MHD mixed convection of a Cu–water nanofluid flow through a channel with an open trapezoidal cavity and an elliptical obstacle

In the current work, numerical simulations are achieved to study the properties and the characteristics of fluid flow and heat transfer of (Cu–water) nanofluid under the magnetohydrodynamic effects in a horizontal rectangular canal with an open trapezoidal enclosure and an elliptical obstacle. The cavity lower wall is grooved and represents the heat source while the obstacle represents a stationary cold wall. On the other hand, the rest of the walls are considered adiabatic. The governing equations for this investigation are formulated, nondimensionalized, and then solved by Galerkin finite element approach. The numerical findings were examined across a wide range of Richardson number (0.1 ≤ Ri ≤ 10), Reynolds number (1 ≤ Re ≤ 125), Hartmann number (0 ≤ Ha ≤ 100), and volume fraction of nanofluid (0 ≤ φ ≤ 0.05). The current study's findings demonstrate that the flow strength increases inversely as the Reynolds number rises, which pushes the isotherms down to the lower part of the trapezoidal cavity. The Nu_avg rises as the Ri rise, the maximum Nu_avg = 10.345 at Ri = 10, Re = 50, ϕ = 0.05, and Ha = 0; however, it reduces with increasing Hartmann number. Also, it increase by increasing ϕ, at Ri = 10, the Nu_avg increased by 8.44% when the volume fraction of nanofluid increased from (ϕ = 0–0.05).     

A PID-incorporated Latent Factorization of Tensors Approach to Dynamically Weighted Directed Network Analysis

A large-scale dynamically weighted directed network (DWDN) involving numerous entities and massive dynamic interaction is an essential data source in many big-data-related applications, like in a terminal interaction pattern analysis system (TIPAS). It can be represented by a high-dimensional and incomplete (HDI) tensor whose entries are mostly unknown. Yet such an HDI tensor contains a wealth knowledge regarding various desired patterns like potential links in a DWDN. A latent factorization-of-tensors (LFT) model proves to be highly efficient in extracting such knowledge from an HDI tensor, which is commonly achieved via a stochastic gradient descent (SGD) solver. However, an SGD-based LFT model suffers from slow convergence that impairs its efficiency on large-scale DWDNs. To address this issue, this work proposes a proportional-integral-derivative (PID)-incorporated LFT model. It constructs an adjusted instance error based on the PID control principle, and then substitutes it into an SGD solver to improve the convergence rate. Empirical studies on two DWDNs generated by a real TIPAS show that compared with state-of-the-art models, the proposed model achieves significant efficiency gain as well as highly competitive prediction accuracy when handling the task of missing link prediction for a given DWDN.      

Antimicrobial residues survey by LC-MS in food-producing animals in Lebanon

ABSTRACT

The treatment of animals with antimicrobial products may lead to the contamination of edible tissues by their residues, which may represent a risk to human health. Therefore, this study aimed to determine the level of antimicrobial residues in food-producing animals (chicken, beef, and milk) in Lebanon. A total of 310 samples were collected and analysed using an LC-MS/MS for the determination of 48 compounds belonging to different families in order to map their compliance according to the European Commission decision 2002/657/EC. Results show that 60% of the analysed samples were not contaminated by any residue, while 12% presented a concentration higher than the MRLs for tetracyclines, sulphonamides, quinolones, and macrolides. Results revealed that chicken were the most contaminated by antimicrobial residues, when compared to beef and milk. The obtained results demonstrate the uncontrolled use of antimicrobials in some Lebanese farms and claim for better management of livestock.     

Dynamic model of online information quality perceptions and impacts: a literature review

This paper reviews the literature related to the concept of information quality (IQ) in the context of the online environment to understand how it has been conceptualised in the Information Systems (IS) literature, to identify gaps in the literature, and to make recommendations for future research. This study also extends the Information Processing Model (IPM) and proposes a novel dynamic model of online IQ perceptions and impacts. To understand the online IQ construct, an in-depth review of the literature is conducted. Overall, we reviewed 508 journal articles published between 1995 and 2016. This study found that there is a substantial gap in the IS literature in regards to a full understanding of the online IQ construct and its relation with the IPM. More research is needed to understand the way individuals process and respond to online information. Further, although the importance of context in theory development has been emphasised in the literature, very few empirical articles have explored the impact of contextual factors on the IPM as well as perceived online IQ. The findings provide online vendors with important guidelines that should be considered to motivate individuals to acquire more information from their websites that could lead to more satisfied and loyal users.     

A Q-learning approach for machine-type communication random access in LTE-Advanced

Telecommunication Systems - Due to the wide proliferation of the 3GPP long term evolution (LTE) and LTE-Advanced systems as the air interface for 4th generation (4G) wireless systems and beyond,...     

Coupled particle swarm optimization method with genetic algorithm for the static–dynamic performance of the magneto-electro-elastic nanosystem

As a first attempt, Fourier series expansion (FSE), particle swarm optimization (PSO), and genetic algorithm (GA) methods are coupled for analysis of the static–dynamic performance and propagated waves in the magneto-electro-elastic (MEE) nanoplate. The FSE method is presented for solving the motion equations of the MEE nanoplate. For increasing the performance of genetic algorithms for solving the problem, the particle swarm optimization technique is added as an operator of the GA. Accuracy, convergence, and applicability of the proposed mixed approach are shown in the results section. Also, we prove that for obtaining the convergence results of the PSO and GA, we should consider more than 16 iterations. Finally, it is shown that if designers consider the presented algorithm in their model, the results of phase velocity of the nanosystem will be increased by 27%. A useful suggestion is that there is a region the same as a trapezium in which there are no effects from magnetic and electric potential of the MEE face sheet on the phase velocity of the smart nanoplate, and the region will be bigger by increasing the wavenumber.

     

Thermal Management Enables Bright and Stable Perovskite Light-Emitting Diodes

The performance of lead-halide perovskite light-emitting diodes (LEDs) has increased rapidly in recent years. However, most reports feature devices operated at relatively small current densities (<500 mA cm⁻²) with moderate radiance (<400 W sr⁻¹ m⁻²). Here, Joule heating and inefficient thermal dissipation are shown to be major obstacles toward high radiance and long lifetime. Several thermal management strategies are proposed in this work, such as doping charge-transport layers, optimizing device geometry, and attaching heat spreaders and sinks. Combining these strategies, high-performance perovskite LEDs are demonstrated with maximum radiance of 2555 W sr⁻¹ m⁻², peak external quantum efficiency (EQE) of 17%, considerably reduced EQE roll-off (EQE > 10% to current densities as high as 2000 mA cm⁻²), and tenfold increase in operational lifetime (when driven at 100 mA cm⁻²). Furthermore, with proper thermal management, a maximum current density of 2.5 kA cm⁻² and an EQE of ≈1% at 1 kA cm⁻² are shown using electrical pulses, which represents an important milestone toward electrically driven perovskite lasers.     

Convolutional neural networks for the classification of chest X-rays in the IoT era

Multimedia Tools and Applications - Chest X-ray medical imaging technology allows the diagnosis of many lung diseases. It is known that this technology is frequently used in hospitals, and it is...