Asymmetry through time dependency

Given a single network of interactions, asymmetry arises when the links are directed. For example, if protein A upregulates protein B and protein B upregulates protein C, then (in the absence of any further relationships between them) A may affect C but not vice versa. This type of imbalance is reflected in the associated adjacency matrix, which will lack symmetry. A different type of imbalance can arise when interactions appear and disappear over time. If A meets B today and B meets C tomorrow, then (in the absence of any further relationships between them) A may pass a message or disease to C, but not vice versa. Hence, even when each interaction is a two-way exchange, the effect of time ordering can introduce asymmetry. This observation is very closely related to the fact that matrix multiplication is not commutative. In this work, we describe a method that has been designed to reveal asymmetry in static networks and show how it may be combined with a measure that summarizes the potential information flow between nodes in the temporal case. This results in a new method that quantifies the asymmetry arising through time ordering. We show by example that the new tool can be used to visualize and quantify the amount of asymmetry caused by the arrow of time

Modern temporal network theory: A colloquium

The power of any kind of network approach lies in the ability to simplify a complex system so that one can better understand its function as a whole. Sometimes it is beneficial, however, to include more information than in a simple graph of only nodes and links. Adding information about times of interactions can make predictions and mechanistic understanding more accurate. The drawback, however, is that there are not so many methods available, partly because temporal networks is a relatively young field, partly because it more difficult to develop such methods compared to for static networks. In this colloquium, we review the methods to analyze and model temporal networks and processes taking place on them, focusing mainly on the last three years. This includes the spreading of infectious disease, opinions, rumors, in social networks; information packets in computer networks; various types of signaling in biology, and more. We also discuss future directions.Comment: Final accepted versio

Measurement of Z0 decays to hadrons, and a precise determination of the number of neutrino species

We have made a precise measurement of the cross section for e+e--->Z0-->hadrons with the L3 detector at LEP, covering the range from 88.28 to 95.04 GeV. From a fit to the Z0 mass, total width, and the hadronic cross section to be MZ0=91.160 +/- 0.024 (experiment) +/-0.030(LEP) GeV, [Gamma]Z0=2.539+/-0.054 GeV, and [sigma]h(MZ0)=29.5+/-0.7 nb. We also used the fit to the Z0 peak cross section and the width todetermine [Gamma]invisible=0.548+/-0.029 GeV, which corresponds to 3.29+/-0.17 species of light neutrinos. The possibility of four or more neutrino flavors is thus ruled out at the 4[sigma] confidence level.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/28683/3/0000500.pd

A measurement of the Z0 leptonic partial widths and the vector and axial vector coupling constants

We have measured the partial widths of the Z0 into lepton pairs, and the forward-backward charge asymmetry for the process e+e--->[mu]+[mu]- using the L3 detector at LEP. We obtain an average [Gamma]ll of 83.0+/-2.1+/-1.1 MeV.From this result and the asymmetry measurement, we extract the values of the vector and axial vector couplings of the Z0 to leptons: grmv=-0.066-0.027+0.046 and grmA= -0.495-0.007+0.007.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/28666/3/0000483.pd

Evaluation Of Screening For Breast Cancer In a Non-Randomised Study (The Dom Project) By Means Of a Case-Control Study

In 1974 a non-randomised study of the effect of mass screening by physical examination and xeromammography on mortality from breast cancer was started. Of the 20 555 eligible women in the city of Utrecht born between 1911 and 1925 (aged 50-64 at the start of the study), 14 796 attended for screening. Four rounds of screening were carried out. The relative risk of dying from breast cancer among women ever screened compared with women never screened was 0·30 (95% confidence interval 0·13 - 0·70)

Abdominal fat predominance in women is associated with a decreased prevalence of the high risk P2, DY mammographic breast patterns.

Body fat distribution was studied in relation to mammographic breast morphology in a cross-sectional sample of 583 women aged 41-75 years participating in the DOM project, a regional breast cancer detection project in Utrecht, the Netherlands. The waist/hip ratio (WHR) was used as an indicator of body fat topography. Mammographic breast morphology was categorized according to the parenchymal breast patterns (N1, P1, P2, DY) as defined by Wolfe. Multivariate associations between the waist/hip ratio, Quetelet's index, age and parity and mammographic parenchymal patterns were tested by multiple linear logistic regression. Independently of age, parity and the degree of obesity, women with a high WHR ratio, i.e. with a predominant fat accumulation in the abdominal region, were significantly less likely to have the high risk P2, DY mammographic parenchymal pattern than women with a low WHR, i.e. with a preferential gluteal-femoral fat accumulation