Certificate of Discharge - Howe, Asa C.

Certificate of Discharge for Asa C. Howe of Lovell, Mainehttps://digitalmaine.com/aroostook_war_discharges/1018/thumbnail.jp

Certificate of Discharge - Kilgore, Moses Jr.

Certificate of Discharge for Moses Kilgore Jr. of Lovell, Mainehttps://digitalmaine.com/aroostook_war_discharges/1008/thumbnail.jp

Certificate of Discharge - Ewins, John

Certificate of Discharge for John Ewins of Paris, Mainehttps://digitalmaine.com/aroostook_war_discharges/1016/thumbnail.jp

Certificate of Discharge - Kilgore, Moses

Certificate of Discharge for Moses Kilgore of Lovell, Mainehttps://digitalmaine.com/aroostook_war_discharges/1000/thumbnail.jp

Hybrid logistic and confined exponential growth models : estimation using SEM software

The logistic and confined exponential curves represent growth over time in various contexts such as learning and technology transfer. Logistic growth operates as a contagion process in a population of interest, while the confined exponential curve represents the diffusion of an external process on a system, such as the transfer of information through communication channels. Prior work (e.g., Grimm and Ram, 2009) has shown that such nonlinear curves can be estimated using structural equation modeling (SEM) software, allowing model comparison. As an alternative to binary choice between such models, this paper shows how a hybrid model representing a weighted combination of the two models may be specified. In order to assess whether the hybrid model can be successfully estimated using SEM software and conditions under which it can be successfully differentiated from the stand-alone logistic and confined exponential alternatives, Monte Carlo simulations varying the number of measurement occasions (5, 10, and 15), internal consistency ([alpha] = .5, .7, and .8), and sample size (N = 1,000, 500, and 300) were conducted. Convergence failures appeared appreciable only when the estimated hybrid models were the special cases of logistic or confined exponential curves. The hybrid model was successfully preferred over the stand-alone models when 10 or 15 measurement occasions are employed and when internal consistency is moderate ([alpha] = .7 or .8) across all sample sizes but not when only five measurement occasions are used or when internal consistency is low ([alpha] = .5). Implications for the application of the hybrid model to learning, growth, and psychopathology are discussed.by Kyle R. RipleyIncludes bibliographical reference

Dynamic quantum clustering: a method for visual exploration of structures in data

A given set of data-points in some feature space may be associated with a Schrodinger equation whose potential is determined by the data. This is known to lead to good clustering solutions. Here we extend this approach into a full-fledged dynamical scheme using a time-dependent Schrodinger equation. Moreover, we approximate this Hamiltonian formalism by a truncated calculation within a set of Gaussian wave functions (coherent states) centered around the original points. This allows for analytic evaluation of the time evolution of all such states, opening up the possibility of exploration of relationships among data-points through observation of varying dynamical-distances among points and convergence of points into clusters. This formalism may be further supplemented by preprocessing, such as dimensional reduction through singular value decomposition or feature filtering.Comment: 15 pages, 9 figure

Agricultural development in the north Kimberley : terms, conditions and farm size recommendations

There are approximately 1,250,000 hectares of land in this area of Kimberley which may be sown to pastures such as Townsville Stylo, other Stylosanthes species or to other introduced pastures. The report recommends that grazing properties comprising 10,000 ha. of land capable of growing improved pastures, together with 60,000 ha. of native pasture land, should be established in the area. The economic size of the farm unit is 5,300 adult cattle equivalents

Power and the Production of Science. Assessing Cod Stocks as the Mechanistic Fishery Collapses

This paper discusses power relations in the production of knowledge claims and the validation of management strategies. The experience of doing stock assessment science and creating management plans for Canada’s east coast cod fishery illustrates this general process. We demonstrate that the cyborgization of fisheries-management is limited by its inability to produce power for stabilizing the relations between managers, fishers, technology and fish. Lack of stability forces scientists and managers either to ignore a threat or to intervene by changing their strategy. Consensus is unlikely. Scientists and managers must reconsider reasons for action or lack of it, thus producing a new rationality. Managers attempt to control that reconstruction process in the interests of resolving shortterm challenges. Some scientists resist change and protect their earlier positions against new evidence or re-interpretations. The winning rationality has more to do with the power of the claimant than with the quality of reasoning

Visit of working party on North Kimberley Agricultural Development to the area in July 1977

Report suggests that the area of land suitable for Townsville Stylo in the North Kimberley above the 750 mm rainfall isohyet is about 1.25 million hectares. The regions in which land suitable for Stylosanthes can be found are shown. A brief description of the suitability of the land systems of the region for Stylosanthes is given

Likelihood informed dimension reduction for inverse problems in remote sensing of atmospheric constituent profiles

We use likelihood informed dimension reduction (LIS) (T. Cui et al. 2014) for inverting vertical profile information of atmospheric methane from ground based Fourier transform infrared (FTIR) measurements at Sodankyl\"a, Northern Finland. The measurements belong to the word wide TCCON network for greenhouse gas measurements and, in addition to providing accurate greenhouse gas measurements, they are important for validating satellite observations. LIS allows construction of an efficient Markov chain Monte Carlo sampling algorithm that explores only a reduced dimensional space but still produces a good approximation of the original full dimensional Bayesian posterior distribution. This in effect makes the statistical estimation problem independent of the discretization of the inverse problem. In addition, we compare LIS to a dimension reduction method based on prior covariance matrix truncation used earlier (S. Tukiainen et al. 2016)