Dynamics of deceptive interactions in social networks

In this paper we examine the role of lies in human social relations by implementing some salient characteristics of deceptive interactions into an opinion formation model, so as to describe the dynamical behaviour of a social network more realistically. In this model we take into account such basic properties of social networks as the dynamics of the intensity of interactions, the influence of public opinion, and the fact that in every human interaction it might be convenient to deceive or withhold information depending on the instantaneous situation of each individual in the network. We find that lies shape the topology of social networks, especially the formation of tightly linked, small communities with loose connections between them. We also find that agents with a larger proportion of deceptive interactions are the ones that connect communities of different opinion, and in this sense they have substantial centrality in the network. We then discuss the consequences of these results for the social behaviour of humans and predict the changes that could arise due to a varying tolerance for lies in society.Comment: 17 pages, 8 figures; Supplementary Information (3 pages, 1 figure

Universal model for the skin colouration patterns of neotropical catfishes of the genus Pseudoplatystoma

Fish skin colouration has been widely studied because it involves a variety of processes that are important to the broad field of the developmental biology. Mathematical modelling of fish skin patterning first predicted the existence of morphogens and helped to elucidate the mechanisms of pattern formation. The catfishes of the genus Pseudoplatystoma offer a good biological study model, since its species exhibit the most spectacular and amazing variations of colour patterns on the skin. They present labyrinths, closed loops (or cells), alternate spots and stripes, only spots and combinations of these. We have extended a well known mathematical model to study the skin of Pseudoplatystoma. The basic model is a two component, non-linear reaction diffusion system that presents a richness of bifurcations. The extended model assumes that there are two interacting cell/tissue layers in which morphogens diffuse and interact giving rise to the skin colouration pattern. We have found that by varying only two parameters we are able to accurately reproduce the distinct patterns found in all species of Pseudoplatystoma. The histological analysis of skin samples of two species of this genus, with different patterns, revealed differences on the disposition of the colouration cells that are consistent with our theoretical predictions.Fil: Scarabotti, Pablo Augusto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto Nacional de Limnología. Universidad Nacional del Litoral. Instituto Nacional de Limnología; ArgentinaFil: Govezensky, Tzipe. Universidad Nacional Autónoma de México; MéxicoFil: Bolcatto, Pablo Guillermo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Matemática Aplicada del Litoral. Universidad Nacional del Litoral. Instituto de Matemática Aplicada del Litoral; ArgentinaFil: Barrio, Rafael Ángel. Universidad Nacional Autónoma de México; Méxic

Neutrophil to lymphocyte ratio and principal component analysis offer prognostic advantage for dogs with mammary tumors

IntroductionIn veterinary medicine, cancer is the leading cause of death in companion animals, and mammary gland tumors represent the most common neoplasm in female dogs. Several epidemiological risk factors, such as age, breed, hormones, diet, and obesity have been reported to be relevant for canine mammary tumors. Nowadays, the gold standard for diagnosis of canine mammary tumors is the pathological examination of the suspected tissue. However, tumor grade can only be assessed after surgical removal or biopsy of the altered tissue. Therefore, in cases of tumors that could be surgically removed, it would be very helpful to be able to predict the biological behavior of the tumor, before performing any surgery. Since, inflammation constitutes part of the tumor microenvironment and it influences each step of tumorigenesis, cellular and biochemical blood markers of systemic inflammation, such as the neutrophil to lymphocyte ratio (NLR) and the albumin to globulin ratio (AGR) have been proposed as prognostic factors for human cancer development. The NLR and the AGR have not been explored enough as prognostic factors for cancer development in veterinary medicine.MethodsTo determine the prognostic value of NLR in canine mammary tumors, clinical records including biochemistry and hematological studies of female dogs with mammary tumors and of control healthy dogs, were used to determine the pre-treatment NLR and AGR. Other clinical data included age, breed, tumor size, histological tumor grade, and survival time after surgery.Results and discussionIt was found that a higher pre-treatment NLR value (NLR > 5) associates with less survival rate. In contrast, the AGR did not show any predictive value on the malignancy of the tumor. However, by combining the NLR with AGR, age of the dog, and tumor size in a principal component analysis (PCA), the grade of the tumor and survival after surgery could be appropriately predicted. These data strongly suggest that pre-treatment NLR values have a prognostic value for the survival rate after surgery of dogs with mammary tumors

Socio-economic pandemic modelling: case of Spain

A global disaster, such as the recent Covid-19 pandemic, afects every aspect of our lives and there is a need to investigate these highly complex phenomena if one aims to diminish their impact in the health of the population, as well as their socio-economic stability. In this paper we present an attempt to understand the role of the governmental authorities and the response of the rest of the population facing such emergencies. We present a mathematical model that takes into account the epidemiological features of the pandemic and also the actions of people responding to it, focusing only on three aspects of the system, namely, the fear of catching this serious disease, the impact on the economic activities and the compliance of the people to the mitigating measures adopted by the authorities. We apply the model to the specifc case of Spain, since there are accurate data available about these three features. We focused on tourism as an example of the economic activity, since this sector of economy is one of the most likely to be afected by the restrictions imposed by the authorities, and because it represents an important part of Spanish economy. The results of numerical calculations agree with the empirical data in such a way that we can acquire a better insight of the diferent processes at play in such a complex situation, and also in other diferent circumstances.Fil: Snellman, Jan E.. Aalto University; FinlandiaFil: Barreiro, Nadia Luisina. Ministerio de Defensa. Instituto de Investigaciones Científicas y Técnicas para la Defensa; ArgentinaFil: Barrio, Rafael Ángel. Universidad Nacional Autónoma de México; MéxicoFil: Ventura, Cecilia Ileana. Universidad Nacional de Río Negro; Argentina. Comisión Nacional de Energía Atómica. Gerencia del Área de Investigación y Aplicaciones No Nucleares. Gerencia de Física (Centro Atómico Bariloche); Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte; ArgentinaFil: Govezensky, Tzipe. Universidad Nacional Autónoma de México; MéxicoFil: Kaski, Kimmo K.. Aalto University; FinlandiaFil: Korpi Lagg, Maarit J.. Stockholms Universitet; Sueci

Impact of institutional organization on research productivity and multidisciplinarity

In this article, we will describe a model to examine the influence of differently organized institutions on their scientific productivity. We take two extreme cases, on one hand, an institution divided in departments with no collaboration between people in different departments. These could be disciplines or merely projects. On the other hand, we consider an institution that allows interactions between all individuals, without a departmental structure to a department. We compare the results with data from the Institute of Renewable Energy (IER) at UNAM, which has changed its organization and policies during the last 30 years, and we could quantitatively predict the changes observed in productivity and multidisciplinarity. This model can be applied to a broader set of institutions and processes