一种基于FCOS神经网络的小建筑物目标检测方法北大核心

提出了一种基于FCOS神经网络的小建筑物目标检测算法,针对FCOS模型在特征提取阶段提取到的小建筑物目标特征较少问题,引入多尺度检测和可变形卷积方式,加强网络对小建筑物目标的特征提取能力,并通过改进后的SGE注意力机制降低特征图中的干扰噪声权重。改进后的网络可以提取到更多的小建筑物目标特征,对环境干扰噪声的鲁棒性更强。在自己搭建的数据集上进行了实验测试,结果表明,在相同环境下网络改进后建筑物的整体检测准确率提升了1.7%,其中对小建筑物目标提升了3.6%,减少了小建筑物目标漏检、误检的问题。     

一种基于抽取LMS的距离旁瓣抑制方法

在噪声雷达中，传统相关处理方法的距离旁瓣受到时宽带宽积的限制，在有限相关处理时间内得到的距离旁瓣较高，会造成微弱目标被强目标、杂波旁瓣淹没的现象。提出一种基于抽取最小均方（Least Mean Square,LMS）滤波的噪声雷达旁瓣抑制方法，将LMS滤波器的系数作为距离压缩结果，从而获取较低的距离旁瓣。对该方法的性能进行了理论分析，并通过数字仿真验证了算法的有效性和理论分析的正确性。     

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.     

Co?N graphene encapsulated cobalt catalyst for H2O2 decomposition under acidic conditions

Hydrogen peroxide (H₂O₂) has been listed as one of the 100 most important chemicals in the world. However, huge amount of residual H₂O₂ is hard to timely decomposed into O₂ and H₂O under acidic condition, easily resulting in explosion hazard. Here, we reported a core–shell structure catalyst, that is graphene with Co N structure encapsulated Co nanoparticles. Co N graphene shell serves as the active site for the H₂O₂ decomposition, and Co core further enhance this decomposition. Benefiting from it, the H₂O₂ decomposition were close to 100% after 6 cycles without pH adjustment, which increased 6 orders of magnitude compared with no catalyst. At the same time, the O₂ generation reached 99.67% in 2 h with little metal leaching, and ·OH has been greatly inhibited to only 0.08%. This work can cleanly remove H₂O₂ with little deep oxidation and protect the process of H₂O₂ utilization to achieve a safer world.     

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.     

A triptycene derived hypercrosslinked polymer for gas capture and separation applications

This work describes facile synthesis of a porous polymeric material ( T-HCP ) using readily available reagents. Specifically, T-HCP is a thermally stable and hypercrosslinked polymer (HCP) that is essentially microporous with a high BET specific surface area (940 m² g^?1). Triptycene based polymers are known to feature internal free volume. Thus, the incorporation of triptycene units and extensive crosslinking by an external cross-linker in T-HCP makes it a promising adsorbent for small gas capture applications. Experimental results show that T-HCP demonstrated good CO₂ capture capacity of 132 mg g^?1 (273 K, 1 bar). Molecular hydrogen storage capacity of T-HCP is estimated to be 17.7 mg g^?1 (77 K, 1 bar). T-HCP revealed high CO₂/N₂ selectivity (up to 63) as well as promising CO₂/CH₄ (up to 9.1) selectivity suggesting its potential applicability for CO₂ separation from flue and natural gases.     

Flash Lamps as Ignition and Initiation Sources of the VS-2 Pyrotechnic Composition

In the present work it is found that the pyrotechnic composition VS-2 can be initiated with flash lamps IFC-500 and EVIS. VS-2 pyrotechnic composition contains 90% of mercury（Ⅱ） 5-hydrazinotetrazolate perchlorate and 10% of optically transparent copolymer of 2-methyl-5-vinyltetrazole and methacrylic acid （PVMT）. We have found that the flash lamps make it possible to initiate combustion of VS-2 composition with its transition to detonation both in cylindrical charges placed in brass caps of 5 mm diameter and 2 mm high， and film charges with 10 mm×80 mm in size and surface weights of 60 mg·cm^-2 and 90 mg·cm^-2， showing ignition delay times 10 μs and 3 μs， respectively. We also measured detonation velocities for VS-2 composition film charges， which were 4375-4505 m·s^-1 （of the charge being surface mass 60 mg·cm^-2） and 4221-4281 m·s^-1 （of the charge being surface mass 90 mg·cm^-2） and their blasting action on the aluminum plate. The depths of the normal shock wave imprints at the charge-barrier interface were 0.6-0.7 mm （for surface mass of the film charges 60 mg·cm^-2） and 1.2-1.3 mm （for surface mass of the film charges 90 mg·cm^-2）.     

CNT-interconnected iron-doped NiP2/Ni2P heterostructural nanoflowers as high-efficiency electrocatalyst for oxygen evolution reaction

Oxygen evolution reaction (OER) plays a decisive role in electrolytic water splitting. However, it is still challengeable to develop low-cost and efficient OER electrocatalysts. Herein, we present a combination strategy via heteroatom doping, hetero-interface engineering and introducing conductive skeleton to synthesize a hybrid OER catalyst of CNT-interconnected iron-doped NiP₂/Ni₂P (Fe-(NiP₂/Ni₂P)@CNT) heterostructural nanoflowers by a simple hydrothermal reaction and subsequent phosphorization process. The optimized Fe-(NiP₂/Ni₂P)@CNT catalyst delivers an ultralow Tafel slope of 46.1 mV dec^?1 and overpotential of 254 mV to obtain 10 mA cm^?2, which are even better than those of commercial OER catalyst RuO₂. The excellent OER performance is mainly attributed to its unique nanoarchitecture and the synergistic effects: the nanoflowers constructed by a 2D-like nanosheets guarantee large specific area and abundant active sites; the highly conductive CNT skeleton and the electronic modulation by the heterostructural NiP₂/Ni₂P interface and the hetero-atom doping can improve the catalytic activity; porous nanostructure benefits electrolyte penetration and gas release; most importantly, the rough surface and rich defects caused by phosphorization process can further enhance the OER performance. This work provides a deep insight to boost catalytic performance by heteroatom doping and interface engineering for water splitting.     

Investigation of liquid water heterogeneities in large area proton exchange membrane fuel cells using a Darcy two-phase flow model in a multiphysics code

Proper management of the liquid water and heat produced in proton exchange membrane (PEM) fuel cells remains crucial to increase both its performance and durability. In this study, a two-phase flow and multicomponent model, called two-fluid model, is developed in the commercial COMSOL Multiphysics® software to investigate the liquid water heterogeneities in large area PEM fuel cells, considering the real flow fields in the bipolar plate. A macroscopic pseudo-3D multi-layers approach has been chosen and generalized Darcy's relation is used both in the membrane-electrode assembly (MEA) and in the channel. The model considers two-phase flow and gas convection and diffusion coupled with electrochemistry and water transport through the membrane. The numerical results are compared to one-fluid model results and liquid water measurements obtained by neutron imaging for several operating conditions. Finally, according to the good agreement between the two-fluid and experimentation results, the numerical water distribution is examined in each component of the cell, exhibiting very heterogeneous water thickness over the cell surface.     

Topological homogenization of metamaterial variability

With the proliferation of additive manufacturing and 3D printing technologies, a broader palette of material properties can be elicited from cellular solids, also known as metamaterials, architected foams, programmable materials, or lattice structures. Metamaterials are designed and optimized under the assumption of perfect geometry and a homogeneous underlying base material. Yet in practice real lattices contain thousands or even millions of complex features, each with imperfections in shape and material constituency. While the role of these defects on the mean properties of metamaterials has been well studied, little attention has been paid to the stochastic properties of metamaterials, a crucial next step for high reliability aerospace or biomedical applications. In this work we show that it is precisely the large quantity of features that serves to homogenize the heterogeneities of the individual features, thereby reducing the variability of the collective structure and achieving effective properties that can be even more consistent than the monolithic base material. In this first statistical study of additive lattice variability, a total of 239 strut-based lattices were mechanically tested for two pedagogical lattice topologies (body centered cubic and face centered cubic) at three different relative densities. The variability in yield strength and modulus was observed to exponentially decrease with feature count (to the power −0.5), a scaling trend that we show can be predicted using an analytic model or a finite element beam model. The latter provides an efficient pathway to extend the current concepts to arbitrary/complex geometries and loading scenarios. These results not only illustrate the homogenizing benefit of lattices, but also provide governing design principles that can be used to mitigate manufacturing inconsistencies via topological design.