Dependable Deployment Method for Multiple Applications in Cloud Services Delivery Network

The mutual-interference phenomenon among multiple applications delivered as services through Cloud Services Delivery Network(CSDN)influences their QoS seriously.In order to deploy multiple applications dependably and efficiently,we propose the Multiple Applications Co-Exist(MACE)method.MACE classifies multiple applications into different types and deploys them using isolation to some extent.Meanwhile,resource static allocation,dynamic supplement and resource reserved mechanism to minimize mutual-interference and maximize resource utilization are designed.After MACE is applied to a real large-scale CSDN and evaluated through 6-month measurement,we find that the CSDN load is more balanced,the bandwidth utilization increases by about 20%,the multiple applications'potential statistical multiplexing ratio decreases from 12% to 5%,and the number of complaint events affecting the dependability of CSDN services caused by multiple applications'mutual-interference has dropped to 0.Obviously,MACE offers a tradeoff and improvement for the dependability and efficiency goals of CSDN.

Protein Flexibility and Multiple Docking in Ligand Docking and Virtual Screening to the BRAF(TypeⅠ1/2)Inhibitors

BRAF has been recognized as a promising target for cancer therapy. A number of crystal structures have been published. Molecular docking is one of the most effective techniques in the field of computer-aided drug design（CADD）. Appropriate protein conformation and docking method are essential for the successful virtual screening experiments. One approach considering protein flexibility and multiple docking methods was proposed in this study. Six DFG-in/αC-helix-out crystal structures of BRAF, three docking programs（Glide, GOLD and Ligand Fit） and 12 scoring functions were applied for the best combination by judging from the results of pose prediction and retrospective virtual screening（VS）. The most accurate results（mean RMSD of about 0.6 A） of pose prediction were obtained with two complex structures（PDB： 3 C4 C and 3 SKC） using Glide SP. From the retrospective VS, the most active compounds were identified by using the complex structure of 3 SKC, indicated by a ROC/AUC score of 0.998 and an EF of 20.6 at 5% of the database screen with Glide-SP. On the whole, PDB 3 SKC could achieve a higher rate of correct reproduction, a better enrichment and more diverse compounds. A comparison of 3 SKC and the other X-ray crystal structures led to a rationale for the docking results. PDB 3 SKC could achieve a broad range of sulfonamide substitutions through an expanded hydrophobic pocket formed by a further shift of the αC-helix. Our study emphasized the necessity and significance of protein flexibility and scoring functions in both ligand docking and virtual screening.

Clinical Application of Preliminary Breast Cancer Screening for Dense Breasts Using Real-Time AI-Powered Ultrasound with Deep-Learning Computer Vision

Objective:We propose a solution that is backed by cloud computing,combines a series of AI neural networks of computer vision;is capable of detecting,highlighting,and locating breast lesions from a live ultrasound video feed,provides BI-RADS categorizations;and has reliable sensitivity and specificity.Multiple deep-learning models were trained on more than 300,000 breast ultrasound images to achieve object detection and regions of interest classification.The main objective of this study was to determine whether the performance of our Al-powered solution was comparable to that of ultrasound radiologists.Methods:The noninferiority evaluation was conducted by comparing the examination results of the same screening women between our AI-powered solution and ultrasound radiologists with over 10 years of experience.The study lasted for one and a half years and was carried out in the Duanzhou District Women and Children's Hospital,Zhaoqing,China.1,133 females between 20 and 70 years old were selected through convenience sampling.Results:The accuracy,sensitivity,specificity,positive predictive value,and negative predictive value were 93.03%,94.90%,90.71%,92.68%,and 93.48%,respectively.The area under the curve(AUC)for all positives was 0.91569 and the AUC for all negatives was 0.90461.The comparison indicated that the overall performance of the AI system was comparable to that of ultrasound radiologists.Conclusion:This innovative AI-powered ultrasound solution is cost-effective and user-friendly,and could be applied to massive breast cancer screening.

Scheduling Method Based on Backfill Strategy for Multiple DAGs in Cloud Computing

Multiple DAGs scheduling strategy is a critical factor affecting resource utilization and operating cost in the cloud computing. To solve the problem that multiple DAG scheduling cannot meet the resource utilization and reliability when multiple DAGs arrive at different time, the multiple DAGs scheduling problem can be transformed into a single DAG scheduling problem with limited resource available time period through multiple DAGs scheduling model based on backfill. On the basis of discussing the available time period description of resources and the sorting of task scheduling when the available time period is limited, the multiple DAGs scheduling strategy is proposed based on backfill. The experimental analysis shows that this strategy can effectively shorten the makespan and improve the resources utilization when multiple DAGs arrive at different time.

应用Multiple-SNaPshot技术无创性产前检测唐氏综合征

目的：探讨1种相对便捷。准确。经济的适用于杂合型SNP位点的无创性产前检测胎儿唐氏综合征的方法。方法：选择50例孕整倍体胎儿（孕15-21周）。13例孕21三体胎儿（孕19-26周）的母血浆样本,应用Multiple-SNaPshot法检测胎盘源性PLAC4基因上5个SNP等位基因的基因比率及其杂合性,从而对杂合型SNP位点的胎儿无创性产前检测唐氏综合征;同时对我国苏南地区200例人群的5个SNP位点进行基因型别研究。结果：从63例单胎孕妇外周血中成功提取到PLAC4 mRNA,检测出17例PLAC4上为杂合型SNP的样本,通过分析SNP等位基因比率检测出14例正常整倍体胎儿及3例21三体胎儿。苏南地区人群PLAC4上Rs8130833和Rs4818219位点的杂合度分别为0.278和0.343。结论：对PLAC4基因上为杂合型SNP位点的胎儿,用Multiple-SNaPshot法检测其等位基因比率可用于无创性产前筛查唐氏综合征。苏南地区人群PLAC4基因上SNP杂合度较高的位点有Rs8130833和Rs4818219。

Optimization of the OCO-2 Cloud Screening Algorithm and Evaluation against MODIS and TCCON Measurements over Land Surfaces in Europe and Japan

A method to tighten the cloud screening thresholds based on local conditions is used to provide more stringent schemes for Orbiting Carbon Observatory-2(OCO-2)cloud screening algorithms.Cloud screening strategies are essential to remove scenes with significant cloud and/or aerosol contamination from OCO-2 observations,which helps to save on the data processing cost and ensure high quality retrievals of the column-averaged CO2 dry air mole fraction(XCO2).Based on the radiance measurements in the 0.76μm O2A band,1.61μm(weak),and 2.06μm(strong)CO2 bands,the current combination of the A-Band Preprocessor(ABP)algorithm and Iterative Maximum A Posteriori(IMAP)Differential Optical Absorption Spectroscopy(DOAS)Preprocessor(IDP)algorithm passes around 20%-25%of all soundings,which means that some contaminated scenes also pass the screening process.In this work,three independent pairs of threshold parameters used in the ABP and IDP algorithms are sufficiently tuned until the overall pass rate is close to the monthly clear-sky fraction from the MODIS cloud mask.The tightened thresholds are applied to observations over land surfaces in Europe and Japan in 2016.The results show improvement of agreement and positive predictive value compared to the collocated MODIS cloud mask,especially in summer and fall.In addition,analysis indicates that XCO2 retrievals with more stringent thresholds are in closer agreement with measurements from collocated Total Carbon Column Observing Network(TCCON)sites.

Brain organoids are new tool for drug screening of neurological diseases

At the level of in vitro drug screening,the development of a phenotypic analysis system with highcontent screening at the core provides a strong platform to support high-throughput drug screening.There are few systematic reports on brain organoids,as a new three-dimensional in vitro model,in terms of model stability,key phenotypic fingerprint,and drug screening schemes,and particula rly rega rding the development of screening strategies for massive numbers of traditional Chinese medicine monomers.This paper reviews the development of brain organoids and the advantages of brain organoids over induced neurons or cells in simulated diseases.The paper also highlights the prospects from model stability,induction criteria of brain organoids,and the screening schemes of brain organoids based on the characteristics of brain organoids and the application and development of a high-content screening system.

De novo multiple primary carcinomas in a patient after liver transplantation:A case report

BACKGROUND Liver transplantation(LT)is the most effective treatment strategy for advanced liver diseases.With the increasing survival rate and prolonged survival time,the postoperative long-term complications of LT recipients are becoming an important concern.Among them,the newly developed cancer after LT is the second complication and cause of LT-related death after cardiovascular disease.At present,few papers have reported multiple primary carcinomas(MPCs)after LT.Herein,we retrospectively analyzed an MPC case with gastric cancer and lung cancer after LT.CASE SUMMARY Herein,we retrospectively analyzed an MPC case with de novo gastric cancer and lung cancer after LT with no obvious complaints.Forty-one months after LT,the patient underwent radical distal gastrectomy(Billroth II)for intramucosal signet ring cell carcinoma,and then thoracoscopic wedge resection of the right lower lobe of the right lung and localized lymph node dissection 2 mo later.Therefore,paying attention to follow-up in LT recipients with early detection and intervention of de novo MPCs is the key to improving the survival rate and quality of life of LT recipients.CONCLUSION De novo MPCs after LT are rare,and the prognosis is poorer.However,early detection and related intervention can significantly improve the prognosis of patients.Therefore,we recommend that liver transplant recipients should be followed and screened for newly developed malignant tumors to improve the survival rate and quality of life.

BFS-SVM Classifier for QoS and Resource Allocation in Cloud Environment

In cloud computing Resource allocation is a very complex task.Handling the customer demand makes the challenges of on-demand resource allocation.Many challenges are faced by conventional methods for resource allocation in order tomeet the Quality of Service(QoS)requirements of users.For solving the about said problems a new method was implemented with the utility of machine learning framework of resource allocation by utilizing the cloud computing technique was taken in to an account in this research work.The accuracy in the machine learning algorithm can be improved by introducing Bat Algorithm with feature selection(BFS)in the proposed work,this further reduces the inappropriate features from the data.The similarities that were hidden can be demoralized by the Support Vector Machine(SVM)classifier which is also determine the subspace vector and then a new feature vector can be predicted by using SVM.For an unexpected circumstance SVM model can make a resource allocation decision.The efficiency of proposed SVM classifier of resource allocation can be highlighted by using a singlecell multiuser massive Multiple-Input Multiple Output(MIMO)system,with beam allocation problem as an example.The proposed resource allocation based on SVM performs efficiently than the existing conventional methods;this has been proven by analysing its results.

空间分集光密钥生成的信道相关性影响

利用无线光信道本身的特性实现光密钥生成和分发,可为高速星地保密通信提供安全和高效的保障。开展了无线光信道空间分集密钥生成系统相邻子信道相关性的研究。通过实现功率谱反演产生的Kolmogorov大气湍流相位屏,构建了无线光信道(WOC)信道中的多输入多输出(MIMO)模型,采用蒙特卡罗模拟了高斯光束经大气湍流传输特性,比较了不同湍流强度和光束传输距离对光强分布的影响,分析了大气湍流强度、相邻两接收孔径之间的距离、接收孔径、传输距离、光波波长对相邻子信道相关性的影响。结果表明,相邻两接收孔径接收到的光信号功率的相关性随相邻两接收孔径的直径和波长的增大而增加,随相邻两接收孔径之间的距离、光波的传输距离、湍流强度的增加而减小。在大气折射率结构常数C_(n)^(2)为5×10^(-14)m^(-2/3)、接收口径为0.03 m、传输距离为2000 m的近地水平链路条件下,相邻信道之间的距离在0.07 m时接收到的光信号功率的相关性近似为零,此时两个相邻信道彼此独立。该结果可为建立空间分集大气光信道密钥提取系统提供参考。

基于TOF相机的振动筛上物料状态动态监测方法

振动筛筛上物料载荷异常不仅影响生产效率还可能导致安全隐患,实时准确地监测筛上物料状态具有重要意义。针对传统人工监测方法劳动强度大、速度慢、有极高安全隐患并且不容易发现设备微小故障等问题。基于TOF相机物料动态监测技术,提出了一种联合KD树与帧差法的点云数据补全方法和基于曲面重构的筛上物料动态监测方法。该点云数据补全方法有效修补了因筛上物料表面水分和物料缝隙导致的TOF相机拍摄过程中的点云数据缺失问题,通过对补全后的筛上物料进行点云曲面重构分析,判断欠载、过载、左偏载和右偏载四种筛上物料状态,实时监测筛上物料状态。研究通过TOF相机直接获取筛上物料状态信息,对筛上物料实时检测,减少了人工干预的需求且具备实时性。为筛上物料状态实时监测问题提供了一个可靠的解决方案。

物料冲击对椭圆振动筛筛分性能的动态影响

为了研究物料冲击对振动筛动态特性的影响,加工了某型三轴椭圆振动筛样机。首先,建立简化后的筛机模型,采用离散元法与多体动力学相结合的方法对椭圆振动筛的筛分过程进行数值模拟;其次,引入有限元法对物料冲击下的筛面进行分析,以筛分效率、物料运输速度、筛上物质量和最大冲击力为筛分性能的评价指标;最后,通过试验对其不同工况下的结构振动和应变信号进行了测试和分析,研究了振幅、振频、筛面倾角以及入料速度对筛分性能的影响,揭示了常规筛机评价指标与振动参数之间的关系,为多目标评价和振动筛机优化设计提供了参考。

基于足迹理论的钢铁企业低碳选址评价方法

为推动钢铁企业在资源约束下完成产业升级,在环境约束下提升技术效率,提出一种基于足迹理论的钢铁企业低碳选址评价方法。首先,在钢铁企业常规选址指标的基础上,以足迹理论表征的环境支持力和压力指标为切入点,客观评估待选地区环境容量对新建厂址的容许程度,利用改进灰色关联度完成指标定量筛选,构建钢铁企业低碳选址评价体系。其次,运用差异系数法将主客观权重进行组合优化,采用可拓云模型求解选址综合评价等级隶属度和特征值,并结合可信度因子进行检验。最后,以某钢铁企业产能置换选址为例,确定待选厂址的评价等级。该方法在钢铁企业低碳选址综合评价中具有较好的可行性和适用性。

《我本是高山》的类型建构、上镜头性与伦理化叙事

《我本是高山》沿袭了新主流电影的创作规律和类型化特征,通过经典类型化叙事来塑造人物性格,以一种近乎质朴的影像表达、上镜头性与伦理化叙事,塑造人物形象,表现时空,承载着电影价值观和情感弥合点。影片在网络上引发的巨大争议,则提醒人们反思电影批评对于创作者、对于观众及对于批评本身的重要意义。

面向多元可控负荷调控的云边协同负荷资源分配策略

针对多元可控负荷资源进行可控负荷管理时需要占用大量计算资源,且无法实现自动功率精准控制的问题,提出了一种面向多元可控负荷调控的云边协同负荷资源分配策略。首先,设计了云边协同调控架构,整合处理各种多元可控负荷资源数据;其次,考虑不同边缘节点计算任务的相似度,以所有计算任务的时间开销最小为优化目标,给出云端计算资源分配策略,合理分配计算资源;最后,通过基于自适应交叉—变异概率的遗传算法进行计算资源分配的求解。实验结果表明,所提算法在任务完成时间和执行成本上具有较为明显的优势,并且任务数量越多,计算资源越小时优势越明显,可以显著提升计算效率,降低计算耗时。

堆石坝压实密度快速检测方法的研究

提出了基于三维激光扫描、图像智能识别与小粒径骨料自动筛分机的堆石坝密度快速检测方法,旨在提高堆石坝检测精度和效率,保障水利工程安全。通过三维激光扫描获取堆石坝测坑表面的三维点云数据,实现测坑体积的快速计算;结合图像智能识别技术,实现对骨料粒径的自动测量;利用小粒径骨料自动筛分机对堆石坝中的骨料进行筛分和测量,定量评价压实状态。该方法具有快速、准确等优点,适用于大规模的堆石坝密度检测,达到了推动碾压施工自动化水平的效果。

对融合特征敏感的三维点云识别与分割

三维点云分类分割网络忽视了融合特征中的冗余信息,缺乏放大有效特征占比能力,不能充分挖掘特征的表达性。在CurveNet网络基础上,提出了一种能够筛选和丰富融合特征的方法,对点云的识别与分割效果达到了较先进水平。首先,提出了对融合特征具有筛选能力的特征选择子网络,利用结合了打分机制的Top K算子选出包含有效信息的融合特征,并且能够自适应地赋予被选特征权重。其次,在聚合曲线特征模块中增加了两个新分支,分别学习曲线内部点距离特征和曲线之间的线距离特征,通过快速通道相关性注意力机制提取各分支的内部相关性,增强了网络特征的信息描述能力。实验结果表明,分类任务在ModelNet40数据集上准确率达到了93.8%,分割任务在ShapeNet Part数据集上平均交并比达到了86.4%。与基准网络相比,分类效果与分割效果均有所提高,证明了算法的有效性。

猕猴桃溃疡病病原菌MLVA分型引物的筛选及验证

【目的】筛选出一组可精准快速地对丁香假单胞菌猕猴桃致病变种(Pseudomonas syringae pv.actinidiae,Psa)进行分型的引物组合。【方法】针对前期文献已报道的34对引物,采用PCR技术验证该34对引物对中国Psa菌株的扩增效率及准确性;利用模拟PCR获取菌株串联重复(TR)数;以辛普森指数(Simpson’s index,SI)作为筛选引物组合的标准,基于R软件平台,筛选最优引物组合。【结果】34对引物对中国Psa扩增效果均良好,其中TR14与TR11II、TR19与Psa-01引物序列相同;TR8与Psa-08、TR39II与Psa-10、GM-1834与TR10I、GM-1553与TR64II、TR19Psa-01与TR19II扩增同一TR;Psa-09扩增产物串联重复单元长度不唯一,TR2II扩增产物侧翼变异较大,不能通过电泳确定串联重复数;最终确定SI值与全部引物组合相同的最低引物数量为9对,使用该9对引物的组合可将Psa已知的5种生物型准确分开。【结论】TR23/Psa-04、Psa-03、Psa-05、Psa-06、TR10IGM-1834、TR30I、TR1II、Psa-10TR39II、TR64IIGM-1553等9对引物可代表当前文献报道的34对引物,进行Psa分型研究,探索猕猴桃溃疡病的传播和流行规律,为病害防控策略的制定提供科学依据。

在老年女性中以人工智能+云诊断细胞学阅片为主导的宫颈癌联合筛查模式应用分析

目的探讨在老年女性中基于人工智能+云诊断细胞学阅片为主导的联合宫颈癌筛查模式的应用效果及价值。方法回顾性分析2017年1月至2021年12月连云港市妇幼保健院行宫颈锥切治疗的319例宫颈上皮内瘤变(CIN)患者病历资料,其中传统细胞学检查联合人乳头瘤病毒(HPV)检测84例作为A组,人工智能+云诊断细胞学阅片联合HPV检测127例作为B组,人工智能+云诊断细胞学阅片联合高危HPV E6/E7 mRNA检测108例作为C组,比较各组年龄、孕次、阴道镜活检点数、绝经率、转化区完全可见率、宫颈管搔刮率、治疗间隔时间、冷刀锥切率、锥切后病变一致率、锥切后病变升级率。结果各组之间年龄、孕次、阴道镜活检点数、绝经率、转化区完全可见率、宫颈管搔刮率、治疗间隔时间、冷刀锥切率等指标比较,差异无统计学意义(P>0.05)。B组和C组锥切后病理结果的一致率高于A组,病变升级率低于A组,差异有统计学意义(P<0.05)。结论在老年女性中,基于人工智能+云诊断细胞学阅片技术的宫颈癌联合筛查模式具有更低的漏诊率和更高的准确率,更适用于老年女性宫颈癌筛查。