Economies of scale and efficiency measurement in Switzerland's Nursing homes

This paper examines the cost efficiency in the nursing home industry, an issue of concern to Swiss policy makers because of the explosive growth of national expenditure on elderly care and the aging of the population. A stochastic cost frontier model with a translog function has been applied to a balanced panel data of 1780 observations from 356 nursing homes operating over five years (1998-2002) in Switzerland. We compare the estimation results from different panel data econometric techniques focusing on the various methods of specification of unobserved heterogeneity across firms. In particular, the potential effects of such unobserved factors on the estimation results and their interpretation have been discussed. The paper eventually addresses three empirical issues: (1) the measurement of economies of scale in the nursing home sector, (2) the assessment of the economic performance of the firms by estimating their cost efficiency scores, and (3) the role of unobserved heterogeneity in the estimation process. The findings suggest that the economies of scale are an important potential source of cost reduction in a majority of Swiss nursing homes. Taking the size as given the efficiency performance of most individual units is practically very close to the estimated best practice. Nevertheless, the efficiency estimates suggest that some of the nursing homes can significantly reduce their costs by improving their operations.COST EFFICIENCY, ECONOMIES OF SCALE, NURSING HOMES, STOCHASTIC FRONTIER, PANEL DATA

El cos entre néixer, desnéixer i morir a Mercè Rodoreda, Maria-Mercè Marçal i Imma Monsó

This article brings together the first chapter of La plaça del Diamant by Mercè Rodoreda; the poems which deal with the mother figure in Maria-Mercè Marçal’s posthumous collection Raó del cos; and a key part of Imma Monsó’s novel Un home de paraula, in which the narrator’s beloved husband suddenly dies in front of her eyes. The three texts are analyzed through meaningful intertextual connections regarding the representation of the body and the problematic space for the maternal in Western culture. Moreover, they are identified as narratives of mourning in a way that problematizes the Freudian distinction between the supposedly healthy process of mourning and the allegedly pathological process of melancholia

The Transformative Integration of Artificial Intelligence with CMMC and NIST 800-171 For Advanced Risk Management and Compliance

This paper explores the transformative potential of integrating Artificial Intelligence (AI) with established cybersecurity frameworks such as the Cybersecurity Maturity Model Certification (CMMC) and the National Institute of Standards and Technology (NIST) Special Publication 800-171. The thesis argues that the relationship between AI and these frameworks has the capacity to transform risk management in cybersecurity, where it could serve as a critical element in threat mitigation. In addition to addressing AI’s capabilities, this paper acknowledges the risks and limitations of these systems, highlighting the need for extensive research and monitoring when relying on AI. One must understand boundaries when integrating AI into frameworks that ensure the security of sensitive data, otherwise, the ethicality of AI systems is compromised. This paper overviews compliance audits and their intricate relationship with cybersecurity frameworks CMMC and NIST 800-171, underscoring their complementary nature and shared objectives. Finally, the significance of AI in ensuring compliance with these frameworks will be explored, and the transformative potential of AI in automating processes and its advancements in risk management will be discussed

Recordar per oblidar? Trauma i gènere a Elisa Kiseljak (2005), de Lolita Bosch

This article establishes a critical dialogue with the construction of gender and trauma in Lolita Bosch’s novels, especially in Elisa Kiseljak (2005), and frames the analysis within the current debates on trauma

Spatiotemporal adaptive multiscale multiphysics simulations of two-phase flow

We present a spatiotemporal adaptive multiscale algorithm, which is based on the Multiscale Finite Volume method. The algorithm offers a very efficient framework to deal with multiphysics problems and to couple regions with different spatial resolution. We employ the method to simulate two-phase flow through porous media. At the fine scale, we consider a pore-scale description of the flow based on the Volume Of Fluid method. In order to construct a global problem that describes the coarse-scale behavior, the equations are averaged numerically with respect to auxiliary control volumes, and a Darcy-like coarse-scale model is obtained. The space adaptivity is based on the idea that a fine-scale description is only required in the front region, whereas the resolution can be coarsened elsewhere. Temporal adaptivity relies on the fact that the fine-scale and the coarse-scale problems can be solved with different temporal resolution (longer time steps can be used at the coarse scale). By simulating drainage under unstable flow conditions, we show that the method is able to capture the coarse-scale behavior outside the front region and to reproduce complex fluid patterns in the front region

Local and Global Error Models to Improve Uncertainty Quantification

In groundwater applications, Monte Carlo methods are employed to model the uncertainty on geological parameters. However, their brute-force application becomes computationally prohibitive for highly detailed geological descriptions, complex physical processes, and a large number of realizations. The Distance Kernel Method (DKM) overcomes this issue by clustering the realizations in a multidimensional space based on the flow responses obtained by means of an approximate (computationally cheaper) model; then, the uncertainty is estimated from the exact responses that are computed only for one representative realization per cluster (the medoid). Usually, DKM is employed to decrease the size of the sample of realizations that are considered to estimate the uncertainty. We propose to use the information from the approximate responses for uncertainty quantification. The subset of exact solutions provided by DKM is then employed to construct an error model and correct the potential bias of the approximate model. Two error models are devised that both employ the difference between approximate and exact medoid solutions, but differ in the way medoid errors are interpolated to correct the whole set of realizations. The Local Error Model rests upon the clustering defined by DKM and can be seen as a natural way to account for intra-cluster variability; the Global Error Model employs a linear interpolation of all medoid errors regardless of the cluster to which the single realization belongs. These error models are evaluated for an idealized pollution problem in which the uncertainty of the breakthrough curve needs to be estimated. For this numerical test case, we demonstrate that the error models improve the uncertainty quantification provided by the DKM algorithm and are effective in correcting the bias of the estimate computed solely from the MsFV results. The framework presented here is not specific to the methods considered and can be applied to other combinations of approximate models and techniques to select a subset of realization

Local-global splitting for spatiotemporal-adaptive multiscale methods

We present a novel spatiotemporal-adaptive Multiscale Finite Volume (MsFV) method, which is based on the natural idea that the global coarse-scale problem has longer characteristic time than the local fine-scale problems. As a consequence, the global problem can be solved with larger time steps than the local problems. In contrast to the pressure-transport splitting usually employed in the standard MsFV approach, we propose to start directly with a local-global splitting that allows to locally retain the original degree of coupling. This is crucial for highly non-linear systems or in the presence of physical instabilities. To obtain an accurate and efficient algorithm, we devise new adaptive criteria for global update that are based on changes of coarse-scale quantities rather than on fine-scale quantities, as it is routinely done before in the adaptive MsFV method. By means of a complexity analysis we show that the adaptive approach gives a noticeable speed-up with respect to the standard MsFV algorithm. In particular, it is efficient in case of large upscaling factors, which is important for multiphysics problems. Based on the observation that local time stepping acts as a smoother, we devise a self-correcting algorithm which incorporates the information from previous times to improve the quality of the multiscale approximation. We present results of multiphase flow simulations both for Darcy-scale and multiphysics (hybrid) problems, in which a local pore-scale description is combined with a global Darcy-like description. The novel spatiotemporal-adaptive multiscale method based on the local-global splitting is not limited to porous media flow problems, but it can be extended to any system described by a set of conservation equations

Multiscale finite-volume method for density-driven flow in porous media

The multiscale finite-volume (MSFV) method has been developed to solve multiphase flow problems on large and highly heterogeneous domains efficiently. It employs an auxiliary coarse grid, together with its dual, to define and solve a coarse-scale pressure problem. A set of basis functions, which are local solutions on dual cells, is used to interpolate the coarse-grid pressure and obtain an approximate fine-scale pressure distribution. However, if flow takes place in presence of gravity (or capillarity), the basis functions are not good interpolators. To treat this case correctly, a correction function is added to the basis function interpolated pressure. This function, which is similar to a supplementary basis function independent of the coarse-scale pressure, allows for a very accurate fine-scale approximation. In the coarse-scale pressure equation, it appears as an additional source term and can be regarded as a local correction to the coarse-scale operator: It modifies the fluxes across the coarse-cell interfaces defined by the basis functions. Given the closure assumption that localizes the pressure problem in a dual cell, the derivation of the local problem that defines the correction function is exact, and no additional hypothesis is needed. Therefore, as in the original MSFV method, the only closure approximation is the localization assumption. The numerical experiments performed for density-driven flow problems (counter-current flow and lock exchange) demonstrate excellent agreement between the MSFV solutions and the corresponding fine-scale reference solution

In vivo quantitative lipidic map of brown adipose tissue by chemical shift imaging at 4.7 tesla

In the present paper, chemical shift imaging techniques are applied to quantitative in vivo evaluation of fat and water content in interscapular brown adipose tissue (BAT). The experiments have been carried out on five female Sprague-Dawley rats after calibration and testing with suitable phantoms containing known amounts of water and oil. We found that, in the interscapular BAT, the fat is about 50% at the surface (mainly unilocular) region, but its percentage drops to 20–30% in the deepest (mainly multilocular) portion. The perirenal deposits of white adipose tissue (WAT) contained significantly higher amount of fat with large areas ranging from 70 to 90%. Later the rats were killed and the same procedure was repeated with dead animals. Experiments performed in dead rats show a modification of the hydro-lipidic ratio more evident in the multilocular portions of the deposit. The present work demonstrates that MRI-based methods allow a non-invasive, in vivo quantitative mapping of the lipid content which can be applied to investigation of brown adipose tissue deposits in small experiment animals.—Lunati, E., P. Marzola, E. Nicolato, M. Fedrigo, M. Villa, and A. Sbarbati. In vivo quantitative lipidic map of brown adipose tissue by chemical shift imaging at 4.7 tesla. J. Lipid Res. 1999. 40: 1395–1400