Static modeling of dynamic recreation behavior: Implications for prediction and welfare estimation

This paper examines the consequences of using a static model of recreation trip-taking behavior when the underlying decision problem is dynamic. Specifically we examine the implications for trip forecasting and welfare estimation using a panel dataset of Lake Michigan salmon anglers for the 1996 and 1997 fishing seasons. We derive and estimate both a structural dynamic model using Bellman's equation, and a reduced-form static model with trip probability expressions mimicking those of the dynamic model. We illustrate an inherent identification problem in the reduced-form model that creates biased welfare estimates, and we discuss the general implications of this for the interpretation of preference parameters in static models. We then use both models to simulate trip taking behavior and show that although their in-sample trip forecasts are similar, their welfare estimates and out-of-sample forecasts are quite different.     

基于悬浮体系的大跨度铁路斜拉桥减震控制方案模拟分析

本文提出了基于悬浮体系的大跨度斜拉桥结构减震控制方案。用El Centro波模拟计算了采用非正常使用状态下,斜拉桥悬浮体系的空间动力反应,尤其是控制截面的内力反应,并与其它约束条件下的结构动力反应进行了对比,证实了采用悬浮体系,实现大跨铁路斜拉桥主动减震控制的可行性;进而利用联想记忆智能化混合结构控制算法,进一步优化结构控制效果,通过仿真计算说明了采用该控制算法实施控制的有效性;最后概略介绍了准备实施模拟试验的控制驱动装置方案,给出了本文的小结。     

基于24Model的不安全动作内在致因研究

为实现有效的不安全行为纠错,提升自我行为控制效果,基于24Model构建不安全动作的内在致因分析模型及分析程序,包含5项能力要素、15个维度因子和具有完整逻辑程序的4阶段步骤,并采用随机森林(RF)方法以煤矿安全专业人员为研究对象开展了不安全动作内在致因实证研究.结果 表明:对目标不安全动作影响最大的内在致因能力要素为...     

Modelling dispersal with diffusion and habitat selection: Analytical results for highly fragmented landscapes

Quantifying dispersal is crucial both for understanding ecological population dynamics, and for gaining insight into factors that affect the genetic structure of populations. The role of dispersal becomes pronounced in highly fragmented landscapes inhabited by spatially structured populations. We consider a landscape consisting of a set of habitat patches surrounded by unsuitable matrix, and model dispersal by assuming that the individuals follow a random walk with parameters that may be specific to the habitat type. We allow for spatial variation in patch quality, and account for edge-mediated behavior, the latter meaning that the individuals bias their movement towards the patches when close to an edge between a patch and the matrix. We employ a diffusion approximation of the random walk model to derive analytical expressions for various characteristics of the dispersal process. For example, we derive formulae for the time that an individual is expected to spend in its current patch i, and for the time that it will spend in the matrix, both conditional on the individual hitting next a given patch j before hitting any of the other patches or dying. The analytical formulae are based on the assumptions that the landscape is infinitely large, that the patches are circularly shaped, and that the patches are small compared to interpatch distances. We evaluate the effect of these assumptions by comparing the analytical results to numerical results in a real patch network that violates all of the three assumptions. We then consider a landscape that fulfills the assumptions, and show that in this case the analytical results are in a very good agreement with the numerical results. The results obtained here allow the construction of computationally efficient dispersal models that can be used as components of metapopulation models.     

Who should wear mask against airborne infections? Altering the contact network for controlling the spread of contagious diseases

There are several ways of controlling the propagation of a contagious disease. For instance, to reduce the spreading of an airborne infection, individuals can be encouraged to remain in their homes and/or to wear face masks outside their domiciles. However, when a limited amount of masks is available, who should use them: the susceptible subjects, the infective persons or both populations? Here we employ susceptible-infective-recovered (SIR) models described in terms of ordinary differential equations and probabilistic cellular automata in order to investigate how the deletion of links in the random complex network representing the social contacts among individuals affects the dynamics of a contagious disease. The inspiration for this study comes from recent discussions about the impact of measures usually recommended by health public organizations for preventing the propagation of the swine influenza A (H1N1) virus. Our answer to this question can be valid for other eco-epidemiological systems.     

Impacts of meteorology and precursor emission change on O3 variation in Tianjin, China from 2015 to 2021

Deterioration of surface ozone (O₃) pollution in Northern China over the past few years received much attention. For many cities, it is still under debate whether the trend of surface O₃ variation is driven by meteorology or the change in precursors emissions. In this work, a time series decomposition method (Seasonal-Trend decomposition procedure based on Loess (STL)) and random forest (RF) algorithm were utilized to quantify the meteorological impacts on the recorded O₃ trend and identify the key meteorological factors affecting O₃ pollution in Tianjin, the biggest coastal port city in Northern China. After “removing” the meteorological fluctuations from the observed O₃ time series, we found that variation of O₃ in Tianjin was largely driven by the changes in precursors emissions. The meteorology was unfavorable for O₃ pollution in period of 2015-2016, and turned out to be favorable during 2017-2021. Specifically, meteorology contributed 9.3 µg/m³ O₃ (13%) in 2019, together with the increase in precursors emissions, making 2019 to be the worst year of O₃ pollution since 2015. Since then, the favorable effects of meteorology on O₃ pollution tended to be weaker. Temperature was the most important factor affecting O₃ level, followed by air humidity in O₃ pollution season. In the midday of summer days, O₃ pollution frequently exceeded the standard level (>160 µg/m³) at a combined condition with relative humidity in 40%-50% and temperature > 31°C. Both the temperature and the dryness of the atmosphere need to be subtly considered for summer O₃ forecasting.     

基于RBI的苯乙烯/环氧丙烷装置压力管道在线检验研究

对苯乙烯／环氧丙烷装置进行腐蚀回路划分,并将腐蚀回路中的压力管道按照管径、材质及用途等因素划分为不同的组别后进行RBI分析。根据风险评估结果,结合压力管道的使用情况、失效机理及剩余使用寿命等确定下一个检验周期和检验策略。以腐蚀回路中的组别作为检验单元,根据其失效可能性及风险等级确定各检验单元的检验比例和检验方法进行在线检验。结果表明：基于RBI分析结果的压力管道在线抽检方法可以验证风险评估的结果,同时还可以满足使用单位对管道的风险控制要求。     

Does seeing it make a difference? The self-reported deterrent impact of random breath testing

Introduction: Random Breath Testing (RBT) remains a primary method to both deter and apprehend drink drivers, yet a large proportion of road fatalities continue to be caused by the offense. Outstanding questions remain regarding how much exposure to RBT operations is needed to influence deterrence-based perceptions and subsequent offending. Method: Given this, licensed motorists (N = 961) in Queensland were recruited to complete a questionnaire either in the community (N = 741) or on the side of the road after just being breath tested (N = 243). Survey items measured different types of exposure to RBT operations (e.g., “seen” vs. “being tested”) and subsequent perceptions of apprehension as well as self-reported drink driving behaviors. Results: The key findings that emerged were: motorists were regularly exposed to RBT operations (both viewing and being tested), such exposure was not significantly correlated with perceptions of apprehension certainty, and a sizable proportion reported engaging in drink driving behaviors (e.g., approx. 25%), although roadside participants naturally reported a lower percentage of offending behaviors. Importantly, it was revealed that current “observations” of RBT was sufficient, but not actual levels of active testing (which needed to be doubled). Nevertheless, higher levels of exposure to RBT operations was found to be predictive of a lack of intention to drink and drive again in the future. Conclusions: This paper suggests that mere exposure to enforcement may not create the intended rule compliance, and that the frequency of exposure is also essential for the roadside.     

Diversity and community structure of culturable arsenic-resistant bacteria across a soil arsenic gradient at an abandoned tungsten-tin mining area

We studied the bacterial diversity at a single location (the Terrubias mine; Salamanca province, Spain) with a gradient of soil As contamination to test if increasing levels of As would (1) change the preponderant groups of arsenic-resistant bacteria and (2) increase the tolerance thresholds to arsenite [As(III)] and arsenate [As(V)] of such bacteria. We studied the genetic and taxonomic diversity of culturable arsenic-resistant bacteria by PCR fingerprinting techniques and 16S rRNA gene sequencing. Then, the tolerance thresholds to As(III) and As(V) were determined for representative strains and mathematically analyzed to determine relationships between tolerances to As(III) and As(V), as well as these tolerances with the soil contamination level. The diversity of the bacterial community was, as expected, inversely related to the soil As content. The overall preponderant arsenic-resistant bacteria were Firmicutes (mainly Bacillus spp.) followed by γ-Proteobacteria (mainly Pseudomonas spp.), with increasing relative frequencies of the former as the soil arsenic concentration increased. Moreover, a strain of the species Rahnella aquatilis (γ-Proteobacteria class) exhibited strong endurance to arsenic, being described for the first time in literature such a phenotype within this bacterial species. Tolerances of the isolates to As(III) and As(V) were correlated but not with their origin (soil contamination level). Most of the strains (64%) showed relatively low tolerances to As(III) and As(V), but the second most numerous group of isolates (19%) showed increased tolerance to As(III) rather than to As(V), even though the As(V) anion is the prevalent arsenic species in soil solution at this location. To our knowledge, this is the first study to report a shift towards preponderance of Gram-positive bacteria (Firmicutes) related to high concentrations of soil arsenic. It was also shown that, under aerobic conditions, strains with relatively enhanced tolerance to As(III) predominated over the most As(V)-tolerant ones.     

灰色预测法在设备状态趋势预报中的应用

分析了设备运行状态的特征 ,运用灰色系统理论对设备状态特征量——振动烈度 ,建立了灰色预测模型。计算结果表明 ,预测模型的计算值与实际测定值非常接近 ,而且可进一步预报设备运行状态趋势。灰色预测法的引进 ,丰富了设备状态监测与故障诊断技术学科的基础理论 ,推动了该学科向更高水平发展 ,预示了该学具有更广阔的应用前景。