Novel flangeless video laryngoscope for limited mouth opening

Airway management plays a crucial role in providing adequate oxygenation and ventilation to patients during various medical procedures and emergencies.When patients have a limited mouth opening due to factors such as trauma,inflammation,or anatomical abnormalities airway management becomes challenging.A commonly utilized method to overcome this challenge is the use of video laryngoscopy(VL),which employs a specialized device equipped with a camera and a light source to allow a clear view of the larynx and vocal cords.VL overcomes the limitations of direct laryngoscopy in patients with limited mouth opening,enabling better visualization and successful intubation.Various types of VL blades are available.We devised a novel flangeless video laryngoscope for use in patients with a limited mouth opening and then tested it on a manikin.

不同方法对根管内氢氧化钙去除效果的micro-CT评价

目的:应用显微CT(micro-computed tomography,micro-CT)建立磨牙根管模型,评价不同方法对氢氧化钙的清除效率。方法:收集2023年10月—2024年2月口腔综合科门诊拔除的11颗磨牙(24个根管),按照标准根管治疗流程,镍钛器械预备完成后,在根管内置入氢氧化钙,1周后,根据不同冲洗方法将样本随机分为侧方开口注射器组、超声荡洗组(EMS组)和声波震荡组(EDDY组)等3组(n=8)。冲洗前后使用micro-CT重建根管系统并使用不同颜色标记独立根管,计算各个根管氢氧化钙体积,比较各组氢氧化钙清除率。采用SPSS 19.0软件包对数据进行统计学分析。结果:3种方法均无法完全去净根管内氢氧化钙。使用次氯酸钠作为冲洗液时,超声荡洗和声波震荡清除效果优于侧方开口冲洗器(P<0.05);超声荡洗和声波震荡去除氢氧化钙效率相当,差异无统计学意义(P>0.05);氢氧化钙残留部位集中于根尖区。结论:Micro-CT能较为高效地重建磨牙根管模型,可用于评价氢氧化钙去除效果。超声荡洗组和声波震荡组清除氢氧化钙效率相当,优于侧方开口注射器组。

Micro LED车灯投影光学系统设计与优化

本文提出了一种基于Micro LED阵列的车灯投影方案,设计了以像素尺寸为80μm×80μm的200×150白光Micro LED阵列作为显示光源,视场角为16°×34°的车灯投影光学系统,并对物面倾斜角度和光学系统结构进行了优化。此外,分别采用反向畸变处理方法和像素灰度调制方法用以解决车灯投影图像的梯形畸变和照度均匀性问题,并搭建了投影实验平台,对图像校正方法进行了验证。实验结果表明:校正后图像梯形畸变系数p1,p2分别从0.0932和0.3680下降至0.0835和0.0373,像面照度均匀性从83.2%提高到93.2%。本文通过对基于Micro LED的倾斜投影车灯光学系统进行优化设计及采用图像校正方法,实现了高光效、低畸变的车灯投影。

光子晶体Micro LED微显示阵列加工及光学特性分析

Micro LED器件具有高亮度、低功耗和高可靠性等优点,但Micro LED显示像素巨量转移和光提取效率低的问题为其应用带来挑战。开发了具有高转移效率和出光效率的单片64×64 Micro LED微显示阵列,提出了倒装型GaN基单片Micro LED微显示阵列芯片和Si基驱动电路的设计方法及集成工艺。通过时域有限差分(FDTD)方法对Micro LED微显示阵列光学特性进行了建模分析,设计了一种提高Micro LED微显示阵列出光效率的光提取结构。结合仿真结果,开发了一种在Micro LED蓝宝石衬底表面制备光子晶体结构的聚焦离子束(FIB)微纳加工工艺,并进行了器件加工。测试结果表明,蓝宝石衬底上加工的光子晶体结构可以提高Micro LED器件的表面出光效率,光功率平均值提升了16.36%,对Micro LED微显示阵列加工及微显示像素光提取问题具有借鉴意义。

Using microscopic video data measures for driver behavior analysis during adverse winter weather:opportunities and challenges

This paper presents a driver behavior analysis using microscopic video data measures including vehicle speed, lane-changing ratio, and time to collision. An analytical framework was developed to evaluate the effect of adverse winter weather conditions on highway driving behavior based on automated （computer） and manual methods. The research was conducted through two case studies. The first case study was conducted to evaluate the feasibility of applying an au- tomated approach to extracting driver behavior data based on 15 video recordings obtained in the winter 2013 at three dif- ferent locations on the Don Valley Parkway in Toronto, Canada. A comparison was made between the automated approach and manual approach, and issues in collecting data using the automated approach under winter conditions were identified. The second case study was based on high quality data collected in the winter 2014, at a location on Highway 25 in Montreal, Canada. The results demonstrate the effectiveness of the automated analytical framework in analyzing driver behavior, as well as evaluating the impact of adverse winter weather conditions on driver behavior. This approach could be applied to evaluate winter maintenance strategies and crash risk on highways during adverse winter weather conditions.

Design and Practice of The Teaching Mode of Flipped Classroom Based on Micro Video

This paper makes micro video combine with flipped classroom,constructs the teaching mode of flipped classroom based on micro video.This mode specifically include three teaching processes,such as design and practice of pre class task,design and practice of classroom interaction task,task and practice of comprehensive evaluation after class,and tries in the teaching of the course of Financial Management,improves the students＇ autonomous learning ability, enhances the participation degree of classroom teaching,promotes knowledge absorption of students,the effect of teaching is good.

The Design Principles of Micro-Video Production and In-Class Activities on the Base of Flipped Classroom

Flipped classroom is a brand-new teaching mode both at home and abroad. Its core is to reverse teaching sequence and teaching content by letting students watch self-made videos to learn relatively junior teaching content before class, thus leaving students adequate space to exert full activities in the classroom to complete knowledge absorption and consolidation. This article focus mainly on the design principles and relevant experiences of video production. In the meanwhile, the article also puts forward instructive suggestions for teachers to make appealing and stylistic videos as well as mobilize the enthusiasm of students.Video as the stepping stone only serves as a media to convey knowledge before class, the class is the core to convert students' traditional role to be the real master by a series of effective activities, which should be carefully designed by teachers. So the second focus of the articles falls on the design principles of in-class activities.

基于Micro CT的铜导线短路熔痕孔洞特征分析

导线短路是造成电气火灾的重要原因之一。现行国家标准中将导线短路熔痕分为起火前发生的一次短路熔痕和起火后造成的二次短路熔痕,然而现行国家标准中的鉴定仅停留在定性判断的阶段。火灾现场铜导线短路熔痕特征的量化分析研究是国内外研究人员主要关注的重点。本文应用Micro CT技术对铜导线短路熔痕进行断层扫描检测并重构铜导线短路熔痕的3D图像数据,在此基础上统计、归纳、总结铜导线短路熔痕内部孔洞形态及分布等孔洞特征。研究表明,Micro CT能够全面采集铜导线短路熔痕的整体形态和内部孔洞特征,一次短路熔痕与二次短路熔痕内部孔洞半径、表面积、紧密度的特征数据存在差别,可为短路熔痕定性和定量分析判据研究提供新的理论依据。

Micro-CT分析跟骨内骨小梁分布及结构特征

背景:跟骨位于足的后下部,受力较大。跟骨外形复杂且不规则,外周有较薄的皮质骨包绕,内部充满大量的骨小梁,探讨骨小梁的微观结构、走行及分布特征有助于提高对跟骨骨折的认识。目的:采用微计算机断层扫描仪(Micro-CT)扫描跟骨标本获得其影像资料,对其内部骨小梁结构进行分析,探讨跟骨内骨小梁的形态、分布及结构特征。方法:采用Micro-CT连续扫描干燥成人跟骨标本,扫描后获得影像图像,将其以DICOM格式存储。导入影像资料到Hiscan Analyzer软件,显示清晰完整的成人跟骨矢状面、冠状面、水平面的图像,逐层观察骨小梁的走行,依据骨小梁走行特点将跟骨矢状面分为6个部分,在以7 mm为标准的相同厚度下,每个部分选择1个49 mm2等面积的兴趣区,三维重建后获得跟骨及骨小梁的立体微观结构,二值化后运用软件计算感兴趣区域内骨小梁的体积分数、表面密度、骨小梁厚度、骨小梁间隙和骨小梁数量参数。结果与结论:①跟骨表面皮质层很薄,内部充满大量骨松质,在Gissane角的骨皮质明显增厚;②跟骨上部的骨小梁体积分数大于跟骨下部前端、中和三角区、跟骨下后部、跟骨结节部、跟骨底部,跟骨结节部的骨小梁体积分数大于跟骨下部前端、中和三角区、跟骨下后部、跟骨底部;跟骨结节部的骨小梁表面密度大于跟骨下部前端、中和三角区、跟骨底部,跟骨上部、跟骨下后部的骨小梁表面密度大于中和三角区;跟骨上部的骨小梁厚度大于跟骨结节部;中和三角区的骨小梁间隙大于跟骨上部、跟骨结节部;跟骨结节部的骨小梁数量大于中和三角区;③中和三角区主要分布杆状骨小梁,骨小梁表面密度最小、体积分数较小、骨小梁间隙最大;该部位骨质较疏松,受到高冲击力时抗压缩能力差,骨小梁最先发生断裂,是易发生骨折的部位。

Micro segment analysis of supercritical methane thermal-hydraulic performance and pseudo-boiling in a PCHE straight channel

The printed circuit heat exchanger(PCHE) is receiving wide attention as a new kind of compact heat exchanger and is considered as a promising vaporizer in the LNG process. In this paper, a PCHE straight channel in the length of 500 mm is established, with a semicircular cross section in a diameter of 1.2 mm.Numerical simulation is employed to investigate the flow and heat transfer performance of supercritical methane in the channel. The pseudo-boiling theory is adopted and the liquid-like, two-phase-like, and vapor-like regimes are divided for supercritical methane to analyze the heat transfer and flow features.The results are presented in micro segment to show the local convective heat transfer coefficient and pressure drop. It shows that the convective heat transfer coefficient in segments along the channel has a significant peak feature near the pseudo-critical point and a heat transfer deterioration when the average fluid temperature in the segment is higher than the pseudo-critical point. The reason is explained with the generation of vapor-like film near the channel wall that the peak feature related to a nucleateboiling-like state and heat transfer deterioration related to a film-boiling-like state. The effects of parameters, including mass flow rate, pressure, and wall heat flux on flow and heat transfer were analyzed.In calculating of the averaged heat transfer coefficient of the whole channel, the traditional method shows significant deviation and the micro segment weighted average method is adopted. The pressure drop can mainly be affected by the mass flux and pressure and little affected by the wall heat flux. The peak of the convective heat transfer coefficient can only form at high mass flux, low wall heat flux, and near critical pressure, in which condition the nucleate-boiling-like state is easier to appear. Moreover,heat transfer deterioration will always appear, since the supercritical flow will finally develop into a filmboiling-like state. So heat transfer deterioration should be taken seriously in the design and safe operation of vaporizer PCHE. The study of this work clarified the local heat transfer and flow feature of supercritical methane in microchannel and contributed to the deep understanding of supercritical methane flow of the vaporization process in PCHE.

Customized Convolutional Neural Network for Accurate Detection of Deep Fake Images in Video Collections

The motivation for this study is that the quality of deep fakes is constantly improving,which leads to the need to develop new methods for their detection.The proposed Customized Convolutional Neural Network method involves extracting structured data from video frames using facial landmark detection,which is then used as input to the CNN.The customized Convolutional Neural Network method is the date augmented-based CNN model to generate‘fake data’or‘fake images’.This study was carried out using Python and its libraries.We used 242 films from the dataset gathered by the Deep Fake Detection Challenge,of which 199 were made up and the remaining 53 were real.Ten seconds were allotted for each video.There were 318 videos used in all,199 of which were fake and 119 of which were real.Our proposedmethod achieved a testing accuracy of 91.47%,loss of 0.342,and AUC score of 0.92,outperforming two alternative approaches,CNN and MLP-CNN.Furthermore,our method succeeded in greater accuracy than contemporary models such as XceptionNet,Meso-4,EfficientNet-BO,MesoInception-4,VGG-16,and DST-Net.The novelty of this investigation is the development of a new Convolutional Neural Network(CNN)learning model that can accurately detect deep fake face photos.

Workout Action Recognition in Video Streams Using an Attention Driven Residual DC-GRU Network

Regular exercise is a crucial aspect of daily life, as it enables individuals to stay physically active, lowers thelikelihood of developing illnesses, and enhances life expectancy. The recognition of workout actions in videostreams holds significant importance in computer vision research, as it aims to enhance exercise adherence, enableinstant recognition, advance fitness tracking technologies, and optimize fitness routines. However, existing actiondatasets often lack diversity and specificity for workout actions, hindering the development of accurate recognitionmodels. To address this gap, the Workout Action Video dataset (WAVd) has been introduced as a significantcontribution. WAVd comprises a diverse collection of labeled workout action videos, meticulously curated toencompass various exercises performed by numerous individuals in different settings. This research proposes aninnovative framework based on the Attention driven Residual Deep Convolutional-Gated Recurrent Unit (ResDCGRU)network for workout action recognition in video streams. Unlike image-based action recognition, videoscontain spatio-temporal information, making the task more complex and challenging. While substantial progresshas been made in this area, challenges persist in detecting subtle and complex actions, handling occlusions,and managing the computational demands of deep learning approaches. The proposed ResDC-GRU Attentionmodel demonstrated exceptional classification performance with 95.81% accuracy in classifying workout actionvideos and also outperformed various state-of-the-art models. The method also yielded 81.6%, 97.2%, 95.6%, and93.2% accuracy on established benchmark datasets, namely HMDB51, Youtube Actions, UCF50, and UCF101,respectively, showcasing its superiority and robustness in action recognition. The findings suggest practicalimplications in real-world scenarios where precise video action recognition is paramount, addressing the persistingchallenges in the field. TheWAVd dataset serves as a catalyst for the development ofmore robust and effective fitnesstracking systems and ultimately promotes healthier lifestyles through improved exercise monitoring and analysis.

Advances in microfluidic-based DNA methylation analysis

DNA methylation has been extensively investigated in recent years,not least because of its known relationship with various diseases.Progress in analytical methods can greatly increase the relevance of DNA methylation studies to both clinical medicine and scientific research.Microflu-idic chips are excellent carriers for molecular analysis,and their use can provide improvements from multiple aspects.On-chip molecular analysis has received extensive attention owing to its advantages of portability,high throughput,low cost,and high efficiency.In recent years,the use of novel microfluidic chips for DNA methylation analysis has been widely reported and has shown obvious superiority to conventional methods.In this review,wefirst focus on DNA methylation and its applications.Then,we discuss advanced microfluidic-based methods for DNA methylation analysis and describe the great progress that has been made in recent years.Finally,we summarize the advantages that microfluidic technology brings to DNA methylation analysis and describe several challenges and perspectives for on-chip DNA methylation analysis.This review should help researchers improve their understanding and make progress in developing microfluidic-based methods for DNA methylation analysis.

Pulse rate estimation based on facial videos:an evaluation and optimization of the classical methods using both self-constructed and public datasets

Pulse rate is one of the important characteristics of traditional Chinese medicine pulse diagnosis,and it is of great significance for determining the nature of cold and heat in diseases.The prediction of pulse rate based on facial video is an exciting research field for getting palpation information by observation diagnosis.However,most studies focus on optimizing the algorithm based on a small sample of participants without systematically investigating multiple influencing factors.A total of 209 participants and 2,435 facial videos,based on our self-constructed Multi-Scene Sign Dataset and the public datasets,were used to perform a multi-level and multi-factor comprehensive comparison.The effects of different datasets,blood volume pulse signal extraction algorithms,region of interests,time windows,color spaces,pulse rate calculation methods,and video recording scenes were analyzed.Furthermore,we proposed a blood volume pulse signal quality optimization strategy based on the inverse Fourier transform and an improvement strategy for pulse rate estimation based on signal-to-noise ratio threshold sliding.We found that the effects of video estimation of pulse rate in the Multi-Scene Sign Dataset and Pulse Rate Detection Dataset were better than in other datasets.Compared with Fast independent component analysis and Single Channel algorithms,chrominance-based method and plane-orthogonal-to-skin algorithms have a more vital anti-interference ability and higher robustness.The performances of the five-organs fusion area and the full-face area were better than that of single sub-regions,and the fewer motion artifacts and better lighting can improve the precision of pulse rate estimation.

高亮绿光氮化镓基Micro-LED微型显示器制备

Micro-LED作为一种新型的显示技术,具有对比度高、响应快及寿命长等优点,已成为当前研究的热点。然而,尽管潜力巨大,Micro-LED技术的商业化之路仍面临诸多技术上的挑战与瓶颈。本文旨在探讨高亮绿光氮化镓基Micro-LED微型显示器的制备过程及其相关技术。基于WVGA041全数字信号电路CMOS硅基驱动电路,制作了0.41 inch、分辨率为800×480的主动式单色绿光Micro-LED微型显示器。利用高精度倒装焊接技术实现了CMOS驱动电路与LED发光芯片的电气连接。结果表明,制备出LED显示芯片正常启亮电压为2.8V,EL光谱峰值波长524nm;在硅基CMOS电路驱动范围内,Micro-LED微型显示器在5V电压下,器件亮度为108000cd/m^(2)(最大亮度可达250000 cd/m^(2)),电流密度达到0.61A/cm^(2)时色坐标为(0.175,0.756)。当电流密度从0.3A/cm^(2)增加到1.3A/cm^(2)时,色坐标从(0.178,0.757)变化到(0.175,0.746),器件的色稳定性能够满足实际应用要求。

Effect of dry-wet cycles on dynamic properties and microstructures of sandstone:Experiments and modelling

Underground pumped storage power plant(UPSP)is an innovative concept for space recycling of abandoned mines.Its realization requires better understanding of the dynamic performance and durability of reservoir rock.This paper conducted ultrasonic detection,split Hopkinson pressure bar(SHPB)impact,mercury intrusion porosimetry(MIP),and backscatter electron observation(BSE)tests to investigate the dynamical behaviour and microstructure of sandstone with cyclical dry-wet damage.A coupling FEM-DEM model was constructed for reappearing mesoscopic structure damage.The results show that dry-wet cycles decrease the dynamic compressive strength(DCS)with a maximum reduction of 39.40%,the elastic limit strength is reduced from 41.75 to 25.62 MPa.The sieved fragments obtain the highest crack growth rate during the 23rd dry-wet cycle with a predictable life of 25 cycles for each rock particle.The pore fractal features of the macropores and micro-meso pores show great differences between the early and late cycles,which verifies the computational statistics analysis of particle deterioration.The numerical results show that the failure patterns are governed by the strain in pre-peak stage and the shear cracks are dominant.The dry-wet cycles reduce the energy transfer efficiency and lead to the discretization of force chain and crack fields.

Micro RNAs与急性心肌梗死关系的研究进展

急性心肌梗死(acute myocardial infarction,AMI)是冠状动脉疾病最严重的表现,其引起的心肌组织损伤可促进心力衰竭的发展。尽管近些年由于生活方式的改变、治疗方式(如经皮冠状动脉介入治疗)的发展使AMI的预后得到了改善,但是AMI依旧每年危害着全球700多万人的身心健康,AMI仍然是世界范围内高发病率和高死亡率的主要疾病之一[1]。微小RNA(micro RNAs,miRNAs)是在20世纪90年代被发现的,mi RNAs的研究已经迅速发展成为一个成熟而广阔的领域。mi RNAs存在于几乎所有类型的细胞和细胞的病理生理活动中,包括与心血管系统相关的细胞。本文将mi RNAs对AMI病理生理进程的影响进行综述,希望为临床治疗提供新思路。

Trends in Event Understanding and Caption Generation/Reconstruction in Dense Video:A Review

Video description generates natural language sentences that describe the subject,verb,and objects of the targeted Video.The video description has been used to help visually impaired people to understand the content.It is also playing an essential role in devolving human-robot interaction.The dense video description is more difficult when compared with simple Video captioning because of the object’s interactions and event overlapping.Deep learning is changing the shape of computer vision(CV)technologies and natural language processing(NLP).There are hundreds of deep learning models,datasets,and evaluations that can improve the gaps in current research.This article filled this gap by evaluating some state-of-the-art approaches,especially focusing on deep learning and machine learning for video caption in a dense environment.In this article,some classic techniques concerning the existing machine learning were reviewed.And provides deep learning models,a detail of benchmark datasets with their respective domains.This paper reviews various evaluation metrics,including Bilingual EvaluationUnderstudy(BLEU),Metric for Evaluation of Translation with Explicit Ordering(METEOR),WordMover’s Distance(WMD),and Recall-Oriented Understudy for Gisting Evaluation(ROUGE)with their pros and cons.Finally,this article listed some future directions and proposed work for context enhancement using key scene extraction with object detection in a particular frame.Especially,how to improve the context of video description by analyzing key frames detection through morphological image analysis.Additionally,the paper discusses a novel approach involving sentence reconstruction and context improvement through key frame object detection,which incorporates the fusion of large languagemodels for refining results.The ultimate results arise fromenhancing the generated text of the proposedmodel by improving the predicted text and isolating objects using various keyframes.These keyframes identify dense events occurring in the video sequence.

Survey on Video Security:Examining Threats,Challenges,and Future Trends

Videos represent the most prevailing form of digital media for communication,information dissemination,and monitoring.However,theirwidespread use has increased the risks of unauthorised access andmanipulation,posing significant challenges.In response,various protection approaches have been developed to secure,authenticate,and ensure the integrity of digital videos.This study provides a comprehensive survey of the challenges associated with maintaining the confidentiality,integrity,and availability of video content,and examining how it can be manipulated.It then investigates current developments in the field of video security by exploring two critical research questions.First,it examine the techniques used by adversaries to compromise video data and evaluate their impact.Understanding these attack methodologies is crucial for developing effective defense mechanisms.Second,it explores the various security approaches that can be employed to protect video data,enhancing its transparency,integrity,and trustworthiness.It compares the effectiveness of these approaches across different use cases,including surveillance,video on demand(VoD),and medical videos related to disease diagnostics.Finally,it identifies potential research opportunities to enhance video data protection in response to the evolving threat landscape.Through this investigation,this study aims to contribute to the ongoing efforts in securing video data,providing insights that are vital for researchers,practitioners,and policymakers dedicated to enhancing the safety and reliability of video content in our digital world.