Alien Registration- Broad, George W. (Mars Hill, Aroostook County)

https://digitalmaine.com/alien_docs/34125/thumbnail.jp

Efficient Training and Implementation of Gaussian Process Potentials

Molecular simulations are a powerful tool for translating information about the intermolecular interactions within a system to thermophysical properties via statistical mechanics. However, the accuracy of any simulation is limited by the potentials that model the microscopic interactions. Most first principles methods are too computationally expensive for use at every time-step or cycle of a simulation, which require typically thousands of energy evaluations. Meanwhile, cheaper semi-empirical potentials give rise to only qualitatively accurate simulations. Consequently, methods for efficient first principles predictions in simulations are of interest. Machine-learned potentials (MLPs) have shown promise in this area, offering first principles predictions at a fraction of the cost of ab initio calculation. Of particular interest are Gaussian process (GP) potentials, which achieve equivalent accuracy to other MLPs with smaller training sets. They therefore offer the best route to employing information from expensive ab initio calculations, for which building a large data set is time-consuming. GP potentials, however, are among the most computationally intensive MLPs. Thus, they are far more costly to employ in simulations than semi-empirical potentials. This work addresses the computational expense of GP potentials by both reducing the training set size at a given accuracy and developing a method to invoke GP potentials efficiently for first principles prediction in simulations. By varying the cross-over distance between the GP and a long-range function with the accuracy of the former, training by sequential design requires up to 40 % fewer training points at fixed accuracy. This method was applied successfully to the CO-Ne, HF-Ne, HF-Na+, CO2-Ne, 2CO, 2HF and 2HCl systems, and can be extended easily to other interactions and methods of prediction. Meanwhile, a significant reduction in the time taken for Monte Carlo displacement and volume change moves is achieved by parallelisation of the requisite GP calculations. Though this exploits in part the framework of GP regression, the distribution of the calculations themselves is general to other methods of prediction. The work also shows that current kernels and input transforms for modelling intermolecular interactions are not improved easily

Efficient Training and Implementation of Gaussian Process Potentials

Molecular simulations are a powerful tool for translating information about the intermolecular interactions within a system to thermophysical properties via statistical mechanics. However, the accuracy of any simulation is limited by the potentials that model the microscopic interactions. Most first principles methods are too computationally expensive for use at every time-step or cycle of a simulation, which require typically thousands of energy evaluations. Meanwhile, cheaper semi-empirical potentials give rise to only qualitatively accurate simulations. Consequently, methods for efficient first principles predictions in simulations are of interest. Machine-learned potentials (MLPs) have shown promise in this area, offering first principles predictions at a fraction of the cost of ab initio calculation. Of particular interest are Gaussian process (GP) potentials, which achieve equivalent accuracy to other MLPs with smaller training sets. They therefore offer the best route to employing information from expensive ab initio calculations, for which building a large data set is time-consuming. GP potentials, however, are among the most computationally intensive MLPs. Thus, they are far more costly to employ in simulations than semi-empirical potentials. This work addresses the computational expense of GP potentials by both reducing the training set size at a given accuracy and developing a method to invoke GP potentials efficiently for first principles prediction in simulations. By varying the cross-over distance between the GP and a long-range function with the accuracy of the former, training by sequential design requires up to 40 % fewer training points at fixed accuracy. This method was applied successfully to the CO-Ne, HF-Ne, HF-Na+, CO2-Ne, 2CO, 2HF and 2HCl systems, and can be extended easily to other interactions and methods of prediction. Meanwhile, a significant reduction in the time taken for Monte Carlo displacement and volume change moves is achieved by parallelisation of the requisite GP calculations. Though this exploits in part the framework of GP regression, the distribution of the calculations themselves is general to other methods of prediction. The work also shows that current kernels and input transforms for modelling intermolecular interactions are not improved easily

Representation of a complex Green function on a real basis: I. General Theory

When the Hamiltonian of a system is represented by a finite matrix, constructed from a discrete basis, the matrix representation of the resolvent covers only one branch. We show how all branches can be specified by the phase of a complex unit of time. This permits the Hamiltonian matrix to be constructed on a real basis; the only duty of the basis is to span the dynamical region of space, without regard for the particular asymptotic boundary conditions that pertain to the problem of interest.Comment: about 40 pages with 5 eps-figure

Pichia stipitis genomics, transcriptomics, and gene clusters

Genome sequencing and subsequent global gene expression studies have advanced our understanding of the lignocellulose-fermenting yeast Pichia stipitis. These studies have provided an insight into its central carbon metabolism, and analysis of its genome has revealed numerous functional gene clusters and tandem repeats. Specialized physiological traits are often the result of several gene products acting together. When coinheritance is necessary for the overall physiological function, recombination and selection favor colocation of these genes in a cluster. These are particularly evident in strongly conserved and idiomatic traits. In some cases, the functional clusters consist of multiple gene families. Phylogenetic analyses of the members in each family show that once formed, functional clusters undergo duplication and differentiation. Genome-wide expression analysis reveals that regulatory patterns of clusters are similar after they have duplicated and that the expression profiles evolve along with functional differentiation of the clusters. Orthologous gene families appear to arise through tandem gene duplication, followed by differentiation in the regulatory and coding regions of the gene. Genome-wide expression analysis combined with cross-species comparisons of functional gene clusters should reveal many more aspects of eukaryotic physiology

Influence of Electrification Pathways in the Electricity Sector of Ethiopia—Policy Implications Linking Spatial Electrification Analysis and Medium to Long-Term Energy Planning

Ethiopia is a low-income country, with low electricity access (45%) and an inefficient power transmission network. The government aims to achieve universal access and become an electricity exporter in the region by 2025. This study provides an invaluable perspective on different aspects of Ethiopia’s energy transition, focusing on achieving universal access and covering the country’s electricity needs during 2015–2065. We co-developed and investigated three scenarios to examine the policy and technology levels available to the government to meet their national priorities. To conduct this analysis, we soft-linked OnSSET, a modelling tool used for geospatial analysis, with OSeMOSYS, a cost-optimization modelling tool used for medium to long-run energy planning. Our results show that the country needs to diversify its power generation system to achieve universal access and cover its future electricity needs by increasing its overall carbon dioxide emissions and fully exploit hydropower. With the aim of achieving universal access by 2025, the newly electrified population is supplied primarily by the grid (65%), followed by stand-alone (32%) technologies. Similarly, until 2065, most of the electrified people by 2025 will continue to be grid-connected (99%). The country’s exports will increase to 17 TWh by 2065, up from 832 GWh in 2015, leading to a cumulative rise in electricity export revenues of 184 billion USD

Relativistic J-matrix method

The relativistic version of the J-matrix method for a scattering problem on the potential vanishing faster than the Coulomb one is formulated. As in the non-relativistic case it leads to a finite algebraic eigenvalue problem. The derived expression for the tangent of phase shift is simply related to the non-relativistic case formula and gives the latter as a limit case. It is due to the fact that the used basis set satisfies the ``kinetic balance condition''.Comment: 21 pages, RevTeX, accepted for publication in Phys. Rev.

Changes in neuromuscular structure and functions of human colon during ageing are region-dependent

Objective: To determine if human colonic neuromuscular functions decline with increasing age.Design: Looking for non-specific changes in neuromuscular function, a standard burst of electrical field stimulation (EFS) was used to evoke neuronally mediated (cholinergic/nitrergic) contractions/relaxations in ex vivomuscle strips of human ascending and descending colon, aged 35–91 years (macroscopically normal tissue; 239 patients undergoing cancer resection). Then, to understand mechanisms of change, numbers and phenotype of myenteric neurons (30 306 neurons stained with different markers), densities of intramuscular nerve fibres (51 patients in total) and pathways involved in functional changes were systematically investigated (by immunohistochemistry and use of pharmacological tools) in elderly (≥70 years) and adult (35–60 years) groups.Results: With increasing age, EFS was more likely to evoke muscle relaxation in ascending colon instead of contraction (linear regression: n=109, slope 0.49%±0.21%/year, 95% CI ), generally uninfluenced by comorbidity or use of medications. Similar changes were absent in descending colon. In the elderly, overall numbers of myenteric and neuronal nitric oxide synthaseimmunoreactive neurons and intramuscular nerve densities were unchanged in ascending and descending colon, compared with adults. In elderly ascending, not descending, colon numbers of cell bodies exhibiting choline acetyltransferase immunoreactivity increased compared with adults (5.0±0.6 vs 2.4±0.3 neurons/mm myenteric plexus, p=0.04). Cholinergically mediated contractions were smaller in elderly ascending colon compared with adults (2.1±0.4 and 4.1±1.1 g-tension/gtissue during EFS; n=25/14; p=0.04); there were no changes in nitrergic function or in ability of the muscle to contract/relax. Similar changes were absent in descending colon.Conclusion: In ascending not descending colon, ageing impairs cholinergic function

Infrastructure to Improve Beef Business Outcomes in the Queensland Gulf

There are significant economic and environmental issues impacting on the short and long term viability of family-run breeding enterprises in the Queensland Gulf. Falling cattle prices and increased business costs threaten the social and financial well-being of many beef producers. Set stocking and overgrazing combine to reduce native 3P (productive, palatable and perennial) grass frequency and herd productivity. The Ryan family on Greenhills Station at George-town in the Queensland Gulf embarked on a 5 year water and fencing infrastructure development program aiming to improve pasture utilisation, land condition and long term carrying capacity