基于可接受安全间距的单车道交通流模拟模型

交通流微观模拟是采用计算机对交通流进行描述及分析的方法。尤其对于复杂的交通流而言,微观模拟具有明显的优势,然而模拟的准确与否,关键在于模型的建立。笔者即是在研究我国单车道交通流特点的基础上,借鉴车道变换理论,基于驾驶员可接受的交通安全间距,分析安全变换车道的各间距之间的关系,阐述了有超车的单车道交通流模拟模型的建立方法     

能源安全工程研究体系探讨

随着矿物能源开采消耗量的急剧增加,煤炭开采安全、能源开采和消耗引起的生态环境改变及破坏、世界石油市场油价波动对经济增长的不利影响、水电等可再生能源所占比重较低等,构成了制约可持续发展的能源安全问题。能源安全工程研究体系由区域能源开发消费安全、合理能源结构和消费布局、能源安全战略及相关法律法规等研究内容组成。通过分层次研究和循环促进,开展能源安全战略、能源安全技术、能源生态关系、能源安全经济的系统研究,为科学解决能源安全问题、实现国家或区域社会经济的可持续发展,提供了理论支持和科技保障。     

桂林市极端天气气候事件分析

桂林是以"甲天下"的山水美景而闻名的国际旅游城市,极端天气气候事件造成的灾害将给其社会经济的发展带来负面影响.本文采用桂林1951～2004年的资料,统计干旱、暴雨、高温和强对流天气等极端天气气候事件的出现频率、强度并分析其演变趋势.结果显示,近50年来,桂林市极端天气气候事件除暴雨、干旱强度增大外,频率变化呈平稳或减小趋势.     

Effect of 450 MHz Microwave Modulated with 217 Hz on Human EEG in Rest

Summary This study focuses on discrimination of changes, produced by low-level microwave exposure in intensity and time variability of the human EEG at rest. The power spectral density (PSD) method and nonlinear scaling analysis of the length distribution of low variability periods (LDLVP) were selected for analysis of the EEG signal. During the study, 19 healthy volunteers were exposed to a microwave (450 MHz) of 217 Hz frequency on-off modulation. The field power density at the scalp was 0.16 mW/cm². The experimental protocol consisted of ten cycles of repetitive microwave exposure. Signals from frontal, temporal, parietal and occipital EEG channels on EEG theta, alpha and beta rhythms were analysed. Exposure to microwave causes average increase of EEG activity. LDLVP analysis discriminated significant effect in time variability for 2 subjects (11%). PSD method detected significant changes in intensity for 4 subjects (21%). The effect of low-level microwave exposure is stronger on EEG beta rhythm in temporal and parietal regions of the human brain.     

The Water Fluxes of the Yellow River to the Sea in the Past 50 Years, in Response to Climate Change and Human Activities

Since the 1970s, the water fluxes to the sea of the Yellow River have declined significantly. Based on data of precipitation, air temperature, the measured and “natural” river flow, the water diversion and consumption, and the areas of erosion and sediment control measures over the drainage basin, water fluxes to the sea of the Yellow River are studied in relation with the influences of changing climate and human activities. The Yellow River basin can be divided into different water source areas; multiple regression indicates that the variation in precipitation over different water source areas has different effect on water fluxes to the sea. In the period between 1970 and 1997, averaged air temperature over the whole Yellow River increased by about 1.0°C, from 16.5°C to 17.5°C, a factor that is negatively correlated with the water yield of the Yellow River. Water diversion and consumption has sharply increased and resulted in a significant decline in the water fluxes to the sea. Since the 1960s, erosion and sediment control measures have been practiced over the drainage basin. This factor, to a lesser degree, is also responsible for the decrease in water fluxes to the sea. A multiple regression equation has been established to estimate the change in water fluxes to the sea caused by the changes in precipitation, air temperature, water diversion and consumption, erosion, and sediment control measures, indicating that the contribution of water diversion and consumption to the variation in annual water flux to the sea is 41.3%, that of precipitation is 40.8%, that of temperature is 11.4%, and that of erosion and sediment control measures is 6.5%.     

Impact of Human Activities on Carbon Dioxide (CO<Subscript>2</Subscript>) Emissions: A Statistical Analysis

Summary The balance of evidence suggests a perceptible human influence on global ecosystems. Human activities are affecting the global ecosystem, some directly and some indirectly. If researchers could clarify the extent to which specific human activities affect global ecosystems, they would be in a much better position to suggest strategies for mitigating against the worst disturbances. Sophisticated statistical analysis can help in interpreting the influence of specific human activities on global ecosystems more carefully. This study aims at identifying significant or influential human activities (i.e. factors) on CO₂ emissions using statistical analyses. The study was conducted for two cases: (i) developed countries and (ii) developing countries. In developed countries, this study identified three influential human activities for CO₂ emissions: (i) combustion of fossil fuels, (ii) population pressure on natural and terrestrial ecosystems, and (iii) land use change. In developing countries, the significant human activities causing an upsurge of CO₂ emissions are: (i) combustion of fossil fuels, (ii) terrestrial ecosystem strength and (iii) land use change. Among these factors, combustion of fossil fuels is the most influential human activity for CO₂ emissions both in developed and developing countries. Regression analysis based on the factor scores indicated that combustion of fossil fuels has significant positive influence on CO₂ emissions in both developed and developing countries. Terrestrial ecosystem strength has a significant negative influence on CO₂ emissions. Land use change and CO₂ emissions are positively related, although regression analysis showed that the influence of land use change on CO₂ emissions was still insignificant. It is anticipated, from the findings of this study, that CO₂ emissions can be reduced by reducing fossil-fuel consumption and switching to alternative energy sources, preserving exiting forests, planting trees on abandoned and degraded forest lands, or by planting trees by social/agroforestry on agricultural lands.     

Resource Use Dynamics and Land-Cover Change in Ang Nhai Village and Phou Phanang National Reserve Forest, Lao PDR

This study integrated aerial photographs from 1952, 1981, and 1998, and a satellite image from 2000 with oral histories and socioeconomic surveys to assess changes in forest and land cover in Ang Nhai village, Laos. The study documents the history of resource use and changes in household access to resources in the village. Three distinctive trends were observed in terms of forest and land cover—forest degradation, deforestation, and regeneration. Project results suggest that land and forest cover change dynamically under different circumstances. The case study also points out that integration into the market economy can induce intensification of unused lowland areas, while removing pressures from upland areas previously used for supplementing agricultural production. In addition, the creation of a national reserve forest to restrict local access and forest use was an ineffective tool for regulating encroachment and logging activities.     

BASIN SCALE WATER MANAGEMENT AND FORECASTING USING ARTIFICIAL NEURAL NETWORKS1

ABSTRACT: Water scarcity in the Sevier River Basin in south‐central Utah has led water managers to seek advanced techniques for identifying optimal forecasting and management measures. To more efficiently use the limited quantity of water in the basin, better methods for control and forecasting are imperative. Basin scale management requires advanced forecasts of the availability of water. Information about long term water availability is important for decision making in terms of how much land to plant and what crops to grow; advanced daily predictions of streamflows and hydraulic characteristics of irrigation canals are of importance for managing water delivery and reservoir releases; and hourly forecasts of flows in tributary streams to account for diurnal fluctuations are vital to more precisely meet the day‐to‐day expectations of downstream farmers. A priori streamflow information and exogenous climate data have been used to predict future streamflows and required reservoir releases at different timescales. Data on snow water equivalent, sea surface temperatures, temperature, total solar radiation, and precipitation are fused by applying artificial neural networks to enhance long term and real time basin scale water management information. This approach has not previously been used in water resources management at the basin‐scale and could be valuable to water users in semi‐arid areas to more efficiently utilize and manage scarce water resources.     

SUMMER LOW FLOWS IN NEW ENGLAND DURING THE 20TH CENTURY1

ABSTRACT: High springtime river flows came earlier by one to two weeks in large parts of northern New England during the 20th Century. In this study it was hypothesized that late spring/early summer recessional flows and late summer/early fall low flows could also be occurring earlier. This could result in a longer period of low flow recession and a decrease in the magnitude of low flows. To test this hypothesis, variations over time in the magnitude and timing of low flows were analyzed. To help understand the relation between low flows and climatic variables in New England, low flows were correlated with air temperatures and precipitation. Analysis of data from 23 rural, unregulated rivers across New England indicated little evidence of consistent changes in the timing or magnitude of late summer/early fall low flows during the 20th Century. The interannual variability in the timing and magnitude of the low flows in northern New England was explained much more by the interannual variability in precipitation than by the interannual variability of air temperatures. The highest correlation between the magnitude of the low flows and air temperatures was with May through November temperatures (r =?0.37, p= 0.0017), while the highest correlation with precipitation was with July through August precipitation (r = 0.67, p > 0.0001).     

安全降变原理及C-S-R事故致因新模型

为发展安全科学原理和给事故防控与调查提供新的方法,根据变化对系统安全的影响机制,开展安全降变原理及事故致因新模型研究。首先,提出安全降变原理并解析其内涵及研究意义。其次,基于安全降变原理,给出不同层级安全系统变化的分类实例,并对作业场所事故及其致因重新定义和分类。再次,构建基于安全降变原理的C-S-R事故致因新模型。最后,基于事故案例分析,验证所提出的C-S-R事故致因新模型与安全降变原理的有效性。结果表明,各级安全系统中自发或是受联动的变化超出系统的变化承受水平时,将导致事故的发生。经事故案例分析验证可知,安全降变原理及C-S-R事故致因新模型具有充分的实用性。