With the global population on the rise, our cities have been expanding to
accommodate the growing number of people. The expansion of cities generally
leads to the engulfment of peripheral areas. However, such expansion of urban
areas is likely to cause increment in areas with increased land surface
temperature (LST). By considering each summer as a data point, we form LST
multi-year time-series and cluster it to obtain spatio-temporal pattern. We
observe several interesting phenomena from these patterns, e.g., some clusters
show reasonable similarity to the built-up area, whereas the locations with
high temporal variation are seen more in the peripheral areas. Furthermore, the
LST center of mass shifts over the years for cities with development activities
tilted towards a direction. We conduct the above-mentioned studies for three
different cities in three different continents.

城市扩张导致了周边地区的淹没，而这种城市区域的扩张很可能导致土地表面温度增加。通过考虑每年夏季作为一个数据点，我们形成土地表面温度多年时间序列并进行聚类以获取时空模式。从这些模式中，我们观察到一些有趣的现象，如一些聚类与建筑区域具有合理的相似性，而具有高时空变化的位置更多地出现在周边地区。此外，城市发展活动倾向于某个方向，而土地表面温度的质心随着时间的推移也会发生变化。我们对三个不同大洲的三个城市进行了上述研究。

城市地区的演变与地表温度

Evolution of urban areas and land surface temperature

The internet activity records (IARs) of a mobile cellular network posses
significant information which can be exploited to identify the network's
efficacy and the mobile users' behavior. In this work, we extract useful
information from the IAR data and identify a healthy predictability of
spatio-temporal pattern within the network traffic. The information extracted
is helpful for network operators to plan effective network configuration and
perform management and optimization of network's resources. We report
experimentation on spatiotemporal analysis of IAR data of the Telecom Italia.
Based on this, we present mobile traffic partitioning scheme. Experimental
results of the proposed model is helpful in modelling and partitioning of
network traffic patterns.

本文从移动蜂窝网络的互联网活动记录（IAR）数据中提取了有用信息，并识别出网络流量中的健康可预测性的时空模式。这些提取出的信息有助于网络运营商规划有效的网络配置和执行网络资源的管理和优化。我们在 Telecom Italia 的 IAR 数据上进行了实验。基于此，我们提出了移动流量分区方案。所提出的模型的实验结果有助于建模和分割网络流量模式。

利用网络活动记录数据来理解和划分移动流量 -- 一种时空方法

Understanding and Partitioning Mobile Traffic using Internet Activity  Records Data -- A Spatiotemporal Approach

A chimera state is a spatio-temporal pattern in a network of identical
coupled oscillators in which synchronous and asynchronous oscillation coexist.
This state of broken symmetry, which usually coexists with a stable spatially
symmetric state, has intrigued the nonlinear dynamics community since its
discovery in the early 2000s. Recent experiments have led to increasing
interest in the origin and dynamics of these states. Here we review the history
of research on chimera states and highlight major advances in understanding
their behaviour.

该文综述分析了有关混合状态的研究历史和理解其行为的主要进展，其中混合状态是一种具有时空模式的网络，其中同步和异步振荡共存，通常与稳定的空间对称状态共存。