Small sample estimation for Taylor's power law

An analysis of counts of sample size N=2 arising from a survey of the grass Bromus commutatus identified several factors which might seriously affect the estimation of parameters of Taylor's power law for such small sample sizes. The small sample estimation of Taylor's power law was studied by simulation. For each of five small sample sizes, N=2, 3, 5, 15 and 30, samples were simulated from populations for which the underlying known relationship between variance and mean was given by ² = c^d. One thousand samples generated from the negative binomial distribution were simulated for each of the six combinations of c=1,2 and 11, and d=1, 2, at each of four mean densities, =0.5, 1, 10 and 100, giving 4000 samples for each combination. Estimates of Taylor's power law parameters were obtained for each combination by regressing log₁₀ s ² on log₁₀ m, where s ² and m are the sample variance and mean, respectively. Bias in the parameter estimates, b and log₁₀ a, reduced as N increased and increased with c for both values of d and these relationships were described well by quadratic response surfaces. The factors which affect small-sample estimation are: (i) exclusion of samples for which m = s ² = 0; (ii) exclusion of samples for which s ² = 0, but m > 0; (iii) correlation between log₁₀ s ² and log₁₀ m; (iv) restriction on the maximum variance expressible in a sample; (v) restriction on the minimum variance expressible in a sample; (vi) underestimation of log₁₀ s ² for skew distributions; and (vii) the limited set of possible values of m and s ². These factors and their effect on the parameter estimates are discussed in relation to the simulated samples. The effects of maximum variance restriction and underestimation of log₁₀ s ² were found to be the most severe. We conclude that Taylor's power law should be used with caution if the majority of samples from which s ² and m are calculated have size, N, less than 15. An example is given of the estimated effect of bias when Taylor's power law is used to derive an efficient sampling scheme.     

Side biases in humans (Homo sapiens): three ecological studies on hemispheric asymmetries

Hemispheric asymmetries and side biases have been studied in humans mostly in laboratory settings, and evidence obtained in naturalistic settings is scarce. We here report the results of three studies on human ear preference observed during social interactions in noisy environments, i.e., discotheques. In the first study, a spontaneous right-ear preference was observed during linguistic exchange between interacting individuals. This lateral bias was confirmed in a quasi-experimental study in which a confederate experimenter evoked an ear-orienting response in bystanders, under the pretext of approaching them with a whispered request. In the last study, subjects showed a greater proneness to meet an experimenter’s request when it was directly addressed to the right rather than the left ear. Our findings are in agreement both with laboratory studies on hemispheric lateralization for language and approach/avoidance behavior in humans and with animal research. The present work is one of the few studies demonstrating the natural expression of hemispheric asymmetries, showing their effect in everyday human behavior.     

“精密度偏性分析”是环境监测质量保证的重要手段

“精密度偏性分析”是环境监测质量保证的重要手段。通过它可以了解其方法的误差和检出限是否达到要求,同时也了解实验室和操作人员对该方法的适应性。     

Inter-observer variation in habitat survey data: investigating the consequences for professional practice

Environmental assessments and land-use planning require reliable information on the botanical composition and distribution of habitats. There have been numerous academic studies of inter-observer variation in species-inventory and habitat mapping, but studies addressing the prevalence of inter-observer variation and consequences of poor quality data in professional practice are lacking. This paper addresses these questions via a questionnaire survey of environmental professionals, using the standard Phase 1 and National Vegetation Classification (NVC) survey methods in the United Kingdom. The survey revealed that misidentification of habitat types within survey reports was relatively common (approximating to 20% of all reports seen by respondents over the previous five years). Approximately 40% of respondents who had encountered erroneous reports stated that these had led to inaccurate initial site ecological assessments. Additional field surveys and discussions with surveyors were commonly used to resolve these issues, but for Phase 1 and NVC 26% and 34% of respondents, respectively, had encountered one or more cases where errors resulted in negative consequences for clients commissioning surveys (in terms of extra costs and project delays). Net loss of biodiversity arising from inaccurate reports was reported in at least one instance by 32% and 38% of respondents for Phase 1 and NVC surveys, respectively – results that may contribute to the attrition of natural capital within the UK. The study highlights the need to extend studies of inter-observer variation to consider impacts on environmental assessments and decision-making in professional practice. The potential benefits of introducing an accreditation scheme (favoured by the majority of respondents to the questionnaire) are discussed.     

加强和改进医院新毕业生思想政治工作的思考

随值取向、服度来约束,量来凝聚。着社会的发展和医疗环境的复杂化,医院新毕业生的道德观念、思维方式、价务理念都受到不同程度的冲击。针对这一现状,医院对新毕业生要以严格的制以良好的机制来激励和关爱,以丰富的网络资源来教育,以优秀的团队文化力     

电除尘器中离子风对除尘效果的影响

目的研究电除尘器中离子风对除尘过程的影响。方法分析电除尘器中离子风对除尘效果的影响,建立完整的颗粒荷电模型,在Fluent软件平台上进行计算。结果离子风在电极线附近呈双螺旋结构,正对电极线位置的离子风速度最大,在远离电极线的方向上逐渐变小,越靠近电极线,速度下降的梯度越大,对流场有扰动作用,随流速增加,离子风效应被逐渐削弱。当主流速小于等于0.5 m/s时,离子风体现为增大驱进速度,颗粒更快到达极板,有利于改善除尘效率。结论电极线的偏置可以提高除尘效率,当电极线置于电场宽度方向1/4处时,可以获得最佳除尘效果。     

高校思想政治教育创新发展对环境保护意识培养的促进作用研究

为提高全民综合素质,高校思想政治教育提出创新发展.与此同时,环境污染问题亟待解决,为从根本上改善和保护环境,对全民环境保护意识进行培养至关重要.首先分析高校思想政治教育创新发展历程,说明高校思想政治教育创新发展势在必行的原因,依据其发展准则,制定其创新内容.再对目前全民环保意识现状进行评估,差异性环境教育及较低的国民素质急需对全民环保意识进行培养.分析高校思想政治教育的环保价值,结合环境保护意识培养实现的效果,得出高校思想政治教育创新发展对环境保护意识培养有极大的促进作用.     

Correcting for non-response bias in contingent valuation surveys concerning environmental non-market goods: an empirical investigation using an online panel

Data collection for economic valuation by using Internet surveys and pre-recruited Internet panels can be associated with severe disadvantages. Problems concerning sample coverage and sample representativeness can be expected. Representation errors may occur since people can choose whether to be part of an Internet panel and subsequently whether they wish to participate in the survey, thereby introducing two elements of potential self-selection. These elements may be correlated with preferences, thus making the respondents a non-random and non-representative sample, ultimately biasing results. This paper analyses a sample used for an Internet contingent valuation method survey eliciting preferences for improvements in water quality of a river. We find that some variables that affect the survey participation decision also affect willingness-to-pay, consequently biasing our welfare estimates. We show how adjusting willingness-to-pay for this bias can be accomplished by using a grouped data model incorporating a correlation parameter to account for selection.     

Social media and mobility landscape: Uncovering spatial patterns of urban human mobility with multi source data

In this paper, we present a three-step methodological framework, including location identification, bias modification, and out-of-sample validation, so as to promote human mobility analysis with social media data. More specifically, we propose ways of identifying personal activity-specific places and commuting patterns in Beijing, China, based on Weibo (China’s Twitter) check-in records, as well as modifying sample bias of check-in data with population synthesis technique. An independent citywide travel logistic survey is used as the benchmark for validating the results. Obvious differences are discerned from Weibo users’ and survey respondents’ activity-mobility patterns, while there is a large variation of population representativeness between data from the two sources. After bias modification, the similarity coefficient between commuting distance distributions of Weibo data and survey observations increases substantially from 23% to 63%. Synthetic data proves to be a satisfactory cost-effective alternative source of mobility information. The proposed framework can inform many applications related to human mobility, ranging from transportation, through urban planning to transport emission modeling.

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