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Spatial Pattern of Long-term Residence in the Urban Floating Population of China and its Influencing Factors 被引量:6
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作者 CHEN Le XI Meijun +1 位作者 JIN Wanfu HU Ya 《Chinese Geographical Science》 SCIE CSCD 2021年第2期342-358,共17页
Exploring long-term residence among the urban floating population is crucial to understanding urban growth in China,particularly since the 2008 financial crisis.By using China Migrants Dynamic Survey data for 2012–20... Exploring long-term residence among the urban floating population is crucial to understanding urban growth in China,particularly since the 2008 financial crisis.By using China Migrants Dynamic Survey data for 2012–2014,China Labor-force Dynamics Survey data for 2014–2016,and macroscale urban matched data,we analyzed the spatial pattern of long-term residential behavior in China’s urban floating population in 2012–2016 and developed an urban spatial utility equilibrium model containing‘macro’urban factors and‘micro’individual and household factors to explain the pattern.The results first revealed that long-term residence is defined as≥6 yr for the urban floating population in China.Second,members of this population are more likely to be long-term residents of the megacities in the three urban agglomerations in eastern China as well as of small and medium-sized cities in western and northeastern China,whereas short-term residence is more likely in cities in central China and near the three urban agglomerations.Third,urban population density and housing prices,both have a significant U-shaped effect,are main factors affecting the spatial pattern of long-term residence. 展开更多
关键词 long-term residence urban floating population spatial pattern spatial utility equilibrium model China
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Multi-chip multi-phase DC−DC converters for AI power:a ring,a chain,or a net,independent or master-slave?
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作者 Yan Lu Zhiguo Tong +3 位作者 Jiacheng Yang Zhewen Yu Mo Huang Xiangyu Mao 《Journal of Semiconductors》 2025年第7期2-4,共3页
Motivation.As artificial intelligence(AI)workloads escalate exponentially,ultra-thin,high-efficiency voltage regulator modules(VRMs)with exceptional power density become essential for backside-mounted configurations[1... Motivation.As artificial intelligence(AI)workloads escalate exponentially,ultra-thin,high-efficiency voltage regulator modules(VRMs)with exceptional power density become essential for backside-mounted configurations[1].Thus,highdensity multiphase DC−DC converters are pivotal for implementing vertical power delivery(VPD)architectures in XPU platforms.Strategically positioning these converters beneath processors and maximizing spatial utilization enables core rail currents exceeding 2 kA while significantly reducing the power distribution network(PDN)losses compared to conventional solutions.The VPD configuration elevates system-level energy efficiency with>100 W power saving per processor,yielding megawatt-scale savings in a datacenter that uses~100000 processors.The synergy of 48 V power conversion architectures and advanced packaging techniques enables the industry’s commitment to balancing computational demands with CO_(2)emission reduction and environmental sustainability. 展开更多
关键词 maximizing spatial utilization vertical power delivery vpd architectures multi chip AI power ring topology xpu platformsstrategically multiphase dc dc converters core rail currents
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