Labor markets and monetary policy: A new-Keynesian model with unemployement

We construct a utility-based model of fluctuations, with nominal rigidities andunemployment, and draw its implications for the unemployment-inflation trade-off and for the conduct of monetary policy.We proceed in two steps. We first leave nominal rigidities aside. We show that,under a standard utility specification, productivity shocks have no effect onunemployment in the constrained efficient allocation. We then focus on theimplications of alternative real wage setting mechanisms for fluctuations in un-employment. We show the role of labor market frictions and real wage rigiditiesin determining the effects of productivity shocks on unemployment.We then introduce nominal rigidities in the form of staggered price setting byfirms. We derive the relation between inflation and unemployment and discusshow it is influenced by the presence of labor market frictions and real wagerigidities. We show the nature of the tradeoff between inflation and unemployment stabilization, and its dependence on labor market characteristics. We draw the implications for optimal monetary policy.

Hybrid consumption paths in the attribute space: A model and application with scanner data

This paper presents and estimates a dynamic choice model in the attribute space considering rational consumers. In light of the evidence of several state-dependence patterns, the standard attribute-based model is extended by considering a general utility function where pure inertia and pure variety-seeking behaviors can be explained in the model as particular linear cases. The dynamics of the model are fully characterized by standard dynamic programming techniques. The model presents a stationary consumption pattern that can be inertial, where the consumer only buys one product, or a variety-seeking one, where the consumer shifts among varied products.We run some simulations to analyze the consumption paths out of the steady state. Underthe hybrid utility assumption, the consumer behaves inertially among the unfamiliar brandsfor several periods, eventually switching to a variety-seeking behavior when the stationary levels are approached. An empirical analysis is run using scanner databases for three different product categories: fabric softener, saltine cracker, and catsup. Non-linear specifications provide the best fit of the data, as hybrid functional forms are found in all the product categories for most attributes and segments. These results reveal the statistical superiority of the non-linear structure and confirm the gradual trend to seek variety as the level of familiarity with the purchased items increases.

A BPE model for the Burgers' equation

We study the BPE (Brownian particle equation) model of the Burgers equationpresented in the preceeding article [6]. More precisely, we are interestedin establishing the existence and uniqueness properties of solutions usingprobabilistic techniques.

Elevated serum uric acid is associated with high circulating inflammatory cytokines in the population-based Colaus study.

BACKGROUND: The relation of serum uric acid (SUA) with systemic inflammation has been little explored in humans and results have been inconsistent. We analyzed the association between SUA and circulating levels of interleukin-6 (IL-6), interleukin-1beta (IL-1beta), tumor necrosis factor- alpha (TNF-alpha) and C-reactive protein (CRP). METHODS AND FINDINGS: This cross-sectional population-based study conducted in Lausanne, Switzerland, included 6085 participants aged 35 to 75 years. SUA was measured using uricase-PAP method. Plasma TNF-alpha, IL-1beta and IL-6 were measured by a multiplexed particle-based flow cytometric assay and hs-CRP by an immunometric assay. The median levels of SUA, IL-6, TNF-alpha, CRP and IL-1beta were 355 micromol/L, 1.46 pg/mL, 3.04 pg/mL, 1.2 mg/L and 0.34 pg/mL in men and 262 micromol/L, 1.21 pg/mL, 2.74 pg/mL, 1.3 mg/L and 0.45 pg/mL in women, respectively. SUA correlated positively with IL-6, TNF-alpha and CRP and negatively with IL-1beta (Spearman r: 0.04, 0.07, 0.20 and 0.05 in men, and 0.09, 0.13, 0.30 and 0.07 in women, respectively, P<0.05). In multivariable analyses, SUA was associated positively with CRP (beta coefficient +/- SE = 0.35+/-0.02, P<0.001), TNF-alpha (0.08+/-0.02, P<0.001) and IL-6 (0.10+/-0.03, P<0.001), and negatively with IL-1beta (-0.07+/-0.03, P = 0.027). Upon further adjustment for body mass index, these associations were substantially attenuated. CONCLUSIONS: SUA was associated positively with IL-6, CRP and TNF-alpha and negatively with IL-1beta, particularly in women. These results suggest that uric acid contributes to systemic inflammation in humans and are in line with experimental data showing that uric acid triggers sterile inflammation.

Particle agglomeration study in rf silane plasmas: In situ study by polarization-sensitive laser light scattering

To determine self‐consistently the time evolution of particle size and their number density in situ multi‐angle polarization‐sensitive laser light scattering was used. Cross‐polarization intensities (incident and scattered light intensities with opposite polarization) measured at 135° and ex situ transmission electronic microscopy analysis demonstrate the existence of nonspherical agglomerates during the early phase of agglomeration. Later in the particle time development both techniques reveal spherical particles again. The presence of strong cross‐polarization intensities is accompanied by low‐frequency instabilities detected on the scattered light intensities and plasma emission. It is found that the particle radius and particle number density during the agglomeration phase can be well described by the Brownian free molecule coagulation model. Application of this neutral particle coagulation model is justified by calculation of the particle charge whereby it is shown that particles of a few tens of nanometer can be considered as neutral under our experimental conditions. The measured particle dispersion can be well described by a Brownian free molecule coagulation model including a log‐normal particle size distribution.

APPRAISAL OF THE SNAP MODEL FOR PREDICTING NITROGEN MINERALIZATION IN TROPICAL SOILS UNDER EUCALYPTUS

The Soil Nitrogen Availability Predictor (SNAP) model predicts daily and annual rates of net N mineralization (NNM) based on daily weather measurements, daily predictions of soil water and soil temperature, and on temperature and moisture modifiers obtained during aerobic incubation (basal rate). The model was based on in situ measurements of NNM in Australian soils under temperate climate. The purpose of this study was to assess this model for use in tropical soils under eucalyptus plantations in São Paulo State, Brazil. Based on field incubations for one month in three, NNM rates were measured at 11 sites (0-20 cm layer) for 21 months. The basal rate was determined in in situ incubations during moist and warm periods (January to March). Annual rates of 150-350 kg ha-1 yr-1 NNM predicted by the SNAP model were reasonably accurate (R2 = 0.84). In other periods, at lower moisture and temperature, NNM rates were overestimated. Therefore, if used carefully, the model can provide adequate predictions of annual NNM and may be useful in practical applications. For NNM predictions for shorter periods than a year or under suboptimal incubation conditions, the temperature and moisture modifiers need to be recalibrated for tropical conditions.

Expression, purification, and structural insights for the human uric acid transporter, GLUT9, using the Xenopus laevis oocytes system.

The urate transporter, GLUT9, is responsible for the basolateral transport of urate in the proximal tubule of human kidneys and in the placenta, playing a central role in uric acid homeostasis. GLUT9 shares the least homology with other members of the glucose transporter family, especially with the glucose transporting members GLUT1-4 and is the only member of the GLUT family to transport urate. The recently published high-resolution structure of XylE, a bacterial D-xylose transporting homologue, yields new insights into the structural foundation of this GLUT family of proteins. While this represents a huge milestone, it is unclear if human GLUT9 can benefit from this advancement through subsequent structural based targeting and mutagenesis. Little progress has been made toward understanding the mechanism of GLUT9 since its discovery in 2000. Before work can begin on resolving the mechanisms of urate transport we must determine methods to express, purify and analyze hGLUT9 using a model system adept in expressing human membrane proteins. Here, we describe the surface expression, purification and isolation of monomeric protein, and functional analysis of recombinant hGLUT9 using the Xenopus laevis oocyte system. In addition, we generated a new homology-based high-resolution model of hGLUT9 from the XylE crystal structure and utilized our purified protein to generate a low-resolution single particle reconstruction. Interestingly, we demonstrate that the functional protein extracted from the Xenopus system fits well with the homology-based model allowing us to generate the predicted urate-binding pocket and pave a path for subsequent mutagenesis and structure-function studies.

A model of cellular dosimetry for macroscopic tumors in radiopharmaceutical therapy.

PURPOSE: In the radiopharmaceutical therapy approach to the fight against cancer, in particular when it comes to translating laboratory results to the clinical setting, modeling has served as an invaluable tool for guidance and for understanding the processes operating at the cellular level and how these relate to macroscopic observables. Tumor control probability (TCP) is the dosimetric end point quantity of choice which relates to experimental and clinical data: it requires knowledge of individual cellular absorbed doses since it depends on the assessment of the treatment's ability to kill each and every cell. Macroscopic tumors, seen in both clinical and experimental studies, contain too many cells to be modeled individually in Monte Carlo simulation; yet, in particular for low ratios of decays to cells, a cell-based model that does not smooth away statistical considerations associated with low activity is a necessity. The authors present here an adaptation of the simple sphere-based model from which cellular level dosimetry for macroscopic tumors and their end point quantities, such as TCP, may be extrapolated more reliably. METHODS: Ten homogenous spheres representing tumors of different sizes were constructed in GEANT4. The radionuclide 131I was randomly allowed to decay for each model size and for seven different ratios of number of decays to number of cells, N(r): 1000, 500, 200, 100, 50, 20, and 10 decays per cell. The deposited energy was collected in radial bins and divided by the bin mass to obtain the average bin absorbed dose. To simulate a cellular model, the number of cells present in each bin was calculated and an absorbed dose attributed to each cell equal to the bin average absorbed dose with a randomly determined adjustment based on a Gaussian probability distribution with a width equal to the statistical uncertainty consistent with the ratio of decays to cells, i.e., equal to Nr-1/2. From dose volume histograms the surviving fraction of cells, equivalent uniform dose (EUD), and TCP for the different scenarios were calculated. Comparably sized spherical models containing individual spherical cells (15 microm diameter) in hexagonal lattices were constructed, and Monte Carlo simulations were executed for all the same previous scenarios. The dosimetric quantities were calculated and compared to the adjusted simple sphere model results. The model was then applied to the Bortezomib-induced enzyme-targeted radiotherapy (BETR) strategy of targeting Epstein-Barr virus (EBV)-expressing cancers. RESULTS: The TCP values were comparable to within 2% between the adjusted simple sphere and full cellular models. Additionally, models were generated for a nonuniform distribution of activity, and results were compared between the adjusted spherical and cellular models with similar comparability. The TCP values from the experimental macroscopic tumor results were consistent with the experimental observations for BETR-treated 1 g EBV-expressing lymphoma tumors in mice. CONCLUSIONS: The adjusted spherical model presented here provides more accurate TCP values than simple spheres, on par with full cellular Monte Carlo simulations while maintaining the simplicity of the simple sphere model. This model provides a basis for complementing and understanding laboratory and clinical results pertaining to radiopharmaceutical therapy.

An Experimental Validation of a Statistical-Based Damage Detection Approach, January 2011

In this work, a previously-developed, statistical-based, damage-detection approach was validated for its ability to autonomously detect damage in bridges. The damage-detection approach uses statistical differences in the actual and predicted behavior of the bridge caused under a subset of ambient trucks. The predicted behavior is derived from a statistics-based model trained with field data from the undamaged bridge (not a finite element model). The differences between actual and predicted responses, called residuals, are then used to construct control charts, which compare undamaged and damaged structure data. Validation of the damage-detection approach was achieved by using sacrificial specimens that were mounted to the bridge and exposed to ambient traffic loads and which simulated actual damage-sensitive locations. Different damage types and levels were introduced to the sacrificial specimens to study the sensitivity and applicability. The damage-detection algorithm was able to identify damage, but it also had a high false-positive rate. An evaluation of the sub-components of the damage-detection methodology and methods was completed for the purpose of improving the approach. Several of the underlying assumptions within the algorithm were being violated, which was the source of the false-positives. Furthermore, the lack of an automatic evaluation process was thought to potentially be an impediment to widespread use. Recommendations for the improvement of the methodology were developed and preliminarily evaluated. These recommendations are believed to improve the efficacy of the damage-detection approach.

Spatial behavior in groups: an agent-based approach

We present an agent-based model with the aim of studying how macro-level dynamics of spatial distances among interacting individuals in a closed space emerge from micro-level dyadic and local interactions. Our agents moved on a lattice (referred to as a room) using a model implemented in a computer program called P-Space in order to minimize their dissatisfaction, defined as a function of the discrepancy between the real distance and the ideal, or desired, distance between agents. Ideal distances evolved in accordance with the agent's personal and social space, which changed throughout the dynamics of the interactions among the agents. In the first set of simulations we studied the effects of the parameters of the function that generated ideal distances, and in a second set we explored how group macrolevel behavior depended on model parameters and other variables. We learned that certain parameter values yielded consistent patterns in the agents' personal and social spaces, which in turn led to avoidance and approaching behaviors in the agents. We also found that the spatial behavior of the group of agents as a whole was influenced by the values of the model parameters, as well as by other variables such as the number of agents. Our work demonstrates that the bottom-up approach is a useful way of explaining macro-level spatial behavior. The proposed model is also shown to be a powerful tool for simulating the spatial behavior of groups of interacting individuals.

ABCtoolbox: a versatile toolkit for approximate Bayesian computations.

BACKGROUND: The estimation of demographic parameters from genetic data often requires the computation of likelihoods. However, the likelihood function is computationally intractable for many realistic evolutionary models, and the use of Bayesian inference has therefore been limited to very simple models. The situation changed recently with the advent of Approximate Bayesian Computation (ABC) algorithms allowing one to obtain parameter posterior distributions based on simulations not requiring likelihood computations. RESULTS: Here we present ABCtoolbox, a series of open source programs to perform Approximate Bayesian Computations (ABC). It implements various ABC algorithms including rejection sampling, MCMC without likelihood, a Particle-based sampler and ABC-GLM. ABCtoolbox is bundled with, but not limited to, a program that allows parameter inference in a population genetics context and the simultaneous use of different types of markers with different ploidy levels. In addition, ABCtoolbox can also interact with most simulation and summary statistics computation programs. The usability of the ABCtoolbox is demonstrated by inferring the evolutionary history of two evolutionary lineages of Microtus arvalis. Using nuclear microsatellites and mitochondrial sequence data in the same estimation procedure enabled us to infer sex-specific population sizes and migration rates and to find that males show smaller population sizes but much higher levels of migration than females. CONCLUSION: ABCtoolbox allows a user to perform all the necessary steps of a full ABC analysis, from parameter sampling from prior distributions, data simulations, computation of summary statistics, estimation of posterior distributions, model choice, validation of the estimation procedure, and visualization of the results.

Levels and determinants of inflammatory biomarkers in a Swiss population-based sample (CoLaus Study).

OBJECTIVE: to assess the levels and determinants of interleukin (IL)-1ß, IL-6, tumour necrosis factor (TNF)-a and C-reactive protein (CRP) in a healthy Caucasian population.METHODS: population sample of 2884 men and 3201 women aged 35 to 75. IL-1ß, IL-6 and TNF-a were assessed by a multiplexed particle-based flow cytometric assay and CRP by an immunometric assay.RESULTS: Spearman rank correlations between duplicate cytokine measurements (N?=?80) ranged between 0.89 and 0.96; intra-class correlation coefficients ranged between 0.94 and 0.97, indicating good reproducibility. Among the 6085 participants, 2289 (37.6%), 451 (7.4%) and 43 (0.7%) had IL-1ß, IL-6 and TNF-a levels below detection limits, respectively. Median (interquartile range) for participants with detectable values were 1.17 (0.48-3.90) pg/ml for IL-1ß; 1.47 (0.71-3.53) pg/ml for IL-6; 2.89 (1.82-4.53) pg/ml for TNF-a and 1.3 (0.6-2.7) ng/ml for CRP. On multivariate analysis, greater age was the only factor inversely associated with IL-1ß levels. Male sex, increased BMI and smoking were associated with greater IL-6 levels, while no relationship was found for age and leisure-time PA. Male sex, greater age, increased BMI and current smoking were associated with greater TNF-a levels, while no relationship was found with leisure-time PA. CRP levels were positively related to age, BMI and smoking, and inversely to male sex and physical activity.CONCLUSION: Population-based levels of several cytokines were established. Increased age and BMI, and to a lesser degree sex and smoking, significantly and differentially impact cytokine levels, while leisure-time physical activity has little effect.

Association of statins with inflammatory cytokines: a population-based Colaus study.

PURPOSE: A pleiotropic effect of statins has been reported in numerous studies. However, the association between statin use and inflammatory cytokines is controversial. We examined the associations between statin use and C-reactive protein (CRP), tumour necrosis factor α (TNF-α), interleukin-1β (IL-1β) and interleukin-6 (IL-6) in a healthy Caucasian population. METHODS: Cross-sectional study of 6184 participants aged 35-75years from Lausanne, Switzerland. Cytokines were assessed by multiplexed particle-based flow cytometric assay. Self-reported history of medication was collected for statins and other medication. 99 participants without cytokine data were excluded. RESULTS: Among the 6085 participants, 2289 (37.6%), 451 (7.4%) and 43 (0.7%) had IL-1β, IL-6 and TNF-α levels below detection limits, respectively. On multivariate analysis adjusting for age, gender, smoking status, body mass index, hypertension, diabetes, baseline cardiovascular disease, total cholesterol, anti-inflammatory use, other cytokine modifying drugs and other drugs, participants on statins had significantly lower CRP levels (adjusted mean±standard error: 1.22±1.05 vs. 1.38±1.04mg/L for use and non-use, respectively, p<0.01 on log-transformed data). Conversely, no association was found between statin use and IL-1β (p=0.91), IL-6 (p=0.25) or TNF-α (p=0.28) levels. On multivariate analysis, individuals in the statin group (β coefficient=-0.12; 95% CI=-0.21, -0.03) had lower levels of CRP as compared to those in the reference group (i.e. those not using statin). However, no significant associations were observed between IL-1β, IL-6 and TNF-α and statins. CONCLUSION: Individuals on statins have lower CRP levels; conversely, no effect was found for IL-1β, IL-6 and TNF-α levels.

Cytokines and hs-CRP levels in individuals treated with low-dose aspirin for cardiovascular prevention: a population-based study (CoLaus Study).

Pro-inflammatory cytokines and high-sensitive C-reactive protein (hs-CRP) are associated with increased risk for cardiovascular disease. Low-dose aspirin for CV prevention is reported to have anti-inflammatory effects. The aim of this study was to determine the association between pro-inflammatory cytokines and hs-CRP levels and low-dose aspirin use for cardiovascular prevention in a population-based cohort (CoLaus Study). We assessed blood samples in 6085 participants (3201 women) aged 35-75years. Medications' use and indications were recorded. Among aspirin users (n=1'034; 17%), overall low-dose users (351; 5.8%) and low-dose for cardiovascular prevention users (324; 5.3%) were selected for analysis. Pro-inflammatory cytokines (IL-1β, IL-6 and TNF-α were assessed by a multiplex particle-based flow cytometric assay and hs-CRP by an immunometric assay. Cytokines and hs-CRP were presented in quartiles. Multivariate analysis adjusting for sex, age, smoking status, body mass index, diabetes mellitus and immunomodulatory drugs showed no association between cytokines and hs-CRP levels and low-dose aspirin use for cardiovascular prevention, either comparing the topmost vs. the three other quartiles (OR 95% CI, 0.84 (0.59-1.18), 1.03 (0.78-1.32), 1.10 (0.83-1.46), 1.00 (0.67-1.69) for IL-1β, IL-6, TNF-α and hs-CRP, respectively), or comparing the topmost quartile vs. the first one (OR 95% CI, 0.87 (0.60-1.26), 1.19 (0.79-1.79), 1.26 (0.86-1.84), 1.06 (0.67-1.69)). Low-dose aspirin use for cardiovascular prevention does not impact plasma pro-inflammatory cytokine and hs-CRP levels in a population-based cohort.

Development of a Subgrade Drainage Model for Unpaved Roads, TR-654, 2015

With over 68 thousand miles of gravel roads in Iowa and the importance of these roads within the farm-to-market transportation system, proper water management becomes critical for maintaining the integrity of the roadway materials. However, the build-up of water within the aggregate subbase can lead to frost boils and ultimately potholes forming at the road surface. The aggregate subbase and subgrade soils under these gravel roads are produced with material opportunistically chosen from local sources near the site and, many times, the compositions of these sublayers are far from ideal in terms of proper water drainage with the full effects of this shortcut not being fully understood. The primary objective of this project was to provide a physically-based model for evaluating the drainability of potential subbase and subgrade materials for gravel roads in Iowa. The Richards equation provided the appropriate framework to study the transient unsaturated flow that usually occurs through the subbase and subgrade of a gravel road. From which, we identified that the saturated hydraulic conductivity, Ks, was a key parameter driving the time to drain of subgrade soils found in Iowa, thus being a good proxy variable for accessing roadway drainability. Using Ks, derived from soil texture, we were able to identify potential problem areas in terms of roadway drainage . It was found that there is a threshold for Ks of 15 cm/day that determines if the roadway will drain efficiently, based on the requirement that the time to drain, Td, the surface roadway layer does not exceed a 2-hr limit. Two of the three highest abundant textures (loam and silty clay loam), which cover nearly 60% of the state of Iowa, were found to have average Td values greater than the 2-hr limit. With such a large percentage of the state at risk for the formation of boils due to the soil with relatively low saturated hydraulic conductivity values, it seems pertinent that we propose alternative design and/or maintenance practices to limit the expensive repair work in Iowa. The addition of drain tiles or French mattresses my help address drainage problems. However, before pursuing this recommendation, a comprehensive cost-benefit analysis is needed.