Covalent triazine framework with efficient photocatalytic activity in aqueous and solid media

Covalent triazine frameworks (CTFs) have been recently employed for visible light-driven photocatalysis due to their unique optical and electronic properties. However, the usually highly hydrophobic nature of CTFs, which originates from their overall aromatic backbone, leads to limitations of CTFs for applications in aqueous media. In this study, we aim to extend the range of the application media of CTFs and design hybrid material of a CTF and mesoporous silica (SBA-15) for efficient photocatalysis in aqueous medium. A thiophene-containing CTF was directly synthesized in mesopores of SBA-15. Due to the high surface area and the added hydrophilic properties by silica, the hybrid material demonstrated excellent adsorption of organic molecules in water. This leads not only to high photocatalytic performance of the hybrid material for the degradation of organic dyes in water, but also for efficient photocatalysis in solvent-free and solid state. Furthermore, the reusability, stability and easy recovery of the hybrid material offers promising metal-free heterogeneous photocatalyst for broader applications in different reaction media.     

Boolean factors as a means of clustering of interestingness measures of association rules

Measures of interestingness play a crucial role in association rule mining. An important methodological problem, on which several papers appeared in the literature, is to provide a reasonable classification of the measures. In this paper, we explore Boolean factor analysis, which uses formal concepts corresponding to classes of measures as factors, for the purpose of clustering of the measures. Unlike the existing studies, our method reveals overlapping clusters of interestingness measures. We argue that the overlap between clusters is a desired feature of natural groupings of measures and that because formal concepts are used as factors in Boolean factor analysis, the resulting clusters have a clear meaning and are easy to interpret. We conduct three case studies on clustering of measures, provide interpretations of the resulting clusters and compare the results to those of the previous approaches reported in the literature.     

A new fast motion estimation algorithm using fast mode decision for high-efficiency video coding standard

High-efficiency video coding is the latest standardization effort of the International Organization for Standardization and the International Telecommunication Union. This new standard adopts an exhaustive algorithm of decision based on a recursive quad-tree structured coding unit, prediction unit, and transform unit. Consequently, an important coding efficiency may be achieved. However, a significant computational complexity is resulted. To speed up the encoding process, efficient algorithms based on fast mode decision and optimized motion estimation were adopted in this paper. The aim was to reduce the complexity of the motion estimation algorithm by modifying its search pattern. Then, it was combined with a new fast mode decision algorithm to further improve the coding efficiency. Experimental results show a significant speedup in terms of encoding time and bit-rate saving with tolerable quality degradation. In fact, the proposed algorithm permits a main reduction that can reach up to 75 % in encoding time. This improvement is accompanied with an average PSNR loss of 0.12 dB and a decrease by 0.5 % in terms of bit-rate.     

Real-time quality authentication of honey using atmospheric pressure chemical ionisation mass spectrometry (APCI-MS)

The aim of this study was to use gas chromatography-mass spectrometry (GC-MS) and APCI-MS techniques to detect adulteration in honey. The key volatile compounds in the headspace of the adulterated honey were marked by GC-MS and their representative fragment ions were utilised in scanning honey samples using the real-time APCI-MS system. The PLS models validated using independent data sets resulted in coefficient of the determination () of 0.97 and 0.96 and root mean square error in prediction (RMSEP) of 2.62 and 2.45 for the GC-MS and APCI-MS data sets respectively. The most efficient volatiles from GC-MS analysis and their corresponding fragment ions m/z from APCI-MS data analysis were then identified and used to develop new PLS models to predict the level of adulteration. The best PLS model gave of 0.95 and RMEP of 2.60% in the independent validation set indicating that the model was very accurate in predicting the level of adulteration.     

A 2D finite element analysis of the effect of numerical parameters on the reliability of Ti6Al4V machining modeling

Abstract

The numerical analysis, based on the finite element modeling (FEM), presents nowadays an efficient computational tool. It allows a better understanding of several thermo-mechanical phenomena involved during the machining process. However, its reliability heavily depends on the accurate definition of the numerical model. In this regard, a FE analysis focused on the 2D modeling of the Ti6Al4V dry orthogonal machining was carried out in this study. The relevance of different numerical meshing approaches and finite elements topologies was studied. The effect of the friction coefficient on the numerical chip morphology, its geometry, the cutting and the feed forces was investigated. The adequacy of several compared adaptive meshing approaches, in terms of the modeling of severe contact conditions taking place around the cutting-edge radius, was underlined in the current study. However, numerical serrated chips, closer to the experimental ones, were only predicted when the pure Lagrangian formulation was adopted and a proper determination of the failure energy was carried out. The definition of different mesh topologies highlighted the efficiency of the 4-node quadrangular mesh, with a suitable edge length, in increasing the agreement with the experimental data, while reducing the computing times.     

Build-Operate-Transfer in Infrastructure Projects in the United States

While the infrastructure in the United States is in need of large and immediate investment, the funds provided by public agencies are not nearly sufficient to face such a challenge. Build-operate-transfer (BOT) is a delivery/financing system that can be a solution to this problem. In this system, a private sponsor finances the design, construction, maintenance, and operation of a public project for a specified concession period, at the end of which it transfers ownership to the government agency, hopefully after recouping its costs and achieving profits. A questionnaire survey of large municipalities and state departments of transportation was conducted to determine the extent to which they are using BOT in their large projects, to investigate the implementation of BOT, and the reasons why some government agencies avoid using BOT. The findings indicate that very few agencies use BOT. The reasons why most do not use BOT were reported by the respondents to be the availability of proven alternatives and enough funds, the existence of political barriers, and resistance to change both on the part of government agencies and private sponsors. When government agencies and private sponsors explore the use of BOT, they should avoid the pitfalls perceived by the respondents in this study.     

Analytical evaluation of six monovarietal virgin olive oils from Northern Tunisia

The characterization of virgin olive oils from six Tunisian cultivars, namely Chétoui, Ain Jarboua, Jarboui, Regregui, Rekhami and Neb Jmel, grown in Nebeur (a region of the Kef) was carried out. These cultivars dominate their natural habitats, but with the exception of the Chétoui cultivar they are only scattered throughout the nation. Several analytical parameters were evaluated; these include quality index, fatty acid composition, chlorophylls, carotenoids, sterols, α‐tocopherol and phenolic compounds. Their relationship with oxidative stability was also tested. The main phenols found were tyrosol, hydroxytyrosol, the dialdehydic form of elenolic acid linked to tyrosol and hydroxytyrosol, oleuropein aglycon and pinoresinol. These phenolic compounds, the colorimetric total phenol content and o‐diphenols showed significant correlations with oxidative stability. Furthermore, most of the analytical parameters of the oils that were determined in this study were greatly influenced by genetic factors (cultivar).     

Physiological and behavioral responses of Orchestia gammarellus (Amphipoda,Talitridae) towards trace elements contamination soil

Effects of trace elements on the hepatopancreas ultrastructure and on the locomotor activity rhythm were investigated in the amphipod talitrid Orchestia gammarellus collected from Bizerte lagoon banks situated in the north of Tunisia. Animals were exposed to a series of contaminated soil with different concentrations of cadmium and zinc. The locomotor activity rhythm was studied under constant darkness. Histopathological analysis showed that the trace elements, especially the Cd, induced significant changes in the morphology and in the ultrastructural organization of hepatopancreatic cells. The significant alterations obtained were dose dependent. Concerning the behavioral response, results revealed the presence of two components whatever the experimental conditions. In addition, a great inter-individual variability of the locomotor rhythm was observed. Patterns were in majority bimodal for the control individuals and became unimodal and multimodal when exposed under Cd and Zn, respectively. Furthermore, ultradian and circadian periods were determined. The circadian period lengthened after Zn exposure. In addition, the locomotor activity rhythm was more stable for control individuals. However, those exposed to Cd were less active.     

Effective Level Set Image Segmentation With a Kernel Induced Data Term

This study investigates level set multiphase image segmentation by kernel mapping and piecewise constant modeling of the image data thereof. A kernel function maps implicitly the original data into data of a higher dimension so that the piecewise constant model becomes applicable. This leads to a flexible and effective alternative to complex modeling of the image data. The method uses an active curve objective functional with two terms: an original term which evaluates the deviation of the mapped image data within each segmentation region from the piecewise constant model and a classic length regularization term for smooth region boundaries. Functional minimization is carried out by iterations of two consecutive steps: 1) minimization with respect to the segmentation by curve evolution via Euler-Lagrange descent equations and 2) minimization with respect to the regions parameters via fixed point iterations. Using a common kernel function, this step amounts to a mean shift parameter update. We verified the effectiveness of the method by a quantitative and comparative performance evaluation over a large number of experiments on synthetic images, as well as experiments with a variety of real images such as medical, satellite, and natural images, as well as motion maps.