Triadic Motifs in the Partitioned World Trade Web

AbstractOne of the crucial aspects of the Internet of Things that influences the effectiveness of communication among devices is the communication model, for which no universal solution exists. The actual interaction pattern can in general be represented as a directed graph, whose nodes represent the "Things" and whose directed edges represent the sent messages. Frequent patterns can identify channels or infrastructures to be strengthened and can help in choosing the most suitable message routing schema or network protocol. In general, frequent patterns have been called motifs and overrepresented motifs have been recognized to be the low-level building blocks of networks and to be useful to explain many of their properties, playing a relevant role in determining their dynamic and evolution. In this paper triadic motifs are found first partitioning a network by strength of connections and then analyzing the partitions separately. The case study is the World Trade Web (WTW), that is the directed graph connecting world Countries with trade relationships, with the aim of finding its topological characterization in terms of motifs and isolating the key factors underlying its evolution. The WTW has been split based on the weights of the graph to highlight structural differences between the big players in terms of volumes of trade and the rest of the world. As test case, the period 2003-2010 has been analyzed, to show the structural effect of the economical crisis in the year 2007

Defining the role of two newly identified proteins in the Vibrio vulnificus TonB2 system

Vibrio vulnificus is a human pathogenic bacteria that is closely related to Vibrio cholera, the disease causing agent of cholera. Three TonB transport systems are found in the outer membrane of V. vulnificus and are responsible for powering the uptake of iron bound siderophores into the cell. Within the Ton82 and TonB3 systems are two proteins, Orf1 and Orf6. The function and necessity of Orf1 and Orf6 to the TonB systems were investigated through the use of growth, motility, and antibiotic sensitivity assays and RNA transcriptional level analysis

Statistical moments of power spectrum: a fast tool for the classification of seismic events recorded on volcanoes

Abstract. Spectral analysis has been applied to almost thousand seismic events recorded at Vesuvius volcano (Naples, southern Italy) in 2018 with the aim to test a new tool for a fast event classification. We computed two spectral parameters, central frequency and shape factor, from the spectral moments of order 0, 1, and 2, for each event at seven seismic stations taking the mean among the three components of ground motion. The analyzed events consist of volcano-tectonic earthquakes, low frequency events and unclassified events (landslides, rockfall, thunders, quarry blasts, etc.). Most of them are of low magnitude, and/or low maximum signal amplitude, therefore the signal to noise ratio is very different between the low noise summit stations and the higher noise stations installed at low elevation around the volcano. The results of our analysis show that volcano-tectonic earthquakes and low frequency events are easily distinguishable through the spectral moments values, particularly at seismic stations closer to the epicenter. On the contrary, unclassified events show the spectral parameters values distributed in a broad range which overlap both the volcano-tectonic earthquakes and the low frequency events. Since the computation of spectral parameters is extremely easy and fast for a detected event, it may become an effective tool for event classification in observatory practice