Real-time Rescue Target Detection Based on UAV Imagery for Flood Emergency Response

Timely acquisition of rescue target information is critical for emergency response after a flood disaster.Unmanned Aerial Vehicles(UAVs)equipped with remote sensing capabilities offer distinct advantages,including high-resolution imagery and exceptional mobility,making them well suited for monitoring flood extent and identifying rescue targets during floods.However,there are some challenges in interpreting rescue information in real time from flood images captured by UAVs,such as the complexity of the scenarios of UAV images,the lack of flood rescue target detection datasets and the limited real-time processing capabilities of the airborne on-board platform.Thus,we propose a real-time rescue target detection method for UAVs that is capable of efficiently delineating flood extent and identifying rescue targets(i.e.,pedestrians and vehicles trapped by floods).The proposed method achieves real-time rescue information extraction for UAV platforms by lightweight processing and fusion of flood extent extraction model and target detection model.The flood inundation range is extracted by the proposed method in real time and detects targets such as people and vehicles to be rescued based on this layer.Our experimental results demonstrate that the Intersection over Union(IoU)for flood water extraction reaches an impressive 80%,and the IoU for real-time flood water extraction stands at a commendable 76.4%.The information on flood stricken targets extracted by this method in real time can be used for flood emergency rescue.

Real eigenvalues determined by recursion of eigenstates

Quantum physics is primarily concerned with real eigenvalues,stemming from the unitarity of time evolutions.With the introduction of PT symmetry,a widely accepted consensus is that,even if the Hamiltonian of the system is not Hermitian,the eigenvalues can still be purely real under specific symmetry.Hence,great enthusiasm has been devoted to exploring the eigenvalue problem of non-Hermitian systems.In this work,from a distinct perspective,we demonstrate that real eigenvalues can also emerge under the appropriate recursive condition of eigenstates.Consequently,our findings provide another path to extract the real energy spectrum of non-Hermitian systems,which guarantees the conservation of probability and stimulates future experimental observations.

A Stochastic Model to Assess the Epidemiological Impact of Vaccine Booster Doses on COVID-19 and Viral Hepatitis B Co-Dynamics with Real Data

A patient co-infected with COVID-19 and viral hepatitis B can be atmore risk of severe complications than the one infected with a single infection.This study develops a comprehensive stochastic model to assess the epidemiological impact of vaccine booster doses on the co-dynamics of viral hepatitis B and COVID-19.The model is fitted to real COVID-19 data from Pakistan.The proposed model incorporates logistic growth and saturated incidence functions.Rigorous analyses using the tools of stochastic calculus,are performed to study appropriate conditions for the existence of unique global solutions,stationary distribution in the sense of ergodicity and disease extinction.The stochastic threshold estimated from the data fitting is given by:R_(0)^(S)=3.0651.Numerical assessments are implemented to illustrate the impact of double-dose vaccination and saturated incidence functions on the dynamics of both diseases.The effects of stochastic white noise intensities are also highlighted.

基于Real ESRGAN的视频修复系统研究

图像修复和视频修复是计算机视觉的一项重要任务,其中图像修复又是视频修复的基础。为此,如何有效提升图像质量是实现视频质量提升的关键。传统的图像修复算法主要以样本信息为基础,通过对样本内容的扩撒来实现对破损区域的修复;由于这种方式对于图像样本有一定要求,从而制约传统图像修复技术的发展。为此,以生成新图像内容为基础的神经网络如GAN的出现,为图像修复技术转向深度学习提供方向。该课题主要以Real ESRGAN网络的图像修复技术为基础,通过对音频视频数据的隔离处理以及相同帧数据的优化和标记,构建视频修复处理流程。通过对随机视频样本的测试,并通过对单帧图片质量和视频数据流畅性与协调性的评估,该视频处理方法表现出较好的系统性能。

A Comparative Study between Landmark Based and Real Time Ultrasound Guided Sub Arachnoid Block

Background: Sub arachnoid block (SAB) performed by traditional landmark palpation technique can be inaccurate. This problem is exacerbated by altered patient anatomy due to obesity and age-related changes. A pre-procedural ultrasound scan of the lumbar spine has been shown to be of benefit in guiding lumbar epidural insertion in obstetric patients. Information on the use of real-time ultrasound (RUS) guided SAB, to date, been limited. This study compared RUS guided SAB to traditional landmark guided technique in patients undergoing spinal anesthesia for different surgical procedures. Methods: This was a prospective, single center, comparative observational study conducted in the department of anesthesiology at our center. 560 patients who underwent spinal anesthesia either by landmark based technique or real-time ultrasound-guided methods. The primary outcome was the first attempt success rate of dural puncture when employing the two methods. Results: Baseline characteristics were similar in the two study groups. The first attempt success rate of dural puncture in landmark guided group was 64.3% compared to 72.6% in the ultrasound guided group. This difference was not statistically significant. The procedure performance time was significantly shorter with landmark palpation compared to use of real-time ultrasound guided method. Conclusion: Use of RUS-guided technique does not significantly improve the first attempt success rate of SAB dural puncture during spinal anesthesia compared to the traditional landmark-guided technique.

Research on the Impact and Opportunities of the Digital Economy Promoting the Development of Real Economy

The digital economy has infused vitality into the transformation and development of the real economy,urging enterprises to break through core technological barriers,address bottleneck issues,and improve their core competitiveness.It fosters the comprehensive digital transformation of agriculture,manufacturing,and service sectors,improving the dynamism of the real economy and fostering more consumption hotspots.Efforts are underway to enhance industrial supply chains and innovation chains,optimize regional resource allocation,and promote a virtuous cycle within the real economy.Initiatives are being undertaken to standardize the development of digital economic platforms,promote the high-quality development of regional economies,and leverage the advantages of the socialist market economy with Chinese characteristics.

An Effective Prediction Method for Supporting Decision Making in Real Estate Area Selection

Real estate has been a dominant industry in many countries. One problem for real estate companies is determining the most valuable area before starting a new project. Previous studies on this issue mainly focused on market needs and economic prospects, ignoring the impact of natural disasters. We observe that natural disasters are important for real estate area selection because they will introduce considerable losses to real estate enterprises. Following this observation, we first develop a self-defined new indicator named Average Loss Ratio to predict the losses caused by natural disasters in an area. Then, we adopt the existing ARIMA model to predict the Average Loss Ratio of an area. After that, we propose to integrate the TOPSIS model and the Grey Prediction Model to rank the recommendation levels for candidate areas, thereby assisting real estate companies in their decision-making process. We conduct experiments on real datasets to validate our proposal, and the results suggest the effectiveness of the proposed method.

Research on Value Evaluation Method of Investment Project Based on Fuzzy Composite Real Options

Venture capital investments are characterized by high input,high yield,and high risk.Due to the complexity of the market environment,stage-by-stage investment is becoming increasingly important.Traditional evaluation methods like comparison,proportion,maturity,internal rate of return,scenario analysis,decision trees,and net present value cannot fully consider the uncertainty and stage characteristics of the project.The fuzzy real options method addresses this by combining real option theory,fuzzy number theory,and composite option theory to provide a more accurate and objective evaluation of Public-Private Partnership(PPP)projects.It effectively considers the interaction of options and the ambiguity of project parameters,making it a valuable tool for project evaluation in the context of venture capital investment.

Real与Media流媒体技术比较

通过研究和实例设计，探讨了Ｒｅａｌ流媒体技术和Ｍｅｄｉａ流媒体技术的异同之处，以及在应用当中各自的优缺点。

Real流媒体技术及其在远程教学中的应用

研究目的是希望通过对Ｒｅａｌ流媒体及其软件开发包的研究，能实现一套以Ｒｅａｌ系统为平台的远程教育系统，实现同步和异步的远程教学活动。

Real-time PCR和PCR方法快速检测犬细小病毒

为适应出入境口岸对进出境宠物快速检疫的需要,本研究在建立PCR方法检测犬细小病毒(CPV)的基础上,进一步采用Taqman探针技术建立了快速检测CPV的Real-time PCR方法。通过灵敏度对比试验,证实Real-time PCR方法比PCR方法检测灵敏度显著提高。通过对大量不同采样部位样品的检测证实,本研究建立的Real-time PCR和PCR方法具有较高的可靠性,并可显著提高CPV的阳性检出率。

Real Time PCR研究进展及其在海洋病原生物检测中的应用

Real Time PCR,即实时监测PCR扩增产物并进行解析的方法,目前已广泛应用于分子生物学研究的各个领域。Real Time PCR技术秉承及发展了普通PCR的快速、高灵敏度检出等优点,同时克服了普通PCR不能准确定量、容易污染等缺点,无需在反应结束后通过电泳操作确认扩增产物。目前,Real Time PCR可设计多对引物在同一反应体系中同时对多个靶基因进行扩增,实现多重实时定量检测。Real Time PCR使PCR技术发生了质的飞跃,扩展了PCR技术的应用范畴,是一种具有划时代意义的技术。本文主要介绍Real Time PCR的主要原理、解析方法、技术发展趋势及其在海洋病原生物检测方面的应用。

Real-time PCR和常规PCR方法快速鉴定肉骨粉中的牛源性成份

疯牛病是一种严重危害动物和人类健康的疾病 ,其病原朊病毒可以通过食物链进行传播 ,因此建立准确的检测牛源性成份的方法非常重要。我们采用常规PCR和Real_timePCR中的TaqMan技术建立了快速鉴定牛源性成份的方法 ,使用Chelex_10 0提取肉骨粉中的DNA ,过程简单可靠仅需要 2 0min左右。对不同含量的牛肉骨粉进行检测 ,常规PCR能够检测到的最低含量是 0 0 0 1% ,而Real_timePCR对相同的样品进行检测所得到的灵敏度更高 ,最高可达到 0 0 0 0 1% ,两种PCR方法的鉴定过程都非常简单快速 ,各需要 2h左右。

基因Ⅰ型草鱼呼肠孤病毒TaqMan Real-Time PCR检测方法的建立及应用

为了建立和应用可检测基因I型草鱼呼肠孤病毒（GCRV）的荧光定量检测方法，实验根据基因I型GCRV的s6保守序列，分别设计扩增目的条带661bp普通引物（P1、P2）、扩增目的条带159bp荧光定量引物（F1、F2）和一条探针；同时构建含有目的片段的PVAX1-S6作为标准质粒，10倍梯度稀释构建质粒拷贝数与Ct值的标准曲线（Y=-3．389X＋38．076）。结果表明，此方法在3．9×10^7～3．9×10^1拷贝／uL之间相关性较好，R2为0．992，最小检测量为4拷贝／uL；且与基因Ⅱ型、Ⅲ型GCRV以及其他病原核酸无交叉反应。运用该方法检测16份草鱼出血病疑似样品，阳性结果为4份；而普通PCR检测仅2份显示阳性。本研究建立了针对基因I型GCRV的荧光定量检测方法，具有高效、特异、灵敏、可重复性强的优点，适合于目前基因I型GCRV的临床快速检测和病毒定量分析。

金黄色葡萄球菌基因表达的DNA扣除法Real-time RT PCR相对定量分析

【目的】金黄色葡萄球菌作为一种分布广泛的致病微生物和研究革兰氏阳性菌遗传背景的模式菌株,利用real-time RT PCR对相关毒素及调控基因进行表达定量分析,在生物、医学、食品检测等领域具有较大研究价值。【方法】对制备好的反转录(RT,含有cDNA和DNA)和非反转录(RT—,仅含DNA)样品进行Real-time PCR检测,根据经典(1+E)—△△Ct相对定量算法并结合PCR效率公式建立一种基因表达相对定量分析的DNA扣除法,将得到的Ct值转换为各样品含量,从RT样品中扣除RT—样品的量,无需DNaseⅠ酶解处理就可以去除DNA的影响,RT—样品的检测结果还可同时作为稳定的DNA内参。【结果】采用以上方法分析金黄色葡萄球菌肠毒素A基因(sea)、16S rRNA和RNAⅢ的表达情况,在含有葡萄糖的NB培养基中sea的相对转录水平随着葡萄糖浓度的增大而升高,RNAⅢ的相对转录水平随葡萄糖浓度的变化而产生小幅度的波动,16S rRNA在菌体生长初期时的表达量较为稳定;与绝对定量法比较,结果差异较小(均小于15%),且差异不显著(p>0.05)。【结论】这种基于DNA扣除法的Real-time RT PCR相对定量方法可以有效的对金黄色葡萄球菌的基因表达进行分析。

Real-time RT-PCR检测西尼罗病毒一步法的建立

目的建立针对西尼罗病毒E基因的一步法Real-time RT-PCR检测方法,用于西尼罗病毒感染样本的快速准确检测和定量。方法针对西尼罗病毒的保守基因E设计引物和探针,建立一步法Real-time RT-PCR反应方法并分析敏感性和特异性。结果本研究建立的一步法Real-time RT-PCR方法可以特异性检测出西尼罗病毒,不与日本脑炎病毒及其他病毒产生交叉反应。该方法的最低检出浓度为3.6×102copies/μl,标准曲线的线性范围为3.6×102～3.6×107copies/μl。结论本研究建立的一步法real-time RT-PCR方法敏感性和特异性较高,且不易出现污染引起的假阳性结果,适合用于西尼罗病毒感染样本的检测。

荧光Real-time PCR鉴定鸡胸骨总RNA质量

为了更准确地鉴定提取鸡骨总RNA的质量,试验分别用核酸蛋白检测仪、1%琼脂糖凝胶电泳和荧光Real-time PCR检测评价3种不同的方法提取成年鸡胸骨总RNA的质量。结果显示,荧光Real-time PCR可更好地鉴定提取的骨总RNA的质量。用核酸蛋白检测仪、1%琼脂糖凝胶电泳能粗略检测RNA的纯度和完整性,但不能反映提取过程中是否引起基因不均一的减少,所检测的纯度也不能精确反映RNA的反转录效率。

赤羽病病毒Real-time RT-PCR检测方法的建立与初步应用

为了研究赤羽病病毒的检测方法，试验根据GenBank中已发表的赤羽病病毒（Akabanevirus，AKAV）的s基因序列建立了检测AKAV的Real-timeRT—PCR方法。结果表明：该方法对AKAV的检测有高度的特异性，与牛病毒性腹泻病毒（BVDV）、传染性牛鼻气管炎病毒（IBRV）等13种病毒均无交叉反应；Real—timeRT—PCR能够扩增稀释度为1×10^-5的病毒RNA（核酸含量约1．18ng／μL），比普通RT—PCR高出1000倍；用此方法检测130份奶牛血清样品与1份流产胎儿病料，均未检测到阳性样本；AKAV在血清模拟样品中可被有效检出。

建立Real流媒体技术的网络教学系统

目前流媒体技术的主要格式有Media 和Real 两种。其中的Real 流媒体由于具有众多的技术优势和特点被作为我们构建网络多媒体教学系统的基本技术。本文我们着重介绍采用Real流媒体技术在网络教学中的实现。