Terminating Cycles for Iterated Difference Values of Four—Digit Integers

1. Introduction Since D. R. Kaprekar discoverd the interesting property of the number 6174 an interesting mathematical model has been developed:

An Analysis of Value Differences in English and Chinese Idioms from the Perspective of Intercultural Communication

Idioms are the essence and gems of human wisdom and an important carrier of national culture. As a special form of language, they play an important role in intercultural communication. Due to the uniqueness of each culture, English and Chinese idioms are different in many aspects, values included. The present paper attempts to analyze the different values in English and Chinese idioms from three aspects: dependence vs independence, past-time orientation vs future-time orientation, and harmony vs competition. And the authors hope that it will be of some practical significance in people's intercultural communication.

ON WELL-CONDITIONED BOUNDARY VALUE PROBLEMS FOR SYSTEMS OF SECOND ORDER DIFFERENCE EQUATIONS

In this paper well-conditioning of boundary value problems for systems of second order difference equa-tions is studied.First,a sufficient condition for the existence of a unique bounded solution (for large enough number of steps) of an associated homogeneous system is given.Finally,a sufficient condition for well-condi-tioning,intrinsically related to the problem data is proposed.

Effect of Cu and Ni on Growth, Mineral Uptake,Photosynthesis and Enzyme Activities of Chlorella vulgaris at Different pH Values

A pH dependent reduction in growth, Pigment, ATP content, O,' evolution, carbonfixation, Photosynthetic electron transport system, nutrient uptake (NO,' and NH4+),nitrate reductase, and ATPase activities and increase in K+ emux of Chlorella vulgaris wasnoticed following supplementation of Cu and Ni to the culture medium. PS II was foundto be more sensitive to both pH and metals than PS I. Though, nitrate reductase (NR) wasmore sensitive to both PH and metals, the ATPase was however, more sensitive t0 metalsbut less sensitive to acidic pH. Acid PH was found to dst the nutrient (NO,' and NH4+)uptake and nitrate reductase in a non-competitive manner. The inhibition Pnduced by thetest metals alone was of noncompetitive type for NO3' uptake, nitrate reductase andATPase and competitive for NH'+ uptake. Acidity not only inhibited the metabolicvariables directly but also through facilitated uptake of metals and increased membranepermeability. A very low sensitivity of ATPase to acidic pH seems to be resgnsible forthe survival of algae in acid environment.

Physical background on estimating bvalue

The G R relation lg N=a-bM( 1954)is an empirical formula used widely in the seismicity research. But the linearity of b curves has great difference in different time and space domains. An interested question in this paper is that in how large a space time strength domain the b value has certain physical connotation. This study told us that we can get optimal statistical results of b value in those space time domains which can develop correspondent strong shocks with magnitude interval( M S≥8.5, 8.0≤ M S<8.5, 7.0≤ M S<8.0). Thus, the possible seismogenic areas in which strong shocks with different magnitude intervals develop can be inferred in different regions of the mainland of China. Finally, some new problems are proposed, such as the delimitation of seismic province, the seismicity parameter determination in seismic hazard analysis and in earthquake predictions by using b value.

Naive Bayes for value difference metric

The value difference metric （VDM） is one of the best-known and widely used distance functions for nominal attributes. This work applies the instance weighting technique to improve VDM. An instance weighted value difference met- ric （IWVDM） is proposed here. Different from prior work, IWVDM uses naive Bayes （NB） to find weights for train- ing instances. Because early work has shown that there is a close relationship between VDM and NB, some work on NB can be applied to VDM. The weight of a training instance x, that belongs to the class c, is assigned according to the dif- ference between the estimated conditional probability P（c／x） by NB and the true conditional probability P（c／x）, and the weight is adjusted iteratively. Compared with previous work, IWVDM has the advantage of reducing the time complex- ity of the process of finding weights, and simultaneously im- proving the performance of VDM. Experimental results on 36 UCI datasets validate the effectiveness of IWVDM.

Harmonic dissipative soliton resonance pulses in a fiber ring laser at different values of anomalous dispersion

The pulse dynamics of harmonic mode-locking in a dissipative soliton resonance(DSR) region in an erbiumdoped fiber ring laser is investigated at different values of anomalous dispersion. The fiber laser is mode-locked by a nonlinear polarization rotation technique. By inserting 0–200 m anomalous dispersion single-mode fiber in the laser cavity, the cavity length is changed from 17.3 to 217.3 m, and the corresponding dispersion of the cavity ranges from -0.27 to-4.67 ps^2. The observed results show that the tuning range of repetition rate under a harmonic DSR condition is highly influenced by the cavity dispersion. Furthermore, it is found that, by automatically adjusting their harmonic orders, the lasers can work at certain values of repetition rate, which are independent of the cavity length and dispersion. The pulses at the same repetition rate in different laser configurations have similar properties, demonstrating that each achievable repetition rate represents an operation regime of harmonic DSR lasers.

Adapt Bagging to Nearest Neighbor Classifiers

It is well-known that in order to build a strong ensemble, the component learners should be with high diversity as well as high accuracy. If perturbing the training set can cause significant changes in the component learners constructed, then Bagging can effectively improve accuracy. However, for stable learners such as nearest neighbor classifiers, perturbing the training set can hardly produce diverse component learners, therefore Bagging does not work well. This paper adapts Bagging to nearest neighbor classifiers through injecting randomness to distance metrics. In constructing the component learners, both the training set and the distance metric employed for identifying the neighbors are perturbed. A large scale empirical study reported in this paper shows that the proposed BagInRand algorithm can effectively improve the accuracy of nearest neighbor classifiers.