检索结果-南通市图书馆

Effects of land use change and water reuse options on urban water cycle

Journal of Environmental Sciences 2010年第6期22卷 923-928页

作者： jiho Lee Gijung Pak Chulsang yoo Sangdan Kim Jaeyoung yoon School of Civil Environmentaland Architectural EngineeringKorea University Department of Environmental Engineering Korea University Department of Environmental System Engineering Pukyong National University

The aim of this article was to study the effects of land use change and water reuse options on an urban water cycle. A water cycle analysis was performed on the Goonja drainage basin, located in metropolitan Seoul, using the Aquacycle model. The chronological effects of urbanization were first assessed for the land uses of the Goonja drainage basin from 1975 to 2005, where the ratio of impervious areas ranged from 43% to 84%. Progressive urbanization was identified as leading to a decrease in evapotranspiration （29%）, an increase in surface runoff （41%） and a decrease in groundwater recharge （74%）, indicating a serious distortion of the water cycle. From a subsequent analysis of the water reuse options, such as rainwater use and wastewater reuse, it is concluded that wastewater reuse seemed to have an advantage over rainwater use for providing a consistent water supply throughout the year for a country like Korea. where the rainy season is concentrated during the summer monsoon.

关键词： Aquacycle model land use change water reuse

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Differential Inhibition of Nav1.7 and Neuropathic Pain by Hybridoma-Produced and Recombinant Monoclonal Antibodies that Target Nav1.7

引用

Neuroscience Bulletin 2018年第1期34卷 22-41页

作者： Sangsu Bang Jiho Yoo Xingrui Gong Di Liu Qingjian Han Xin Luo Wonseok Chang Gang Chen Sang-Taek Im Yong Ho Kim Judith A.Strong Ma-Zhong Zhang Jun-Ming Zhang Seok-Yong Lee Ru-Rong Ji Department of Anesthesiology Duke University Medical Center Department of Biochemistry Duke University Medical Center Pain Research Center Department of AnesthesiologyUniversity of Cincinnati Department of Anesthesiology Shanghai Children's Medical Center Department of Physiology and Biophysics College of Medicine Eulji University Department of Physiology College of Medicine Gachon University

Abstract The voltage-gated Na＋ channel subtype Nav1.7 is important for pain and itch in rodents and humans. We previously showed that a Nav1.7-targeting monoclonal antibody （SVmab） reduces Na＋ currents and pain and itch responses in mice. Here, we investigated whether recom- binant SVmab （rSVmab） binds to and blocks Nav1.7 similar to SVmab. ELISA tests revealed that SVmab was capable of binding to Nav1.7-expressing HEK293 cells, mouse DRG neurons, human nerve tissue, and the voltagesensor domain II of Nav1.7. In contrast, rSVmab showed no or weak binding to Nav1.7 in these tests. Patch-clamp recordings showed that SVmab, but not rSVmab, markedly inhibited Na＋ currents in Nav1.7-expressing HEK293 cells. Notably, electrical field stimulation increased the blocking activity of SVmab and rSVmab in Nav1.7- expressing HEK293 cells. SVmab was more effective than rSVmab in inhibiting paclitaxel-induced mechanical allodynia. SVmab also bound to human DRG neurons and inhibited their Na＋ currents. Finally, potential reasons for the differential efficacy of SVmab and rSVmab and future directions are discussed.

关键词： Primary afferent neuron Patch clamping （electrophysiology） Sodium channels Animal models

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Ash-free coal as fuel for direct carbon fuel cell

引用

Science China Chemistry 2014年第7期57卷 1010-1018页

作者： LEE Injae JIN Sunmi CHUN Donghyuk CHOI Hokyung LEE Sihyun LEE Kibong yoo jiho Clean Fuel Laboratory Korea Institute of Energy Research 152 Gajeong-roYuseong-gu Daejeon 305-343 Korea Department of Chemical & Biological Engineering Korea University Anam-dongSeongbuk-gu Seoul 136-713 Korea

This work describes the performance of the direct carbon fuel cell(DCFC)fuelled by ash-free coal.Employing coal in the DCFC might be problematic,mainly because of the ash deposition after the cell reactions.In the study,the carbonaceous ash-free component of coal is obtained,which is then evaluated as the DCFC fuel and compared with raw coal,active carbon,carbon black,and graphite.The electrolyte-supported SOFC structure is adapted to build the DCFC.The DCFC based on the ash-free coal fuel exhibits good performance with regard to the maximum power density,day-by-day measurements,and durability at continuous run.When the carbon fuels are internally gasified to H2 and CO,the power density is generally much improved,compared to N2 pyrolysis environment.The power generation is most likely related to the concentration of pyrolyzed gases as well as the electrochemical reactivity of the solid carbon.

关键词：燃料电池用煤含碳功率密度热解气体电化学反应灰分沉积电池反应

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Deep-learning-based inverse design model for intelligent discovery of organic molecules

引用

npj Computational Materials 2018年第1期4卷 103-109页

作者： Kyungdoc Kim Seokho Kang Jiho Yoo Youngchun Kwon Youngmin Nam Dongseon Lee Inkoo Kim Youn-Suk Choi Yongsik Jung Sangmo Kim Won-Joon Son Jhunmo Son Hyo Sug Lee Sunghan Kim Jaikwang Shin Sungwoo Hwang Samsung Advanced Institute of Technology Samsung Electronics Co.Ltd.130 Samsung-roYeongtong-guSuwon-siGyeonggi-do 16678Republic of Korea Department of Systems Management Engineering Sungkyunkwan University2066 Seobu-roJangan-guSuwon-siGyeonggi-do 16419Republic of Korea

The discovery of high-performance functional materials is crucial for overcoming technical issues in modern industries.Extensive efforts have been devoted toward accelerating and facilitating this process,not only experimentally but also from the viewpoint of materials design.Recently,machine learning has attracted considerable attention,as it can provide rational guidelines for efficient material exploration without time-consuming iterations or prior human knowledge.In this regard,here we develop an inverse design model based on a deep encoder-decoder architecture for targeted molecular design.Inspired by neural machine language translation,the deep neural network encoder extracts hidden features between molecular structures and their material properties,while the recurrent neural network decoder reconstructs the extracted features into new molecular structures having the target properties.In material design tasks,the proposed fully data-driven methodology successfully learned design rules from the given databases and generated promising light-absorbing molecules and host materials for a phosphorescent organic light-emitting diode by creating new ligands and combinatorial rules.

关键词： inverse learning devoted

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：