Grey is the new RGB: How good is GAN-based image colorization for image compression?

Multimedia Tools and Applications - GAN-based image colorization techniques are capable of producing highly realistic color in real-time. Subjective assessment of these approaches has demonstrated...     

Partnership ability and co-authorship network of information literacy field

Scientometrics - Scientific collaboration or co-authorship has different forms and can be a factor in creating knowledge and even increasing the quality of scientific works. Beyond the quantity,...     

A Novel Cultural Crowd Model Toward Cognitive Artificial Intelligence

Existing literature shows cultural crowd management has unforeseen issues due to four dynamic elements; time, capacity, speed, and culture. Cross-cultural variations are increasing the complexity level because each mass and event have different characteristics and challenges. However, no prior study has employed the six Hofstede Cultural Dimensions (HCD) for predicting crowd behaviors. This study aims to develop the Cultural Crowd-Artificial Neural Network (CC-ANN) learning model that considers crowd’s HCD to predict their physical (distance and speed) and social (collectivity and cohesion) characteristics. The model was developed towards a cognitive intelligent decision support tool where the predicted characteristics affect the estimated regulation plan’s time and capacity. We designed the experiments as four groups to analyze the proposed model’s outcomes and extract the interrelations between the HCD of crowd’s grouped individuals and their physical and social characteristics. Furthermore, the extracted interrelations were verified with the dataset’s statistical correlation analysis with a P-value < 0.05. Results demonstrate that the predicted crowd’s characteristics were positively/negatively affected by their considered cultural features. Similarly, analyzing outcomes identified the most influential HCD for predicting crowd behavior. The results also show that the CC-ANN model improves the prediction and learning performance for the crowd behavior because the achieved accepted level of accuracy does not exceed 10 to 20 epochs in most cases. Moreover, the performance improved by 90%, 93% respectively in some cases. Finally, all prediction best cases were related to one or more cultural features with a low error of 0.048, 0.117, 0.010, and 0.014 mean squared error, indicating a novel cultural learning model.     

LaTiOxNy Thin Film Model Systems for Photocatalytic Water Splitting: Physicochemical Evolution of the Solid–Liquid Interface and the Role of the Crystallographic Orientation

The size of the band gap and the energy position of the band edges make several oxynitride semiconductors promising candidates for efficient hydrogen and oxygen production under solar light illumination. Intense research efforts dedicated to oxynitride materials have unveiled the majority of their most important properties. However, two crucial aspects have received much less attention: One is the critical issue of compositional/structural surface modifications that occur during operation and how these affect photoelectrochemical performance. The second concerns the relation between electrochemical response and the crystallographic surface orientation of the oxynitride semiconductor. These are indeed topics of fundamental importance, since it is exactly at the surface where the visible‐light‐driven electrochemical reaction takes place. In contrast to conventional powder samples, thin films represent the best model system for these investigations. This study reviews current state‐of‐the‐art oxynitride thin film fabrication and characterization, before focusing on LaTiO₂N, selected as a representative photocatalyst. An investigation of the initial physicochemical evolution of the surface is reported. Then, it is shown that after stabilization the absorbed photon‐to‐current conversion efficiency of epitaxial thin films can differ by about 50% for different crystallographic surface orientations, and be up to 5 times larger than for polycrystalline samples.     

Docking Studies on Binding Modes between the CatechoI-O-Methyltransferase and Catechol Derivatives for Antiparkinson Drug

Inhibition of the enzyme COMT （catechol-O-methyltransferase） is an important approach in the treatment of Parkinson＇s disease. A series of potent catechols for COMT may give insight to develop new ways of antiparkinson drug. COMT inhibitors represent a new class of antiparkinson drugs, when they are coadministered with levodopa. Our goal of research is to study the inhibition of catechol-O-methyltransferase by molecular modeling methods. Different molecular modeling tools are used to perform this work （molecular mechanics, molecular dynamics and molecular docking （molegro virtnaldocker））. The results obtained from this work, into which the inhibition of catechol-O-methyltransferase by molecular modeling methods was elucidated, allow us to conclude that different catechols presents a more optimised inhibition of catechol-O-methyltransferase. The results suggest reducing the severity of Parkinson＇s disease.     

A New Sparse Gaussian Elimination Algorithm and the Niederreiter Linear System for Trinomials over F 2

An important factorization algorithm for polynomials over finite fields was developed by Niederreiter. The factorization problem is reduced to solving a linear system over the finite field in question, and the solutions are used to produce the complete factorization of the polynomial into irreducibles. One charactersistic feature of the linear system arising in the Niederreiter algorithm is the fact that, if the polynomial to be factorized is sparse, then so is the Niederreiter matrix associated with it. In this paper, we investigate the special case of factoring trinomials over the binary field. We develop a new algorithm for solving the linear system using sparse Gaussian elmination with the Markowitz ordering strategy. Implementing the new algorithm to solve the Niederreiter linear system for trinomials over F₂ suggests that, the system is not only initially sparse, but also preserves its sparsity throughout the Gaussian elimination phase. When used with other methods for extracting the irreducible factors using a basis for the solution set, the resulting algorithm provides a more memory efficient and sometimes faster sequential alternative for achieving high degree trinomial factorizations over F₂.     

AASMAn: An adaptive organisational policy for a society of market-based agents

Several formalisms for implementing organisational policies that assign specific roles to each of the agents in a multi-agent system (MAS) have been proposed like the contract net protocol, the social reasoning mechanism and the distributed computational economy. However, as no single organisation is appropriate in all situations, organisation self design had been proposed to allow an organisation of problem solvers to adapt itself to a dynamically changing environment. In this paper we propose an adaptive organisational framework that exploits and integrates the essential features of these existing organisational policies not only to meet the needs of time constrained noncritical applications, where computational load on the organisation cannot be predicted ahead of time, but also to utilise the available system resources efficiently. We also introduce the notion of decommitments and penalties in this approach which was not present in the original contract net protocol.     

Quantitating Fluorescence Intensity From Fluorophores: Practical Use of MESF Values

The present work uses fluorescein as the model fluorophore and points out critical steps in the use of MESF (Molecules of Equivalent Soluble Fluorophores) values for quantitative flow cytometric measurements. It has been found that emission spectrum matching between a reference solution and an analyte and normalization by the corresponding extinction coefficient are required for quantifying fluorescence signals using flow cytometers. Because of the use of fluorescein, the pH value of the medium is also critical for accurate MESF assignments. Given that the emission spectrum shapes of microbead suspensions and stained biological cells are not significantly different, the percentage of error due to spectrum mismatch is estimated. We have also found that the emission spectrum of a microbead with a seven-methylene linker between the fluorescein and the bead surface (bead7) provides the best match with the spectra from biological cells. Therefore, bead7 is potentially a better calibration standard for flow cytometers than the existing one that is commercially available and used in the present study.     

Generalisation de la theorie de l'electrode dite “electrode a disque-anneau’, dans un fluide d'otswald. Calcul des facteurs de collection

Supposing that in the diffusional boundary layer, the tangential component V_x and radial component V_r of the relative fluid velocity are respectively written in the form V_xS₀x^by and V_ra₀r^by (S₀, a₀ are independent coefficient of the normal coordinate y, tengential coordinate x, radial coordinate r;b is a numerical exponent that is expressed in terms of the behaviour law and of the flow), the authors calculate a analytical expression for the collection factor N defined as the quotient, with the sign inverted, of the limiting diffusional flux on the downstream active surface by the limiting diffusional flux on the upstream active surface. This factor N is dependent only on geometrical characteristics of system and on exponent b.