Transfer Learning by Similarity Centred Architecture Evolution for Multiple Residential Load Forecasting

The development from traditional low voltage grids to smart systems has become extensive and adopted worldwide. Expanding the demand response program to cover the residential sector raises a wide range of challenges. Short term load forecasting for residential consumers in a neighbourhood could lead to a better understanding of low voltage consumption behaviour. Nevertheless, users with similar characteristics can present diversity in consumption patterns. Consequently, transfer learning methods have become a useful tool to tackle differences among residential time series. This paper proposes a method combining evolutionary algorithms for neural architecture search with transfer learning to perform short term load forecasting in a neighbourhood with multiple household load consumption. The approach centres its efforts on neural architecture search using evolutionary algorithms. The neural architecture evolution process retains the patterns of the centre-most house, and later the architecture weights are adjusted for each house in a multihouse set from a neighbourhood. In addition, a sensitivity analysis was conducted to ensure model performance. Experimental results on a large dataset containing hourly load consumption for ten houses in London, Ontario showed that the performance of the proposed approach performs better than the compared techniques. Moreover, the proposed method presents the average accuracy performance of 3.17 points higher than the state-of-the-art LSTM one shot method

Deep neural network for load forecasting centred on architecture evolution

Nowadays, electricity demand forecasting is critical for electric utility companies. Accurate residential load forecasting plays an essential role as an individual component for integrated areas such as neighborhood load consumption. Short-term load forecasting can help electric utility companies reduce waste because electric power is expensive to store. This paper proposes a novel method to evolve deep neural networks for time series forecasting applied to residential load forecasting. The approach centres its efforts on the neural network architecture during the evolution. Then, the model weights are adjusted using an evolutionary optimization technique to tune the model performance automatically. Experimental results on a large dataset containing hourly load consumption of a residence in London, Ontario shows that the performance of unadjusted weights architecture is comparable to other state-of-the-art approaches. Furthermore, when the architecture weights are adjusted the model accuracy surpassed the state-of-the-art method called LSTM one shot by 3.0%

Binding of SARS-CoV-2 to cell receptors: a tale of molecular evolution

The magnified infectious power of the SARS-CoV-2 virus compared to its precursor SARS-CoV is intimately linked to an enhanced ability in the mutated virus to find available hydrogen bond sites in the host cells. This characteristic is acquired during virus evolution because of the selective pressure exerted at the molecular level. We pinpoint the specific residue (in the virus) to residue (in the cell) contacts during the initial recognition and binding and show that the virus\ub7 \ub7 \ub7 cell interaction is mainly due to an extensive network of hydrogen bonds and to a large surface of non-covalent interactions. In addition to the formal quantum characterization of bonding interactions, computation of absorption spectra for the specific virus\ub7 \ub7 \ub7 cell interacting residues yields significant shifts of 06\u3bb max = 47 and 66 nm in the wavelength for maximum absorption in the complex with respect to the isolated host and virus, respectively

Trichodoridae from southern Spain, with description of Trichodorus giennensis n.sp. (Nemata : Trichodoridae)

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Mouse models of primary aldosteronism: from physiology to pathophysiology

Primary aldosteronism (PA) is a common form of endocrine hypertension that is characterized by the excessive production of aldosterone relative to suppressed plasma renin levels. PA is usually caused by either a unilateral aldosterone-producing adenoma or bilateral adrenal hyperplasia. Somatic mutations have been identified in several genes that encode ion pumps and channels that may explain the aldosterone excess in over half of aldosterone-producing adenomas, whereas the pathophysiology of bilateral adrenal hyperplasia is largely unknown. A number of mouse models of hyperaldosteronism have been described that recreate some features of the human disorder although none replicate the genetic basis of human PA. Animal models that reproduce the genotype-phenotype associations of human PA are required to establish the functional mechanisms that underlie the endocrine autonomy and deregulated cell growth of the affected adrenal and for preclinical studies of novel therapeutics. Herein, we discuss the differences in adrenal physiology across species and describe the genetically-modified mouse models of PA that have been developed to date

Reduced expression of mir15a in the blood of patients with oral squamous cell carcinoma is associated with tumor staging

MicroRNAs (miRNAs) mirl 5a and let7a are iMportant regulators of bcl-2, ras and c-myc proteins Considering that these miRNAs are commonly altered in many human cancers and that these proteins are reported to be altered in oral squamous cell carcinoma (OSCC), we investigated them in a set of OSCC cases \u27I he miRNAs as well as the proteins were evaluated in the tumor and blood of 20 patients by real-time quantitative PCR and iMmunohistochemistry, respectively The expression of nfirl5a and bcl-2 proteins in the tumors was not associated with each other or with tumor staging On the other hand, we found reduced expression of this miRNA in the blood of patients with an advanced stage of OSCC and with lymph node metastasis The expression of let7a in the tumor and blood was not associated with tumor size lymph node metastasis, tumor staging and immunoexpression of ras and c-myc proteins In conclusion, the present study shows that reduced expression of Mir15a is associated with OSCC stagin

Constraining the string scale: from Planck to Weak and back again

String and field theory ideas have greatly influenced each other since the so called second string revolution. We review this interrelation paying particular attention to its phenomenological implications. Our guiding principle is the radical shift in the way that we think about the fundamental scale, in particular the way in which string models have been able to accommodate values from the Planck $M_\mathrm{Pl}\sim 10^{18}$ GeV down to the electroweak scale $M_{EW}\sim$ TeV.Comment: Invited review aimed at an experimental audienc

Intersecting Brane Worlds -- A Path to the Standard Model ?

In this review we describe the general geometrical framework of brane world constructions in orientifolds of type IIA string theory with D6-branes wrapping 3-cycles in a Calabi-Yau 3-fold. These branes generically intersect in points on the internal space, and the patterns of intersections govern the chiral fermion spectra. We discuss how the open string spectra in intersecting brane models are constructed, how the Standard Model can be embedded, and also how supersymmetry can be realized in this class of string vacua. After the general considerations we specialize the discussion to the case of orbifold backgrounds with intersecting D6-branes and to the quintic Calabi-Yau manifold. Then, we discuss parts of the effective action of intersecting brane world models. Specifically we compute from the Born-Infeld action of the wrapped D-branes the tree-level, D-term scalar potential, which is important for the stability of the considered backgrounds as well as for questions related to supersymmetry breaking. Second, we review the recent computation concerning of gauge coupling unification and also of one-loop gauge threshold corrections in intersecting brane world models. Finally we also discuss some aspects of proton decay in intersecting brane world models.Comment: 31 pages, To appear in the proceedings of the RTN-workshop ``The quantum structure of spacetime and the geometric nature of fundamental interactions'', September 2003 in Copenhagen, revised version contains new refs and one corrected equatio

The young open cluster NGC 7067 using Stromgren photometry

© The Authors 2016. Published by Oxford University Press on behalf of The Royal Astronomical Society. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. M. Monguio et al, ' The young open cluster NGC 7067 using Stromgren photometry ', MNRAS Vol 466(3): 3636-3647 (2017), first published online 17 December 2016, the version of record is available online via doi: 10.1093/mnras/stw3302NGC 7067 is a young open cluster located in the direction between the first and the second Galactic quadrants and close to the Perseus spiral arm. This makes it useful for studies of the nature of the Milky Way spiral arms. Stromgren photometry taken with the Wide Field Camera at the Isaac Newton Telescope allowed us to compute individual physical parameters for the bserved stars and hence to derive cluster’s physical parameters. Spectra from the 1.93-m telescope at the Observatoire de Haute-Provence helped to check and improve the results. We obtained photometry for 1233 stars, individual physical parameters for 515 and spectra for 9 of them. The 139 selected cluster members lead to a cluster distance of 4.4±0.4 kpc, with an age below log10(t(yr))=7.3 and a present Mass of 1260±160M⊙. The morphology of the data reveals that the centre of the cluster is at (α,δ)=(21: 24: 13.69,+48: 00: 39.2) J2000, with a radius of 6.′1. Stromgren and spectroscopic data allowed us to improve the previous parameters available for the cluster in the literature.Peer reviewedFinal Published versio