Collaborative Distribution Alignment for 2D image-based 3D shape retrieval

Retrieving 3D shapes with 2D images has become a popular research area nowadays, and a great deal of work has been devoted to reducing the discrepancy between 3D shapes and 2D images to improve retrieval performance. However, most approaches ignore the semantic information and decision boundaries of the two domains, and cannot achieve both domain alignment and category alignment in one module. In this paper, a novel Collaborative Distribution Alignment (CDA) model is developed to address the above existing challenges. Specifically, we first adopt a dual-stream CNN, following a similarity guided constraint module, to generate discriminative embeddings for input 2D images and 3D shapes (described as multiple views). Subsequently, we explicitly introduce a joint domain-class alignment module to dynamically learn a class-discriminative and domain-agnostic feature space, which can narrow the distance between 2D image and 3D shape instances of the same underlying category, while pushing apart the instances from different categories. Furthermore, we apply a decision boundary refinement module to avoid generating class-ambiguity embeddings by dynamically adjusting inconsistencies between two discriminators. Extensive experiments and evaluations on two challenging benchmarks, MI3DOR and MI3DOR-2, demonstrate the superiority of the proposed CDA method for 2D image-based 3D shape retrieval task.     

Double pyrovanadates CaMgV2O7: Formation mechanism,phase structure,and thermodynamic properties

A double pyrovanadate CaMgV₂O₇ sample was synthesized via a facile solid-state route under an air atmosphere. The nonequilibrium formation pathways of the CaMgV₂O₇ were investigated via powder X-ray diffraction. A multistep reactions path (metavanadates–pyrovanadates–double pyrovanadate CaMgV₂O₇) was proposed to describe the formation of the CaMgV₂O₇ considering the thermodynamic and kinetic factors. The cell unit parameters of the CaMgV₂O₇ sample indicated the crystallization according to a monoclinic system with space group P12/c1(14), and the lattice parameters of a = 6.756 Å, b = 14.495 Å, c = 11.253 Å, β = 99.12, and V = 108.806 Å³. X-ray photoelectron spectroscopy also confirmed the +5 oxidation state vanadium in CaMgV₂O₇. The endothermic effects at 1033 and 1143 K were related to the incongruent melting and liquidus temperatures of CaMgV₂O₇, respectively. The comprehensive thermodynamic properties of CaMgV₂O₇ were established in both low- and high-temperature regions, utilizing a physical property measurement system and multi-high-temperature calorimetry (96 lines). The heat capacity (200 J mol K⁻¹) and entropy (198 J mol K⁻¹) at 298.15 K were computed based on the low-temperature heat capacity values, and the enthalpy of formation at 298.15 K was also estimated. The fitted high-temperature capacity can be used to obtain the changes in the enthalpy, entropy, and Gibbs free energy. This study is part of building a reliable thermodynamic database of the CaO–MgO–V₂O₅ system.     

Isostructural phase transition (IPT) in CaMoO4 with Scheelite structure

The ceramic compound CaMoO₄ is synthesized via a solid-state reaction technique. Rietveld refinement studies were done on the powder X-ray diffraction data of CaMoO₄ and revealed that the compound is crystallized in the tetragonal Scheelite structure with I4₁/a space group. The differential scanning calorimetry (DSC) studies on CaMoO₄ divulged an anomaly around 440 °C. This anomaly is further probed using the temperature-dependent Raman and dielectric spectroscopic measurements and are corroborating with the results obtained from DSC. A detailed investigation on the temperature-dependent Raman spectroscopic data revealed that the A_1g mode of CaMoO₄ showed a soft phonon behavior up to the phase transition temperature. It is observed that the A_1g mode displayed phonon hardening behavior with further increasing the temperature. The anomaly is attributed to an isostructural phase transition (IPT), a rarely observed phenomenon in the compounds with Scheelite structure. The IPT in CaMoO₄ is elucidated with a phonon softening mechanism.     

基于卷积神经网络的5G蜂窝网络无线定位方法

5G蜂窝网络发展迅猛，其覆盖面积将逐渐增大，因此使用5G蜂窝网络进行定位是有研究潜力的研究方向。本文提出一种新的深度学习技术来实现高效、高精度和低占用的定位，以代替传统指纹定位过程中繁重的指纹库生成以及距离计算。该方法建立了一个特殊的卷积神经网络，并根据5G天线信号的接收信号强度指示、相位和到达角等特征量，选择合适的输入数据格式构造样本组建训练集，对该卷积神经网络进行训练。训练得到的卷积神经网络可以替代指纹定位中的庞大指纹库，非常有利于直接在5G移动设备端实现定位。虽然卷积神经网络在训练过程中需要大量时间，但在训练完毕后直接进行分类定位的速度非常快，可以保障定位实现的实时性。本文所实现的卷积神经网络权重与偏置所占内存不到0.5 MB，且能够在实际应用环境中以95%的定位准确率以及0.1 m的平均定位精度实现高精度定位。     

Thermal properties of hierarchical YSZ and LZO ceramic microspheres with multi-scaled voids investigated by using theoretical,experimental and simulation methods

Heat transfer within ceramic feedstock powders is still unclear, which impedes optimization of the thermal and mechanical properties of the thermal sprayed coatings. The microspheres (yttria-stabilized zirconia YSZ and lanthanum zirconate LZO) were prepared via the electro-spraying assisted phase inversion method (ESP). The thermal properties of the two ESP microspheres and a commercial hollow spherical powder (HOSP) were investigated by using theoretical, experimental, and simulation methods. Thermal conductivity of the single microsphere was estimated via a novel nest model that was derived from the Maxwell-Eucken 1 and the EMT model. Thermal conductivity of a single YSZ/LZO-ESP microsphere prepared at 1100–1200 °C was within 0.36–0.75 W/m K, which was ～ 20 % lower than that of a single YSZ-HOSP microsphere with a similar porosity. Heat flux simulation showed that high tortuosity around the multi-scaled voids of the ESP microsphere led to a more efficient decrease in thermal conductivity compared with total porosity.     

Revealing active species of CePO4 catalyst for selective catalytic reduction of NOx with NH3

Revealing the active species of the catalyst is conducive to the design of more efficient catalyst. Herein, we tried to demonstrate the roles of amorphous and crystalline structures on CePO₄ catalyst during selective catalytic reduction (SCR) of NO_x by NH₃. Higher calcination temperature promotes the transfer of amorphous structure to crystalline structure on the surface of CePO₄. Both amorphous and crystalline CePO₄ species on CePO-X samples can provide acid sites for NH₃ adsorption, but the former can provide more acid sites. The superior redox property of surface amorphous CePO₄ species contributes to its high NH₃-SCR activity at low temperature, but it also leads to the decrease of high temperature (>350 °C) NH₃-SCR activity due to the oxidation of NH₃. In contrast, crystalline CePO₄ species shows high activity only at high temperature because of its poor redox property. Therefore, it can be inferred that amorphous and crystalline structures on CePO₄ catalyst can be the efficient active species of NH₃-SCR at low and high temperature, respectively.     

In-situ measurement of mineral phase transition and kinetics in roasting process of Bayan Obo mixed rare earth concentrate by sodium carbonate

In this study, the Bayan Obo rare earth concentrates mixed with Na₂CO₃ were used for roasting research. The phase change process of each firing stage was analyzed. The kinetic mechanism model of the continuous heating process was calculated. This study aims to recover valuable elements and optimize the production process to provide a certain theoretical basis. Using X-ray diffraction (XRD), Fourier infrared spectroscopy, scanning electron microscopy with energy dispersive spectrometry, the reaction process and the existence of mineral phases were analyzed. The variable temperature XRD and thermogravimetric method were used to calculate the roasting kinetics. The phase transition results show that carbonate-like substances first decompose into fine mineral particles, and CaO, MgO, and SiO₂ react to form silicates, causing hardening. Further, REPO₄ and NaF can directly generate CeF₃ and CeF₄ at high temperatures, and a part of CeF₄ and NaF forms a solid solution substance Na₃CeF₇. Rare earth oxides calcined at a high temperature of 750 °C were separated to produce Ce_0.6Nd_0.4O_1.8, Ce₄O₇, and LaPrO_3+x. Then, BaSO₄, Na₂CO₃, and Fe₂O₃ react to form barium ferrite BaFe₁₂O₁₉; the kinetic calculation results show that during the continuous heating process, the apparent activation energy E reaches the minimum in the entire reaction stage in the temperature range of 440–524 °C, and the reaction order n reaches the maximum, which indicates that the decomposition product REFO significantly impacts the reaction system and reduces the activation energy. The mechanism function is F(α) = [?ln (1?α)]^1/3. The reaction order n reaches the minimum in the temperature range of 680–757 °C, and the apparent activation energy E is large. The difficulty of the reaction increases during the final stage. The reaction mechanism function is F(α) = [1?(1?α)^1/3]². Observing the entire reaction stage, the step of controlling the reaction rate changes from random nucleation to three-dimensional diffusion (spherical symmetry).     

A Tradeoff Between Accuracy and Speed for K-Means Seed Determination

With a sharp increase in the information volume, analyzing and retrieving this vast data volume is much more essential than ever. One of the main techniques that would be beneficial in this regard is called the Clustering method. Clustering aims to classify objects so that all objects within a cluster have similar features while other objects in different clusters are as distinct as possible. One of the most widely used clustering algorithms with the well and approved performance in different applications is the k-means algorithm. The main problem of the k-means algorithm is its performance which can be directly affected by the selection in the primary clusters. Lack of attention to this crucial issue has consequences such as creating empty clusters and decreasing the convergence time. Besides, the selection of appropriate initial seeds can reduce the cluster’s inconsistency. In this paper, we present a new method to determine the initial seeds of the k-mean algorithm to improve the accuracy and decrease the number of iterations of the algorithm. For this purpose, a new method is proposed considering the average distance between objects to determine the initial seeds. Our method attempts to provide a proper tradeoff between the accuracy and speed of the clustering algorithm. The experimental results showed that our proposed approach outperforms the Chithra with 1.7% and 2.1% in terms of clustering accuracy for Wine and Abalone detection data, respectively. Furthermore, achieved results indicate that comparing with the Reverse Nearest Neighbor (RNN) search approach, the proposed method has a higher convergence speed.     

Microstructural and mechanical properties assessment of transient liquid phase bonding of CoCuFeMnNi high entropy alloy

The transient liquid phase (TLP) bonding of CoCuFeMnNi high entropy alloy (HEA) was studied. The TLP bonding was performed using AWS BNi-2 interlayer at 1050 °C with the TLP bonding time of 20, 60, 180 and 240 min. The effect of bonding time on the joint microstructure was characterized by SEM and EDS. Microstructural results confirmed that complete isothermal solidification occurred approximately at 240 min of bonding time. For samples bonded at 20, 60 and 180 min, athermal solidification zone was formed in the bonding area which included Cr-rich boride and Mn₃Si intermetallic compound. For all samples, the γ solid solution was formed in the isothermal solidification zone of the bonding zone. To evaluate the effect of TLP bonding time on mechanical properties of joints, the shear strength and micro-hardness of joints were measured. The results indicated a decrement of micro-hardness in the bonding zone and an increment of micro-hardness in the adjacent zone of joints. The minimum and maximum values of shear strength were 100 and 180 MPa for joints with the bonding time of 20 and 240 min, respectively.