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Bo Zhou

Publications and source records attributed to Bo Zhou.

At least 289 records · Page 16Linked to original sources
arXiv2018

New trial wave function for nuclear cluster structure of nuclei

A new trial wave function is proposed for nuclear physics, in which an exact solution to the long-standing center-of-mass problem is given. In the new approach, the widths of the single-nucleon Gaussian wave packets and the widths of the relative Gaussian wave functions describing correlations of nucleons or clusters are treated as variables in the explicit intrinsic wave function of the nuclear system. As an example, this new wave function was applied to study the typical ${^{20}{\rm Ne}}$ ($α$+${^{16}{\rm O}}$) cluster system. By removing exactly the spurious center-of-mass effect in a very simple way, the energy curve of ${^{20}{\rm Ne}}$ was obtained by the variational calculations with the width of $α$ cluster, the width of ${^{16}{\rm O}}$ cluster, and the size parameter of the nucleus. They are considered as the three crucial variational variables in describing the ${^{20}{\rm Ne}}$ ($α$+${^{16}{\rm O}}$) cluster system. This shows that the new wave function can be a very interesting new tool for studying many-body and cluster effects in nuclear physics.

nucl-th↗
arXiv2018

Feature Decomposition Based Saliency Detection in Electron Cryo-Tomograms

Electron Cryo-Tomography (ECT) allows 3D visualization of subcellular structures at the submolecular resolution in close to the native state. However, due to the high degree of structural complexity and imaging limits, the automatic segmentation of cellular components from ECT images is very difficult. To complement and speed up existing segmentation methods, it is desirable to develop a generic cell component segmentation method that is 1) not specific to particular types of cellular components, 2) able to segment unknown cellular components, 3) fully unsupervised and does not rely on the availability of training data. As an important step towards this goal, in this paper, we propose a saliency detection method that computes the likelihood that a subregion in a tomogram stands out from the background. Our method consists of four steps: supervoxel over-segmentation, feature extraction, feature matrix decomposition, and computation of saliency. The method produces a distribution map that represents the regions' saliency in tomograms. Our experiments show that our method can successfully label most salient regions detected by a human observer, and able to filter out regions not containing cellular components. Therefore, our method can remove the majority of the background region, and significantly speed up the subsequent processing of segmentation and recognition of cellular components captured by ECT.

q-bio.QM↗
arXiv2018

Model compression for faster structural separation of macromolecules captured by Cellular Electron Cryo-Tomography

Electron Cryo-Tomography (ECT) enables 3D visualization of macromolecule structure inside single cells. Macromolecule classification approaches based on convolutional neural networks (CNN) were developed to separate millions of macromolecules captured from ECT systematically. However, given the fast accumulation of ECT data, it will soon become necessary to use CNN models to efficiently and accurately separate substantially more macromolecules at the prediction stage, which requires additional computational costs. To speed up the prediction, we compress classification models into compact neural networks with little in accuracy for deployment. Specifically, we propose to perform model compression through knowledge distillation. Firstly, a complex teacher network is trained to generate soft labels with better classification feasibility followed by training of customized student networks with simple architectures using the soft label to compress model complexity. Our tests demonstrate that our compressed models significantly reduce the number of parameters and time cost while maintaining similar classification accuracy.

q-bio.QM↗
arXiv2018

Investigation of the 9B nucleus and its cluster-nucleon correlations

In order to study the correlation between clusters and nucleons in light nuclei, we formulate a new superposed THSR wave function which describes both spatial large spreading and cluster-correlated dynamics of valence nucleons. By using the new THSR wave function, the binding energy of 9B is essentially improved comparing with our previous studies. We calculate the excited states of 9B and obtain the energy spectrum of 9B which is consistent with the experimental results, including prediction of the 1/2+ excited state of 9B which is not fixed yet experimentally. We study the proton dynamics in 9B and find that the cluster-proton correlation plays an essential role for the proton dynamics in the ground state of 9B. Further more, we discuss the density distribution of the valence proton with special attention to its tail structure. Finally, the resonance nature of excited states of 9B is illustrated by comparing root-mean-square radii between the ground and excited states.

nucl-th↗
arXiv2017

2$α$+$t$ cluster structure in $^{11}$B

The 2$α+t$ cluster structure in $^{11}$B is investigated by the microscopic generator coordinate method (GCM) with the Brink cluster wave functions. With a proper choice of the parameters of the effective interaction, the calculated energy spectrum shows reasonable agreement with the observed low-lying spectra of both parities. On the basis of the calculated radii, monopole and $B(E2)$ transition strengths, several developed cluster states of $^{11}$B are suggested. For the negative-parity states, in addition to the well-known $3/2_3^-$ cluster state, the $1/2_2^-$ and $5/2_3^-$ states are also proposed as the well-developed cluster states. For the positive-parity states, it is found that many states around the 2$α+t$ threshold show the feature of developed clusters. In particular, the $1/2_2^+$ state is found to have a linear-chain-like structure, which is consistent with the previous antisymmetrized molecular dynamics calculation, but contradicts to the orthogonality condition model calculation. It is also found that many of these positive-parity cluster candidates have the non-negligible isoscalar dipole transition strengths, which require the experimental confirmation.

nucl-th↗
arXiv2017

Simultaneously Learning Neighborship and Projection Matrix for Supervised Dimensionality Reduction

Explicitly or implicitly, most of dimensionality reduction methods need to determine which samples are neighbors and the similarity between the neighbors in the original highdimensional space. The projection matrix is then learned on the assumption that the neighborhood information (e.g., the similarity) is known and fixed prior to learning. However, it is difficult to precisely measure the intrinsic similarity of samples in high-dimensional space because of the curse of dimensionality. Consequently, the neighbors selected according to such similarity might and the projection matrix obtained according to such similarity and neighbors are not optimal in the sense of classification and generalization. To overcome the drawbacks, in this paper we propose to let the similarity and neighbors be variables and model them in low-dimensional space. Both the optimal similarity and projection matrix are obtained by minimizing a unified objective function. Nonnegative and sum-to-one constraints on the similarity are adopted. Instead of empirically setting the regularization parameter, we treat it as a variable to be optimized. It is interesting that the optimal regularization parameter is adaptive to the neighbors in low-dimensional space and has intuitive meaning. Experimental results on the YALE B, COIL-100, and MNIST datasets demonstrate the effectiveness of the proposed method.

cs.CV↗
arXiv2017

The distance Laplacian spectral radius of unicyclic graphs

For a connected graph $G$, the distance Laplacian spectral radius of $G$ is the spectral radius of its distance Laplacian matrix $\mathcal{L}(G)$ defined as $\mathcal{L}(G)=Tr(G)-D(G)$, where $Tr(G)$ is a diagonal matrix of vertex transmissions of $G$ and $D(G)$ is the distance matrix of $G$. In this paper, we determine the unique graphs with maximum distance Laplacian spectral radius among unicyclic graphs.

math.CO↗
arXiv2017

Transforming Sensor Data to the Image Domain for Deep Learning - an Application to Footstep Detection

Convolutional Neural Networks (CNNs) have become the state-of-the-art in various computer vision tasks, but they are still premature for most sensor data, especially in pervasive and wearable computing. A major reason for this is the limited amount of annotated training data. In this paper, we propose the idea of leveraging the discriminative power of pre-trained deep CNNs on 2-dimensional sensor data by transforming the sensor modality to the visual domain. By three proposed strategies, 2D sensor output is converted into pressure distribution imageries. Then we utilize a pre-trained CNN for transfer learning on the converted imagery data. We evaluate our method on a gait dataset of floor surface pressure mapping. We obtain a classification accuracy of 87.66%, which outperforms the conventional machine learning methods by over 10%.

cs.CV↗
arXiv2017

New cluster approach on properties of 8-11Be isotopes with isospin-dependent spin-orbit potential

The nonlocalized clustering approach is generalized to 8-11Be isotopes with isospin dependent spin-orbit potential. A new form of the Tohsaki-Horiuchi-Schuck-Röpke (THSR) wave function is introduced to provide a correct description for the σ-binding neutron in 11Be. Systematic calculations for 8-11Be isotopes are performed and results fit well with experimental values. The low energy spectrum of 11Be is also obtained, especially the correct spin-parity 1/2+ is reproduced for the intruder ground state. The exotic neutron halo structure of 11Be is studied by calculations of root-mean-square radii and density distribution. We obtain a large spatial distribution for the last valence neutron of 11Be, which fits the phenomenological extracted value from experimental data. The spectroscopic factor is also calculated and discussed for the 1/2+ ground state of 11Be.

nucl-th↗
arXiv2017

Alpha Cluster Formation and Decay in Quartetting Wave Function Approach

We present a microscopic calculation of alpha-cluster formation in heavy nuclei by using the quartetting wave function approach. The interaction of the quartet with the core nucleus is taken in local density approximation. The alpha-cluster formation is found to be particularly sensitive to the interplay of the mean field felt by the alpha-cluster and the Pauli blocking as a consequence of antisymmetrization. The striking feature of alpha-cluster formation probability across the major shell closures of 82 protons and 126 neutrons is reproduced. The shell (or subshell) effects on the alpha-cluster formation in superheavy nuclei are also analyzed.

nucl-th↗
arXiv2017

Anomalous behavior of membrane fluidity caused by copper-copper bond coupled phospholipids

Membrane fluidity, well-known to be essential for cell functions, is obviously affected by copper. However, the underlying mechanism is still far from being understood, especially on the atomic level. Here, we unexpectedly observed that a decrease in phospholipid (PL) bilayer fluidity caused by Cu2+ was much more significant than those induced by Zn2+ and Ca2+, while a comparable reduction occurred in the last two ions. This finding clearly disagrees with the placement in the periodic table of Cu just next to Zn and far from Ca. The physical nature was revealed to be a special attraction between Cu+ cations, which can induce a motif forming of two phospholipids coupled by Cu-Cu bond (PL-diCu-PL). Namely, upon Cu2+ ion binding to a negatively charged phosphate group of lipid, Cu2+ was reduced to Cu+. The special attraction of the cations then caused one Cu+ ion simultaneously binding to two lipids and another Cu+, resulting in the formation of PL-diCu-PL structure. In contrast, this attraction cannot occur in the cases of Zn and Ca ions due to their electron structure. Remarkably, besides lipids, the phosphate group widely exists in other biological molecules, including DNA, RNA, ADP and ATP, which would also induce the similar structure of Cu ions with the molecules. Our findings thus provide a new view for understanding the biological functions of copper and the mechanism underlying copper-related diseases.

physics.bio-ph↗
arXiv2017

Validation of Internal Meters of Mobile Android Devices

In this paper we outline our results for validating the precision of the internal power meters of smart-phones under different workloads. We compare its results with an external power meter. This is the first step towards creating customized energy models on the fly and towards optimizing battery efficiency using genetic program improvements. Our experimental results indicate that the internal meters are sufficiently precise when large enough time windows are considered. This is part of our work on the "dreaming smart-phone". For a technical demonstration please watch our videos https://www.youtube.com/watch?v=xeeFz2GLFdU and https://www.youtube.com/watch?v=C7WHoLW1KYw.

cs.OH↗
arXiv2016

ARPES study of the epitaxially grown topological crystalline insulator SnTe(111)

SnTe is a prototypical topological crystalline insulator, in which the gapless surface state is protected by a crystal symmetry. The hallmark of the topological properties in SnTe is the Dirac cones projected to the surfaces with mirror symmetry, stemming from the band inversion near the L points of its bulk Brillouin zone, which can be measured by angle-resolved photoemission. We have obtained the (111) surface of SnTe film by molecular beam epitaxy on BaF2(111) substrate. Photon-energy-dependence of in situ angle-resolved photoemission, covering multiple Brillouin zones in the direction perpendicular tothe (111) surface, demonstrate the projected Dirac cones at the Gamma_bar and M_bar points of the surface Brillouinzone. In addition, we observe a Dirac-cone-like band structure at the Gamma point of the bulk Brillouin zone,whose Dirac energy is largely different from those at the Gamma_bar and M_bar points.

cond-mat.mtrl-sci↗
arXiv2016

Breathing-like excited state of the Hoyle state in ${^{12}{\rm C}}$

The existence of the $0_3^+$ and $0_4^+$ states around 10 MeV excitation energy in ${^{12}{\rm C}}$ is confirmed by a fully microscopic 3$α$ cluster model. Firstly, a GCM (generator coordinate method) calculation is performed by superposing optimized 2$α$+$α$ THSR (Tohsaki-Horiuchi-Schuck-Röpke) wave functions with the radius-constraint method. The obtained two excited $0^+$ states above the Hoyle state are consistent with the recently observed states by experiment. Secondly, a variational calculation using the single 2$α$+$α$ THSR wave function orthogonalized to the ground and Hoyle states is made and it also supports the existence of the $0_3^+$ state obtained by the GCM calculation. The analysis of the obtained $0_3^+$ state is made by studying its 2$α$-$α$ reduced width amplitude, its 2$α$ correlation function, and the large monopole matrix element between this state and the Hoyle state, which shows that this $0_3^+$ state is a breathing-like excited state of the Hoyle state. This character of the $0_3^+$ state is very different from the $0_4^+$ state which seems to have a bent-arm 3$α$ structure.

nucl-th↗
arXiv2016

Stochastic Content-Centric Multicast Scheduling for Cache-Enabled Heterogeneous Cellular Networks

Caching at small base stations (SBSs) has demonstrated significant benefits in alleviating the backhaul requirement in heterogeneous cellular networks (HetNets). While many existing works focus on what contents to cache at each SBS, an equally important problem is what contents to deliver so as to satisfy dynamic user demands given the cache status. In this paper, we study optimal content delivery in cache-enabled HetNets by taking into account the inherent multicast capability of wireless medium. We consider stochastic content multicast scheduling to jointly minimize the average network delay and power costs under a multiple access constraint. We establish a content-centric request queue model and formulate this stochastic optimization problem as an infinite horizon average cost Markov decision process (MDP). By using \emph{relative value iteration} and special properties of the request queue dynamics, we characterize some properties of the value function of the MDP. Based on these properties, we show that the optimal multicast scheduling policy is of threshold type. Then, we propose a structure-aware optimal algorithm to obtain the optimal policy. We also propose a low-complexity suboptimal policy, which possesses similar structural properties to the optimal policy, and develop a low-complexity algorithm to obtain this policy.

cs.IT↗
arXiv2016

Electronic Structure, Surface Doping, and Optical Response in Epitaxial WSe2 Thin Films

High quality WSe2 films have been grown on bilayer graphene (BLG) with layer-by-layer control of thickness using molecular beam epitaxy (MBE). The combination of angle-resolved photoemission (ARPES), scanning tunneling microscopy/spectroscopy (STM/STS), and optical absorption measurements reveal the atomic and electronic structures evolution and optical response of WSe2/BLG. We observe that a bilayer of WSe2 is a direct bandgap semiconductor, when integrated in a BLG-based heterostructure, thus shifting the direct-indirect band gap crossover to trilayer WSe2. In the monolayer limit, WSe2 shows a spin-splitting of 475 meV in the valence band at the K point, the largest value observed among all the MX2 (M = Mo, W; X = S, Se) materials. The exciton binding energy of monolayer-WSe2/BLG is found to be 0.21 eV, a value that is orders of magnitude larger than that of conventional 3D semiconductors, yet small as compared to other 2D transition metal dichalcogennides (TMDCs) semiconductors. Finally, our finding regarding the overall modification of the electronic structure by an alkali metal surface electron doping opens a route to further control the electronic properties of TMDCs.

cond-mat.mtrl-sci↗
arXiv2016

Caching Incentive Design in Wireless D2D Networks: A Stackelberg Game Approach

Caching in wireless device-to-device (D2D) networks can be utilized to offload data traffic during peak times. However, the design of incentive mechanisms is challenging due to the heterogeneous preference and selfish nature of user terminals (UTs). In this paper, we propose an incentive mechanism in which the base station (BS) rewards those UTs that share contents with others using D2D communication. We study the cost minimization problem for the BS and the utility maximization problem for each UT. In particular, the BS determines the rewarding policy to minimize his total cost, while each UT aims to maximize his utility by choosing his caching policy. We formulate the conflict among UTs and the tension between the BS and the UTs as a Stackelberg game. We show the existence of the equilibrium and propose an iterative gradient algorithm (IGA) to obtain the Stackelberg Equilibrium. Extensive simulations are carried out to evaluate the performance of the proposed caching scheme and comparisons are drawn with several baseline caching schemes with no incentives. Numerical results show that the caching scheme under our incentive mechanism outperforms other schemes in terms of the BS serving cost and the utilities of the UTs.

cs.IT↗