Short, medium and long term load forecasting model and virtual load forecaster based on radial basis neural networks

Artificial neural networks (ANNs) can be easily applied to short-term load forecasting (STLF) models for electric power distribution applications. However, they are not typically used in medium and long term load forecasting (MLTLF) electric power models because of the difficulties associated with collecting and processing the necessary data. Virtual instrument (VI) techniques can be applied to electric power load forecasting but this is rarely reported in the literature. In this paper, we investigate the modelling and design of a VI for short, medium and long term load forecasting using ANNs. Three ANN models were built for STLF of electric power. These networks were trained using historical load data and also considering weather data which is known to have a significant affect of the use of electric power (such as wind speed, precipitation, atmospheric pressure, temperature and humidity). In order to do this a V-shape temperature processing model is proposed. With regards MLTLF, a model was developed using radial basis function neural networks (RBFNN). Results indicate that the forecasting model based on the RBFNN has a high accuracy and stability. Finally, a virtual load forecaster which integrates the VI and the RBFNN is presented.

Two-stage mixed discrete-continuous identification of radial basis function (RBF) neural models for nonlinear systems

The identification of nonlinear dynamic systems using radial basis function (RBF) neural models is studied in this paper. Given a model selection criterion, the main objective is to effectively and efficiently build a parsimonious compact neural model that generalizes well over unseen data. This is achieved by simultaneous model structure selection and optimization of the parameters over the continuous parameter space. It is a mixed-integer hard problem, and a unified analytic framework is proposed to enable an effective and efficient two-stage mixed discrete-continuous; identification procedure. This novel framework combines the advantages of an iterative discrete two-stage subset selection technique for model structure determination and the calculus-based continuous optimization of the model parameters. Computational complexity analysis and simulation studies confirm the efficacy of the proposed algorithm.

Combined R-matrix eigenstate basis set and finite-difference propagation method for the time-dependent Schrodinger equation: The one-electron case

In this work we present the theoretical framework for the solution of the time-dependent Schrödinger equation (TDSE) of atomic and molecular systems under strong electromagnetic fields with the configuration space of the electron’s coordinates separated over two regions; that is, regions I and II. In region I the solution of the TDSE is obtained by an R-matrix basis set representation of the time-dependent wave function. In region II a grid representation of the wave function is considered and propagation in space and time is obtained through the finite-difference method. With this, a combination of basis set and grid methods is put forward for tackling multiregion time-dependent problems. In both regions, a high-order explicit scheme is employed for the time propagation. While, in a purely hydrogenic system no approximation is involved due to this separation, in multielectron systems the validity and the usefulness of the present method relies on the basic assumption of R-matrix theory, namely, that beyond a certain distance (encompassing region I) a single ejected electron is distinguishable from the other electrons of the multielectron system and evolves there (region II) effectively as a one-electron system. The method is developed in detail for single active electron systems and applied to the exemplar case of the hydrogen atom in an intense laser field.

Unravelling the genetic basis of renal diseases; from single gene to multifactorial disorders

Chronic kidney disease is common with up to 5% of the adult population reported to have an estimated glomerular filtration rate of

Structural basis for the platelet-collagen interaction - The smallest motif within collagen that recognizes and activates platelet glycoprotein VI contains two glycine-proline-hydroxyproline triplets

Collagen-related peptide is a selective agonist for the platelet collagen receptor Glycoprotein VI. The triple helical peptide contains ten GPO triplets/strand (single letter amino acid nomenclature, where O is hydroxyproline) and so over-represents GPO compared with native collagen sequence. To investigate the ability of Glycoprotein VI to recognize GPO triplets in a setting more representative of the collagens, we synthesized a set of triple helical peptides containing fewer GPO triplets, varying their number and spacing within an inert (GPP)(n) backbone. The adhesion of recombinant human Glycoprotein VI ectodomain, like that of human platelets, to these peptides increased with their GPO content, and platelet adhesion was abolished by the specific anti-Glycoprotein VI-blocking antibody, 10B12. Platelet aggregation and protein tyrosine phosphorylation were induced only by cross-linked peptides and only those that contained two or more GPO triplets. Such peptides were less potent than cross-linked collagen-related peptide. Our data suggest that both the sequences GPOGPO and GPO center dot center dot center dot center dot center dot center dot center dot center dot center dot GPO represent functional Glycoprotein VI recognition motifs within collagen. Furthermore, we propose that the (GPO)(4) motif can support simultaneous binding of two glycoprotein VI molecules, in either a parallel or anti-parallel stacking arrangement, which could play an important role in activation of signaling.

Structural basis for the inhibition of the essential Plasmodium falciparum M1 neutral aminopeptidase

Plasmodium falciparum parasites are responsible for the major global disease malaria, which results in > 2 million deaths each year. With the rise of drug-resistant malarial parasites, novel drug targets and lead compounds are urgently required for the development of new therapeutic strategies. Here, we address this important problem by targeting the malarial neutral aminopeptidases that are involved in the terminal stages of hemoglobin digestion and essential for the provision of amino acids used for parasite growth and development within the erythrocyte. We characterize the structure and substrate specificity of one such aminopeptidase, PfA-M1, a validated drug target. The X-ray crystal structure of PfA-M1 alone and in complex with the generic inhibitor, bestatin, and a phosphinate dipeptide analogue with potent in vitro and in vivo antimalarial activity, hPheP[CH2] Phe, reveals features within the protease active site that are critical to its function as an aminopeptidase and can be exploited for drug development. These results set the groundwork for the development of antimalarial therapeutics that target the neutral aminopeptidases of the parasite.

Efficient advanced encryption standard implementation using lookup and normal basis

A new type of advanced encryption standard (AES) implementation using a normal basis is presented. The method is based on a lookup technique that makes use of inversion and shift registers, which leads to a smaller size of lookup for the S-box than its corresponding implementations. The reduction in the lookup size is based on grouping sets of inverses into conjugate sets which in turn leads to a reduction in the number of lookup values. The above technique is implemented in a regular AES architecture using register files, which requires less interconnect and area and is suitable for security applications. The results of the implementation are competitive in throughput and area compared with the corresponding solutions in a polynomial basis.

IS THERE A PHYSIOLOGICAL-BASIS FOR THE COUVADE AND ONSET OF PATERNAL CARE

Couvade is the male experience of pregnancy and couvade syndrome incorporates a range of symptoms suffered by ''pregnant'' men. The aetiology of the couvade syndrome is unknown. Anthropologists, psychiatrists, nurses and sociologists have provided explanations for behaviour changes in ''pregnant'' men in terms of cultural pressure, intrapsychic processes and psychosocial adaptation to a new situation. The adoption of a biological perspective allows us to ask a new question: is there a physiological basis for the couvade syndrome? A fresh research agenda would include measurement of physiological change and a search for causation. Implications for nursing are outlined.