Role of prostacyclin in pulmonary hypertension

Date of Acceptance: 11/12/2014 This is an open access article distributed under the terms of the Creative Commons Attribution license CC BY-4.0, which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited.Prostacyclin is a powerful cardioprotective hormone released by the endothelium of all blood vessels. Prostacyclin exists in equilibrium with other vasoactive hormones and a disturbance in the balance of these factors leads to cardiovascular disease including pulmonary arterial hypertension. Since it’s discovery in the 1980s concerted efforts have been made to make the best therapeutic utility of prostacyclin, particularly in the treatment of pulmonary arterial hypertension. This has centred on working out the detailed pharmacology of prostacyclin and then synthesising new molecules based on its structure that are more stable or more easily tolerated. In addition, newer molecules have been developed that are not analogues of prostacyclin but that target the receptors that prostacyclin activates. Prostacyclin and related drugs have without doubt revolutionised the treatment and management of pulmonary arterial hypertension but are seriously limited by side effects within the systemic circulation. With the dawn of nanomedicine and targeted drug or stem cell delivery systems it will, in the very near future, be possible to make new formulations of prostacyclin that can evade the systemic circulation allowing for safe delivery to the pulmonary vessels. In this way, the full therapeutic potential of prostacyclin can be realised opening the possibility that pulmonary arterial hypertension will become, if not curable, a chronic manageable disease that is no longer fatal. This review discusses these and other issues relating to prostacyclin and its use in pulmonary arterial hypertensionPeer reviewedFinal Published versio

Novel Views of Objects from a Single Image

Taking an image of an object is at its core a lossy process. The rich information about the three-dimensional structure of the world is flattened to an image plane and decisions such as viewpoint and camera parameters are final and not easily revertible. As a consequence, possibilities of changing viewpoint are limited. Given a single image depicting an object, novel-view synthesis is the task of generating new images that render the object from a different viewpoint than the one given. The main difficulty is to synthesize the parts that are disoccluded; disocclusion occurs when parts of an object are hidden by the object itself under a specific viewpoint. In this work, we show how to improve novel-view synthesis by making use of the correlations observed in 3D models and applying them to new image instances. We propose a technique to use the structural information extracted from a 3D model that matches the image object in terms of viewpoint and shape. For the latter part, we propose an efficient 2D-to-3D alignment method that associates precisely the image appearance with the 3D model geometry with minimal user interaction. Our technique is able to simulate plausible viewpoint changes for a variety of object classes within seconds. Additionally, we show that our synthesized images can be used as additional training data that improves the performance of standard object detectors

Materials for spintronics: electronic and transport properties of the zigzag graphene nanoribbon/hexagonal boron nitride heterostructures

Abstract High charge carrier mobility in graphene at room temperature creates large potentials for the fabrication of electronic and spintronic devices For creating HEMT (high electron mobility transistor) devices based on ZGNR it is extremely important to study charge carriers mobility. It is necessary to understand and to be able to control the transport properties of electronic devices. Thus, in this work, the effects of the edge and substrate on the band gap, magnetism and transport properties of the charge carriers in 8-ZGNR/h-BN Band structure calculations were performed using the Quantum Espresso For both carrier types in the N-ZGNR/h-BN(0001) heterostructures a common picture is observed: increasing carrier mobility with the decrease of the number of dimers in nanoribbon. For electrons, the mobility increases from . It should also be noted that according to the PBEsol (PBE-D2) calculations the values of the carrier mobility in N-ZGNR/h-BN(0001) heterostructures appear to be 3.5% (7%) higher than in ZGNR without substrate. Thus, the influence of substrate and nanoribbon width on the low-energy spectrum of $\pi$-electrons, local magnetic moments of interface atoms, and the mobilities of charge carriers in N-ZGNR/h-BN(0001) (N = 2, 4, 6, 8) heterostructures have been studied using ab-initio plane-wave pseudopotential method within the DFT framework. Using two different approximations for total energy functional (PBEsol, PBE-D2) we have ascertained the effect of increase of charge carriers mobility by reduction of dimers' number in nanoribbons. Our DFT study have shown that the mobilities of charge carriers in N-ZGNR/h-BN(0001) heterostructures were 5% higher than in suspended nanoribbons. Predicted high electro

Irreducible representations of Upq[gl(2/2)]

The two-parametric quantum superalgebra $U_{pq}[gl(2/2)]$ and its representations are considered. All finite-dimensional irreducible representations of this quantum superalgebra can be constructed and classified into typical and nontypical ones according to a proposition proved in the present paper. This proposition is a nontrivial deformation from the one for the classical superalgebra gl(2/2), unlike the case of one-parametric deformations.Comment: Latex, 8 pages. A reference added in v.

Automatic interpretation of unordered point cloud data for UAV navigation in construction

© 2016 IEEE. The objective of this work is to develop a data processing system that can automatically generate waypoints for navigation of an unmanned aerial vehicle (UAV) to inspect surfaces of structures like buildings and bridges. The input includes data recorded by two 2D laser scanners, orthogonally mounted on the UAV, and an inertial measurement unit (IMU). To achieve the goal, algorithms are developed to process the data collected. They are separated into three major groups: (i) the data registration and filtering to generate a 3D model of the structure and control the density of point clouds for data completeness enhancement; (ii) the surface and obstacle detection to assist the UAV in monitoring tasks; and (iii) the waypoint generation to set the flight path. Experiments on different data sets show that the developed system is able to reconstruct a 3D point cloud of the structure, extract its surfaces and objects, and generate waypoints for the UAV to accomplish inspection tasks

Artificial intelligence-based solutions for coffee leaf disease classification

Coffee is one of the most widely consumed beverages and the quantity and quality of coffee beans depend significantly on the health and condition of coffee plants, particularly their leaves. The automation of coffee leaf disease classification using AI is an essential need, providing not only economic benefits but also contributing to environmental conservation and creating better conditions for sustainable coffee cultivation. Through the application of AI, early disease detection is facilitated, thereby reducing pest and disease control costs, minimizing crop losses, increasing coffee productivity and product quality, and promoting environmental preservation. Many studies have proposed AI algorithms for coffee disease classification. However, numerous algorithms employ classical algorithms, while some utilize deep learning, the current state-of-the-art in computer vision. The challenge lies in the fact that when using deep learning, a substantial amount of data is required for training. The design of deep learning architectures to enhance model accuracy while still working with a small training dataset remains an area of ongoing research. In this study, we propose deep learning-based method for coffee leaf disease classification. We propose the combination of different deep convolutional neural networks to further improve overall classification performance. Early and late fusion have been conducted to evaluate the effectiveness of the pre-trained model. Our experimental results demonstrate that the ensemble method outperforms single-model approaches, achieving high accuracy and precision in BRACOL coffee disease leaf

Mitigating large vibrations of stayed cables in wind and rain hazards

This paper presents an experimental investigation of stayed cable vibrations in dry-wind and rain-wind coupling hazards. To mitigate large vibrations of the cable, the use of spiral wires wrapped around the cable is proposed. By testing two cable models in a wind tunnel in dry and rain conditions for different yaw angles and wind speeds, the effectiveness of using the spiral wires to mitigate large vibrations is clarified. Finally, the paper provides a further understanding of the complex mechanism of wind-induced and rain-wind-induced vibrations. It is found that the low-frequency vortex flows in the wake play a significant role in the excitation of large responses of the cable in high wind speeds. The spiral wires dismiss these low-frequency flows and then reduce the large vibrations

Quantum key distribution using gaussian-modulated coherent states

Quantum continuous variables are being explored as an alternative means to implement quantum key distribution, which is usually based on single photon counting. The former approach is potentially advantageous because it should enable higher key distribution rates. Here we propose and experimentally demonstrate a quantum key distribution protocol based on the transmission of gaussian-modulated coherent states (consisting of laser pulses containing a few hundred photons) and shot-noise-limited homodyne detection; squeezed or entangled beams are not required. Complete secret key extraction is achieved using a reverse reconciliation technique followed by privacy amplification. The reverse reconciliation technique is in principle secure for any value of the line transmission, against gaussian individual attacks based on entanglement and quantum memories. Our table-top experiment yields a net key transmission rate of about 1.7 megabits per second for a loss-free line, and 75 kilobits per second for a line with losses of 3.1 dB. We anticipate that the scheme should remain effective for lines with higher losses, particularly because the present limitations are essentially technical, so that significant margin for improvement is available on both the hardware and software.Comment: 8 pages, 4 figure

Nuclear structure calculations with a separable approximation for Skyrme interactions

A finite rank separable approximation for the quasiparticle RPA calculations with Skyrme interactions that was proposed in our previous work is extended to take into account the coupling between one- and two-phonon terms in the wave functions of excited states. It is shown that characteristics calculated within the suggested approach are in a good agreement with available experimental data.Comment: 6 pages, proceedings of the International Symposium on Physics of Unstable Nuclei (ISPUN02), Halong Bay, Vietnam, November 20-25, 200