RETRACTED: Nuclear Structure Study of Odd-Odd Yttrium Nuclei within Interacting-Boson Fermi-Fermion Model (IBFFM)

Short Retraction NoticeThe paper does not meet the standards of "Journal of Applied Mathematics and Physics". This article has been retracted to straighten the academic record. In making this decision the Editorial Board follows COPE's Retraction Guidelines. The aim is to promote the circulation of scientific research by offering an ideal research publication platform with due consideration of internationally accepted standards on publication ethics. The Editorial Board would like to extend its sincere apologies for any inconvenience this retraction may have caused.Editor guiding this retraction: Prof. Wen-Xiu Ma (EiC of JAMP)The full retraction notice in PDF is preceding the original paper, which is marked "RETRACTED".

Term Structure of Interest Rates Based on Artificial Neural Network

In light of the nonlinear approaching capability of artificial neural networks （ ANN）, the term structure of interest rates is predicted using The generalized regression neural network （GRNN） and back propagation （BP） neural networks models. The prediction performance is measured with US interest rate data. Then, RBF and BP models are compared with Vasicek＇s model and Cox-Ingersoll-Ross （CIR） model. The comparison reveals that neural network models outperform Vasicek＇s model and CIR model, which are more precise and closer to the real market situation.

Modelling the Term Structure of Hong Kong Inter-Bank Offered Rates （HIBOR）

Different single-factor models are used to estimate the term structure of Hong Kong Inter-Bank Offered Rates （HIBOR）. These models use stochastic differential equations which effectively reflect market characteristics of short- and long-term interest rates, such as capability of mean reversion and interest rate level fluctuation. For the period from 2005 to early 2007, the economy of Hong Kong had been relatively stable with pretty low volatilities in interest rate. However, starting from 2008 to beginning of 2012, the Hong Kong and the world economies had been steering from relatively stable to fluctuations, the 2008 financial tsunami initiated by the U,S. had been causing financial instability globally. With the U.S： government taking quantitative easing monetary policy, U.S. interest rates fluctuated and submerged rapidly. Volatility of HIBOR was extremely sensitive to fluctuation of U.S. interest rates, since Hong Kong dollar exchange rate has been pegged with U.S. dollar. In short, during the period of early 2008 to early 2012, volatility of short-term interest rate was extremely sensitive. Obviously, the term structure of interest rate for these two periods had made major shift, combining the two periods would lead to unfavorable econometric results.

Volatility Structures of ForwardRates and the Dynamics of the TermStructure:a Multifactor Case

For general volatility structures for forward rates, the evolution of interest rates may not be Markovian and the entire path may be necessary to capture the dynamics of the term structure. This article identifies conditions on the volatility structure of forward rates that permit the dynamics of the term structure to be represented by a finite-dimensional state variable Markov process. In the deterministic volatility case, we interpret then-factor model as a sum ofn unidimensional models.

Simulation Methods of Stochastic Volatility Interest Rate Term Structure

A term structure model bearing features of stochastic volatility and stochastic mean drift with jump （SVJ-SD model for short） is built in the paper to describe the stochastic behavior of interest rates.Based on sample data of an interest rate of national bond repurchase,maximum likelihood （ML）,linear Kalman filter and efficient method of moments （EMM） are used to estimate the model.While ML works well for simple models,it may lead to considerable deviation in parameter estimation when dynamic risks of interest rates are considered in them.Linear Kalman filter is a tractable and reasonably accurate technique for estimation cases where ML was not feasible.Moreover,when compared with the first two approaches,using EMM can obtain better parameter estimates for complex models with non-affine structures.

Perturbation Analysis of Structured Least Squares Problems and Its Application in Calibration of Interest Rate Term Structure

A structured perturbation analysis of the least squares problem is considered in this paper.The new error bound proves to be sharper than that for general perturbations. We apply the new error bound to study sensitivity of changing the knots for curve fitting of interest rate term structure by cubic spline.Numerical experiments are given to illustrate the sharpness of this bound.

Empirical Estimation of Term Structure of Interbank Rates in China

Nelson-Siegel model （ NS model） and 2 extended NS models were compared by using daily interbank government bond data Based on the grouping of bonds according to the residual term to maturity, the empirical research proceeded with in-sample and outof-sample tests. The results show that the 3 models are almost equivalent in estimating interbank term structure of interest rates. Within the term to maturities between 0 and 7 years, the gap of the absolute errors of the 3 models between in-sample and out-of-sample is smRller than 0.2 Yuan, and the absolute values of the in-sample and out-of-sample errors are smaller than 0. 1 Yuan, so the estimation is credible. Within the term to maturities between 7 and 20 years, the gap of the absolute errors of the 3 models between in-sample and out-of-sample is larger than 0.4 Yuan, and the absolute values of the in-sample and out-of-sample errors are larger than 1.0 Yuan, so the estimation is incredible.

Modelling time series properties of Australian lending interest rates

The purpose of this paper is to examine the time series properties of Australian residential mortgage interest rates, and in doing so, establish whether or not selected home loan rates （product-level monthly home loan interest rates for CBA） exhibit the expected cyclical and seasonal variations and whether seasonality, if present, is stochastic or deterministic. In particular, due to a well established presence of cyclicality in financial markets＇ interest rates and strong correlation between financial markets＇ interest rates and home loan interest rates, the paper presumes that cyclicality is also to be found in home loan interest rates. Furthermore, the paper tests the hypothesis that home loan interest rates, for selected products, exhibit the three identified （＂Spring＂, ＂Autumn＂ and ＂The end of the Financial Year＂） season-related interest rate reductions. The paper uses a structural time series modelling approach and product-level home loan interest rates data from one of the biggest banks in Australia, Commonwealth Bank of Australia （CBA）. As expected, the results overall confirm the existence of cyclicality in home loan interest rates. With respect to the seasonality of home loan interest rate, although most of the analysed variables show the presence of statistically significant seasonal factors, the majority of the statistically significant seasonal factors observed cannot be attributed to any of the three considered seasonal effects.

LINEAR FILTERING FOR VASICEK TERM STRUCTURE MODEL WITH SEQUENTIALLY CORRELATED NOISE

When Kalman filter is used in the estimation of Vasicek term structure of interest rates,it is usual to assume that the measurement noise is uncorrelated.Study results are more favorable to the assumption of correlated measurement noise.An augmented state Kalman filter form for Vasicek model is proposed to optimally estimate the unobservable state variable with the assumption of correlated measurement noise.Empirical results indicate that the model with sequentially correlated measurement noise can more accurately describe the dynamics of the term structure of interest rates.

Structured scene modeling using micro stereo vision system with large field of view

This paper presents a method for structured scene modeling using micro stereo vision system with large field of view. The proposed algorithm includes edge detection with Canny detector, line fitting with principle axis based approach, finding corresponding lines using feature based matching method, and 3D line depth computation.

汇率变动、OFDI与出口贸易--中国与欧亚经济联盟经贸关系的经验分析

巩固和发展同欧亚经济联盟的经贸合作关系对于促进“一带一路”倡议的深远发展具有重要意义。作者基于新经济地理学理论,结合引入汇率因素的结构化贸易引力模型,在理论层面上构建了汇率变动、OFDI与出口贸易关系的理论模型并提出研究假设,将汇率变动划分为汇率水平变动与汇率波动,引入第三方汇率波动并细化为区域邻国汇率波动、中美汇率波动和中欧汇率波动三方面,采用2003—2017年中国与欧亚经济联盟成员国贸易和投资面板数据,运用全面可行广义最小二乘法(FGLS)、工具变量法(2SLS、GMM和LIML)等估计方法实证检验了汇率变动、OFDI对出口贸易的影响以及异质性汇率变动条件下OFDI的出口效应。通过研究发现:中国对欧亚经济联盟OFDI与出口贸易呈现互补关系;汇率波动对出口贸易产生显著抑制作用,而汇率水平变动影响则不显著;区域经济一体化显著降低中国对欧亚经济联盟的出口贸易;引入第三方汇率波动变量,发现第三方汇率波动效应具有异质性,区域邻国汇率波动有助于促进中国对欧亚经济联盟的出口,而中美与中欧汇率波动影响并不显著。利用国际贸易标准货物分类(SITC)将出口产品分为初级产品、劳动密集型产品和资本密集型产品,进一步探究OFDI对异质性产品出口贸易的影响,发现中国对欧亚经济联盟OFDI与不同类型的产品均具有显著互补关系,汇率水平变动对不同类型产品出口影响仍然不显著;双边汇率波动、区域经济一体化显著抑制中国与欧亚经济联盟的出口贸易,同时在考虑第三方汇率波动的情形下,双边汇率波动对初级产品的影响程度增强,对劳动和资本密集型产品的影响减弱;第三方汇率波动对不同类型产品的影响具有异质性,初级产品中第三方汇率波动均显著促进出口;劳动密集型产品中第三方汇率波动均无显著影响;资本密集型产品中仅有邻国汇率波动促进出口。设定汇率变动、第三方汇率波动和区域经济一体化与OFDI的交互项模型,实证检验了异质性汇率变动条件下中国对欧亚经济联盟OFDI的出口效应,研究发现OFDI出口效应中,汇率波动具有显著抑制效应,区域经济一体化和汇率水平变动影响不显著;第三方汇率波动效应具有异质性,区域邻国汇率波动显著抑制OFDI的出口效应,而中美和中欧汇率波动影响不显著。

Modeling of Heat Transfer and Steam Condensation Inside a Horizontal Flattened Tube

This work investigates the steam condensation phenomena in an air-cooled condenser.The considered horizontal flattened tube has a 30 mm hydraulic diameter,and its length is a function of the steam quality with a limit value between 0.95 and 0.05.The mass flow rate ranges from 4 to 40 kg/m^(2).s with a saturated temperature spanning an interval from 40°C to 80°C.A special approach has been implemented using the Engineering Equation Solver(EES)to solve a series of equations for the two-phase flow pattern and the related heat transfer coefficients.A wavy-stratified structure of the two-phase flow has been found when the mass rate was between 4 and 24 kg/m^(2).s.In contrast,an initially annular flow is gradually converted into a wavy stratified flow(due to the condensation process taking place inside the flattened tube)when the considered range ranges from 32 to 40 kg/m^(2).s.

Effects of Multicollinearity on Type I Error of Some Methods of Detecting Heteroscedasticity in Linear Regression Model

Heteroscedasticity and multicollinearity are serious problems when they exist in econometrics data. These problems exist as a result of violating the assumptions of equal variance between the error terms and that of independence between the explanatory variables of the model. With these assumption violations, Ordinary Least Square Estimator (OLS) will not give best linear unbiased, efficient and consistent estimator. In practice, there are several structures of heteroscedasticity and several methods of heteroscedasticity detection. For better estimation result, best heteroscedasticity detection methods must be determined for any structure of heteroscedasticity in the presence of multicollinearity between the explanatory variables of the model. In this paper we examine the effects of multicollinearity on type I error rates of some methods of heteroscedasticity detection in linear regression model in other to determine the best method of heteroscedasticity detection to use when both problems exist in the model. Nine heteroscedasticity detection methods were considered with seven heteroscedasticity structures. Simulation study was done via a Monte Carlo experiment on a multiple linear regression model with 3 explanatory variables. This experiment was conducted 1000 times with linear model parameters of β0 = 4 , β1 = 0.4 , β2= 1.5 and β3 = 3.6. Five (5) levels of mulicollinearity are with seven (7) different sample sizes. The method’s performances were compared with the aids of set confidence interval (C.I.) criterion. Results showed that whenever multicollinearity exists in the model with any forms of heteroscedasticity structures, Breusch-Godfrey (BG) test is the best method to determine the existence of heteroscedasticity at all chosen levels of significance.

How Users Perceive Infrastructure Development Affects Their Transport Mode Choice

Transport infrastructure development and perception vary across and within countries, influencing mode choice among road users. This study explores how road users perceive the development of infrastructure modes, service attributes, embedded safety levels, and commuting modes. Additionally, the research examines whether participants’ environmental backgrounds impact their mode choice patterns. The study gathered responses from 1169 participants residing in two regions of Amman, Jordan, each with distinct infrastructure development and population densities. Participants completed a standardized questionnaire, and several statistical techniques were employed for analysis. The findings revealed that facilities’ infrastructure attributes, development, and safety were assessed using three indices. Both participant groups perceived these indices differently on average. Residents of low population density areas with relatively developed infrastructure showed more consistent assessments, irrespective of their most frequently used mode of transportation, tending towards lower scores. Interestingly, subjective ratings of infrastructure development were higher (4.96) than attribute-based ratings (4.32). Despite their generally low-quality perception, public transportation services received the highest appraisal (4.9). Conversely, pedestrian infrastructure complementing public transport received the lowest assessment (4.57), only slightly higher than street environments (4.59). The study found weak associations between subjective service characteristics ratings. Traveler and trip characteristics influenced mode choice and trips more than infrastructure perception. In conclusion, the study suggests that policies should be developed to encourage green transportation, ensure social equality and safety. In addition, the study contributes to understanding perceptions about transport infrastructure, modes of transportation, and the factors that influence sustainable and equitable transportation systems.

基于岩石CT扫描的冻融作用对花岗岩细观结构及力学强度影响研究

近年来随着西部地区的基础工程建设数量及规模不断增加,西部高原地区的季节性冻融循环效应的影响也随之增强,开展冻融循环作用下岩石细观特性及强度劣化性质研究对指导西部寒区基础工程建设至关重要。首先在偏光显微镜下对岩石薄片进行观察,获取岩石的矿物成分和微结构;接着利用CT扫描技术,对冻融后的花岗岩进行扫描,对扫描图层利用阈值分割进行二值化处理,堆叠得到样品内外结构的高分辨3D数据及影像;结合分形理论计算图像计盒维数并由此对图像复杂度做出量化判断,由此对冻融循环对花岗岩内部结构演化分布特点进行分析;进而揭示其强度演化规律,探究结构演化与强度之间的关系。偏光显微镜下,岩石呈块状构造,具有似斑状粗粒不等粒花岗结构,局部见交代蠕虫结构。似斑晶矿物主要为碱性长石;其他矿物粒径0.25~4.0 mm为主,矿物成分主要为石英、斜长石、碱性长石,次要矿物为黑云母、绿帘石,副矿物有磷灰石、锆石、黄铁矿等,镜下鉴定为似斑状粗粒不等粒黑云二长花岗岩。CT扫描显示,冻融循环效应在影响花岗岩细观结构时,会导致花岗岩内部孔隙率的整体上升,但岩石渗透性变化不大,岩石渗透率仅上升0.003×10^(-3)μm^(2);内部孔隙发育不均匀,试样整体结构改变以萌生较多新的微孔隙为主。冻融循环后岩石内部结构复杂度有所下降,但岩石整体完整性仍然较好,分形维数仍保持在较高水平。分形研究显示,20次冻融循环并未导致花岗岩的结构复杂度发生较大变化,同时试样整体力学特性出现下降,黏性增加以及长期强度出现较大幅度的衰减,进入蠕变试验阶段的应变阈值提高。在评价此类原生结构较致密的岩石的安全性时,仅从结构上进行考量与实际情况往往会出现偏差,应结合必要的强度指标综合评估。岩石在经历冻融循环后,在强度更低的同时会发生更大的变形。该研究可为分形理论在岩石细观结构演化方面的应用及岩石细观结构与强度演化相关研究提供借鉴,并对高寒地区工程施工有指导意义。

基于综合贡献率的舰船装备体系寿命评估

为了更科学地预测装备寿命,提升装备的作战效益,从装备对体系的“综合贡献率”视角出发,探究了舰船装备“体系寿命”的评估方法。首先,基于作战环理论和非线性结构方程模型,引入二次交互项,构建舰船装备体系作战能力的指标体系,建立了体系作战效能的评估模型;然后,运用阈值法建立了舰船装备体系的复杂网络模型,基于拓扑特征统计值,构建了舰船装备体系网络结构特征的指标体系,将层次分析法与熵权法相结合来计算指标权重;最后,提出了舰船装备体系综合贡献率、体系寿命的定义和数学模型,并以航母编队体系对抗为算例,通过实验仿真数据,验证了模型和方法的可行性和有效性。

Application and Model of Term Structure of Stochastic Interest Rate Based on the Inflation Rate

In this paper, we build the arbitrage-free term structure model on the inflation rate, and discuss the relations between the arbitrage-free term structure and the equivalent martingale measure. The volatility terms of diffusion processes of the real forward interest rate, the nominal forward interest rate and the inflation index （Jarrow and Yildirim, 2003） are extended into many dimensional Brownian motions. Moreover, as we derive the differential equations of three-factor term structure, our results are generalized. At last, the analytic solutions of European option can be deduced on the inflation rate.

喷嘴结构内流场数值模拟研究

提升雾化喷嘴出口流量可以提高液体出口速度,从而获得更细小的雾滴,增强雾化效果.为了抑制空化效应,获得更大的出口流量,本文通过建立喷嘴内流场的数值模型,对内流场速度、液相体积分数以及湍动能分布等流场信息进行分析.针对空化的产生机理,提出多种改进喷嘴结构的方案:减小喷嘴长度、增加喷嘴倒角和降低壁面粗糙度,有效降低了空化效应,显著增大了喷嘴的出口流量,改善了雾化效果,为喷嘴结构的优化提供了参考.

循环载荷作用下煤岩复合结构宏-细观破坏特征及能量-损伤本构模型

煤炭深部开采过程中,周期性开采扰动行为会使邻近煤层的煤岩复合结构承受循环载荷的作用,因此,研究不同循环载荷作用下煤岩复合试样的力学响应行为及宏-细观失效特征具有重要工程意义。选取3种不同的加(卸)载速率,开展了2种循环加卸载路径下的单轴循环压缩试验(同步测定声发射信号),分析了煤岩复合试样的损伤失效特征;基于能量耗散原理,构建了煤岩复合试样在循环载荷作用下的能量-损伤本构模型,最后结合试验实测数据进行验证。结果表明:加(卸)载速率与复合试样的峰值强度呈正相关,当加(卸)载速率从0.05 mm/min增大到0.15 mm/min时,恒定下限逐步循环加卸载路径(路径I)、变上下限等幅循环加卸载路径(路径II)下,试样的峰值应力分别增加了22.44%和28.89%;高加(卸)载速率下,试样的内部裂纹扩展越快,煤岩复合试样中煤组分的破碎程度加剧,分形维数随之增大,试样的内部裂纹扩展越快;随着加(卸)载速率的增大,煤组分中沿基质破坏增多。循环分级跨度大的路径(路径I)有助于试样内部的应力传递,为试样内部裂纹的发育提供了有利条件,导致对应试样的破坏程度更高。试验曲线和能量-损伤本构理论曲线具有较强的一致性,表明所建的能量-损伤本构模型能够很好地描述煤岩复合试样在循环加卸载过程中的变形行为。

PMCMC for Term Structure of Interest Rates under Markov Regime Switching and Jumps

A parameter estimation method,called PMCMC in this paper,is proposed to estimate a continuous-time model of the term structure of interests under Markov regime switching and jumps.There is a closed form solution to term structure of interest rates under Markov regime.However,the model is extended to be a CKLS model with non-closed form solutions which is a typical nonlinear and non-Gaussian state-space model(SSM)in the case of adding jumps.Although the difficulty of parameter estimation greatly prevents from researching models,we prove that the nonlinear and non-Gaussian state-space model has better performances in studying volatility.The method proposed in this paper will be implemented in simulation and empirical study for SHIBOR.Empirical results illustrate that the PMCMC algorithm has powerful advantages in tackling the models.