PROSPECT model and hyperspectral indices for estimating biochemical properties of P. euphratica leaves. Both the shapes and biochemical properties of P. euphratica leaves were found to change with the heights from ground surface. The results indicated that the model inversion calibrated for each leaf shape performed much better than the model calibrated for all leaf shapes, and also better than hyperspectral indices. Similar results were obtained for estimations of equivalent water thickness （EWT） and leaf mass per area （LMA）. Hyperspectral indices identified in this study for estimating these leaf properties had root mean square error （RMSE） and R2 values between those obtained with the two calibration strategies using the inversed PROSPECT model. Hence, the inversed PROSPECT model can be applied to estimate leaf biochemical properties in arid ecosystems, but the calibration to the model requires special attention.展开更多
A kind of international rapid field measurement methods of hydraulic conductivity and it's applications in Sanjiang Plain have been introduced in the paper.
Gravity variation data observed in the process of seismogenesis and occurrences of earthquakes show that the location with the greatest gravity changes does not necessarily coincide with the epicenter. To explain this...Gravity variation data observed in the process of seismogenesis and occurrences of earthquakes show that the location with the greatest gravity changes does not necessarily coincide with the epicenter. To explain this we defined the center of effective mass of stress volume as hypocentroid, and the vertical projection of which on the earths surface as epicentroid. Here we adopt three rotating models, including spheroid, ellipsoid and cylinder, to represent the region of an impending earthquake. Based on the models of gravity variations induced by uniform dilatancy, epicentroids associated with sixteen earthquakes with M>4.0 occurred in 1981~2000 in the Beijing-Tianjin-Tangshan-Zhangjiakou region are determined by means of a proposed least squares iterative inversion method. The results indicate that cylinder model is preferable to the other two, and epicentroids obtained by the cylinder model separate from the epicenters by a range of 0~40 km. Epicentroids are inevitably located within intact tectonic blocks, and usually cluster in groups; while the epicenters are generally located at the terminations of faults or at the intersections of faults. It seems that there exist earthquake-hatching areas in the block among faults. Earthquakes hatch in these areas, but occur around these areas, meanwhile the existence of faults may play an important role in controlling the processes.展开更多
To realize the handedness controllable circularly polarized luminescence(CPL) system remains challenging. Herein, the solvent-mediated CPL inversion and amplification systems were successfully constructed by camptothe...To realize the handedness controllable circularly polarized luminescence(CPL) system remains challenging. Herein, the solvent-mediated CPL inversion and amplification systems were successfully constructed by camptothecin derivative(CPT-A). Due to the planar structure of N,N-dimethylformamide, it could coassemble with CPT-A, resulting in the alteration of g_(lum) from –0.0082 to +0.0085 by increasing water content. While in the non-planar solvent(hexafluoroisopropanol), the g_(lum) was amplified to 0.034 with the increase in water content. Moreover, the CPT-A could react with the glutathione, resulting in the anticancer drug CPT to make it more toxic to the cancer cells. Overall, the handedness controllable CPL systems were realized by tuning the supramolecular self-assembly of a prodrug.展开更多
As an advanced device for observing atmospheric winds,the spaceborne Doppler Asymmetric Spatial Heterodyne(DASH)interferometer also encounters challenges associated with phase distortion,par-ticularly in limb sounding...As an advanced device for observing atmospheric winds,the spaceborne Doppler Asymmetric Spatial Heterodyne(DASH)interferometer also encounters challenges associated with phase distortion,par-ticularly in limb sounding scenarios.This paper discusses interferogram modeling and phase distortion cor-rection techniques for spaceborne DASH interferometers.The modeling of phase distortion interferograms with and without Doppler shift for limb observation was conducted,and the effectiveness of the analytical expression was verified through numerical simulation.The simulation results indicate that errors propagate layer by layer while using the onion-peeling inversion algorithm to handle phase-distorted interferograms.In contrast,the phase distortion correction algorithm can achieve effective correction.This phase correction method can be successfully applied to correct phase distortions in the interferograms of the spaceborne DASH interferometer,providing a feasible solution to enhance its measurement accuracy.展开更多
Improving the accuracy of anthropogenic volatile organic compounds(VOCs)emission inventory is crucial for reducing atmospheric pollution and formulating control policy of air pollution.In this study,an anthropogenic s...Improving the accuracy of anthropogenic volatile organic compounds(VOCs)emission inventory is crucial for reducing atmospheric pollution and formulating control policy of air pollution.In this study,an anthropogenic speciated VOCs emission inventory was established for Central China represented by Henan Province at a 3 km×3 km spatial resolution based on the emission factormethod.The 2019 VOCs emission in Henan Provincewas 1003.5 Gg,while industrial process source(33.7%)was the highest emission source,Zhengzhou(17.9%)was the city with highest emission and April and August were the months with the more emissions.High VOCs emission regions were concentrated in downtown areas and industrial parks.Alkanes and aromatic hydrocarbons were the main VOCs contribution groups.The species composition,source contribution and spatial distribution were verified and evaluated through tracer ratio method(TR),Positive Matrix Factorization Model(PMF)and remote sensing inversion(RSI).Results show that both the emission results by emission inventory(EI)(15.7 Gg)and by TRmethod(13.6 Gg)and source contribution by EI and PMF are familiar.The spatial distribution of HCHO primary emission based on RSI is basically consistent with that of HCHO emission based on EI with a R-value of 0.73.The verification results show that the VOCs emission inventory and speciated emission inventory established in this study are relatively reliable.展开更多
Young's modulus and Poisson's ratio are crucial parameters for reservoir characterization and rock brittleness evaluation.Conventional methods often rely on indirect computation or approximations of the Zoeppr...Young's modulus and Poisson's ratio are crucial parameters for reservoir characterization and rock brittleness evaluation.Conventional methods often rely on indirect computation or approximations of the Zoeppritz equations to estimate Young's modulus,which can introduce cumulative errors and reduce the accuracy of inversion results.To address these issues,this paper introduces the analytical solution of the Zoeppritz equation into the inversion process.The equation is re-derived and expressed in terms of Young's modulus,Poisson's ratio,and density.Within the Bayesian framework,we construct an objective function for the joint inversion of PP and PS waves.Traditional gradient-based algorithms often suffer from low precision and the computational complexity.In this study,we address limitations of conventional approaches related to low precision and complicated code by using Circle chaotic mapping,Levy flights,and Gaussian mutation to optimize the quantum particle swarm optimization(QPSO),named improved quantum particle swarm optimization(IQPSO).The IQPSO demonstrates superior global optimization capabilities.We test the proposed inversion method with both synthetic and field data.The test results demonstrate the proposed method's feasibility and effectiveness,indicating an improvement in inversion accuracy over traditional methods.展开更多
As energy demands continue to rise in modern society,the development of high-performance lithium-ion batteries(LIBs)has become crucial.However,traditional research methods of material science face challenges such as l...As energy demands continue to rise in modern society,the development of high-performance lithium-ion batteries(LIBs)has become crucial.However,traditional research methods of material science face challenges such as lengthy timelines and complex processes.In recent years,the integration of machine learning(ML)in LIB materials,including electrolytes,solid-state electrolytes,and electrodes,has yielded remarkable achievements.This comprehensive review explores the latest applications of ML in predicting LIB material performance,covering the core principles and recent advancements in three key inverse material design strategies:high-throughput virtual screening,global optimization,and generative models.These strategies have played a pivotal role in fostering LIB material innovations.Meanwhile,the paper briefly discusses the challenges associated with applying ML to materials research and offers insights and directions for future research.展开更多
To meet the requirements of electromagnetic(EM)theory and applied physics,this study presents an overview of the state-of-the-art research on obtaining the EM properties of media and points out potential solutions tha...To meet the requirements of electromagnetic(EM)theory and applied physics,this study presents an overview of the state-of-the-art research on obtaining the EM properties of media and points out potential solutions that can break through the bottlenecks of current methods.Firstly,based on the survey of three mainstream approaches for acquiring EM properties of media,we identify the difficulties when implementing them in realistic environments.With a focus on addressing these problems and challenges,we propose a novel paradigm for obtaining the EM properties of multi-type media in realistic environments.Particularly,within this paradigm,we describe the implementation approach of the key technology,namely“multipath extraction using heterogeneous wave propagation data in multi-spectrum cases”.Finally,the latest measurement and simulation results show that the EM properties of multi-type media in realistic environments can be precisely and efficiently acquired by the methodology proposed in this study.展开更多
A 3D crustal model was constructed using a combination of cutting-edge techniques,which were integrated to provide a density model for Egypt and address the sporadic distribution of seismic data.These techniques inclu...A 3D crustal model was constructed using a combination of cutting-edge techniques,which were integrated to provide a density model for Egypt and address the sporadic distribution of seismic data.These techniques include obtaining gravity data from the Gravity Field and Steady-State Ocean Circulation Explorer(GOCE),creating seismic profiles,analyzing the receiver functions of seismic data,obtaining information from boreholes,and providing geological interpretations.GOCE satellite gravity data were processed to construct a preliminary model based on nonlinear inversions of the data.A regional crustal thickness model was developed using receiver functions,seismic refraction profiles,and geological insights.The inverted model was validated using borehole data and compared with seismic estimates.The model exhibited strong consistency and revealed a correlation between crustal thickness,geology,and tectonics of Egypt.It showed that the shallowest depths of the Moho are located in the north along the Mediterranean Sea and in the eastern part along the Red Sea,reflecting an oceanic plate with a thin,high-density crust.The deepest Moho depths are located in the southwestern part of Egypt,Red Sea coastal mountains,and Sinai Peninsula.The obtained 3D model of crustal thickness provided finely detailed Moho depth estimates that aligned closely with geology and tectonic characteristics of Egypt,contributing valuable insights into the subsurface structure and tectonic processes of region.展开更多
Finding materials with specific properties is a hot topic in materials science.Traditional materials design relies on empirical and trial-and-error methods,requiring extensive experiments and time,resulting in high co...Finding materials with specific properties is a hot topic in materials science.Traditional materials design relies on empirical and trial-and-error methods,requiring extensive experiments and time,resulting in high costs.With the development of physics,statistics,computer science,and other fields,machine learning offers opportunities for systematically discovering new materials.Especially through machine learning-based inverse design,machine learning algorithms analyze the mapping relationships between materials and their properties to find materials with desired properties.This paper first outlines the basic concepts of materials inverse design and the challenges faced by machine learning-based approaches to materials inverse design.Then,three main inverse design methods—exploration-based,model-based,and optimization-based—are analyzed in the context of different application scenarios.Finally,the applications of inverse design methods in alloys,optical materials,and acoustic materials are elaborated on,and the prospects for materials inverse design are discussed.The authors hope to accelerate the discovery of new materials and provide new possibilities for advancing materials science and innovative design methods.展开更多
This study presents an inversion method to recover the tidal flow velocity using tidal signals extracted from geomagnetic satellite dataset.By integrating the latest Earth conductivity profile and the Earth's magn...This study presents an inversion method to recover the tidal flow velocity using tidal signals extracted from geomagnetic satellite dataset.By integrating the latest Earth conductivity profile and the Earth's magnetic field model,the limited memory quasi-Newton method(L-BFGS)is used to directly invert seawater flow velocities.We used the radial component of the induced magnetic field as the observed data,constructed an L_(2)-norm-based data misfit term using theoretical response and observed data,and applied smoothness constraints to the ocean flow velocity.The results agree well with the widely used HAMTIDE model in low-and mid-latitude regions,which is attributed to Macao Science Satellite-1's(MSS-1)unique low-inclination orbit of full coverage in these areas.These findings underscore MSS-1's potential to advance research on tidal-induced magnetic fields and their applications in ocean dynamics studies.展开更多
Due to the heterogeneity of rock masses and the variability of in situ stress,the traditional linear inversion method is insufficiently accurate to achieve high accuracy of the in situ stress field.To address this cha...Due to the heterogeneity of rock masses and the variability of in situ stress,the traditional linear inversion method is insufficiently accurate to achieve high accuracy of the in situ stress field.To address this challenge,nonlinear stress boundaries for a numerical model are determined through regression analysis of a series of nonlinear coefficient matrices,which are derived from the bubbling method.Considering the randomness and flexibility of the bubbling method,a parametric study is conducted to determine recommended ranges for these parameters,including the standard deviation(σb)of bubble radii,the non-uniform coefficient matrix number(λ)for nonlinear stress boundaries,and the number(m)and positions of in situ stress measurement points.A model case study provides a reference for the selection of these parameters.Additionally,when the nonlinear in situ stress inversion method is employed,stress distortion inevitably occurs near model boundaries,aligning with the Saint Venant's principle.Two strategies are proposed accordingly:employing a systematic reduction of nonlinear coefficients to achieve high inversion accuracy while minimizing significant stress distortion,and excluding regions with severe stress distortion near the model edges while utilizing the central part of the model for subsequent simulations.These two strategies have been successfully implemented in the nonlinear in situ stress inversion of the Xincheng Gold Mine and have achieved higher inversion accuracy than the linear method.Specifically,the linear and nonlinear inversion methods yield root mean square errors(RMSE)of 4.15 and 3.2,and inversion relative errors(δAve)of 22.08%and 17.55%,respectively.Therefore,the nonlinear inversion method outperforms the traditional multiple linear regression method,even in the presence of a systematic reduction in the nonlinear stress boundaries.展开更多
Accurate medical diagnosis,which involves identifying diseases based on patient symptoms,is often hindered by uncertainties in data interpretation and retrieval.Advanced fuzzy set theories have emerged as effective to...Accurate medical diagnosis,which involves identifying diseases based on patient symptoms,is often hindered by uncertainties in data interpretation and retrieval.Advanced fuzzy set theories have emerged as effective tools to address these challenges.In this paper,new mathematical approaches for handling uncertainty in medical diagnosis are introduced using q-rung orthopair fuzzy sets(q-ROFS)and interval-valued q-rung orthopair fuzzy sets(IVq-ROFS).Three aggregation operators are proposed in our methodologies:the q-ROF weighted averaging(q-ROFWA),the q-ROF weighted geometric(q-ROFWG),and the q-ROF weighted neutrality averaging(qROFWNA),which enhance decision-making under uncertainty.These operators are paired with ranking methods such as the similarity measure,score function,and inverse score function to improve the accuracy of disease identification.Additionally,the impact of varying q-rung values is explored through a sensitivity analysis,extending the analysis beyond the typical maximum value of 3.The Basic Uncertain Information(BUI)method is employed to simulate expert opinions,and aggregation operators are used to combine these opinions in a group decisionmaking context.Our results provide a comprehensive comparison of methodologies,highlighting their strengths and limitations in diagnosing diseases based on uncertain patient data.展开更多
Serial-parallel manipulators are of great interest to academic community in recent years,especially those composed of classical parallel mechanisms.There have been many studies around 2(3RPS)and 2(3SPR)S-PMs,but unfor...Serial-parallel manipulators are of great interest to academic community in recent years,especially those composed of classical parallel mechanisms.There have been many studies around 2(3RPS)and 2(3SPR)S-PMs,but unfortunately their inverse kinematics have not yet been resolved.This paper discovers that the unknown kinematic parameters of middle platform are responsible for the unresolvable of inverse kinematics,meanwhile the unknown kinematic parameters of middle platform also have huge coupling relationships.Therefore,to break through this challenges,the huge coupling relationships are decoupled layer by layer,the kinematic parameters of middle platform are solved by combining Sylvester's elimination method,and the inverse displacements of 2(3RPS)and 2(3SPR)S-PMs are obtained subsequently.This paper not only solves the inverse kinematics of classical 2(3RPS)and 2(3SPR)S-PMs,but also reveals the essence of the inverse kinematics of general(3-DOF)+(3-DOF)6-DOF S-PMs and proposes a corresponding solution.展开更多
In this study,we examine the problem of sliced inverse regression(SIR),a widely used method for sufficient dimension reduction(SDR).It was designed to find reduced-dimensional versions of multivariate predictors by re...In this study,we examine the problem of sliced inverse regression(SIR),a widely used method for sufficient dimension reduction(SDR).It was designed to find reduced-dimensional versions of multivariate predictors by replacing them with a minimally adequate collection of their linear combinations without loss of information.Recently,regularization methods have been proposed in SIR to incorporate a sparse structure of predictors for better interpretability.However,existing methods consider convex relaxation to bypass the sparsity constraint,which may not lead to the best subset,and particularly tends to include irrelevant variables when predictors are correlated.In this study,we approach sparse SIR as a nonconvex optimization problem and directly tackle the sparsity constraint by establishing the optimal conditions and iteratively solving them by means of the splicing technique.Without employing convex relaxation on the sparsity constraint and the orthogonal constraint,our algorithm exhibits superior empirical merits,as evidenced by extensive numerical studies.Computationally,our algorithm is much faster than the relaxed approach for the natural sparse SIR estimator.Statistically,our algorithm surpasses existing methods in terms of accuracy for central subspace estimation and best subset selection and sustains high performance even with correlated predictors.展开更多
We report a robust pillar-layered metal-organic framework,Zn‑tfbdc‑dabco(tfbdc:tetrafluoroterephthal-ate,dabco:1,4-diazabicyclo[2.2.2]octane),featuring the fluorinated pore environment,for the preferential binding of ...We report a robust pillar-layered metal-organic framework,Zn‑tfbdc‑dabco(tfbdc:tetrafluoroterephthal-ate,dabco:1,4-diazabicyclo[2.2.2]octane),featuring the fluorinated pore environment,for the preferential binding of propane over propylene and thus highly inverse selective separation of propane/propylene mixture.The inverse propane-selective performance of Zn‑tfbdc‑dabco for the propane/propylene separation was validated by single-component gas adsorption isotherms,isosteric enthalpy of adsorption calculations,ideal adsorbed solution theory calculations,along with the breakthrough experiment.The customized fluorinated networks served as a propane-trap to form more interactions with the exposed hydrogen atoms of propane,as unveiled by the simulation studies at the molecular level.With the advantage of inverse propane-selective adsorption behavior,high adsorption capacity,good cycling stability,and low isosteric enthalpy of adsorption,Zn‑tfbdc‑dabco can be a promising candidate adsorbent for the challenging propane/propylene separation to realize one-step purification of the target propylene substance.展开更多
This study analyzed 10 years of sounding data from Yongxing Island to characterize temperature,humidity,and wind profiles in the atmospheric boundary layer(ABL).Our key findings are as follows.(1)Relative humidity inv...This study analyzed 10 years of sounding data from Yongxing Island to characterize temperature,humidity,and wind profiles in the atmospheric boundary layer(ABL).Our key findings are as follows.(1)Relative humidity inversions(RIs)were the most frequent events(99.8%),followed by surface-based temperature inversions(SBIs,63%),elevated temperature inversions(EIs,50%),and low-level jets(LLJs,41%).(2)Higher near-surface temperature leads to a decrease in EI height,thickness,and intensity.(3)When EIs occurred,RIs were consistently observed beneath the base of the EIs.(4)The intensity of the RIs correlated negatively with surface humidity,whereas the intensity of the LLJs correlated positively with surface winds except in summer.(5)The boundary layer heights(BLHs)are best estimated using the potential temperature gradient method when EIs occur,otherwise,the Richardson number method is the best method.In contrast,the relative humidity and temperature gradient methods exhibit high dispersion or uncertainty.(6)The BLHs showed seasonal variability,peaking in winter(350–1450 m).These findings advance our understanding of ABL dynamics and BLH estimation over tropical islands.展开更多
基金the financial support from the National Natural Science Foundation of China(No.61904005,52103010 and 52003200)Guangdong Provincial Department of Education Featured Innovation Project(No.2021KTSCX138)+4 种基金Jiangmen Key Project of Research for Basic and Basic Application(No.2021030102800007443 and 2021030102790006114)the Science Foundation for Young Research Group of Wuyi University(No.2020AL021,2019AL019,and 2020AL016)Wuyi University-Hong Kong/Macao Joint Research Funds(No.2021WGALH05)Youth Innovation Talent Project for the Universities of Guangdong(No.2020KQNCX089)Guangdong Basic and Applied Basic Research Foundation(No.2020A1515110897)
文摘Organic perovskites are promising semiconductor materials for advanced photoelectric applications.Their fluorescence typically shows a negative temperature coefficient due to bandgap change and structural instability.In this study,a novel perovskite-based composite with positive sensitivity to temperature was designed and obtained based on its inverse temperature crystallization,demonstrating good flexibility and solution processability.The supercritical drying method was used to address the limitations of annealing drying in preparing high-performance perovskite.Optimizing the precursor composition proved to be an effective approach for achieving high fluorescence and structural integrity in the perovskite material.This perovskite-based composite exhibited a positive temperature sensitivity of 28.563%℃^(-1)for intensity change and excellent temperature cycling reversibility in the range of 25-40℃in an ambient environment.This made it suitable for use as a smart window with rapid response.Furthermore,the perovskite composite was found to offer temperature-sensing photoluminescence and flexible processability due to its components of perovskite-based compounds and polyethylene oxide.The organic precursor solvent could be a promising candidate for use as ink to print or write on various substrates for optoelectronic devices responding to temperature.
基金financial support from the National Key R&D Program of China(No.2021YFA1200301)the National Natural Science Foundation of China(Nos.21890734,92156018,and 21972150)CAS Project for Young Scientists in Basic Research(No.YSBR-027)。
文摘Here,we designed asymmetric(m DS)and symmetrical(d DS)chiral V-shaped molecules by linking one or two dansyl groups to trans-1,2-cyclohexane diamine and investigated the solvent-regulated structural transformation and inversed circularly polarized luminescence(CPL)in the self-assemblies.Upon increasing water volume fraction(fw)in the mixed solvent of water/acetonitrile,asymmetric mDS selfassembled into hollow nanospheres and microtubes,while solid nanospheres and solid microplates were corresponding to symmetric d DS.During this transformation process,the emission of m DS and d DS was changed from yellow-green to blue and cyan color,which was ascribed to twisted intramolecular charge transfer(TICT)and locally excited(LE)fluorescence of V-shaped DS molecules.The conformation of N,Ndimethyl groups with respect to naphthalene ring also led to the transformation of structures.These tubular and platelike structures had stronger and reversed CPL signals in comparison with spheroidal structures.The chiral information of DS assembly could be effective transferred to achiral Nile red via co-assembly strategy,which endowed Nile red exhibiting inversed induced CPL signal regulated by water fraction.This work provides a method for achieving a variety of self-assembled structures with adjustable chiroptical properties.
基金supported by the West Light Talents Cultivation Program of Chinese Academy of Sciences (XBBS 200801)the National Natural Science Foundation of China (40801146)the JSPS Project (21403001)
文摘Leaf biochemical properties have been widely assessed using hyperspectral reflectance information by inversion of PROSPECT model or by using hyperspectral indices, but few studies have focused on arid ecosystems. As a dominant species of riparian ecosystems in arid lands, Populus euphratica Oliv. is an unusual tree species with polymorphic leaves along the vertical profile of canopy corresponding to different growth stages. In this study, we evaluated both the inversed PROSPECT model and hyperspectral indices for estimating biochemical properties of P. euphratica leaves. Both the shapes and biochemical properties of P. euphratica leaves were found to change with the heights from ground surface. The results indicated that the model inversion calibrated for each leaf shape performed much better than the model calibrated for all leaf shapes, and also better than hyperspectral indices. Similar results were obtained for estimations of equivalent water thickness （EWT） and leaf mass per area （LMA）. Hyperspectral indices identified in this study for estimating these leaf properties had root mean square error （RMSE） and R2 values between those obtained with the two calibration strategies using the inversed PROSPECT model. Hence, the inversed PROSPECT model can be applied to estimate leaf biochemical properties in arid ecosystems, but the calibration to the model requires special attention.
文摘A kind of international rapid field measurement methods of hydraulic conductivity and it's applications in Sanjiang Plain have been introduced in the paper.
基金State Natural Science Foundation of China (49774224)Joint Seismological Science Foundation of China (102019).
文摘Gravity variation data observed in the process of seismogenesis and occurrences of earthquakes show that the location with the greatest gravity changes does not necessarily coincide with the epicenter. To explain this we defined the center of effective mass of stress volume as hypocentroid, and the vertical projection of which on the earths surface as epicentroid. Here we adopt three rotating models, including spheroid, ellipsoid and cylinder, to represent the region of an impending earthquake. Based on the models of gravity variations induced by uniform dilatancy, epicentroids associated with sixteen earthquakes with M>4.0 occurred in 1981~2000 in the Beijing-Tianjin-Tangshan-Zhangjiakou region are determined by means of a proposed least squares iterative inversion method. The results indicate that cylinder model is preferable to the other two, and epicentroids obtained by the cylinder model separate from the epicenters by a range of 0~40 km. Epicentroids are inevitably located within intact tectonic blocks, and usually cluster in groups; while the epicenters are generally located at the terminations of faults or at the intersections of faults. It seems that there exist earthquake-hatching areas in the block among faults. Earthquakes hatch in these areas, but occur around these areas, meanwhile the existence of faults may play an important role in controlling the processes.
基金the National Natural Science Foundation of China (No. 22101280)Wenzhou Medical University (No. KYYW201901)+1 种基金University of Chinese Academy of Science (Nos. WIBEZD201700103 and WIUCASQD2020005)Zhejiang Provincial Natural Science Foundation (No. LQ20B020009) for financial support。
文摘To realize the handedness controllable circularly polarized luminescence(CPL) system remains challenging. Herein, the solvent-mediated CPL inversion and amplification systems were successfully constructed by camptothecin derivative(CPT-A). Due to the planar structure of N,N-dimethylformamide, it could coassemble with CPT-A, resulting in the alteration of g_(lum) from –0.0082 to +0.0085 by increasing water content. While in the non-planar solvent(hexafluoroisopropanol), the g_(lum) was amplified to 0.034 with the increase in water content. Moreover, the CPT-A could react with the glutathione, resulting in the anticancer drug CPT to make it more toxic to the cancer cells. Overall, the handedness controllable CPL systems were realized by tuning the supramolecular self-assembly of a prodrug.
文摘As an advanced device for observing atmospheric winds,the spaceborne Doppler Asymmetric Spatial Heterodyne(DASH)interferometer also encounters challenges associated with phase distortion,par-ticularly in limb sounding scenarios.This paper discusses interferogram modeling and phase distortion cor-rection techniques for spaceborne DASH interferometers.The modeling of phase distortion interferograms with and without Doppler shift for limb observation was conducted,and the effectiveness of the analytical expression was verified through numerical simulation.The simulation results indicate that errors propagate layer by layer while using the onion-peeling inversion algorithm to handle phase-distorted interferograms.In contrast,the phase distortion correction algorithm can achieve effective correction.This phase correction method can be successfully applied to correct phase distortions in the interferograms of the spaceborne DASH interferometer,providing a feasible solution to enhance its measurement accuracy.
基金supported by Zhengzhou PM_(2.5)and O_(3)Collaborative Control and Monitoring Project(No.20220347A)the 2020 National Supercomputing Zhengzhou Center Innovation Ecosystem Construction Technology Project(No.201400210700).
文摘Improving the accuracy of anthropogenic volatile organic compounds(VOCs)emission inventory is crucial for reducing atmospheric pollution and formulating control policy of air pollution.In this study,an anthropogenic speciated VOCs emission inventory was established for Central China represented by Henan Province at a 3 km×3 km spatial resolution based on the emission factormethod.The 2019 VOCs emission in Henan Provincewas 1003.5 Gg,while industrial process source(33.7%)was the highest emission source,Zhengzhou(17.9%)was the city with highest emission and April and August were the months with the more emissions.High VOCs emission regions were concentrated in downtown areas and industrial parks.Alkanes and aromatic hydrocarbons were the main VOCs contribution groups.The species composition,source contribution and spatial distribution were verified and evaluated through tracer ratio method(TR),Positive Matrix Factorization Model(PMF)and remote sensing inversion(RSI).Results show that both the emission results by emission inventory(EI)(15.7 Gg)and by TRmethod(13.6 Gg)and source contribution by EI and PMF are familiar.The spatial distribution of HCHO primary emission based on RSI is basically consistent with that of HCHO emission based on EI with a R-value of 0.73.The verification results show that the VOCs emission inventory and speciated emission inventory established in this study are relatively reliable.
基金supported by Fundamental Research Funds for the Central Universities,CHD300102264715National Key Research and Development Program of China under Grant 2021YFA0716902Natural Science Basic Research Program of Shaanxi 2024JCYBMS-199。
文摘Young's modulus and Poisson's ratio are crucial parameters for reservoir characterization and rock brittleness evaluation.Conventional methods often rely on indirect computation or approximations of the Zoeppritz equations to estimate Young's modulus,which can introduce cumulative errors and reduce the accuracy of inversion results.To address these issues,this paper introduces the analytical solution of the Zoeppritz equation into the inversion process.The equation is re-derived and expressed in terms of Young's modulus,Poisson's ratio,and density.Within the Bayesian framework,we construct an objective function for the joint inversion of PP and PS waves.Traditional gradient-based algorithms often suffer from low precision and the computational complexity.In this study,we address limitations of conventional approaches related to low precision and complicated code by using Circle chaotic mapping,Levy flights,and Gaussian mutation to optimize the quantum particle swarm optimization(QPSO),named improved quantum particle swarm optimization(IQPSO).The IQPSO demonstrates superior global optimization capabilities.We test the proposed inversion method with both synthetic and field data.The test results demonstrate the proposed method's feasibility and effectiveness,indicating an improvement in inversion accuracy over traditional methods.
基金supported by the National Natural Science Foundation of China(Grant Nos.22225801,W2441009,22408228)。
文摘As energy demands continue to rise in modern society,the development of high-performance lithium-ion batteries(LIBs)has become crucial.However,traditional research methods of material science face challenges such as lengthy timelines and complex processes.In recent years,the integration of machine learning(ML)in LIB materials,including electrolytes,solid-state electrolytes,and electrodes,has yielded remarkable achievements.This comprehensive review explores the latest applications of ML in predicting LIB material performance,covering the core principles and recent advancements in three key inverse material design strategies:high-throughput virtual screening,global optimization,and generative models.These strategies have played a pivotal role in fostering LIB material innovations.Meanwhile,the paper briefly discusses the challenges associated with applying ML to materials research and offers insights and directions for future research.
基金supported by the Beijing Natural Science Foundation(No.L212029)the National Natural Science Foundation of China(No.62271043).
文摘To meet the requirements of electromagnetic(EM)theory and applied physics,this study presents an overview of the state-of-the-art research on obtaining the EM properties of media and points out potential solutions that can break through the bottlenecks of current methods.Firstly,based on the survey of three mainstream approaches for acquiring EM properties of media,we identify the difficulties when implementing them in realistic environments.With a focus on addressing these problems and challenges,we propose a novel paradigm for obtaining the EM properties of multi-type media in realistic environments.Particularly,within this paradigm,we describe the implementation approach of the key technology,namely“multipath extraction using heterogeneous wave propagation data in multi-spectrum cases”.Finally,the latest measurement and simulation results show that the EM properties of multi-type media in realistic environments can be precisely and efficiently acquired by the methodology proposed in this study.
文摘A 3D crustal model was constructed using a combination of cutting-edge techniques,which were integrated to provide a density model for Egypt and address the sporadic distribution of seismic data.These techniques include obtaining gravity data from the Gravity Field and Steady-State Ocean Circulation Explorer(GOCE),creating seismic profiles,analyzing the receiver functions of seismic data,obtaining information from boreholes,and providing geological interpretations.GOCE satellite gravity data were processed to construct a preliminary model based on nonlinear inversions of the data.A regional crustal thickness model was developed using receiver functions,seismic refraction profiles,and geological insights.The inverted model was validated using borehole data and compared with seismic estimates.The model exhibited strong consistency and revealed a correlation between crustal thickness,geology,and tectonics of Egypt.It showed that the shallowest depths of the Moho are located in the north along the Mediterranean Sea and in the eastern part along the Red Sea,reflecting an oceanic plate with a thin,high-density crust.The deepest Moho depths are located in the southwestern part of Egypt,Red Sea coastal mountains,and Sinai Peninsula.The obtained 3D model of crustal thickness provided finely detailed Moho depth estimates that aligned closely with geology and tectonic characteristics of Egypt,contributing valuable insights into the subsurface structure and tectonic processes of region.
基金funded by theNationalNatural Science Foundation of China(52061020)Major Science and Technology Projects in Yunnan Province(202302AG050009)Yunnan Fundamental Research Projects(202301AV070003).
文摘Finding materials with specific properties is a hot topic in materials science.Traditional materials design relies on empirical and trial-and-error methods,requiring extensive experiments and time,resulting in high costs.With the development of physics,statistics,computer science,and other fields,machine learning offers opportunities for systematically discovering new materials.Especially through machine learning-based inverse design,machine learning algorithms analyze the mapping relationships between materials and their properties to find materials with desired properties.This paper first outlines the basic concepts of materials inverse design and the challenges faced by machine learning-based approaches to materials inverse design.Then,three main inverse design methods—exploration-based,model-based,and optimization-based—are analyzed in the context of different application scenarios.Finally,the applications of inverse design methods in alloys,optical materials,and acoustic materials are elaborated on,and the prospects for materials inverse design are discussed.The authors hope to accelerate the discovery of new materials and provide new possibilities for advancing materials science and innovative design methods.
基金financially supported by the National Natural Science Foundation of China(42250102,42250101)the Macao Foundation。
文摘This study presents an inversion method to recover the tidal flow velocity using tidal signals extracted from geomagnetic satellite dataset.By integrating the latest Earth conductivity profile and the Earth's magnetic field model,the limited memory quasi-Newton method(L-BFGS)is used to directly invert seawater flow velocities.We used the radial component of the induced magnetic field as the observed data,constructed an L_(2)-norm-based data misfit term using theoretical response and observed data,and applied smoothness constraints to the ocean flow velocity.The results agree well with the widely used HAMTIDE model in low-and mid-latitude regions,which is attributed to Macao Science Satellite-1's(MSS-1)unique low-inclination orbit of full coverage in these areas.These findings underscore MSS-1's potential to advance research on tidal-induced magnetic fields and their applications in ocean dynamics studies.
基金funded by the National Key R&D Program of China(Grant No.2022YFC2903904)the National Natural Science Foundation of China(Grant Nos.51904057 and U1906208).
文摘Due to the heterogeneity of rock masses and the variability of in situ stress,the traditional linear inversion method is insufficiently accurate to achieve high accuracy of the in situ stress field.To address this challenge,nonlinear stress boundaries for a numerical model are determined through regression analysis of a series of nonlinear coefficient matrices,which are derived from the bubbling method.Considering the randomness and flexibility of the bubbling method,a parametric study is conducted to determine recommended ranges for these parameters,including the standard deviation(σb)of bubble radii,the non-uniform coefficient matrix number(λ)for nonlinear stress boundaries,and the number(m)and positions of in situ stress measurement points.A model case study provides a reference for the selection of these parameters.Additionally,when the nonlinear in situ stress inversion method is employed,stress distortion inevitably occurs near model boundaries,aligning with the Saint Venant's principle.Two strategies are proposed accordingly:employing a systematic reduction of nonlinear coefficients to achieve high inversion accuracy while minimizing significant stress distortion,and excluding regions with severe stress distortion near the model edges while utilizing the central part of the model for subsequent simulations.These two strategies have been successfully implemented in the nonlinear in situ stress inversion of the Xincheng Gold Mine and have achieved higher inversion accuracy than the linear method.Specifically,the linear and nonlinear inversion methods yield root mean square errors(RMSE)of 4.15 and 3.2,and inversion relative errors(δAve)of 22.08%and 17.55%,respectively.Therefore,the nonlinear inversion method outperforms the traditional multiple linear regression method,even in the presence of a systematic reduction in the nonlinear stress boundaries.
文摘Accurate medical diagnosis,which involves identifying diseases based on patient symptoms,is often hindered by uncertainties in data interpretation and retrieval.Advanced fuzzy set theories have emerged as effective tools to address these challenges.In this paper,new mathematical approaches for handling uncertainty in medical diagnosis are introduced using q-rung orthopair fuzzy sets(q-ROFS)and interval-valued q-rung orthopair fuzzy sets(IVq-ROFS).Three aggregation operators are proposed in our methodologies:the q-ROF weighted averaging(q-ROFWA),the q-ROF weighted geometric(q-ROFWG),and the q-ROF weighted neutrality averaging(qROFWNA),which enhance decision-making under uncertainty.These operators are paired with ranking methods such as the similarity measure,score function,and inverse score function to improve the accuracy of disease identification.Additionally,the impact of varying q-rung values is explored through a sensitivity analysis,extending the analysis beyond the typical maximum value of 3.The Basic Uncertain Information(BUI)method is employed to simulate expert opinions,and aggregation operators are used to combine these opinions in a group decisionmaking context.Our results provide a comprehensive comparison of methodologies,highlighting their strengths and limitations in diagnosing diseases based on uncertain patient data.
基金Supported by National Natural Science Foundation of China(Grant No.52275033)National Natural Science Youth Foundation of China(Grant No.52205033)Hebei Provincial Natural Science Foundation of China(Grant No.E2021203019)。
文摘Serial-parallel manipulators are of great interest to academic community in recent years,especially those composed of classical parallel mechanisms.There have been many studies around 2(3RPS)and 2(3SPR)S-PMs,but unfortunately their inverse kinematics have not yet been resolved.This paper discovers that the unknown kinematic parameters of middle platform are responsible for the unresolvable of inverse kinematics,meanwhile the unknown kinematic parameters of middle platform also have huge coupling relationships.Therefore,to break through this challenges,the huge coupling relationships are decoupled layer by layer,the kinematic parameters of middle platform are solved by combining Sylvester's elimination method,and the inverse displacements of 2(3RPS)and 2(3SPR)S-PMs are obtained subsequently.This paper not only solves the inverse kinematics of classical 2(3RPS)and 2(3SPR)S-PMs,but also reveals the essence of the inverse kinematics of general(3-DOF)+(3-DOF)6-DOF S-PMs and proposes a corresponding solution.
文摘In this study,we examine the problem of sliced inverse regression(SIR),a widely used method for sufficient dimension reduction(SDR).It was designed to find reduced-dimensional versions of multivariate predictors by replacing them with a minimally adequate collection of their linear combinations without loss of information.Recently,regularization methods have been proposed in SIR to incorporate a sparse structure of predictors for better interpretability.However,existing methods consider convex relaxation to bypass the sparsity constraint,which may not lead to the best subset,and particularly tends to include irrelevant variables when predictors are correlated.In this study,we approach sparse SIR as a nonconvex optimization problem and directly tackle the sparsity constraint by establishing the optimal conditions and iteratively solving them by means of the splicing technique.Without employing convex relaxation on the sparsity constraint and the orthogonal constraint,our algorithm exhibits superior empirical merits,as evidenced by extensive numerical studies.Computationally,our algorithm is much faster than the relaxed approach for the natural sparse SIR estimator.Statistically,our algorithm surpasses existing methods in terms of accuracy for central subspace estimation and best subset selection and sustains high performance even with correlated predictors.
文摘We report a robust pillar-layered metal-organic framework,Zn‑tfbdc‑dabco(tfbdc:tetrafluoroterephthal-ate,dabco:1,4-diazabicyclo[2.2.2]octane),featuring the fluorinated pore environment,for the preferential binding of propane over propylene and thus highly inverse selective separation of propane/propylene mixture.The inverse propane-selective performance of Zn‑tfbdc‑dabco for the propane/propylene separation was validated by single-component gas adsorption isotherms,isosteric enthalpy of adsorption calculations,ideal adsorbed solution theory calculations,along with the breakthrough experiment.The customized fluorinated networks served as a propane-trap to form more interactions with the exposed hydrogen atoms of propane,as unveiled by the simulation studies at the molecular level.With the advantage of inverse propane-selective adsorption behavior,high adsorption capacity,good cycling stability,and low isosteric enthalpy of adsorption,Zn‑tfbdc‑dabco can be a promising candidate adsorbent for the challenging propane/propylene separation to realize one-step purification of the target propylene substance.
基金National Key Research and Development Program of China(2023YFC3008002)National Natural Science Foundation of China(U21A6001,42075059)Key Laboratory of Guangdong Province(2020B1212060025)。
文摘This study analyzed 10 years of sounding data from Yongxing Island to characterize temperature,humidity,and wind profiles in the atmospheric boundary layer(ABL).Our key findings are as follows.(1)Relative humidity inversions(RIs)were the most frequent events(99.8%),followed by surface-based temperature inversions(SBIs,63%),elevated temperature inversions(EIs,50%),and low-level jets(LLJs,41%).(2)Higher near-surface temperature leads to a decrease in EI height,thickness,and intensity.(3)When EIs occurred,RIs were consistently observed beneath the base of the EIs.(4)The intensity of the RIs correlated negatively with surface humidity,whereas the intensity of the LLJs correlated positively with surface winds except in summer.(5)The boundary layer heights(BLHs)are best estimated using the potential temperature gradient method when EIs occur,otherwise,the Richardson number method is the best method.In contrast,the relative humidity and temperature gradient methods exhibit high dispersion or uncertainty.(6)The BLHs showed seasonal variability,peaking in winter(350–1450 m).These findings advance our understanding of ABL dynamics and BLH estimation over tropical islands.
