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The glass-forming ability (GFA) of Mg-Cu-Ni-Gd alloy system was evaluated using copper mold casting. A three-dimensional composition map of Mg-Cu-Ni-Gd system with GFA over 6 mm was revealed, confirming that the Ni addition decreased the GFA of Mg-Cu-Gd system. The maximum Ni tolerance was about 6 at.% for the Mg-Cu-Ni-Gd BMGs with GFA over 6 mm. The compressive tests displayed that the Ni addition as small as 3.45 at.% could result in higher strength for the Mg-Cu-Gd BMGs. The Mg-Cu-Ni-Gd system with small Ni content can be balanced candidates for the Mg-based BMGs with both acceptable GFA and high strength. [ABSTRACT FROM AUTHOR]

This article provides a novel and practical approach for investigating the characteristics of intercity telecommunication network whose overall and complete information is unavailable. Using a mobile phone call data set covering 4.39 million subscribers registered in a particular region, we construct two intercity mobile communication subnets and infer characteristics of the whole intercity mobile communication network of China. Results confirm that intercity communication intensity is characterized by the gravity model. The communication intensity based on mobile call number decreases along the distance with a scaling exponent 0.5, whereas the scaling exponent for the communication intensity based on mobile call duration is 0.4. Moreover, we uncover the rank-size distribution of tie strength (mobile call number and duration) between a city and its neighbours. The rank-size law of tie strengths between cities is mainly determined by the rank-size distribution of cities. The distance between cities plays a less decisive role than the size distribution in the network, but significantly impacts mobile communication patterns. The call duration of individual intercity mobile communication is generally positively correlated to the communication distance, explaining why the distance decay of communication intensity based on call durations is slower than that based on call numbers. The contribution of this research is twofold. First, we identify the distance decay effect in intercity mobile communications of China and uncover the dominant impact of the rank-size distribution of cities. Second, a method for estimating the properties of the whole network according to the observed interactions of its subnets is developed. [ABSTRACT FROM PUBLISHER]

Today, large-volume mobile phone call datasets are widely applied to investigate the spatio-temporal characteristics of human urban activity. This paper discusses several fundamental issues in estimating population distributions based on mobile call data. By adopting an individual-based call activity dataset that consists of nearly two million mobile subscribers who made over one hundred million communications over seven consecutive days, we explore the relationships among the Erlang values, the number of calls, and the number of active mobile subscribers. Then, the LandScan population density dataset is introduced to evaluate the process of estimating the population. The empirical findings indicate that: (1) Temporal variation exists in the relation between the Erlang values and the number of calls; (2) The number of calls is linearly proportional to the number of active mobile subscribers; (3) The proportion between the mobile subscribers and the actual total population varies in different areas, thus failing to represent the underlying population. Hence, the call activity reflects “activity intensity” rather than population distribution. The Erlang is a defective indicator of population distribution, whereas the number of calls serves as a better measure. This research provides an explicit clarification with respect to using call activity data for estimating population distribution. [ABSTRACT FROM AUTHOR]

Abnormal events in earth science have great influence on both the natural environment and the human society. Finding association patterns among these events has great significance. Because data in earth science has characteristics of mass, high dimension, spatial autocorrelation and time delay, existing mining technologies cannot be directly used on it. We propose a RSNN (range-based searching nearest neighbors) spatial clustering algorithm to reduce the data size and auto-correlation. Based on the clustered data, we propose a GEAM (geographic episode association pattern mining) algorithm which can deal with events time lags and find interesting patterns with specific constraints, to mine the association patterns. We carried out experiments on global climate datasets and found many interesting association patterns. Some of the patterns are coincident with known knowledge in climate science, which indicates the correctness and feasibilities of our methods, and the others are unknown to us before, which will give new information to this research field. [ABSTRACT FROM AUTHOR]