570 research outputs found
The global migration network of sex-workers
Differences in the social and economic environment across countries encourage
humans to migrate in search of better living conditions, including job
opportunities, higher salaries, security and welfare. Quantifying global
migration is, however, challenging because of poor recording, privacy issues
and residence status. This is particularly critical for some classes of
migrants involved in stigmatised, unregulated or illegal activities. Escorting
services or high-end prostitution are well-paid activities that attract workers
all around the world. In this paper, we study international migration patterns
of sex-workers by using network methods. Using an extensive international
online advertisement directory of escorting services and information about
individual escorts, we reconstruct a migrant flow network where nodes represent
either origin or destination countries. The links represent the direct routes
between two countries. The migration network of sex-workers shows different
structural patterns than the migration of the general population. The network
contains a strong core where mutual migration is often observed between a group
of high-income European countries, yet Europe is split into different network
communities with specific ties to non-European countries. We find
non-reciprocal relations between countries, with some of them mostly offering
while others attract workers. The GDP per capita is a good indicator of country
attractiveness for incoming workers and service rates but is unrelated to the
probability of emigration. The median financial gain of migrating, in
comparison to working at the home country, is 15.9%. Only sex-workers coming
from 77% of the countries have financial gains with migration and average gains
decrease with the GDPc of the country of origin. Our results shows that
high-end sex-worker migration is regulated by economic, geographic and cultural
aspects.Comment: Comments and feedback welcomed. Two tables and 6 figures including S
Mass spectrometry improvement on an high current ion implanter
The development of accurate mass spectrometry, enabling the identification of all the ions extracted from the ion source in a high current implanter is described. The spectrometry system uses two signals (x-y graphic), one proportional to the magnetic field (x-axes), taken from the high-voltage potential with an optic fiber system, and the other proportional to the beam current intensity (y-axes), taken from a beam-stop. The ion beam mass register in a mass spectrum of all the elements magnetically analyzed with the same radius and defined by a pair of analyzing slits as a function of their beam intensity is presented. The developed system uses a PC to control the displaying of the extracted beam mass spectrum, and also recording of all data acquired for posterior analysis. The operator uses a LabView code that enables the interfacing between an I/O board and the ion implanter. The experimental results from an ion implantation experiment are shown. (C) 2011 Elsevier B.V. All rights reserved
The Effect of Feed Supplementation and Sward Characteristics on the Ingestive Behaviour of Grazing Ewes
The objective of this study was to assess the effect of protein/energy supplementation and sward physical characteristics on grazing behaviour of lactating ewes grazing Italian ryegrass (Lolium multiflorum Lam.). The experiment was carried out in the spring of 1999 at the Universidade Federal de Santa Maria. The grazing behaviour was assessed in two periods: 2 and 3 September, and 8 and 9 October of 1999, using a group of twelve yearling ewes. Groups of four ewes were either supplemented (with 1% of the animals live weight) with soybean meal (protein source), with corn (energy source) or not supplemented. The experiment was carried out in a completely randomised block design with four replications. This experiment shows that grazing behaviour is more strongly affected by sward characteristics than by protein or energy supplementation
DyNetVis: a system for visualization of dynamic networks
The concept of networks has been important in the study of complex systems. In networks, links connect pairs of nodes forming complex structures. Studies have shown that networks not only contain structure but may also evolve in time. The addition of the temporal dimension adds complexity on the analysis and requests the development of innovative methods for the visualization of real-life networks. In this paper we introduce the Dynamic Network Visualization System (DyNetVis), a software tool for visualization of dynamic networks. The system provides several tools for user interaction and offers two coordinated visual layouts, named structural and temporal. Structural refers to standard network drawing techniques, in which a single snapshot of nodes and links are placed in a plane, whereas the temporal layout allows for simultaneously visualization of several temporal snapshots of the dynamic network. In addition, we also investigate two approaches for temporal layout visualization: (i) Recurrent Neighbors, a node ordering strategy that highlights frequent connections in time, and (ii) Temporal Activity Map (TAM), a layout technique with focus on nodes activity. We illustrate the applicability of the layouts and interaction functionalities provided by the system in two visual analysis case studies, demonstrating their advantages to improve the overall user experience on visualization and exploratory data analysis on dynamic networks
Emergence of Secondary Acute Leukemia in a Patient Treated for Osteosarcoma: Implications of Germline TP53 Mutations
Secondary leukemia and myelodysplastic syndromes have been reported
in patients following treatment for a wide range of neoplastic disorders. However
second malignancies after chemotherapy and/or irradiation for osteosarcoma are
unusual. PROCEDURE: We report the case of a 15-year-old girl who developed a
myelodysplastic syndrome with evolution to acute nonlymphocytic leukemia after
treatment for osteosarcoma. Therapy-related acute leukemia karyotype findings
such as abnormalities of chromosomes 5, 7, and 17 were found in the cytogenetic
analysis. Moreover, using denaturing gradient gel electrophoresis and DNA
sequencing, we detected the presence of a double germline mutation in exon 7 of
the TP53 gene. CONCLUSION: This observation supports the possibility of a causal
relationship between germline TP53 mutations and the development of secondary
leukemia and myelodysplasi
Evolution of the public opinion on COVID-19 vaccination in Japan
Vaccines are promising tools to control the spread of COVID-19. An effective
vaccination campaign requires government policies and community engagement,
sharing experiences for social support, and voicing concerns to vaccine safety
and efficiency. The increasing use of online social platforms allows us to
trace large-scale communication and infer public opinion in real-time. We
collected more than 100 million vaccine-related tweets posted by 8 million
users and used the Latent Dirichlet Allocation model to perform automated topic
modeling of tweet texts during the vaccination campaign in Japan. We identified
15 topics grouped into 4 themes on Personal issue, Breaking news, Politics, and
Conspiracy and humour. The evolution of the popularity of themes revealed a
shift in public opinion, initially sharing the attention over personal issues
(individual aspect), collecting information from the news (knowledge
acquisition), and government criticisms, towards personal experiences once
confidence in the vaccination campaign was established. An interrupted time
series regression analysis showed that the Tokyo Olympic Games affected public
opinion more than other critical events but not the course of the vaccination.
Public opinion on politics was significantly affected by various events,
positively shifting the attention in the early stages of the vaccination
campaign and negatively later. Tweets about personal issues were mostly
retweeted when the vaccination reached the younger population. The associations
between the vaccination campaign stages and tweet themes suggest that the
public engagement in the social platform contributed to speedup vaccine uptake
by reducing anxiety via social learning and support
Sampling of temporal networks: methods and biases
Temporal networks have been increasingly used to model a diversity of systems that evolve in time; for example, human contact structures over which dynamic processes such as epidemics take place. A fundamental aspect of real-life networks is that they are sampled within temporal and spatial frames. Furthermore, one might wish to subsample networks to reduce their size for better visualization or to perform computationally intensive simulations. The sampling method may affect the network structure and thus caution is necessary to generalize results based on samples. In this paper, we study four sampling strategies applied to a variety of real-life temporal networks. We quantify the biases generated by each sampling strategy on a number of relevant statistics such as link activity, temporal paths and epidemic spread. We find that some biases are common in a variety of networks and statistics, but one strategy, uniform sampling of nodes, shows improved performance in most scenarios. Given the particularities of temporal network data and the variety of network structures, we recommend that the choice of sampling methods be problem oriented to minimize the potential biases for the specific research questions on hand. Our results help researchers to better design network data collection protocols and to understand the limitations of sampled temporal network data
Random walk centrality for temporal networks
Nodes can be ranked according to their relative importance within a network. Ranking algorithms based on random walks are particularly useful because they connect topological and diffusive properties of the network. Previous methods based on random walks, for example the PageRank, have focused on static structures. However, several realistic networks are indeed dynamic, meaning that their structure changes in time. In this paper, we propose a centrality measure for temporal networks based on random walks under periodic boundary conditions that we call TempoRank. It is known that, in static networks, the stationary density of the random walk is proportional to the degree or the strength of a node. In contrast, we find that, in temporal networks, the stationary density is proportional to the in-strength of the so-called effective network, a weighted and directed network explicitly constructed from the original sequence of transition matrices. The stationary density also depends on the sojourn probability q, which regulates the tendency of the walker to stay in the node, and on the temporal resolution of the data. We apply our method to human interaction networks and show that although it is important for a node to be connected to another node with many random walkers (one of the principles of the PageRank) at the right moment, this effect is negligible in practice when the time order of link activation is included
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