Proximal Symmetric Non-negative Latent Factor Analysis: A Novel Approach to Highly-Accurate Representation of Undirected Weighted Networks

An Undirected Weighted Network (UWN) is commonly found in big data-related applications. Note that such a network's information connected with its nodes, and edges can be expressed as a Symmetric, High-Dimensional and Incomplete (SHDI) matrix. However, existing models fail in either modeling its intrinsic symmetry or low-data density, resulting in low model scalability or representation learning ability. For addressing this issue, a Proximal Symmetric Nonnegative Latent-factor-analysis (PSNL) model is proposed. It incorporates a proximal term into symmetry-aware and data density-oriented objective function for high representation accuracy. Then an adaptive Alternating Direction Method of Multipliers (ADMM)-based learning scheme is implemented through a Tree-structured of Parzen Estimators (TPE) method for high computational efficiency. Empirical studies on four UWNs demonstrate that PSNL achieves higher accuracy gain than state-of-the-art models, as well as highly competitive computational efficiency

A Dynamic Linear Bias Incorporation Scheme for Nonnegative Latent Factor Analysis

High-Dimensional and Incomplete (HDI) data is commonly encountered in big data-related applications like social network services systems, which are concerning the limited interactions among numerous nodes. Knowledge acquisition from HDI data is a vital issue in the domain of data science due to their embedded rich patterns like node behaviors, where the fundamental task is to perform HDI data representation learning. Nonnegative Latent Factor Analysis (NLFA) models have proven to possess the superiority to address this issue, where a linear bias incorporation (LBI) scheme is important in present the training overshooting and fluctuation, as well as preventing the model from premature convergence. However, existing LBI schemes are all statistic ones where the linear biases are fixed, which significantly restricts the scalability of the resultant NLFA model and results in loss of representation learning ability to HDI data. Motivated by the above discoveries, this paper innovatively presents the dynamic linear bias incorporation (DLBI) scheme. It firstly extends the linear bias vectors into matrices, and then builds a binary weight matrix to switch the active/inactive states of the linear biases. The weight matrix's each entry switches between the binary states dynamically corresponding to the linear bias value variation, thereby establishing the dynamic linear biases for an NLFA model. Empirical studies on three HDI datasets from real applications demonstrate that the proposed DLBI-based NLFA model obtains higher representation accuracy several than state-of-the-art models do, as well as highly-competitive computational efficiency.Comment: arXiv admin note: substantial text overlap with arXiv:2306.03911, arXiv:2302.12122, arXiv:2306.0364

Effects of Norepinephrine and Acetylcholine on the Development of Cultured Leydig Cells in Mice

Few data have suggested how norepinephrine (NE) and acetylcholine (Ach) regulate the development of Leydig cells in mice at prepuberty, except for data indicating endocrine effects. The present study aims to elucidate the roles of NE and Ach on the differentiation and proliferation of Leydig cells. Firstly, the expression of adrenergic receptors and muscarinic acetylcholine receptors in Leydig cells was investigated. It was found that adrenergic receptors (β1AR, β2AR, and α1D) and muscarinic acetylcholine receptors (M1 and M3) mRNA are expressed in adult Leydig cells. Then, the effects of NE and Ach on the differentiation and proliferation of Leydig cells were analyzed. The results showed that NE and Ach at 10 μM significantly increased the number of 3β-hydroxysteroid-dehydrogenase-(3β-HSD-) positive Leydig cells and improved the expression of proliferating cell nuclear antigen (PCNA) in Leydig cells on postnatal day (PD) 15 (P < 0.05). NE and Ach at 10 μM had no impact on the expression of PCNA mRNA (P > 0.05), but reduced the expression of 3β-HSD mRNA in adult Leydig cells and a murine Leydig tumor cell line (MLTC-1) (P < 0.05). Therefore, a conclusion may be reached that NE and Ach participated in stimulating the development of Leydig cells in mice from prepuberty to adult stage

CFD investigation of gas-solids flow in a new fluidized catalyst cooler

In our previous work, a new concept of annular catalyst cooler (ACC) was proposed and validated experimentally, which showed that an internal circulation of solids could be formed by using two gas distributors and both hydrodynamics and heat transfer could be largely improved. The current work simulated detailed hydrodynamics of gas-solids flow to advance our understanding of the ACC by using the two-fluid model. The influences of effective particle diameter dp⁎ and specularity coefficient φ were examined and compared with experimental data. Optimum values of dp⁎ = 170 μm and φ = 0.3 were determined and used in the simulations. Detailed hydrodynamics of gas-solids flow were then obtained, and the influential parameters were examined. The results showed that the proper selection of the ratio of gas velocities and the position of the heat transfer tube were needed to form a stable internal solids circulation in the ACC. The ACC had a combined hydrodynamic feature of up-flow and down-flow catalyst coolers with bigger solids volume fraction and smaller particle resident time, which are beneficial for improving the heat transfer between solids and wall

DEM numerical investigation of wet particle flow behaviors in multiple-spout fluidized beds

Spout fluidized beds are important for industrial processing, and multiple-spout fluidized beds play an important role in chemical reactions. However, particle flow behaviors in multiple-spout fluidized beds are not well known in wet particle systems. In this study, the flow behaviors of particles were investigated in dry and humid multiple-spout fluidized beds using a discrete element method (DEM). The simulated spout fluidized beds are similar to the ones used in the Buijtenen et al.’s experiment (published in Chemical Engineering Science, 2011, 66(11): 2368-2376). In the reference, particle flow behaviors were measured and investigated by PIV and PEPT in multiple spout fluidized beds. In this work, the simulated results are compared with the experimental data in single and double spout fluidized beds from Buijtenen et al., and the time-averaged particle velocities are compared to validate the simulation method. In contrast, simulated results with a liquid content of 1% in the bed showed good agreement with the data in the experimental results with an air relative humidity of 50%. Different liquid contents of the particles were applied to investigate the particle flow behaviors in wet granular systems. The liquid bridge force had a strong influence on the flow behaviors of the particles in the dense region, which resulted in different hydrodynamic characteristics between the dry and wet particles. In addition, the drag force dominated the particle flow behavior in the dry and wet particle systems. Moreover, in a wet granular system, the mass particle fluxes decreased, and the fluctuation of the pressure drops increased with an increasing influence of the liquid bridge force on the particles. Furthermore, with an increasing liquid content, the energy fluctuation of the particles and bubbles weakened gradually with less active motions. A comparison of the hydrodynamic flow behaviors in single-spout and double-spout fluidized beds was carried out as well. Comparisons of the solid circulation rate and the colliding characteristics between single-spout and double-spout fluidized beds were conducted. Particularly, a comparison of the mixing characteristics demonstrated that the particles were mixed more completely in a double-spout fluidized bed. Therefore, the double-spout fluidized bed could provide more adequate space for mass and heat transfer under the same condition. This was important in providing a theory for designing the industrial reactor

Spatial and Temporal Characteristic Analysis of Imbalance Usage in the Hangzhou Public Bicycle System

Calculating the availability of bicycles and racks is a traditional method for detecting imbalance usage in a public bicycle system (PBS). However, for bike-sharing systems in Asian countries, which have compact layouts and larger system scales, an alternative docking station may be found within walking distance. In this paper, we proposed a synthetic and spatial-explicit approach to discover the imbalance usage by using the Hangzhou public bicycle system as an example. A spatial filter was used to remove the false-alarm docking stations and to obtain true imbalance areas of interest (AOI), where the system operation department installs more stations or increases the capacity of existing stations. In addition, sub-nearest neighbor analysis was adopted to determine the average distance between stations, resulting in an average station spacing of 190 m rather than 15.5 m, which can reflect the nonbiased service level of Hangzhou’s public bicycle systems. Our study shows that neighboring stations are taken into account when analyzing PBSs that use a staggered or face-to-face layout, and our method can reduce the number of problematic stations that need to be reallocated by about 92.81%

Effect of thermo hydrogen treatment on lattice defects and microstructure refinement of Ti6Al4V alloy

An investigation of a rolled Ti6Al4V alloy after thermo hydrogen treatment was performed. The effect of hydrogen content on the types and amount of lattice defects, the microstructure refinement after hydrogenation-dehydrogenation processing and the refining mechanisms were studied. The results show that the types of defects are at first vacancies and dislocations, and then they are mainly dislocations with increasing of hydrogen content. The amount of defects increases gradually with increasing of hydrogen content. After thermo hydrogen treatment, the rolled microstructure of Ti6Al4V alloy is refined

Nonlinear optical conductivity of Weyl semimetals in the terahertz regime

We analyze the nonlinear optical properties in Weyl semimetals which result from the intraband and the interband contributions around the Weyl points respectively. Based on the Boltzmann equation and the Floquet method to the Schrödinger equation under the tight-binding model we can calculate any order of nonlinear optical conductivity in the Terahertz regime with the effective chiral Hamiltonian used. We find that the influences of the interband transition and intraband term on the optical properties of the system are opposite each other when increasing frequency and interband transitions dominates the optical responses. The part of the linear conductivity of the system which is contributed from the intraband electric motion increases when the relaxation time reduces and the part of the linear conductivity from the interband transitions increases with the decrease of the temperature. The part of the third harmonic generation which is contributed to the interband transitions is proportional to ω−3 and will be considerable when the frequency become small enough. The nonlinear terms enhance the optical reponses of Weyl semimetals and provide more information about the critical properties