跨行政区游憩空间柔性一体化研究 ——以高莱茵河沿岸地区为例

随着城市化与区域一体化的迅速发展,不同行政区之间的联动关系越来越紧密,这种联动关系在城市各功能空间的设计上有所体现,更渗透到了与市民息息相关的游憩空间建构之中。受制于行政管理等方面的原因,在跨行政区的游憩空间一体化实施过程中,往往会采取一系列柔性措施。以欧洲高莱茵河沿岸地区为研究对象,分析高莱茵河沿岸地区游憩空间的发展与现状,总结其游憩空间体系的构建特点,为中国跨城市河流沿岸的游憩空间柔性一体化建构提供策略与建议。     

关于COVID-19、膜脂质与公众健康（网络首发、推荐阅读）

冠状病毒具有一层脂质膜。虽然复制需要劫持宿主的RNA工具来合成病毒体蛋白，但必须将其包裹在脂质膜中，促其萌生以扩展感染。最近研究表明，某些必需脂肪酸可以抑制其复制活性。脂质膜通常被认为是水溶物的脂肪屏障，但它对细胞和亚细胞的功能是高度有序和组分特异性的，其对病毒外壳可能也有最佳的特异性。虽然复制中DNA、RNA和蛋白质组成不受饮食影响，但脂质膜受其影响。此外，自1960年代以来，人们就知道男性对这些必需脂肪酸和膜完整性不足的敏感性高于女性。有证据表明，花生四烯酸和二十二碳六烯酸具有抗病毒、免疫、抗炎、控制血压和消退素活性，因此，迫切需要考察它们在Covid-19预防和治疗中的地位，也需重新评估现行的膳食指导。当前，有关脑、神经、血管和免疫系统等富含膜系统对脂质需求还尚未被详细认识。毫无疑问，这些脂质在几百万年来塑造人类基因组方面具有重要意义，因此，如果这些膜脂质失衡将会使人类面临机体紊乱和感染风险，且男性比女性风险更大。     

基于VMD和BSA-KELM的高陡边坡位移预测模型研究

边坡位移的时间序列曲线存在复杂的非线性特性,传统的预测模型精度不足以满足预测要求。为此提出了基于变分模态分解的鸟群优化-核极限学习机的预测模型,并用于河北省某水泥厂的边坡位移预测。该方法首先采用VMD把边坡位移序列分解为一系列的有限带宽的子序列,再对各子序列分别采用相空间重构并用核极限学习机预测,采用鸟群算法优化相空间重构的嵌入维度和KELM中惩罚系数和核参数三个数值,以取得最优预测模型。最后将各个子序列预测值叠加,得到边坡位移的最终预测值。结果表明：和KELM、BSA-KELM、EEMD-BSA-KELM模型相比,基于VMD的BSA-KELM预测精度更高,为边坡位移的预测提供一种有效的方法。     

基于公众心理健康视角的绿色空间研究与展望

增进公众心理健康与福祉是人类面临的重要公共卫生课题,以促进心理健康为目标的绿色空间规划设计是健康城市建设的关键。基于Web of Science(WoS)数据库核心合集的英文文献,从绿色空间对心理健康的影响因素、影响机制与测度方法3个方面,梳理绿色空间与公众心理健康关联性研究的进展。既有研究表明:绿色空间与心理健康之间存在多因素混合、多机制协同作用;绿地自身特征与暴露特征主要通过3种间接途径产生心理健康效益,并受到个人与社会因素的调节。考虑既有研究在指标阈值与因果权重中的争议,以及在学科融合、指标选取及数据获取与分析方面的局限,建议未来研究在加强跨领域学科融合、细化绿地属性特征、关注个体属性与行为、进行纵向与实验研究、引入智能新技术等方面予以完善。     

基于光谱尺度空间与管道滤波的红外目标检测

为了准确地从复杂干扰背景下检测出真实弱小目标，本文引入视觉显著性，设计了基于快速光谱尺度空间与动态管道滤波的红外目标检测算法。基于真实目标与背景内容之间的整体差异，引入快速光谱尺度空间与阈值分割技术，设计视觉显著性机制，对红外图像完成处理，输出全局显著性映射，以高效过滤干扰背景内容。考虑目标与背景的局部特征差异，构建自适应局部对比度增强机制，对粗检测结果实施处理，获取对应的局部显著性映射，改善视觉显著性区域内目标的对比度。引入高斯差分理论，通过估算每一帧红外图像中的目标像素直径，形成动态管道滤波，充分消除虚警，准确识别出弱小目标。多组实验数据显示：较已有的红外目标检测技术而言，在各种不同的复杂背景干扰下，所提算法呈现出更好的检测能力，拥有更理想的接收机工作特性ROC曲线。     

温州某公轨共建高架车站结构设计

为了解决城市廊道资源的紧张和公共交通发展需求的矛盾,出现了轨道交通和快速路的共建型式,即公轨共建的复合型交通模式,以温州市域铁路S2线一期工程的人民路站为例,研究公轨共建高架车站的结构设计要点。首先,为降低浅层气体对桩基的承载力及沉降影响,对遇到局部浅层气体发育的基础设计提供了合理的解决方案。然后针对公轨共建一体化车站分别进行了多遇和罕遇地震作用分析,研究表明构件及整体指标满足规范要求。最后针对工程的一些关键技术,如快速路桥面体系的选型、超长结构温度应力的控制措施、轨道梁挠度及应力的控制、快速路桥面振动对车站的影响等进行了分析,并给出了具体的解决方案和指导意见。     

Efficient Flexible M-Tree Bulk Loading Using FastMap and Space-Filling Curves

Many database applications currently deal with objects in a metric space. Examples of such objects include unstructured multimedia objects and points of interest (POIs) in a road network. The M-tree is a dynamic index structure that facilitates an efficient search for objects in a metric space. Studies have been conducted on the bulk loading of large datasets in an M-tree. However, because previous algorithms involve excessive distance computations and disk accesses, they perform poorly in terms of their index construction and search capability. This study proposes two efficient M-tree bulk loading algorithms. Our algorithms minimize the number of distance computations and disk accesses using FastMap and a space-filling curve, thereby significantly improving the index construction and search performance. Our second algorithm is an extension of the first, and it incorporates a partitioning clustering technique and flexible node architecture to further improve the search performance. Through the use of various synthetic and real-world datasets, the experimental results demonstrated that our algorithms improved the index construction performance by up to three orders of magnitude and the search performance by up to 20.3 times over the previous algorithm.     

Reduced‐order method for mathematical modeling of multiphase dc‐dc converter

A multiphase dc‐dc converter is effective for miniaturization and achieving high‐power density in a switching power supply. However, its mathematical modeling becomes complex as the phase number of the circuit increases. This study proposes a new modeling method to derive a reduced‐order method in a simple manner. The frequency characteristics of the reduced‐order model are fit to those of the original mathematical model of the multiphase dc‐dc converter. Therefore, the efficacy of the proposed method is validated.     

Human responses to high levels of carbon dioxide and air temperature

In this study, 30 subjects were exposed to different combinations of air temperature (T_a: 24, 27, and 30°C) and CO₂ level (8000, 10 000, and 12 000 ppm) in a high-humidity (RH: 85%) underground climate chamber. Subjective assessments, physiological responses, and cognitive performance were investigated. The results showed that as compared with exposure to T_a = 24°C, exposure to 30°C at all CO₂ levels caused subjects to feel uncomfortably warm and experience stronger odor intensity, while increased mental effort and greater intensity of acute health symptoms were reported. However, no significant effects of T_a on task performance or physiological responses were found. This indicated that subjects had to exert more effort to maintain their performance in an uncomfortably warm environment. Increasing CO₂ from 8000 to 12 000 ppm at all T_a caused subjects to report higher rates of headache, fatigue, agitation, and feeling depressed, although the results were statistically significant only at 24 and 27°C. The text typing performance and systolic blood pressure (SBP) decreased significantly at this exposure, whereas diastolic blood pressure (DBP) and thermal discomfort increased significantly. These effects suggest higher arousal/stress. No significant interaction effect of T_a and CO₂ concentration on human responses was identified.     

Chemical Bonding by the Chemical Orthogonal Space of Reactivity

The fashionable Parr–Pearson (PP) atoms-in-molecule/bonding (AIM/AIB) approach for determining the exchanged charge necessary for acquiring an equalized electronegativity within a chemical bond is refined and generalized here by introducing the concepts of chemical power within the chemical orthogonal space (COS) in terms of electronegativity and chemical hardness. Electronegativity and chemical hardness are conceptually orthogonal, since there are opposite tendencies in bonding, i.e., reactivity vs. stability or the HOMO-LUMO middy level vs. the HOMO-LUMO interval (gap). Thus, atoms-in-molecule/bond electronegativity and chemical hardness are provided for in orthogonal space (COS), along with a generalized analytical expression of the exchanged electrons in bonding. Moreover, the present formalism surpasses the earlier Parr–Pearson limitation to the context of hetero-bonding molecules so as to also include the important case of covalent homo-bonding. The connections of the present COS analysis with PP formalism is analytically revealed, while a numerical illustration regarding the patterning and fragmentation of chemical benchmarking bondings is also presented and fundamental open questions are critically discussed.