相关维数计算中的ln c(r)～ln r线性拟和

相关维数是定量描述非线性时间序列的一个重要参数,在脑电、心电等生物医学信号的特征描述方面得到了广泛地应用.相关维数的计算涉及到诸如延迟时间、嵌入维数等多个参数的选择,同时需要确定ln C_m(r)～ln r线性拟和的尺度区间.本文介绍了一种新的确定尺度区间的方法,利用该方法确定尺度区间能够保持计算结果的稳定性与一致性.     

Bootstrap方法及其在生物学研究中的应用

Bootstrap方法是以原始数据为基础的模拟抽样统计推断法,特别适用于那些难以用常规方法导出的参数的区间估计、假设检验等问题.本文介绍了该方法的基本思想及具体步骤,并附有生物学研究中应用的实例.生物科学中有许多数据总体分布信息往往很难确定,难以用常规的方法进行统计分析,因此Bootstrap方法在生物科学研究中具有很大的应用价值.     

利用SSR标记定位水稻糊化温度的QTLs

糊化温度（GT）是决定稻米蒸煮食用品质的一个重要指标。研究了以碱消值表示的糊化温度（ASV－GT）的遗传和QTL位点,选择在ASV－GT上具有显著差别的灿稻品种南特号和粳稻品种Balilla杂交,并以Balilla回交得到含有142株的回交群体,ASV－GT的测定表明,在分离群体中ASV－GT表现为双峰连续分布,说明在该群体中ASV－GT是由一主效基因控制的,并伴有微效基因的修饰,进一步用119个在双亲间具有多态性的微卫星（SSR）标记构建了全基因组的分子标记连锁图,采用区间作图法对控制碱消值的基因进行了定位分析,结果表明,位于第6染色体的qASV6-1为一主效基因,其贡献率高达87．6％,来自于亲本南特号中的等位基因可降低碱消值3．26;其余5个QTLs(qASV2,qASV3,qASV6-2,qASV9,qASV11)为微效基因,分别位于第2,3,6,9和11染色体上,双亲中都带有增效和减效等位基因。     

雄性不交换条件下F2群体区间标记——QTL定位的相关方法（英文）

提出了雄性不交换条件下F2群体区间标记定位QTL的相关方法,并且对其适用的条件进行了讨论,通过对分子区间标记进行赋值,计算在无交叉干涉条件下分子标记与表型值的简单相关系数,并在此基础上进行连锁检验,在特定条件下可以估计数量性状座位（QTL）与分子标记座位间的连锁值。     

作物杂种后代基因型值和杂种优势的预测方法

本文提出了利用作物亲本和F_1预测杂种后代基因型值和杂种优势的统计分析方法.该方法运用加性-显性遗传模型,分析双列杂交试验资料,用MINQUE(1)法估算方差分量以及预测遗传效应值.由加性和显性效应预测值可进一步预测F_1,F_2,BC_1,BC_2,等不同世代的基因型值,在预测F_1群体平均优势和群体超亲优势的基础上,可以推导出其它各世代的杂种优势.提出了预测杂种后代保持超亲优势世代数的简单公式,根据杂交组合F_1群体平均优势和双亲相对遗传差异,便可预测该组合能在生产上直接利用的世代数.以棉花六个品种完全双列杂交试验资料为例,分析了各组合F_1和F_2的基因型值、超亲优势和保持5％超亲优势的世代数.     

基于等度规映射的大鼠初级视觉皮层视像整体特征识别

整体特征是视觉信息的基本特征之一。为了认知大鼠初级视觉皮层神经元对视像整体特征的处理机制,首先给出确定有效响应时间区间的方法,确定了有效响应时间区间;然后,确定有效响应时间区间内、不同整体特征视像刺激下的神经元发放特征,并利用等度规映射进行了特征整合,进而对整合后的特征使用支持向量机进行分类;最后,将该方法应用于大鼠的初级视觉皮层视像整体特征识别,并将其分类结果分别与使用主成分分析法进行特征整合以及直接统计神经元发放特征的分类结果进行了对比。对比表明:该方法较其他两种方法,对于整体特征的识别准确率均有不同程度的明显提高。     

具交叉干涉的三点测交区间标记定位（QTL）的相关方法

本文提出在有交叉干涉条件下,在测交群体中对区间标记座位赋值后求其与待定位的数量性状表型值间的简单相关系数R,以此进行连锁测验,并且在一定条件下用R值求出该数量性状座位（QTL）与各标记座位（ML）间的重组值。     

蛋白质质谱数据缺失值填补方法的比较与评估

基于质谱数据的蛋白质定量分析一直是目前高通量蛋白质组学的重要研究手段.但是基于现有质谱技术的限制,大规模蛋白质定量过程中往往会产生大量的缺失值,这在一定程度上影响了下游分析的准确性.尽管很多缺失值填补方法被不断提出,但是蛋白质组学领域对于不同情况下缺失值填补方法效力的综合评估仍然缺乏.本研究基于真实数据的分布特征,构建...     

区间离散时滞广义系统的鲁棒稳定性

讨论了一类区间离散时滞广义系统的鲁棒稳定性问题,在给出区间离散时滞广义系统的等价描述之后,基于系统参数矩阵不等式,分别得出了时滞独立和时滞依赖情况下区间离散广义系统稳定的充分条件,数值例子说明了该方法的有效性．     

选择指数中计算经济加权值方法的研究

本文介绍了计算选择指数中经济加权值较常用的两种方法— 利润方程和回归法,同时根据我国 的实际情况,将利润方涅和回归法相结合,并利用逐步回归的原理,提出了一种“优化利润回归法”来估 计主要经济性状的经济加权值。文中还利用北京市原种鸡场1986年的经济资料及“京白川系”蛋鸡早 期六个性状的记录资料,说明了优化利润回归法的计算过程及实际效果,结果表明利用此法来计算性状 的相对经济加权值效果很好,可直接用于选择指数。     

Amino acid type-selective backbone 1H-15N-correlations for Arg and Lys

Four novel amino acid type-selective triple resonance experiments to identify the backbone amino proton and nitrogen resonances of Arg and Lys and of their sequential neighbors in (¹³C,¹⁵N)-labeled proteins are presented: the R(i+1)-HSQC and R(i,i+1)-HSQC select signals originating from Arg side chains, the K(i+1)-HSQC and K(i,i+1)-HSQC select signals originating from Lys side chains. The selection is based on exploiting the characteristic chemical shifts of a pair of carbon atoms in Arg and Lys side chains using selective 90° pulses. The new experiments are recorded as two-dimensional ¹H-¹⁵N-correlations and their performance is demonstrated with the application to a protein domain of 83 amino acids.     

Fuzzy logic for elimination of redundant information of microarray data

Gene subset selection is essential for classification and analysis of microarray data. However, gene selection is known to be a very difficult task since gene expression data not only have high dimensionalities, but also contain redundant information and noises. To cope with these difficulties, this paper introduces a fuzzy logic based pre-processing approach composed of two main steps. First, we use fuzzy inference rules to transform the gene expression levels of a given dataset into fuzzy values. Then we apply a similarity relation to these fuzzy values to define fuzzy equiva- lence groups, each group containing strongly similar genes. Dimension reduction is achieved by considering for each group of similar genes a single representative based on mutual information. To assess the usefulness of this approach, exten- sive experimentations were carried out on three well-known public datasets with a combined classification model using three statistic filters and three classifiers.     

Automatic variable selection for exposure-driven propensity score matching with unmeasured confounders

Multivariable model building for propensity score modeling approaches is challenging. A common propensity score approach is exposure-driven propensity score matching, where the best model selection strategy is still unclear. In particular, the situation may require variable selection, while it is still unclear if variables included in the propensity score should be associated with the exposure and the outcome, with either the exposure or the outcome, with at least the exposure or with at least the outcome. Unmeasured confounders, complex correlation structures, and non-normal covariate distributions further complicate matters. We consider the performance of different modeling strategies in a simulation design with a complex but realistic structure and effects on a binary outcome. We compare the strategies in terms of bias and variance in estimated marginal exposure effects. Considering the bias in estimated marginal exposure effects, the most reliable results for estimating the propensity score are obtained by selecting variables related to the exposure. On average this results in the least bias and does not greatly increase variances. Although our results cannot be generalized, this provides a counterexample to existing recommendations in the literature based on simple simulation settings. This highlights that recommendations obtained in simple simulation settings cannot always be generalized to more complex, but realistic settings and that more complex simulation studies are needed.     

Risk-Based Evaluation of Turkish Agricultural Strategies using Fuzzy AHP and Fuzzy ANP

In this article, we propose a model for selection of an agricultural strategy for Turkey by using fuzzy analytical hierarchy process (AHP) and analytical network process (ANP) based on linguistic terms. Fuzzy AHP-based methodology will be discussed to tackle the different decision criteria such as risk factors, ecological structure, socioeconomic structure, and technological structure involved in the selection of an agricultural strategy for Turkey and ANP will represent an effective tool for providing a suitable solution for managers and government administrators of this case. The linguistic levels of comparisons produced by the experts for each comparison are tapped in the form of triangular fuzzy numbers in order to construct fuzzy pairwise comparison matrices. The implementation of the system is demonstrated by a problem having four stages of hierarchy that contains 4 criteria and 15 sub-criteria.     

Characterization of TAP Ambr 250 disposable bioreactors,as a reliable scale‐down model for biologics process development

Demands for development of biological therapies is rapidly increasing, as is the drive to reduce time to patient. In order to speed up development, the disposable Automated Microscale Bioreactor (Ambr 250) system is increasingly gaining interest due to its advantages, including highly automated control, high throughput capacity, and short turnaround time. Traditional early stage upstream process development conducted in 2 ‐ 5 L bench‐top bioreactors requires high foot‐print, and running cost. The establishment of the Ambr 250 as a scale‐down model leads to many benefits in process development. In this study, a comprehensive characterization of mass transfer coefficient (k_La) in the Ambr 250 was conducted to define optimal operational conditions. Scale‐down approaches, including dimensionless volumetric flow rate (vvm), power per unit volume (P/V) and k_La have been evaluated using different cell lines. This study demonstrates that the Ambr 250 generated comparable profiles of cell growth and protein production, as seen at 5‐L and 1000‐L bioreactor scales, when using k_La as a scale‐down parameter. In addition to mimicking processes at large scales, the suitability of the Ambr 250 as a tool for clone selection, which is traditionally conducted in bench‐top bioreactors, was investigated. Data show that cell growth, productivity, metabolite profiles, and product qualities of material generated using the Ambr 250 were comparable to those from 5‐L bioreactors. Therefore, Ambr 250 can be used for clone selection and process development as a replacement for traditional bench‐top bioreactors minimizing resource utilization during the early stages of development in the biopharmaceutical industry. © 2017 American Institute of Chemical Engineers Biotechnol. Prog., 33:478–489, 2017     

A cost-effective plasmid purification protocol suitable for fluorescent automated DNA sequencing

A cost-effective, reliable, and reproducible method has been developed to produce good-quality, double-stranded plasmid DNA for automated sequence analysis. The method incorporates modifications to a previously described plasmid-purification protocol used in manual sequencing. The quality of the DNA produced from the present protocol is suitable for automated fluorescent sequencing. Using a dye-terminator sequencing protocol, most runs using plasmid DNA prepared using this protocol produced over 700 bases with greater than 99% base-calling accuracy.     

Healthcare Failure Mode and Effects Analysis Under Fuzziness

Failure modes and effects analysis (FMEA) is a step-by-step approach for identifying all possible failures in a design, a manufacturing or assembly process, or a product or service. The purpose of the FMEA is to take actions to eliminate or reduce failures, starting with the highest-priority ones. This article presents a basis for prioritizing the healthcare problems using FMEA with linguistic variables and fuzzy if–then rules. Severity rating of healthcare problems is handled under the categories of catastrophic, major, moderate, and minor events. MATLAB 2007 is used to obtain the results of fuzzy if–then rules for prioritizing healthcare failures. A numerical example is given for four possible healthcare problems to be prioritized, which are wrong patient, delay in therapy, wrong analgesic selection, and wrong drug.     

The use of an automated cell tracking system to identify specific cell types competent for regeneration and transformation

Summary Combining stepper-motors for microscope stage movement with a specially designed software program has led to the establishment of an efficient cell tracking system. Cell immobilization, fixed reference points for calibration of target cell positions, and a video recording system complete the cell finder system. Specific cells can be identified (either beforehand or in retrospect), their locations fixed, and subsequent development of the individual cells monitored daily using computer-assisted relocation. In this way, the specific cell type capable of sustained division and regeneration has recently been identified within a low efficiency protoplast system of a recalcitrant species, sugarbeet. These totipotent cells originated from stomatal guard cells. Isolation and purification procedures were then optimized in a directed way to yield millions of guard cell protoplasts (GCPs). Using polyethylene glycol (PEG)-mediated gene transfer and glucuronidase (GUS) activity for transient expression studies proved that GCPs were amenable to transformation. Gene transfer efficiency was high, as was the number of stably transformed plants that can be produced. At present, the optimized procedure yields 600 transgenic individuals per person per year. This number allows for the selection of the best plants with regard to copy number, DNA insert size, gene expression, and field performance. Prospects for future application of the cell finder system will be discussed. Presented as part of the symposium “Early Events in Tissue Culture and Transformation at the Cellular Level” at the 1997 Congress on In Vitro Biology, Washington, DC 14–18 June 1997.     

Industrial strain improvement: Mutagenesis and random screening procedures

Industrial strain improvement plays a central role in the commercial development of microbial fermentation processes. In recent years new procedures such as rational screening and genetic engineering have begun to make a significant contribution to this activity but mutagenesis and selection - so-called ‘random screening’ - is still a cost-effective procedure, and for reliable short-term strain development is frequently the method of choice. The current practice of strain improvement by mutagenesis and selection is a highly developed technique drawing on the latest advances from a wide range of scientific and technical disciplines. Mutagenic procedures can be optimized in terms of type of mutagen and dose, mutagen specificity effects can be taken into account and mutagenesis itself can be enhanced or directed in order to obtain the maximum frequency of desirable mutant types among the isolates to be screened. Screens can be designed to allow maximum expression of the desirable mutant types and the application of statistically-based screening procedures will maximize the probability of detecting them. Automated procedures can be developed using robotics and microprocessors to increase the numbers of isolates that can be processed through a screen per unit time. The relationship between screening and production conditions can be organized so as to minimize the probability of improved isolates selected by the screen failing to scale up.     

基于LSMM和改进的FCM提取城市植被覆盖度——以北京市海淀区为例

植被是城市生态系统的重要组成部分,及时获取植被覆盖信息对城市生态环境监测具有重要意义。利用中分辨率Landsat TM遥感数据,采用线性光谱分解模型(LSMM)开展城市植被覆盖度提取;同时,通过改进训练样本选择方式,在最小噪声变换(MNF)、像元纯净指数分析(PPI)、N维可视化分析基础上得到端元样本,再运用模糊C-均值(FCM)获取植被覆盖度;最后以高分辨率SPOT5遥感数据对两种方式的提取结果进行精度检验。结果显示,基于LSMM和改进的FCM提取的城市植被覆盖度与检验数据相关系数分别为0.8252和0.9381,后者可以较好地处理其他要素的非线性影响,因而具有较高精度。