IDentifier DNA分型盒(炎黄34)的法医学验证及应用评估

目的 测试IDentifier DNA分型盒(炎黄34)的技术性能指标,评估其法医学应用价值。方法 根据《法庭科学人类荧光标记STR复合扩增检测试剂质量基本要求》(GB/T 37226—2018),从种属特异性、分型准确性、灵敏度、适应性、耐受性、一致性、均衡性、反应条件验证、混合样本、稳定性、批间差11个方面对IDentifier DNA分型盒(炎黄34)进行测试。比较IDentifier DNA分型盒(炎黄34)与Power Plex~?Fusion 6C系统、Versa Plex~?27PY系统、Veri Filer~(TM) Plus PCR扩增试剂盒的系统效能。使用IDentifier DNA分型盒(炎黄34)检测日常案件中的拭子类生物检材,观察其STR检验结果 。结果 IDentifier DNA分型盒(炎黄34)具有良好的种属特异性、分型准确性、适应性、耐受性和均衡性,灵敏度可达0.062 5 ng,能检测案件中不同类型的检材、降解检材及混有抑制剂的检材,对混合比例为4∶1以内的样本均能获得完整分型。该试剂盒的系统效能非常高,TDP可达1-1.08×10~(-37),CPE_(trio)和CPE_(duo)分别可达1-5.47×10~(-14)和1-6.43×10~(-9)。针对案件中的接触类生物检材,其有效检出率可达21.05%。针对亲缘关系鉴定,单亲鉴定和全同胞鉴定的系统效能均得到了有效提高。结论 IDentifier DNA分型盒(炎黄34)的上述性能指标符合要求,可用于个体识别及亲权鉴定,适合在法庭科学领域应用。

A Novel Method in Wood Identification Based on Anatomical Image Using Hybrid Model

Nowadays,wood identification is made by experts using hand lenses,wood atlases,and field manuals which take a lot of cost and time for the training process.The quantity and species must be strictly set up,and accurate identification of the wood species must be made during exploitation to monitor trade and enforce regulations to stop illegal logging.With the development of science,wood identification should be supported with technology to enhance the perception of fairness of trade.An automatic wood identification system and a dataset of 50 commercial wood species from Asia are established,namely,wood anatomical images collected and used to train for the proposed model.In the convolutional neural network(CNN),the last layers are usually soft-max functions with dense layers.These layers contain the most parameters that affect the speed model.To reduce the number of parameters in the last layers of the CNN model and enhance the accuracy,the structure of the model should be optimized and developed.Therefore,a hybrid of convolutional neural network and random forest model(CNN-RF model)is introduced to wood identification.The accuracy’s hybrid model is more than 98%,and the processing speed is 3 times higher than the CNN model.The highest accuracy is 1.00 in some species,and the lowest is 0.92.These results show the excellent adaptability of the hybrid model in wood identification based on anatomical images.It also facilitates further investigations of wood cells and has implications for wood science.

利用Identifiler分型系统推断同胞关系

目的探讨自主开发的同胞关系鉴定自动分析软件（ASI）对Identifiler分型系统进行同胞关系鉴定的可行性。方法应用本课题组所开发的软件ASI,对151对同胞及31 224对人工模拟无关个体进行Identifiler系统的15个常染色体STR基因座分型进行分析,计算亲权指数（PI）、同胞关系概率（WFS）和等位基因匹配情况,所获数据进行统计分析,自动计算排序。结果当WFS大于99.999%时,同胞个体占39.07%,无关个体占0%,两组具有显著差异,可以推断两个体同胞关系。当WFS介于1%~99.999%范围内,同胞个体和无关个体有部分重叠,同胞个体占60.93%,无关个体占21.3%,两者具有一定差异,可以通过增加检测STR基因座,再结合案情加作Y-STR、m tDNA检测,以推断两个体是否具有同胞关系。当WFS小于1%时,同胞个体占0%,无关个体占78.7%,可以推断两个体不具有同胞关系。个体间等位基因匹配结果表明：在检测Identifiler体系15个STR基因座时,当两个体常染色体STR基因座的全相同数目≥5时,或全不同数目≤1时,提示为同胞关系;当两个体全不同数目≥6时,或全相同数目≤1时,提示为无关个体,以此作为预测有无同胞关系的界值。结论Identifiler系统及同胞关系鉴定自动分析软件ASI可用于推断同胞关系。

Structural modal parameter identifi cation and damage diagnosis based on Hilbert-Huang transform

Traditional modal parameter identifi cation methods have many disadvantages,especially when used for processing nonlinear and non-stationary signals.In addition,they are usually not able to accurately identify the damping ratio and damage.In this study,methods based on the Hilbert-Huang transform(HHT) are investigated for structural modal parameter identifi cation and damage diagnosis.First,mirror extension and prediction via a radial basis function(RBF) neural network are used to restrain the troublesome end-effect issue in empirical mode decomposition(EMD),which is a crucial part of HHT.Then,the approaches based on HHT combined with other techniques,such as the random decrement technique(RDT),natural excitation technique(NExT) and stochastic subspace identifi cation(SSI),are proposed to identify modal parameters of structures.Furthermore,a damage diagnosis method based on the HHT is also proposed.Time-varying instantaneous frequency and instantaneous energy are used to identify the damage evolution of the structure.The relative amplitude of the Hilbert marginal spectrum is used to identify the damage location of the structure.Finally,acceleration records at gauge points from shaking table testing of a 12-story reinforced concrete frame model are taken to validate the proposed approaches.The results show that the proposed approaches based on HHT for modal parameter identifi cation and damage diagnosis are reliable and practical.

Analysis of identifiers in IoT platforms

The Internet of Things(IoT)provides new opportunities for different IoT platforms connecting various devices together.The need to identify those devices is the foremost important to perform any kind of operation.Many organizations and standard bodies that provide specifications and frameworks for the IoT currently have their own identification mechanisms.Some existing industrial identification mechanisms can also be used in the IoT.There is no common Identification Scheme(IS)for the IoT as yet,because of the political and commercial differences amongst the standard bodies.The unavailability of a unified IS method makes the inter-working among IoT platforms challenging.This paper analyses and compares ISs used by several selected IoT platforms.This work will help in understanding the need for a common identification mechanism to provide inter-working among different IoT platforms.

DC中Identifier项的模式体系标准化探析

网络时代 ,元数据 DC是组织网络信息资源的重要手段 ,为了增强互操作性其元素项的限定是必要的。本文在分析了 DC中 Identifier项的模式体系的基础上 ,探讨了 URI、URL 和 URN三者之间的关系 ,认为 U RN将成为该项模式体系的国际标准。

An Identifier-Based Network Access Control Mechanism Based on Locator/Identifier Split

Legacy IP address-based access control has met many challenges, because the network nodes cannot be identified accurately based on their variable IP addresses. “Locator/Identifier Split” has made it possible to build a network access control mechanism based on the permanent identifier. With the support of “Locator/Identifier Split” routing and addressing concept, the Identifier-based Access Control (IBAC) makes net-work access control more accurate and efficient, and fits for mobile nodes’ access control quite well. Moreover, Self-verifying Identifier makes it possible for the receiver to verify the packet sender’s identity without the third part authentication, which greatly reduces the probability of “Identifier Spoofing”.

Overall-Transparent Dynamic Identifier-Mapping Mechanism Against Scanning and Worm Propagation in the SINET

Static assignment of IP addresses or identifiers can be exploited by an adversary to attack a network. However, existing dynamic IP address assignment approaches suffer from two limitations, namely: participation of terminals in the assignment and inadequate network server management. Thus, in this paper, we propose an Overall-transparent Dynamic Identifier-mapping Mechanism(ODIM) to manage the identifier of network nodes to defend against scanning and worm propagation in the Smart Identifier NETwork(SINET). We establish the selection and allocation constraints, and present selection and allocation algorithms to determine the constraints. The non-repetition probability and cover cycle allow us to evaluate the defense efficiency against scanning. We propose the probability for routing identifiers and derive the defense efficiency of ODIM against worm propagation. Simulation results and theoretical analysis show that the proposed method effectively reduces the detection probability of Routing IDentifiers(RIDs) and thus improves defense capabilities against worm propagation.

Parameter Identifiability and Parameter Estimation of a Diesel Engine Combustion Model

In this paper an original method based on the link between a piecewise identifiability analysis and a piecewise numerical estimation is presented for estimating parameters of a phenomenological diesel engine combustion model. This model is used for design, validation and pre-tuning of engine control laws. A cascade algebro-differential elimination method is used for studying identifiability. This investigation is done by using input-output-parameter relationship. Then these relations are transformed by using iterated integration. They are combined with an original numerical derivative estimation based on distribution theory which gives explicit point-wise derivative?estimation formulas for each given order. Then new approximate relations, linking block of parameters and outputs (without derivative) are obtained. These relations are linear relatively to the blocks of parameters and yield a first estimation of parameters which is used as initial guess for a local optimization method (least square method and a local search genetic algorithm).

A novel voting system for the identification of eukaryotic genome promoters

Motivation: Accurate identification and delineation of promoters/TSSs (transcription start sites) is important for improving genome annotation and devising experiments to study and understand transcriptional regulation. Many promoter identifiers are developed for promoter identification. However, each promoter identifier has its own focuses and limitations, and we introduce an integration scheme to combine some identifiers together to gain a better prediction performance. Result: In this contribution, 8 promoter identifiers (Proscan, TSSG, TSSW, FirstEF, eponine, ProSOM, EP3, FPROM) are chosen for the investigation of integration. A feature selection method, called mRMR (Minimum Redundancy Maximum Relevance), is novelly transferred to promoter identifier selection by choosing a group of robust and complementing promoter identifiers. For comparison, four integration methods (SMV, WMV, SMV_IS, WMV_IS), from simple to complex, are developed to process a training dataset with 1400 se- quences and a testing dataset with 378 sequences. As a result, 5 identifiers (FPROM, FirstEF, TSSG, epo- nine, TSSW) are chosen by mRMR, and the integration of them achieves 70.08% and 67.83% correct prediction rates for a training dataset and a testing dataset respectively, which is better than any single identifier in which the best single one only achieves 59.32% and 61.78% for the training dataset and testing dataset respectively.

Identifier Management of Industrial Internet Based on Multi-Identifier Network Architecture

The industrial Internet realizes intelligent control and optimized operation of the industrial system through network interconnection.The industrial Internet identifier is the core element to accomplish this task.The traditional industrial Internet identifier resolution technologies depend excessively on IP networks,and cannot meet the requirements of ubiquitous resource-restraint Internet of Things(IoT)devices.An industrial Internet identifier resolution management strategy based on multi-identifier network architecture is proposed in this paper,which supports content names,identities,locations,apart from the traditional IP address.The application of multiple types of identifiers not only solves the problem of IP addresses exhaustion,but also enhances the security,credibility,and availability of the industrial Internet identification resolution system.An inter-translation scheme between multiple identifiers is designed to support multiple identifiers and the standard ones.We present an addressing and routing algorithm for identifier resolution to make it convenient to put our strategy into practice.

Application of Industrial Internet Identifier in Optical Fiber Industrial Chain

The industrial Internet has germinated with the integration of the traditional industry and information technologies.An identifier is the identification of an object in the industrial Internet.The identifier technology is a method to validate the identification of an object and trace it.The identifier is a bridge to connect information islands in the industry,as well as the data basis for building a technology application ecosystem based on identifier resolution.We propose three practical applications and application scenarios of the industrial Internet identifier in this paper.Future applications of identifier resolution in the industrial Internet field are also presented.

Geometrical Frameworks in Identification Problem

The purpose of this review is to apply geometric frameworks in identification problems. In contrast to the qualitative theory of dynamical systems (DSQT), the chaos and catastrophes, researches on the application of geometric frameworks have not been performed in identification problems. The direct transfer of DSQT ideas is inefficient through the peculiarities of identification systems. In this paper, the attempt is made based on the latest researches in this field. A methodology for the synthesis of geometric frameworks (GF) is proposed, which reflects features of nonlinear systems. Methods based on GF analysis are developed for the decision-making on properties and structure of nonlinear systems. The problem solution of structural identifiability is obtained for nonlinear systems under uncertainty.

Structural-Identification Aspects of Decision-Making in Systems with Bouc-Wen Hysteresis

Considering the structural analysis problem of systems properties with Bouc-Wen hysteresis (BWH), various approaches are proposed for the identification of BWH parameters. The applied methods and algorithms are based on the design of parametric models and consider a priori information and the results of data analysis. Structural changes in the BWH form a priori. Methods for the Bouc-Wen model (BWM) identification and its structure estimation are not considered under uncertainty. The study’s purpose is the analysis the structural problems of the Bouc-Wen hysteresis identification. The analysis base is the application of geometric frameworks (GF) under uncertainty. Methods for adaptive estimation parameters and structural of BWM were proposed. The adaptive system stability is proved based on vector Lyapunov functions. An approach is proposed to estimate the identifiability and structure of the system with BWH. The method for estimating the identifiability degree based on the analysis of GF is considered. BWM modifications are proposed to guarantee the system’s stability and simplify its description.

Dimensional Synthesis for 3-PRS Mechanism Based on Identifiability Performance

Many performance indices for parallel mechanism are put forward in the phase of dimensional synthesis,except for identifiability index,which determines the difficulty of kinematical calibration.If the dimensional parameters are inappropriately selected,the existing methods for optimizing identifiability will not effectively work.Thus,with the aim of studying identifiability optimization in dimensional synthesis for 3-PRS mechanism,kinematics with structural errors is analyzed to provide theoretical bases for kinematical model.Then through a comparison of two 3-PRS mechanisms with different dimensional parameters,identifiability performance is proved to be necessary and feasible for optimization in the phase of dimensional design.Finally,an index δ is proposed to scale the identifiability performance.With the index,identifiability analysis and dimensional synthesis simulation in the whole workspace is completed.The index is verified to be correct and feasible,and based on the index,a procedure of dimensional synthesis,as well as an example set of non-dimensional parameters of 3-PRS mechanism,is proposed.The proposed identifiability index and design method can effectively introduce identifiability optimization into dimensional synthesis,and will obviously benefit later kinematical calibration.

Two novel gastric cancer-associated genes identified by differential display

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High-throughput screening of mouse gene knockouts identifies established and novel skeletal phenotypes

Screening gene function in vivo is a powerful approach to discover novel drug targets. We present high-throughput screening （HTS） data for 3 762 distinct global gene knockout （KO） mouse lines with viable adult homozygous mice generated using either gene-trap or homologous recombination technologies. Bone mass was determined from DEXA scans of male and female mice at 14 weeks of age and by microCT analyses of bones from male mice at 16 weeks of age. Wild-type （WT） cagemates/littermates were examined for each gene KO. Lethality was observed in an additional 850 KO lines. Since primary HTS are susceptible to false positive findings, additional cohorts of mice from KO lines with intriguing HTS bone data were examined. Aging, ovariectomy, histomorphometry and bone strength studies were performed and possible non-skeletal phenotypes were explored. Together, these screens identified multiple genes affecting bone mass： 23 previously reported genes （Calcr, Cebpb, Crtap, Dcstamp, Dkkl, Duoxa2, Enppl, Fgf23, Kissl/Kisslr, Kl （Klotho）, Lrp5, Mstn, Neol, Npr2, Ostml, Postn, Sfrp4, S1c30a5, Sic39a13, Sost, Sumf1, Src, Wnt10b）, five novel genes extensively characterized （Cldn18, Fam20c, Lrrkl, Sgpll, Wnt16）, five novel genes with preliminary characterization （Agpat2, RassfS, Slc10a7, Stc26a7, Slc30a10） and three novel undisclosed genes coding for potential osteoporosis drug targets.

Identification of variable coefficients for vibrating systems by boundary control and observation

We consider the identification problem of coefficients for vibrating systems described by a Euler-Bernoulli beam eq~. ation Or a string equation, with one end clamped and with an input exerted on the other end. For the beam equation, the observations are the velocity and the angle velocity at the free end, while for the string equation, the observation is the velocity at the free end. In the framework of well-posed linear system theory, we show that both the density and the flexural rigidity of the beam, and the tension of the string, can be uniquely determined by the observations for all positive times. Moreover, a general constructive method is developed to show that the mass density and the elastic modulus of the string are not determined by the observation.

Experimentation with Personal Identifiable Information

In this paper, actual personal identifiable information (PII) texts are analyzed to capture different types of PII sensitivities. The sensitivity of PII is one of the most important factors in determining an individual’s perception of privacy. A “gradation” of sensitivity of PII can be used in many applications, such as deciding the security level that controls access to data and developing a measure of trust when self-disclosing PII. This paper experiments with a theoretical analysis of PII sensitivity, defines its scope, and puts forward possible methodologies of gradation. A technique is proposed that can be used to develop a classification scheme of personal information depending on types of PII. Some PII expresses relationships among persons, some specifies aspects and features of a person, and some describes relationships with nonhuman objects. Results suggest that decomposing PII into privacy-based portions helps in factoring out non-PII information and focusing on a proprietor’s related information. The results also produce a visual map of the privacy sphere that can be used in approximating the sensitivity of different territories of privacy-related text. Such a map uncovers aspects of the proprietor, the proprietor’s relationship to social and physical entities, and the relationships he or she has with others.

Adaptive Control of a Two-Link Robot Using Batch Least-Square Identifier

We design a regulation-triggered adaptive controller for robot manipulators to efficiently estimate unknown parameters and to achieve asymptotic stability in the presence of coupled uncertainties.Robot manipulators are widely used in telemanipulation systems where they are subject to model and environmental uncertainties.Using conventional control algorithms on such systems can cause not only poor control performance,but also expensive computational costs and catastrophic instabilities.Therefore,system uncertainties need to be estimated through designing a computationally efficient adaptive control law.We focus on robot manipulators as an example of a highly nonlinear system.As a case study,a 2-DOF manipulator subject to four parametric uncertainties is investigated.First,the dynamic equations of the manipulator are derived,and the corresponding regressor matrix is constructed for the unknown parameters.For a general nonlinear system,a theorem is presented to guarantee the asymptotic stability of the system and the convergence of parameters'estimations.Finally,simulation results are discussed for a two-link manipulator,and the performance of the proposed scheme is thoroughly evaluated.