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。     

Facile synthesis of Ti3C2 MXene-modified Bi2.15WO6 nanosheets with enhanced reactivity for photocatalytic reduction of Cr(VI)

Through a facile hydrothermal method, we have successfully prepared Ti₃C₂/Bi_2.15WO₆ (TC/BWO) composite, and systematically investigated their reactivity for the photocatalytic reduction of Cr(VI) under visible light. X-ray diffraction and Raman analysis confirm the formation of heterostructure between Bi_2.15WO₆ and Ti₃C₂. The resultant 7TC/BWO composite exhibits enhanced photoactivity toward Cr(VI) reduction. After 120 min irradiation, the conversion of Cr(VI) reaches 92.5% with the quasi-first-order kinetic constant of k = 0.0145 min^?1, which is higher than that of pure BWO (30% and k = 0.0005 min^?1). The electrochemical and photoluminescent characterization confirm that the introduction of Ti₃C₂ is conducive to the separation of carriers, thus significantly improves the photocatalytic performance of TC/BWO. Furthermore, the radical capture experiments verify that the electrons are important for enhancing reduction of Cr(VI) to Cr(III). As a result, this research provides a comprehensive understanding of the reduction of Cr(VI) by TC/BWO composite under visible light.     

Real time power management strategy for fuel cell hybrid electric bus based on Lyapunov stability theorem

The fuel cell/battery durability and hybrid system stability are major considerations for the power management of fuel cell hybrid electric bus (FCHEB) operating on complicated driving conditions. In this paper, a real time nonlinear adaptive control (NAC) with stability analyze is formulated for power management of FCHEB. Firstly, the mathematical model of hybrid power system is analyzed, which is established for control-oriented design. Furthermore, the NAC-based strategy with quadratic Lyapunov function is set up to guarantee the stability of closed-loop power system, and the power split between fuel cell and battery is controlled with the durability consideration. Finally, two real-time power management strategies, state machine control (SMC) and fuzzy logic control (FLC), are implemented to evaluate the performance of NAC-based strategy, and the simulation results suggest that the guaranteed stability of NAC-based strategy can efficiently prolong fuel cell/battery lifespan and provide better fuel consumption economy for FCHEB.     

Enhanced oxygen evolution reaction kinetics through biochar-based nickel-iron phosphides nanocages in water electrolysis for hydrogen production

Highly-efficient and stable non-noble metal electrocatalysts for overcoming the sluggish kinetics of oxygen evolution reaction (OER) is urgent for water electrolysis. Biomass-derived biochar has been considered as promising carbon material because of its advantages such as low-cost, renewable, simple preparation, rich structure, and easy to obtain heteroatom by in-situ doping. Herein, Ni₂P–Fe₂P bimetallic phosphide spherical nanocages encapsulated in N/P-doped pine needles biochar is prepared via a simple two-step pyrolysis method. Benefiting from the maximum synergistic effects of bimetallic phosphide and biochar, high conductivity of biochar encapsulation, highly exposed active sites of Ni₂P–Fe₂P spherical nanocages, rapid mass transfer in porous channels with large specific surface area, and the promotion in adsorption of reaction intermediates by high-level heteroatom doping, the (Ni_0.75Fe_0.25)₂P@NP/C demonstrates excellent OER activity with an overpotential of 250 mV and a Tafel slope of 48 mV/dec at 10 mA/cm² in 1 M KOH. Also it exhibits a long-term durability in 10 h electrolysis and its activity even improves during the electrocatalytic process. The present work provides a favorable strategy for the inexpensive synthesis of biochar-based transition metal electrocatalysts toward OER, and improves the water electrolysis for hydrogen production.     

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.     

高效液相色谱法测定化妆品中依克多因的含量

建立高效液相色谱法测定化妆品中依克多因的分析方法,采用Agilent Poroshell 120 EC-C₁₈色谱柱（100 mm×3.0 mm,2.7μm）分离,以甲醇和p H为3.0的40 mmol/L磷酸二氢钠-10 mmol/L 1-庚烷磺酸钠缓冲溶液梯度洗脱,流速0.8 m L/min,柱温30℃,检测波长210 nm。采用外标法定量测定化妆品中的依克多因含量。结果表明,依克多因在5～800 mg/L的质量浓度范围内呈现良好线性关系,相关系数为0.999 8,方法的检出限和定量限分别为0.3和1.0 mg/L。该方法具有分离效率高、分析时间短、节省溶剂等优点,解决了依克多因在C₁₈色谱柱上保留弱的问题。     

个性化学习路径推荐综述

近年来，伴随着现代信息技术的迅猛发展，以人工智能为代表的新兴技术在教育领域得到了广泛应用，引发了学习理念和方式的深刻变革.在这种大背景下，在线学习超越了时空的限制，为学习者“随时随地”学习提供了更多的可能性，从而得到了蓬勃发展.然而，在线学习中师生时间、空间分离的特征，导致教师无法及时掌握学生的学习状态，一定程度上制约了在线学习中教学质量的提升.面对多元化的学习需求及海量学习资源，如何迅速完成学习目标、降低学习成本、合理分配学习资源等问题成为限制个人和时代发展的重大问题.然而，传统的“一刀切”的教育模式已经不能满足人们获取知识的需求了，需要一个更高效、更科学的个性化教育模式，以帮助学习者以最小的学习成本最大限度地完成学习目标.基于以上背景，如何自动高效识别学习者特征，高效地组织和分配学习资源，为每一位学习者规划个性化路径，成为面向个体的精准化教育资源匹配机制研究中亟待解决的问题.系统地综述并分析了当前个性化学习路径推荐的研究现状，并从多学科领域的角度分析了对于同一问题的不同研究思路，同时也归纳总结了当前研究中最为主流的核心推荐算法.最后，强调当前研究存在的主要不足之处.     

Prediction of fish quality level with machine learning

In this study, sea bream, sea bass, anchovy and trout were captured and recorded using a digital camera during refrigerated storage for 7 days. In addition, their total viable counts (TVC) were determined on a daily basis. Based on the TVC, each fish was classified as ‘fresh’ when it was <5 log cfu per g, and as ‘not fresh’ when it was >7 log cfu per g. They were uploaded on a web-based machine learning software called Teachable Machine (TM), which was trained about the pupils and heads of the fish. In addition, images of each species from different angles were uploaded to the software in order to ensure the recognition of fish species by TM. The data of the study indicated that the TM was able to distinguish fish species with high accuracy rates and achieved over 86% success in estimating the freshness of the fish species tested.