MMSE as a predictor of on-road driving performance in community dwelling older drivers

Screening tools such as the MMSE have been used extensively in driving research studies to determine mild cognitive impairment or dementia. While some studies have shown the MMSE to correlate with driving performance, few studies have shown the predictive validity of the MMSE in determining on-road performance. In a sample of 168 community dwelling older adults, including 20 with Parkinson's disease (PD), the primary objective was to determine the validity of the MMSE to predict pass/fail outcomes of an on-road driving test using receiver operating characteristics curves. The area under the curve (AUC), an index of discriminability, for the total sample was .654, 95% CI = 0.536–0.772, p = .009. Meanwhile, the AUC for the PD group was 0.791, 95% CI = 0.587–0.996, p = .036. The total sample showed statistically significant yet poor predictive validity. However, the PD group showed statistically significant and good predictive validity of the MMSE to predict pass/fail outcomes on the road test, but caution is warranted as the confidence intervals are wide (due to small sample) and the positive and negative predictive values are less than desirable due to the associated error. The findings show that using the current cut-off point of ≤24 on the MMSE is not adequately sensitive to predict on-road performance in both community dwelling older drivers and in drivers with PD. This study offers strong evidence to support the current best practice of not using the MMSE in isolation to predict on-road performance.     

Criteria for grouping nursing subunits in hospitals.

Data from 135 nursing subunits were used to identify a set of organizational variables that best explained the grouping of activities into nursing subunits in hospitals. Relatively strong support was provided for technology as a basis for grouping nursing subunits; characteristics of the hospital, including its type, size, and location, also were relevant.     

The autocorrelation coefficient as a tool for assessing goodness of fit between bioassay predictions and measurement data

Project IDEAS has produced guidelines for internal dose assessment. An integral part of this process is assessing the goodness of fit of biokinetic models to bioassay data. It is recommended that a fit should only be accepted if (a) it is close enough to the data not to be rejected by a chi2 test and (b) if it looks acceptable to 'the eye'. The latter criterion was added to enable the assessor to reject fits which seemed to display some sort of systematic bias. However, there are problems with both of these tests: (a) the chi2 test is dependent on the assumed uncertainties which are often unknown, (b) 'by eye' assessment is subjective. In this paper, another statistic, the autocorrelation coefficient of the residuals, rho, is investigated. The main advantages of the rho statistic are that it is objective, very sensitive to biasing and independent of the assumed errors.     

The fit between environmental management systems and organisational learning orientation

With the significant increase in the adoption of environmental management systems (EMSs), it is important to evaluate whether EMSs can improve the business value for organisations that adopt them. However, less is known about whether or not EMSs lead to improved firm performance with only few studies evaluating the broad link between an organisation’s environmental strategies and its business performance. Furthermore, previous studies are inconsistent in their findings about the relationship between environmental strategies and firm performance. We attribute this inconsistency to the misfit between environmental strategies and organisational learning orientation which results in operational inefficiency within the firm. This study tries to find out the proper fit pattern between EMSs and organisational learning orientation by investigating their joint effect on firm performance. Based on survey data from 214 Chinese manufacturing companies, we found that the interactions between EMSs and four dimensions of organisational learning orientation have positive impacts on firm performance. Thus, the proper organisational learning orientation for efficiency and effective EMSs is characterised by high levels of commitment to learning, shared vision, open-mindedness and knowledge sharing.     

The fit between capabilities and priorities and its impact on performance improvement: revisiting and extending the theory of production competence

This paper revisits and extends the theory of production competence, which has received wide attention in the operations and production management literature. As such, considering the aspects of quality, delivery, flexibility, and cost, we develop two novel measures that assess the concept of production competence, which is conceptualised as the fit between production and operations management (POM) capabilities and production and operations management priorities. Inherent to both measures is their multi-dimensional conceptualisation of POM capabilities. We then investigate the influence of the production competence measures on the improvement in plant productivity and plant responsiveness, which are more immediate outcomes compared with what had been utilised in prior production competence research. Furthermore, we investigate a range of control variables, an omission in most extant production competence research. We assess the relationship based on data collected recently in a large-scale, multi-national survey encompassing a multitude of industries. Results consistently confirm the impact of the production competence measures on plant-productivity improvement, and partially support the relationship to the improvement in plant responsiveness. The importance of this research is emphasised by the fundamental nature of the theory of production competence to the field of production research, and by limitations in prior studies examining this concept. Most notably, the current research contributes to the theory of production competence by its investigation with two novel measures among a dataset that is much more recent and global in scope compared with prior studies. Our investigation thus contributes to the generalizability of the theory of production competence. Implications for practitioners and academics studying production research are provided.     

A relationship between technology indicators and stock market performance

One of the main objectives of technology analyses is to understand how investing intechnological innovation can have commercial benefits. However, empirical studies of therelationship between investments in technology and subsequent economic performance arerelatively scarce. This paper provides such an analysis by demonstrating how quantitative R&Dand technology indicators may be used to forecast company stock price performance. The purposeof the analysis is to utilize a unique patent database, and the science and technology indicatorsdeveloped from the data therein, to explore this issue of technological competence and economicperformance.The underlying concept behind this study is that the quality of a company's technology isreflected in its patent portfolio. Previous research has shown that a company with a largepercentage of influential patents is much more likely to be technologically successful than acompany with weaker patents. The analysis presented here reveals that such a company is alsomore likely to be successful in capital markets.     

The Manchester Driver Behaviour Questionnaire as a predictor of road traffic accidents

The Driver Behaviour Questionnaire (DBQ) has mainly been used as a predictor of self-reported road traffic accidents. The associations between crashes and the violation and error factors of the DBQ, however, may be spuriously high due to reporting bias. In the present study, the DBQ was tested as a predictor of self-reported and recorded accidents in four samples of private and professional drivers. The findings show that the DBQ scale only predicts self-reported accidents, not recorded crashes, despite the higher validity of company data and the higher means of the recorded data across these samples. The results can be explained by a common method variance bias. In a review of the DBQ research, the use of the instrument was found to be heterogeneous concerning the number of items, scales used and factor analytic methods applied. Thus, the DBQ may not be as homogeneous and as successful in predicting accidents as is often claimed.     

真空发生器结构参数与性能参数关系研究

简要介绍了真空发生器的工作原理及应用,探讨了真空发生器的结构参数与性能参数之间的联系.     

纺丝工艺与PAN/CA中空纤维超滤膜性能的关系

研究了干－湿法纺丝工艺参数对聚丙烯腈／二醋酸纤维素（ＰＡＮ／ＣＡ）中空纤维超滤膜性能的影响。结果表明，随着填充液压力的升高，挤出速率的增大，以及干纺程的增加，中空纤维膜的孔隙率、平均孔直径和水通量增加，截留率下降。内、外凝固液浓度对膜性能有不同的影响。在总拉伸倍数一定的情况下，改变第一二级拉伸，可有效调节中空纤维的性能。     

The perovskite structure – a review of its role in ceramic science and technology

Starting with the history of the fundamental science of the relation of structure to composition delineated completely by Goldschmidt, we use the perovskite structure to illustrate the enormous power of crystal chemistry-based intelligent synthesis in creating new materials. The perovskite structure is shown to be the single most versatile ceramic host. By appropriate changes in composition one can modify the most significant electroceramic dielectric (BaTiO₃ and its relatives) phase in industry, into metallic conductors, superconductors or the highest pressure phases in the earth. After an historical introduction of the science, detailed treatment of the applications is confined to the most recent research on novel uses in piezoelectric, ferroelectric and related applications. Received: 29 November 1999 / Accepted: 3 July 2000     

表面结构与碳毡吸湿性能的相关性研究

以不同类型碳毡经过石墨化处理后表面结构与形貌的变化为基础,研究了碳毡的表面结构与吸湿性之间的关系.研究表明表面亲水基团、粗糙的形貌结构、石墨微晶结构规整性提高都会使碳毡的吸湿性能提升.为制备低吸潮、高纯度碳毡奠定理论基础.     

错位微缝板吸声性能研究

目前,微穿孔板和微缝板吸声理论成熟、应用广泛。一般,薄板确保了其具备良好的吸声性能,却限制了其工程应用范围。错位微缝板融合了微穿孔板和微缝板,由双层板错位交叠而成,每层板由一系列微缝组成,上下两层微缝交错处形成微孔。交错后的微缝只在交汇的微孔处是通透的,交错形成的微孔仅是一个微孔截面,几何厚度为零。对错位微缝板进行黏热声学仿真,得到结构的相对声阻抗和吸声系数与实验数据一致性较好。仿真分析表明,结构的微孔截面处声压梯度和空气粒子振动速度最大,其黏热声能耗散主要集中在微孔截面的边界处,错位微缝板的厚度对吸声性能的影响远小于微穿孔板和微缝板,可以在厚板上实现较好的吸声性能。     

Evaluation of the spectral fit algorithm as functions of frequency range and deltakaeff.

Considerable effort has been directed at quantifying the properties of the tissue microstructure (i.e., scatterer correlation length) to diagnose disease and monitor treatment. In vivo assessments have had limited success due to frequency-dependent attenuation along the propagation path (i.e., total attenuation) masking the frequency dependence of the scattering from the tissue microstructure. Previously, both total attenuation and scatterer correlation length, given by the effective radius, were solved simultaneously by a two-parameter minimization of the mean squared error between a reference spectrum, modified by the attenuation and scatterer effective radius, and the backscattered waveforms using an algorithm termed the spectral fit algorithm. Herein, the impact of frequency range (largest frequency minus smallest frequency) and deltakaeff (largest kaeff value minus smallest kaeff value; k is wave number and aeff is scatterer effective radius) used by the spectral fit algorithm on estimating the scatterer effective radius, and total attenuation was assessed by computer simulations while excluding frequencies of the backscattered power spectrum dominated by electronic noise. The simulations varied the effective radius of the scatterers (5 microm to 150 microm), the attenuation of the region (0 to 1 dB/cm-MHz), the bandwidth of the source, and the amount of electronic noise added to the radio frequency (rf) waveforms. The center frequency of the source was maintained at 8 MHz. Comparable accuracy and precision of the scatterer effective radius were obtained for all the simulations whenever the same deltakaeff was used to obtain the estimates. A deltakaeff of 1 gave an accuracy and precision of approximately 15% +/- 35%, and a width of 1.5 gave an accuracy and precision of approximately 5% +/- 15% consistently for all of the simulations. Similarly, the accuracy and precision of the total attenuation estimate were improved by increasing the frequency range used by the spectral fit algorithm.     

Highest electron affinity as a predictor of cluster anion structures

Small clusters have a range of unique physical and chemical phenomena that are strongly size dependent. However, analysis of these phenomena often assumes that thermodynamic equilibrium conditions prevail. We compare experimentally measured and ab initio computed photoelectron spectra of bare and deuterated silicon cluster anions produced in a plasma environment. We find that the isomers detected experimentally are usually not the ground-state isomers, but metastable ones, which indicates that cluster relaxation is strongly limited kinetically by a dwell time that is much shorter than the relaxation time. We show that, under these conditions, the highest electron affinity replaces the traditional lowest total energy as the appropriate criterion for predicting isomer structures. These findings demonstrate that a stringent examination of non-equilibrium effects can be crucial for a correct analysis of cluster properties.     

Sustainable economic development across globe: The dynamics between technology,digital trade and economic performance

Technology makes a significant contribution to economic performance globally. Information and communication technologies and the economic growth nexus are widely debated; however, this study examined the economic performance of 93 countries categorized as developed and developing countries between 2005 and 2019. The study employs Breitung et al.'s [1] novel bias-corrected method of moments estimators for dynamic panel data models. To serve the purpose, the study utilizes the novel Bias-corrected method of moments estimators for dynamic panel data models by Breitung et al. [1]. The results were threefold: first, technology has both direct and indirect impacts on economic performance. Education plays a moderating role in further escalating economic performance through technology across the globe. Second, digital trade does contribute to economic growth as well. Third, there is a heterogeneous effect of COVID-19 on economic performance across various income groups of countries. The innovative results of the study suggest important policy recommendations.     

The relation between fit and prediction for alternative forms of learning curves and relearning curves

Learning-curve models fitted to initial data are used to predict subsequent performance; however, the model that fits the initial data best may not predict best in future periods - a paradox documented in applications of other prediction models. Little evidence exists about the magnitude of the problem in the domain of learning curves and relearning curves. Using laboratory data, the authors examine the predictive ability of alternative models, examine the strength of the relation between goodness-of-fit and predictive ability, and test whether this relation is the same for both learning curves and relearning curves. Although the correlations between measures of goodness-of-fit and predictive ability are not high, one curve (a log-log-linear model recently introduced to the literature) tended to dominate the rankings on the basis of predictive ability for both learning curves and relearning curves. This curve also tended to provide the best fit in the estimation period as a relearning curve, and the second-best fit as a learning curve.     

The relationship between plastic flow macrolocalization and a dislocation structure

We have established a quantitative relationship between the spatial period of localization of plastic straining and the parameters of the dislocation structure of a zirconium alloy. It is found that the wavelength of localized straining is proportional to the average size of elements of a dislocation substructure formed in the material in various stages of plastic flow. A quantitative interpretation of this relationship is proposed.     

Correlation between the capacitor performance and pore structure of ordered mesoporous carbons

Mesoporous carbons were synthesized by organic–organic self-assembly of triblock copolymer F127 and phenolic resin oligomers composed of resorcinol–formaldehyde or resorcinol–furfural. The mesostructure control was performed by using different polymerization catalysts, ammonia and acetic acid. The effects of the aldehyde and polymerization catalyst on pore architecture of mesoporous carbons were investigated. Disordered mesostructure with poorly disconnected mesopores was formed using furfural. In contrast, when formaldehyde was used, ordered structure with mesochannels was formed. In addition, changes in mesochannel length and the degree of long-range order are found to depend on polymerization catalyst. The porous carbons with different structure were used as a model material to investigate the ion storage/transfer behavior in electrical double-layer capacitor. Electrochemical cyclic voltammetry measurements were conducted in 1 M sulfuric acid electrolyte solution. The ordered mesoporous carbons show superior capacitances and rate performance over the disordered carbons. Electrochemical impedance spectroscopy was used to assess the transport properties. The impedance data clearly demonstrated that the degree of long-range order and channel length can influence the ion transport, resulting in superior capacitive performances.     

活性炭的孔结构与其电容特性的关系研究

采用传统工艺制备了超级电容器用高比表面积微孔炭,利于氮气吸附、循环伏安和恒流充放电研究了样品的孔结构和电容特性.结果表明,试验研制的微孔炭的比表面积达到2496m2/g,大孔径微孔含量很高,在5mA/cm2的电流密度下,活性炭的比容达到307F/g,而且具有良好的功率特性.超级电容器用活性炭的比容主要来自微孔比表面积的贡献,中孔对比容的贡献很小,其作用主要是改善功率特性.为了获得高比容和高功率密度,活性炭应该具有尽可能多的大孔径微孔和适量的小孔径中孔.     

Utility of R0 as a predictor of disease invasion in structured populations

Early theoretical work on disease invasion typically assumed large and well-mixed host populations. Many human and wildlife systems, however, have small groups with limited movement among groups. In these situations, the basic reproductive number, R0, is likely to be a poor predictor of a disease pandemic because it typically does not account for group structure and movement of individuals among groups. We extend recent work by combining the movement of hosts, transmission within groups, recovery from infection and the recruitment of new susceptibles into a stochastic model of disease in a host metapopulation. We focus on how recruitment of susceptibles affects disease invasion and how population structure can affect the frequency of superspreading events (SSEs). We show that the frequency of SSEs may decrease with the reduced movement and the group sizes due to the limited number of susceptible individuals available. Classification tree analysis of the model results illustrates the hierarchical nature of disease invasion in host metapopulations. First, the pathogen must effectively transmit within a group (R0>1), and then the pathogen must persist within a group long enough to allow for movement among the groups. Therefore, the factors affecting disease persistence--such as infectious period, group size and recruitment of new susceptibles--are as important as the local transmission rates in predicting the spread of pathogens across a metapopulation.