Charity care and community benefits by hospital type in Texas

Hospital care is the largest component of the health care sector. This industry is made up of for profit hospital (FPH) organizations, not for profit (NFP) hospitals, and government (GOV) run hospital facilities. Objectives of this analysis were: (a) to conduct a literature review on NFP hospital legislation at the state level in Texas and at the federal level in the broader U.S.; and (b) to describe the types of charity care and community benefits currently being provided: by NFP hospitals compared to FPH hospitals and GOV hospitals; by hospitals geographic proximity to the Texas-Mexico border; and by hospital community type (rural, suburban, and urban); and (c) propose specific policy changes that may be needed to improve the current Texas State statute. Methods. In describing the historical and current policy context of NFP hospital legislation in the United States, federal legislation was reviewed from 1913 to the present and Texas State legislation was reviewed from 1980 to the present. In describing the provision of charity care, data from the 2008 Annual Cooperative Hospital Survey were examined by hospital organizational type, size, proximity to the border, and community type using linear regression and chi-squared tests to assess differences in charity care and community benefits. Results. The data included 123 NFP hospitals, 114 GOV hospitals, and 123 FPH. Results. Small sized (p<0.001) and medium sized (p<0.001) NFP hospitals provide a greater percent of total charity care when compared to FPH hospitals and to both GOV and FPH hospitals respectively; however, no significant difference in total charity care was found among large sized NFP hospitals when compared to FPH hospitals alone (p=.345) and both GOV and FPH facilities (p=.214). The amount of charity care provided was not found to be different based on proximity to the border or community type. Community benefit planning and budgeting was found to be similar regardless of community type and proximity to the border. Conclusion. No differences in charity care in Texas were found for large sized NFP hospitals compared to FPH and GOV hospitals. Contrary to widely held beliefs, this study did not find the border region to provide a greater amount of charity care or bad debt. Charity care also did not vary by community type. These findings underscore the need for continued collection of transparent data from all hospitals in order to provide policy makers and consumers with information on utilization trends to ensure benefits are being provided to the community. Policy changes or revoking tax-benefits may occur as charity care utilization declines with the implementation of health reform in the next few years.^

La Cordillera de los Andes : de muro a portal : visiones del otro a través del espacio

Nos hemos planteado los cambios de percepción de un accidente geográfico, como la cadena montañosa de los Andes, desde la Colonia hasta nuestros días, como un modo de comprender mejor nuestras maneras de ver el mundo. En efecto, la relación con el espacio avala universalmente la particularidad de las identidades, tal como ha sido estudiado por la antropología, entre otras disciplinas que se han ocupado de la problemática entre identidad y espacio. Nos interesa concentrarnos en las significaciones que le ha sido asignado al macizo andino en ciertas etapas, en uno y otro lado del mismo. La significación de muro que se le atribuye a la cordillera constituye una de las varias que existen y circulan en los textos literarios y no literarios. La relevancia que tiene ese punto de vista –el muro- se puede apreciar mejor en el campo de las relaciones internacionales entre ambos países. Sin embargo, existen otras relaciones espacio-representación que han alentado procesos integracionistas.

At surface behaviour data of juvenile southern elephant seals from Marion Island between 2001 and 2006 with links to datasets

Marine mammals forage in dynamic environments characterized by variables that are continuously changing in relation to large-scale oceanographic processes. In the present study, behavioural states of satellite-tagged juvenile southern elephant seals (n = 16) from Marion Island were assessed for each reliable location, using variation in turning angle and speed in a state-space modelling framework. A mixed modelling approach was used to analyse the behavioural response of juvenile southern elephant seals to sea-surface temperature and proximity to frontal and bathymetric features. The findings emphasised the importance of frontal features as potentially rewarding areas for foraging juvenile southern elephant seals and provided further evidence of the importance of the area west of Marion Island for higher trophic-level predators. The importance of bathymetric features during the transit phase of juvenile southern elephant seal migrations indicates the use of these features as possible navigational cues.

Updated bathymetric chart of the East Aral Sea

The Aral Sea is located in an arid region with much sand and salt deposits in the surrounding barren open land. Hence, significant displacements of sediments into the lakebed by the action of wind, water, gravity, or snow are likely. The bathymetry of the lake was last observed in the 1960s, and within the last half century, the structure of the lakebed has changed. Based on satellite observations of the temporal changes of shoreline (Landsat optical remote sensing) and water level (multi-mission satellite altimetry) over more than one decade an updated bathymetric chart for the East Basin of the Aral Sea has been generated. During this time, the geometry of the shallow East Basin experienced strong fluctuations due to the occurrence of periods of drying and strong inflow. By the year 2014 the East Basin fell dry. The dynamic behavior of the basin allowed for estimating the lake's bathymetry from a series of satellite-based information. The river mouth made its impression in the present East Aral Sea, because its shrinking led to the inflow of much sediment into the lake's interior. In addition, salt deposits along the shorelines increased the corresponding elevation, a phenomenon that is more pronounced in the reduced lakebed because of increased salinity. It must be noted that height estimates from satellite altimetry were only possible down to a minimum elevation of 27 m above sea level due to a lack of reliable altimetry data over the largely reduced water surface. In order to construct a complete bathymetric chart of the lakebed of the East Aral Sea heights below 27 m were obtained solely from Landsat optical images following the SRB (Selected Region Boundary) approach as described by Singh et al. (2015).

Forecasting Electricity Prices and their volatilities using Unobserved Components.

The liberalization of electricity markets more than ten years ago in the vast majority of developed countries has introduced the need of modelling and forecasting electricity prices and volatilities, both in the short and long term. Thus, there is a need of providing methodology that is able to deal with the most important features of electricity price series, which are well known for presenting not only structure in conditional mean but also time-varying conditional variances. In this work we propose a new model, which allows to extract conditionally heteroskedastic common factors from the vector of electricity prices. These common factors are jointly estimated as well as their relationship with the original vector of series, and the dynamics affecting both their conditional mean and variance. The estimation of the model is carried out under the state-space formulation. The new model proposed is applied to extract seasonal common dynamic factors as well as common volatility factors for electricity prices and the estimation results are used to forecast electricity prices and their volatilities in the Spanish zone of the Iberian Market. Several simplified/alternative models are also considered as benchmarks to illustrate that the proposed approach is superior to all of them in terms of explanatory and predictive power.

PWM Control of a Buck Converter with an Amorphous Core Coil

Pulse-width modulation is widely used to control electronic converters. One of the most topologies used for high DC voltage/low DC voltage conversion is the Buck converter. It is obtained as a second order system with a LC filter between the switching subsystem and the load. The use of a coil with an amorphous magnetic material core instead of air core lets design converters with smaller size. If high switching frequencies are used for obtaining high quality voltage output, the value of the auto inductance L is reduced throughout the time. Then, robust controllers are needed if the accuracy of the converter response must not be affected by auto inductance and load variations. This paper presents a robust controller for a Buck converter based on a state space feedback control system combined with an additional virtual space variable which minimizes the effects of the inductance and load variations when a not-toohigh switching frequency is applied. The system exhibits a null steady-state average error response for the entire range of parameter variations. Simulation results are presented.

Consciousness, Action Selection, Meaning and Phenomenic Anticipation

Phenomenal states are generally considered the ultimate sources of intrinsic motivation for autonomous biological agents. In this article, we will address the issue of the necessity of exploiting these states for the design and implementation of robust goal-directed artificial systems. We will provide an analysis of consciousness in terms of a precise definition of how an agent "understands" the informational flows entering the agent and its very own action possibilities. This abstract model of consciousness and understanding will be based in the analysis and evaluation of phenomenal states along potential future trajectories in the state space of the agents. This implies that a potential strategy to follow in order to build autonomous but still customer-useful systems is to embed them with the particular, ad hoc phenomenality that captures the system-external requirements that define the system usefulness from a customer-based, requirements-strict engineering viewpoint.

An approach to operational modal analysis using the expectation maximization algorithm

This paper presents the Expectation Maximization algorithm (EM) applied to operational modal analysis of structures. The EM algorithm is a general-purpose method for maximum likelihood estimation (MLE) that in this work is used to estimate state space models. As it is well known, the MLE enjoys some optimal properties from a statistical point of view, which make it very attractive in practice. However, the EM algorithm has two main drawbacks: its slow convergence and the dependence of the solution on the initial values used. This paper proposes two different strategies to choose initial values for the EM algorithm when used for operational modal analysis: to begin with the parameters estimated by Stochastic Subspace Identification method (SSI) and to start using random points. The effectiveness of the proposed identification method has been evaluated through numerical simulation and measured vibration data in the context of a benchmark problem. Modal parameters (natural frequencies, damping ratios and mode shapes) of the benchmark structure have been estimated using SSI and the EM algorithm. On the whole, the results show that the application of the EM algorithm starting from the solution given by SSI is very useful to identify the vibration modes of a structure, discarding the spurious modes that appear in high order models and discovering other hidden modes. Similar results are obtained using random starting values, although this strategy allows us to analyze the solution of several starting points what overcome the dependence on the initial values used.

Operational modal analisys using joint statistical analysis of multiple records

In Operational Modal Analysis (OMA) of a structure, the data acquisition process may be repeated many times. In these cases, the analyst has several similar records for the modal analysis of the structure that have been obtained at di�erent time instants (multiple records). The solution obtained varies from one record to another, sometimes considerably. The differences are due to several reasons: statistical errors of estimation, changes in the external forces (unmeasured forces) that modify the output spectra, appearance of spurious modes, etc. Combining the results of the di�erent individual analysis is not straightforward. To solve the problem, we propose to make the joint estimation of the parameters using all the records. This can be done in a very simple way using state space models and computing the estimates by maximum-likelihood. The method provides a single result for the modal parameters that combines optimally all the records.

A unified framework for linear function approximation of value functions in stochastic control

This paper contributes with a unified formulation that merges previ- ous analysis on the prediction of the performance ( value function ) of certain sequence of actions ( policy ) when an agent operates a Markov decision process with large state-space. When the states are represented by features and the value function is linearly approxi- mated, our analysis reveals a new relationship between two common cost functions used to obtain the optimal approximation. In addition, this analysis allows us to propose an efficient adaptive algorithm that provides an unbiased linear estimate. The performance of the pro- posed algorithm is illustrated by simulation, showing competitive results when compared with the state-of-the-art solutions.

Joint statistical analysis of multiple measurement setups for the estimation of vibrational modes

Computing the modal parameters of large structures in Operational Modal Analysis often requires to process data from multiple non simultaneously recorded setups of sensors. These setups share some sensors in common, the so-called reference sensors that are fixed for all the measurements, while the other sensors are moved from one setup to the next. One possibility is to process the setups separately what result in different modal parameter estimates for each setup. Then the reference sensors are used to merge or glue the different parts of the mode shapes to obtain global modes, while the natural frequencies and damping ratios are usually averaged. In this paper we present a state space model that can be used to process all setups at once so the global mode shapes are obtained automatically and subsequently only a value for the natural frequency and damping ratio of each mode is computed. We also present how this model can be estimated using maximum likelihood and the Expectation Maximization algorithm. We apply this technique to real data measured at a footbridge.

Teaching and evaluating mechanical vibrations with Matlab®

The study of the response of mechanical systems to external excitations, even in the simplest cases, involves solving second-order ordinary differential equations or systems thereof. Finding the natural frequencies of a system and understanding the effect of variations of the excitation frequencies on the response of the system are essential when designing mechanisms [1] and structures [2]. However, faced with the mathematical complexity of the problem, students tend to focus on the mathematical resolution rather than on the interpretation of the results. To overcome this difficulty, once the general theoretical problem and its solution through the state space [3] have been presented, Matlab®[4] and Simulink®[5] are used to simulate specific situations. Without them, the discussion of the effect of slight variations in input variables on the outcome of the model becomes burdensome due to the excessive calculation time required. Conversely, with the help of those simulation tools, students can easily reach practical conclusions and their evaluation can be based on their interpretation of results and not on their mathematical skills

Modelos para el análisis dinámico y la predicción a corto plazo de los precios de la electricidad en mercados liberalizados

En esta tesis se va a describir y aplicar de forma novedosa la técnica del alisado exponencial multivariante a la predicción a corto plazo, a un día vista, de los precios horarios de la electricidad, un problema que se está estudiando intensivamente en la literatura estadística y económica reciente. Se van a demostrar ciertas propiedades interesantes del alisado exponencial multivariante que permiten reducir el número de parámetros para caracterizar la serie temporal y que al mismo tiempo permiten realizar un análisis dinámico factorial de la serie de precios horarios de la electricidad. En particular, este proceso multivariante de elevada dimensión se estimará descomponiéndolo en un número reducido de procesos univariantes independientes de alisado exponencial caracterizado cada uno por un solo parámetro de suavizado que variará entre cero (proceso de ruido blanco) y uno (paseo aleatorio). Para ello, se utilizará la formulación en el espacio de los estados para la estimación del modelo, ya que ello permite conectar esa secuencia de modelos univariantes más eficientes con el modelo multivariante. De manera novedosa, las relaciones entre los dos modelos se obtienen a partir de un simple tratamiento algebraico sin requerir la aplicación del filtro de Kalman. De este modo, se podrán analizar y poner al descubierto las razones últimas de la dinámica de precios de la electricidad. Por otra parte, la vertiente práctica de esta metodología se pondrá de manifiesto con su aplicación práctica a ciertos mercados eléctricos spot, tales como Omel, Powernext y Nord Pool. En los citados mercados se caracterizará la evolución de los precios horarios y se establecerán sus predicciones comparándolas con las de otras técnicas de predicción. ABSTRACT This thesis describes and applies the multivariate exponential smoothing technique to the day-ahead forecast of the hourly prices of electricity in a whole new way. This problem is being studied intensively in recent statistics and economics literature. It will start by demonstrating some interesting properties of the multivariate exponential smoothing that reduce drastically the number of parameters to characterize the time series and that at the same time allow a dynamic factor analysis of the hourly prices of electricity series. In particular this very complex multivariate process of dimension 24 will be estimated by decomposing a very reduced number of univariate independent of exponentially smoothing processes each characterized by a single smoothing parameter that varies between zero (white noise process) and one (random walk). To this end, the formulation is used in the state space model for the estimation, since this connects the sequence of efficient univariate models to the multivariate model. Through a novel way, relations between the two models are obtained from a simple algebraic treatment without applying the Kalman filter. Thus, we will analyze and expose the ultimate reasons for the dynamics of the electricity price. Moreover, the practical aspect of this methodology will be shown by applying this new technique to certain electricity spot markets such as Omel, Powernext and Nord Pool. In those markets the behavior of prices will be characterized, their predictions will be formulated and the results will be compared with those of other forecasting techniques.

Monte Carlo limit cycle characterization

The fixed point implementation of IIR digital filters usually leads to the appearance of zero-input limit cycles, which degrade the performance of the system. In this paper, we develop an efficient Monte Carlo algorithm to detect and characterize limit cycles in fixed-point IIR digital filters. The proposed approach considers filters formulated in the state space and is valid for any fixed point representation and quantization function. Numerical simulations on several high-order filters, where an exhaustive search is unfeasible, show the effectiveness of the proposed approach.

Comment: Is memristor a dynamic element?

The authors present a charge/flux formulation of the equations of memristive circuits, which seemingly show that the memristor should not be considered as a dynamic circuit element. Here, is shown that this approach implicitly reduces the dynamic analysis to a certain subset of the state space in such a way that the dynamic contribution of memristors is hidden. This reduction might entail a substantial loss of information, regarding e.g. the local stability properties of the circuit. Two examples illustrate this. It is concluded that the memristor, even with its unconventional features, must be considered as a dynamic element.