8,098 research outputs found
Well design as a factor contributing to loss of water from the Floridan Aquifer, eastern Clay County, Florida
A number of wells penetrating the Floridan aquifer in eastern
Clay County were found to be losing water to permeable zones above
this aquifer. A differential in artesian pressure was observed in closely
spaced wells of similar depth. Further investigation. revealed that
the pressure differential in the wells was due to the design of the
wells, of which there were four principal types.
A comparison of the four types of wells in relation to the subsurface
geology showed that three types of wells were open to the permeable
zones above the Floridan aquifer. In such wells water of relatively
high head from the Floridan aquifer moves up through the well bore
and out into zones of relatively low head.
The estimated water loss from poorly designed wells ranged
from 32 to 180 gpm (gallons per minute). The artesian head loss in
leaky wells ranged from 3 to 15 feet. A total loss of water of 39 mgd
(million gallons per day) was estimated from all the leaky wells in
the area.
A significant decline of the piezometric surface of the Floridan
aquifer was observed in eastern Clay County. Some of this decline can
be attributed to the loss of water from the Floridan aquifer through
these poorly designed wells. (Document has 16 pages.
Freedom, Opportunity and Wellbeing
This paper reexamines key results from the measurement of opportunity freedom, or the extent to which a set of options offers a decision maker real opportunities to achieve. Three cases are investigated: no preferences, a single preference, and plural preferences. The three co the cardinality relation, the indirect utility relation, and the effective freedom relation variations are considered within a common axiomatic framework. Special attention is given to representations of freedom rankings, with the goal of providing practical approaches for measuring opportunity freedom and the extent of capabilities.
A Report on Mexican Multidimensional Poverty Measurement
This report addresses the challenges arising from a change in Mexico’s official poverty methodology from an income-only basis to a multidimensional basis that includes education, access to health services, access to social security, shelter characteristics, access to basic services, access to food, and level of social cohesion. The concept of poverty underlying this report is drawn from Amartya Sen’s capability approach. The specific multidimensional measurement framework used is that of Alkire and Foster (2007). Special emphasis is placed on the measure’s population decomposability and dimensional decomposability. The new identification and aggregation methods are then applied to 2005 data provided by CONEVAL to illustrate the feasibility of the methodology and the kinds of results that one might obtain.
Keynesian Policies Stimulate Dabate And Debt, Not Employment
Antizyklische Finanzpolitik; Keynesianismus; Wirtschaftspolitische Wirkungsanalyse
Treebank Embedding Vectors for Out-of-domain Dependency Parsing
A recent advance in monolingual dependency parsing is the idea of a treebank
embedding vector, which allows all treebanks for a particular language to be
used as training data while at the same time allowing the model to prefer
training data from one treebank over others and to select the preferred
treebank at test time. We build on this idea by 1) introducing a method to
predict a treebank vector for sentences that do not come from a treebank used
in training, and 2) exploring what happens when we move away from predefined
treebank embedding vectors during test time and instead devise tailored
interpolations. We show that 1) there are interpolated vectors that are
superior to the predefined ones, and 2) treebank vectors can be predicted with
sufficient accuracy, for nine out of ten test languages, to match the
performance of an oracle approach that knows the most suitable predefined
treebank embedding for the test set.Comment: Camera ready for ACL 202
An optimal polynomial approximation of Brownian motion
In this paper, we will present a strong (or pathwise) approximation of
standard Brownian motion by a class of orthogonal polynomials. The coefficients
that are obtained from the expansion of Brownian motion in this polynomial
basis are independent Gaussian random variables. Therefore it is practical
(requires independent Gaussian coefficients) to generate an approximate
sample path of Brownian motion that respects integration of polynomials with
degree less than . Moreover, since these orthogonal polynomials appear
naturally as eigenfunctions of an integral operator defined by the Brownian
bridge covariance function, the proposed approximation is optimal in a certain
weighted sense. In addition, discretizing Brownian paths as
piecewise parabolas gives a locally higher order numerical method for
stochastic differential equations (SDEs) when compared to the standard
piecewise linear approach. We shall demonstrate these ideas by simulating
Inhomogeneous Geometric Brownian Motion (IGBM). This numerical example will
also illustrate the deficiencies of the piecewise parabola approximation when
compared to a new version of the asymptotically efficient log-ODE (or
Castell-Gaines) method.Comment: 27 pages, 8 figure
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