融合前沿研究的液体电介质击穿教学研究

针对《高电压与绝缘技术》课程中液体电介质的教学难点，提出了融合前沿研究的液体电介质击穿教学方法。基于前沿的液体放电应用背景与先进的液体放电研究平台，形象地展示液体电介质的动态击穿过程，在教学内容、教学方法、考核方式等方面进行科教融合改进，实施“以学生为中心”理念的课程教学设计。该教学方式取得了较好的教学效果，能够为其它知识点的教学质量提升提供参考。     

In‐plane shear damage behaviours of 2D needled C/SiC composites

Understanding the in‐plane shear behaviour of composites is essential to establish the design basis for practical applications. This study aims to investigate the shear damage behaviours of 2D needled C/SiC composites by various characterization techniques. The effect of layer arrangement on shear modulus and strength was discussed via shear stress‐strain responses. The shear strain field evolution and uniformity variation were studied by digital image correlation. It shows that the uniformity of shear strain field changes with the shear load, and the shear strain field evolution consist of 5 stages. The electrical resistivity measurement results indicate that structural deformation and damage evolution caused the electrical resistivity change. Furthermore, the damage evolution has a double effect on the electrical resistivity variation. The acoustic emission monitoring shows that the shear damage evolution is a 3‐stage nonlinear process before failure. The shear damages were categorized via acoustic characteristics. Besides, the postfailure behaviours were also discussed in this study.     

The application of photography in investigating fraud

The impact of fraud on the world economy is significant. As fraud has evolved it has become more organized and increasingly cyber-enabled and committed across borders of law enforcement jurisdictions. The technological demands facing fraud investigators are increasing. Yet, little attention has been given to how forensic photography can help tackle emerging crime types, like fraud. This study reviews literature surrounding forensic photography and provides an up to date and collective narrative. This article focuses on the advancements in photography and how imaging-science techniques can apply to a fraud investigation. Photographic practice plays a key role in many crime investigations but must embrace continual change to ensure that it remains relevant to modern policing. Fresh approaches are essential and practitioners must fully utilize new technologies and adapt to tackle the increasingly demanding scope of fraud types.     

Advanced Functional Structure‐Based Sensing and Imaging Strategies for Cancer Detection: Possibilities,Opportunities, Challenges,and Prospects

Cancer is the second most common cause of death in the world. The principal limitations thus far encountered in the clinical practice of probing cancer are diverse and include low sensitivity, time consumption, bulkiness, and cost. In this respect, nanomaterial (NM)‐based sensing techniques are recognized as a superior alternative to efficiently resolve such limitations. A better understanding of NM‐based sensing platforms is thus important so that these novel avenues can easily be explored for clinical applications. These platforms have the merits of high sensitivity, high specificity, rapid response, and easy‐to‐read signals. This review offers a comprehensive survey of NM‐based advanced cancer‐sensing techniques and will help the scientific community establish optimum sensing strategies based on an accurate assessment of the interactions between cancer biomarkers and NM‐based platforms.     

A Versatile Theranostic Nanoemulsion for Architecture‐Dependent Multimodal Imaging and Dually Augmented Photodynamic Therapy

To design a clinically translatable nanomedicine for photodynamic theranostics, the ingredients should be carefully considered. A high content of nanocarriers may cause extra toxicity in metabolism, and multiple theranostic agents would complicate the preparation process. These issues would be of less concern if the nanocarrier itself has most of the theranostic functions. In this work, a poly(ethylene glycol)‐boron dipyrromethene amphiphile (PEG‐F₅₄‐BODIPY) with 54 fluorine‐19 (¹⁹F) is synthesized and employed to emulsify perfluorohexane (PFH) into a theranostic nanoemulsion (PFH@PEG‐F₅₄‐BODIPY). The as‐prepared PFH@PEG‐F₅₄‐BODIPY can perform architecture‐dependent fluorescence/photoacoustic/¹⁹F magnetic resonance multimodal imaging, providing more information about the in vivo structure evolution of nanomedicine. Importantly, this nanoemulsion significantly enhances the therapeutic effect of BODIPY through both the high oxygen dissolving capability and less self‐quenching of BODIPY molecules. More interestingly, PFH@PEG‐F₅₄‐BODIPY shows high level of tumor accumulation and long tumor retention time, allowing a repeated light irradiation after a single‐dose intravenous injection. The “all‐in‐one” photodynamic theranostic nanoemulsion has simple composition, remarkable theranostic efficacy, and novel treatment pattern, and thus presents an intriguing avenue to developing clinically translatable theranostic agents.     

Automatic brain tissue segmentation in MR images using hybrid atlas forest based on confidence-weighted probability matrix

The segmentation of specific tissues in an MR brain image for quantitative analysis can assist the disease diagnosis and medical research. Therefore, a robust and accurate method for automatic segmentation is necessary. Atlas-based-method is a common and effective method of automatic segmentation where an atlas refers to a pair of image consist of an intensity image and its corresponding label image. Apart from the general multi-atlas-based methods, which propagate labels through the single atlas then fuse them, we proposed a hybrid atlas forest based on confidence-weighted probability matrix to consider the atlases set as a whole and treat each voxel differently. In the framework, we first register the atlas to the image space of target and calculate the confidence of voxels in the registered atlas. Then, a confidence-weighted probability matrix is generated and it augments to the intensity image of the atlas or target for providing spatial information of the target tissue. Third, a hybrid atlas forest is trained to gather the features and correlation information among the atlases in the dataset. Finally, the segmentation of the target tissues is predicted by the trained hybrid atlas forest. The segment performance and the components efficiency of the proposed method are evaluated on the two public datasets. Based on the experiment results and quantitative comparisons, our method can gather spatial information and correlation among the atlases to obtain an accurate segmentation.