Effect of preload forces on multidimensional signal dynamic behaviours for battery early safety warning

Providing early safety warning for batteries in real-world applications is challenging.In this study,comprehensive thermal abuse experiments are conducted to clarify the multidimensional signal evolution of battery failure under various preload forces.The time-sequence relationship among expansion force,voltage,and temperature during thermal abuse under five categorised stages is revealed.Three characteristic peaks are identified for the expansion force,which correspond to venting,internal short-circuiting,and thermal runaway.In particular,an abnormal expansion force signal can be detected at temperatures as low as 42.4°C,followed by battery thermal runaway in approximately 6.5 min.Moreover,reducing the preload force can improve the effectiveness of the early-warning method via the expansion force.Specifically,reducing the preload force from 6000 to 1000 N prolongs the warning time(i.e.,227 to 398 s)before thermal runaway is triggered.Based on the results,a notable expansion force early-warning method is proposed that can successfully enable early safety warning approximately 375 s ahead of battery thermal runaway and effectively prevent failure propagation with module validation.This study provides a practical reference for the development of timely and accurate early-warning strategies as well as guidance for the design of safer battery systems.

Improving the utility of locally differentially private protocols for longitudinal and multidimensional frequency estimates

This paper investigates the problem of collecting multidimensional data throughout time(i.e.,longitudinal studies)for the fundamental task of frequency estimation under Local Differential Privacy(LDP)guarantees.Contrary to frequency estimation of a single attribute,the multidimensional aspect demands particular attention to the privacy budget.Besides,when collecting user statistics longitudinally,privacy progressively degrades.Indeed,the“multiple”settings in combination(i.e.,many attributes and several collections throughout time)impose several challenges,for which this paper proposes the first solution for frequency estimates under LDP.To tackle these issues,we extend the analysis of three state-of-the-art LDP protocols(Generalized Randomized Response–GRR,Optimized Unary Encoding–OUE,and Symmetric Unary Encoding–SUE)for both longitudinal and multidimensional data collections.While the known literature uses OUE and SUE for two rounds of sanitization(a.k.a.memoization),i.e.,L-OUE and L-SUE,respectively,we analytically and experimentally show that starting with OUE and then with SUE provides higher data utility(i.e.,L-OSUE).Also,for attributes with small domain sizes,we propose Longitudinal GRR(L-GRR),which provides higher utility than the other protocols based on unary encoding.Last,we also propose a new solution named Adaptive LDP for LOngitudinal and Multidimensional FREquency Estimates(ALLOMFREE),which randomly samples a single attribute to be sent with the whole privacy budget and adaptively selects the optimal protocol,i.e.,either L-GRR or L-OSUE.As shown in the results,ALLOMFREE consistently and considerably outperforms the state-of-the-art L-SUE and L-OUE protocols in the quality of the frequency estimates.

RFFsNet-SEI:a multidimensional balanced-RFFs deep neural network framework for specific emitter identification

Existing specific emitter identification(SEI)methods based on hand-crafted features have drawbacks of losing feature information and involving multiple processing stages,which reduce the identification accuracy of emitters and complicate the procedures of identification.In this paper,we propose a deep SEI approach via multidimensional feature extraction for radio frequency fingerprints(RFFs),namely,RFFsNet-SEI.Particularly,we extract multidimensional physical RFFs from the received signal by virtue of variational mode decomposition(VMD)and Hilbert transform(HT).The physical RFFs and I-Q data are formed into the balanced-RFFs,which are then used to train RFFsNet-SEI.As introducing model-aided RFFs into neural network,the hybrid-driven scheme including physical features and I-Q data is constructed.It improves physical interpretability of RFFsNet-SEI.Meanwhile,since RFFsNet-SEI identifies individual of emitters from received raw data in end-to-end,it accelerates SEI implementation and simplifies procedures of identification.Moreover,as the temporal features and spectral features of the received signal are both extracted by RFFsNet-SEI,identification accuracy is improved.Finally,we compare RFFsNet-SEI with the counterparts in terms of identification accuracy,computational complexity,and prediction speed.Experimental results illustrate that the proposed method outperforms the counterparts on the basis of simulation dataset and real dataset collected in the anechoic chamber.

AAK Theorem and a Design of Multidimensional BIBO Stable Filters

Rational approximation theory occupies a significant place in signal processing and systems theory. This research paper proposes an optimal design of BIBO stable multidimensional Infinite Impulse Response filters with a realizable (rational) transfer function thanks to the Adamjan, Arov and Krein (AAK) theorem. It is well known that the one dimensional AAK results give the best approximation of a polynomial as a rational function in the Hankel semi norm. We suppose that the Hankel matrix associated to the transfer function has a finite rank.

A Corpus-Based Comparative Multidimensional Analysis of the Two English Translations of Luoyang Jialan Ji

By using the MD approach, this study aims at making a comparison between the lexical features in W. J. F. Jenner’s and Wang Yitong’s translations of Luoyang Jialan Ji (547 AD) from a multidimensional perspective. Statistics show that both the two translations belong to the General Narrative Exposition Register. However, there are significant discrepancies between the two versions in Dimension 1 “Involved versus Informational Production”, Dimension 4 “Overt Expression of Persuasion” and Dimension 5 “Abstract versus Non-Abstract Information”. The differences in Dimension 2 “Narrative versus Non-Narrative Concerns” and Dimension 3 “Explicit versus Situation-Dependent Reference” are not that significant. It is found that in Dimension 1, the information density of Wang’s version is much higher than that of Jenner’s. In Dimension 4, Wang’s version contains more overt persuasive effort than Jenner’s. In Dimension 5, the positive and negative contrast between the two versions indicates that Wang’s version provides information in a more abstract way, whereas Jenner’s in a relatively non-abstract way. Combined with typical examples in the two translation versions, this study is hoped to help better understand the translations of Luoyang Jialan Ji and conduct future studies on the translation styles of the two translators.

Multidimensional Perspectives on the Teaching and Practice of Typography Design

With the deepening of the curriculum teaching reform in colleges and universities,the teaching reform of art design professional courses is imperative.The study found that the current art design professional font design course teaching there are more solidified teaching methods,students operating ability is relatively homogenised,the teaching content to the"westernised"based,resulting in poor adaptability of students and other prominent problems.This paper starts from the"three effects"of"effect","efficiency"and"effectiveness",and adopts a multi-dimensional and emotional thinking perspective to carry out the curriculum of typeface design.This paper starts from the"three effects"of"effect","efficiency"and"effectiveness",and adopts a multi-dimensional and emotional perspective of thinking to carry out the teaching and practice of typeface design in order to strengthen the visual information of Chinese culture,and at the same time,to explore the creative potential of the students,so as to improve the students'innovation and creativity.

Multidimensional defects tailoring local electron and Mg^(2+) diffusion channels for boosting magnesium storage performance of WO_(3)/MoO_(2)

Defect engineering presents great promise in addressing lower specific capacity,sluggish diffusion kinetics and poor cycling life issues in energy storage devices.Herein,multidimensional(0D/2D/3D) structural defects are constructed in WO_(3)/MoO_(2) simultaneously via competing for and sharing with O atoms during simple hydrothermal process.OD and 2D defects tailor local electron,activating more sites and generating built-in electric fields to yield ion reservoir,meanwhile,3D defect owning lower anisotropic property tailors Mg^(2+) diffusion channels to fully exploit Mg^(2+) adsorbed sites induced by OD and 2D defects,enhance the kinetics and maintain structural stability.Benefitted from synergistic effect of 0D/2D/3D structural defects,the designed WO_(3)/MoO_(2) shows the higher specific capacity(112.8 mA h g^(-1) at 50 mA g^(-1) with average attenuation rate per cycle of 0.068%),superior rate capability and excellent cycling stability(specific capacity retention of 80% after 1500 cycles at 1000 mA g^(-1)).This strategy provides design ideas of introducing multidimensional structural defects for tailoring local electron and microstructure to improve energy storage property.

Soil water content and nitrogen differentially correlate with multidimensional leaf traits of two temperate broadleaf species

The variation and correlation of leaf economics and vein traits are crucial for predicting plant ecological strategies under different environmental changes.However,correlations between these two suites of traits and abiotic factors such as soil water and nitrogen content remain ambiguous.We measured leaf economics and vein traits as well as soil water and nitrogen content for two different shade-tolerant species(Betula platyphylla and Acer mono)in four mixed broadleaved-Korean pine(Pinus koraiensis)forests along a latitudinal gradient in Northeast China.We found that leaf economics traits and vein traits were decoupled in shade-intolerant species,Betula platphylla,but significantly coupled in a shadetolerant species,A.mono.We found stronger correlations among leaf traits in the shade tolerant species than in the shade intolerant species.Furthermore,leaf economic traits were positively correlated with the soil water gradient for both species,whereas vein traits were positively correlated with soil water gradient for the shade intolerant species but negatively correlated in the shade tolerant species.Although economic traits were positively correlated with soil nitrogen gradient in shade intolerant species but not correlated in shade tolerant species,vein traits were negatively correlated with soil nitrogen gradient in shade tolerant species but not correlated in shade intolerant species.Our study provides evidence for distinct correlations between leaf economics and vein traits and local abiotic factors of species differing in light demands.We recommend that the ecological significance of shade tolerance be considered for species when evaluating ecosystem functions and predicting plant responses to environmental changes.

Psychometric Properties among Japanese Women Based on the Multidimensional Assessment of Women’s Experience of Childbirth

Aims/Background: Perceived experiences of childbirth are important for mothers as they affect their self-esteem, mother-child interactions, subsequent mother-child bonding, and their desire for another child. This study examined the factor structure and construct validity of Salmon and Drew’s Multidimensional Assessment of Women’s Experience of Childbirth (MAWEC) in Japanese. Design/Methods: This study conducted a questionnaire survey using the Japanese version of the MAWEC and other variables with 759 women with infants in Japan. The participants’ mean (standard deviation [SD], range) age was 31.9 (5.3, 18 - 46) years. A total of 353 (46.5%) participants were primiparous and 384 (50.6%) were multiparous, and 22 (2.9%) did not answer. The data were randomly divided into two groups for exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) and separately analyzed the positive- and negative-worded items. I conducted EFA using the maximum-likelihood method with PROMAX rotation from one-through two- and three-factor structures. Different factor structure models were compared in terms of CFAs using, as indicator of goodness-of-fit, chi-square/df, comparative fit index (CFI), and root mean square of error approximation (RMSEA). Results: This study showed that a bifactor model for the MAWEC with four subscales (positive emotion, positive coping, negative emotion, and negative coping) fit the data the best. These four subscales were associated with demographic, obstetric, neonatal, and feeding characteristics. For example, primiparas were more vulnerable to coping aspects of perceived childbirth experiences, including sense of mastery over the delivery process and ability to enjoy the delivery. Gestational age at birth was associated with emotional aspects of perceived childbirth experiences. Conclusion: The Japanese version of the MAWEC consists of four aspects regarding perceived childbirth experience. Perinatal health professionals may examine women’s childbirth experiences from these four perspectives. .

Evolution trend analysis of urban residents’ low-carbon travel development based on multidimensional game theory

In the travel process of urban residents,travelers will take a series of activities such as imitation and exclusion by observing other people’s travel modes,which affects their following trips.This process can be seen as a repeated game between members of the travelers.Based on the analysis of this game and its evolution trend,a multi-dimensional game model of low-carbon travel for residents is established.The two dimensional game strategies include whether to accept the low-carbon concept and whether to choose low-carbon travel.Combined with evolutionary game theory,the low-carbon travel choices of residents in different cities are simulated,and the evolutionary stability strategies are obtained.Finally,the influences of the main parameters of the model on the evolution process and stability strategies are discussed.The results show that travelers would develop towards two trends.Cities with more developed public traffic system have a higher proportion of receiving low-carbon concept and choosing low-carbon travel.Cities with underdeveloped public transport system could increase this proportion by some measures such as encouraging residents to choose slow transport and increasing the propaganda of low-carbon travel,but the positive effects of the measures like propaganda have a limited impact on the proportion.

Multidimensional(0D-3D)functional nanocarbon:Promising material to strengthen the photocatalytic activity of graphitic carbon nitride

As a prospective visible-light-responsive photochemical material,graphitic carbon nitride(g-C_(3)N_(4))has become a burgeoning research hot topics and aroused a wide interest as a metal-free semiconductor in the area of energy utilization and conversion,environmental protection due to its unique properties,such as facile synthesis,high physicochemical stability,excellent electronic band structure,and sustainability.However,the shortcomings of high recombination rate of charge carriers,relatively low electrical conductivity and visible light absorption impede its practical application.Various strategies,such as surface photosensitization,heteroatom deposition,semiconductor hybridization,etc.,have been applied to overcome the barriers.Among all the strategies,functional nanocarbon materials with various dimensions(0D~3D)attract much attention as modifiers of g-C_(3)N_(4)due to their unique electronic properties,optical properties,and easy functionalization.More importantly,the properties of these functional nanocarbon materials can be tuned by various dimensions and thus there will be a way to overcome the defects of g-C_(3)N_(4)by choosing different dimensional carbon materials.Distinguishing from some present reviews,this review starts with the fundamental physicochemical characteristics of g-C_(3)N_(4)materials,followed by analyzing the advantages of functional nanocarbon materials modifying gC_(3)N_(4).Then,we present a systematic introduction to various dimensional carbon materials.The design philosophy of carbon/g-C_(3)N_(4)composites and the advanced studies are exemplified in detail.Finally,a nichetargeting summary and outlook on the major challenges,opportunities for future research in high-powered carbon/g-C_(3)N_(4)composites was proposed.

Multidimensional Hybrid Architecture Encapsulating Cobalt Oxide Nanoparticles into Carbon Nanotube Branched Nitrogen-Doped Reduced Graphene Oxide Networks for Lithium–Sulfur Batteries

Lithium–sulfur batteries(LSBs)are regarded as promising candidates for the next-generation energy storage devices owing to their high-theoretical capacity(1675 mAh g^(−1))and affordable cost.However,several limitations of LSBs such as the lithium polysulfide shuttle,large volume expansion,and low electrical conductivity of sulfur need to be resolved for practical applications.To address these limitations,herein,a multidimensional architectured hybrid(Co@CNT/nG),where Co_(3)O_(4) nanoparticles are encapsulated into threedimensional(3D)porous N-doped reduced graphene oxide interconnected with carbon nanotube(CNT)branches,is synthesized through a simple pyrolysis method.The synergistic effect achieved through the homogeneously distributed and encapsulated Co_(3)O_(4) nanoparticles,the interconnected CNT branches,and the 3D hierarchical porous structure and N-doping of Co@CNT/nG significantly suppresses the shuttle effect of lithium polysulfides and enhances the conversion redox kinetics for the improved sulfur utilization.We validate this effect through various measurements including symmetric cells,Li_(2)S nucleation,shuttle currents,Tafel slopes,diffusion coefficients,and post-mortem analyses.Importantly,Co@CNT/nG-70S-based LSB cells achieve a high-specific capacity of 1193.1 mAh g^(−1) at 0.1 C and a low capacity decay rate of 0.030%per cycle for 700 cycles at 5 C,delivering a high areal capacity of 5.62 mAh cm^(−2) even with a loading of 6.5 mg cm^(−2).

PRECISE ASYMPTOTICS IN SELF-NORMALIZED SUMS OF ITERATED LOGARITHM FOR MULTIDIMENSIONALLY INDEXED RANDOM VARIABLES

In the case of Z＋^d（d ≥ 2）-the positive d-dimensional lattice points with partial ordering ≤, {Xk,k∈ Z＋^d} i.i.d, random variables with mean 0, Sn =∑k≤nXk and Vn^2 = ∑j≤nXj^2, the precise asymptotics for ∑n1/｜n｜（log｜n｜dP（｜Sn/Vn｜≥ε√log log｜n｜） and ∑n（logn｜）b/｜n｜（log｜n｜）^d-1P（｜Sn/Vn｜≥ε√log n）,as ε↓0,is established.

Applying XML for designing and interchanging information for multidimensional model

In order to exchange and share information among the conceptual models of data warehouse, and to build a solid base for the integration and share of metadata, a new multidimensional concept model is presented based on XML and its DTD is defined, which can perfectly describe various semantic characteristics of multidimensional conceptual model. According to the multidimensional conceptual modeling technique which is based on UML, the mapping algorithm between the multidimensional conceptual model is described based on XML and UML class diagram, and an application base for the wide use of this technique is given.

Optimizing Spray and Combustion in Diesel Engine by Multidimensional Numerical Simulation

The calculation of spray and combustion in diesel engines is described by using the softwares FIRE and BOOST. The application of the resulting computational method to the simulation of fuel spray and breakup, mixture formation and combustion in a heavy duty diesel is presented. According to detailed insight into the governing processes provided by the simulation results, various aspects of the dependence of the spray propagation and combustion on the chamber geometry and spray angle are discussed. Then, global cylinderaveraged pressure traces are extracted from the space and time resolved field quantities and compared to incylinder pressure measurements. Finally, an optimized configuration of the chamber geometry and spray angle with a new injection rate of higher injection pressure is proposed.

Impact of climate-smart agricultural technology on multidimensional poverty in rural Ethiopia

A large body of empirical literature showed that the adoption of agricultural technologies reduces poverty. However, dominants of those studies so far used one-dimensional income or expenditure-based measures of poverty which may not reflect other types of deprivations. Therefore, the major objective of this study is to examine the impact of adopting climate-smart agricultural technology, which refers to a joint application of row planting methods and the use of chemical fertilizers, on the multidimensional poverty status of rural households in Ethiopia. To estimate the impact of the stated technologies, this study employs propensity score matching and endogenous switching regression methods. To measure the multidimensional poverty index, the study also uses the Alkire and Foster counting approach. Using the Ethiopian Socioeconomic Survey(ESS), collected in 2015-Wave 3, the results of the study show that the adoption of these technologies reduces deprivation score and one of its component, the standard of living part. Regionally, a high reduction in deprivation is observed in Amhara and Oromiya regions. The results also show that the impact is significantly higher in severely deprived households. It is also observed that the reduction in multidimensional poverty due to the technology is through an increase in income/consumption via improvement in production gain. The impact channels more through the non-food expenditure pathway. Finally, this study also sheds light on the effects that technology adoption has on multidimensional poverty reduction.

Analyzing multidimensional measures of poverty and their influences in China's Qinba Mountains

We use the Alkire–Foster poverty measure and decomposition method to study multidimensional poverty in the Qinling–Daba contiguous poor area of China's Henan Province.We examine absolute,relative,and multidimensional poverty focusing on heads of household and family characteristics as constituents of escaping each.We find that the multidimensional poverty index declines to a low level as values of k increase.Combining first-order random dominance with second-order stochastic dominance quickly determines rankings in the multidimensional poverty index.Increasing non-agricultural income emerges as the most important influence on escaping rural poverty,whereas households with elderly and children are at greatest risk for falling into poverty.

A New Multidimensional Time Series Forecasting Method Based on the EOF Iteration Scheme

In this paper a new .mnultidimensional time series forecasting scheme based on the empirical orthogonal function (EOF) stepwise iteration process is introduced. The scheme is tested in a series of forecast experiments of Nino3 SST anomalies and Tahiti-Darwin SO index. The results show that the scheme is feasible and ENSO predictable.

MULTIDIMENSIONAL MULTI-KNOTS PIECEWISE LINEAR SPECTRAL SEQUENCES

Motivated by representing multidimensional periodic nonlinear and non-stationary signals （functions）, we study a class of orthonormal exponential basis for L2（Id） with I ：= [0, 1）, whose exponential parts are piecewise linear spectral sequences with p-knots. It is widely applied in time-frequency analysis.

Distributed Localization Algorithm for Wireless Sensor Network Based on Multidimensional Scaling and the Shortest Path Distance Correction

Sensor localization is crucial for the configuration and applications of wireless sensor network (WSN). A novel distributed localization algorithm, MDS-DC was proposed for wireless sensor network based on multidimensional scaling (MDS) and the shortest path distance correction. In MDS-DC, several local positioning regions with reasonable distribution were firstly constructed by an adaptive search algorithm, which ensures the mergence between the local relative maps of the adjacent local position regions and can reduce the number of common nodes in the network. Then, based on the relationships between the estimated distances and actual distances of anchors, the distance estimation vectors of sensors around anchors were corrected in each local positioning region. During the computations of the local relative coordinates, an iterative process, which is the combination of classical MDS algorithm and SMACOF algorithm, was applied. Finally, the global relative positions or absolute positions of sensors were obtained through merging the relative maps of all local positioning regions. Simulation results show that MDS-DC has better performances in positioning precision, energy efficiency and robustness to range error, which can meet the requirements of applications for sensor localization in WSN.