Static Safety for an Actor Dedicated Process Calculus by Abstract Interpretation

The actor model eases the definition of concurrent programs with non uniform behaviors. Static analysis of such a model was previously done in a data-flow oriented way, with type systems. This approach was based on constraint set resolution and was not able to deal with precise properties for communications of behaviors. We present here a new approach, control-flow oriented, based on the abstract interpretation framework, able to deal with communication of behaviors. Within our new analyses, we are able to verify most of the previous properties we observed as well as new ones, principally based on occurrence counting

AMR, stability and higher accuracy

Efforts to achieve better accuracy in numerical relativity have so far focused either on implementing second order accurate adaptive mesh refinement or on defining higher order accurate differences and update schemes. Here, we argue for the combination, that is a higher order accurate adaptive scheme. This combines the power that adaptive gridding techniques provide to resolve fine scales (in addition to a more efficient use of resources) together with the higher accuracy furnished by higher order schemes when the solution is adequately resolved. To define a convenient higher order adaptive mesh refinement scheme, we discuss a few different modifications of the standard, second order accurate approach of Berger and Oliger. Applying each of these methods to a simple model problem, we find these options have unstable modes. However, a novel approach to dealing with the grid boundaries introduced by the adaptivity appears stable and quite promising for the use of high order operators within an adaptive framework

Impact of Cognitive Impairment on Functional Outcome in Stroke

The aim of this study was to investigate the effect of the cognitive impairment on functional status in patients with subacute stroke. Fifty-two patients with subacute stroke were included in the study. Mini mental state examination (MMSE) test was used for the evaluation of cognitive status. Patients were separated into two groups according to their cognitive functions. Functional follow-up parameters were activities of daily living (ADL), global recovery and ambulation status. All patients were evaluated on admission to rehabilitation unit, at discharge and 6 months after discharge. Forty-four patients were completed the study. Mean age was 66 and 57 years; disease duration on admission was 4,8 and 3,5 months in the cognitively impaired and normal groups, respectively. Significant improvement was found in terms of functional follow-up parameters in both groups at discharge (P < .05). Functional follow-up parameters did not show statistically significant difference between the groups. But community ambulation rate was higher in cognitively normal group at the sixth month visit. As a result of this study, inpatient rehabilitation was effective both cognitively normal and impaired subacute stroke patients

A Simple Correction Term to Model Infiltration in Water-Repellent Soils

Soil water repellency can substantially alter hydrologic processes, particularly the ability of soils to infiltrate water. Water repellency often changes through time, making it difficult to simulate infiltration behaviors of water-repellent soils using standard models. Here, we propose a simple rate-based correction term that starts with a value of zero at the beginning of the infiltration process (t&nbsp;=&nbsp;0) and asymptotically approaches 1 as time increases, thus simulating decreasing soil water repellency through time. The correction term can be used with any infiltration model. For this study, we selected a simple two-term infiltration equation and then, using two data sets of infiltration measurements conducted in soils with varying water repellency, compared model error with versus without the added term. The correction substantially reduced model error, particularly in more repellent soils. At the same time, the rate constant parameter introduced in the new model may be useful to better understand dynamics of soil water repellency and to provide more consistent interpretations of hydraulic properties in water-repellent soils

Modeling water infiltration into soil under fractional wettability conditions

The heterogeneous distribution of water-repellent materials at the soil surface causes a phenomenon known as fractional wettability. This condition frequently triggers destabilization of the wetting front during water infiltration, resulting in the formation of fingered bypass flow. However, few analytical tools exist to understand and model this behavior. Moreover, existing infiltration models fail to fit certain infiltration curves that exist in experimental data. For these reasons, we introduce a novel infiltration model to simulate water infiltration under fractional wettable conditions. We conceptualize the soil surface as a composite of two distinct portions: a water-repellent fraction, where hydrophobic effects impede water infiltration, and a wettable fraction, where capillarity and gravity are the dominant forces controlling the process. The new model was validated using a dataset comprising infiltration data from 60 field measurements. Additionally, validation was performed using 660 analytically generated infiltration curves from six synthetic soils with varying textures. This innovative approach enabled us to account for the combined influence of these two fractions and to enhance the interpretation of infiltration curves with mixed shapes, which other common methods are unable to reproduce