基于SNP位点的身高预测模型的评估

目的根据报道的547个欧洲人群身高相关SNP位点构建中国汉族男性身高预测模型,评估此模型预测身高的准确性。方法采用Affymetrix SNP Array 6.0芯片和Hi Seq 4000测序平台对59例山东汉族男性样本进行DNA分型检测,并将这547个身高相关SNP位点作为预测因子,采用加权等位基因求和(weight allele sums,WAS)的计算方法建立预测模型。通过受试者工作特征曲线及曲线下面积(area under curve,AUC)对身高预测模型的准确性进行分析。结果样本全基因组关联分析未发现身高显著相关SNP位点。本研究用WAS法构建身高预测模型,获得的AUC值为0.67(95%置信区间为0.53~0.90)。结论用547个SNP位点的WAS模型预测山东汉族男性群体身高具有参考价值,但预测模型准确度的进一步提升需要通过筛选更多具有人群特异性的身高相关SNP位点来实现。     

交通流缺失数据的修补技术探究

城市道路交通中交通检测器获得的数据往往不完整,存在丢失现象,需要对其进行修补,以保证交通流预测模型的实际应用精度。以离散和连续缺失的线圈检测器交通流量数据为研究对象,提出一种基于最小二乘支持向量机(Least Squares Support Vector Machines,LS-SVM)的交通流时间序列数据修补模型,并将其结果与利用RBF神经网络模型和一元非线性回归模型的结果进行比较。研究结果表明,LS-SVM模型修补精度优于RBF(Radical Basis Function)神经网络模型和非线性回归模型。最后,针对历史数据缺失难以构建LS-SVM模型的问题,提出了两阶段故障数据修补组合模型,取得了好的效果。     

交通信息采集摄像机辅力交通管理智能化

正视频交通流数据的应用可以帮我们从采集断面数据转向采集交通状态特征信息,就好比给交通信息系统加上了"眼睛"。视频车辆检测器的缺点是,易受到能见度、照明条件的影响,对于恶劣天气、无光环境一般的视频车辆检测器检测精度大大降低。精确数据对交通管理有着至关重要的作用,步入数据时代,通过精确数据采集反馈是交通管理系统的发展方向,没有精确数据根本无从谈智能管理、控     

信号机与车辆检测器通信协议测试软件研究

当前,各种新型交通流检测产品大量涌现,并为交通信号控制机灵活、精确地进行路口信号配时提供了重要保障.但在实际应用中交通流检测设备与交通信号控制机之间的兼容性问题较为突出.本文为此设计并实现了交通信号控制机与车辆检测器通信协议测试软件,可灵活选择检测项目、设置检测参数,同时可将通信过程中的每个命令及检测结果等信息保存在word文档中,方便用户比对校验.该软件对于判断检测交通信号控制机是否符合相关行业标准具有一定参考价值,结果表明所设计的软件模块结构、控制流程是有效可行的.     

从模糊理论看科学主义和人本主义的认识观

认识的精确化是社会实践和人类心智发展的必然结果，然而精确方法也存在自身的局限性。模糊理论的互克性原理揭示了片面追求精确化将导致认识结果的可行性和有意义性的降低，精确方法不是处理复杂事物尤其是人文系统的有效手段。模糊理论将认识的有意义性置于首位，标志着人类思维方式的重大变革。从模糊理论的观点看，传统的科学主义和人本主义在认识上各执一端，都没有正确地看待认识中主体的作用，把理性和非理性、精确性和模糊性绝对地对立起来，片面地理解实证方法，因而不可避免地走入了理论的误区。模糊理论拓展了传统科学的形式化和实证方法，代表着人类认识发展的合理方向     

创业企业融资需求预测新视野——修正的可持续增长模型预测方法

本文在分析了创业企业融资特点的基础上,对传统的可持续增长模型进行修正,探讨了一种符合创业企业实际情况的融资需求预测方法:修正的可持续增长模型融资预测模型;对该预测方法的预测程序以及预测的特点进行了分析;同时本文采用这种方法对一个创业企业的融资进行预测。     

基于ARMA模型的我国财产类犯罪人数预测研究

在定量犯罪学的语境下,以《中国法律年鉴》全国检察机关决定批捕和自行决定批捕的侵犯财产类犯罪人数之和作为我国财产类犯罪人数的统计衡量指标,做出了1986-2010年全国财产类犯罪人数变迁的时间序列.通过时间序列分析法和计算机软件EViews5.0,对时间序列逐步进行平稳性检验、独立性检验,建立了我国财产类犯罪的ARMA(1,10)拟合预测模型.一方面,预测分析表明2011年我国财产类犯罪人数的点预测结果为387914,区间预测结果为[334369,451351](单位:人);另一方面,拟合精度分析证实,建立的模型通过了统计学检验,模型整体显著,预测精度较高,是一个优良的时间序列预测模型,对我国财产类犯罪定量实证预测研究能起到良好的借鉴作用.     

专利法上可预测与不可预测技术的区分标准

发明公开制度是专利法的核心制度之一，而公开充分性的判断标准在我国理论上较少得到讨论。由于专利所保护的技术存在不同的性质，可区分为可预测技术与不可预测技术，适用不同的公开充分性规则是合理的。一般而言，相比诸如生物科技等不可预测技术领域的发明，在传统的机械和计算机软件等可预测技术领域的发明中，适用公开充分性的条件应宽松一些。     

党在新世纪意识形态领域工作的指针

江泽民总书记的“七·一”讲话 ,系统地总结了我们党 80年来的光辉历程和基本经验 ,全面阐述了“三个代表”思想的科学内涵 ,明确提出了加强和改进党的建设的基本要求。其中也总结了建党 80年来党在意识领域工作的历史经验 ,特别是总结了党在新时期意识形态领域工作的新经验 ,对于我们如何在新世纪做好意识形态领域的工作 ,是方向鲜明的指针     

火灾损失的灰色模糊预测方法

对于火灾损失的预测,由于诸多不确定因素,导致火灾损失预测具有“部分信息已知,部分信息未知”的“小样本”、“贫信息”不确定性,同时,在进行预测时要用精确值来表示各种事件的概率显然是不切实际的,而用模糊数或预言变量来表示他们则显得更为合理。同时,由于存在时间这一变化基准,要综合考虑时间、成本、信息等要素对火灾损失预测的影响。鉴于这种原因,本文考虑火灾损失为贫信息不确定性、预测分析模糊的方法问题。     

Revisiting prediction models in policing: Identifying high-risk offenders

The use of prediction models for classifying offenders has been a common practice by the criminal justice system. Given the recent developments in criminal career research and continuing evidence that a small proportion of chronic offenders are responsible for the majority of crime, there is a continued need to identify high-risk offenders early on in their offending careers. The present study provides support for the accuracy of an innovative prediction instrument that was developed for identifying high-risk offenders in a rural county in a southern state. Offender risk classification was found to be associated with reoffending across different dimensions of assessment and the high-risk offenders had accumulated a greater mean number of arrests upon six-month follow-up when compared to the medium and low-risk offenders. Policy implications and directions for future research incorporating prediction models in policing are also discussed.     

Experimental tests for the validation of active numerical human models

The development of numerical human models is a topic of current interdisciplinary research. In the field of automotive safety these models can be applied for the optimization of protection systems. In forensic research human models can be used for the investigation of injury mechanisms and for the prediction and reproduction of injury patterns. However, up to now human models have been validated on the basis of PMHS tests without considering the effects of muscle activity. This paper shows two experimental volunteer test set-ups for the generation of experimental validation data. In a pendulum set-up the influence of muscle activity on the human kinematics was investigated. A drop test set-up was developed for the analysis of the effects of muscle activity on impact response characteristics of muscle tissue. Experimental results, presented in this paper, can be used for the validation and optimization of active numerical human models.     

Perceptions of Poverty and Wealth in Western and Post-Communist Countries

This paper analyzes the felt legitimacy of poverty and wealth in the United States, West Germany, The Netherlands, Hungary, the Czech Republic, and Russia. Several theories on poverty and wealth perception are discussed; of these, dominant ideology theory has been the most influential. This theory can predict the existence not only of a legitimizing ideology in a society, but also of challenging beliefs that incumbents of specific social positions hold. It is argued that poverty and wealth perceptions are more complex, however, involving at least three latent dimensions. Using data from the International Social Justice Project it is demonstrated that, regarding poverty, individuals distinguish between merited, unmerited, and fatalistic types of poverty. Merited poverty is poverty brought about by the individual's own doing or not doing, unmerited poverty is due to forces external to the individual, whereas fatalistic explanations attribute poverty to ascribed properties of the individual. For wealth also there are three causally relevant factors: in addition to merited und unmerited ones, a social capital factor that sees social contacts as a source for determining economic success. Using a structural equation approach and its group comparison option for comparing countries, the different explanations of poverty and wealth are translated into specific measurement models. Testing simultaneously with linear regression models show how preferences for particular explanations are shaped by stratification-related experiences and by the social position of an observer.     

Analysis of ecstasy tablets: comparison of reflectance and transmittance near infrared spectroscopy

Calibration models for the quantitation of commonly used ecstasy substances have been developed using near infrared spectroscopy (NIR) in diffuse reflectance and in transmission mode by applying seized ecstasy tablets for model building and validation. The samples contained amphetamine, N-methyl-3,4-methylenedioxy-amphetamine (MDMA) and N-ethyl-3,4-methylenedioxy-amphetamine (MDE) in different concentrations. All tablets were analyzed using high performance liquid chromatography (HPLC) with diode array detection as reference method. We evaluated the performance of each NIR measurement method with regard to its ability to predict the content of each tablet with a low root mean square error of prediction (RMSEP). Best calibration models could be generated by using NIR measurement in transmittance mode with wavelength selection and 1/x-transformation of the raw data. The models build in reflectance mode showed higher RMSEPs using as data pretreatment, wavelength selection, 1/x-transformation and a second order Savitzky-Golay derivative with five point smoothing was applied to obtain the best models. To estimate the influence of inhomogeneities in the illegal tablets, a calibration of the destroyed, i.e. triturated samples was build and compared to the corresponding data of the whole tablets. The calibrations using these homogenized tablets showed lower RMSEPs. We can conclude that NIR analysis of ecstasy tablets in transmission mode is more suitable than measurement in diffuse reflectance to obtain quantification models for their active ingredients with regard to low errors of prediction. Inhomogeneities in the samples are equalized when measuring the tablets as powdered samples.     

政府购买冲击与商业周期——一个基于Keynes波动理论与真实商业周期理论的比较分析

基于IS-LM模型的传统凯恩斯波动理论主要从需求的角度用乘数理论分析政府购买冲击对宏观经济变量的静态影响;基本的真实商业周期理论则主要从供给的角度用财富效应和劳动力跨期替代理论分析政府购买冲击对消费、劳动投入、总产出等宏观经济变量的动态效应。不同的动态随机一般均衡模型得出的校准结论常常大相径庭。Keynes波动理论和真实商业周期理论对政府购买的消费效应持有截然不同的观点。     

Survival analysis: A survey

This paper is a survey of statistical methods used to analyze the length of time until a specified event occurs. These models have often been used to analyze the survival times (i.e., time until death) of medical patients, and so the term survival analysis is natural. In criminology, the main application of these models has been to analyze the time until recidivism, but many other applications are possible. The paper summarizes the statistical literature on survival analysis, and describes its applications in criminology. The methods are illustrated by an application to the prediction of time until recidivism for a sample of North Carolina prison releasees.     

Handling manipulated evidence

Bayesian Networks have been advocated as useful tools to describe the relations of dependence/independence among random variables and relevant hypotheses in a crime case. Moreover, they have been applied to help the investigator structure the problem and evaluate the impact of the observed evidence, typically with respect to the hypothesis of guilt of a suspect. In this paper we describe a model to handle the possibility that one or more pieces of evidence have been manipulated in order to mislead the investigations. This method is based on causal inference models, although it is developed in a different, specific framework.     

Bloodstain age estimation through infrared spectroscopy and Chemometric models

The chemical profiling of bloodstains is essential to link the suspect with the crime. The current study proposed a proof-of-concept methodology for the investigation of bloodstains by utilizing advanced ATR-FTIR spectroscopy coupled with new generation chemometric methods. Current study provides encouraging data to allow discrimination between human and animal blood though with small sample size. In this study, different models for the age estimation of human bloodstains are developed from the trained data sets of 1–175 days old bloodstains. The models such as curve estimation (CE), multiple linear regression (MLR), and partial least squares regressions (PLSR) are developed to determine the best prediction model for aged human bloodstains. The obtained results on the dating of bloodstains are very encouraging and also tested for unknown samples. The maximum dating errors are observed in the curve estimation models whereas, the other models MLR, PLSR show excellent age estimation of unknown bloodstains. These models represent an error of ~3 ± 1 days and ~4 ± 1 days in actual and estimated date, respectively, which is lowest ever reported so far. The present methodology is expected to provide a valuable insight into forensic society and hence, to the law enforcement community. The present methodology can further be explored for an ideal model by including all other external variables/factors and for more longer aging time.     

A theory of identification

This paper analyzes the phenomenon of “identification” by an individual with actors in his environment. It argues that individuals interpret their environment according to “frames,” which they, as recipients of a message, derive by a complex process of interpretation of the communication setting. The paper also argues that individuals identify with actors in their environment, because this identification increases their utility vis-à-vis a “neutral” watching of their environment. The paper applies this approach to a variety of real life examples, in particular to voting.     

Parallel business models and the innovativeness of research-based spin-off ventures

Research-Based Spin-Offs (RBSOs) are seen as a potential mechanism for technology transfer by commercializing academic research and thereby stimulate industrial innovation. RBSOs are heterogeneous, however, and in this paper we investigate how the use of different business models by RBSOs is related to their innovativeness. We use a sample of 82 young RBSOs from Norway to explore typologies of RBSOs developed in earlier studies. Our findings show that some types of business models are associated with higher innovativeness than others. The typology approach has portrayed RBSOs as if they pursue only one business model. In this paper we challenge this assumption by drawing on evolutionary theory and the idea that firms may follow several business models in parallel. Our empirical findings suggest that most RBSOs pursue several business models in parallel and that such firms are more innovative. This study extends the typology approach within the academic entrepreneurship literature by showing that some business models are associated with higher innovativeness than others and that firms pursuing several business models at the same time may be particularly important for the commercialization of academic research. These findings have important implications for research and practise.