Role of Selective Interaction in Wealth Distribution

In our simplified description‘wealth’is money(m).A kinetic theory of a gas like model of money is investigated where two agents interact(trade)selectively and exchange some amount of money between them so that sum of their money is unchanged and thus total money of all the agents remains conserved.The probability distributions of individual money(P(m)vs.m)is seen to be influenced by certain ways of selective interactions.The distributions shift away from Boltzmann-Gibbs like the exponential distribution,and in some cases distributions emerge with power law tails known as Pareto’s law(P(m)/m−(1+®)).The power law is also observed in some other closely related conserved and discrete models.A discussion is provided with numerical support to obtain insight into the emergence of power laws in such models.

Teleportation of N-qubit W State without Bell-State Measurement via Selective Resonant Interaction in Cavity QED

We present a scheme in which the N-atom W state is teleported by employing the selective interactionof a cavity field with a driven three-level atom in the A configuration and detecting a single atom in one of the groundstates.The long-lived W state is teleported from atom A to atom B when the atoms B and A are sent through acavity successively and atom A is then detected.The advantage is that the present one does not involve the Bell-statemeasurement and is robust against the atomic spontaneous emission.

Synergetic catalysis of ceria and titania for selective reduction of NO

The promotional effect of the interaction between titania and ceria on the catalytic performance for selective reduction of NO was studied.The catalysts,CeO 2,TiO 2,CeO 2 /TiO 2 and Ti x Ce 1-x O 2,were synthesized and tested in NH 3-Selective catalytic reduction（SCR） of NO,and the samples were characterized by the Brunaller,Emmett and Teller（BET absorbed gas N 2）,X-ray diffraction（XRD）,high resolution transmission electron microscopy（HR-TEM）,and temperature programmed desorption（TPD NH 3） techniques.The improvement mechanism of the interaction between the titania and ceria had been explored and discussed from two aspects of micro-structure and surface acidity.The interaction between the titania and ceria greatly improved the catalytic activity but had little effect on the active temperature.It was first reported that the acid amount determined the catalytic activity and the acid strength determined the active temperature for NH 3-SCR of NO.

Multitarget tracking control algorithm under local information selection interaction mechanism

This study focuses on the problem of multitarget tracking.To address the existing problems of current tracking algorithms,as manifested by the time consumption of subgroup separation and the uneven group size of unmanned aerial vehicles(UAVs)for target tracking,a multitarget tracking control algorithm under local information selection interaction is proposed.First,on the basis of location,number,and perceived target information of neighboring UAVs,a temporary leader selection strategy is designed to realize the local follow-up movement of UAVs when the UAVs cannot fully perceive the target.Second,in combination with the basic rules of cluster movement and target information perception factors,distributed control equations are designed to achieve a rapid gathering of UAVs and consistent tracking of multiple targets.Lastly,the simulation experiments are conducted in two-and three-dimensional spaces.Under a certain number of UAVs,clustering speed of the proposed algorithm is less than 3 s,and the equal probability of the UAV subgroup size after group separation is over 78%.

A Feature Selection Method for Prediction Essential Protein

Essential proteins are vital to the survival of a cell. There are various features related to the essentiality of proteins, such as biological and topological features. Many computational methods have been developed to identify essential proteins by using these features. However, it is still a big challenge to design an effective method that is able to select suitable features and integrate them to predict essential proteins. In this work, we first collect 26 features, and use SVM-RFE to select some of them to create a feature space for predicting essential proteins, and then remove the features that share the biological meaning with other features in the feature space according to their Pearson Correlation Coefficients（PCC）. The experiments are carried out on S. cerevisiae data. Six features are determined as the best subset of features. To assess the prediction performance of our method, we further compare it with some machine learning methods, such as SVM, Naive Bayes, Bayes Network, and NBTree when inputting the different number of features. The results show that those methods using the 6 features outperform that using other features, which confirms the effectiveness of our feature selection method for essential protein prediction.

AFExplorer:Visual analysis and interactive selection of audio features

Acoustic quality detection is vital in the manufactured products quality control field since it represents the conditions of machines or products.Recent work employed machine learning models in manufactured audio data to detect anomalous patterns.A major challenge is how to select applicable audio features to meliorate model’s accuracy and precision.To relax this challenge,we extract and analyze three audio feature types including Time Domain Feature,Frequency Domain Feature,and Cepstrum Feature to help identify the potential linear and non-linear relationships.In addition,we design a visual analysis system,namely AFExplorer,to assist data scientists in extracting audio features and selecting potential feature combinations.AFExplorer integrates four main views to present detailed distribution and relevance of the audio features,which helps users observe the impact of features visually in the feature selection.We perform the case study with AFExplore according to the ToyADMOS and MIMII Dataset to demonstrate the usability and effectiveness of the proposed system.

Radial deformation of single-walled carbon nanotubes on quartz substrates and the resultant anomalous diameter-dependent reaction selectivity

Owing to the unique conjugated structure, the chemical-reaction selectivity of single-walled carbon nanotubes （SWNTs） has attracted great attention. By utilizing the radial deformation of SWNTs caused by the strong interactions with the quartz lattice, we achieve an anomalous diameter-dependent reaction selectivity of quartz lattice-oriented SWNTs in treatment with iodine vapor; this is distinctly different from the widely reported and well accepted higher reaction activity in small-diameter tubes compared to large-diameter tubes. The radial deformation of SWNTs on quartz substrate is verified by detailed Raman spectroscopy and mappings in both G-band and radial breathing mode. Due to the strong interaction between SWNTs and the quartz lattice, large-diameter tubes present a larger degree of radial deformation and more delocalized partial electrons are distributed at certain sidewall sites with high local curvature. It is thus easier for the carbon--carbon bonds at these high-curvature sites on large-diameter tubes to break down during reaction. This anomalous reaction activity offers a novel approach for selective removal of small-band^aD large-diameter tubes.