Scaling laws of human interaction activity

Even though people in our contemporary, technological society are depending on communication, our understanding of the underlying laws of human communicational behavior continues to be poorly understood. Here we investigate the communication patterns in two social Internet communities in search of statistical laws in human interaction activity. This research reveals that human communication networks dynamically follow scaling laws that may also explain the observed trends in economic growth. Specifically, we identify a generalized version of Gibrat's law of social activity expressed as a scaling law between the fluctuations in the number of messages sent by members and their level of activity. Gibrat's law has been essential in understanding economic growth patterns, yet without an underlying general principle for its origin. We attribute this scaling law to long-term correlation patterns in human activity, which surprisingly span from days to the entire period of the available data of more than one year. Further, we provide a mathematical framework that relates the generalized version of Gibrat's law to the long-term correlated dynamics, which suggests that the same underlying mechanism could be the source of Gibrat's law in economics, ranging from large firms, research and development expenditures, gross domestic product of countries, to city population growth. These findings are also of importance for designing communication networks and for the understanding of the dynamics of social systems in which communication plays a role, such as economic markets and political systems.Comment: 20+7 pages, 4+2 figure

On Universality in Human Correspondence Activity

Identifying and modeling patterns of human activity has important ramifications in applications ranging from predicting disease spread to optimizing resource allocation. Because of its relevance and availability, written correspondence provides a powerful proxy for studying human activity. One school of thought is that human correspondence is driven by responses to received correspondence, a view that requires distinct response mechanism to explain e-mail and letter correspondence observations. Here, we demonstrate that, like e-mail correspondence, the letter correspondence patterns of 16 writers, performers, politicians, and scientists are well-described by the circadian cycle, task repetition and changing communication needs. We confirm the universality of these mechanisms by properly rescaling letter and e-mail correspondence statistics to reveal their underlying similarity.Comment: 17 pages, 3 figures, 1 tabl

Qualité des modèles : retours d'expériences

National audienceAvec la complexification des systèmes d'information (systèmes ubiquitaires, entreprises ouvertes etc.), de nombreux nouveaux langages de modélisation sont proposés. Face à ce développement de langages spécifiques, on peut s'interroger sur la qualité des modèles qui en sont issus. Cet article traite de ce problème en tirant les leçons de nos expériences passées. Elles mettent en évidence les besoins d'outillage automatisé pour l'évaluation de la qualité de modèles, la participation conjointe des différentes parties prenantes dans le processus d'évaluation, et la nécessité d'envisager une véritable ingénierie des langages et des modèles centrée sur l'humain

The inception of a group psychotherapeutic intervention in infertile women – difficulties and obstacles through the constitution of a group setting in a maternity hospital

Several cases of infertility without the presence of a known medical cause and with a spontaneous remission have been studied from the psychological point of view. A look at infertility, in a psychodynamic way, suggests that it is the result of a defensive activation, aimed at promoting emotional protection, seen in pregnant women in high-risk obstetrics, in infertile couples waiting for infertility appointments and in pregnant women waiting for amniocentesis examination outcome. Thus, a spontaneous remission may be seen as a translation that the psychological impasse would have been overcome. This article intends to present a research project that has been held at the Maternity Hospital Dr. Alfredo da Costa (MAC), in Lisbon, and which participants are women followed in the MAC infertility consultation, unable to conceive or lead to good fruition a pregnancy after at least one year of regular sexual intercourse without resorting to contraceptive methods. In this article we intend to reflect the hindrances, difficulties and obstacles felt through the inception of a group psychotherapeutic setting in a Maternity Hospital. After all the bureaucratic issues have been solved out, the psychological resistance of the participants emerged, revealing to be a pattern

Development of support vector machine learning algorithm for real time update of resource estimation and grade classification

This paper presents the development and implementation of a theoretical mathematical-statistical framework for sequential updating of the grade control model, based on a support vector machine learning algorithm. Utilising the Zambujal orebody within the Neves-Corvo Cu deposit in Portugal, parameters that can be measured in real time, used in visualisation, modelled for resource estimation, and used for process control visualisation and optimisation are considered. The methodology broadly comprises of three steps. Firstly, the provided dataset is used to develop a virtual asset model (VAM) representing the true 3D grade distribution in order to simulate the mining method. Then ore quality parameters are established simulating real time monitoring sensor installation at: (a) stope development and rock face monitoring (face imaging and drillholes); and (b) transport monitoring (muck pile, LHD/scooptram). Next, the acquired data was assimilated into the models as part of the sequential model update. Two different mining methods and the monitoring information that can be acquired during the ore extraction are analysed: (a) drift and fill mining and (b) bench and fill mining, which are widely implemented at the Neves-Corvo mine. Selected study zones were chosen such as to contrast mining through the high/low grade zones with different degrees of heterogeneity, which demonstrate the performance of resource estimation and classification models developed in heterogeneous mining stopes. The grade accuracy and error in the resource model, and high/low grade ore classification accuracy and error are evaluated as performance metrics for the proposed methods. In drift and fill mining, drillhole and face sampling data collection was simulated in a real-time manner and fed into the support vector machine (SVM) regressor to update the resource estimation model in both a high grade and low grade drift scenarios. In each scenario, six drift and fill mining steps were simulated sequentially and the posterior resource models, after integrating real time mining data, have shown significant improvement of bias correction in both updating planned resources and reconciling extracted ore. In bench and fill mining, grade classification based on random sampling data from muck pile was demonstrated, considering scoop by scoop derived monitoring data. Three different classifiers (mean, median, and Bayesian) were tested and shown very good performance. In the case study presented here, a sequence of 15 blasting steps was simulated with each step requiring 112 scooping operations to transport the blasted ore. Using the real time monitored information, it was shown that at each blasting step over 85% of the scoops can be labelled correctly using the proposed methods and with an accuracy of over 95%

Uptake of oxLDL and IL-10 production by macrophages requires PAFR and CD36 recruitment into the same lipid rafts

Macrophage interaction with oxidized low-density lipoprotein (oxLDL) leads to its differentiation into foam cells and cytokine production, contributing to atherosclerosis development. In a previous study, we showed that CD36 and the receptor for platelet-activating factor (PAFR) are required for oxLDL to activate gene transcription for cytokines and CD36. Here, we investigated the localization and physical interaction of CD36 and PAFR in macrophages stimulated with oxLDL. We found that blocking CD36 or PAFR decreases oxLDL uptake and IL-10 production. OxLDL induces IL-10 mRNA expression only in HEK293T expressing both receptors (PAFR and CD36). OxLDL does not induce IL-12 production. The lipid rafts disruption by treatment with βCD reduces the oxLDL uptake and IL-10 production. OxLDL induces co-immunoprecipitation of PAFR and CD36 with the constitutive raft protein flotillin-1, and colocalization with the lipid raft-marker GM1-ganglioside. Finally, we found colocalization of PAFR and CD36 in macrophages from human atherosclerotic plaques. Our results show that oxLDL induces the recruitment of PAFR and CD36 into the same lipid rafts, which is important for oxLDL uptake and IL-10 production. This study provided new insights into how oxLDL interact with macrophages and contributing to atherosclerosis development

Expression of histone methyltransferases as novel biomarkers for renal cell tumor diagnosis and prognostication

Renal cell tumors (RCTs) are the most lethal of the common urological cancers. The widespread use of imaging entailed an increased detection of small renal masses, emphasizing the need for accurate distinction between benign and malignant RCTs, which is critical for adequate therapeutic management. Histone methylation has been implicated in renal tumorigenesis, but its potential clinical value as RCT biomarker remains mostly unexplored. Hence, the main goal of this study was to identify differentially expressed histone methyltransferases (HMTs) and histone demethylases (HDMs) that might prove useful for RCT diagnosis and prognostication, emphasizing the discrimination between oncocytoma (a benign tumor) and renal cell carcinoma (RCC), especially the chromophobe subtype (chRCC). We found that the expression levels of three genes-SMYD2, SETD3, and NO66-was significantly altered in a set of RCTs, which was further validated in a large independent cohort. Higher expression levels were found in RCTs compared to normal renal tissues (RNTs) and in chRCCs comparatively to oncocytomas. SMYD2 and SETD3 mRNA levels correlated with protein expression assessed by immunohistochemistry. SMYD2 transcript levels discriminated RCTs from RNT, with 82.1% sensitivity and 100% specificity (AUC=0.959), and distinguished chRCCs from oncocytomas, with 71.0% sensitivity and 73.3% specificity (AUC: 0.784). Low expression levels of SMYD2, SETD3, and NO66 were significantly associated with shorter disease-specific and disease-free survival, especially in patients with non-organ confined tumors. We conclude that expression of selected HMTs and HDMs might constitute novel biomarkers to assist in RCT diagnosis and assessment of tumor aggressiveness.This study was funded by research grants from Research Center of Portuguese Oncology Institute – Porto (CI-IPOP 4-2012) and European Community’s Seventh Framework Program – Grant number FP7-HEALTH-F5-2009-241783. ASP-L and FQV are and were supported by FCT-Fundação para a Ciência e a Tecnologia grants (SFRH/SINTD/94217/2013 and SFRH/ BD/70564/2010, respectively)