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the patterns of variations in SSD in the Andrew’s toad(Bufo andrewsi)follow Rensch’s rule was tested using unpublished data from 14 populations and published data from 17 populations.Results show the reduced major axis regression of log10(male size)on log10(female size)across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.

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.

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.

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.

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.

The Duties of SMEs Office： From the Viewpoint of WTO＇s Rules

Medium and small-sized enterprises are the important part of China＇s national economy,but they are confronted with some difficulties and problems. So, from the spirit of WTO, SMEs Office has a significant duty to provide capital exchange, talent training, information consultancy and technological guidance, and so on.

Study on Growth Rules and Photosynthetic Physiology of Biennial Container Seedlings and Bare Root Seedlings of Phoebe

Transplantation experiment was carried out using biennial container seedlings and bare root seedlings of Phoebe zhennan S. Lee as materials. In the experiment,it measured the growth indicators such as the seedling height,basal diameter,and number of branches and leaves. Besides,it also measured net photosynthetic rate( Pn),transpiration rate( Tr),stomatal conductance( Gs),intercellular CO_2 concentration( Ci) and soluble sugar,soluble protein,malondialdehyde( MDA) content,superoxide dismutase activity and root activity. The results indicated that the growth indicators of the Phoebe container seedlings performed the best in the plant height,basal diameter,and number of branches and leaves; photosynthetic capacity was the strongest,and the fertilization could enhance the photosynthetic capacity of seedlings; soluble sugar,soluble protein content,superoxide dismutase activity and root activity of Phoebe container seedlings were higher than that of bare root seedlings.

The New Approach of Expansion Baldwin-Aibassov＇s Rules for Ring-Closing Reaction for d- and f-elements Periodic Table of Elements

The authors have studied the effect of a magnetic field on Baldwin＇s rules. The authors have proposed a new mechanism that takes into account the effect of the angle and energy endo- or exo-cyclization. The authors propose to extend the rule Bouldwin not only for sp^3-, sp^2- and sp- orbits, but and for d^1 - d^10 and f^1 - f^14 elements of I-VIII of the Periodic table.

A Study of the Effects of Family Precepts,Rules and Ethics on Children’s Education During the Tang Dynasty

From the perspectives of the prosperity of the Sui and Tang dynasties,the rise and fall of the aristocrats and the prevalence of the imperial examination,this paper studies the impact of family precepts,rules,and ethics on children’s education.I believe that an important feature of family precepts in the Tang Dynasty was the development of the cultural tradition of poetry and literature study within the family,which promoted virtues like loyalty,filial piety,diligence,frugality and modesty and had a profound influence on future generations.The rise and fall of Tang Dynasty families was closely related to family precepts,rules,ethics,and learning.Famous and respectable families often regarded these traits as important means to maintain the family’s status,which objectively promoted the development of family scholarship and the importance of children’s education in the Tang Dynasty.The concept of learning as a“carry-on treasure”has become a common belief among scholars and has played a positive role in educating Chinese society,enriching our culture,and keeping society in order.

Stability and stabilization of discrete T-S fuzzy time-delay system based on maximal overlapped-rules group

The problems of stability and stabilization for the discrete Takagi-Sugeno（T-S） fuzzy time-delay system are investigated.By constructing a discrete piecewise Lyapunov-Krasovskii function（PLKF） in each maximal overlapped-rules group（MORG）,a new sufficient stability condition for the open-loop discrete T-S fuzzy time-delay system is proposed and proved.Then the systematic design of the fuzzy controller is investigated via the parallel distributed compensation control scheme,and a new stabilization condition for the closed-loop discrete T-S fuzzy time-delay system is proposed.The above two sufficient conditions only require finding common matrices in each MORG.Compared with the common Lyapunov-Krasovskii function（CLKF） approach and the fuzzy Lyapunov-Krasovskii function（FLKF） approach,these proposed sufficient conditions can not only overcome the defect of finding common matrices in the whole feasible region but also largely reduce the number of linear matrix inequalities to be solved.Finally,simulation examples show that the proposed PLKF approach is effective.

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.

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.

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。

A Study of China's Employment Patern

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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.