云雾混合网络下基于多智能体架构的资源分配及卸载决策研究

针对D2D辅助的云雾混合架构下资源分配及任务卸载决策优化问题,该文提出一种基于多智能体架构深度强化学习的资源分配及卸载决策算法.首先,该算法考虑激励约束、能量约束以及网络资源约束,联合优化无线资源分配、计算资源分配以及卸载决策,建立了最大化系统总用户体验质量(QoE)的随机优化模型,并进一步将其转化为MDP问题.其次,...     

基于三维卷积的帕金森患者拖步识别

冻结步态(FoG)是一种在帕金森病(PD)中常见的异常步态,而拖步则是冻结步态的一种表现形式,也是医生用来判断患者的治疗状况的重要因素,并且拖步状态也对PD患者的日常生活有很大影响。该文提出一种通过计算机视觉来实现患者拖步状态自动识别的方法,该方法通过以3维卷积为基础的网络结构,可以从PD患者的TUG测试视频中自动识别出患者是否具有拖步症状。其思路是首先利用特征提取模块从经过预处理的视频序列中提取出时空特征,然后将得到的特征在不同空间和时间尺度上进行融合,之后将这些特征送入分类网络中得到相应的识别结果。在该工作中共收集364个正常步态样本和362个具有拖步状态的样本来构成实验数据集,在该数据集上的实验表明,该方法的平均准确率能够达到91.3%。并且其能从临床常用的TUG测试视频中自动准确地识别出患者的拖步状态,这也为远程监测帕金森病患者的治疗状态提供了助力。     

4D Printing of Shape Memory Materials for Textiles: Mechanism,Mathematical Modeling,and Challenges

Shape memory materials (SMMs) in 3D printing (3DP) technology garnered much attention due to their ability to respond to external stimuli, which direct this technology toward an emerging area of research, “4D printing (4DP) technology.” In contrast to classical 3D printed objects, the fourth dimension, time, allows printed objects to undergo significant changes in shape, size, or color when subjected to external stimuli. Highly precise and calibrated 4D materials, which can perform together to achieve robust 4D objects, are in great demand in various fields such as military applications, space suits, robotic systems, apparel, healthcare, sports, etc. This review, for the first time, to the best of the authors’ knowledge, focuses on recent advances in SMMs (e.g., polymers, metals, etc.) based wearable smart textiles and fashion goods. This review integrates the basic overview of 3DP technology, fabrication methods, the transition of 3DP to 4DP, the chemistry behind the fundamental working principles of 4D printed objects, materials selection for smart textiles and fashion goods. The central part summarizes the effect of major external stimuli on 4D textile materials followed by the major applications. Lastly, prospects and challenges are discussed, so that future researchers can continue the progress of this technology.     

Epitaxial Growth of 2D Materials on High-Index Substrate Surfaces

Recently, the successful synthesis of wafer-scale single-crystal graphene, hexagonal boron nitride (hBN), and MoS₂ on transition metal surfaces with step edges boosted the research interests in synthesizing wafer-scale 2D single crystals on high-index substrate surfaces. Here, using hBN growth on high-index Cu surfaces as an example, a systematic theoretical study to understand the epitaxial growth of 2D materials on various high-index surfaces is performed. It is revealed that hBN orientation on a high-index surface is highly dependent on the alignment of the step edges of the surface as well as the surface roughness. On an ideal high-index surface, well-aligned hBN islands can be easily achieved, whereas curved step edges on a rough surface can lead to the alignment of hBN along with different directions. This study shows that high-index surfaces with a large step density are robust for templating the epitaxial growth of 2D single crystals due to their large tolerance for surface roughness and provides a general guideline for the epitaxial growth of various 2D single crystals.     

Nanopoxia: Targeting Cancer Hypoxia by Antimonene-Based Nanoplatform for Precision Cancer Therapy

Most anticancer drugs with broad toxicities are systematically administrated to cancer patients and their distribution in tumors is extremely low owing to hypoxia, which compromises the therapeutic efficacies of these cancer drugs. Consequently, a preponderant proportion of cancer drugs is distributed in off-target-healthy tissues, which often causes severe adverse effects. Precision cancer therapy without overdosing patients with drugs remains one of the most challenging issues in cancer therapy. Here, a novel concept of nanopoxia is presented, which is a tumor-hypoxia-based photodynamic nanoplatform for the release of therapeutic agents to achieve precision cancer therapy. Under tumor hypoxia, exposure of tumors to laser irradiation induces the fracture of polymer outer shell and produces anticancer reactive oxygen species, and switches 2D antimonene (Sb) nanomaterials to cytotoxic trivalent antimony to synergistically kill tumors. In preclinical cancer models, delivery of Sb nanomaterials to mice virtually ablates tumor growth without producing any detectable adverse effects. Mechanistically, the tumor hypoxia-triggered generation of trivalent antimony displays direct damaging effects on cancer cells and suppression of tumor angiogenesis. Together, the study provides a proof-of-concept of hypoxia-based precision cancer therapy by developing a novel nanoplatform that offers multifarious mechanisms of cancer eradication.     

Wood-Inspired Binder Enabled Vertical 3D Printing of g-C3N4/CNT Arrays for Highly Efficient Photoelectrochemical Hydrogen Evolution

2D nanomaterials are very attractive for photoelectrochemical applications due to their ultra-thin structure, excellent physicochemical properties of large surface-area-to-volume ratios, and the resulting abundant active sites and high charge transport capacity. However, the application of commonly used 2D nanomaterials with disordered-stacking is always limited by high photoelectrode tortuosity, few surface-active sites, and low mass transfer efficiency. Herein, inspired by wood structures, a vertical 3D printing strategy is developed to rapidly build vertically aligned and hierarchically porous graphitic carbon nitride/carbon nanotube (g-C₃N₄/CNT) arrays by using lignin as a binder for efficient photoelectrochemical hydrogen evolution. Arising from the directional electron transport and multiple light scattering in the out-of-plane aligned and porous architecture, the resulting g-C₃N₄/CNT arrays display an outstanding hydrogen evolution performance, with the hydrogen yield up to 4.36 µmol (cm⁻² h⁻¹) at a bias of −0.5 V versus RHE, 12.7 and 41.6 times higher than traditional thick g-C₃N₄/CNT and g-C₃N₄ films, respectively. Moreover, this 3D printed structure can overcome the agglomeration problem of the commonly used g-C₃N₄ with powder configuration and shows desirable recyclability and stability. This facile and scalable vertical 3D printing strategy will open a new avenue to highly enhance the photoelectrochemical performance of 2D nanomaterials for sustainably production of clean energy.     

支持向量机漏电特征模型的电力设施漏电识别

针对电力设施中漏电引起的故障问题,提出了新型的漏电特性分析方法,该方法融合了基于支持向量机的漏电算法模型,实现了电力设施漏电特性的图像采集和A/D转换处理,最后输出后的数据信息通过DSP计算模块进行计算,最终输出电力设施的强电漏电信息或者弱电漏电信息,实现了电力设施漏电信息的识别.该研究将传统技术中的漏电难以分析的问题...     

New Frontiers on van der Waals Layered Metal Phosphorous Trichalcogenides

The exponentially growing works on 2D materials have resulted in both high scientific interest and huge potential applications in nanocatalysis, optoelectronics, and spintronics. Of especial note is that the newly emerged and promising family of metal phosphorus trichalcogenides (MPX₃) contains semiconductors, metals, and insulators with intriguing layered structures and architectures. The bandgaps of the members in this family range from 1.3 to 3.5 eV, significantly enriching the application of 2D materials in the broad wavelength spectrum. In this review, emphasizing their remarkable structural, physicochemical, and magnetic properties, as well as the numerous applications in various fields, the innovative progress on layered MPX₃ crystals is summarized. Different from other layered materials, these crystals will advance a fascinating frontier in magnetism and spintronic devices with their especially featured atomic layered nanosheets. Thus, their crystal and electronic structures, along with some related researches in magnetism, are discussed in detail. The assortments of growth methods are then summarized. Considering their potential applications, the prominent utilization of these 2D MPX₃ nanoscrystals in catalysis, batteries, and optoelectronics is also discussed. Finally, the outlook of these kinds of layered nanomaterials is provided.     

In Situ Formation of Copper‐Based Hosts Embedded within 3D N‐Doped Hierarchically Porous Carbon Networks for Ultralong Cycle Lithium–Sulfur Batteries

Lithium–sulfur (Li–S) batteries are promising energy storage systems due to their large theoretical energy density of 2600 Wh kg^?1 and cost effectiveness. However, the severe shuttle effect of soluble lithium polysulfide intermediates (LiPSs) and sluggish redox kinetics during the cycling process cause low sulfur utilization, rapid capacity fading, and a low coulombic efficiency. Here, a 3D copper, nitrogen co‐doped hierarchically porous graphitic carbon network developed through a freeze‐drying method (denoted as 3D Cu@NC‐F) is prepared, and it possesses strong chemical absorption and electrocatalytic conversion activity for LiPSs as highly efficient sulfur host materials in Li–S batteries. The porous carbon network consisting of 2D cross‐linked ultrathin carbon nanosheets provides void space to accommodate volumetric expansion upon lithiation, while the Cu, N‐doping effect plays a critical role for the confinement of polysulfides through chemical bonding. In addition, after sulfuration of Cu@NC‐F network, the in situ grown copper sulfide (Cu_xS) embedded within Cu_xS@NC/S‐F composite catalyzes LiPSs conversion during reversible cycling, resulting in low polarization and fast redox reaction kinetics. At a current density of 0.1 C, the Cu_xS@NC/S‐F composites' electrode exhibits an initial capacity of 1432 mAh g^?1 and maintains 1169 mAh g^?1 after 120 cycles, with a coulombic efficiency of nearly 100%.     

一种基于清晰度的显微浮雕轮廓术

提出了一种基于清晰度的显微浮雕轮廓术。 采用5倍显微物镜,将正弦条纹通过投影仪从显 微镜目镜瞳口处耦合投射到载物台上,按照一个合适的步长移动Z轴,用CCD采集一系列不同 离焦量下 的条纹图像,用variance清晰度评价函数计算清晰度与离焦量之间的归一化曲线图,由此建 立清晰度与高 度的查找表;然后,放入待测浮雕物体,用CCD采集对应的条纹图像,采用图像分割分解不 同浮雕高度的 区域,再计算各区域内条纹的清晰度,根据查找表查找相应的高度,从而得到待测浮雕物体 不同区域的高 度信息,以此来重构浮雕物体的三维形貌。实验仿真分析证明了该方法的可行性,硬币上数 字为“0”的浮雕 物体表面三维形貌重建结果证明了该方法的有效性,其误差范围在[－2μm,2μm]之间 。