Alien Registration- Dubuc, Gilberte B. (Auburn, Androscoggin County)

https://digitalmaine.com/alien_docs/31135/thumbnail.jp

Surface Studies of Calcium Oxalate Dihydrate Single Crystals During Dissolution in the Presence of Urine

Single crystals of Calcium Oxalate Dihydrate (COD) were grown from solution under controlled release of the reacting ions. Dissolution of COD was studied at different pH levels and in different dilutions of urine. The descriptors of the contour were determined during dissolution of COD using a quantitative morphological technique. The shape parameters and surface ruggedness were determined from Fourier and fractal analysis. The results obtained give quantitative information on the dissolution kinetics and the surface geometry of COD crystals in normal and diluted urine. Dissolution inhibition and morphological changes of COD crystals during dissolution were attributed to selective adsorption of urine non-ionic macromolecules on the crystal stepped surface. Surface etching of COD was found to depend on urine dilution and time of incubation. The data obtained suggest that the geometric structure of the surface is likely to be a potential factor in understanding crystal aggregation in stone formation

Evaluation of the Surface Roughness of Cystine Stones Using a Visible Laser Diode Scattering Approach

To understand the processes of fragmentation and the chemical reactivity of solids, proper characterization of surface topography is crucial. This paper describes a non-destructive technique of quantifying the surface roughness of cystine renal stones, using visible laser diode scattering and fractal geometry. Fragments of cystine stones were mounted on microscope slides and coated by a carbon-sputtering apparatus. The slides were placed under a dynamic active-vision system, using a visible laser diode to measure three-dimensional surface coordinates. The data obtained were analyzed by fractal geometry. Surface fractal dimensions were determined by the variation method. The results showed that the surface of a compact-size sample can be evaluated quantitatively. The technique is valuable for the accurate presentation of surfaces in three dimensions

Approximate Jacobians for the Solution of the Euler and Navier-Stokes Equations. G.U. Aero Report 9705

This paper describes a method for efficiently solving the steady-state Euler and Navier-Stokes equations. Robustness is achieved through the use of an upwind TVD scheme for discretising the convective terms. The approximate solution is advanced in time implicitly and the linear system arising at each implicit step is solved using a Conjugate Gradient type method. The main emphasis of this paper is on the use of Jacobian matrices associated with a simpler spatial discretisation. This leads to better conditioned linear systems. The resulting method has lower memory and CPU-time requirements when compared with the one using exact Jacobians

A Contractual Approach to Investor-State Regulatory Disputes

International investment arbitral tribunals are increasingly tasked with resolving regulatory disputes. This relatively new form of dispute involves a challenge by a foreign investor to a host state’s generally applicable regulation, enacted in good faith to promote the public interest but resulting incidentally in harm to the investor’s business. Such claims typically invoke the “fair and equitable treatment” standard provided for in the bilateral investment treaty between the host state and the investor’s home state. The dominant view among commentators, and increasingly among the tribunals themselves, is that regulatory disputes should be analyzed within a public law framework, using tools derived from constitutional or administrative law. That means, for example, balancing the investor’s rights and host state’s regulatory concerns as part of a proportionality analysis. I argue that the public law approach is flawed because it requires tribunals to weigh incommensurable values and ultimately to make policy judgments when they lack the expertise and legitimacy to do so. This Article proposes that tribunals instead draw on tools from contract law and theory to approximate what the contracting states intended when they agreed to a fair and equitable treatment standard. The investment treaties themselves give no guidance on how that standard should be applied to regulatory disputes. When courts confront similar gaps in contracts, they do not simply abandon the inquiry into the parties’ intent but instead apply additional tools or principles to form the best possible estimate. The Article explores three specific tools: a default rule approach and two default standards derived from contract law’s analysis of changed circumstances. More generally, I argue that a contractual approach, by focusing tribunals on the contracting states’ intent rather than requiring them to independently assess the substance of a host state’s policy, will facilitate more principled reasoning as well as enhance the tribunals’ legitimacy, and thereby better promote the goals of international investment in the long run

Synchronizing Automata on Quasi Eulerian Digraph

In 1964 \v{C}ern\'{y} conjectured that each $n$-state synchronizing automaton posesses a reset word of length at most $(n-1)^2$. From the other side the best known upper bound on the reset length (minimum length of reset words) is cubic in $n$. Thus the main problem here is to prove quadratic (in $n$) upper bounds. Since 1964, this problem has been solved for few special classes of \sa. One of this result is due to Kari \cite{Ka03} for automata with Eulerian digraphs. In this paper we introduce a new approach to prove quadratic upper bounds and explain it in terms of Markov chains and Perron-Frobenius theories. Using this approach we obtain a quadratic upper bound for a generalization of Eulerian automata.Comment: 8 pages, 1 figur

Solution of the Euler Unsteady Equations Using Deforming Grids. G.U. Aero Report 9704.

No abstract available

Fractal Analysis of Protein Potential Energy Landscapes

The fractal properties of the total potential energy V as a function of time t are studied for a number of systems, including realistic models of proteins (PPT, BPTI and myoglobin). The fractal dimension of V(t), characterized by the exponent \gamma, is almost independent of temperature and increases with time, more slowly the larger the protein. Perhaps the most striking observation of this study is the apparent universality of the fractal dimension, which depends only weakly on the type of molecular system. We explain this behavior by assuming that fractality is caused by a self-generated dynamical noise, a consequence of intermode coupling due to anharmonicity. Global topological features of the potential energy landscape are found to have little effect on the observed fractal behavior.Comment: 17 pages, single spaced, including 12 figure

Structure of shells in complex networks

In a network, we define shell $\ell$ as the set of nodes at distance $\ell$ with respect to a given node and define $r_\ell$ as the fraction of nodes outside shell $\ell$. In a transport process, information or disease usually diffuses from a random node and reach nodes shell after shell. Thus, understanding the shell structure is crucial for the study of the transport property of networks. For a randomly connected network with given degree distribution, we derive analytically the degree distribution and average degree of the nodes residing outside shell $\ell$ as a function of $r_\ell$. Further, we find that $r_\ell$ follows an iterative functional form $r_\ell=\phi(r_{\ell-1})$, where $\phi$ is expressed in terms of the generating function of the original degree distribution of the network. Our results can explain the power-law distribution of the number of nodes $B_\ell$ found in shells with $\ell$ larger than the network diameter $d$, which is the average distance between all pairs of nodes. For real world networks the theoretical prediction of $r_\ell$ deviates from the empirical $r_\ell$. We introduce a network correlation function $c(r_\ell)\equiv r_{\ell+1}/\phi(r_\ell)$ to characterize the correlations in the network, where $r_{\ell+1}$ is the empirical value and $\phi(r_\ell)$ is the theoretical prediction. $c(r_\ell)=1$ indicates perfect agreement between empirical results and theory. We apply $c(r_\ell)$ to several model and real world networks. We find that the networks fall into two distinct classes: (i) a class of {\it poorly-connected} networks with $c(r_\ell)>1$, which have larger average distances compared with randomly connected networks with the same degree distributions; and (ii) a class of {\it well-connected} networks with $c(r_\ell)<1$

Mapping the big data landscape: technologies, platforms and paradigms for real-time analytics of data streams

The ‘Big Data’ of yesterday is the ‘data’ of today. As technology progresses, new challenges arise and new solutions are developed. Due to the emergence of Internet of Things applications within the last decade, the field of Data Mining has been faced with the challenge of processing and analysing data streams in real-time, and under high data throughput conditions. This is often referred to as the Velocity aspect of Big Data. Whereas there are numerous reviews on Data Stream Mining techniques and applications, there is very little work surveying Data Stream processing paradigms and associated technologies, from data collection through to pre-processing and feature processing, from the perspective of the user, not that of the service provider. In this paper, we evaluate a particular type of solution, which focuses on streaming data, and processing pipelines that permit online analysis of data streams that cannot be stored as-is on the computing platform. We review foundational computational concepts such as distributed computation, fault-tolerant computing, and computational paradigms/architectures. We then review the available technological solutions, and applications that pertain to data stream mining as case studies of these theoretical concepts. We conclude with a discussion of the field of data stream processing/analytics, future directions and research challenges