A Monetarist Model of Equity Valuation.

Prior to 1945, few academic articles had been addressed to the area of equity valuation models. Since that time, with the advances of analytic economics and in particular the theory of interest rates, several formal equity valuation models have been developed. Several of the models myopically concentrated on microeconomic variables resulting in their inability to discern cyclical shifts in aggregate equity value indices. This shortcoming has been rectified by economists who have tended toward the reemerging monetarist school of thought. The result has been the construction of models designed to examine the movement of aggregate equity share price indices with regard to aggregate macroeconomic variables. A basic distinguishing characteristic of the monetarist school of thought is its emphasis on the effects of changes in the nominal money supply on the aggregate level of economic activity. A key variable through which these changes transmit their effects is the interest rate. The early monetarists viewed interest rates as the equilibrating mechanism between the demand for capital goods and the supply of loanable funds. From the times when Bohm-Bawerk and Wicksell wrote, the interest rate has been used, by those using the loanable funds theory, as the equilibrating mechanism between the money supply and the cost of debt. With the advent of the writings of Milton Friedman, economists began to seriously consider alternative forms of wealth as being affected by changes in the money supply and interest rate. Among the alternative forms, and the one with which this paper will deal, was equities. It is the intent of this research effort to link relevant macroeconomic aggregates to an equity share price index through a model based on monetarist thinking and specifically a loanable funds type theory of interest rates. Of primary importance will be the demonstration of the money supply\u27s effect upon an aggregate equity share index

Some considerations of oxygen utilization rates in Puget Sound

Concentrationa of dissolved oxygen in tributary basins of the fjord-like Puget Sound region (Washington) have been determined during monthly surveys of water characteristics. By selecting periods when a consideration of conaervative properties suggests that the effects of advection and diffusion are small, the local rates of change in oxygen concentration have been determined; it is assumed that these rates approximate the utilization or consumption rates...

Textural variations in MORB sulfide droplets due to differences in crystallization history

Sulfide droplets from fresh Mid-Ocean-Ridge Basalt (MORB) glasses show different textures. Some are fine-grained droplets consist of Monosulfide Solid Solution (Mss) and Intermediate Solid Solution (Iss) micrometric intergrowths with pentlandite at the Mss-Iss interface and disseminated Fe-oxide grains; other droplets display a characteristic “zoned” texture consisting of segregated massive grains of Mss and Iss, with euhedral Fe-oxides and pentlandite occuring as equant grains and as flame-shaped domains in the Mss formed by exsolutions. The difference in the textures implies a difference in the crystallization history of the sulfide droplets. These different textures are observed in droplets that are only millimeters apart in the same sample, and thus had an identical cooling history. Therefore, some other factors controlled the textural development. There is relationship between the size and the texture of the droplets. The larger sulfide droplets tend to have zoned textures and the smaller ones fine-grained textures. We propose that the latter have experienced greater undercooling before crystallization. The reason for the delay in crystallization could be that, in the small sulfide droplets, large stable grains with low surface to volume ratio cannot form, which results in higher effective solubility of the Mss. Due to the high degree of undercooling in the small droplets, there were numerous nucleation sites and the diffusion rates of the crystal components in the liquid were lower, leading to fine-grained Mss-Iss intergrowths. In contrast, larger droplets with lower effective solubility of Mss began to crystallize at higher temperature, and thus had fewer nucleation sites, higher diffusion rates, and more time for sulfide differentiation

Use of population pharmacokinetic‐pharmacodynamic modelling to inform antimalarial dose optimization in infants

Infants bear a significant malaria burden but are usually excluded from participating in early dose optimization studies that inform dosing regimens of antimalarial therapy. Unlike older children, infants' exclusion from early‐phase trials has resulted in limited evidence to guide accurate dosing of antimalarial treatment for uncomplicated malaria or malaria‐preventive treatment in this vulnerable population. Subsequently, doses used in infants are often extrapolated from older children or adults, with the potential for under‐ or overdosing. Population pharmacokinetic‐pharmacodynamic (PK‐PD) modelling, a quantitative methodology that applies mathematical and statistical techniques, can aid the design of clinical studies in infants that collect sparse pharmacokinetic data as well as support the analysis of such data to derive optimized antimalarial dosing in this complex and at‐risk yet understudied subpopulation. In this review, we reflect on what PK‐PD modelling can do in programmatic settings of most malaria‐endemic areas and how it can be used to inform antimalarial dose optimization for preventive and curative treatment of uncomplicated malaria in infants. We outline key developmental physiological changes that affect drug exposure in early life, the challenges of conducting dose optimization studies in infants, and examples of how PK‐PD modelling has previously informed antimalarial dose optimization in this subgroup. Additionally, we discuss the limitations and gaps of PK‐PD modelling when used for dose optimization in infants. To utilize modelling well, there is a need to generate useful, sparse, PK and PD data in this subpopulation to inform antimalarial optimal dosing in infancy

Vibrational-Resonance Enhancement of Positron Annihilation in Molecules

A first study of positron annihilation as a function of positron energy was performed. The rate of annihilation of low-energy positrons in molecular gases was discussed. It was shown that the large observed values of annihilation rates are due to the excitation of long-lived vibrational resonances of the positron-molecule complex. The results are consistent with a theoretical model of resonant annihilation

Sodium-Bearing Waste Treatment Alternatives Implementation Study

The purpose of this document is to discuss issues related to the implementation of each of the five down-selected INEEL/INTEC radioactive liquid waste (sodium-bearing waste - SBW) treatment alternatives and summarize information in three main areas of concern: process/technical, environmental permitting, and schedule. Major implementation options for each treatment alternative are also identified and briefly discussed. This report may touch upon, but purposely does not address in detail, issues that are programmatic in nature. Examples of these include how the SBW will be classified with respect to the Nuclear Waste Policy Act (NWPA), status of Waste Isolation Pilot Plant (WIPP) permits and waste storage availability, available funding for implementation, stakeholder issues, and State of Idaho Settlement Agreement milestones. It is assumed in this report that the SBW would be classified as a transuranic (TRU) waste suitable for disposal at WIPP, located in New Mexico, after appropriate treatment to meet transportation requirements and waste acceptance criteria (WAC)

Estimation of functional connectivity from electromagnetic signals and the amount of empirical data required

An increasing number of neuroimaging studies are concerned with the identification of interactions or statistical dependencies between brain areas. Dependencies between the activities of different brain regions can be quantified with functional connectivity measures such as the cross-correlation coefficient. An important factor limiting the accuracy of such measures is the amount of empirical data available. For event-related protocols, the amount of data also affects the temporal resolution of the analysis. We use analytical expressions to calculate the amount of empirical data needed to establish whether a certain level of dependency is significant when the time series are autocorrelated, as is the case for biological signals. These analytical results are then contrasted with estimates from simulations based on real data recorded with magnetoencephalography during a resting-state paradigm and during the presentation of visual stimuli. Results indicate that, for broadband signals, 50–100 s of data is required to detect a true underlying cross-correlations coefficient of 0.05. This corresponds to a resolution of a few hundred milliseconds for typical event-related recordings. The required time window increases for narrow band signals as frequency decreases. For instance, approximately 3 times as much data is necessary for signals in the alpha band. Important implications can be derived for the design and interpretation of experiments to characterize weak interactions, which are potentially important for brain processing

Agent Based Models and Opinion Dynamics as Markov Chains

This paper introduces a Markov chain approach that allows a rigorous analysis of agent based opinion dynamics as well as other related agent based models (ABM). By viewing the ABM dynamics as a micro description of the process, we show how the corresponding macro description is obtained by a projection construction. Then, well known conditions for lumpability make it possible to establish the cases where the macro model is still Markov. In this case we obtain a complete picture of the dynamics including the transient stage, the most interesting phase in applications. For such a purpose a crucial role is played by the type of probability distribution used to implement the stochastic part of the model which defines the updating rule and governs the dynamics. In addition, we show how restrictions in communication leading to the co-existence of different opinions follow from the emergence of new absorbing states. We describe our analysis in detail with some specific models of opinion dynamics. Generalizations concerning different opinion representations as well as opinion models with other interaction mechanisms are also discussed. We find that our method may be an attractive alternative to mean-field approaches and that this approach provides new perspectives on the modeling of opinion exchange dynamics, and more generally of other ABM.Comment: 26 pages, 12 figure

From single cells to tissues: interactions between the matrix and human breast cells in real time.

International audienceMammary gland morphogenesis involves ductal elongation, branching, and budding. All of these processes are mediated by stroma--epithelium interactions. Biomechanical factors, such as matrix stiffness, have been established as important factors in these interactions. For example, epithelial cells fail to form normal acinar structures in vitro in 3D gels that exceed the stiffness of a normal mammary gland. Additionally, heterogeneity in the spatial distribution of acini and ducts within individual collagen gels suggests that local organization of the matrix may guide morphogenesis. Here, we quantified the effects of both bulk material stiffness and local collagen fiber arrangement on epithelial morphogenesis. The formation of ducts and acini from single cells and the reorganization of the collagen fiber network were quantified using time-lapse confocal microscopy. MCF10A cells organized the surrounding collagen fibers during the first twelve hours after seeding. Collagen fiber density and alignment relative to the epithelial surface significantly increased within the first twelve hours and were a major influence in the shaping of the mammary epithelium. The addition of Matrigel to the collagen fiber network impaired cell-mediated reorganization of the matrix and increased the probability of spheroidal acini rather than branching ducts. The mechanical anisotropy created by regions of highly aligned collagen fibers facilitated elongation and branching, which was significantly correlated with fiber organization. In contrast, changes in bulk stiffness were not a strong predictor of this epithelial morphology. Localized regions of collagen fiber alignment are required for ductal elongation and branching suggesting the importance of local mechanical anisotropy in mammary epithelial morphogenesis. Similar principles may govern the morphology of branching and budding in other tissues and organs