Some remarks on the dynamical conformity of rock joints

A recently developed computerized method for assessing the rock joint coefficients is discussed. The performances of formerly introduced relative similarity indicators, along with the correlation coefficient, are subjected to critical analysis. These relative numerical indicators are replaced by two absolute indicators whose properties better describe surface textures of rock joints. The first absolute indicator results from the Fourier Matrix and evaluates wavy shapes of surfaces. The second absolute indicator quantifies the heights of surface reliefs, and is defined as the root mean square height of the surface outline. The behavior of the newly introduced numerical indicators are investigated by means of the deterministic periodic surface reliefs. The practical application of the new indicators is presented and the convenient performances of both the indicators are documented.

Tri-party deep network representation learning using inductive matrix completion

Most existing network representation learning algorithms focus on network structures for learning.However,network structure is only one kind of view and feature for various networks,and it cannot fully reflect all characteristics of networks.In fact,network vertices usually contain rich text information,which can be well utilized to learn text-enhanced network representations.Meanwhile,Matrix-Forest Index(MFI)has shown its high effectiveness and stability in link prediction tasks compared with other algorithms of link prediction.Both MFI and Inductive Matrix Completion(IMC)are not well applied with algorithmic frameworks of typical representation learning methods.Therefore,we proposed a novel semi-supervised algorithm,tri-party deep network representation learning using inductive matrix completion(TDNR).Based on inductive matrix completion algorithm,TDNR incorporates text features,the link certainty degrees of existing edges and the future link probabilities of non-existing edges into network representations.The experimental results demonstrated that TFNR outperforms other baselines on three real-world datasets.The visualizations of TDNR show that proposed algorithm is more discriminative than other unsupervised approaches.

Gene therapy of liver cancer

The application of gene transfer technologies to the treatment of cancer has led to the development of new experimental approaches like gene directed enzyme/pro- drug therapy (GDEPT), inhibition of oncogenes and restoration of tumor-suppressor genes. In addition, gene therapy has a big impact on other fields like cancer immunotherapy, anti-angiogenic therapy and virotherapy. These strategies are being evaluated for the treatment of primary and metastatic liver cancer and some of them have reached clinical phases. We present a review on the basis and the actual status of gene therapy approaches applied to liver cancer.

Isothermal crystallization in Ce_(70)Ga_6Cu_(24) bulk metallic glass

The isothermal crystallization behaviors in a newly developed CeGaCu bulk metallic glass have been investigated through the classic differential scanning calorimeter （DSC） method. It is found that the apparent activation energy （Ea） strongly depends on the fraction （x） of isothermal crystallization. Johnson-Mehl-Avrami （JMA） formula was used to analyze the mechanism of crystallization and the obtained Avrami exponent （n） was discovered to show an obvious correlation with the crystallization fraction x. With the help of the relation between Ea and n, the nucleation and growth activation energies, En and Eg, were estimated to be 214-304 kJ/mol and 91 kJ/mol, respectively. This result suggests that the main energy barrier against crystallization in the present glass should be the nucleation of nucleates, rather than the growth of crystals. Such a large E, is also believed to be responsible for the good glass forming ability of the CeGaCu alloy.