8,770 research outputs found
The Network Picture of Labor Flow
We construct a data-driven model of flows in graphs that captures the
essential elements of the movement of workers between jobs in the companies
(firms) of entire economic systems such as countries. The model is based on the
observation that certain job transitions between firms are often repeated over
time, showing persistent behavior, and suggesting the construction of static
graphs to act as the scaffolding for job mobility. Individuals in the job
market (the workforce) are modelled by a discrete-time random walk on graphs,
where each individual at a node can possess two states: employed or unemployed,
and the rates of becoming unemployed and of finding a new job are node
dependent parameters. We calculate the steady state solution of the model and
compare it to extensive micro-datasets for Mexico and Finland, comprised of
hundreds of thousands of firms and individuals. We find that our model
possesses the correct behavior for the numbers of employed and unemployed
individuals in these countries down to the level of individual firms. Our
framework opens the door to a new approach to the analysis of labor mobility at
high resolution, with the tantalizing potential for the development of full
forecasting methods in the future.Comment: 27 pages, 6 figure
Frictional Unemployment on Labor Flow Networks
We develop an alternative theory to the aggregate matching function in which
workers search for jobs through a network of firms: the labor flow network. The
lack of an edge between two companies indicates the impossibility of labor
flows between them due to high frictions. In equilibrium, firms' hiring
behavior correlates through the network, generating highly disaggregated local
unemployment. Hence, aggregation depends on the topology of the network in
non-trivial ways. This theory provides new micro-foundations for the Beveridge
curve, wage dispersion, and the employer-size premium. We apply our model to
employer-employee matched records and find that network topologies with
Pareto-distributed connections cause disproportionately large changes on
aggregate unemployment under high labor supply elasticity
3D discrete element modeling of concrete: study of the rolling resistance effects on the macroscopic constitutive behavior
The Discrete Element Method (DEM) is appropriate for modeling granular materials [14] but also cohesive materials as concrete when submitted to a severe loading such an impact leading to fractures or fragmentation in the continuum [1, 5, 6, 8]. Contrarily to granular materials, the macroscopic constitutive behavior of a cohesive material is not directly linked to contact interactions between the rigid Discrete Elements (DE) and interaction laws are then defined between DE surrounding each DE. Spherical DE are used because the contact detection is easy to implement and the computation time is reduced in comparison with the use of 3D DE with a more complex shape. The element size is variable and the assembly is disordered to prevent preferential cleavage planes. The purpose of this paper is to highlight the influence of DE rotations on the macroscopic non-linear quasi-static behavior of concrete. Classically, the interactions between DE are modeled by spring-like interactions based on displacements and rotation velocities of DE are only controlled by tangential forces perpendicular to the line linking the two sphere centroids. The disadvantage of this modeling with only spring-like interactions based on displacements is that excessive rolling occurs under shear, therefore the macroscopic behavior of concrete is too brittle. To overcome this problem a non linear Moment Transfer Law (MTL) is introduced to add a rolling resistance to elements. This solution has no influence on the calculation cost and allows a more accurate macroscopic representation of concrete behavior. The identification process of material parameters is given and simulations of tests performed on concrete samples are shown
Quantum Walk on a Line with Two Entangled Particles
We introduce the concept of a quantum walk with two particles and study it
for the case of a discrete time walk on a line. A quantum walk with more than
one particle may contain entanglement, thus offering a resource unavailable in
the classical scenario and which can present interesting advantages. In this
work, we show how the entanglement and the relative phase between the states
describing the coin degree of freedom of each particle will influence the
evolution of the quantum walk. In particular, the probability to find at least
one particle in a certain position after steps of the walk, as well as the
average distance between the two particles, can be larger or smaller than the
case of two unentangled particles, depending on the initial conditions we
choose. This resource can then be tuned according to our needs, in particular
to enhance a given application (algorithmic or other) based on a quantum walk.
Experimental implementations are briefly discussed
Renormalization group flows and fixed points for a scalar field in curved space with nonminimal coupling
Using covariant methods, we construct and explore the Wetterich equation for
a non-minimal coupling of a quantized scalar field to the Ricci
scalar of a prescribed curved space. This includes the often considered
non-minimal coupling as a special case. We consider the
truncations without and with scale- and field-dependent wave function
renormalization in dimensions between four and two. Thereby the main emphasis
is on analytic and numerical solutions of the fixed point equations and the
behavior in the vicinity of the corresponding fixed points. We determine the
non-minimal coupling in the symmetric and spontaneously broken phases with
vanishing and non-vanishing average fields, respectively. Using functional
perturbative renormalization group methods, we discuss the leading universal
contributions to the RG flow below the upper critical dimension .Comment: 17 pages, 4 figure
Renormalization group flows and fixed points for a scalar field in curved space with nonminimal coupling
Using covariant methods, we construct and explore the Wetterich equation for
a non-minimal coupling of a quantized scalar field to the Ricci
scalar of a prescribed curved space. This includes the often considered
non-minimal coupling as a special case. We consider the
truncations without and with scale- and field-dependent wave function
renormalization in dimensions between four and two. Thereby the main emphasis
is on analytic and numerical solutions of the fixed point equations and the
behavior in the vicinity of the corresponding fixed points. We determine the
non-minimal coupling in the symmetric and spontaneously broken phases with
vanishing and non-vanishing average fields, respectively. Using functional
perturbative renormalization group methods, we discuss the leading universal
contributions to the RG flow below the upper critical dimension .Comment: 17 pages, 4 figure
Testing the long-run implications of the expectation hypothesis using cointegration techniques with structural change
This paper investigates whether or not multivariate cointegrated process with structural change can describe the Brazilian term structure of interest rate data from 1995 to 2006. In this work the break point and the number of cointegrated vector are assumed to be known. The estimated model has four regimes. Only three of them are statistically different. The first starts at the beginning of the sample and goes until September of 1997. The second starts at October of 1997 until December of 1998. The third starts at January of 1999 and goes until the end of the sample. It is used monthly data. Models that allows for some similarities across the regimes are also estimated and tested. The models are estimated using the Generalized Reduced-Rank Regressions developed by Hansen (2003). All imposed restrictions can be tested using likelihood ratio test with standard asymptotic qui-squared distribution. The results of the paper show evidence in favor of the long run implications of the expectation hypothesis for Brazil.Term structure, cointegration, structural change
Changes in endotoxin levels in T2DM subjects on anti-diabetic therapies
Introduction
Chronic low-grade inflammation is a significant factor in the development of obesity associated diabetes. This is supported by recent studies suggesting endotoxin, derived from gut flora, may be key to the development of inflammation by stimulating the secretion of an adverse cytokine profile from adipose tissue.
Aims
The study investigated the relationship between endotoxin and various metabolic parameters of diabetic patients to determine if anti-diabetic therapies exerted a significant effect on endotoxin levels and adipocytokine profiles.
Methods
Fasting blood samples were collected from consenting Saudi Arabian patients (BMI: 30.2 ± (SD)5.6 kg/m2, n = 413), consisting of non-diabetics (ND: n = 67) and T2DM subjects (n = 346). The diabetics were divided into 5 subgroups based on their 1 year treatment regimes: diet-controlled (n = 36), metformin (n = 141), rosiglitazone (RSG: n = 22), a combined fixed dose of metformin/rosiglitazone (met/RSG n = 100) and insulin (n = 47). Lipid profiles, fasting plasma glucose, insulin, adiponectin, resistin, TNF-α, leptin, C-reactive protein (CRP) and endotoxin concentrations were determined.
Results
Regression analyses revealed significant correlations between endotoxin levels and triglycerides (R2 = 0.42; p < 0.0001); total cholesterol (R2 = 0.10; p < 0.001), glucose (R2 = 0.076; p < 0.001) and insulin (R2 = 0.032; p < 0.001) in T2DM subjects. Endotoxin showed a strong inverse correlation with HDL-cholesterol (R2 = 0.055; p < 0.001). Further, endotoxin levels were elevated in all of the treated diabetic subgroups compared with ND, with the RSG treated diabetics showing significantly lower endotoxin levels than all of the other treatment groups (ND: 4.2 ± 1.7 EU/ml, RSG: 5.6 ± 2.2 EU/ml). Both the met/RSG and RSG treated groups had significantly higher adiponectin levels than all the other groups, with the RSG group expressing the highest levels overall.
Conclusion
We conclude that sub-clinical inflammation in T2DM may, in part, be mediated by circulating endotoxin. Furthermore, that whilst the endotoxin and adipocytokine profiles of diabetic patients treated with different therapies were comparable, the RSG group demonstrated significant differences in both adiponectin and endotoxin levels. We confirm an association between endotoxin and serum insulin and triglycerides and an inverse relationship with HDL. Lower endotoxin and higher adiponectin in the groups treated with RSG may be related and indicate another mechanism for the effect of RSG on insulin sensitivity
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