Simulations of the Water Food Energy Nexus for policy driven intervention.

Water-Food-Energy (WFE) resources exert mutual influences upon each other and thus cannot be managed separately. Information on household WFE expenditures addresses knowledge that distinguishes between geospatial districts' social welfare. Social welfare and investment in districts' WFE resources are interconnected. District (node) product of WFE normalized expenditures (Volume) is considered as a representative WFE Nexus holistic quantity. This Volume is assumed to be a function of residents' knowledge of welfare level across districts. We prove that the Volume rate conforms to Boltzmann entropy, and this is the premise of our hypothesis for directed information from high to low welfare between network nodes. Welfare mass (WM) represents the district's Volume combined with its income and population density. This WM is used as input into a model balancing between all domain nodes that allows policymakers to simulate the effects of potential quantifiable policy decisions targeted to individual districts at a domain level while also considering influences between districts. Based on existing historic data, the established tool exemplifies its potential by providing outcomes for Israel districts showing the influence of imposing different temporal allocation/deallocation actions as managerial regulations to prescribed districts. It is found that districts with a high WM do not suffer when a defund is applied, but districts that have a low WM gain from subsidies.

A compartmental brain model for chemical transport and CO2 controlled blood flow.

A compartmental transport model is developed, capable of predicting the evolution of CO2, HCO-3 and H+ in the cerebrovascular system. In the model, the transport of these components is simulated at a subset of three compartments: cerebrospinal fluid (CSF), capillary-choroid plexus and brain tissue, belonging to a seven compartmental assembly representing the entire brain. The remaining ones are; artery, vein, venous sinus and jugular bulb. The model accounts for advection associated with non-steady perfusion fluxes across semi-previous boundaries. Pressures, associated with perfusion, are solved in the seven-compartment model. The three-compartment transport model also takes into account changes in compartmental volume due to displacement of its boundaries, diffusion through boundaries and rate of generation of substances by chemical reactions. A first-order reaction rate is assumed in the CSF compartment. A parameter estimation method is then developed to assess boundary diffusivities from time-averaged observed values of perfusion pressure, tension of carbon dioxide, pH values, and concentration of free hydrogen and bicarbonate ions. An equation of state describing the regulation of flow from arteries to capillaries, as a function of CO2 tension in the CSF, is then suggested. Upon solving all coupled mass balance equations, and for a pre-evaluated perfusion pressure in the artery and capillary compartments, one can estimate the change in arteries to capillaries conductance at every time step. Boundary diffusivities between the capillary, cerebrospinal fluid and brain tissue compartments, were estimated. A sensitivity analysis proves the consistency between model predictions and available clinical observations, this, in terms of the influence of the parameter associated with CO2 metabolic rate on CO2 tension. It was shown that decrease of this tension caused an abrupt pressure fall at the first instant which later increased to an asymptotic value. This, however, was not evident in the capillaries at which pressure slightly falls and then remains constant.

Resistances and compliances of a compartmental model of the cerebrovascular system.

A lumped parameter compartmental model for the nonsteady flow of the cerebrovascular fluid is constructed. The model assumes constant resistances that relate fluid flux to pressure gradients, and compliances between compartments that relate fluid accumulation to rate of pressure changes. Resistances are evaluated by using mean values of artery and cerebrospinal fluid (CSF) fluxes and mean compartmental pressures. Compliances are then evaluated from clinical data of simultaneous pulse wave recordings in the different compartments. Estimate of the average CSF compartmental deformation, based on the compliance between the CSF and brain tissue compartments, proves to be of the order of magnitude of actual experimental measurements.

Joint mobilization education and clinical use in the United States.

Joint mobilization in the physical therapy evaluation and treatment of patients with synovial joint dysfunction has come into general use only within the past decade. The purposes of this study were 1) to collect survey data regarding the education of physical therapists in mobilization techniques, 2) to examine quantitative changes in entry-level curricula from 1970 to 1986, and 3) to examine basic and continuing education opportunities and determine whether physical therapists are making use of these opportunities. Using chi-square analysis, significant changes (p less than or equal to .01) were found in the number of entry-level programs offering instruction in joint mobilization techniques and in the interest in initiating or expanding relevant course work. In the survey of practicing physical therapists, the increase in the number of therapists who have had instruction in mobilization techniques was also found to be significant (p less than or equal to .01). These results would seem to indicate that mobilization techniques are becoming more widely used by physical therapists to treat joint dysfunction and that entry-level physical therapy education programs are making an attempt to prepare students by expanding curricula.

A non-steady compartmental flow model of the cerebrovascular system.

A lumped parameter compartmental model for the cerebrovascular fluid system is constructed and solved for the general linear problem of a nonsteady flow with constant resistances and compliances. The model predicts the intracranial pressure waves in the various compartments of the brain in response to pressure changes in the vascular system.