Theoretical study of potential energy curves,spectroscopic constants,and radiative lifetimes of low-lying states in an SeO molecule

The low-lying potential energy curves of the SeO molecule are computed by means of an ab initio multireference configuration interaction technique, taking into account relativistic （scalar plus spin~）rbit coupling） effects. The spectroscopic constants of Ω states for X3∑-, a1△, b2∑＋, A3П , A′3△, and A″ 3∑＋ states are obtained, and they are in good accordance with available experimental values. The Franck-Condon factors and transition dipole moments to the ground state are computed, and the natural radiative lifetimes of low-lying Ω states are theoretically obtained. Comparisons of the natural lifetimes of Ω states with previous experimental results and those of isovalent TeO molecule are made.

Potential energy curves, transition dipole moments, and radiative lifetimes of KBe molecule

An ab initio calculations on the ground and low-lying excited statesX2∑＋,2^2∑＋,3^2∑＋,1^4∏,2^4∏,1^4∑＋,2^4∑＋,and 3^4∑＋of KBe molecule have been performed using multireference configuration interaction （MRCI） plus Davidsoncorrections （MRCI＋Q） approach with all electron basis set aug-cc-pCV5Z-DK for Be and def2-AQZVPP-JKFI for K.3^2∑＋,1^4∏,2^4∏,1^4∑＋,2^4∑＋and3^4∑＋states are investigated for the first time. Inner shell electron correlations are computed on the potential energy curves （PECs） calculations. The spectroscopic and molecular parameters are also predicted. In addition, The transition properties including transition dipole moment, Franck-Condon factors qv′v″, Einstein coefficients Av′v″, and the radiative lifetimesτ′for the2^2∑＋-X2∑＋,3^2∑＋-X2∑＋,and 2^4∏-1^4∏ transitions are predictedat the same time.

Insights and reviews on battery lifetime prediction from research to practice

The rising demand for energy storage solutions,especially in the electric vehicle and renewable energy sectors,highlights the importance of accurately predicting battery health to enhance their longevity and reliability.This article comprehensively examines various methods used to forecast battery health,including physics-based models,empirical models,and equivalent circuit models,among others.It delves into the promise of data-driven prognostics,utilizing both conventional machine learning and cuttingedge deep neural network techniques.The advantages and limitations of hybrid models are thoroughly analyzed,with a focus on the benefits of integrating diverse data sources to improve prognostic precision.Through practical case studies,the article showcases the effectiveness and flexibility of these approaches.It also critically addresses the challenges encountered in applying battery health prognostics in realworld scenarios,such as issues of scalability,complexity,and data anomalies.Despite these challenges,the article underscores the emerging opportunities brought about by recent technological,academic,and research advancements.These include the development of digital twin models for batteries,the use of data-centric AI and standardized benchmarking,the potential integration of blockchain technology for enhanced data security and transparency,and the synergy between edge and cloud computing to boost data analysis and processing.The primary goal of this article is to enrich the understanding of current battery health prognostic techniques and to inspire further research aimed at overcoming existing hurdles and tapping into new opportunities.It concludes with a visionary perspective on future research directions and potential developments in this evolving field,encouraging both researchers and practitioners to explore innovative solutions.

Inverse design of mechanical metamaterial achieving a prescribedconstitutive curve

Besides exhibiting excellent capabilities such as energy absorption,phase-transforming metamaterials offer a vast design space for achieving nonlinear constitutive relations.This is facilitated by switching between different patterns under deformation.However,the related inverse design problem is quite challenging,due to the lack of appropriate mathematical formulation and the convergence issue in the post-buckling analysis of intermediate designs.In this work,periodic unit cells are explicitly described by the moving morphable voids method and effectively analyzed by eliminating the degrees of freedom in void regions.Furthermore,by exploring the Pareto frontiers between error and cost,an inverse design formulation is proposed for unit cells.This formulation aims to achieve a prescribed constitutive curve and is validated through numerical examples and experimental results.The design approach presented here can be extended to the inverse design of other types of mechanical metamaterials with prescribed nonlinear effective properties.

A comparative study of data-driven battery capacity estimation based on partial charging curves

With its generality and practicality, the combination of partial charging curves and machine learning(ML) for battery capacity estimation has attracted widespread attention. However, a clear classification,fair comparison, and performance rationalization of these methods are lacking, due to the scattered existing studies. To address these issues, we develop 20 capacity estimation methods from three perspectives:charging sequence construction, input forms, and ML models. 22,582 charging curves are generated from 44 cells with different battery chemistry and operating conditions to validate the performance. Through comprehensive and unbiased comparison, the long short-term memory(LSTM) based neural network exhibits the best accuracy and robustness. Across all 6503 tested samples, the mean absolute percentage error(MAPE) for capacity estimation using LSTM is 0.61%, with a maximum error of only 3.94%. Even with the addition of 3 m V voltage noise or the extension of sampling intervals to 60 s, the average MAPE remains below 2%. Furthermore, the charging sequences are provided with physical explanations related to battery degradation to enhance confidence in their application. Recommendations for using other competitive methods are also presented. This work provides valuable insights and guidance for estimating battery capacity based on partial charging curves.

A dynamic soil freezing characteristic curve model for frozen soil

The soil freezing characteristic curve(SFCC)plays a fundamental role in comprehending thermohydraulic behavior and numerical simulation of frozen soil.This study proposes a dynamic model to uniformly express SFCCs amidst varying total water contents throughout the freezing-thawing process.Firstly,a general model is proposed,wherein the unfrozen water content at arbitrary temperature is determined as the lesser of the current total water content and the reference value derived from saturated SFCC.The dynamic performance of this model is verified through test data.Subsequently,in accordance with electric double layer(EDL)theory,the theoretical residual and minimum temperatures in SFCC are calculated to be-14.5℃to-20℃for clay particles and-260℃,respectively.To ensure that the SFCC curve ends at minimum temperature,a correction function is introduced into the general model.Furthermore,a simplified dynamic model is proposed and investigated,necessitating only three parameters inherited from the general model.Additionally,both general and simplified models are evaluated based on a test database and proven to fit the test data exactly across the entire temperature range.Typical recommended parameter values for various types of soils are summarized.Overall,this study provides not only a theoretical basis for most empirical equations but also proposes a new and more general equation to describe the SFCC.

A development of lifetime measurement based on the differential decay curve method

A new development of indirect gating case in the differential decay curve method used for lifetime measurement has been introduced.The gate region was extended from partial shifted peak to both shifted and unshifted components.The statistics of flight and stop peaks in gating spectra was improved obviously.The reliability of this change has been tested by reanalysing the lifetime of 2^+ state in^(134) Ce.The result of 32.2(33) ps was fit well with the previous published values within the experimental uncertainty.The developed method was also used to analyse the lifetime of 2_1^+ state in^(138) Nd.

Curve25519点乘算法的高效FPGA实现

为了提高X25519密钥交换算法的运算效率,文章基于现场可编程门阵列(field programmable gate array,FPGA)提出一种高效的曲线Curve25519的点乘设计方案。首先在底层的有限域计算上,针对模约减计算次数多的问题,提出一种基于冗余数的模运算单元,减少了约减次数;同时,所提出的结构可以减少点乘中常系数乘法的运算周期,从而优化了点乘运算通路,提高了并行度,最终减少了运算时间。该文在Xilinx XC7Z020 FPGA上实现了该点乘设计方案,完成一次点乘需要125μs。研究结果表明,与现有的设计相比,所提出的方案具有较低的面积时间积,达到了面积和性能的平衡。

Fully relativistic energies,transition properties,and lifetimes of lithium-like germanium

Employing two fully relativistic methods,the multi-reference configuration Dirac-Hartree-Fock(MCDHF)methodand the relativistic many-body perturbation theory(RMBPT)method,we report energies and lifetime values for the lowest35 energy levels of the(1s^(2))nl configurations(where the principal quantum number n=2-6 and the angular quantum numberl=0,...,n-1)of lithium-like germanium(Ge XXX),as well as complete data on the transition wavelengths,radiativerates,absorption oscillator strengths,and line strengths between the levels.Both the allowed(E1)and forbidden(magneticdipole M1,magnetic quadrupole M2,and electric quadrupole E2)ones are reported.The results from the two methodsare consistent with each other and align well with previous accurate experimental and theoretical findings.We assess theoverall accuracies of present RMBPT results to be likely the most precise ones to date.The present fully relativistic resultsshould be helpful for soft x-ray laser research,spectral line identification,plasma modeling and diagnosing.The datasetspresented in this paper are openly available at https://doi.org/10.57760/sciencedb.j00113.00135.

Method for determining the position of landslide slip-surface with a typical inclinometric curves

In the actual monitoring of deep hole displacement,the identification of slip surfaces is primarily based on abrupt changes observed in the inclinometric curve.In conventional identification methods,inclinometric curves exhibiting indications of sliding can be categorized into three types:B-type,D-type,and r-type.The position of the slip surface is typically determined by identifying the depth corresponding to the point of maximum displacement mutation.However,this method is sensitive to the interval of measurement points and the observation scale of the coordinate axes and suffers from unclear sliding surfaces and uncertain values.Based on the variation characteristics of these diagonal curves,we classified the landslide into three components:the sliding body,the sliding interval,and the immobile body.Moreover,three different generalization models were established to analyze the relationships between the curve form and the slip surface location based on different physical indicators such as displacement rate,relative displacement,and acceleration.The results show that the displacement rate curves of an r-type slope exhibit a clustering feature in the sliding interval,and by solving for the depth of discrete points within the step phase,it is possible to determine the location of the slip surface.On the other hand,D-type slopes have inflection points in the relative displacement curve located at the slip surface.The acceleration curves of B-type slopes exhibit clustering characteristics during the sliding interval,while the scattered acceleration data demonstrate wandering characteristics.Consequently,the slip surface location can be revealed by solving the depth corresponding to the maximum acceleration with cubic spline interpolation.The approach proposed in this paper was applied to the monitoring data of a landslide in Yunnan Province,China.The results indicate that our approach can accurately identify the slip surface location and enable computability of its position,thereby enhancing applicability and reliability of the deep-hole displacement monitoring data.

Gross Alpha and Beta Activities and Related Lifetime Risks Assessment Due to Ingestion of Drinking Water from Different Sources in the District of Abidjan, Cote d’Ivoire

Drinking good quality water is essential for better health. It is therefore essential to assess the radiological quality of all water consumed in the District of Abidjan in order to prevent related hazards. Thus, the objective of this study was to assess the risk of cancer due to the ingestion of alpha and beta emitting radionuclides in the different types of water consumed in the region. A total of 63 water samples with 43 tap water samples, 5 bottled mineral water and 15 sachet water samples was collected and taken to GAEC laboratory for analysis. The low background Gas-less Automatic Alpha/Beta counting system (Canberra iMaticTM) was used to determine alpha and beta activity concentrations. Activity concentrations of both gross alpha and gross beta obtained in water sample were respectively lower than the WHO recommended limits of 0.1 Bq/l and 1 Bq/l. Also, the annual effective dose and total equivalent effective dose found in mineral bottled water samples were higher than in other types of water. The assessment of radiological lifetime risk has shown values of cancer risk due to ingestion alpha and beta emitters lower than recommended limit. These results indicate that there is no health hazard associated to consumption of water in the District of Abidjan.

Research into Applicability of Wöhler Curve Method for Low-Cycle Fatigue of Metallic Materials

Recently,a description on a practicability of the Wöhler Curve Method for low-cycle fatigue of metals was given by the author.By the description and the low cycle fatigue test data of 16 MnR steel,it is important to show that,for low cycle fatigue of metals,such a way that a stress-based intensity parameter calculated by the linear-elastic analysis is taken to be a stress intensity parameter,S,to establish a relationship between the stress intensity parameter,S,and the fatigue life,N,is practicable.In this paper,many metallic materials from the literature are given to show that the Wöhler Curve Method is well suitable for low-cycle fatigue analysis of metals.

Compression Properties and Energy Absorption of A Novel Double Curved Beam Negative Stiffness Honeycomb Structures

This paper presents the design of a novel honeycomb structure with a double curved beam.The purpose of this design is to achieve vibration isolation for the main engine of an offshore platform and reduce impact loads.An analytical formula for the force-displacement relationship of the honeycomb single-cell structure is presented based on the modal superposition method.This formula provides a theoretical basis for predicting the compression performance of honeycomb structures.The effects of structural geometric parameters,series and parallel connection methods on the mechanical and energy absorption properties are investigated through mathematical modeling and experimental methods.Furthermore,the study focuses on the vibration isolation and impact resistance performance of honeycomb panels.The results show that the designed honeycomb structure has good mechanical and energy absorption performance,and its energy absorption effect is related to the geometric parameters and series and parallel connection methods of the structure.The isolation efficiency of the honeycomb with 4 rows and 3 columns reaches 38%.The initial isolation frequency of the isolator is 11.7 Hz.

Research on batch multielement rapid quantitative analysis based on the standard curve-assisted calibration-free laserinduced breakdown spectroscopy method

This study proposes a batch rapid quantitative analysis method for multiple elements by combining the advantages of standard curve(SC)and calibration-free laser-induced breakdown spectroscopy(CF-LIBS)technology to achieve synchronous,rapid,and accurate measurement of elements in a large number of samples,namely,SC-assisted CF-LIBS.Al alloy standard samples,divided into calibration and test samples,were applied to validate the proposed method.SC was built based on the characteristic line of Pb and Cr in the calibration sample,and the contents of Pb and Cr in the test sample were calculated with relative errors of 6%and 4%,respectively.SC built using Cr with multiple characteristic lines yielded better calculation results.The relative contents of ten elements in the test sample were calculated using CF-LIBS.Subsequently,the SC-assisted CF-LIBS was executed,with the majority of the calculation relative errors falling within the range of 2%-5%.Finally,the Al and Na contents of the Al alloy were predicted.The results demonstrate that it effectively enables the rapid and accurate quantitative analysis of multiple elements after a single-element SC analysis of the tested samples.Furthermore,this quantitative analysis method was successfully applied to soil and Astragalus samples,realizing an accurate calculation of the contents of multiple elements.Thus,it is important to advance the LIBS quantitative analysis and its related applications.

Deep structure of the Southeast Asian curved subduction system and its dynamic process

The deep structure,material circulation,and dynamic processes in the Southeast Asia have long been an elusive scientific puzzle due to the lack of systematic scientific observations and recognized theoretical models.Based on the deep seismic tomography using long-period natural earthquake data,in this study,the deep structure and material circulation of the curved subduction system in Southeast Asia was studied,and the dynamic processes since 100 million years ago was reconstructed.It is pointed out that challenges still exist in the precise reconstruction of deep mantle structures of the study area,the influence of multi-stage subduction on deep material exchange and shallow magma activity,as well as the spatiotemporal evolution and coupling mechanism of multi-plate convergence.Future work should focus on high-resolution land-sea joint 3-D seismic tomography imaging of the curved subduction system in the Southeast Asia,combined with geochemical analysis and geodynamic modelling works.

Quantum dynamics within curved thin layers with deviation

Combining the deviation between thin layers' adjacent surfaces with the confining potential method applied to the quantum curved systems,we derive the effective Schr?dinger equation describing the particle constrained within a curved layer,accompanied by a general geometric potential V_(gq) composed of a compression-corrected geometric potential V_(gq)~*and a novel potential V_(gq)~(**) brought by the deviation.Applying this analysis to the cylindrical layer emerges two types of deviation-induced geometric potential,resulting from the the cases of slant deviation and tangent deviation,respectively,which strongly renormalizes the purely geometric potential and contribute to the energy spectrum based on a very substantial deepening of bound states they offer.

A Non-Parametric Scheme for Identifying Data Characteristic Based on Curve Similarity Matching

For accurately identifying the distribution charac-teristic of Gaussian-like noises in unmanned aerial vehicle(UAV)state estimation,this paper proposes a non-parametric scheme based on curve similarity matching.In the framework of the pro-posed scheme,a Parzen window(kernel density estimation,KDE)method on sliding window technology is applied for roughly esti-mating the sample probability density,a precise data probability density function(PDF)model is constructed with the least square method on K-fold cross validation,and the testing result based on evaluation method is obtained based on some data characteristic analyses of curve shape,abruptness and symmetry.Some com-parison simulations with classical methods and UAV flight exper-iment shows that the proposed scheme has higher recognition accuracy than classical methods for some kinds of Gaussian-like data,which provides better reference for the design of Kalman filter(KF)in complex water environment.

Bending results of graphene origami reinforced doubly curved shell

The present work investigates higher order stress,strain and deformation analyses of a shear deformable doubly curved shell manufactures by a Copper(Cu)core reinforced with graphene origami auxetic metamaterial subjected to mechanical and thermal loads.The effective material properties of the graphene origami auxetic reinforced Cu matrix are developed using micromechanical models cooperate both material properties of graphene and Cu in terms of temperature,volume fraction and folding degree.The principle of virtual work is used to derive governing equations with accounting thermal loading.The numerical results are analytically obtained using Navier's technique to investigate impact of significant parameters such as thermal loading,graphene amount,folding degree and directional coordinate on the stress,strain and deformation responses of the structure.The graphene origami materials may be used in aerospace vehicles and structures and defence technology because of their low weight and high stiffness.A verification study is presented for approving the formulation,solution methodology and numerical results.

A Tutorial Review of the Solar Power Curve: Regressions, Model Chains, and Their Hybridization and Probabilistic Extensions

Owing to the persisting hype in pushing toward global carbon neutrality,the study scope of atmospheric science is rapidly expanding.Among numerous trending topics,energy meteorology has been attracting the most attention hitherto.One essential skill of solar energy meteorologists is solar power curve modeling,which seeks to map irradiance and auxiliary weather variables to solar power,by statistical and/or physical means.In this regard,this tutorial review aims to deliver a complete overview of those fundamental scientific and engineering principles pertaining to the solar power curve.Solar power curves can be modeled in two primary ways,one of regression and the other of model chain.Both classes of modeling approaches,alongside their hybridization and probabilistic extensions,which allow accuracy improvement and uncertainty quantification,are scrutinized and contrasted thoroughly in this review.

Current Status and Perspectives of External Versus Internal Pancreatic Duct Drainage during the Learning Curve of Laparoscopic Pancreaticoduodenectomy

Objectives: To summarize the current status and outlook of pancreatic duct drainage in the learning curve period of laparoscopic pancreaticoduodenectomy (LPD). Methods: By searching the literature related to the efficacy analysis of internal versus external pancreatic duct drainage in pancreaticoduodenectomy (OPD) and the learning curve period of laparoscopic pancreaticoduodenectomy in recent years at home and abroad and making a review. Results: Because of the complexity of the LPD surgical procedure, the high technical requirements and the high complication rate, it is necessary for the operator and his/her team to carry out a certain number of cases to pass through the learning curve in order to have a basic mastery of the procedure. In recent years, more and more pancreatic surgeons have begun to promote and use pancreatic duct drains. However, no consensus conclusion has been reached on whether to choose internal or external drainage for pancreatic duct placement and drainage in LPD. Conclusions: Intraoperative application of pancreatic duct drainage reduces the incidence of pancreatic fistula during the learning curve of laparoscopic pancreaticoduodenectomy. However, external pancreatic duct drainage and internal pancreatic duct drainage have both advantages and disadvantages, so when choosing the drainage method, one should choose the appropriate drainage method in conjunction with one’s own conditions, so as to reduce the incidence of complications.