Restaurant Prices and the Minimum Wage

We examine the effect of the minimum wage on restaurant prices. We contribute to both the study of economic impact of the minimum wage and to the micro patterns of price stickiness. For that purpose, we use a unique dataset of individual price quotes collected to calculate the Consumer Price Index in France and we estimate a price rigidity model based on a flexible (S; s) rule. We find a positive and significant impact of the minimum wage on prices. The effect of the minimum wage on prices is however very protracted. The aggregate impact estimated with our model takes more than a year to fully pass through to retail prices.price stickiness, minimum wage, inflation, restaurant prices

RESTAURANT PRICES AND THE MINIMUM WAGE

We examine the effect of the minimum wage on restaurant prices. For that purpose, we estimate a price rigidity model by exploiting a unique data set of individual price quotes used to calculate the Consumer Price Index in France. We …find a positive and signifi…cant impact of the minimum wage on prices. We obtain that the effect of the minimum wage on prices is very protracted. The aggregate impact estimated with our model takes more than a year to fully pass through to retail prices.Price stickiness, minimum wage, inflation, restaurant prices, Demand and Price Analysis, Industrial Organization,

Diffusion kurtosis imaging as a biomarker of breast cancer

Diffusion kurtosis imaging (DKI) is a diffusion-weighted imaging method that describes non-Gaussian signal behavior using a relatively simple mathematical model. A parameter, kurtosis K, describes the deviation of the diffusion signal decay from a Gaussian pattern. The deviation reflects the complexity of the tissue microstructure affecting water diffusion. Several studies have investigated the diagnostic performance of DKI in distinguishing malignant from benign breast lesions. DKI has been reported to correlate with subtypes and with several molecular and other factors related to the treatment and prognosis of breast cancer. Some technical considerations remain to be resolved for the clinical application of DKI in the breast

Numerical simulation of diffusion MRI signals using an adaptive time-stepping method

International audienceThe effect on the MRI signal of water diffusion in biological tissues in the presence of applied magnetic field gradient pulses can be modelled by a multiple compartment Bloch-Torrey partial differential equation. We present a method for the numerical solution of this equation by coupling a standard Cartesian spatial discretization with an adaptive time discretization. The time discretization is done using the explicit Runge-Kutta-Chebyshev method, which is more efficient than the forward Euler time discretization for diffusive-type problems. We use this approach to simulate the diffusion MRI signal from the extra-cylindrical compartment in a tissue model of the brain gray matter consisting of cylindrical and spherical cells and illustrate the effect of cell membrane permeability

Analytical and numerical study of the apparent diffusion coefficient in diffusion MRI at long diffusion times and low b-values

Diffusion magnetic resonance imaging provides a measure of the average distance travelled by water molecules in a medium and can give useful information on cellular structure and structural change when the medium is biological tissue. In this paper, two approximate models for the apparent diffusion coefficient at low b-values and long diffusion times are formulated and validated. The first is a steady-state partial differential equation model that gives the steady-state (infinite time) effective diffusion tensor for general cellular geometries. For nearly isotropic diffusion where the intra-cellular compartment consists of non-elongated cells, a second approximate model is provided in the form of analytical formulae for the eigenvalue of the steady-state effective diffusion tensor. Both models are validated by numerical simulations on a variety of cells sizes and shapes

Transient Activity in the Human Calcarine Cortex During Visual-Mental Imagery: An Event-Related fMRI Study

Although it is largely accepted that visual-mental imagery and perception draw on many of the same neural structures, the existence and nature of neural processing in the primary visual cortex (or area V1) during visual imagery remains controversial. We tested two general hypotheses: The first was that V1 is activated only when images with many details are formed and used, and the second was that V1 is activated whenever images are formed, even if they are not necessarily used to perform a task. We used event-related functional magnetic resonance imaging (ER-fMRI) to detect and characterize the activity in the calcarine sulcus (which contains the primary visual cortex) during single instances of mental imagery. The results revealed reproducible transient activity in this area whenever participants generated or evaluated a mental image. This transient activity was strongly enhanced when participants evaluated characteristics of objects, whether or not details actually needed to be extracted from the image to perform the task. These results show that visual imagery processing commonly involves the earliest stages of the visual system.Psycholog

The Brainomics/Localizer database

International audienceThe Brainomics/Localizer database exposes part of the data collected by the in house Localizer project, which planned to acquire four types of data from volunteer research subjects: anatomical MRI scans, functional MRI data, behavioral and demographic data, and DNA sampling. Over the years, this local project has been collecting such data from hundreds of subjects. We had selected 94 of these subjects for their complete datasets, including all four types of data, as the basis for a prior publication; the Brainomics/Localizer database publishes the data associated with these 94 subjects. Since regulatory rules prevent us from making genetic data available for download, the database serves only anatomical MRI scans, functional MRI data, behavioral and demographic data. To publish this set of heterogeneous data, we use dedicated software based on the open-source CubicWeb semantic web framework. Through genericity in the data model and flexibility in the display of data (web pages, CSV, JSON, XML), CubicWeb helps us expose these complex datasets in original and efficient ways

Investigation of breast cancer microstructure and microvasculature from time-dependent DWI and CEST in correlation with histological biomarkers

We investigated the associations of time-dependent DWI, non-Gaussian DWI, and CEST parameters with histological biomarkers in a breast cancer xenograft model. 22 xenograft mice (7 MCF-7 and 15 MDA-MB-231) were scanned at 4 diffusion times [Td = 2.5/5 ms with 11 b-values (0-600 s/mm2) and Td = 9/27.6 ms with 17 b-values (0-3000 s/mm2), respectively]. The apparent diffusion coefficient (ADC) was estimated using 2 b-values in different combinations (ADC0-600 using b = 0 and 600 s/mm2 and shifted ADC [sADC200-1500] using b = 200 and 1500 s/mm2) at each of those diffusion times. Then the change (Δ) in ADC/sADC between diffusion times was evaluated. Non-Gaussian diffusion and intravoxel incoherent motion (IVIM) parameters (ADC0, the virtual ADC at b = 0; K, Kurtosis from non-Gaussian diffusion; f, the IVIM perfusion fraction) were estimated. CEST images were acquired and the amide proton transfer signal intensity (APT SI) were measured. The ΔsADC9-27.6 (between [Formula: see text] and [Formula: see text] and ΔADC2.5_sADC27.6 (between [Formula: see text] and [Formula: see text]) was significantly larger for MCF-7 groups, and ΔADC2.5_sADC27.6 was positively correlated with Ki67max and APT SI. ADC0 decreased significantly in MDA-MB-231 group and K increased significantly with Td in MCF-7 group. APT SI and cellular area had a moderately strong positive correlation in MDA-MB-231 and MCF-7 tumors combined, and there was a positive correlation in MDA-MB-231 tumors. There was a significant negative correlation between APT SI and the Ki-67-positive ratio in MDA-MB-231 tumors and when combined with MCF-7 tumors. The associations of ΔADC2.5_sADC27.6 and API SI with Ki-67 parameters indicate that the Td-dependent DW and CEST parameters are useful to predict the histological markers of breast cancers