单增李斯特菌在牛奶中生长曲线的拟合和预测模型的建立

通过生长动力学曲线拟合,建立牛奶中单增李斯特菌的生长预测模型。比较了5、15、25和35℃条件下Gompertz方程、Logistic方程和Hill方程的拟合情况,确定Gompertz方程为单增李斯特菌在牛奶中最优的初级模型。采用Belehradek方程描述温度对最大生长速率和延滞时间的影响,结果表明它们之间成良好的线性关系(R2分别为0.9721和0.9747),并建立了相应的二级模型。对20℃条件下由预测模型构建的微生物生长动力学方程进行了验证,同时对模型的可靠性进行了分析,结果表明预测值和真实值的残差均小于0.2,模型的偏差度为1.04,准确度为1.13,表明建立的模型有效且可靠。在已知初始菌数的情况下,可以根据模型快速预测5~35℃条件下不同贮藏时间点单增李斯特菌在牛奶中的生长情况。      

Assessment of prediction accuracy of protein function from protein--protein interaction data

Functional prediction of open reading frames coded in the genome is one of the most important tasks in yeast genomics. Among a number of large-scale experiments for assigning certain functional classes to proteins, experiments determining protein-protein interaction are especially important because interacting proteins usually have the same function. Thus, it seems possible to predict the function of a protein when the function of its interacting partner is known. However, in vitro experiments often suffer from artifacts and a protein can often have multiple binding partners with different functions. We developed an objective prediction method that can systematically include the information of indirect interaction. Our method can predict the subcellular localization, the cellular role and the biochemical function of yeast proteins with accuracies of 72.7%, 63.6% and 52.7%, respectively. The prediction accuracy rises for proteins with more than three binding partners and thus we present the open prediction results for 16 such proteins.     

Estimating bacterial density from tube dilution data by a Bayesian method

We have developed a statistical computer program based on a Bayesian approach to estimate bacterial density from tube dilution data. The program calculates an expectation, a mode (equivalent to the traditional most probable number (MPN)) and a median as point estimates of the bacterial density. The Bayesian analysis provides a probability density function which reflects the knowledge accumulated about the bacterial density by observing the data. Its expectation is a summary value that incorporates the shape and skewness of the distribution. On the other hand, the MPN (mode) only uses the single most likely value and ignores other values that are consistent with the data. As a result the MPN consistently underestimates the bacterial density and is likely to produce large errors. Thus we recommend the use of the expectation as an estimator for most problems. The theoretical basis of the Bayesian approach and its application toSalmonelladata is discussed. Tables of results for different combinations of tube dilutions are also presented.     

双向数据挖掘的反馈预测分析

针对常规的数据挖掘预测模型只进行单一预测且未对预测的准确度进行分析等问题,提出了一种将关联模型和基于最小二乘法的回归分析模型相结合的反馈预测模型,并使用最小均方算法对预测进行误差分析.仿真结果表明该模型对中长期预测具有较高的精确度.     

The prediction of water activity of some supersaturated non-electrolyte aqueous binary solutions from ternary data

Binary data are required for prediction of the water activities of multicomponent aqueous solutions by various methods. At high concentrations, these methods would need binary data beyond the solubility limits of individual solutes. Such supersaturated data are usually lacking or very difficult to determine experimentally. The Zdanovskii–Stokes–Robinson equation, which has been shown to be a reliable and accurate method for predicting the water activity of complex solutions, may be applied in reverse to calculate the water activities of supersaturated binary solutions from ternary data. Hitherto unpublished supersaturated binary a _w data of mannitol, sucrose and urea obtained using this method as well as polynomials for their prediction are presented in this paper.     

Imaging optical diffuse reflectance in beef muscles for tenderness prediction

The objective of this study was to investigate the potential of a novel optical reflectance imaging method to predict beef tenderness. Two-dimensional (2D) optical reflectance in beef muscles induced by a point incident light was acquired. A set of five parameters were extracted from each reflectance image to describe quantitatively the reflectance profiles. Two parameters, q and B, were derived by numerically fitting the equi-intensity contours of the reflectance pattern. Two spatial gradients were calculated along the directions parallel and perpendicular to muscle fibers and total scattering intensity was obtained by excluding the specular reflectance. This method was applied to analyze 2D images of optical diffuse reflectance in 336 beef samples obtained from 14 steers in which large variations in tenderness were generated by altering animal genetics, suspension method and aging time as well as utilizing muscles varying in their inherent tenderness. Tenderness was evaluated using Warner–Bratzler shear force (WBSF). The effects of animal breed, muscle, types of suspension, and aging were investigated and results indicate that the scattering intensity measured at 1-d was correlated (R² = 0.50 at λ = 720 nm) with 10-d WBSF in M. longissimus dorsi muscles; and the q parameters measured at 1-d was correlated (R² = 0.46 at λ = 720 nm) with 10-d WBSF in M. psoas major muscles. These results show analyzing 2D reflectance images of meat surfaces provides valuable information regarding the physical characteristics of meat that are responsible for beef tenderness.     

Grapevine dormant pruning weight prediction using remotely sensed data

Aerial image analysis was utilised to predict dormant pruning weights between two growing seasons. We utilised an existing in-row spacing trial in order to examine the relationship between dormant pruning weights and remotely sensed data. The experimental vineyard had a constant between-row spacing (2.44 m) and five different in-row spacings (0.91, 1.52, 2.13, 2.74 and 3.35 m) resulting in spatial variation in canopy volume and dormant pruning weights (kg/metre of row). It was shown that the ratio vegetation index (NIR/R) was linearly correlated with field-wide measurements of pruning weight density (dormant pruning weight per metre of canopy) for both the 1998 and 1999 growing seasons (r²= 0.68 and 0.88, respectively). Additionally, it was shown that the regression parameters remained consistent between the two growing seasons allowing for an inter-annual comparison such that the vegetation index vs canopy parameter relationship determined for the 1998 growing season was used to predict field-wide pruning weight densities in the 1999 growing season prior to harvest.     

Growth rate as a predictor of density and mechanical quality of sawn timber from fast growing species

Mechanical quality of structural timber (50×150×3200 mm) is assessed by means of growth rates in different softwoods (Pinus radiata, P. pinaster, P. sylvestris), most of them fast grown species, and hardwoods (Populus sp. andEucalyptus globulus) grown in Spain. The utility of using average density instead of average growth rate is also assessed. Growth rate did not appreciably influence the density and bending properties of timber, and so its utility as predictor of the mechanical quality of timber is very low.     

Measurement of mixing-controlled reactive transport in homogeneous porous media and its prediction from conservative tracer test data

Numerical and theoretical studies have indicated that pore-scale mixing can be the limiting process for reactions among dissolved compounds in porous media. It has been claimed that multicomponent reactions in porous media could be accurately estimated using mixing coefficients obtained from point-like measurements of conservative tracer concentrations. In this study, we verify these concepts experimentally by tracer tests in a homogeneously packed saturated sand column. Fiber-optic fluorometry was applied to detect point-related concentrations of fluorescein, which was used as both the conservative and the reactive tracer. In the reactive tracer experiment, an acidic solution containing the tracer was displaced by an alkaline solution without tracer. Since the fluorescence of fluorescein is quenched at low pH, the fluorescence intensity measured in the reactive breakthrough curve indicated the mixing of the two solutions. The measured reactive breakthrough curves were compared to predictions based on the conservative breakthrough curves. Predictions and measurements agreed well. Our results imply that incomplete mixing on the pore scale is of minor significance for field-scale applications. On this scale, however, even weak sorption might influence mixing significantly.     

密度非均匀分布纬编针织物的变形预测及仿真

针对不同密度的纬编针织物组织结合形成的织物成品变形明显、成品效果预测难度大的问题,提出了一种密度非均匀分布的纬编针织物的变形预测及仿真方法。基于织物中不同密度成员织物组织的具体分布情况,提出了对应的织物弹簧-质点模型的初始状态的确定方法,在此基础上对质点进行受力分析并建立相应的力学微分方程,通过数值方法求解力学微分方程得到质点位置;基于二维Peirce线圈模型建立NURBS线圈模型,并确定曲线控制顶点和织物圈距、圈高的关系,进一步建立质点-控制点关联式;将质点受力偏移后的位置代入质点-控制点关联式,实现带有曲线线圈形态的密度非均匀分布的纬编针织物变形模拟;将织物仿真图与真实针织样品进行对比,结果表明仿真效果可靠。     

Mathematical model developed for environmental samples: prediction of GC/MS dioxin TEQ from XDS-CALUX bioassay data

Remediation of hazardous waste sites requires efficient and cost-effective methods to assess the extent of contamination by toxic substances including dioxin-like chemicals. Traditionally, dioxin-like contamination has been assessed by gas chromatography/high-resolution mass spectrometry (GC/MS) analysis for specific polychlorinated dibenzo-p-dioxins, dibenzofurans, and biphenyl congeners. Toxic equivalency factors for these congeners are then used to estimate the overall dioxin toxic equivalency (TEQ) of complex mixtures found in samples. The XDS-CALUX bioassay estimates contamination by dioxin-like chemicals in a sample extract by measuring expression of a sensitive reporter gene in genetically engineered cells. The output of the XDS-CALUX assay is a CALUX-TEQ value, calibrated based on TCDD standards. Soil samples taken from a variety of hazardous waste sites were measured using the XDS-CALUX bioassay and GC/MS. TEQ and CALUX-TEQ from these methods were compared, and a mathematical model was developed describing the relationship between these two data sets: log(TEQ) = 0.654 x log(CALUX-TEQ) + 0.058-(log(CALUX-TEQ))2. Applying this equation to these samples showed that predicted and GC/MS measured TEQ values strongly correlate (R2 = 0.876) and that TEQ values predicted from CALUX-TEQ were on average nearly identical to the GC/MS-TEQ. The ability of XDS-CALUX bioassay data to predict GC/MS-derived TEQ data should make this procedure useful in risk assessment and management decisions.     

烤肠中芽孢杆菌生长动力学模型及货架期预测

以真空包装烤肠中芽孢杆菌为研究对象,建立其生长动力学模型及货架期预测模型。将同批次真空包装烤肠存放于4,10,25℃条件下,定期进行各指标测定,由此建立其中芽孢杆菌生长的一级和二级模型以及货架期预测模型。结果表明,修正的Gompertz模型可以很好的描述烤肠中的芽孢杆菌的生长情况,建立不同温度下3个一级生长动力学模型,其R2均在0.960以上,其偏差因子Bf与准确因子Af值均在可接受范围内;平方根(Belehradck)模型可以很好的描述温度与延滞时间(λ)、最大比生长速率(μmax)间的关系,建立了温度与延滞时间、最大比生长速率间的二级模型,其R2均在0.940以上,其残差的绝对值均小于0.1;通过一级和二级模型建立出了真空包装烤肠在4～25℃条件下贮存的货架期预测模型。     

Developing novel 3D measurement techniques and prediction method for food density determination

Density is a physical characteristic which depends on the experimental technique used and structural properties of food. True, apparent, and bulk are different types of densities based on the way volume is measured. For porous foods such as grain food products, accurate measurement of density is challenging. Current measurement techniques for food density are inconsistent and nutrient databases do not have sufficient density data. Computed tomography (CT) and magnetic resonance imaging (MRI), laser scanners are non-destructive diagnostic tools for characterizing food microstructure. The objectives of this study were to 1) optimize the parameters of CT, MRI, and laser scanner to determine food density and compare the corresponding values with other traditional techniques, and 2) to develop neural networks as a prediction method for apparent and bulk densities. MicroCT 40 (Scano Medical Inc.), Lightspeed QX/i clinical CT (GE Healthcare), and 3 Tesla Signa HDx MRI (GE Healthcare) were used to acquire 3D images of foods for true density. A 3D laser scanner (NextEngine, Inc) was used to scan the foods items for apparent density. Neural networks were used in conjunction with the data collected from laser scanner and using food composition and processing conditions to generate a black-box prediction scheme. The results of CT, MRI, and laser scanner showed great potential to estimate density in comparison to traditional techniques. Porosity was estimated from the CT and MRI scanned image data. Laser scanner was successful in acquiring 3D images and calculating apparent density. Neural networks provided reliable density prediction power and were comparable to the other empirical equations in terms of accuracy. The ability to predict food density based on composition and processing conditions is necessary to fill gaps in nutrient databases and account for new foods.     

Accurate prediction of protein functional class from sequence in the Mycobacterium tuberculosis and Escherichia coli genomes using data mining

The analysis of genomics data needs to become as automated as its generation. Here we present a novel data-mining approach to predicting protein functional class from sequence. This method is based on a combination of inductive logic programming clustering and rule learning. We demonstrate the effectiveness of this approach on the M. tuberculosis and E. coli genomes, and identify biologically interpretable rules which predict protein functional class from information only available from the sequence. These rules predict 65% of the ORFs with no assigned function in M. tuberculosis and 24% of those in E. coli, with an estimated accuracy of 60-80% (depending on the level of functional assignment). The rules are founded on a combination of detection of remote homology, convergent evolution and horizontal gene transfer. We identify rules that predict protein functional class even in the absence of detectable sequence or structural homology. These rules give insight into the evolutionary history of M. tuberculosis and E. coli.     

基于形态特征和多基因序列鉴定储藏稻谷的优势真菌

稻谷储藏期间,真菌生长会影响稻谷质量,严重时会产生真菌毒素,引起食品安全问题。确定储藏期间稻谷的真菌群落组成并准确鉴定优势真菌,是实现有效防控危害真菌的前提,对于保障稻谷的品质和食品安全具有重要意义。基于此,利用传统的微生物分离培养方法,确定了不同地区粮仓内储存稻谷的真菌群落组成,并结合模式菌株和国际权威菌株序列,采用形态学观察及多基因联合系统发育分析方法准确鉴定我国储藏稻谷的优势种。结果表明,南方地区优势种为黄曲霉Aspergillus flavus、黑曲霉A. niger和蒙地曲霉A. montevidensis（阿姆斯特丹曲霉A. amstelodami）,北方地区优势种是多育曲霉Aspergillus proliferans和蒙地曲霉A. montevidensis。并阐述了南北方储藏稻谷主要优势种的详细鉴定过程及相关资料,为粮食中主要危害真菌物种的准确鉴定提供参考。     

基于大数据挖掘的医院食品安全风险预测管理模型

目的设计基于大数据挖掘的医院食品安全风险预测管理模型。方法建立医院食品安全风险评估指标体系,并采用三标度法比较影响食品安全指标的重要程度,得到各个指标的权重,后计算食品样品中检测指标不合格率与不合格数,将检测指标的不合格率与不合格数结合为一个风险系数,完成对医院食品安全风险预测。结果实验证明,此次设计的基于大数据挖掘的医院食品安全风险预测管理模型比传统模型预测准确度高。结论可为食品安全领域的发展提供参考依据。     

粘胶织物中烟酰胺的释放曲线及其模型拟合

为将新兴的绿色、高效的超临界CO₂流体整理技术用于生物活性纺织品开发,提高服用类织物附加值,以生物活性药物烟酰胺为模型药物,粘胶织物为基材,利用超临界CO₂流体分别在不同温度、压力条件下制备负载有烟酰胺的生物活性粘胶织物,将其置于释放介质中,考察烟酰胺从粘胶织物中释放行为的影响因素。结果表明：烟酰胺从粘胶织物中的绝对释放量及绝对释放速率与其在粘胶织物上的负载量正相关;低流体温度(60℃)以及高流体压力(20 MPa)下制备的生物活性粘胶织物累积释放百分比及累积释放速率更低,释放平衡时分别接近87.6%、87.3%;烟酰胺从粘胶织物中的释放行为符合Korsmeyer-Peppas模型,其扩散以菲克扩散为主。     

A novel fitting algorithm for alignment curve radius estimation using corneal elevation data in orthokeratology lens trial

Purpose

To evaluate a novel fitting algorithm for estimation of alignment curve (AC) radius during orthokeratology lens trial.