We provide a way to precisely control the geometry of a SiNx nanopore by adjusting the applied electric pulse. The pore is generated by applying the current pulse across a SiNx membrane, which is immersed in potassium...We provide a way to precisely control the geometry of a SiNx nanopore by adjusting the applied electric pulse. The pore is generated by applying the current pulse across a SiNx membrane, which is immersed in potassium chloride solution. We can generate single conical and cylindrical pores with different electric pulses. A theoretical model based on the Poisson and Nernst-Planck equations is employed to simulate the ion transport properties in the channel. In turn, we can analyze pore geometries by fitting the experimental current-voltage （I-V） curves. for the conical pores with a pore size of 0.5-2nm in diameter, the slope angles are around -2.5% to -10%. Moreover, the pore orifice can be enlarged slightly by additional repeating pulses. The conic pore lumen becomes close to a cylindrical channel, resulting in a symmetry I-V transport under positive and negative biases. A qualitative understanding of these effects will help us to prepare useful solid-nanopores as demanded.展开更多
In this paper, we present our research on building computing machines consciousness about intuitive geometry based on mathematics experiments and statistical inference. The investigation consists of the following five...In this paper, we present our research on building computing machines consciousness about intuitive geometry based on mathematics experiments and statistical inference. The investigation consists of the following five steps. At first, we select a set of geometric configurations and for each configuration we construct a large amount of geometric data as observation data using dynamic geometry programs together with the pseudo-random number generator. Secondly, we refer to the geometric predicates in the algebraic method of machine proof of geometric theorems to construct statistics suitable for measuring the approximate geometric relationships in the observation data. In the third step, we propose a geometric relationship detection method based on the similarity of data distribution, where the search space has been reduced into small batches of data by pre-searching for efficiency, and the hypothetical test of the possible geometric relationships in the search results has be performed. In the fourth step, we explore the integer relation of the line segment lengths in the geometric configuration in addition. At the final step, we do numerical experiments for the pre-selected geometric configurations to verify the effectiveness of our method. The results show that computer equipped with the above procedures can find out the hidden geometric relations from the randomly generated data of related geometric configurations, and in this sense, computing machines can actually attain certain consciousness of intuitive geometry as early civilized humans in ancient Mesopotamia.展开更多
A spice formulation study in Burkina Faso was carried out using local ingredients for the benefit of households. The objective of this study was to propose some spice formulations based on local ingredients in order t...A spice formulation study in Burkina Faso was carried out using local ingredients for the benefit of households. The objective of this study was to propose some spice formulations based on local ingredients in order to reduce the use of chemical spices in the preparation of different dishes. The Design of Experiments (DOE) methodology was used for the formulation of the spices and their physicochemical, nutritional and sensory characteristics were evaluated by standardized and standard methods. The results obtained showed lipid contents (g/100 g DM) ranging from 10.41 ± 0.26 to 15.64 ± 0.68, total sugars from 4.39 ± 0.32 to 5.46 ± 0.31, protein from 3.65 ± 0.17 to 12.04 ± 0.35 and ash from 5.83 ± 0.01 to 7.02 ± 0.01. The polyphenol content ranged from 9.09 ± 1.60 to 11.33 ± 0.90, and the flavonoid content ranged from 0.65 ± 0.03 to 1.08 ± 0.13. The sensory analysis carried out showed that the spices have generally satisfactory organoleptic characteristics. These results constitute new information in the diet of populations and are an alternative to the chemical spices used in their cooking.展开更多
In this work,the selected icebreaker model experiment is performed in a towing tank.We focus on the influence of seawater salinity on ship ice resistance in the ice floe field and the innovative ice model and ship mod...In this work,the selected icebreaker model experiment is performed in a towing tank.We focus on the influence of seawater salinity on ship ice resistance in the ice floe field and the innovative ice model and ship model test technology,including the similitude rule of ship model tests,test principles,and validation with full-scale ship data.A formula for calculating the relationship between the temperature and salinity of the water is constructed,which can be used to simulate the role of seawater in freshwater ice pools.On this basis,the effect of salinity on the resistance of ships sailing in broken ice fields is studied.A technique in which artificial ice made of polyethylene spheres is used to simulate ice resistance is proposed.With a series of ship model experiments in spherical and triangular ice fields,the effects of salinity and velocity on the ice resistance test of the ship model are analyzed.A relationship of the ice resistance of the ship model to the spherical ice field and the triangular ice field is proposed.The conversion results are consistent with onsite data of the full-size ship,which verifies the method of converting the test results of the ship model to the prototype.展开更多
The Taishan Antineutrino Observatory(TAO)is a satellite experiment of the Jiangmen Underground Neutrino Observatory,located near the Taishan nuclear power plant(NPP).The TAO aims to measure the energy spectrum of reac...The Taishan Antineutrino Observatory(TAO)is a satellite experiment of the Jiangmen Underground Neutrino Observatory,located near the Taishan nuclear power plant(NPP).The TAO aims to measure the energy spectrum of reactor antineutrinos with unprecedented precision,which would benefit both reactor neutrino physics and the nuclear database.A detector geometry and event visualization system was developed for the TAO.The software was based on ROOT packages and embedded in the TAO offline software framework.This provided an intuitive tool for visualizing the detector geometry,tuning the reconstruction algorithm,understanding neutrino physics,and monitoring the operation of reactors at NPP.Further applications of the visualization system in the experimental operation of TAO and its future development are discussed.展开更多
Soft electronics,which are designed to function under mechanical deformation(such as bending,stretching,and folding),have become essential in applications like wearable electronics,artificial skin,and brain-machine in...Soft electronics,which are designed to function under mechanical deformation(such as bending,stretching,and folding),have become essential in applications like wearable electronics,artificial skin,and brain-machine interfaces.Crystalline silicon is one of the most mature and reliable materials for high-performance electronics;however,its intrinsic brittleness and rigidity pose challenges for integrating it into soft electronics.Recent research has focused on overcoming these limitations by utilizing structural design techniques to impart flexibility and stretchability to Si-based materials,such as transforming them into thin nanomembranes or nanowires.This review summarizes key strategies in geometry engineering for integrating crystalline silicon into soft electronics,from the use of hard silicon islands to creating out-of-plane foldable silicon nanofilms on flexible substrates,and ultimately to shaping silicon nanowires using vapor-liquid-solid or in-plane solid-liquid-solid techniques.We explore the latest developments in Si-based soft electronic devices,with applications in sensors,nanoprobes,robotics,and brain-machine interfaces.Finally,the paper discusses the current challenges in the field and outlines future research directions to enable the widespread adoption of silicon-based flexible electronics.展开更多
This paper delves into the visual teaching of analytic geometry facilitated by GeoGebra software.Through a meticulous analysis of the current landscape of analytic geometry instruction and the distinct advantages of G...This paper delves into the visual teaching of analytic geometry facilitated by GeoGebra software.Through a meticulous analysis of the current landscape of analytic geometry instruction and the distinct advantages of GeoGebra software,it expounds upon the imperative and feasibility of its application within the realm of analytic geometry teaching.Furthermore,it presents a detailed account of the teaching practice process grounded in this software,encompassing teaching design and the demonstration of teaching cases,and conducts an in-depth investigation and analysis of the teaching outcomes.The research findings indicate that the GeoGebra software can effectively elevate the level of visualization in analytic geometry teaching,thereby augmenting students’learning enthusiasm and comprehension capabilities.It thus offers novel perspectives and methodologies for the pedagogical reform of analytic geometry.展开更多
Fatigue failure continues to be a significant challenge in designing structural and mechanical components subjected to repeated and complex loading.While earlier studies mainly examined material properties and how str...Fatigue failure continues to be a significant challenge in designing structural and mechanical components subjected to repeated and complex loading.While earlier studies mainly examined material properties and how stress affects lifespan,this review offers the first comprehensive,multiscale comparison of strategies that optimize geometry to improve fatigue performance.This includes everything from microscopic features like the shape of graphite nodules to large-scale design elements such as fillets,notches,and overall structural layouts.We analyze and combine various methods,including topology and shape optimization,the ability of additive manufacturing to finetune internal geometries,and reliability-based design approaches.A key new contribution is our proposal of a standard way to evaluate geometry-focused fatigue design,allowing for consistent comparison and encouraging validation across different fields.Furthermore,we highlight important areas for future research,such as incorporating manufacturing flaws,using multiscale models,and integrating machine learning techniques.This work is the first to provide a broad geometric viewpoint in fatigue engineering,laying the groundwork for future design methods that are driven by data and centered on reliability.展开更多
We have developed a class of charged,anisotropic,and spherically symmetric solutions,described by the function f(R,A)=R+a A,where R represents the Ricci scalar,A is the anticurvature scalar,andαis the coupling consta...We have developed a class of charged,anisotropic,and spherically symmetric solutions,described by the function f(R,A)=R+a A,where R represents the Ricci scalar,A is the anticurvature scalar,andαis the coupling constant.The model was constructed using the Karmarkar condition to obtain the radial metric component,while the time metric component followed the approach proposed by Adler.We assumed a specific charge distribution inside the star to build the model.To ensure a smooth spacetime transition,we established boundary conditions,considering Bardeen?s solution for the exterior spacetime.Additionally,we examined various physical aspects,such as energy density,pressure components,pressure anisotropy,energy conditions,the equation of state,surface redshift,compactness factor,adiabatic index,sound speed,and the Tolman-Oppenheimer-Volkoff equilibrium condition.All these conditions were met,demonstrating that the solutions we obtained are physically viable.展开更多
In this paper,we propose a numerical calculation model of the multigroup neutron diffusion equation in 3D hexagonal geometry using the nodal Green's function method and verified it.We obtained one-dimensional tran...In this paper,we propose a numerical calculation model of the multigroup neutron diffusion equation in 3D hexagonal geometry using the nodal Green's function method and verified it.We obtained one-dimensional transverse integrated equations using the transverse integration procedure over 3D hexagonal geometry and denoted the solutions as a nodal Green's functions under the Neumann boundary condition.By applying a quadratic polynomial expansion of the transverse-averaged quantities,we derived the net neutron current coupling equation,equation for the expansion coefficients of the transverse-averaged neutron flux,and formulas for the coefficient matrix of these equations.We formulated the closed system of equations in correspondence with the boundary conditions.The proposed model was tested by comparing it with the benchmark for the VVER-440 reactor,and the numerical results were in good agreement with the reference solutions.展开更多
The traditional orbit determination method based on pulsar profile distortion can determine the six elements of the orbit.However,the estimation accuracies of these methods are limited and the computational load of a ...The traditional orbit determination method based on pulsar profile distortion can determine the six elements of the orbit.However,the estimation accuracies of these methods are limited and the computational load of a six-dimensional search is huge.To solve this problem,the differential-geometry-based Multi-dimensional Joint Position-Velocity Estimation(MJPVE)using Crab pulsar profile distortion is proposed in this paper.Firstly,through theoretical analysis,it is found that the pulsar profile distortion caused by the initial state error in some joint positionvelocity directions is very small.In other words,the accuracies of estimation in these directions are very low.Namely,the search dimension can be reduced,which in turn greatly reduces the computational load.Then,we construct the chi-squared function of the pulsar profile with respect to the estimation error in joint position-velocity direction and use differential geometry to find the joint position-velocity directions corresponding to different degrees of distortion.Finally,we utilize the grid search based on directory folding in these joint position-velocity directions corresponding to large degrees of distortion to obtain the joint position-velocity estimation.The experimental results show that compared with the grouping bi-chi-squared inversion method,MJPVE has high precision and extensive navigation information.展开更多
Reasonable field acquisition geometry can not only guide seismic exploration to obtain sufficient geological information of target body,but also reduce acquisition cost to the maximum.In this study,building on convent...Reasonable field acquisition geometry can not only guide seismic exploration to obtain sufficient geological information of target body,but also reduce acquisition cost to the maximum.In this study,building on conventional ray-based geometry design methods,we incorporate imaging results as a constraint to optimize the geometry design and evaluate its effectiveness.Firstly,the geological model of the target layer is established based on the geological data of the study area and surface seismic data combined with exploration tasks.Then,the ray-tracing method is employed to simulate and assess the proposed geometry design,verifying whether its parameters meet the exploration requirements.Finally,the imaging effect of the designed geometry on the target layer is tested by the cross-well seismic reverse time migration method.This methodology was applied to design the cross-well seismic acquisition geometry for offshore deviated wells in the X Oilfield.The simulation results demonstrate that the imaging-driven geometry design approach effectively guides field operations,enhances the imaging quality of the target layer,and reduces acquisition costs.展开更多
The Main Himalayan Thrust(MHT),where the 2015 MW7.8 Gorkha earthquake occurred,features the most seismicity of any structure in Nepal.The structural complexity of the MHT makes it difficult to obtain a definitive inte...The Main Himalayan Thrust(MHT),where the 2015 MW7.8 Gorkha earthquake occurred,features the most seismicity of any structure in Nepal.The structural complexity of the MHT makes it difficult to obtain a definitive interpretation of deep seismogenic structures.The application of new methods and data in this region is necessary to enhance local seismic hazard analyses.In this study,we used a well-designed machine learning-based earthquake location workflow(LOC-FLOW),which incorporates machine learning phase picking,phase association,absolute location,and double-difference relative location,to process seismic data collected by the Hi-CLIMB and NAMASTE seismic networks.We built a high-precision earthquake catalog of both the quiet-period and aftershock seismicity in this region.The seismicity distribution suggests that the quietperiod seismicity(388 events)was controlled by a mid-crustal ramp and the aftershock seismicity(12,669 events)was controlled by several geological structures of the MHT.The higher-level detail of the catalogs derived from this machine learning method reveal clearer structural characteristics,showing how the flat-ramp geometry and a possible duplex structure affect the depth distribution of the seismic events,and how a tear fault changes this distribution along strike.展开更多
Accurately predicting relative permeability is an important issue in the research of multiphase flow in tight reservoirs.Existing predictive models typically rely on the capillary tube bundle model featuring circular ...Accurately predicting relative permeability is an important issue in the research of multiphase flow in tight reservoirs.Existing predictive models typically rely on the capillary tube bundle model featuring circular cross-sections,often overlooking the impact of pore geometry on fluid flow behavior within reservoirs.In this work,the intermingled fractal theory of porous media is introduced to characterize the intricate local features within the internal space of tight rocks.Initially,iterative rules for diverse fractal units are skillfully designed to capture the actual characteristics of pore cross-sectional shapes.Subsequently,analytical relationships are derived between the iterative parameters and the area,wetted perimeter,and hydraulic diameter of pores generated by these units,followed by the establishment of a relative permeability model that considers pore geometry.The model's validity is confirmed through comparisons with experimental data and published relative permeability models,with correlation coefficients exceeding 0.996.Finally,various factors affecting two-phase flow characteristics are analyzed.The results reveal that pore geometry has a significant impact on flow behavior in porous media.Assuming that the flow channels are cylindrical typically leads to an overestimation of permeability,with the maximum relative error reaching 46.91%.Additionally,the tortuosity fractal dimension is a determinant factor influencing the relative permeability of both wetting and nonwetting fluids,and the phase permeability is sensitive to variations in solid particle size and porosity.The proposed intermingled fractal model enhances the accuracy of evaluating fluid flow characteristics in microscale pore channels and offers a novel framework for simulating porous media with complex geometries.展开更多
High-pressure and high-temperature(HPHT)experiments in large-volume presses(LVPs)benefit from reliable,available,and affordable heaters to achieve stable and homogeneous heating and,in some circumstances,X-ray transpa...High-pressure and high-temperature(HPHT)experiments in large-volume presses(LVPs)benefit from reliable,available,and affordable heaters to achieve stable and homogeneous heating and,in some circumstances,X-ray transparency for monitoring of properties of an in situ experiment using X-ray diffraction and contrast imaging techniques.We have developed heaters meeting the above requirements,and we screen the ternary system TiB2–SiC–hexagonal(h)BN(denoted as TSB)to enable manufacture of X-ray transparent heaters for HPHT runs.Heaters fabricated using optimized TSB-631(60%TiB2–30%SiC–10%hBN by weight)have been tested in modified truncated assemblies,showing excellent performance up to 22 GPa and 2395 K in HPHT runs.TSB-631 has good ceramic machinability,outstanding reproducibility,high stability,and negligible temperature gradient for runs at 3–7 GPa with cell assemblies with truncated edge lengths of 8–12 mm.The fabricated heaters not only show excellent performance in HPHT runs,but also demonstrate high X-ray transparency over a wide X-ray wavelength region,indicating potential applications for in situ X-ray diffraction/imaging under HPHT conditions in LVPs and other high-pressure apparatus.展开更多
The accuracy of numerical computation heavily relies on appropriate meshing,whichserves as the foundation for numerical computation.Although adaptive refinement methods areavailable,an adaptive numerical solution is l...The accuracy of numerical computation heavily relies on appropriate meshing,whichserves as the foundation for numerical computation.Although adaptive refinement methods areavailable,an adaptive numerical solution is likely to be ineffective if it originates from a poorly ini-tial mesh.Therefore,it is crucial to generate meshes that accurately capture the geometric features.As an indispensable input in meshing methods,the Mesh Size Function(MSF)determines the qual-ity of the generated mesh.However,the current generation of MSF involves human participation tospecify numerous parameters,leading to difficulties in practical usage.Considering the capacity ofmachine learning to reveal the latent relationships within data,this paper proposes a novel machinelearning method,Implicit Geometry Neural Network(IGNN),for automatic prediction of appro-priate MSFs based on the existing mesh data,enabling the generation of unstructured meshes thatalign precisely with geometric features.IGNN employs the generative adversarial theory to learnthe mapping between the implicit representation of the geometry(Signed Distance Function,SDF)and the corresponding MSF.Experimental results show that the proposed method is capableof automatically generating appropriate meshes and achieving comparable meshing results com-pared to traditional methods.This paper demonstrates the possibility of significantly decreasingthe workload of mesh generation using machine learning techniques,and it is expected to increasethe automation level of mesh generation.展开更多
The integration of artificial intelligence (AI) with high-throughput experimentation (HTE) techniques is revolutionizing catalyst design, addressing challenges in efficiency, cost, and scalability. This review explore...The integration of artificial intelligence (AI) with high-throughput experimentation (HTE) techniques is revolutionizing catalyst design, addressing challenges in efficiency, cost, and scalability. This review explores the synergistic application of AI and HTE, highlighting their role in accelerating catalyst discovery, optimizing reaction parameters, and understanding structure-performance relationships. HTE facilitates the rapid preparation, characterization, and evaluation of diverse catalyst formulations, generating large datasets essential for AI model training. Machine learning algorithms, including regression models, neural networks, and active learning frameworks, analyze these datasets to uncover the underlying relationships between the data, predict performance, and optimize experimental workflows in real-time. Case studies across heterogeneous, homogeneous, and electrocatalysis demonstrate significant advancements, including improved reaction selectivity, enhanced material stability, and shorten discovery cycles. The integration of AI with HTE has significantly accelerated discovery cycles, enabling the optimization of catalyst formulations and reaction conditions. Despite these achievements, challenges remain, including reliance on researcher expertise, real-time adaptability, and the complexity of large-scale data analysis. Addressing these limitations through refined experimental protocols, standardized datasets, and interpretable AI models will unlock the full potential of AI-HTE integration.展开更多
Thoracic reconstructions are essential surgical techniques used to replace severely damaged tissues and restore protection to internal organs.In recent years,advancements in additive manufacturing have enabled the pro...Thoracic reconstructions are essential surgical techniques used to replace severely damaged tissues and restore protection to internal organs.In recent years,advancements in additive manufacturing have enabled the production of thoracic implants with complex geometries,offering more versatile performance.In this study,we investigated a design based on a spring-like geometry manufactured by laser powder bed fusion(LPBF),as proposed in earlier research.The biomechanical behavior of this design was analyzed using various isolated semi-ring-rib models at different levels of the rib cage.This approach enabled a comprehensive examination,leading to the proposal of several implant configurations that were incorporated into a 3D rib cage model with chest wall defects,to simulate different chest wall reconstruction scenarios.The results revealed that the implant design was too rigid for the second rib level,which therefore was excluded from the proposed implant configurations.In chest wall reconstruction simulations,the maximum stresses observed in all prostheses did not exceed 38%of the implant material's yield stress in the most unfavorable case.Additionally,all the implants showed flexibility compatible with the physiological movements of the human thorax.展开更多
The upper bound on the model error will be decreased when the mean square error and the maximum distance deviation are sufficiently small in the uniform designs for mixture experiments and the design is more robust fo...The upper bound on the model error will be decreased when the mean square error and the maximum distance deviation are sufficiently small in the uniform designs for mixture experiments and the design is more robust for the model.However,the analytical expressions of MSED and MD are currently only available in the hypercube,but both types of deviations in other studies are just approximations.Although it can obtain good approximations in the low-dimensional case,the calculation will be more complicated for an experiment with more variables.Therefore,in this paper,an algorithm based on lattice point partitioning design is proposed to obtain the analytical expression of the MSED and MD in the region covered by the lattice points.Furthermore,the design’s optimality is considered and illustrated by examples under the same uniformity.展开更多
With the increasing development of deepburied engineering projects,rockburst disasters have become a frequent concern.Studies have indicated that tunnel diameter is a critical factor influencing the occurrence of rock...With the increasing development of deepburied engineering projects,rockburst disasters have become a frequent concern.Studies have indicated that tunnel diameter is a critical factor influencing the occurrence of rockbursts.To investigate the influence of tunnel diameter on the deformation and failure characteristics of surrounding rock,large-sized rocklike gypsum specimens were tested using a selfdeveloped true triaxial rockburst loading system containing circular tunnels with three different diameters(D=0.07 m,0.11 m,and 0.15 m).Acoustic emission monitoring,together with a miniature intelligent camera,was employed to analyze the entire process,focusing on macroscopic failure patterns,fragment characteristics,and underlying failure mechanisms.In addition,theoretical analyses were carried out and combined with numerical simulations to investigate the differences in energy evolution associated with rockburst physical models.The results indicate that:(1)The rockburst process with different tunnel diameters consistently evolved through three distinct stages—initial particle ejection,crack propagation accompanied by flake spalling,and,finally,fragment ejection leading to the formation of a‘V'-shaped notch.(2)Increasing tunnel diameter reduces rockburst failure load while increasing surrounding rock damage extent,total mass and average size of ejected fragments.Additionally,shear failure proportion decreases with tensile failure becoming increasingly dominant.(3)Larger tunnel diameters reduce the attenuation rate of elastic strain energy,thereby expanding the zone of elastic strain energy accumulation and disturbance and creating conditions for larger volume rockburst.(4)Larger tunnel diameters result in a smaller principal stress ratio at equivalent distances in the surrounding rock,indicating a higher likelihood of tensile failure.(5)Numerical analyses further reveal that larger tunnel diameters reduce the maximum elastic strain energy density around the tunnel,lowering the energy released per unit volume of rockburst fragments and their ejection velocities.However,both the total failure volume and overall energy release from rockburst increase.Model experiments with different tunnel diameters are of great significance for optimizing engineering design and parameter selection,as well as guiding tunnel construction under complex geological conditions.展开更多
基金Supported by the National Natural Science Foundation of China under Grant Nos 61471336,51503207 and 61504146the Joint-Scholar of West Light Foundation of Chinese Academy of Sciences
文摘We provide a way to precisely control the geometry of a SiNx nanopore by adjusting the applied electric pulse. The pore is generated by applying the current pulse across a SiNx membrane, which is immersed in potassium chloride solution. We can generate single conical and cylindrical pores with different electric pulses. A theoretical model based on the Poisson and Nernst-Planck equations is employed to simulate the ion transport properties in the channel. In turn, we can analyze pore geometries by fitting the experimental current-voltage （I-V） curves. for the conical pores with a pore size of 0.5-2nm in diameter, the slope angles are around -2.5% to -10%. Moreover, the pore orifice can be enlarged slightly by additional repeating pulses. The conic pore lumen becomes close to a cylindrical channel, resulting in a symmetry I-V transport under positive and negative biases. A qualitative understanding of these effects will help us to prepare useful solid-nanopores as demanded.
文摘In this paper, we present our research on building computing machines consciousness about intuitive geometry based on mathematics experiments and statistical inference. The investigation consists of the following five steps. At first, we select a set of geometric configurations and for each configuration we construct a large amount of geometric data as observation data using dynamic geometry programs together with the pseudo-random number generator. Secondly, we refer to the geometric predicates in the algebraic method of machine proof of geometric theorems to construct statistics suitable for measuring the approximate geometric relationships in the observation data. In the third step, we propose a geometric relationship detection method based on the similarity of data distribution, where the search space has been reduced into small batches of data by pre-searching for efficiency, and the hypothetical test of the possible geometric relationships in the search results has be performed. In the fourth step, we explore the integer relation of the line segment lengths in the geometric configuration in addition. At the final step, we do numerical experiments for the pre-selected geometric configurations to verify the effectiveness of our method. The results show that computer equipped with the above procedures can find out the hidden geometric relations from the randomly generated data of related geometric configurations, and in this sense, computing machines can actually attain certain consciousness of intuitive geometry as early civilized humans in ancient Mesopotamia.
文摘A spice formulation study in Burkina Faso was carried out using local ingredients for the benefit of households. The objective of this study was to propose some spice formulations based on local ingredients in order to reduce the use of chemical spices in the preparation of different dishes. The Design of Experiments (DOE) methodology was used for the formulation of the spices and their physicochemical, nutritional and sensory characteristics were evaluated by standardized and standard methods. The results obtained showed lipid contents (g/100 g DM) ranging from 10.41 ± 0.26 to 15.64 ± 0.68, total sugars from 4.39 ± 0.32 to 5.46 ± 0.31, protein from 3.65 ± 0.17 to 12.04 ± 0.35 and ash from 5.83 ± 0.01 to 7.02 ± 0.01. The polyphenol content ranged from 9.09 ± 1.60 to 11.33 ± 0.90, and the flavonoid content ranged from 0.65 ± 0.03 to 1.08 ± 0.13. The sensory analysis carried out showed that the spices have generally satisfactory organoleptic characteristics. These results constitute new information in the diet of populations and are an alternative to the chemical spices used in their cooking.
基金financially supported by Jiangsu Province University(High Tech Ship)Collaborative Innovation Center(Grant No.XTCXKY20230008).
文摘In this work,the selected icebreaker model experiment is performed in a towing tank.We focus on the influence of seawater salinity on ship ice resistance in the ice floe field and the innovative ice model and ship model test technology,including the similitude rule of ship model tests,test principles,and validation with full-scale ship data.A formula for calculating the relationship between the temperature and salinity of the water is constructed,which can be used to simulate the role of seawater in freshwater ice pools.On this basis,the effect of salinity on the resistance of ships sailing in broken ice fields is studied.A technique in which artificial ice made of polyethylene spheres is used to simulate ice resistance is proposed.With a series of ship model experiments in spherical and triangular ice fields,the effects of salinity and velocity on the ice resistance test of the ship model are analyzed.A relationship of the ice resistance of the ship model to the spherical ice field and the triangular ice field is proposed.The conversion results are consistent with onsite data of the full-size ship,which verifies the method of converting the test results of the ship model to the prototype.
基金supported by the National Natural Science Foundation of China(Nos.12175321,11975021,and 11675275)the Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDA10010900)。
文摘The Taishan Antineutrino Observatory(TAO)is a satellite experiment of the Jiangmen Underground Neutrino Observatory,located near the Taishan nuclear power plant(NPP).The TAO aims to measure the energy spectrum of reactor antineutrinos with unprecedented precision,which would benefit both reactor neutrino physics and the nuclear database.A detector geometry and event visualization system was developed for the TAO.The software was based on ROOT packages and embedded in the TAO offline software framework.This provided an intuitive tool for visualizing the detector geometry,tuning the reconstruction algorithm,understanding neutrino physics,and monitoring the operation of reactors at NPP.Further applications of the visualization system in the experimental operation of TAO and its future development are discussed.
基金the National Natural Science Foundation of China under granted No.62104100National Key Research Program of China under No.92164201+1 种基金National Natural Science Foundation of China for Distinguished Young Scholars under No.62325403National Natural Science Foundation of China under No.61934004.
文摘Soft electronics,which are designed to function under mechanical deformation(such as bending,stretching,and folding),have become essential in applications like wearable electronics,artificial skin,and brain-machine interfaces.Crystalline silicon is one of the most mature and reliable materials for high-performance electronics;however,its intrinsic brittleness and rigidity pose challenges for integrating it into soft electronics.Recent research has focused on overcoming these limitations by utilizing structural design techniques to impart flexibility and stretchability to Si-based materials,such as transforming them into thin nanomembranes or nanowires.This review summarizes key strategies in geometry engineering for integrating crystalline silicon into soft electronics,from the use of hard silicon islands to creating out-of-plane foldable silicon nanofilms on flexible substrates,and ultimately to shaping silicon nanowires using vapor-liquid-solid or in-plane solid-liquid-solid techniques.We explore the latest developments in Si-based soft electronic devices,with applications in sensors,nanoprobes,robotics,and brain-machine interfaces.Finally,the paper discusses the current challenges in the field and outlines future research directions to enable the widespread adoption of silicon-based flexible electronics.
基金The 2024 Undergraduate Education Teaching Research and Reform Project of Colleges and Universities in the Autonomous Region“Construction of School-based Digital Resources for Ideological and Political Education in the Course of Analytic Geometry”(XJGXJGPTB-2024104)。
文摘This paper delves into the visual teaching of analytic geometry facilitated by GeoGebra software.Through a meticulous analysis of the current landscape of analytic geometry instruction and the distinct advantages of GeoGebra software,it expounds upon the imperative and feasibility of its application within the realm of analytic geometry teaching.Furthermore,it presents a detailed account of the teaching practice process grounded in this software,encompassing teaching design and the demonstration of teaching cases,and conducts an in-depth investigation and analysis of the teaching outcomes.The research findings indicate that the GeoGebra software can effectively elevate the level of visualization in analytic geometry teaching,thereby augmenting students’learning enthusiasm and comprehension capabilities.It thus offers novel perspectives and methodologies for the pedagogical reform of analytic geometry.
文摘Fatigue failure continues to be a significant challenge in designing structural and mechanical components subjected to repeated and complex loading.While earlier studies mainly examined material properties and how stress affects lifespan,this review offers the first comprehensive,multiscale comparison of strategies that optimize geometry to improve fatigue performance.This includes everything from microscopic features like the shape of graphite nodules to large-scale design elements such as fillets,notches,and overall structural layouts.We analyze and combine various methods,including topology and shape optimization,the ability of additive manufacturing to finetune internal geometries,and reliability-based design approaches.A key new contribution is our proposal of a standard way to evaluate geometry-focused fatigue design,allowing for consistent comparison and encouraging validation across different fields.Furthermore,we highlight important areas for future research,such as incorporating manufacturing flaws,using multiscale models,and integrating machine learning techniques.This work is the first to provide a broad geometric viewpoint in fatigue engineering,laying the groundwork for future design methods that are driven by data and centered on reliability.
基金Deanship of Research and Graduate Studies at King Khalid University for funding this work through Large Research Project under Grant No.RGP2/30/45。
文摘We have developed a class of charged,anisotropic,and spherically symmetric solutions,described by the function f(R,A)=R+a A,where R represents the Ricci scalar,A is the anticurvature scalar,andαis the coupling constant.The model was constructed using the Karmarkar condition to obtain the radial metric component,while the time metric component followed the approach proposed by Adler.We assumed a specific charge distribution inside the star to build the model.To ensure a smooth spacetime transition,we established boundary conditions,considering Bardeen?s solution for the exterior spacetime.Additionally,we examined various physical aspects,such as energy density,pressure components,pressure anisotropy,energy conditions,the equation of state,surface redshift,compactness factor,adiabatic index,sound speed,and the Tolman-Oppenheimer-Volkoff equilibrium condition.All these conditions were met,demonstrating that the solutions we obtained are physically viable.
文摘In this paper,we propose a numerical calculation model of the multigroup neutron diffusion equation in 3D hexagonal geometry using the nodal Green's function method and verified it.We obtained one-dimensional transverse integrated equations using the transverse integration procedure over 3D hexagonal geometry and denoted the solutions as a nodal Green's functions under the Neumann boundary condition.By applying a quadratic polynomial expansion of the transverse-averaged quantities,we derived the net neutron current coupling equation,equation for the expansion coefficients of the transverse-averaged neutron flux,and formulas for the coefficient matrix of these equations.We formulated the closed system of equations in correspondence with the boundary conditions.The proposed model was tested by comparing it with the benchmark for the VVER-440 reactor,and the numerical results were in good agreement with the reference solutions.
基金supported in part by the National Natural Science Foundation of China(Nos.61873196,62373030,61772187)the Innovation Program for Quantum Science and Technology(No.2021ZD0303400)。
文摘The traditional orbit determination method based on pulsar profile distortion can determine the six elements of the orbit.However,the estimation accuracies of these methods are limited and the computational load of a six-dimensional search is huge.To solve this problem,the differential-geometry-based Multi-dimensional Joint Position-Velocity Estimation(MJPVE)using Crab pulsar profile distortion is proposed in this paper.Firstly,through theoretical analysis,it is found that the pulsar profile distortion caused by the initial state error in some joint positionvelocity directions is very small.In other words,the accuracies of estimation in these directions are very low.Namely,the search dimension can be reduced,which in turn greatly reduces the computational load.Then,we construct the chi-squared function of the pulsar profile with respect to the estimation error in joint position-velocity direction and use differential geometry to find the joint position-velocity directions corresponding to different degrees of distortion.Finally,we utilize the grid search based on directory folding in these joint position-velocity directions corresponding to large degrees of distortion to obtain the joint position-velocity estimation.The experimental results show that compared with the grouping bi-chi-squared inversion method,MJPVE has high precision and extensive navigation information.
基金funded by the Young Scientists Fund of the National Natural Science Foundation of China(42304135)the scientific research project of Gansu Coal Geology Bureau(2023-07).
文摘Reasonable field acquisition geometry can not only guide seismic exploration to obtain sufficient geological information of target body,but also reduce acquisition cost to the maximum.In this study,building on conventional ray-based geometry design methods,we incorporate imaging results as a constraint to optimize the geometry design and evaluate its effectiveness.Firstly,the geological model of the target layer is established based on the geological data of the study area and surface seismic data combined with exploration tasks.Then,the ray-tracing method is employed to simulate and assess the proposed geometry design,verifying whether its parameters meet the exploration requirements.Finally,the imaging effect of the designed geometry on the target layer is tested by the cross-well seismic reverse time migration method.This methodology was applied to design the cross-well seismic acquisition geometry for offshore deviated wells in the X Oilfield.The simulation results demonstrate that the imaging-driven geometry design approach effectively guides field operations,enhances the imaging quality of the target layer,and reduces acquisition costs.
基金funded by the National Key R&D Program of China(2022YFF0800601)National Natural Science Foundation of China(42174069,U1939204).
文摘The Main Himalayan Thrust(MHT),where the 2015 MW7.8 Gorkha earthquake occurred,features the most seismicity of any structure in Nepal.The structural complexity of the MHT makes it difficult to obtain a definitive interpretation of deep seismogenic structures.The application of new methods and data in this region is necessary to enhance local seismic hazard analyses.In this study,we used a well-designed machine learning-based earthquake location workflow(LOC-FLOW),which incorporates machine learning phase picking,phase association,absolute location,and double-difference relative location,to process seismic data collected by the Hi-CLIMB and NAMASTE seismic networks.We built a high-precision earthquake catalog of both the quiet-period and aftershock seismicity in this region.The seismicity distribution suggests that the quietperiod seismicity(388 events)was controlled by a mid-crustal ramp and the aftershock seismicity(12,669 events)was controlled by several geological structures of the MHT.The higher-level detail of the catalogs derived from this machine learning method reveal clearer structural characteristics,showing how the flat-ramp geometry and a possible duplex structure affect the depth distribution of the seismic events,and how a tear fault changes this distribution along strike.
基金financially supported by the Hebei Provincial Natural Science Foundation of China(No.D2023402012)the Major Science and Technology Project of China National Petroleum Corporation(No.2024DJ87)。
文摘Accurately predicting relative permeability is an important issue in the research of multiphase flow in tight reservoirs.Existing predictive models typically rely on the capillary tube bundle model featuring circular cross-sections,often overlooking the impact of pore geometry on fluid flow behavior within reservoirs.In this work,the intermingled fractal theory of porous media is introduced to characterize the intricate local features within the internal space of tight rocks.Initially,iterative rules for diverse fractal units are skillfully designed to capture the actual characteristics of pore cross-sectional shapes.Subsequently,analytical relationships are derived between the iterative parameters and the area,wetted perimeter,and hydraulic diameter of pores generated by these units,followed by the establishment of a relative permeability model that considers pore geometry.The model's validity is confirmed through comparisons with experimental data and published relative permeability models,with correlation coefficients exceeding 0.996.Finally,various factors affecting two-phase flow characteristics are analyzed.The results reveal that pore geometry has a significant impact on flow behavior in porous media.Assuming that the flow channels are cylindrical typically leads to an overestimation of permeability,with the maximum relative error reaching 46.91%.Additionally,the tortuosity fractal dimension is a determinant factor influencing the relative permeability of both wetting and nonwetting fluids,and the phase permeability is sensitive to variations in solid particle size and porosity.The proposed intermingled fractal model enhances the accuracy of evaluating fluid flow characteristics in microscale pore channels and offers a novel framework for simulating porous media with complex geometries.
基金financially supported by the National Natural Science Foundation of China(Grant Nos.22090041 and 22401297)the Guangdong Basic and Applied Basic Research Foundation(Grant No.2022B1515120014).
文摘High-pressure and high-temperature(HPHT)experiments in large-volume presses(LVPs)benefit from reliable,available,and affordable heaters to achieve stable and homogeneous heating and,in some circumstances,X-ray transparency for monitoring of properties of an in situ experiment using X-ray diffraction and contrast imaging techniques.We have developed heaters meeting the above requirements,and we screen the ternary system TiB2–SiC–hexagonal(h)BN(denoted as TSB)to enable manufacture of X-ray transparent heaters for HPHT runs.Heaters fabricated using optimized TSB-631(60%TiB2–30%SiC–10%hBN by weight)have been tested in modified truncated assemblies,showing excellent performance up to 22 GPa and 2395 K in HPHT runs.TSB-631 has good ceramic machinability,outstanding reproducibility,high stability,and negligible temperature gradient for runs at 3–7 GPa with cell assemblies with truncated edge lengths of 8–12 mm.The fabricated heaters not only show excellent performance in HPHT runs,but also demonstrate high X-ray transparency over a wide X-ray wavelength region,indicating potential applications for in situ X-ray diffraction/imaging under HPHT conditions in LVPs and other high-pressure apparatus.
基金co-supported by the Aeronautical Science Foundation of China(Nos.2018ZA52002 and 2019ZA052011)。
文摘The accuracy of numerical computation heavily relies on appropriate meshing,whichserves as the foundation for numerical computation.Although adaptive refinement methods areavailable,an adaptive numerical solution is likely to be ineffective if it originates from a poorly ini-tial mesh.Therefore,it is crucial to generate meshes that accurately capture the geometric features.As an indispensable input in meshing methods,the Mesh Size Function(MSF)determines the qual-ity of the generated mesh.However,the current generation of MSF involves human participation tospecify numerous parameters,leading to difficulties in practical usage.Considering the capacity ofmachine learning to reveal the latent relationships within data,this paper proposes a novel machinelearning method,Implicit Geometry Neural Network(IGNN),for automatic prediction of appro-priate MSFs based on the existing mesh data,enabling the generation of unstructured meshes thatalign precisely with geometric features.IGNN employs the generative adversarial theory to learnthe mapping between the implicit representation of the geometry(Signed Distance Function,SDF)and the corresponding MSF.Experimental results show that the proposed method is capableof automatically generating appropriate meshes and achieving comparable meshing results com-pared to traditional methods.This paper demonstrates the possibility of significantly decreasingthe workload of mesh generation using machine learning techniques,and it is expected to increasethe automation level of mesh generation.
基金supported by the Special Project of National Natural Science Foundation(42341204)the the National Natural Science Foundation of China(W2411009).
文摘The integration of artificial intelligence (AI) with high-throughput experimentation (HTE) techniques is revolutionizing catalyst design, addressing challenges in efficiency, cost, and scalability. This review explores the synergistic application of AI and HTE, highlighting their role in accelerating catalyst discovery, optimizing reaction parameters, and understanding structure-performance relationships. HTE facilitates the rapid preparation, characterization, and evaluation of diverse catalyst formulations, generating large datasets essential for AI model training. Machine learning algorithms, including regression models, neural networks, and active learning frameworks, analyze these datasets to uncover the underlying relationships between the data, predict performance, and optimize experimental workflows in real-time. Case studies across heterogeneous, homogeneous, and electrocatalysis demonstrate significant advancements, including improved reaction selectivity, enhanced material stability, and shorten discovery cycles. The integration of AI with HTE has significantly accelerated discovery cycles, enabling the optimization of catalyst formulations and reaction conditions. Despite these achievements, challenges remain, including reliance on researcher expertise, real-time adaptability, and the complexity of large-scale data analysis. Addressing these limitations through refined experimental protocols, standardized datasets, and interpretable AI models will unlock the full potential of AI-HTE integration.
文摘Thoracic reconstructions are essential surgical techniques used to replace severely damaged tissues and restore protection to internal organs.In recent years,advancements in additive manufacturing have enabled the production of thoracic implants with complex geometries,offering more versatile performance.In this study,we investigated a design based on a spring-like geometry manufactured by laser powder bed fusion(LPBF),as proposed in earlier research.The biomechanical behavior of this design was analyzed using various isolated semi-ring-rib models at different levels of the rib cage.This approach enabled a comprehensive examination,leading to the proposal of several implant configurations that were incorporated into a 3D rib cage model with chest wall defects,to simulate different chest wall reconstruction scenarios.The results revealed that the implant design was too rigid for the second rib level,which therefore was excluded from the proposed implant configurations.In chest wall reconstruction simulations,the maximum stresses observed in all prostheses did not exceed 38%of the implant material's yield stress in the most unfavorable case.Additionally,all the implants showed flexibility compatible with the physiological movements of the human thorax.
基金Supported by Science and Technology Fund for Basic Research of Guizhou Province([2020]1Y010)National Nature Sciences Foundation of China(11901260,12071096,12501342)Specialized Fund for the Doctoral Development of Kaili University(BS202502028)。
文摘The upper bound on the model error will be decreased when the mean square error and the maximum distance deviation are sufficiently small in the uniform designs for mixture experiments and the design is more robust for the model.However,the analytical expressions of MSED and MD are currently only available in the hypercube,but both types of deviations in other studies are just approximations.Although it can obtain good approximations in the low-dimensional case,the calculation will be more complicated for an experiment with more variables.Therefore,in this paper,an algorithm based on lattice point partitioning design is proposed to obtain the analytical expression of the MSED and MD in the region covered by the lattice points.Furthermore,the design’s optimality is considered and illustrated by examples under the same uniformity.
基金funded by the National Natural Science Foundation of China(Nos.42077228,52174085)。
文摘With the increasing development of deepburied engineering projects,rockburst disasters have become a frequent concern.Studies have indicated that tunnel diameter is a critical factor influencing the occurrence of rockbursts.To investigate the influence of tunnel diameter on the deformation and failure characteristics of surrounding rock,large-sized rocklike gypsum specimens were tested using a selfdeveloped true triaxial rockburst loading system containing circular tunnels with three different diameters(D=0.07 m,0.11 m,and 0.15 m).Acoustic emission monitoring,together with a miniature intelligent camera,was employed to analyze the entire process,focusing on macroscopic failure patterns,fragment characteristics,and underlying failure mechanisms.In addition,theoretical analyses were carried out and combined with numerical simulations to investigate the differences in energy evolution associated with rockburst physical models.The results indicate that:(1)The rockburst process with different tunnel diameters consistently evolved through three distinct stages—initial particle ejection,crack propagation accompanied by flake spalling,and,finally,fragment ejection leading to the formation of a‘V'-shaped notch.(2)Increasing tunnel diameter reduces rockburst failure load while increasing surrounding rock damage extent,total mass and average size of ejected fragments.Additionally,shear failure proportion decreases with tensile failure becoming increasingly dominant.(3)Larger tunnel diameters reduce the attenuation rate of elastic strain energy,thereby expanding the zone of elastic strain energy accumulation and disturbance and creating conditions for larger volume rockburst.(4)Larger tunnel diameters result in a smaller principal stress ratio at equivalent distances in the surrounding rock,indicating a higher likelihood of tensile failure.(5)Numerical analyses further reveal that larger tunnel diameters reduce the maximum elastic strain energy density around the tunnel,lowering the energy released per unit volume of rockburst fragments and their ejection velocities.However,both the total failure volume and overall energy release from rockburst increase.Model experiments with different tunnel diameters are of great significance for optimizing engineering design and parameter selection,as well as guiding tunnel construction under complex geological conditions.
