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.

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.

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.

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.

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.

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.

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.

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).

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.

Identification of bioactive anti-angiogenic constitutes targeting tumor endothelial cells in Shenmai Injection using multidimensional pharmacokinetics

OBJECTIVE To identify the bioactive anti-angiogenic constitutes targeting tumor endothelial cells(TECs)in Shenmai Injection(SMI).METHEODS For pharmacokinetic(PK)studies,Balb/c mice harboring human colorectal cancer(LoVo)xenografts were treated with SMI 10 mL·kg^-1 daily for 1 or 8 d.Multidimensional PK profiles of ginsenosides in plasma,subcutaneous tumors,and TECs were investigated.For PD studies,the tumor-bearing mice Intravital multi-photon imaging and CD31 immunofluorescence staining were used to evaluate the number of microves⁃sels and braches.Double staining of CD31 and α-SMA was performed to evaluate pericytes coverage ratios around vessels.ELISA was performed to determine the concentrations of VEGF and FGF in tumor tissues.For synergistic anti-tumor study,the tumor-bearing mice were treated with SMI 10 mL·kg^-1 daily,Rd 5 mg·kg^-1 daily with or without 5-FU 15 mg·kg^-1 every 3 d for 20 d.HPLC-MS/MS was used to determine the concentrations of 5-FU in plasma and tumor tissues.RESULTS SMI decreased the number of microvessels(P<0.05)and vessel branches(P<0.05)and improved vascular pericytes coverage(P<0.05).PK studies showed that the concentrations of protopanaxadiol-type(PPD)ginsenosides(Rb1,Rb2/Rb3,Rc,and Rd)in both,plasma and tumors,were higher than those of protopanaxatriol-type(Rg1 and Re)and oleanane-type(Ro)ginsenosides.Among PPD ginsenosides,Rd exhibited the greatest concentrations in tumors and TECs after repeated injection.In fact,the proportion of Rd in the detectable components of SMI gradually increased in the following order:SMI formula(2.8%),plasma(16.0%),tumor tissues(34.3%),and TECs(40.3%).In vivo bioactivity results showed that Rd 5 mg·kg^-1 daily significantly decreased the number of microvessels(P<0.05)and vessel branches(P<0.05)and increased pericytes coverage(P<0.05)while Rd 0.5 mg·kg^-1 daily,Rb1 and Rg1 had no significant effect on them.Rd 5 mg·kg^-1 suppressed the expression of VEGF and FGF simultaneously.Rd 5 mg·kg^-1 enhanced the antitumor effect of 5-FU via increasing the distribution of 5-FU in tumor tissues(P<0.05)in xenograft mice.CONCLUSION Ginsenoside Rd may be the major bioactive anti-angiogenic constituent targeting TECs after SMI treatment.

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.

Precise large deviations for sums of random vectors in a multidimensional size-dependent renewal risk model

Consider a multidimensional renewal risk model, in which the claim sizes {Xk, k ≥1} form a sequence of independent and identically distributed random vectors with nonnegative components that are allowed to be dependent on each other. The univariate marginal distributions of these vectors have consistently varying tails and finite means. Suppose that the claim sizes and inter-arrival times correspondingly form a sequence of independent and identically distributed random pairs, with each pair obeying a dependence structure. A precise large deviation for the multidimensional renewal risk model is obtained.

The Application of Genetic Algorithms and Multidimensional Distinguishing Model in Forecasting and Evaluating Credits for Mobile Clients

To solve the arrearage problem that puzzled most of the mobile corporations, we propose an approach to forecast and evaluate the credits for mobile clients, devising a method that is of the coalescence of genetic algorithm and multidimensional distinguishing model. In the end of this paper, a result of a testing application in Zhuhai Branch, GMCC was provided. The precision of the forecasting and evaluation of the client’s credit is near 90%. This study is very significant to the mobile communication corporation at all levels. The popularization of the techniques and the result would produce great benefits of both society and economy.

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.

From Nonparametric Density Estimation to Parametric Estimation of Multidimensional Diffusion Processes

The paper deals with the estimation of parameters of multidimensional diffusion processes that are discretely observed. We construct estimator of the parameters based on the minimum Hellinger distance method. This method is based on the minimization of the Hellinger distance between the density of the invariant distribution of the diffusion process and a nonparametric estimator of this density. We give conditions which ensure the existence of an invariant measure that admits density with respect to the Lebesgue measure and the strong mixing property with exponential rate for the Markov process. Under this condition, we define an estimator of the density based on kernel function and study his properties (almost sure convergence and asymptotic normality). After, using the estimator of the density, we construct the minimum Hellinger distance estimator of the parameters of the diffusion process and establish the almost sure convergence and the asymptotic normality of this estimator. To illustrate the properties of the estimator of the parameters, we apply the method to two examples of multidimensional diffusion processes.

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.

Investigating poverty in rural Iran: The multidimensional poverty approach

In this study, rural poverty in Iran is investigated applying a multidimensional approach, association rules mining technique, and Levine, F and Tukey tests to household data of 2008. The results indicate that poverty in its multi-dimensions is an epidemic problem in rural Iran. The results also exhibit that there are 11 patterns of poverty in the rural areas including four main patterns with 99.62% coverage and seven sub-patterns with nearly 0.38% coverage. In these patterns, housing and household education are the most important dimensions of poverty and income poverty is the least important dimension. Government income support policy to households, in enforcement the law of targeting subsidies, cannot be regarded as pro poor policy but it follows other political aspects.