Validation of the steady state hover formulation for accurate performance predictions

This paper shows accurate predictions for hover performance regardless of planform geometry, blade-tip Mach number, or disk loading. To prove this statement, sensitivity analyses were performed along with performance predictions for four rotor designs. Planform effects were also studied, such as the blade anhedral, showing the strong sensitivity of the rotor blade performance due to geometric features. The steady-state solution methodology with imposed Froude boundary conditions is shown to give accurate results for relatively coarse grid sizes. This approach leads to reduced computational costs as compared to time-dependent simulations. It is also recognized that, given the current accuracy of the available experimental data, the use of more advanced computational fluid dynamics methods may not be fully justified. To advance the accuracy of modern computational fluid dynamics methods, a comprehensive experimental dataset is required

Сложность алгоритмов криптографической системы Эль–Гамаля и ихэффективность

Objective. - Electrical remodeling as well as atrial contractile dysfunction after the conversion of atrial fibrillation (AF) to sinus rhythm (SR) are mainly caused by a reduction of the inward L-type Ca2+ current (ICaL). We investigated whether the expression of L-type Ca2+-channel subunits was reduced in atrial myocardium of AF patients. Methods. - Right atrial appendages were obtained from patients undergoing coronary artery bypass graft surgery (CAD, n = 35) or mitral valve surgery (MVD, n = 37). Seventeen of the CAD patients and 18 of the MVD patients were in chronic (>3 months) AF, whereas the others were in SR. The protein expression of the L-type Ca2+-channel subunits {alpha}1C and {beta}2 was quantified by western blot analysis. Furthermore, we measured the density of dihydropyridine (DHP)-binding sites of the L-type Ca2+ channel using 3H-PN220-100 as radioligand. Results. - Surprisingly, the {alpha}1C and the {beta}2-subunit expression was not altered in atrial myocardium of AF patients. Also, the DHP-binding site density was unchanged. Conclusion. - The protein expression of the L-type Ca2+-channel subunits {alpha}1C or {beta}2 is not reduced in atrial myocardium of AF patients. Therefore, the reduced ICaL might be due to downregulation of other accessory subunits ({alpha}2{delta}), expression of aberrant subunits, changes in channel trafficking or alterations in channel function

Patterning the neuronal cells via inkjet printing of self-assembled peptides on silk scaffolds

The patterning of neuronal cells and guiding neurite growth are important for neuron tissue engineering and cell-based biosensors. In this paper, inkjet printing has been employed to pattern self-assembled I3QGK peptide nanofibers on silk substrates for guiding the growth of neuron-like PC12 cells. Atomic force microscopy (AFM) confirmed the dynamic self-assembly of I3QGK into nanofiber structures. The printed self-assembled peptide strongly adheres to regenerated silk fibroin (RSF) substrates through charge-charge interactions. It was observed that in the absence of I3QGK, PC12 cells exhibited poor attachment to RSF films, while for RSF surfaces coated or printed with peptide nanofibers, cellular attachment was significantly improved in terms of both cell density and morphology. AFM results revealed that peptide nanofibers can promote the generation of axons and terminal buttons of PC12 cells, indicating that I3QGK nanofibers not only promote cellular attachment but also facilitate differentiation into neuronal phenotypes. Inkjet printing allows complex patterning of peptide nanofibers onto RSF substrates, which enabled us to engineer cell alignment and provide an opportunity to direct axonal development in vitro. The live/dead assay showed that printed I3QGK patterns exhibit no cytotoxicity to PC12 cells demonstrating potential for future nerve tissue engineering applications

Differential pain-related behaviors and bone disease in immunocompetent mouse models of myeloma

Bone pain is a serious and debilitating symptom of multiple myeloma (MM) that impairs the quality of life of patients. The underlying mechanisms of the pain are unknown and understudied, and there is a need for immunocompetent preclinical models of myeloma‐induced bone pain. The aim of this study was to provide the first in‐depth behavioral characterization of an immunocompetent mouse model of MM presenting the clinical disease features: osteolytic bone disease and bone pain. We hypothesized that a widely used syngeneic model of MM, established by systemic inoculation of green fluorescent protein‐tagged myeloma cells (5TGM1‐GFP) in immunocompetent C57Bl/KaLwRijHsd (BKAL) mice, would present pain‐related behaviors. Disease phenotype was confirmed by splenomegaly, high serum paraprotein, and tumor infiltration in the bone marrow of the hind limbs; however, myeloma‐bearing mice did not present pain‐related behaviors or substantial bone disease. Thus, we investigated an alternative model in which 5TGM1‐GFP cells were directly inoculated into the intrafemoral medullary cavity. This localized myeloma model presented the hallmarks of the disease, including high serum paraprotein, tumor growth, and osteolytic bone lesions. Compared with control mice, myeloma‐bearing mice presented myeloma‐induced pain‐related behaviors, a phenotype that was reversed by systemic morphine treatment. Micro‐computed tomography analyses of the myeloma‐inoculated femurs showed bone disease in cortical and trabecular bone. Repeated systemic bisphosphonate treatment induced an amelioration of the nociceptive phenotype, but did not completely reverse it. Furthermore, intrafemorally injected mice presented a profound denervation of the myeloma‐bearing bones, a previously unknown feature of the disease. This study reports the intrafemoral inoculation of 5TGM1‐GFP cells as a robust immunocompetent model of myeloma‐induced bone pain, with consistent bone loss. Moreover, the data suggest that myeloma‐induced bone pain is caused by a combinatorial mechanism including osteolysis and bone marrow denervation. © 2019 The Authors. JBMR Plus published by Wiley Periodicals, Inc. on behalf of American Society for Bone and Mineral Research

Potential benefits of melatonin in organ transplantation: a review

Organ transplantation is a useful therapeutic tool for patients with end-stage organ failure; however, graft rejection is a major obstacle in terms of a successful treatment. Rejection is usually a consequence of a complex immunological and nonimmunological antigen-independent cascade of events, including free radical-mediated ischemia-reperfusion injury (IRI). To reduce the frequency of this outcome, continuing improvements in the efficacy of antirejection drugs are a top priority to enhance the long-term survival of transplant recipients. Melatonin (N-acetyl-5-methoxytryptamine) is a powerful antioxidant and ant-inflammatory agent synthesized from the essential amino acid L-tryptophan; it is produced by the pineal gland as well as by many other organs including ovary, testes, bone marrow, gut, placenta, and liver. Melatonin has proven to be a potentially useful therapeutic tool in the reduction of graft rejection. Its benefits are based on its direct actions as a free radical scavenger as well as its indirect antioxidative actions in the stimulation of the cellular antioxidant defense system. Moreover, it has significant anti-inflammatory activity. Melatonin has been found to improve the beneficial effects of preservation fluids when they are enriched with the indoleamine. This article reviews the experimental evidence that melatonin is useful in reducing graft failure, especially in cardiac, bone, otolaryngology, ovarian, testicular, lung, pancreas, kidney, and liver transplantation

A Class of Effective Field Theory Models of Cosmic Acceleration

We explore a class of effective field theory models of cosmic acceleration involving a metric and a single scalar field. These models can be obtained by starting with a set of ultralight pseudo-Nambu-Goldstone bosons whose couplings to matter satisfy the weak equivalence principle, assuming that one boson is lighter than all the others, and integrating out the heavier fields. The result is a quintessence model with matter coupling, together with a series of correction terms in the action in a covariant derivative expansion, with specific scalings for the coefficients. After eliminating higher derivative terms and exploiting the field redefinition freedom, we show that the resulting theory contains nine independent free functions of the scalar field when truncated at four derivatives. This is in contrast to the four free functions found in similar theories of single-field inflation, where matter is not present. We discuss several different representations of the theory that can be obtained using the field redefinition freedom. For perturbations to the quintessence field today on subhorizon lengthscales larger than the Compton wavelength of the heavy fields, the theory is weakly coupled and natural in the sense of t'Hooft. The theory admits a regime where the perturbations become modestly nonlinear, but very strong nonlinearities lie outside its domain of validity.Comment: 43 pages, 2 figures; Version 3 publication versio

MediLabSecure: A virology and entomology laboratories network for a One Health approach of vector-borne and emerging viruses in the Mediterranean and Black Sea regions

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Neural network parametrization of spectral functions from hadronic tau decays and determination of QCD vacuum condensates

The spectral function $\rho_{V-A}(s)$ is determined from ALEPH and OPAL data on hadronic tau decays using a neural network parametrization trained to retain the full experimental information on errors, their correlations and chiral sum rules: the DMO sum rule, the first and second Weinberg sum rules and the electromagnetic mass splitting of the pion sum rule. Nonperturbative QCD vacuum condensates can then be determined from finite energy sum rules. Our method minimizes all sources of theoretical uncertainty and bias producing an estimate of the condensates which is independent of the specific finite energy sum rule used. The results for the central values of the condensates $O_6$ and $O_8$ are both negative.Comment: 29 pages, 18 ps figure

Antimicrobial activity of Bursera morelensis ramírez essential oil

Background: Bursera morelensis, known as “Aceitillo”, is an endemic tree of Mexico. Infusions made from the bark of this species have been used for the treatment of skin infections and for their wound healing properties. In this work, we present the results of a phytochemical and antimicrobial investigation of the essential oil of B. morelensis.Materials and Methods: The essential oil was obtained by a steam distillation method and analyzed using GC-MS. The antibacterial and antifungal activities were evaluated.Results: GC-MS of the essential oil demonstrated the presence of 28 compounds. The principal compound of the essential oil was α-Phellandrene (32.69%). The essential oil had antibacterial activity against Gram positive and negative strains. The most sensitive strains were S. pneumoniae, V. cholerae (cc) and E. coli (MIC 0.125 mg/mL, MBC 0.25 mg/mL). The essential oil was bactericidal for V. cholera (cc). The essential oil inhibited all the filamentous fungi. F. monilifome (IC50 = 2.27 mg/mL) was the most sensitive fungal strain.Conclusions: This work provides evidence that confirms the antimicrobial activity of the B. morelensis essential oil and this is a scientific support about of traditional uses of this species.Keywords: Essential oil; Medicinal plants; Tehuacan-Cuicatlan Valley; Burseraceae; Burser

Evaluation of dimensionality reduction methods applied to numerical weather models for solar radiation forecasting

The interest in solar radiation prediction has increased greatly in recent times among the scientific community. In this context, Machine Learning techniques have shown their ability to learn accurate prediction models. The aim of this paper is to go one step further and automatically achieve interpretability during the learning process by performing dimensionality reduction on the input variables. To this end, three non standard multivariate feature selection approaches are applied, based on the adaptation of strong learning algorithms to the feature selection task, as well as a battery of classic dimensionality reduction models. The goal is to obtain robust sets of features that not only improve prediction accuracy but also provide more interpretable and consistent results. Real data from the Weather Research and Forecasting model, which produces a very large number of variables, is used as the input. As is to be expected, the results prove that dimensionality reduction in general is a useful tool for improving performance, as well as easing the interpretability of the results. In fact, the proposed non standard methods offer important accuracy improvements and one of them provides with an intuitive and reduced selection of features and mesoscale nodes (around 10% of the initial variables centered on three specific nodes).This work has been partially supported by the projects TIN2014-54583-C2-2-R, TEC2014-52289-R and TEC2016-81900-REDT of the Spanish Interministerial Commission of Science and Technology (MICYT), and by Comunidad Autónoma de Madrid, under project PRICAM P2013ICE-2933