1,379 research outputs found

    Loss Allocation in Distribution Networks Based on Aumann-Shapley

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    This paper outlines a procedure for loss allocation in both radial and meshed distribution networks with distributed generation that could be regulated in various ways. The method is analytically developed based on the theory of electrical circuits combined with game theory based on Aumann&-Shapley, which guarantees both the electrical principles and the fair axioms of game theory. The proposed method obtains unitary participation coefficients for each network user based on the currents demanded/injected by each user and the network topology. The proposed allocation method based on Aumann&-Shapley has been compared with other traditional allocation methods, is adaptable to distribution networks, and shows great potential and ease of implementation. Moreover, it can be applied to any kind of distribution network (radial or meshed) with distributed energy resources

    On the Whitham hierarchy: dressing scheme, string equations and additional symmetrie

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    A new description of the universal Whitham hierarchy in terms of a factorization problem in the Lie group of canonical transformations is provided. This scheme allows us to give a natural description of dressing transformations, string equations and additional symmetries for the Whitham hierarchy. We show how to dress any given solution and prove that any solution of the hierarchy may be undressed, and therefore comes from a factorization of a canonical transformation. A particulary important function, related to the τ\tau-function, appears as a potential of the hierarchy. We introduce a class of string equations which extends and contains previous classes of string equations considered by Krichever and by Takasaki and Takebe. The scheme is also applied for an convenient derivation of additional symmetries. Moreover, new functional symmetries of the Zakharov extension of the Benney gas equations are given and the action of additional symmetries over the potential in terms of linear PDEs is characterized

    On the Whitham hierarchy: dressing scheme, string equations and additional symmetrie

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    A new description of the universal Whitham hierarchy in terms of a factorization problem in the Lie group of canonical transformations is provided. This scheme allows us to give a natural description of dressing transformations, string equations and additional symmetries for the Whitham hierarchy. We show how to dress any given solution and prove that any solution of the hierarchy may be undressed, and therefore comes from a factorization of a canonical transformation. A particulary important function, related to the τ\tau-function, appears as a potential of the hierarchy. We introduce a class of string equations which extends and contains previous classes of string equations considered by Krichever and by Takasaki and Takebe. The scheme is also applied for an convenient derivation of additional symmetries. Moreover, new functional symmetries of the Zakharov extension of the Benney gas equations are given and the action of additional symmetries over the potential in terms of linear PDEs is characterized

    Preclinical efficacy of CIGB-300, an anti-CK2 peptide, on breast cancer metastasic colonization

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    CK2 is a serine/threonine kinase that is overexpressed in breast cancer and its inhibition is associated to reduced tumor growth and disease progression. CIGB-300 is an antitumor peptide with a novel mechanism of action, since it binds to protein kinase CK2 catalytic subunit alpha and to CK2 substrates thus preventing the enzyme activity. Our aim was to evaluate the potential therapeutic benefits of CIGB-300 on breast cancer disease using experimental models with translational relevance. We demonstrated that CIGB-300 reduces breast cancer cell growth in MDA-MB-231, MCF-7 and F3II cells, exerting a pro-apoptotic action and cell cycle arrest. We also found that CIGB-300 decreased cell adhesion, migration and clonogenic capacity of malignant cells. Effect on experimental breast cancer lung metastasis was evaluated after surgical removal of primary F3II tumors or after tail vein injection of tumor cells, also we evaluated CIGB-300 effect on spontaneous lung metastasis in an orthotopic model. Systemic CIGB-300 treatment inhibited breast cancer colonization of the lung, reducing the size and number of metastatic lesions. The present preclinical study establishes for the first time the efficacy of CIGB-300 on breast cancer. These encouraging results suggest that CIGB-300 could be used for the management of breast cancer as an adjuvant therapy after surgery, limiting tumor metastatic spread and thus protecting the patient from distant recurrence.Fil: Gottardo, María Florencia. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología. Laboratorio de Oncología Molecular; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Capobianco, Carla Sabrina. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología. Laboratorio de Oncología Molecular; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Sidabra, Johanna Elena. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología. Laboratorio de Oncología Molecular; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Garona, Juan. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología. Laboratorio de Oncología Molecular; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Perera, Yasser. Centro de Ingeniería Genética y Biotecnología ; CubaFil: Perea, Silvio E.. Centro de Ingeniería Genética y Biotecnología ; CubaFil: Alonso, Daniel Fernando. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología. Laboratorio de Oncología Molecular; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Farina, Hernån Gabriel. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología. Laboratorio de Oncología Molecular; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

    Epilepsy in Neurodegenerative Diseases: Related Drugs and Molecular Pathways

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    Epilepsy is a chronic disease of the central nervous system characterized by an electrical imbalance in neurons. It is the second most prevalent neurological disease, with 50 million people affected around the world, and 30% of all epilepsies do not respond to available treatments. Currently, the main hypothesis about the molecular processes that trigger epileptic seizures and promote the neurotoxic effects that lead to cell death focuses on the exacerbation of the glutamate pathway and the massive influx of Ca2+ into neurons by different factors. However, other mechanisms have been proposed, and most of them have also been described in other neurodegenerative diseases, such as Alzheimer's disease, Parkinson's disease, Huntington's disease, or multiple sclerosis. Interestingly, and mainly because of these common molecular links and the lack of effective treatments for these diseases, some antiseizure drugs have been investigated to evaluate their therapeutic potential in these pathologies. Therefore, in this review, we thoroughly investigate the common molecular pathways between epilepsy and the major neurodegenerative diseases, examine the incidence of epilepsy in these populations, and explore the use of current and innovative antiseizure drugs in the treatment of refractory epilepsy and other neurodegenerative diseases. Keywords: Alzheimer's disease; Huntington's disease; Parkinson's disease; epilepsy; multiple sclerosis; neurodegenerative diseases

    Charged Free Fermions, Vertex Operators and Classical Theory of Conjugate Nets

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    We show that the quantum field theoretical formulation of the τ\tau-function theory has a geometrical interpretation within the classical transformation theory of conjugate nets. In particular, we prove that i) the partial charge transformations preserving the neutral sector are Laplace transformations, ii) the basic vertex operators are Levy and adjoint Levy transformations and iii) the diagonal soliton vertex operators generate fundamental transformations. We also show that the bilinear identity for the multicomponent Kadomtsev-Petviashvili hierarchy becomes, through a generalized Miwa map, a bilinear identity for the multidimensional quadrilateral lattice equations.Comment: 28 pages, 3 Postscript figure

    New VVV Survey Globular Cluster Candidates in the Milky Way Bulge

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    © 2017 The American Astronomical Society. All rights reserved.It is likely that a number of Galactic globular clusters remain to be discovered, especially toward the Galactic bulge. High stellar density combined with high and differential interstellar reddening are the two major problems for finding globular clusters located toward the bulge. We use the deep near-IR photometry of the VISTA Variables in the Vía Låctea (VVV) Survey to search for globular clusters projected toward the Galactic bulge, and hereby report the discovery of 22 new candidate globular clusters. These objects, detected as high density regions in our maps of bulge red giants, are confirmed as globular cluster candidates by their color-magnitude diagrams. We provide their coordinates as well as their near-IR color-magnitude diagrams, from which some basic parameters are derived, such as reddenings and heliocentric distances. The color-magnitude diagrams reveal well defined red giant branches in all cases, often including a prominent red clump. The new globular cluster candidates exhibit a variety of extinctions (0.06 < A Ks < 2.77) and distances (5.3 < D < 9.5 kpc). We also classify the globular cluster candidates into 10 metal-poor and 12 metal-rich clusters, based on the comparison of their color-magnitude diagrams with those of known globular clusters also observed by the VVV Survey. Finally, we argue that the census for Galactic globular clusters still remains incomplete, and that many more candidate globular clusters (particularly the low luminosity ones) await to be found and studied in detail in the central regions of the Milky Way.Peer reviewedFinal Accepted Versio

    Galaxy velocity bias in cosmological simulations: Towards per cent-level calibration

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    This is a pre-copyedited, author-produced PDF of an article accepted for publication in Monthly Notices of the Royal Astronomical Society following peer review. The version of record Monthly Notices of the Royal Astronomical Society 510.2 (2022): 2980-2997 is available online at: https://academic.oup.com/mnras/article-abstract/510/2/2980/6472247?redirectedFrom=fulltextGalaxy cluster masses, rich with cosmological information, can be estimated from internal dark matter (DM) velocity dispersions, which in turn can be observationally inferred from satellite galaxy velocities. However, galaxies are biased tracers of the DM, and the bias can vary over host halo and galaxy properties as well as time. We precisely calibrate the velocity bias, bv - defined as the ratio of galaxy and DM velocity dispersions - as a function of redshift, host halo mass, and galaxy stellar mass threshold (M), for massive haloes (200cM) from five cosmological simulations: IllustrisTNG, Magneticum, Bahamas + Macsis, The Three Hundred Project, and MultiDark Planck-2. We first compare scaling relations for galaxy and DM velocity dispersion across simulations; the former is estimated using a new ensemble velocity likelihood method that is unbiased for low galaxy counts per halo, while the latter uses a local linear regression. The simulations show consistent trends of bv increasing with M200c and decreasing with redshift and M. The ensemble-estimated theoretical uncertainty in bv is 2-3 per cent, but becomes percent-level when considering only the three highest resolution simulations. We update the mass-richness normalization for an SDSS redMaPPer cluster sample, and find our improved bv estimates reduce the normalization uncertainty from 22 to 8 per cent, demonstrating that dynamical mass estimation is competitive with weak lensing mass estimation. We discuss necessary steps for further improving this precision. Our estimates for 200c are made publicly availabl

    Somatic and germline analysis of a familial Rothmund-Thomson syndrome in two siblings with osteosarcoma

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    Rothmund–Thomson syndrome (RTS) is characterized by a rash that begins in the first few months of life and eventually develops into poikiloderma. Associated symptoms are alterations in the teeth, sparse hair, thin eyebrows, lack of eyelashes, low stature, bone abnormalities, hematological illnesses, gastrointestinal disease, malnutrition, cataracts, and predisposition to cancer, principally to bone tumors and skin cancer. Diagnostic certitude is provided by a genetic study involving detection of pathogenic variants of the RECQL4 gene. We hereby present a familiar case of RTS in two siblings from a Portuguese family, both diagnosed with osteosarcoma. Genomic analysis (203 genes) of both tumors as well as germline analysis of the RECQL4 gene, thus confirming the syndrome in the family, have been performed. The relevance of clinical recognition of the hallmarks of the disease and thus early diagnosis with early intervention is highlighted

    Addressing the data bottleneck in medical deep learning models using a human-in-the-loop machine learning approach

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    [Abstract]: Any machine learning (ML) model is highly dependent on the data it uses for learning, and this is even more important in the case of deep learning models. The problem is a data bottleneck, i.e. the difficulty in obtaining an adequate number of cases and quality data. Another issue is improving the learning process, which can be done by actively introducing experts into the learning loop, in what is known as human-in-the-loop (HITL) ML. We describe an ML model based on a neural network in which HITL techniques were used to resolve the data bottleneck problem for the treatment of pancreatic cancer. We first augmented the dataset using synthetic cases created by a generative adversarial network. We then launched an active learning (AL) process involving human experts as oracles to label both new cases and cases by the network found to be suspect. This AL process was carried out simultaneously with an interactive ML process in which feedback was obtained from humans in order to develop better synthetic cases for each iteration of training. We discuss the challenges involved in including humans in the learning process, especially in relation to human–computer interaction, which is acquiring great importance in building ML models and can condition the success of a HITL approach. This paper also discusses the methodological approach adopted to address these challenges.This work has been supported by the State Research Agency of the Spanish Government (Grant PID2019-107194GB-I00/AEI/10.13039/501100011033) and by the Xunta de Galicia (Grant ED431C 2022/44), supported in turn by the EU European Regional Development Fund. We wish to acknowledge support received from the Centro de Investigación de Galicia CITIC, funded by the Xunta de Galicia and the European Regional Development Fund (Galicia 2014–2020 Program; Grant ED431G 2019/01).Xunta de Galicia; ED431C 2022/44Xunta de Galicia; ED431G 2019/0
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