Magnetically Modified Waste Bark of Aegle marmelos Tree as a Promising Biosorbent for Uranium(VI) Sorption

Radiochemistry - Magnetically modified waste bark of the Aegle marmelos tree was prepared by using green synthesis method and was used in a batch system for U(VI) removal from aqueous solution. The...     

Power Input Prediction in Agitated Gas‐Liquid Contactors with Non‐coalescent Batch

Volumetric mass transfer coefficients, k_La, just as power input are considered as essential parameters for mechanically agitated gas‐liquid contactors in relation to their optimization and design. The knowledge of power input is crucial for the prediction of other mass transfer characteristics. A power input correlation is created for the industrial design of the process with a non‐coalescent batch that would be appropriate for a broad range of operational conditions. The recommended resulting correlation is able to predict the power input for impellers in industrial‐scale design for a significant scope of operational conditions.     

Activities of MFI-Supported Rhenium Catalysts for the Aromatization of Methane: Effect of Cationic Form of the Inorganic Carrier

MFI type inorganic carrier was used in two different cationic forms, hydrogen and calcium respectively. MFI-supported molybdenum and rhenium catalysts were prepared. The activities of the catalysts were compared for the aromatization reaction of methane. Higher activity values were attained with the catalysts supported on HZSM-5. Aromatics were also observed with the catalysts supported on CaZSM-5, despite their deficiency in acid sites. Highly dispersed rhenium is expected to be formed with the use of the inorganic carrier in calcium form. On the other hand, lower reaction rates were observed with rhenium supported on CaZSM-5, in spite of the improved dispersion of the active rhenium species on this catalyst. This was interpreted in terms of the critical role of the acid sites in the conversion of methane to aromatics, compared to the improved dispersion of the active metal.     

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.     

SONIC: streaming overlapping community detection

A community within a graph can be broadly defined as a set of vertices that exhibit high cohesiveness (relatively high number of edges within the set) and low conductance (relatively low number of edges leaving the set). Community detection is a fundamental graph processing analytic that can be applied to several application domains, including social networks. In this context, communities are often overlapping, as a person can be involved in more than one community (e.g., friends, and family); and evolving, since the structure of the network changes. We address the problem of streaming overlapping community detection, where the goal is to maintain communities in the presence of streaming updates. This way, the communities can be updated more efficiently. To this end, we introduce SONIC—a find-and-merge type of community detection algorithm that can efficiently handle streaming updates. SONIC first detects when graph updates yield significant community changes. Upon the detection, it updates the communities via an incremental merge procedure. The SONIC algorithm incorporates two additional techniques to speed-up the incremental merge; min-hashing and inverted indexes. Results show that SONIC can provide high quality overlapping communities, while handling streaming updates several orders of magnitude faster than the alternatives performing from-scratch computation.     

Empirical modeling of splitting tensile strength from cylinder compressive strength of concrete by genetic programming

Compressive strength and splitting tensile strength are both mechanical properties of concrete that are utilized in structural design. This study presents gene expression programming (GEP) as a new tool for the formulations of splitting tensile strength from compressive strength of concrete. For purpose of building the GEP-based formulations, 536 experimental data have been gathered from existing literature. The GEP-based formulations are developed for splitting tensile strength of concrete as a function of age of specimen and cylinder compressive strength. In experimental parts of this study, cylindrical specimens of 150 × 300 mm and 100 × 200 mm in dimensions are utilized. Training and testing sets of the GEP-based formulations are randomly separated from the complete experimental data. The GEP-based formulations are also validated with additional 173 data of experimental results other than the data used in training and testing sets of the GEP-based formulations. All of the results obtained from the GEP-based formulations are compared with the results obtained from experimental data, the developed regression-based formulation and formulas given by some national building codes. These comparisons showed that the GEP-based formulations appeared to well agree with the experimental data and found to be quite reliable.     

Contribution of laser microdissection-based technology to proteomic analysis in hepatocellular carcinoma developing on cirrhosis

Hepatocellular carcinoma (HCC) is a major cause of cancer worldwide. Proteomic studies provide opportunities to uncover targets for the diagnosis and treatment of this disease. However, in HCC developing in a setting of cirrhosis, the detection of proteome alterations may be hampered by the increased cellular heterogeneity of tissue when analysing global liver homogenates. The aim of this study was to evaluate whether the identification of proteome alterations in these HCC cases was improved when the differential protein profile between tumour and non-tumour areas of liver was determined using hepatocytes isolated by laser microdissection (LM). Differential profiles established with LM-hepatocytes and liver section homogenates using 2-DE and MS exhibited noticeable differences: 30% of the protein spots with deregulated expression in tumorous LM-samples did not display any modification in homogenates; conversely 15% of proteins altered in tumorous homogenates were not impaired in LM-hepatocytes. These alterations resulted from the presence in cirrhotic liver of fibrotic stroma which displayed a protein pattern different from that determined in LM-hepatocytes. In conclusion, our data demonstrate the interest of LM in distinguishing between fibrotic and hepatocyte proteome alterations and thus the benefit of LM to proteome studies of HCC developing in a context of cirrhosis.     

Stable discretization of poroelasticity problems and efficient preconditioners for arising saddle point type matrices

Poroelastic models arise in reservoir modeling and many other important applications. Under certain assumptions, they involve a time-dependent coupled system consisting of Navier–Lamé equations for the displacements, Darcy’s flow equation for the fluid velocity and a divergence constraint equation. Stability for infinite time of the continuous problem and, second and third order accurate, time discretized equations are shown. Methods to handle the lack of regularity at initial times are discussed and illustrated numerically. After discretization, at each time step this leads to a block matrix system in saddle point form. Mixed space discretization methods and a regularization method to stabilize the system and avoid locking in the pressure variable are presented. A certain block matrix preconditioner is shown to cluster the eigenvalues of the preconditioned matrix about the unit value but needs inner iterations for certain matrix blocks. The strong clustering leads to very few outer iterations. Various approaches to construct preconditioners are presented and compared. The sensitivity of the number of outer iterations to the stopping accuracy of the inner iterations is illustrated numerically.     

Polystyrene Containing Carbinolamine/Azomethine Potentially Useful as Antimicrobial Agent: Synthesis and Biological Evaluation

An investigation of antimicrobial properties of 12 novel modified polymer derived from the condensation reaction of (aminomethyl)polystyrene and four substitute salicylaldehyde (2-hydroxy benzaldehyde, 5-fluoro-2 hydroxy benzaldehyde, 5-fluoro-3-chloro-salicylaldehyde and 5-fluoro-3-methyl-salicylaldehyde) has been carried out and Cr(III) and Ni(II) complexes have been prepared. Modified polymers were characterized by magnetic susceptibility, elemental analyses, and spectral studies. The ¹H NMR and ¹³C NMR spectra analysis of the polymeric carbinolamine/azomethine were determined. In addition, surface morphology and composition were determined by SEM/EDX. Thermo gravimetric analyses of polymers were carried out in nitrogen atmosphere. Antibacterial activities of the polymers attached carbinolamine/azomethine and their complexes were studied by the well-diffusion method against Listeria monocytogenes 4b, Staphylococcus aureus, Escherichia coli, Salmonella typhi H, Brucella abortus, Staphylococcus epidermis sp., Micrococcus luteus, Shigella dysenteria type 10, Bacillus cereus, Pseudomonas putida and antifungal activity against Candida albicans.