Determination of dyers’ perceived components of colour difference (depth,brightness and hue) between two similar colours from their spectral reflectance values

The partitioning of colour differences into ΔL^*, ΔC^* and ΔH^* is not directly equivalent to the dyer’s method of partitioning. The dyer’s method involves separation into the components of depth (ΔD), brightness (ΔB) and hue (ΔH), of which only hue difference has a qualitative (and quantitative) equivalent in the CIELAB system. Depth and brightness are important terms to dyers. Depth is related to the amount of dye taken up by a textile material and brightness to that component of colour difference that is neither depth nor hue. Brightness is best defined as the opposite of dullness, dullness being related to the amount of neutral grey present in the colour. An algorithm, called the Wardman–Smith–Farooq algorithm, has been developed to compute the dyers’ variables of ΔD,ΔB and ΔH from spectral reflectance values, enabling dyers to take full advantage of colorimetry. The algorithm is based on extensive experimental work to map surfaces of constant visual depth through the colour space and this paper describes the methodology of the calculation. The correlations of the values of ΔD,ΔB and ΔH, determined using the Wardman–Smith–Farooq algorithm with other empirical models for 117 sample pairs, are given.     

Automatic detection of Moroccan coastal upwelling zones using sea surface temperature images

An efficient unsupervised method is developed for automatic segmentation of the area covered by upwelling waters in the coastal ocean of Morocco using the Sea Surface Temperature (SST) satellite images. The proposed approach first uses the two popular unsupervised clustering techniques, k-means and fuzzy c-means (FCM), to provide different possible classifications to each SST image. Then several cluster validity indices are combined in order to determine the optimal number of clusters, followed by a cluster fusion scheme, which merges consecutive clusters to produce a first segmentation of upwelling area. The region-growing algorithm is then used to filter noisy residuals and to extract the final upwelling region. The performance of our algorithm is compared to a popular algorithm used to detect upwelling regions and is validated by an oceanographer over a database of 92 SST images covering each week of the years 2006 and 2007. The results show that our proposed method outperforms the latter algorithm, in terms of segmentation accuracy and computational efficiency.     

A New Method for Sentiment Analysis Using Contextual Auto-Encoders

Sentiment analysis, a hot research topic, presents new challenges for understanding users’ opinions and judgments expressed online. They aim to classify the subjective texts by assigning them a polarity label. In this paper, we introduce a novel machine learning framework using auto-encoders network to predict the sentiment polarity label at the word level and the sentence level. Inspired by the dimensionality reduction and the feature extraction capabilities of the auto-encoders, we propose a new model for distributed word vector representation “PMI-SA” using as input pointwise-mutual-information “PMI” word vectors. The resulted continuous word vectors are combined to represent a sentence. An unsupervised sentence embedding method, called Contextual Recursive Auto-Encoders “CoRAE”, is also developed for learning sentence representation. Indeed, CoRAE follows the basic idea of the recursive auto-encoders to deeply compose the vectors of words constituting the sentence, but without relying on any syntactic parse tree. The CoRAE model consists in combining recursively each word with its context words (neighbors’ words: previous and next) by considering the word order. A support vector machine classifier with fine-tuning technique is also used to show that our deep compositional representation model CoRAE improves significantly the accuracy of sentiment analysis task. Experimental results demonstrate that CoRAE remarkably outperforms several competitive baseline methods on two databases, namely, Sanders twitter corpus and Facebook comments corpus. The CoRAE model achieves an efficiency of 83.28% with the Facebook dataset and 97.57% with the Sanders dataset.     

Electrosynthesis and structural characterization of a novel aryl ether trimer

The structure of a novel trimer formed by three p-tert-butyl anisole moieties via the controlled potential electrolysis of p-tert-butyl anisole was determined by X-ray diffraction method. By cyclic voltammetry, we report a multistep electron transfer, each followed by a chemical reaction, resulting in an ECECEC mechanism. Preparative scale oxidation of p-tert-butyl anisole in dry acetonitrile leads to its two first oligomers. The symmetrical dimer, 2,2′-dimethoxy-5,5′-di-tert-butylbiphenyl, shows that the favored coupling sites are those in the ortho position of the methoxy group. The title compound, namely the 1-methoxy-bis-2,3-(2′-methoxy-5′-tert-butylphenyl)-4-tert-butylbenzene crystallizes in triclinic space group P-1 with a = 10.571(3) Å, b = 11.739(1) Å, c = 12.733(2) Å, α = 74.64(1)°, β = 88.71(2)°, γ = 76.58(2)°, V = 1480.8(5) Å³, and Z = 2. The structural analysis reveals that two p-tert-butyl anisole moieties are linked in ortho position on a third p-tert-butyl anisole fragment.     

Investigation of buoyancy-driven flow and heat transfer in a trapezoidal cavity filled with water–Cu nanofluid

A numerical study is conducted to investigate the transport mechanism of free convection in a trapezoidal enclosure filled with water–Cu nanofluid. The horizontal walls of the enclosure are insulated while the inclined walls are kept at constant but different temperatures. The numerical approach is based on the finite element technique with Galerkin's weighted residual simulation. Solutions are obtained for a wide range of the aspect ratio (AR) and Prandtl number (Pr) with Rayleigh number (Ra = 10⁵) and solid volume fraction (? = 0.05). The streamlines, isotherm plots and the variation of the average Nusselt number at the left hot wall are presented and discussed. It is found that both AR and Pr affect the fluid flow and heat transfer in the enclosure. A correlation is also developed graphically for the average Nusselt number as a function of the Prandtl number as well as the cavity aspect ratio.     

SURFACE EXCITATION PARAMETER IN QUANTITATIVE SURFACE ANALYSIS BY ELECTRON SPECTROSCOPY

The investigation of influence of surface effects on the energy spectra of electrons is essential for comprehensive understanding of electron-solid interactions as well as quantitative analysis. The accuracy of the analysis depends on the models for elastic and inelastic interactions. Electrons impinging on a solid or escaping from it suffer losses in the surface layer. The energy loss spectra therefore have contributions from surface excitations. The role of surface excitations is characterized by surface excitation parameter (SEP), which indicates the number of surface plasmons created by an electron crossing the surface. The imaginary part of complex self-energy of an electron is related to the energy.‘ loss cross section. SEP is numerically computed using self-energy formalism and compared with the results as described and calculated by different workers.     

ENERGY-LOSS FUNCTIONS DERIVED FROM REELS SPECTRA FOR ALUMINUM

The effective energy loss functions for Al have been derived from differential inverse inelastic mean free path based on the extended Landau approach. It has been revealed that the effective energy loss function is very close in value to the theoretical surface energy loss function in the lower energy loss region but graduaUy approaches the theoretical bulk energy loss function in the higher energy loss region. Moreover, the intensity corresponding to surface excitation in effective energy loss functions decreases with the increase of primary electron energy. These facts show that the present effective energy loss function describes not only surface excitation but also bulk excitation. At last, REELS spectra simulated by Monte Carlo method based on use of the effective energy loss functions has reproduced the experimental REELS spectra with considerable success.     

From Blood to Regenerative Tissue: How Autologous Platelet-Rich Fibrin Can Be Combined with Other Materials to Ensure Controlled Drug and Growth Factor Release

The purpose of this review is to examine the latest literature on the use of autologous platelet-rich fibrin as a drug and growth factor carrier system in maxillofacial surgery. Autologous platelet-rich fibrin (PRF) is a unique system that combines properties such as biocompatibility and biodegradability, in addition to containing growth factors and peptides that provide tissue regeneration. This opens up new horizons for the use of all beneficial ingredients in the blood sample for biomedical purposes. By itself, PRF has an unstable effect on osteogenesis: therefore, advanced approaches, including the combination of PRF with materials or drugs, are of great interest in clinics. The main advantage of drug delivery systems is that by controlling drug release, high drug concentrations locally and fewer side effects within other tissue can be achieved. This is especially important in tissues with limited blood supply, such as bone tissue compared to soft tissue. The ability of PRF to degrade naturally is considered an advantage for its use as a “warehouse” of controlled drug release systems. We are focusing on this concentrate, as it is easy to use in manipulations and can be delivered directly to the surgical site. The target audience for this review are researchers and medical doctors who are involved in the development and research of PRFs further studies. Likewise, surgeons who use PRF in their work to treat patients and who advice patients to take the medicine orally.     

The NIP Genes in Sugar Beet: Underlying Roles in Silicon Uptake and Growth Improvement

Silicon - Silicon (Si) can stimulate plant growth and stress resistance. This study aimed at elucidating the physiological responses and molecular characterization of different NIP (nodulin 26-like...