457 research outputs found
Deterministic hierarchical networks
It has been shown that many networks associated with complex systems are
small-world (they have both a large local clustering coefficient and a small
diameter) and they are also scale-free (the degrees are distributed according
to a power law). Moreover, these networks are very often hierarchical, as they
describe the modularity of the systems that are modeled. Most of the studies
for complex networks are based on stochastic methods. However, a deterministic
method, with an exact determination of the main relevant parameters of the
networks, has proven useful. Indeed, this approach complements and enhances the
probabilistic and simulation techniques and, therefore, it provides a better
understanding of the systems modeled. In this paper we find the radius,
diameter, clustering coefficient and degree distribution of a generic family of
deterministic hierarchical small-world scale-free networks that has been
considered for modeling real-life complex systems
Quantum Google in a Complex Network
We investigate the behavior of the recently proposed quantum Google
algorithm, or quantum PageRank, in large complex networks. Applying the quantum
algorithm to a part of the real World Wide Web, we find that the algorithm is
able to univocally reveal the underlying scale-free topology of the network and
to clearly identify and order the most relevant nodes (hubs) of the graph
according to their importance in the network structure. Moreover, our results
show that the quantum PageRank algorithm generically leads to changes in the
hierarchy of nodes. In addition, as compared to its classical counterpart, the
quantum algorithm is capable to clearly highlight the structure of secondary
hubs of the network, and to partially resolve the degeneracy in importance of
the low lying part of the list of rankings, which represents a typical
shortcoming of the classical PageRank algorithm. Complementary to this study,
our analysis shows that the algorithm is able to clearly distinguish scale-free
networks from other widespread and important classes of complex networks, such
as Erd\H{o}s-R\'enyi networks and hierarchical graphs. We show that the ranking
capabilities of the quantum PageRank algorithm are related to an increased
stability with respect to a variation of the damping parameter that
appears in the Google algorithm, and to a more clearly pronounced power-law
behavior in the distribution of importance among the nodes, as compared to the
classical algorithm. Finally, we study to which extent the increased
sensitivity of the quantum algorithm persists under coordinated attacks of the
most important nodes in scale-free and Erd\H{o}s-R\'enyi random graphs
Recursive graphs with small-world scale-free properties
We discuss a category of graphs, recursive clique trees, which have
small-world and scale-free properties and allow a fine tuning of the clustering
and the power-law exponent of their discrete degree distribution. We determine
relevant characteristics of those graphs: the diameter, degree distribution,
and clustering parameter. The graphs have also an interesting recursive
property, and generalize recent constructions with fixed degree distributions.Comment: 4 pages, 2 figure
Vertex labeling and routing in expanded Apollonian networks
We present a family of networks, expanded deterministic Apollonian networks,
which are a generalization of the Apollonian networks and are simultaneously
scale-free, small-world, and highly clustered. We introduce a labeling of their
vertices that allows to determine a shortest path routing between any two
vertices of the network based only on the labels.Comment: 16 pages, 2 figure
What Matters Most to Patients and Rheumatologists? A Discrete Choice Experiment in Rheumatoid Arthritis
Introduction:
To determine patient and rheumatologist preferences for rheumatoid arthritis (RA) treatment attributes in Spain and to evaluate their attitude towards shared decision-making (SDM).
Methods:
Observational, descriptive, exploratory and cross-sectional study based on a discrete choice experiment (DCE). To identify the attributes and their levels, a literature review and two focus groups (patients [P] = 5; rheumatologists [R] = 4) were undertaken. Seven attributes with 2–4 levels were presented in eight scenarios. Attribute utility and relative importance (RI) were assessed using a conditional logit model. Patient preferences for SDM were assessed using an ad hoc questionnaire.
Results:
Ninety rheumatologists [52.2% women; mean years of experience 18.1 (SD: 9.0); seeing an average of 24.4 RA patients/week (SD: 15.3)] and 137 RA patients [mean age: 47.5 years (SD: 10.7); 84.0% women; mean time since diagnosis of RA: 14.2 years (SD: 11.8) and time in treatment: 13.2 years (SD: 11.2), mean HAQ score 1.2 (SD: 0.7)] participated in the study. In terms of RI, rheumatologists and RA patients viewed: time with optimal QoL: R: 23.41%/P: 35.05%; substantial symptom improvement: R: 13.15%/P: 3.62%; time to onset of treatment action: R: 16.24%/P: 13.56%; severe adverse events: R: 10.89%/P: 11.20%; mild adverse events: R: 4.16%/P: 0.91%; mode of administration: R: 25.23%/P: 25.00%; and added cost: R: 6.93%/P: 10.66%. Nearly 73% of RA patients were involved in treatment decision-making to a greater or lesser extent; however, 27.4% did not participate at all.
Conclusion:
Both for rheumatologists and patients, the top three decision-making drivers are time with optimal quality, treatment mode of administration and time to onset of action, although in different ranking order. Patients were willing to be more involved in the treatment decision-making process
Site-specific perturbations of alpha-synuclein fibril structure by the Parkinson's disease associated mutations A53T and E46K.
PMCID: PMC3591419This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Parkinson's disease (PD) is pathologically characterized by the presence of Lewy bodies (LBs) in dopaminergic neurons of the substantia nigra. These intracellular inclusions are largely composed of misfolded α-synuclein (AS), a neuronal protein that is abundant in the vertebrate brain. Point mutations in AS are associated with rare, early-onset forms of PD, although aggregation of the wild-type (WT) protein is observed in the more common sporadic forms of the disease. Here, we employed multidimensional solid-state NMR experiments to assess A53T and E46K mutant fibrils, in comparison to our recent description of WT AS fibrils. We made de novo chemical shift assignments for the mutants, and used these chemical shifts to empirically determine secondary structures. We observe significant perturbations in secondary structure throughout the fibril core for the E46K fibril, while the A53T fibril exhibits more localized perturbations near the mutation site. Overall, these results demonstrate that the secondary structure of A53T has some small differences from the WT and the secondary structure of E46K has significant differences, which may alter the overall structural arrangement of the fibrils
The water balance in Mendoza : measurement proposals
La Ley N°8051/2009 de Ordenamiento Territorial y Usos del Suelo de Mendoza subraya la importancia de considerar la disponibilidad de agua para garantizar un uso equilibrado del territorio. La Ley General de Aguas de 1884 y la ConstituciĂłn Provincial de 1916 destacan la necesidad de verificar la existencia de excedentes hĂdricos previa a la entrega de nuevas concesiones. Considerando al balance hĂdrico como un elemento para el manejo de la sustentabilidad del recurso hĂdrico y del suelo, los objetivos del presente estudio son: describir los componentes del balance para las cuencas de Mendoza, proponer alternativas para su mediciĂłn y esclarecer su incidencia en la planificaciĂłn del territorio. El balance hĂdrico se mide a nivel de cuenca o subcuenca y se entiende como la diferencia entre la oferta y la demanda de agua, para verificar la existencia de excedentes. La oferta proviene de los aforos de los rĂos y de evaluaciones de recarga subterránea y está afectada cuantitativamente por la contaminaciĂłn. La demanda está integrada por los diferentes usos: domĂ©stico, riego, industrial, municipal y ambiental. Se discuten y proponen alternativas de estimaciĂłn para los tĂ©rminos de la demanda. Ante la falta de mediciones directas sobre los elementos que integran la demanda, se recomienda realizar mediciones indirectas utilizando coeficientes de uso de agua por unidad de consumo. Se sugiere modelizar el balance hĂdrico como variable importante para la construcciĂłn de escenarios alternativos y del modelo territorial deseado.Law 8051 of Land Use Planning and Soil Use in Mendoza, which was passed in 2009, recognizes the importance of considering water availability to ensure a balanced use of the land. The Water Law of 1884 and the Provincial Constitution of 1916 refer to the need to check the existence of water surpluses before granting new water use permits. Since water balance is a crucial element for managing water and soil sustainability, the objectives of this study are to describe the system’s components in the Mendoza basins, to propose measurement alternatives and to explore its impact on land use planning. The water balance is measured at the basin or sub-basin level and since it is considered as the difference between water supply and demand, it is possible to check the existence of water surpluses. The water supply comes from river gauging and from groundwater recharge. Water supply is affected by surface and groundwater pollution. Water demand comes from different uses: domestic, irrigation, industrial, municipal and environmental. Assessment alternatives are discussed and proposed. Given the lack of direct measurements of water demand, it is recommended to conduct indirect measurements using water use coefficients per unit of consumption. The study proposes to model the water balance as a relevant variable to construct alternative scenarios and to apply them to the intended land use model.Fil: Llop, Armando A..
Instituto Nacional del Agua. Centro de EconomĂa, LegislaciĂłn y AdministraciĂłn del AguaFil: Fasciolo, Graciela.
Instituto Nacional del Agua. Centro de EconomĂa, LegislaciĂłn y AdministraciĂłn del AguaFil: Duek, Alicia E..
Instituto Nacional del Agua. Centro de EconomĂa, LegislaciĂłn y AdministraciĂłn del AguaFil: Comellas, Eduardo A..
Instituto Nacional del Agua. Centro de EconomĂa, LegislaciĂłn y AdministraciĂłn del AguaFil: Buccheri, Mauricio J..
Instituto Nacional del Agua. Centro de EconomĂa, LegislaciĂłn y AdministraciĂłn del Agu
Disease networks identify specific conditions and pleiotropy influencing multimorbidity in the general population
Multimorbidity is an emerging topic in public health policy because of its increasing prevalence and socio-economic impact. However, the age- and gender-dependent trends of disease associations at fine resolution, and the underlying genetic factors, remain incompletely understood. Here, by analyzing disease networks from electronic medical records of primary health care, we identify key conditions and shared genetic factors influencing multimorbidity. Three types of diseases are outlined: “central”, which include chronic and non-chronic conditions, have higher cumulative risks of disease associations; “community roots” have lower cumulative risks, but inform on continuing clustered disease associations with age; and “seeds of bursts”, which most are chronic, reveal outbreaks of disease associations leading to multimorbidity. The diseases with a major impact on multimorbidity are caused by genes that occupy central positions in the network of human disease genes. Alteration of lipid metabolism connects breast cancer, diabetic neuropathy and nutritional anemia. Evaluation of key disease associations by a genome-wide association study identifies shared genetic factors and further supports causal commonalities between nervous system diseases and nutritional anemias. This study also reveals many shared genetic signals with other diseases. Collectively, our results depict novel population-based multimorbidity patterns, identify key diseases within them, and highlight pleiotropy influencing multimorbidity.Postprint (author's final draft
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