镍钛锉Hyflex CM、Twisted Files和ProTaper Gold预备重度弯曲根管的成形效果

目的比较Hyflex CM(HCM)、Twisted Files(TF)和ProTaper Gold(PTG)预备重度弯曲根管的成形效果。方法将30颗具有重度弯曲根管的离体磨牙随机分为HCM组、TF组和PTG组,每组10颗,每组采用相应的镍钛锉预备根管。根管预备前后分别用显微CT扫描各离体磨牙,获取轴向横截面图片,测量距离根尖孔1 mm、2 mm、3 mm、4 mm、5 mm处和根管最大弯曲处的近、远中根管壁厚度最小值,计算并比较各组的根管偏移量及轴中心率。结果3组离体磨牙距离根尖孔1~5 mm处的根管偏移量、轴中心率差异有统计学意义(均P<0.05)。3组离体磨牙根管最大弯曲处的根管偏移量、轴中心率差异有统计学意义(均P<0.05),其中PTG组的根管偏移量最小、轴中心率最大。结论HCM、TF和PTG均可安全有效地预备重度弯曲根管,其中PTG的中心定位能力更好,更适合重度弯曲根管的预备。

用FileSystemObject对象模型操作文件系统

详细介绍了面向对象编程的操作文件系统的文件对象模型(FileSystemObject,以下简称FSO)的对象、属性和方法,并举例说明了该对象模型的应用。实例证明:用FSO对象模型操作文件系统比传统文件操作语句更简单、更方便、更灵活,功能更强大。

仅用FILES命令并不能同时打开二十多个文件

1问题的提出 在Novell网上用C语言编制实时微波调度软件时,由于设备、道路、装卸点种类繁多,需统计分析的内容繁多以及工作站之间的信息传递频繁,需处理的文件达30多个,由于系统的实时性,绝大多数文件必须同时打开。但在运行时发现:尽管对CONFIG.SYS文件中的FILES语句赋值很大,但最多只能同时打开15个文件。开始以为是C语言或网络软件有问题,但不在网络上用其它语言试验亦存在同样问题。

新型镍钛器械TwistedFiles的应用

镍钛器械在根管预备中的使用越来越广泛。Twisted Files(TF)采用了新的制造工艺,具有良好的根管成形作用和更好的循环疲劳抵抗力。本文就TF的牙本质切割效率及维持根管原始形态的能力、循环疲劳抵抗、消毒对TF的影响等方面作一综述。

Twisted files的研究进展

Twisted Files(TF)是一种新型的镍钛机动的根管预备器械,它采用扭制的方法制成,且有特殊的外形特点,与其他的镍钛器械相比,其具有更好的抵抗弯曲疲劳机械分离和扭曲机械分离的能力和弹性,且使用简单。因此,在根管成形中TF具有安全和高效两个方面的优势,尤其适应于弯曲根管的预备。在此对TF的组成及外形特点、物理机械性能、使用方法等予以综述。

e-files-box办公管理系统

介绍了办公管理系统在实际应用中的可行性领域.通过对数据库的管理,实现了e files box办公管理系统的开发,着重阐述了系统的主要功能,性能及实现.系统具有友好、简洁、美观的用户界面,良好的安全性,使用户的操作得以充分保障,而且满足数据的一致性和唯一性.

NRT FILES镍钛根管锉预备对弯曲根管应力分布的仿真分析

背景:在根管治疗中,镍钛合金器械常因应力超过金属塑性变形的弹性极限或在根管弯曲处重复弯曲导致镍钛合金疲劳断裂。目的:探索新型镍钛锉NRT FILES在作为根管预备材料时对根管内壁存在的应力分布,明确应力集中区域。方法:利用Solidworks软件对NRT FILES进行三维建模,模拟还原器械在真实口腔环境中存在的状态。建立6组根管简化模型:①弯曲角度30°、弯曲半径5 mm、根尖弯曲;②弯曲角度30°、弯曲半径5 mm、根中弯曲;③弯曲角度30°、弯曲半径2 mm、根尖弯曲;④弯曲角度30°、弯曲半径2 mm、根中弯曲;⑤弯曲角度45°、弯曲半径5 mm、根尖弯曲;⑥弯曲角度45°、弯曲半径2 mm、根尖弯曲。将根管简化模型与根管锉模型进行组配,对根管内壁受力点及应力分布情况进行分析。结果与结论:①-⑥组根管锉最大应力分别为1 185,1 354,1 371,1 678,1 335,2 557 MPa,最大应变分别为0.010 36,0.013 54,0.013 79,0.016 48,0.013 45,0.022 03;根管弯曲部位的不同会影响根管锉所承受的应力大小,因此在根管治疗中,根管锉沿着根管越往下,根管锉与根管接触的半径越大、刚性越差,根管锉所承受的应力越大越容易发生断裂;根管弯曲半径越小,根管锉承受的应力越大;根管弯曲角度越小,根管锉所承受的应力越大。在根尖弯曲部位,根管锉在根管弯曲半径小的弯曲根管需要承受更大的应力,根管锉更容易发生断裂;同理,在根中弯曲部位,根管锉在根管弯曲半径小的弯曲根管亦承受更大的应力,因此要格外注意根管的弯曲程度,以此来选择合适的根管锉进行根管治疗。

Massive Files Prefetching Model Based on LSTM Neural Network with Cache Transaction Strategy

In distributed storage systems,file access efficiency has an important impact on the real-time nature of information forensics.As a popular approach to improve file accessing efficiency,prefetching model can fetches data before it is needed according to the file access pattern,which can reduce the I/O waiting time and increase the system concurrency.However,prefetching model needs to mine the degree of association between files to ensure the accuracy of prefetching.In the massive small file situation,the sheer volume of files poses a challenge to the efficiency and accuracy of relevance mining.In this paper,we propose a massive files prefetching model based on LSTM neural network with cache transaction strategy to improve file access efficiency.Firstly,we propose a file clustering algorithm based on temporal locality and spatial locality to reduce the computational complexity.Secondly,we propose a definition of cache transaction according to files occurrence in cache instead of time-offset distance based methods to extract file block feature accurately.Lastly,we innovatively propose a file access prediction algorithm based on LSTM neural network which predict the file that have high possibility to be accessed.Experiments show that compared with the traditional LRU and the plain grouping methods,the proposed model notably increase the cache hit rate and effectively reduces the I/O wait time.

An Error-Correcting Code-Based Robust Watermarking Scheme for Stereolithographic Files

Stereolithographic(STL)files have been extensively used in rapid prototyping industries as well as many other fields as watermarking algorithms to secure intellectual property and protect three-dimensional models from theft.However,to the best of our knowledge,few studies have looked at how watermarking can resist attacks that involve vertex-reordering.Here,we present a lossless and robust watermarking scheme for STL files to protect against vertexreordering attacks.Specifically,we designed a novel error-correcting code(ECC)that can correct the error of any one-bit in a bitstream by inserting several check digits.In addition,ECC is designed to make use of redundant information according to the characteristics of STL files,which introduces further robustness for defense against attacks.No modifications are made to the geometric information of the three-dimensional model,which respects the requirements of a highprecision model.The experimental results show that the proposed watermarking scheme can survive numerous kinds of attack,including rotation,scaling and translation(RST),facet reordering,and vertex-reordering attacks.

Always-optimally-coordinated candidate selection algorithm for peer-to-peer files sharing system in mobile self-organized networks

In order to improve the performance of peer-to-peer files sharing system under mobile distributed en- vironments, a novel always-optimally-coordinated （AOC） criterion and corresponding candidate selection algorithm are proposed in this paper. Compared with the traditional min-hops criterion, the new approach introduces a fuzzy knowledge combination theory to investigate several important factors that influence files transfer success rate and efficiency. Whereas the min-hops based protocols only ask the nearest candidate peer for desired files, the selection algorithm based on AOC comprehensively considers users＇ preferences and network requirements with flexible balancing rules. Furthermore, its advantage also expresses in the independence of specified resource discovering protocols, allowing for scalability. The simulation results show that when using the AOC based peer selection algorithm, system performance is much better than the rain-hops scheme, with files successful transfer rate improved more than 50% and transfer time re- duced at least 20%.

基于FileSystem API的HDFS文件存取和副本选择优化研究

在对HDFS进行分析和研究的基础上,在HDFS文件分布式系统中应用File System API进行文件存储和访问,并通过改进的蚁群算法对副本选择进行优化。HDFS API能够有效完成海量数据的存储和管理,提高海量数据存储的效率。通过改进的蚁群算法提升了文件读取时副本选择的效率,进一步提高了系统效率并使负载均衡。

A novel clustering and supervising users' profiles method

To better understand different users' accessing intentions, a novel clustering and supervising method based on accessing path is presented. This method divides users' interest space to express the distribution of users' interests, and directly to instruct the constructing process of web pages indexing for advanced performance.

A Preliminary Study on the Management Strategy of University Personnel Files based on Artificial Intelligence Technology

In order to improve the management strategy for personnel files in colleges and universities,simplify the complex process of file management,and improve file management security and content preservation of the files.This paper elaborates on the application of Artificial Intelligence(AI)technology in university personnel file management through theoretical analysis based on the understanding of Al technology.

New Synchronization Algorithm Based on Delta Synchronization for Compressed Files in the Mobile Cloud Environment

The fast growing market of mobile device adoption and cloud computing has led to exploitation of mobile devices utilizing cloud services. One major chal-lenge facing the usage of mobile devices in the cloud environment is mobile synchronization to the cloud, e.g., synchronizing contacts, text messages, imag-es, and videos. Owing to the expected high volume of traffic and high time complexity required for synchronization, an appropriate synchronization algo-rithm needs to be developed. Delta synchronization is one method of synchro-nizing compressed files that requires uploading the whole file, even when no changes were made or if it was only partially changed. In the present study, we proposed an algorithm, based on Delta synchronization, to solve the problem of synchronizing compressed files under various forms of modification (e.g., not modified, partially modified, or completely modified). To measure the effi-ciency of our proposed algorithm, we compared it to the Dropbox application algorithm. The results demonstrated that our algorithm outperformed the regular Dropbox synchronization mechanism by reducing the synchronization time, cost, and traffic load between clients and the cloud service provider.

Automated File Labeling for Heterogeneous Files Organization Using Machine Learning

File labeling techniques have a long history in analyzing the anthological trends in computational linguistics.The situation becomes worse in the case of files downloaded into systems from the Internet.Currently,most users either have to change file names manually or leave a meaningless name of the files,which increases the time to search required files and results in redundancy and duplications of user files.Currently,no significant work is done on automated file labeling during the organization of heterogeneous user files.A few attempts have been made in topic modeling.However,one major drawback of current topic modeling approaches is better results.They rely on specific language types and domain similarity of the data.In this research,machine learning approaches have been employed to analyze and extract the information from heterogeneous corpus.A different file labeling technique has also been used to get the meaningful and`cohesive topic of the files.The results show that the proposed methodology can generate relevant and context-sensitive names for heterogeneous data files and provide additional insight into automated file labeling in operating systems.

Peer selecting model based on FCM for wireless distributed P2P files sharing systems

IIn order to improve the performance of wireless distributed peer-to-peer(P2P)files sharing systems,a general system architecture and a novel peer selecting model based on fuzzy cognitive maps(FCM)are proposed in this paper.The new model provides an effective approach on choosing an optimal peer from several resource discovering results for the best file transfer.Compared with the traditional min-hops scheme that uses hops as the only selecting criterion,the proposed model uses FCM to investigate the complex relationships among various relative factors in wireless environments and gives an overall evaluation score on the candidate.It also has strong scalability for being independent of specified P2P resource discovering protocols.Furthermore,a complete implementation is explained in concrete modules.The simulation results show that the proposed model is effective and feasible compared with min-hops scheme,with the success transfer rate increased by at least 20% and transfer time improved as high as 34%.

Discussion on the Information Collection Methods of Public Health Emergency Files

In public health emergencies, the collection of archival information in the area of public health emergencies is very important, which can provide a reference for the early warning and processing mechanism. At the present stage, the unlimited demand of archival users for resources and the convenience of obtaining resources have become the two driving forces to promote the “transformation” and “growth” of archives. Public health emergencies, the transformation of archives collection and service mode, social media has become an indispensable platform for user information exchange, sharing and transmission, which requires archives to change the mode of archives acquisition and storage. Archival users require more interactive, targeted and cutting-edge forms of access and archival services are also developing toward diversified functions and connotations. Archival information resource sharing is also an important link in this development trend. This paper attempts to analyze the collection methods of archives departments in public health emergencies, and then puts forward the corresponding measures for archives departments to play their functions, such as flexibly solving the needs of archives access, strengthening the development of information resources, doing a good job in the collection of relevant archives, and publicizing archives work in combination with hot spots. This paper discusses the completeness of archival data collection, the means of archival management, the scientific classification of archival data, the ways of archival data collection and so on.

Shaping ability of thermomechanically treated files in simulated S-shaped root canals

Aim: the aim of this study was to investigate the shaping ability of thermomechanically treated files manufactured by twisting(Twisted files)and compare it to conventional rotary system (K3, Sybron Endo, Orange, CA) in S-shaped canals, including formation of ledges, zipping, elbow, outer widening, danger zone, perforation and file deformation. Materials & Methods: Forty S-Shaped canals in resin blocks were randomly divided into 2 groups of 20 each. Pre-instrumentation images of the canals were taken via a digital camera and superimposed on images taken after preparation with TF and K3 systems to apical size of 25/06 and 30/06. Canal aberrations were measured from the superimposed image at five levels using AutoCAD system. Fisher exact test and Mann Whitney test were used for analysis of the data. Results: the incidence of zipping, elbow and apical transportation was significantly lower in the TF group (P = 0.04). Generally the incidence of aberration increased when the apical size increased to 30/0.06 regardless of the file system. Significant file deformation was evident in the TF after single use (P ? 0.001). Conclusion: Under the conditions of this study, TF manufactured by new technique performed better than K3 systems when used up to size 25/06 in simulated S-shaped canals. Clinical significance: The flexibility of thermomechanically treated files is beneficial in canals with multiple curvatures;however, attention should be paid to the instrument taper and final apical size of the preparation.

A Complexity Analysis and Entropy for Different Data Compression Algorithms on Text Files

In this paper, we analyze the complexity and entropy of different methods of data compression algorithms: LZW, Huffman, Fixed-length code (FLC), and Huffman after using Fixed-length code (HFLC). We test those algorithms on different files of different sizes and then conclude that: LZW is the best one in all compression scales that we tested especially on the large files, then Huffman, HFLC, and FLC, respectively. Data compression still is an important topic for research these days, and has many applications and uses needed. Therefore, we suggest continuing searching in this field and trying to combine two techniques in order to reach a best one, or use another source mapping (Hamming) like embedding a linear array into a Hypercube with other good techniques like Huffman and trying to reach good results.

Feasibility of Estimating Patient-Specific Dose Verification Results Directly from Linear Accelerator Log Files in Volumetric Modulated Arc Therapy

The feasibility of estimating patient-specific dose verification results directly from linear accelerator (linac) log files has been investigated for prostate cancer patients who undergo volumetric modulated arc therapy (VMAT). Twenty-six patients who underwent VMAT in our facility were consecutively selected. VMAT plans were created using Monaco treatment planning system and were transferred to an Elekta linac. During the beam delivery, dynamic machine parameters such as positions of the multi-leaf collimator and the gantry were recorded in the log files;subsequently, root mean square (rms) values of control errors, speeds and accelerations of the above machine parameters were calculated for each delivery. Dose verification was performed for all the plans using a cylindrical phantom with diodes placed in a spiral array. The gamma index pass rates were evaluated under 3%/3 mm and 2%/2 mm criteria with a dose threshold of 10%. Subsequently, the correlation coefficients between the gamma index pass rates and each of the above rms values were calculated. Under the 2%/2 mm criteria, significant negative correlations were found between the gamma index pass rates and the rms gantry angle errors (r = 0.64, p < 0.001) as well as the pass rates and the rms gantry accelerations (r = 0.68, p < 0.001). On the other hand, the rms values of the other dynamic machine parameters did not significantly correlate with the gamma index pass rates. We suggest that the VMAT quality assurance (QA) results can be directly estimated from the log file thereby providing potential to simplify patient-specific prostate VMAT QA procedure.