摘要：In this paper, through the investigation and research on some representative art academies, the difference between art academies and general institutions of higher learning in campus environment is explored in depth. Hopefully, the specific characteristics of the design for campus environments of art academies as well as all sorts of factors causing the characteristics can be discovered, including the specific characteristics of campus subjects, the originality of campus buildings, and the novelty of campus sculpture.

摘要：Combining the design of experiments(DOE)and three-dimensional finite element(3D-FE)method,a sequential multiobjectiveoptimization of larger diameter thin-walled(LDTW)Al-alloy tube bending under uncertainties was proposed andimplemented based on the deterministic design *** the fractional factorial design,the significant noise factors are obtained,viz,variations of tube properties,fluctuations of tube geometries and *** the virtual Taguchi’s DOE of inner and outerarrays,considering three major defects,the robust optimization of LDTW Al-alloy tube bending is achieved and *** thebending tools,the robust design of mandrel diameter was conducted under the fluctuations of tube properties,friction and *** the processing parameters,considering the variations of friction,material properties and manufacture deviation ofmandrel,the robust design of mandrel extension length and boosting ratio is realized.

摘要：Fe-containing graphitic carbon nitride（Fe-g-C3N4） materials were synthesized via one-step pyroly-sis of FeCl3 and dicyandiamide. The physicochemical properties of the synthesized Fe-g-C3N4 sam-ples were characterized by N2 adsorption-desorption, X-ray diffraction, thermal gravimetric, Fourier transform infrared, UV-vis diffuse reflectance, X-ray photoelectron spectroscopy, and transmission electron microscopy. The Fe cations were anchored by nitrogen-rich g-C3N4, whereas the graphitic structures of g-C3N4 were retained after the introduction of Fe. As heterogeneous catalysts, Fe-g-C3 N4 exhibited good catalytic activity in the direct hydroxylation of benzene to phenol with H2O2, affording a maximum yield of phenol of up to 17.5%. Compared with other Fe- and V-containing g-C3N4 materials, Fe-g-C3N4 features a more convenient preparation procedure and higher catalytic productivity of phenol.

摘要：Clean catalytic oxidation has a broad prospect in the modern chemical engineering and energy chemistry ***,unexpected over-oxidation and disruptive degradation are frequently induced by excessive reactive oxygen species(ROS).Herein,we reported a new ROS-free approach to effectively drive O_(2) to be activated into highly reactive surface peroxo species through enzyme-mimicking *** from the dual-metal synergy effect between Cu and Co active sites,ROS(H_(2)O_(2) and OH•)is generated in situ while further scavenged completely into surface peroxo species,which gives rise to very high selectivity and extremely high carbon *** example,the CuCo/N-C catalyst affords>99.8%conversion and 94.5%selectivity to 2,5-furanedicarboxylic acid at 25℃ for 6 h in the aerobic oxidation of biomass platform ***,it achieved exceptional performance in the oxidation of a variety of hydroxyl compounds to organic acids with high yields(89.9%–99.5%)at a mild temperature(25–40℃).This exploration introduces an innovative clue for emulating enzyme catalysts,thereby enriching our comprehension and advancement of biologically inspired catalytic oxidations.

摘要：[目的]通过目标分割为果园喷雾机提供树木的表征信息,使喷雾机能够实现精准喷雾。在分割过程中,对苗圃中的树冠、树干等不同部位进行分割,可以帮助喷雾机对喷雾部分对靶,在果园或苗圃景观中实现自动导航以及精准喷药等操作。与图片相比,点云能够更好地表征树木的三维结构并且受照明条件影响小,因此针对点云树木设计分割算法更适合应用在果园、苗圃等室外环境作业的农业机械。[方法]本文基于DGCNN提出了一种分割精度准确、参数量小的树木点云分割网络——TSNet,它可以很容易被部署在果园喷雾机上。该网络主要具有以下特点:1)该网络是基于DGCNN改进的,可以更好实现点云分割任务;2)网络引入了连续递归门控卷积模块(g^(n)Conv),可以提高树木分割的准确率;3)为避免全局信息损失并增加信息传递效率,我们设计了权重通道用于特征传递。[结果]TSNet分割树木的mIoU达到90.08%,模型大小为0.72 M,优于PointNet、PointNet++、DGCNN、CurveNet、PointMLP和D-PointNet++等常用的点云分割算法。[结论]TSNet能够为苗圃树木检测识别和农业机器人作业提供更准确的感知信息。

摘要：The rational design and synthesis of hybrid-type electrode nanomaterials are significant for their diverse applications,including their potential usage as high-efficiency nanoarchitectures for supercapacitors(SCs)as a class of promising energy-storage systems for powering next-generation electric vehicles and electronic ***,we reported a facile and controllable synthesis of core-shell Ni_(3)S_(2)@NiWO_(4)nanoarrays to fabricate a freestanding electrode for hybrid ***,the as-prepared freestanding Ni_(3)S_(2)@NiWO_(4)electrode presents an ultrahigh areal capacity of 2032μA h cm^(-2)at 5 mA cm^(-2),and a capacity retention of 63.6%even when the current density increased up to 50 mA cm^(-2).Remarkably,the Ni_(3)S_(2)@NiWO_(4)nanoarraybased hybrid SC delivers a maximum energy density of 1.283 mW h cm^(-2)at 3.128 mW cm^(-2)and a maximum power density of 41.105 mW cm^(-2)at 0.753 mW h cm^(-2).Furthermore,the hybrid SC exhibits a capacity retention of 89.6%even after continuous 10,000 cycles,proving its superior *** study provides a facile pathway to rationally design a variety of core-shell metal nanostructures for high-performance energy storage devices.

摘要：同伴教学是指身份地位、知识水平与理解能力相近的同龄学生间通过相互指导,对双方的知识、技能、情感和社会化等各方面产生正向影响的活动。同伴教学思想体现了人的知识建构和社会性交往需要。从皮亚杰的个体知识建构到维果斯基的社会知识建构,从米德角色理论到勒温·库尔特群体动力理论,彰显了同伴教学思想的深厚理论意蕴。我国创新型社会的建设和教育公平的诉求为同伴教学的实施提供了土壤。同伴教学的有效实施必须明确多维的教学目标、营造数智赋能的教学环境、设计灵活的教学活动和构建多元的评价方式等。

摘要：以生成式人工智能(GenAI)为代表的智能技术推动了科研范式的转型,有助于复杂科研问题的解决。分析GenAI在科研场景中的使用差异及其影响因素,有利于高校智能化科研建设。基于对浙江大学1226位研究生的问卷调查发现:在科研中使用GenAI占比最多的前四个场景为文献翻译、信息检索、文献综述和润色降重;学科背景在信息检索、头脑风暴和代码生成三个场景中显著影响研究生使用GenAI;而人工智能素养在文献翻译、头脑风暴、文献综述、选择研究问题、实验设计、数据处理、代码生成和润色降重8个场景中显著影响研究生使用GenAI。此外,针对其中部分研究生的访谈分析发现:研究生认为能评估GenAI生成内容质量高低是合理使用GenAI的前提;GenAI应用技巧决定了GenAI辅助科研的效率;除学科背景和人工智能素养水平外,导师对GenAI的态度与使用水平以及高校GenAI资源开发与集成情况同样影响其在科研中使用GenAI。为促进研究生更好地利用GenAI赋能高质量科研创新,建议高校开发适配各专业教科研所需的垂直领域大模型,面向不同学科背景研究生设计融入GenAI使用的课程,全面提升高校师生人工智能素养。

摘要：针对直流到直流(direct-current to direct-current,DC-DC)变换器在负载切换时,传统的控制策略无法取得良好的动态性能问题,提出一种模型补偿自抗扰控制方法,将其应用于DC-DC变换器系统。通过建立BUCK型DC-DC变换器控制系统模型,提出电压外环及电流内环线性自抗扰,并在此基础上对电压外环设计基于扰动补偿的模型自抗扰控制策略。对DC-DC变换器模型自抗扰控制系统进行模拟仿真,仿真结果表明:所提出的数学模型补偿自抗扰方式在电压追踪性能和鲁棒性方面更具优势。

摘要：针对当前印刷电路板(PCB)缺陷检测存在的检测精度低、速度慢等问题,设计一种基于改进YOLOv7的WiseYOLOv7算法。首先,在原有self-attention的基础上加入焦点调制网络,将不同粒度级别的空间特征汇总为调制器,以自适应的方式注入查询操作中,省去大量交互和聚合操作,从而使得模型轻量化;其次,利用RCSOSA模块减少特征图的通道数量,同时增强相邻层特征不同通道间的信息交流,提高模型对PCB小目标缺陷的特征提取能力和数据处理效率;最后,选用动态非单调焦点机制的Wise-IoU损失函数来加强对高质量锚盒的选取,优化目标检测器的性能。与YOLOv7基础算法相比,改进算法将平均精度由92.0%提高至96.1%,提高了4.1%,检测时间由21.9 ms缩短到17.9 ms,改进算法在精度和速度上都有明显提升。