基于Johnson分布体系黄土滑坡影响范围的概率预测

通过在甘肃省天水市进行大量的现场调查,收集已经发生的黄土滑坡数据并建立数据库,利用Johnson分布体系建立了多维滑坡变量模型并预测潜在滑坡发生后的堆积区滑体长度、滑坡体的面积和滑坡体的宽度。通过对比预测结果与验证组中滑坡体真实数据发现预测模型具有较好的精准度,以预测结果90%置信区间上边界作为影响范围的安全值,推导出研究区域内潜在黄土滑坡影响范围的预测公式,并以研究区域以外的同类型黄土滑坡数据加以验证发现预测公式对天水市内其他区域同类型的黄土滑坡的评估具有一定的适用性。预测公式中只有不稳定边坡高度作为自变量,这对现场快速评估不稳定黄土潜在滑坡危害、影响范围提供了极大便利。

Inverse of Rensch’s Rule of Allometry for Sexual Size Dimorphism in Bufo andrewsi

Difference in body size between males and females(sexual size dimorphism:SSD)and its variation are a common phenomenon in animal kingdom.Rensch’s rule predicts that the degree of SSD variation increases with the enlarged mean body size when males are larger than females and decreases when females are larger than males.Here,whether the patterns of variations in SSD in the Andrew’s toad(Bufo andrewsi)follow Rensch’s rule was tested using unpublished data from 14 populations and published data from 17 populations.Results show the reduced major axis regression of log10(male size)on log10(female size)across all populations displayed a significant hyperallometric relationship,which was consistent with inverse Rensch’s rule(the degree of SSD increased with enlarged mean body size).SSD could also be explained by sexual age difference(SAD)due to a positive SSD–SAD relationship among all populations.The findings suggest that the occurrence of inverse Rensch’s rule in B.andrewsi is likely to be a result of fecundity selection on increased reproductive investments in larger females.

Zipf’s Law, Benford’s Law, and Pareto Rule

From a basic probabilistic argumentation, the Zipfian distribution and Benford’s law are derived. It is argued that Zipf’s law fits to calculate the rank probabilities of identical indistinguishable objects and that Benford’s distribution fits to calculate the rank probabilities of distinguishable objects. i.e. in the distribution of words in long texts all the words in a given rank are identical, therefore, the rank distribution is Zipfian. In logarithmic tables, the objects with identical 1st digits are distinguishable as there are many different digits in the 2nd, 3rd… places, etc., and therefore the distribution is according to Benford’s law. Pareto 20 - 80 rule is shown to be an outcome of Benford’s distribution as when the number of ranks is about 10 the probability of 20% of the high probability ranks is equal to the probability of the rest of 80% low probability ranks. It is argued that all these distributions, including the central limit theorem, are outcomes of Planck’s law and are the result of the quantization of energy. This argumentation may be considered a physical origin of probability.

Quantum Algorithm for Mining Frequent Patterns for Association Rule Mining

Maximum frequent pattern generation from a large database of transactions and items for association rule mining is an important research topic in data mining. Association rule mining aims to discover interesting correlations, frequent patterns, associations, or causal structures between items hidden in a large database. By exploiting quantum computing, we propose an efficient quantum search algorithm design to discover the maximum frequent patterns. We modified Grover’s search algorithm so that a subspace of arbitrary symmetric states is used instead of the whole search space. We presented a novel quantum oracle design that employs a quantum counter to count the maximum frequent items and a quantum comparator to check with a minimum support threshold. The proposed derived algorithm increases the rate of the correct solutions since the search is only in a subspace. Furthermore, our algorithm significantly scales and optimizes the required number of qubits in design, which directly reflected positively on the performance. Our proposed design can accommodate more transactions and items and still have a good performance with a small number of qubits.

材料Johnson-Cook破坏准则参数对侵彻行为的影响及校正

利用Johnson-Cook破坏模型和非线性商业软件Abaqus,以4340钢杆弹垂直侵彻半无限4340钢靶板为例,探讨和分析参数D1D5对破坏等效应变及侵彻计算过程与结果的影响,并获得各参数对侵彻深度的影响规律。研究表明:参数D1的取值为正值且应非常接近于0.000,综合考虑计算的稳定性,金属材料可取0.001或稍小;D4可取负值,建议为[-0.005,0.005];弹体在侵彻过程中接触部位所受静水压力为正（以压为正）且数值较大,入射速度为2.47 km/s时,弹体头部最大压力-等效应力比最大,达到142.14;D2和D3的取值应非常谨慎,需要通过数值计算验证。用所给出的校正方法和原则,对4340钢的Johnson-Cook破坏准则中参数进行校正,认为参数D1D5分别可取为0.001、2.730、2.000、0.002和0.610,数值计算表明,用该组数据进行数值计算的结果与实验接近,侵彻仿真过程合理准确。

国产C30混凝土考虑率型微损伤演化的改进Johnson-Cook强度模型

采用Instron1342液压伺服试验机和改进的SHPB技术对国产C30混凝土进行了应变率在一定宽广范围的一维应力下力学性能试验,采用Johnson-Cook强度模型的框架,确定适用于大变形、高应变率及高压下混凝土数值计算的等效强度模型的率相关参数及其他材料常数。由对C30混凝土的大量试验表明,混凝土损伤演化是同时依赖于应变与应变率的率相关过程,提出适用于工程应用的率型损伤演化律来描述C30混凝土的损伤演化过程,并确定了损伤演化常数。由于材料参数小于1,对应于材料的冲击韧化的过程,与国产C30混凝土动态试验结果相吻合。

Johnson法则在成组加工排序中的推广

成组技术（Group Technology）是把工件分组进行加工,以提高生产效率的一种生产组织方法,本文把两台机器同序作业（同顺序流水作业）排序问题F2│perm│C_(max)的John-son法则推广到成组加工上,提出确定组与组之间顺序的最优法则,给出了这个问题成组加工的最优排法,并分析算法的计算复杂性。

Johnson公式用于测紧凑拉伸试样的裂纹扩展

本文介绍了测量裂纹扩展的直流电位法中的Ｊｏｈｎｓｏｎ公式。对两侧切槽紧凑拉伸试样的标定实验和经疲劳予制裂纹试样实测表明，直流电位法的精度对试样裂纹宽度比较敏感。疲劳裂纹试样经裂端钝化效应修正后。

A CUMULATIVE FATIGUE DAMAGE RULE UNDER THE ALTERNATIVE OF CORROSION OR CYCLIC LOADING

Fatigue damage increases with the applied loading cycles in a cumulative manner and the material deteriorates with the corrosion time. A cumulative fatigue damage rule under the alternative of corrosion or cyclic loading was proposed. The specimens of aluminum alloy LY12-CZ soaked in corrosive liquid for different times were tested under the constant amplitude cyclic loading to obtain S-N curves. The test was carried out to verify the proposed cumulative fatigue damage rule under the different combinations among corrosion time, loading level, and the cycle numbers. It was shown that the predicted residual fatigue lives showed a good agreement with the experimental results and the proposed rule was simple and can be easily adopted.

Use Chou’s 5-Steps Rule to Predict Remote Homology Proteins by Merging Grey Incidence Analysis and Domain Similarity Analysis

Detecting remote homology proteins is a challenging problem for both basic research and drug development. Although there are a couple of methods to deal with this problem, the benchmark datasets based on which the existing methods were trained and tested contain many high homologous samples as reflected by the fact that the cutoff threshold was set at 95%. In this study, we reconstructed the benchmark dataset by setting the threshold at 40%, meaning none of the proteins included in the benchmark dataset has more than 40% pairwise sequence identity with any other in the same subset. Using the new benchmark dataset, we proposed a new predictor called “dRHP-GreyFun” based on the grey modeling and functional domain approach. Rigorous cross-validations have indicated that the new predictor is superior to its counterparts in both enhancing success rates and reducing computational cost. The predictor can be downloaded from https://github.com/jcilwz/dRHP-GreyFun.

Mitochondrial homeostasis in Parkinson＇s disease-a triumvirate rule？

Mitochondrial dysfunction in Parkinson＇s disease：Mitochondria are the primary energy generator of the cell and they are important for cell survival and apoptosis.Defective mitochondrial homeostasis is frequently reported in human diseases especially those affecting the brain.

Research on knowledge acquisition method about the IF/THEN rules based on rough set theory

The basic principles of IF/THEN rules in rough set theory are analyzed first, and then the automatic process of knowledge acquisition is given. The numerical data is qualitatively processed by the classification of membership functions and membership degrees to get the normative decision table. The regular method of relations and the reduction algorithm of attributes are studied. The reduced relations are presented by the multi-representvalue method and its algorithm is offered. The whole knowledge acquisition process has high degree of automation and the extracted knowledge is true and reliable.

Scattering Phase Correction for Semiclassical Quantization Rules in Multi-Dimensional Quantum Systems

While the scattering phase for several one-dimensional potentials can be exactly derived, less is known in multi-dimensional quantum systems. This work provides a method to extend the one-dimensional phase knowledge to multi-dimensional quantization rules. The extension is illustrated in the example of Bogomolny＇s transfer operator method applied in two quantum wells bounded by step potentials of different heights. This generalized semiclassical method accurately determines the energy spectrum of the systems, which indicates the substantial role of the proposed phase correction. Theoretically, the result can be extended to other semiclassical methods, such as Gutzwiller trace formula, dynamical zeta functions, and semielassical Landauer Buttiker formula. In practice, this recipe enhances the applicability of semiclassical methods to multi-dimensional quantum systems bounded by general soft potentials.

Alzheimer’s Disease Diagnosis Based on a Semantic Rule-Based Modeling and Reasoning Approach

Alzheimer’s disease(AD)is a very complex disease that causes brain failure,then eventually,dementia ensues.It is a global health problem.99%of clinical trials have failed to limit the progression of this disease.The risks and barriers to detecting AD are huge as pathological events begin decades before appearing clinical symptoms.Therapies for AD are likely to be more helpful if the diagnosis is determined early before the final stage of neurological dysfunction.In this regard,the need becomes more urgent for biomarker-based detection.A key issue in understanding AD is the need to solve complex and high-dimensional datasets and heterogeneous biomarkers,such as genetics,magnetic resonance imaging(MRI),cerebrospinal fluid(CSF),and cognitive scores.Establishing an interpretable reasoning system and performing interoperability that achieves in terms of a semantic model is potentially very useful.Thus,our aim in this work is to propose an interpretable approach to detect AD based on Alzheimer’s disease diagnosis ontology(ADDO)and the expression of semantic web rule language(SWRL).This work implements an ontology-based application that exploits three different machine learning models.These models are random forest(RF),JRip,and J48,which have been used along with the voting ensemble.ADNI dataset was used for this study.The proposed classifier’s result with the voting ensemble achieves a higher accuracy of 94.1%and precision of 94.3%.Our approach provides effective inference rules.Besides,it contributes to a real,accurate,and interpretable classifier model based on various AD biomarkers for inferring whether the subject is a normal cognitive(NC),significant memory concern(SMC),early mild cognitive impairment(EMCI),late mild cognitive impairment(LMCI),or AD.

Asymptotic solutions of the flow of a Johnson-Segalman fluid through a slowly varying pipe using double perturbation strategy

A double perturbation strategy is presented to solve the asymptotic solutions of a Johnson-Segalman （J-S） fluid through a slowly varying pipe. First, a small parameter of the slowly varying angle is taken as the small perturbation parameter, and then the second-order asymptotic solution of the flow of a Newtonian fluid through a slowly varying pipe is obtained in the first perturbation strategy. Second, the viscoelastic parameter is selected as the small perturbation parameter in the second perturbation strategy to solve the asymptotic solution of the flow of a J-S fluid through a slowly varying pipe. Finally, the parameter effects, including the axial distance, the slowly varying angle, and the Reynolds number, on the velocity distributions are analyzed. The results show that the increases in both the axial distance and the slowly varying angle make the axial velocity slow down. However, the radial velocity increases with the slowly varying angle, and decreases with the axial distance. There are two special positions in the distribution curves of the axial velocity and the radial velocity with different Reynolds numbers, and there are different trends on both sides of the special positions. The double perturbation strategy is applicable to such problems with the flow of a non-Newtonian fluid through a slowly varying pipe.

On China's Foreign Trade Development and Linkage with the Customary Rules of International Trade

Although great differences exist between the trade systems of different countries,internationaltrade must go on in line with the customary international trade rules.As China’s economy developsand the socialist market economic system emerges,China is basically qualified to link up withcustomary international trade rules.In the Ninth Five-Year Plan period,China’s reform of its foreigntrade system aims at setting up a trade system that conforms with international trade practice.Forthe purpose,the author of this article suggests that a neutral trade policy should be adopted inaccordance with the international practice since it does not hinder exports,nor restrict imports toan excessive degree.

基于动态剩余S-N曲线的线性疲劳寿命预测模型

为估算结构在变幅载荷下的疲劳寿命,在动态剩余S-N曲线的基础上,结合材料的退化规律,对材料受载过程中的累积疲劳损伤进行了量化,提出了一种预测变幅载荷下线性疲劳损伤预测模型。根据热轧16Mn钢和20Cr2Ni4A标准圆柱齿轮多级载荷下疲劳寿命试验数据,对提出模型的疲劳寿命预测能力进行了验证。结果表明:基于强度退化的线性疲劳寿命预测模型相对传统Miner法则和材料记忆退化累积模型的预测结果更接近试验结果,具有较高的预测精度。

Alternative Error Bounds for Some Numerical Quadrature Rules

Similar to having done for the mid-point and trapezoid quadrature rules,we obtain alternative estimations of error bounds for the Simpson＇s quadrature rule involving n-time（1 ≤ n ≤ 4） differentiable mappings and then to the estimations of error bounds for the adaptive Simpson＇s quadrature rule.

NASH EQUILIBRIA WITHOUT CONTINUITY OF THE CHOICE RULES

The proposal in Alcantud and Alo′s-Ferrer [1], where players that express their tastes according to choice rules facing a competitive situation, is further exploited here. We prove that, under lack of continuity of the choice rules it is also possible to ensure the existence of equilibrium. We shall appeal to general situations that are fulfilled by well-established models, where players have non-transitive preferences of various types.

Gly-LysPred: Identification of Lysine Glycation Sites in Protein Using Position Relative Features and Statistical Moments via Chou’s 5 Step Rule

Glycation is a non-enzymatic post-translational modification which assigns sugar molecule and residues to a peptide.It is a clinically important attribute to numerous age-related,metabolic,and chronic diseases such as diabetes,Alzheimer’s,renal failure,etc.Identification of a non-enzymatic reaction are quite challenging in research.Manual identification in labs is a very costly and timeconsuming process.In this research,we developed an accurate,valid,and a robust model named as Gly-LysPred to differentiate the glycated sites from non-glycated sites.Comprehensive techniques using position relative features are used for feature extraction.An algorithm named as a random forest with some preprocessing techniques and feature engineering techniques was developed to train a computational model.Various types of testing techniques such as self-consistency testing,jackknife testing,and cross-validation testing are used to evaluate the model.The overall model’s accuracy was accomplished through self-consistency,jackknife,and cross-validation testing 100%,99.92%,and 99.88%with MCC 1.00,0.99,and 0.997 respectively.In this regard,a user-friendly webserver is also urbanized to accumulate the whole procedure.These features vectorization methods suggest that they can play a critical role in other web servers which are developed to classify lysine glycation.