论建立国际通用的计数制度——探讨计数单位和计数方法的国际标准化问题

前言在科学领域中,任何一种国际通用的制度的建立和国际标准化的实现,都是以利于国际间交流和科研工作为目的的,都是建立在人类社会需要的基础之上的。国际通用的计数制度也不利外,随着科学技术和国际间经济、文化交流的高度发展,建立一个国际通用的计数制度(参考计量制度)势在必行。长期以来,当人们想到或遇到欧美人把中国的“亿”计作成“100million”或“100兆”,把“万”计作“10千”,或者中国人和日本人把欧美的“bi11ion”计作”10亿”,把“million”计作“100万”时.

阿片类药物需要量的估算方法及应用进展

目的 梳理阿片类药物需要量的估算方法应用现状和问题,为推进合理用药、改善估算方法提出建议。方法检索中国知网、万方数据、PubMed、国际麻醉品管制局有关文件,对纳入文献进行汇总和分析。结果 目前国际上估算阿片类药物需求量主要有3种方法,3种方法对数据要求各不相同,各有优缺点。结论 结合现存问题,建议监管部门投入更多资源,持续改善估算方法规则制定和药物数据记录质量;完善药物估算制度,促进阿片类药物的合理使用。

Correlates of subjectively and objectively measured physical activity in young adolescents

Background： Many studies examining individual-level correlates in youth utilize self-report rather than objective measures of physical activity （PA）. This utilization of self-report may result in associations that are not present when examining objectively measured PA. The present study investigates the relationship between hypothesized correlates of PA with objectively and subjectively measured PA. Methods： Participating children （n 232, 101 males, mean age - 12.3 years） provided a minimum of four monitored days of PA （via accelerometer） and completed a survey assessing moderate-to-vigorous physical activity （MVPA）, sport competence, appearance, enjoyment, and self-efficacy. Height and weight were measured and body mass index （BMI） was calculated. Results： Hierarchical regression models controlling for sex, race, and BMI Z-score showed that only sex and BMI Z-score were significant correlates of objective MVPA while only sex was a significant correlate of objective total PA. However, in a separate model examining the relationship with subjective MVPA, enjoyment of PA and self-efficacy for PA were the only significant correlates of self-reported PA. Conclusion： Measuring MVPA via self-report versus accelerometry produces considerably different results in a sample of young adolescents. Future studies should use caution when selecting outcome measures if the intent is to identify modifiable correlates of MVPA in youth.

Kinematics modeling of a 6-PSS parallel mechanism with wide-range flexure hinges

A novel 6-PSS flexible parallel mechanism was presented,which employed wide-range flexure hinges as passive joints.The proposed mechanism features micron level positioning accuracy over cubic centimeter scale workspace.A three-layer back-propagation(BP) neural network was utilized to the kinematics analysis,in which learning samples containing 1 280 groups of data based on stiffness-matrix method were used to train the BP model.The kinematics performance was accurately calculated by using the constructed BP model with 19 hidden nodes.Compared with the stiffness model,the simulation and numerical results validate that BP model can achieve millisecond level computation time and micron level calculation accuracy.The concept and approach outlined can be extended to a variety of applications.

Parameter identification of inertially stabilized platforms using current command design

Accurate parameter identification is essential when designing controllers for inertially stabilized platforms （lSPs）. But traditional identification methods suffer from observation measurement noise and operating restrictions of ISPs. To address this issue, a novel identification method based on current command design and multilevel coordinate search （MCS） algorithm without any higher order measurement differentiations was proposed. The designed current commands were adopted to obtain parameter decoupled models with the platform operating under allowable conditions. MCS algorithm was employed to estimate the parameters based on parameter decoupled models. A comparison experiment between the proposed method and non-linear least square method was carried out and most of the relative errors of identified parameters obtained by the proposed method were below 10%. Simulation and experiment based on identified parameters were conducted. A velocity control structure was also developed with disturbance observer （DOB） for application in disturbance compensation control system of an ISR Experimental results show that the control scheme based on the identified parameters with DOB has the best disturbance rejection performance. It reduces the peak to peak value （PPV） of velocity error integral to 0.8 mrad which is much smaller than the value （10 mrad） obtained by the single velocity controller without DOB. Compared with the control scheme based on sweep model with DOB compensation, the proposed control scheme improves the PPV of velocity error integral by 1.625 times.

Integrating Data Mining Into Managerial Accounting System： Challenges and Opportunities

Data mining involves extracting information from large data sets, discovering the hidden relationships and unknown dependencies, and supporting strategic decision-making tasks. The alignment of data mining and business would bring benefits to the organization＇s management. The study investigated the adoption of data mining technologies in managerial accounting system, concentrating on the challenges and opportunities. The research showed that with the technology adoption, managerial functions could be improved and current information system could be upgraded. Since the technical progresses are reshaping the world of business and accountancy, it is significant for accountants and finance professionals to exploit information technologies.

Inverted Simulations Demonstrating Strong Ecological Fallacies in Cohort Studies

We start with a description of the statistical inferential framework and the duality between observed data and the true state of nature that underlies it. We demonstrate here that the usual testing of dueling hypotheses and the acceptance of one and the rejection of the other is a framework which can often be faulty when such inferences are applied to individual subjects. This follows from noting that the statistical inferential framework is predominantly based on conclusions drawn for aggregates and noting that what is true in the aggregate frequently does not hold for individuals, an ecological fallacy. Such a fallacy is usually seen as problematic when each data record represents aggregate statistics for counties or districts and not data for individuals. Here we demonstrate strong ecological fallacies even when using subject data. Inverted simulations, of trials rightly sized to detect meaningful differences, yielding a statistically significant p-value of 0.000001 （1 in a million） and associated with clinically meaningful differences between a hypothetical new therapy and a standard therapy, had a proportion of instances of subjects with standard therapy effect better than new therapy effects close to 30%. A ―winner take all‖ choice between two hypotheses may not be supported by statistically significant differences based on stochastic data. We also argue the incorrectness across many individuals of other summaries such as correlations, density estimates, standard deviations and predictions based on machine learning models. Despite artifacts we support the use of prospective clinical trials and careful unbiased model building as necessary first steps. In health care, high touch personalized care based on patient level data will remain relevant even as we adopt more high tech data-intensive personalized therapeutic strategies based on aggregates.

Research on NC interpolation Algorithm based on STM32

This paper analyzes the principle of spline interpolation, pointed out the reasons for the feed rate fluctuations and proposed interpolation algorithm based on the secant iteration method NURBS curve. The algorithm of the speed the planning section uses cubic polynomial acceleration and deceleration control methods to ensure the acceleration of the process of continuous high-speed operation, so that the machine runs smoothly, avoiding the machine have a big impact; while parameter calculation part using the Secant iterative interpolation method to calculate parameter, reducing the speed fluctuation, the machine is further reduced tremor. Simulation results show that the algorithm can obtain a continuous velocity and acceleration curves, and can be controlled in real time interpolation velocity fluctuations in the ideal range, the machine achieve the smooth running ,and meet the high-speed, high quality processing requirements.

Analysis and optimum design of rider-bicycle mechanisms:Design of bicycle parameters for a specified rider

Optimum design of rider-bicycle mechanisms is very important for customizing bicycles and plays a crucial role in the improvement of athletes' performances and in protection of the riders.Since the birth of the first bicycle,people have been keeping optimizing bicycles with respect to physical conditions of human.In modern design,the basic structure of a bicycle has been formulized,while many geographic parameters remain uncertain.In this paper,the bicycle and the human body are considered as a kinematic mechanism,called rider-bicycle mechanism.The optimum design is implemented from the perspective of mechanism.Effort-saving and comfortableness are considered at the same time.The corresponding performance charts are drawn and the relationship between the performances and parameters of seat height,crank length and body parameters are discussed.By using these charts,the optimal design method of bicycle's parameters for a specified person is then founded.Optimum solutions to get suitable seat height and crank length for a person are obtained accordingly.The research is of significance for customizing bicycles and design of bicycle robot.

Statistical Structures on Metric Path Spaces

The authors extend the notion of statistical structure from Riemannian geometry to the general framework of path spaces endowed with a nonlinear connection and a generalized metric.Two particular cases of statistical data are defined.The existence and uniqueness of a nonlinear connection corresponding to these classes is proved.Two Koszul tensors are introduced in accordance with the Riemannian approach.As applications,the authors treat the Finslerian (α,β)-metrics and the Beil metrics used in relativity and field theories while the support Riemannian metric is the Fisher-Rao metric of a statistical model.