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.     

基于三种干旱指标的朝阳市干旱特征分析

旱灾具有出现频率高、持续时间长、波及范围广等特点，本文运用降水距平百分率、Z指数、SPI标准化降水指数，对朝阳地区50a（1969～2018）干旱特征进行分析。结果表明：Z指数与SPI标准化降水指标得到的朝阳地区干旱特征情况基本一致，能较好地反映出该地区的干旱特征，朝阳地区1969～2018年自然灾害频繁发生，严重干旱年份主要集中在1980、1981、1982 年，与实际相符。     

Comparative study of EICP treatment methods on the mechanical properties of sandy soil

This study analyzed the effect of different treatment methods in enzyme-induced carbonate precipitation (EICP) on the mechanical properties of soil. Soybean crude urease was used to catalyze the precipitation of calcium carbonate (CaCO₃). A multiple-phase method was proposed and further compared with commonly practiced EICP treatment methods (including the one-phase method, two-phase method, and premix-and-compact method) from the aspects of chemical conversion efficiency, CaCO₃ precipitation distribution, permeability, and unconfined compressive strength. Based on the findings, the characteristics of each method were further discussed and summarized. Although the enzymatic CaCO₃ precipitation generated from all the treatment methods could potentiate the soil strength to a great or less degree, using the proposed multiple-phase method could bring about a high chemical conversion efficiency, uniform distribution of CaCO₃ as well as preferable permeability retention. In addition, the multiple-phase method could significantly improve the efficiency of urease usage.     

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.     

ZnO·2.7Al2O3 nanocomposite with high optical transparency

Here we report a transparent dual-phase ZnO·2.7Al₂O₃ ceramic. The composite is pore-free and consists of thin nanosheets with a spinel phase and a hexagonal phase, while the two phases match closely in both lattice and refractive index. Such features result in excellent optical transmittance (maximum value >80% in the visible spectrum) at comparable phase volume. This work may provide a new thought for the rational structural design of optical nanocomposites.     

Effect of metallurgical evolution during post-weld aging treatment on localised corrosion of resistance spot welding joints of A286 superalloy

The combined effect of resistance spot welding and precipitation hardening on the localised corrosion of A286 superalloy is studied. The specimens tested by double loop electrochemical potentiokinetic reactivation were welded in the solution treated condition, and then subjected to different precipitation hardening treatments. For both base metal and weld nugget, the maximum localised corrosion is reached when η phase is clearly observable. The fact that the localised corrosion resistance of weld nugget is different from that shown by base metal may be explained by the segregation of Ni and Ti towards the interdendritic region of weld nugget (studied by using scanning electron microscope/energy dispersive X-ray analysis).     

Relevance- and interface-driven clustering for visual information retrieval

Search results of spatio-temporal data are often displayed on a map, but when the number of matching search results is large, it can be time-consuming to individually examine all results, even when using methods such as filtered search to narrow the content focus. This suggests the need to aggregate results via a clustering method. However, standard unsupervised clustering algorithms like $K$-means (i) ignore relevance scores that can help with the extraction of highly relevant clusters, and (ii) do not necessarily optimize search results for purposes of visual presentation. In this article, we address both deficiencies by framing the clustering problem for search-driven user interfaces in a novel optimization framework that (i) aims to maximize the relevance of aggregated content according to cluster-based extensions of standard information retrieval metrics and (ii) defines clusters via constraints that naturally reflect interface-driven desiderata of spatial, temporal, and keyword coherence that do not require complex ad-hoc distance metric specifications as in $K$-means. After comparatively benchmarking algorithmic variants of our proposed approach – RadiCAL – in offline experiments, we undertake a user study with 24 subjects to evaluate whether RadiCAL improves human performance on visual search tasks in comparison to $K$-means clustering and a filtered search baseline. Our results show that (a) our binary partitioning search (BPS) variant of RadiCAL is fast, near-optimal, and extracts higher-relevance clusters than $K$-means, and (b) clusters optimized via RadiCAL result in faster search task completion with higher accuracy while requiring a minimum workload leading to high effectiveness, efficiency, and user satisfaction among alternatives.     

不同醇沉竹荪多糖组分对青春双歧杆菌体外增殖作用的影响

本文以竹荪为原料提取多糖成分并以乙醇分级制备竹荪多糖(DPs)不同组分,通过青春双歧杆菌体外增殖试验初步评价竹荪多糖及其分级醇沉组分的益生元功效。结果显示在α-淀粉酶溶液中水解4 h后,20%、40%、50%、60%竹荪多糖醇沉组分水解度分别为9.10%、8.02%、8.88%、11.67%,与对照组菊粉(水解度13.15%)相比差异显著(P<0.05);80%竹荪多糖醇沉组分、未分级醇沉组分与菊粉对照组相比差异不显著(P>0.05)。在模拟胃液中水解6 h后,20%、40%、50%竹荪多糖醇沉组分水解度分别为17.30%、14.52%、9.61%,与对照组菊粉(水解度5.72%)相比差异显著(P<0.05);60%竹荪多糖醇沉组分、80%竹荪多糖醇沉组分、未分级醇沉组分水解度与对照组相比无显著差异(P>0.05)。随着竹荪多糖添加量的增加,青春双歧杆菌的菌体浓度呈现先增大而后不断减小的趋势。分级醇沉浓度达到80%的竹荪多糖组分和未分级的多糖组分,青春双歧杆菌体外增殖作用与pH下降显著且效果优于菊粉(P<0.05),并在20 h的发酵时间内两者表现出相似的效果。不同竹荪多糖醇沉组分对青春双歧杆菌均有增殖效果,且不同竹荪多糖醇沉组分的增殖效果和抗水解能力随乙醇浓度的增加而增强,未分级的多糖组分同样可以加强青春双歧杆菌增殖能力,具有益生元潜力。     

氮对镀锡钢板的强化作用

通过物理化学相分析研究了3种不同氮含量镀锡板中固溶氮、化合氮的含量,结合相关理论计算了镀锡板中氮的固溶强化和析出强化对强度的贡献。结果表明:随着总氮含量从0.0021%提高到0.0103%,钢中化合氮含量下降10.1%,但是AlN析出相中的氮的含量上升10.7%。氮在提高镀锡板强度方面发挥重要作用,钢中总氮含量提高0.0082%,其对屈服强度的贡献值提升约30 MPa。