Temporal rainfall trend analysis in different agro-ecological regions of southern Africa

Rainfall is a major driver of food production in rainfed smallholder farming systems. This study was conducted to assess linear trends in (i) different daily rainfall amounts (<5, 5–10, 11–20, 21–40 and >40 mm∙day-1), and (ii) monthly and seasonal rainfall amounts. Drought was determined using the rainfall variability index. Daily rainfall data were derived from 18 meteorological stations in southern Africa. Daily rainfall was dominated by <5 mm∙day-1 followed by 5–10 mm∙day -1. Three locations experienced increasing linear trends of <5 mm∙day-1 amounts and two others in sub-humid region had increases in the >40 mm day -1 category. Semi-arid location experienced increasing trends in <5 and 5–10 mm∙day-1 events. A significant linear trend in seasonal rainfall occurred at two locations with decreasing rainfall (1.24 and 3 mm∙season-1). A 3 mm∙season-1 decrease in seasonal rainfall was experienced under semi-arid conditions. There were no apparent linear trends in monthly and seasonal rainfall at 15 of the 18 locations studied. Drought frequencies varied with location and were 50% or higher during the November–March growing season. Rainfall trends were location and agro-ecology specific, but most of the locations studied did not experience significant changes between the 1900s and 2000s

A Game Theoretic Model for the Formation of Navigable Small-World Networks

Kleinberg proposed a family of small-world networks to ex-plain the navigability of large-scale real-world social net-works. However, the underlying mechanism that drives real networks to be navigable is not yet well understood. In this paper, we present a game theoretic model for the for-mation of navigable small world networks. We model the network formation as a game in which people seek for both high reciprocity and long-distance relationships. We show that the navigable small-world network is a Nash Equilib-rium of the game. Moreover, we prove that the navigable small-world equilibrium tolerates collusions of any size and arbitrary deviations of a large random set of nodes, while non-navigable equilibria do not tolerate small group collu-sions or random perturbations. Our empirical evaluation further demonstrates that the system always converges to the navigable network even when limited or no information about other players ’ strategies is available. Our theoretical and empirical analyses provide important new insight on the connection between distance, reciprocity and navigability in social networks

World citation and collaboration networks: uncovering the role of geography in science

Modern information and communication technologies, especially the Internet, have diminished the role of spatial distances and territorial boundaries on the access and transmissibility of information. This has enabled scientists for closer collaboration and internationalization. Nevertheless, geography remains an important factor affecting the dynamics of science. Here we present a systematic analysis of citation and collaboration networks between cities and countries, by assigning papers to the geographic locations of their authors' affiliations. The citation flows as well as the collaboration strengths between cities decrease with the distance between them and follow gravity laws. In addition, the total research impact of a country grows linearly with the amount of national funding for research & development. However, the average impact reveals a peculiar threshold effect: the scientific output of a country may reach an impact larger than the world average only if the country invests more than about 100,000 USD per researcher annually.Comment: Published version. 9 pages, 5 figures + Appendix, The world citation and collaboration networks at both city and country level are available at http://becs.aalto.fi/~rajkp/datasets.htm

Piecing together the puzzle of pictorial representation: How jigsaw puzzles index metacognitive development

Jigsaw puzzles are ubiquitous developmental toys in Western societies, used here to examine the development of metarepresentation. For jigsaw puzzles this entails understanding that individual pieces, when assembled, produce a picture. In Experiment 1, 3-to 5-year-olds (N=117) completed jigsaw puzzles that were normal, had no picture, or comprised non-interlocking rectangular pieces. Pictorial puzzle completion was associated with mental and graphical metarepresentational task performance. Guide pictures of completed pictorial puzzles were not useful. In Experiment 2, 3- to 4-year-olds (N=52) completed a simplified task, to choose the correct final piece. Guide-use associated with age and specifically graphical metarepresentation performance. We conclude that the pragmatically natural measure of jigsaw puzzle completion ability demonstrates general and pictorial metarepresentational development at 4 years

Computational fact checking from knowledge networks

Traditional fact checking by expert journalists cannot keep up with the enormous volume of information that is now generated online. Computational fact checking may significantly enhance our ability to evaluate the veracity of dubious information. Here we show that the complexities of human fact checking can be approximated quite well by finding the shortest path between concept nodes under properly defined semantic proximity metrics on knowledge graphs. Framed as a network problem this approach is feasible with efficient computational techniques. We evaluate this approach by examining tens of thousands of claims related to history, entertainment, geography, and biographical information using a public knowledge graph extracted from Wikipedia. Statements independently known to be true consistently receive higher support via our method than do false ones. These findings represent a significant step toward scalable computational fact-checking methods that may one day mitigate the spread of harmful misinformation

Temporal rainfall trend analysis in different agro-ecological regions of southern Africa

Open Access ArticleRainfall is a major driver of food production in rainfed smallholder farming systems. This study was conducted to assess linear trends in (i) different daily rainfall amounts (40 mm∙day-1), and (ii) monthly and seasonal rainfall amounts. Drought was determined using the rainfall variability index. Daily rainfall data were derived from 18 meteorological stations in southern Africa. Daily rainfall was dominated by 40 mm day -1 category. Semi-arid location experienced increasing trends in <5 and 5–10 mm∙day-1 events. A significant linear trend in seasonal rainfall occurred at two locations with decreasing rainfall (1.24 and 3 mm∙season-1). A 3 mm∙season-1 decrease in seasonal rainfall was experienced under semi-arid conditions. There were no apparent linear trends in monthly and seasonal rainfall at 15 of the 18 locations studied. Drought frequencies varied with location and were 50% or higher during the November–March growing season. Rainfall trends were location and agro-ecology specific, but most of the locations studied did not experience significant changes between the 1900s and 2000s

Theories for influencer identification in complex networks

In social and biological systems, the structural heterogeneity of interaction networks gives rise to the emergence of a small set of influential nodes, or influencers, in a series of dynamical processes. Although much smaller than the entire network, these influencers were observed to be able to shape the collective dynamics of large populations in different contexts. As such, the successful identification of influencers should have profound implications in various real-world spreading dynamics such as viral marketing, epidemic outbreaks and cascading failure. In this chapter, we first summarize the centrality-based approach in finding single influencers in complex networks, and then discuss the more complicated problem of locating multiple influencers from a collective point of view. Progress rooted in collective influence theory, belief-propagation and computer science will be presented. Finally, we present some applications of influencer identification in diverse real-world systems, including online social platforms, scientific publication, brain networks and socioeconomic systems.Comment: 24 pages, 6 figure

SCI

Persistent homology is a powerful tool in Topological Data Analysis (TDA) to capture the topological properties of data succinctly at different spatial resolutions. For graphical data, the shape, and structure of the neighborhood of individual data items (nodes) are an essential means of characterizing their properties. We propose the use of persistent homology methods to capture structural and topological properties of graphs and use it to address the problem of link prediction. We achieve encouraging results on nine different real-world datasets that attest to the potential of persistent homology-based methods for network analysis

Geographic constraints on social network groups

Social groups are fundamental building blocks of human societies. While our social interactions have always been constrained by geography, it has been impossible, due to practical difficulties, to evaluate the nature of this restriction on social group structure. We construct a social network of individuals whose most frequent geographical locations are also known. We also classify the individuals into groups according to a community detection algorithm. We study the variation of geographical span for social groups of varying sizes, and explore the relationship between topological positions and geographic positions of their members. We find that small social groups are geographically very tight, but become much more clumped when the group size exceeds about 30 members. Also, we find no correlation between the topological positions and geographic positions of individuals within network communities. These results suggest that spreading processes face distinct structural and spatial constraints.Comment: 10 pages, 5 figure

Temporal changes in minimum and maximum temperatures at selected locations of southern Africa

Open Access JournalAgriculture is threatened by ever increasing temperatures and this trend is predicted to continue for the near and distant future. The negative impact of rising temperatures on agri-food systems is also compounded by the erratic and highly variable rainfall in most parts of southern Africa. Minimum and maximum temperatures’ variability and trend analysis were undertaken using daily time series data derived from 23 meteorological stations spread across Malawi, Mozambique, South Africa and Zimbabwe. The modified Mann–Kendall and Theil–Sen slope models were used to assess temperature trends and their magnitudes. Temperature varied with location and minimum temperature was more variable than maximum temperature. Semi-arid regions had higher variation in minimum temperature compared to humid and coastal environments. The results showed an upward trend in minimum (0.01–0.83 °C over a 33–38 year period) and maximum (0.01–0.09 °C over a 38–57 year period) temperatures at 9 and15 locations, respectively. A downward trend in minimum temperature (0.03–0.20 °C over 38–41 years) occurred in South Africa at two locations and Dedza (Malawi), while a non-significant decline in maximum temperature (0.01 °C over 54 years) occurred at one location in coastal dry sub-humid Mozambique. The results confirm the increase in temperature over 33–79 years, and highlight the importance of including temperature when designing climate change adaption and mitigation strategies in southern Africa and similar environments