一类考虑病毒发生变异的SIS疾病传播模型

为了研究变异行为对病毒传播的影响,提出了一个病毒发生变异的疾病传播模型,在模型中考虑了两种病毒相互转换的过程,计算机模拟结果表明,两种病毒的稳态感染比例与它们之间的相互转换概率γ1和γ2有关,当γ1＞0且γ2=0时,I1型感染者将消失,当γ1与γ2都大于0时,I1/I2与γ1/γ2成反比,且与α1/β1和α2/β2的取值无关.研究还发现病毒变异时由于缺乏对应的治疗药物和措施而出现一段真空期,这导致变异病毒的感染比例快速增加,但真空期的出现只能增加感染者的瞬时感染比例,而对稳态感染比例没有影响.该研究对人们深入理解病毒传播机理具有启发作用.     

一种基于点集拓扑分形变幻的云计算登录认证方法

考虑到云服务登录安全性及便捷性的需求,针对单点登录认证模式,提出云计算的统一登录认证方法,并采用点集拓扑分形变幻方法生成随机密钥,提高登录认证的安全等级。首先对云计算登录认证系统结构进行分析,然后以网络公共数据库中的指纹图像为例,进行分形变幻环运算,生成伪随机序列,再将这些序列加密并通过UDP发送给服务器端进行认证,最后进行实例仿真。     

中温相变蓄热材料研究进展

对中温相变蓄热材料(PCM)的定义范畴、应用领域、国内外发展现状进行了评述。中温PCM主要针对90~550℃的热动力环境,在太阳能热发电、有机朗肯循环、移动蓄热技术、分布式能源系统等方面有广阔的应用前景。指出进一步的研究方向是拓展中温PCM的应用场合,规范长期稳定性的表征与测试手段,重视与换热器开发以及应用领域的整合,并提出硝酸盐熔融盐混和物将是今后一段时期内中温PCM研发和培育的重点产品对象。     

自适应混合多目标分布估计进化算法

针对多目标分布估计算法全局收敛性较弱的缺陷,提出了一种自适应混合多目标分布估计进化算法。其基本思想是:在多目标分布估计算法中引入全局收敛性较强的差分进化算法,当函数变化率较大时,用分布估计算法产生新种群;当函数变化率较小即算法可能陷入局部收敛时,用差分进化算法产生新种群。理论分析和数值实验结果表明,这种混合算法不仅具有良好的全局收敛性,而且解的分布性和均匀性较没有考虑目标函数变化率的混合多目标分布估计算法也有了一定程度的提高。     

Impact of agriculture on soil consumption of atmospheric CH4 and a comparison of CH4 and N2O flux in subarctic, temperate and tropical grasslands

Increasing concentrations of methane (CH₄) in the atmosphere are projected to account for about 25% of the net radiative forcing. Biospheric emissions of CH₄ to the atmosphere total approximately 400 Tg C y^-1. An estimated 300 Tg of CH₄-C y^-1 is oxidized in the atmosphere by hydroxyl radicals while about 40 Tg y^-1 remains in the atmosphere. Approximately 40 Tg y^-1 of the atmospheric burden is oxidized in aerobic soils. Research efforts during the past several years have focused on quantifying CH₄ sources while relatively less effort has been directed toward quantifying and understanding the soil sink for atmospheric CH₄. Recent research has demonstrated that land use change, including agricultural use of native forest and grassland systems has decreased the soil sink for atmospheric methane. Some agricultural systems consume atmospheric CH₄ at rates less than 10% of those found in comparable undisturbed soils. While it has been necessary to change land use practices over the past centuries to meet the required production of food and fiber, we need to recognize and account for impacts of land use change on the biogeochemical nutrient cycles in the biosphere. Changes that have ensued in these cycles have and will impact the atmospheric concentrations of CH₄ and N₂O. Since CH₄ and N₂O production and consumption are accomplished by a variety of soil microorganisms, the influence of changing agricultural, forest, and, demographic patterns has been large. Existing management and technological practices may already exist to limit the effect of land use change and agriculture on trace gas fluxes. It is therefore important to understand how management and land use affect trace gas fluxes and to observe the effect of new technology on them. This paper describes the role of aerobic soils in the global CH₄ budget and the impact of agriculture on this soil CH₄ sink. Examples from field studies made across subarctic, temperate and tropical climate gradients in grasslands are used to demonstrate the influence of nutrient cycle perturbations on the soil consumption of atmospheric CH₄ and in increased N₂O emissions. This revised version was published online in August 2006 with corrections to the Cover Date.     

我国玻璃纤维复合材料新时期的特点与对策

本文综合论证了玻璃纤维及其主要用途的复合材料工业概况,指出我国玻璃纤维复合材料工业已经进入一个新的发展时期.过去是以发展速度为主要特征,现在则以产品应用、质量提高为重要标志.本文对新时期我国玻璃纤维复合材料的技术方向和行业管理提出建议.     

Field Validation of DNDC Model for Methane and Nitrous Oxide Emissions from Rice-based Production Systems of India

The DNDC (DeNitrification and DeComposition) model was tested against experimental data on CH₄ and N₂O emissions from rice fields at different geographical locations in India. There was a good agreement between the simulated and observed values of CH₄ and N₂O emissions. The difference between observed and simulated CH₄ emissions in all sites ranged from −11.6 to 62.5 kg C ha⁻¹ season⁻¹. Most discrepancies between simulated and observed seasonal fluxes were less than 20% of the field estimate of the seasonal flux. The relative deviation between observed and simulated cumulative N₂O emissions ranged from −237.8 to 28.6%. However, some discrepancies existed between observed and simulated seasonal patterns of CH₄ and N₂O emissions. The model simulated zero N₂O emissions from continuously flooded rice fields and poorly simulated CH₄ emissions from Allahabad site. For all other simulated cases, the model satisfactorily simulated the seasonal variations in greenhouse gas emission from paddy fields with different land management. The model also simulated the C and N balances in all the sites, including other gas fluxes, viz. CO₂, NO, NO₂, N₂ and NH₃ emissions. Sensitivity tests for CH₄ indicate that soil texture and pH significantly influenced the CH₄ emission. Changes in organic C content had a moderate influence on CH₄ emission on these sites. Introducing the mid-season drainage reduced CH₄ emissions significantly. Process-based biogeochemical modeling, as with DNDC, can help in identifying strategies for optimizing resource use, increasing productivity, closing yield gaps and reducing adverse environmental impacts.     

Building a research network to better understand climate governance in the Great Lakes

Climate-driven disturbances threaten the sustainability of coastal communities in the Great Lakes Basin. Because such disturbances are unpredictable, their magnitude, number and intensity are changing, and they occur at varying temporal and spatial scales. Consequently, communities struggle to respond in effective ways. The expected intensification of climate-driven disturbances will require that community capacity and governance structures match the spatial and temporal scales of these disturbances, as the most sustainable social and economic systems will be those that can respond at similar frequencies to key natural system drivers. The Climate Governance Variability in the Great Lakes Research Coordination Network (CGVG-RCN) was recently established to address questions about the relationship between climate-driven disturbances and community response. The objective of this short communication is to introduce the ideas behind the CGVG-RCN, outline its goals, and facilitate engagements and collaboration with social and natural scientists interested in social-ecological systems in the Great Lakes Basin.     

变化环境下“中华水塔”水资源及产流规律变化分析研究

受全球气候变暖的影响,“中华水塔”地区正面临着以“变暖变湿”为主的气候变化。受气候及下垫面条件的综合影响,区域水资源显著增加,各流域产流机理在空间上呈现出明显的地区差异特征。基于“中华水塔”区域1956—2020年水文气象资料,通过趋势、突变、距平等分析方法,分析其水文要素和产流规律的变化趋势、特征及相互之间影响关系。结果表明：近年来“中华水塔”区域气温显著升高,蒸发能力总体增强,区域进入丰水期,降水、径流显著增加,在同等降水径流尺度下,黄河源区产流能力有所降低,长江、澜沧江源区产流能力明显增强;气温升高、降水量持续偏丰以及流域前期影响雨量（蓄水量）增加、枯季径流比例提高、下垫面生态持水能力增强是引起区域产流规律变化、水资源量增加的主要原因。     

Climate change impact on water quality in the integrated Mahabad Dam watershed-reservoir system

Climate change, besides global warming, is expected to intensify the hydrological cycle, which can impact watershed nutrient yields and affect water quality in the receiving water bodies. The Mahabad Dam Reservoir in northwest Iran is a eutrophic reservoir due to excessive watershed nutrient input, which could be exacerbated due to climate change. In this regard, a holistic approach was employed by linking a climate model (CanESM2), watershed-scale model (SWAT), and reservoir water quality model (CE-QUAL-W2). The triple model investigates the cumulative climate change effects on hydrological parameters, watershed yields, and the reservoir’s water quality. The SDSM model downscaled the output of the climate model under moderate (RCP4.5) and extreme (RCP8.5) scenarios for the periods of 2021–2040 and 2041–2060. The impact of future climate conditions was investigated on the watershed runoff and total phosphorus (TP) load, and consequently, water quality status in the dam’s reservoir. The results of comparing future conditions (2021–2060) with observed present values under moderate to extreme climate scenarios showed a 4–7% temperature increase and a 6–11% precipitation decrease. Moreover, the SWAT model showed a 9–16% decline in streamflow and a 12–18% decline in the watershed TP load for the same comparative period. Finally, CE-QUAL-W2 model results showed a 3–8% increase in the reservoir water temperature and a 10–16% increase in TP concentration. It indicates that climate change would intensify the thermal stratification and eutrophication level in the reservoir, especially during the year’s warm months. This finding specifies an alarming condition that demands serious preventive and corrective measures.