RoRePo: Detecting the role information and relative position information for contexts in multi-turn dialogue generation

In multi-turn dialogue generation, dialogue contexts have been shown to have an important influence on the reasoning of the next round of dialogue. A multi-turn dialogue between two people should be able to give a reasonable response according to the relevant context. However, the widely used hierarchical recurrent encoder-decoder model and the latest model that detecting the relevant contexts with self-attention are facing the same problem. Their given response doesn’t match the identity of the current speaker, which we call it role ambiguity. In this paper, we propose a new model, named RoRePo, to tackle this problem by detecting the role information and relative position information. Firstly, as a part of the decoder input, we add a role embedding to identity different speakers. Secondly, we incorporate self-attention mechanism with relative position representation to dialogue context understanding. Besides, the design of our model architecture considers the influence of latent variables in generating more diverse responses. Experimental results of our evaluations on the DailyDialog and DSTC7_AVSD datasets show that our proposed model advances in multi-turn dialogue generation.

Outgrowth of quasi pure states in isolated coupled-harmonic-oscillator

Isolated coupled-harmonic-oscillator here is the system of two distinguishable particles coupled with a harmonic oscillator interaction potential. Each particle stays in a mixed state due to entanglement. However, in center-of-mass reference frame, we obtain quasi wavefunction of the first particle expressing quasi pure state by replacing the second coordinate in the total wavefunction. We discuss the similar systems with the first particle and the potential being same and the second mass changing from micro to macro one. Measured by fidelity and coherence, the quasi pure state approaches to the pure state of a usual harmonic oscillator with same mass and similar potential. It conversely shows that the latter purely superposed state in position representation and its coherence originate from those of the first particle, which are related with some neglected macro object and the interaction between them. The current results provide a possible clue to new insights into quantum states.

Reformulation of Bohmian mechanics

Bohmian mechanics as formulated originally in 1952, has been useful in the implementation of numerical methods applied to quantum mechanics. The scientific community though has had ever since a critical thought about it. Therefore, there are still points to be clarified and rectified. The two main problems are basically: Bohmian mechanics gives a privilege role to the position representation. Secondly, the current interpretation of Bohmian trajectories has been recently proven wrong. In this context, in Chapter 2, new complex Bohmian quantities are defined; so that they allow the capacity to formulate Bohmian mechanics in any arbitrary continuous representation, for instance, the momentum representation. This Chapter is fully based on two articles, regarding the proposed complex Bohmian formulation and its extension into momentum space. Chapter 3 deals with a redefinition and reinterpretation of the Bohmian trajectories from the handling of the continuity equation, this is done without any need of additional postulates or interpretations. Also, it is proved that Bohmian mechanics is actually more than a projective aspect of the Wigner function. As a third point, Chapter 4 presents a sytematic treatment of the hydrodynamic scheme of Bohmian mechanics. Then, a brief summary of the transport equations in Bohmian mechanics is done. Next, a unified hydrodynamic treatment is found for the Bohmian mechanics. This treatment is useful to sketch, a Bohmian treatment to efficiently find the steady value of the transmission integral. In Chapter 5 conclusions of this thesis are drawn.

DBP-PSSM: Combination of evolutionary profiles with the XGBoost algorithm to improve the identification of DNA-binding proteins

Aim and Objective:: Given the rapidly increasing number of molecular biology data available, computational methods of low complexity are necessary to infer protein structure, function, and evolution. Method:: In the work, we proposed a novel mthod, FermatS, which based on the global position information and local position representation from the curve and normalized moments of inertia, respectively, to extract features information of protein sequences. Furthermore, we use the generated features by FermatS method to analyze the similarity/dissimilarity of nine ND5 proteins and establish the prediction model of DNA-binding proteins based on logistic regression with 5-fold crossvalidation. Results:: In the similarity/dissimilarity analysis of nine ND5 proteins, the results are consistent with evolutionary theory. Moreover, this method can effectively predict the DNA-binding proteins in realistic situations. Conclusion:: The findings demonstrate that the proposed method is effective for comparing, recognizing and predicting protein sequences. The main code and datasets can download from https://github.com/GaoYa1122/FermatS.