Spread of biological invasions: The experience of Tilapia species in the Shadegan Wetland, southwest of Iran

The status of non-native tilapia species was evaluated by sampling campaigns in fishing grounds in the central part of the Shadegan Wetland, southwest Iran in 2014–15 (with follow-up in 2019). Considering a high percentage of relative species abundance, the tilapia species (Coptodon zillii and Oreochromis aureus) are well established in the wetland. As the management plans of such species are difficult and expensive, prevention of the introduction of these species to other water bodies is highly recommended.Hussein Valikhani, Asghar Abdoli, Farshad Nejat, Milad Khosravi, Kamal Khezri, Bahram H. Kiab

Activating Natural Killer Cell Receptors, Selectins, and Inhibitory Siglecs Recognize Ebolavirus Glycoprotein

Expression of the extensively glycosylated Ebolavirus glycoprotein (EBOV-GP) induces physical alterations of surface molecules and plays a crucial role in viral pathogenicity. Here we investigate the interactions of EBOV-GP with host surface molecules using purified EBOV-GP, EBOV-GP-transfected cell lines, and EBOV-GP-pseudotyped lentiviral particles. Subsequently, we wanted to examine which receptors are involved in this recognition by binding studies to cells transfected with the EBOV-GP as well as to recombinant soluble EBOV-GP. As the viral components can also bind to inhibitory receptors of immune cells (e.g., Siglecs, TIM-1), they can even suppress the activity of immune effector cells. Our data show that natural killer (NK) cell receptors NKp44 and NKp46, selectins (CD62E/P/L), the host factors DC-SIGNR/DC-SIGN, and inhibitory Siglecs function as receptors for EBOV-GP. Our results show also moderate to strong avidity of homing receptors (P-, L-, and E-selectin) and DC-SIGNR/DC-SIGN to purified EBOV-GP, to cells transfected with EBOV-GP, as well as to the envelope of a pseudotyped lentiviral vector carrying the EBOV-GP. The concomitant activation and inhibition of the immune system exemplifies the evolutionary antagonism between the immune system and pathogens. Altogether these interactions with activating and inhibitory receptors result in a reduced NK cell-mediated lysis of EBOV-GP-expressing cells. Modulation of these interactions may provide new strategies for treating infections caused by this virus.publishedVersio

Application of Linear Discriminant Analysis in Dimensionality Reduction for Hand Motion Classification

The classification of upper-limb movements based on surface electromyography (EMG) signals is an important issue in the control of assistive devices and rehabilitation systems. Increasing the number of EMG channels and features in order to increase the number of control commands can yield a high dimensional feature vector. To cope with the accuracy and computation problems associated with high dimensionality, it is commonplace to apply a processing step that transforms the data to a space of significantly lower dimensions with only a limited loss of useful information. Linear discriminant analysis (LDA) has been successfully applied as an EMG feature projection method. Recently, a number of extended LDA-based algorithms have been proposed, which are more competitive in terms of both classification accuracy and computational costs/times with classical LDA. This paper presents the findings of a comparative study of classical LDA and five extended LDA methods. From a quantitative comparison based on seven multi-feature sets, three extended LDA-based algorithms, consisting of uncorrelated LDA, orthogonal LDA and orthogonal fuzzy neighborhood discriminant analysis, produce better class separability when compared with a baseline system (without feature projection), principle component analysis (PCA), and classical LDA. Based on a 7-dimension time domain and time-scale feature vectors, these methods achieved respectively 95.2% and 93.2% classification accuracy by using a linear discriminant classifier

Computational Fluid Dynamics Simulation of Gas-Solid Hydrodynamics in a Bubbling Fluidized-Bed Reactor: Effects of Air Distributor, Viscous and Drag Models

In this work, we employed a computational fluid dynamics (CFD)-based model with a Eulerian multiphase approach to simulate the fluidization hydrodynamics in biomass gasification processes. Air was used as the gasifying/fluidizing agent and entered the gasifier at the bottom which subsequently fluidized the solid particles inside the reactor column. The momentum exchange related to the gas-phase was simulated by considering various viscous models (i.e., laminar and turbulence models of the re-normalisation group (RNG), k-ε and k-ω). The pressure drop gradient obtained by employing each viscous model was plotted for different superficial velocities and compared with the experimental data for validation. The turbulent model of RNG k-Ɛ was found to best represent the actual process. We also studied the effect of air distributor plates with different pore diameters (2, 3 and 5 mm) on the momentum of the fluidizing fluid. The plate with 3-mm pores showed larger turbulent viscosities above the surface. The effects of drag models (Syamlal–O’Brien, Gidaspow and energy minimum multi-scale method (EMMS) on the bed’s pressure drop as well as on the volume fractions of the solid particles were investigated. The Syamlal–O’Brien model was found to forecast bed pressure drops most consistently, with the pressure drops recorded throughout the experimental process. The formation of bubbles and their motion along the gasifier height in the presence of the turbulent flow was seen to follow a different pattern from with the laminar flow.Ministry of Higher Education (MOHE) Malaysia; Engineering and Physical Sciences Research Counci

O-C Study of 545 Lunar Occultations from 13 Double Stars

International audienceIn this article, we have studied the reports of lunar occultations by this project observation's teams (named APTO) in comparison with other observations of the objects. Thirteen binary stars were selected for this study. All the previous observations of these stars were also collected. Finally, an analysis of O-C of all reports were performed

A study of some fundamental physicochemical variables on the morphology of mesoporous silica nanoparticles MCM-41 type

[EN] All variables affecting the morphology of mesoporous silica nanoparticles (MSN) should be carefully analyzed in order to truly tailored design their mesoporous structure according to their final use. Although complete control on MCM-41 synthesis has been already claimed, reproducibility and repeatability of results remain a big issue due to the lack of information reported in literature. Stirring rate, reaction volume, and system configuration (i.e., opened or closed reactor) are three variables that are usually omitted, making the comparison of product characteristics difficult. Specifically, the rate of solvent evaporation is seldom disclosed, and its influence has not been previously analyzed. These variables were systematically studied in this work, and they were proven to have a fundamental impact on final particle morphology. Hence, a high degree of circularity (C = 0.97) and monodispersed particle size distributions were only achieved when a stirring speed of 500 rpm and a reaction scale of 500 mL were used in a partially opened system, for a 2 h reaction at 80 degrees C. Well-shaped spherical mesoporous silica nanoparticles with a diameter of 95 nm, a pore size of 2.8 nm, and a total surface area of 954 m(2) g(-1) were obtained. Final characteristics made this product suitable to be used in biomedicine and nanopharmaceutics, especially for the design of drug delivery systems.This study was funded partially by Departamento Administrativo de Ciencia Tecnología e Innovación–COLCIENCIAS (recipient, Angela A. Beltrán-Osuna); Ministerio de Economía y Competitividad, MINECO, research number MAT2016-76039-C4-1-R (Recipient, José L. Gómez-Ribelles); and Universidad Nacional de Colombia, grant number DIB201010021438 (Recipient, Jairo E. Perilla).Beltrán-Osuna, A.; Gómez Ribelles, JL.; Perilla-Perilla, JE. (2017). 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Phase transition in Random Circuit Sampling

Quantum computers hold the promise of executing tasks beyond the capability of classical computers. Noise competes with coherent evolution and destroys long-range correlations, making it an outstanding challenge to fully leverage the computation power of near-term quantum processors. We report Random Circuit Sampling (RCS) experiments where we identify distinct phases driven by the interplay between quantum dynamics and noise. Using cross-entropy benchmarking, we observe phase boundaries which can define the computational complexity of noisy quantum evolution. We conclude by presenting an RCS experiment with 70 qubits at 24 cycles. We estimate the computational cost against improved classical methods and demonstrate that our experiment is beyond the capabilities of existing classical supercomputers

Measurement-Induced State Transitions in a Superconducting Qubit: Within the Rotating Wave Approximation

Superconducting qubits typically use a dispersive readout scheme, where a resonator is coupled to a qubit such that its frequency is qubit-state dependent. Measurement is performed by driving the resonator, where the transmitted resonator field yields information about the resonator frequency and thus the qubit state. Ideally, we could use arbitrarily strong resonator drives to achieve a target signal-to-noise ratio in the shortest possible time. However, experiments have shown that when the average resonator photon number exceeds a certain threshold, the qubit is excited out of its computational subspace, which we refer to as a measurement-induced state transition. These transitions degrade readout fidelity, and constitute leakage which precludes further operation of the qubit in, for example, error correction. Here we study these transitions using a transmon qubit by experimentally measuring their dependence on qubit frequency, average photon number, and qubit state, in the regime where the resonator frequency is lower than the qubit frequency. We observe signatures of resonant transitions between levels in the coupled qubit-resonator system that exhibit noisy behavior when measured repeatedly in time. We provide a semi-classical model of these transitions based on the rotating wave approximation and use it to predict the onset of state transitions in our experiments. Our results suggest the transmon is excited to levels near the top of its cosine potential following a state transition, where the charge dispersion of higher transmon levels explains the observed noisy behavior of state transitions. Moreover, occupation in these higher energy levels poses a major challenge for fast qubit reset