Noether-type discrete conserved quantities arising from a finite element approximation of a variational problem

In this work, we prove a weak Noether-type Theorem for a class of variational problems that admit broken extremals. We use this result to prove discrete Noether-type conservation laws for a conforming finite element discretisation of a model elliptic problem. In addition, we study how well the finite element scheme satisfies the continuous conservation laws arising from the application of Noether’s first theorem (1918). We summarise extensive numerical tests, illustrating the conservation of the discrete Noether law using the p-Laplacian as an example and derive a geometric-based adaptive algorithm where an appropriate Noether quantity is the goal functional.

On some Generalizations of a Class of Discrete Functions

In this paper we examine discrete functions that depend on their variables in a particular way, namely the H-functions. The results obtained in this work make the “construction” of these functions possible. H-functions are generalized, as well as their matrix representation by Latin hypercubes.

Geometrical logarithmic and trigonometric hypercomplex functions of quaternionic type

Quaternionic theory has greatly been developed in recent years [1-12]. Thus, in our view, the study of trigonometric and logarithmic type quaternionic functions is important for the determination and realization of a hyper complex theory. In this paper, we intend to give a geometrical foundation for both logarithmic and trigonometric hyper complex functions based on the exponential function of quaternionic type recently introduced by Borges, Marão and Machado in their paper entitled Geometrical octonions II: Hyper regularity and hyper periodicity of the exponential function appearing. © 2011 Pushpa Publishing House.

Time and Energy Complexity of Distributed Computation of a Class of Functions in Wireless Sensor Networks

We consider a scenario in which a wireless sensor network is formed by randomly deploying n sensors to measure some spatial function over a field, with the objective of computing a function of the measurements and communicating it to an operator station. We restrict ourselves to the class of type-threshold functions (as defined in the work of Giridhar and Kumar, 2005), of which max, min, and indicator functions are important examples: our discussions are couched in terms of the max function. We view the problem as one of message-passing distributed computation over a geometric random graph. The network is assumed to be synchronous, and the sensors synchronously measure values and then collaborate to compute and deliver the function computed with these values to the operator station. Computation algorithms differ in (1) the communication topology assumed and (2) the messages that the nodes need to exchange in order to carry out the computation. The focus of our paper is to establish (in probability) scaling laws for the time and energy complexity of the distributed function computation over random wireless networks, under the assumption of centralized contention-free scheduling of packet transmissions. First, without any constraint on the computation algorithm, we establish scaling laws for the computation time and energy expenditure for one-time maximum computation. We show that for an optimal algorithm, the computation time and energy expenditure scale, respectively, as Theta(radicn/log n) and Theta(n) asymptotically as the number of sensors n rarr infin. Second, we analyze the performance of three specific computation algorithms that may be used in specific practical situations, namely, the tree algorithm, multihop transmission, and the Ripple algorithm (a type of gossip algorithm), and obtain scaling laws for the computation time and energy expenditure as n rarr infin. In particular, we show that the computation time for these algorithms scales as Theta(radicn/lo- g n), Theta(n), and Theta(radicn log n), respectively, whereas the energy expended scales as , Theta(n), Theta(radicn/log n), and Theta(radicn log n), respectively. Finally, simulation results are provided to show that our analysis indeed captures the correct scaling. The simulations also yield estimates of the constant multipliers in the scaling laws. Our analyses throughout assume a centralized optimal scheduler, and hence, our results can be viewed as providing bounds for the performance with practical distributed schedulers.

Economic, environmental and mixed objective functions in non-linear process optimization using simulated annealing and tabu search

Screening of topologies developed by hierarchical heuristic procedures can be carried out by comparing their optimal performance. In this work we will be exploiting mono-objective process optimization using two algorithms, simulated annealing and tabu search, and four different objective functions: two of the net present value type, one of them including environmental costs and two of the global potential impact type. The hydrodealkylation of toluene to produce benzene was used as case study, considering five topologies with different complexities mainly obtained by including or not liquid recycling and heat integration. The performance of the algorithms together with the objective functions was observed, analyzed and discussed from various perspectives: average deviation of results for each algorithm, capacity for producing high purity product, screening of topologies, objective functions robustness in screening of topologies, trade-offs between economic and environmental type objective functions and variability of optimum solutions.

Some problems of discrete function theory

An attempt is made by the researcher to establish a theory of discrete functions in the complex plane. Classical analysis q-basic theory, monodiffric theory, preholomorphic theory and q-analytic theory have been utilised to develop concepts like differentiation, integration and special functions.

Beurling zeta functions, generalised primes, and fractal membranes

We study generalised prime systems P (1 < p(1) <= p(2) <= ..., with p(j) is an element of R tending to infinity) and the associated Beurling zeta function zeta p(s) = Pi(infinity)(j=1)(1 - p(j)(-s))(-1). Under appropriate assumptions, we establish various analytic properties of zeta p(s), including its analytic continuation, and we characterise the existence of a suitable generalised functional equation. In particular, we examine the relationship between a counterpart of the Prime Number Theorem (with error term) and the properties of the analytic continuation of zeta p(s). Further we study 'well-behaved' g-prime systems, namely, systems for which both the prime and integer counting function are asymptotically well-behaved. Finally, we show that there exists a natural correspondence between generalised prime systems and suitable orders on N-2. Some of the above results are relevant to the second author's theory of 'fractal membranes', whose spectral partition functions are given by Beurling-type zeta functions, as well as to joint work of that author and R. Nest on zeta functions attached to quasicrystals.

Exact error estimates and optimal randomized algorithms for integration

Exact error estimates for evaluating multi-dimensional integrals are considered. An estimate is called exact if the rates of convergence for the low- and upper-bound estimate coincide. The algorithm with such an exact rate is called optimal. Such an algorithm has an unimprovable rate of convergence. The problem of existing exact estimates and optimal algorithms is discussed for some functional spaces that define the regularity of the integrand. Important for practical computations data classes are considered: classes of functions with bounded derivatives and Holder type conditions. The aim of the paper is to analyze the performance of two optimal classes of algorithms: deterministic and randomized for computing multidimensional integrals. It is also shown how the smoothness of the integrand can be exploited to construct better randomized algorithms.

What Monte Carlo models can do and cannot do efficiently?

The question "what Monte Carlo models can do and cannot do efficiently" is discussed for some functional spaces that define the regularity of the input data. Data classes important for practical computations are considered: classes of functions with bounded derivatives and Holder type conditions, as well as Korobov-like spaces. Theoretical performance analysis of some algorithms with unimprovable rate of convergence is given. Estimates of computational complexity of two classes of algorithms - deterministic and randomized for both problems - numerical multidimensional integration and calculation of linear functionals of the solution of a class of integral equations are presented. (c) 2007 Elsevier Inc. All rights reserved.

A multithickness sea ice model accounting for sliding friction

A multithickness sea ice model explicitly accounting for the ridging and sliding friction contributions to sea ice stress is developed. Both ridging and sliding contributions depend on the deformation type through functions adopted from the Ukita and Moritz kinematic model of floe interaction. In contrast to most previous work, the ice strength of a uniform ice sheet of constant ice thickness is taken to be proportional to the ice thickness raised to the 3/2 power, as is revealed in discrete element simulations by Hopkins. The new multithickness sea ice model for sea ice stress has been implemented into the Los Alamos “CICE” sea ice model code and is shown to improve agreement between model predictions and observed spatial distribution of sea ice thickness in the Arctic.

Implementation of an interior point source in the ultra weak variational formulation through source extraction

The Ultra Weak Variational Formulation (UWVF) is a powerful numerical method for the approximation of acoustic, elastic and electromagnetic waves in the time-harmonic regime. The use of Trefftz-type basis functions incorporates the known wave-like behaviour of the solution in the discrete space, allowing large reductions in the required number of degrees of freedom for a given accuracy, when compared to standard finite element methods. However, the UWVF is not well disposed to the accurate approximation of singular sources in the interior of the computational domain. We propose an adjustment to the UWVF for seismic imaging applications, which we call the Source Extraction UWVF. Differing fields are solved for in subdomains around the source, and matched on the inter-domain boundaries. Numerical results are presented for a domain of constant wavenumber and for a domain of varying sound speed in a model used for seismic imaging.

Floating s- and p-type Gaussian Orbitals

The advantages of including a small number of p-type gaussian functions in a floating spherical gaussian orbital calculation are pointed out and illustrated by calculations on molecules which previously have proved to be troublesome. These include molecules such as F2 with multiple lone pairs and C2H2 with multiple bonds. A feature of the results is the excellent correlation between the orbital energies and those of a double zeta calculation reported by Snyder and Basch.

The designed environment and how it affects brain morphology and mental health

Background The environment is inextricably related to mental health. Recent research replicates findings of a significant, linear correlation between a childhood exposure to the urban environment and psychosis. Related studies also correlate the urban environment and aberrant brain morphologies. These findings challenge common beliefs that the mind and brain remain neutral in the face of worldly experience. Aim There is a signature within these neurological findings that suggests that specific features of design cause and trigger mental illness. The objective in this article is to work backward from the molecular dynamics to identify features of the designed environment that may either trigger mental illness or protect against it. Method This review analyzes the discrete functions putatively assigned to the affected brain areas and a neurotransmitter called dopamine, which is the primary target of most antipsychotic medications. The intention is to establish what the correlations mean in functional terms, and more specifically, how this relates to the phenomenology of urban experience. In doing so, environmental mental illness risk factors are identified. Conclusions Having established these relationships, the review makes practical recommendations for those in public health who wish to use the environment itself as a tool to improve the mental health of a community through design.

ORP2 is a sterol receptor that regulates cellular lipid metabolism

ORP2 is a member of mammalian oxysterol binding protein (OSBP)-related protein/gene family (ORPs), which is found in almost every eukaryotic organism. ORPs have been suggested to participate in the regulation of cellular lipid metabolism, vesicle trafficking and cellular signaling. ORP2 is a cytosolic protein that is ubiquitously expressed and most abundant in the brain. In previous studies employing stable cell lines with constitutive ORP2 overexpression ORP2 was shown to affect cellular cholesterol metabolism. The aim of this study was to characterize the properties and function of ORP2 further. ORP2 ligands were searched for among sterols and phosphoinositides using purified ORP2 and in vitro binding assays. As expected, ORP2 bound several oxysterols and cholesterol, the highest affinity ligand being 22(R)hydroxycholesterol. In addition, affinity for anionic membrane phospholipids, phosphoinositides was observed, which may assist in the membrane targeting of ORP2. Intracellular localization of ORP2 was also investigated. ORP2 was observed on the surface of cytoplasmic lipid droplets, which are storage organelles for neutral lipids. Lipid droplet targeting of ORP2 was inhibited when 22(R)hydroxycholesterol was added to the cells or when the N-terminal FFAT-motif of ORP2 was mutated, suggesting that oxysterols and the N-terminus of ORP2 regulate the localization and the function of ORP2. The role of ORP2 in cellular lipid metabolism was studied using HeLa cell lines that can be induced to overexpress ORP2. Overexpression of ORP2 was shown to enhance cholesterol efflux from the cells resulting in a decreased amount of cellular free cholesterol. ORP2 overexpressing cells responded to the loss of cholesterol by upregulating cholesterol synthesis and uptake. Intriguingly, also cholesterol esterification was increased in ORP2 overexpressing cells. These results may be explained by the ability of ORP2 to bind and thus transport cholesterol, which most likely leads to changes in cholesterol metabolism when ORP2 is overexpressed. ORP2 function was further investigated by silencing the endogenous ORP2 expression with short interfering RNAs (siRNA) in A431 cells. Silencing of ORP2 led to a delayed break-down of triglycerides under lipolytic conditions and an increased amount of cholesteryl esters in the presence of excess triglycerides. Together these results suggest that ORP2 is a sterol-regulated protein that functions on the surface of cytoplasmic lipid droplets to regulate the metabolism of triglycerides and cholesteryl esters. Although the exact mode of ORP2 action still remains unclear, this study serves as a good basis to investigate the molecular mechanisms and possible cell type specific functions of ORP2.