Oxymatrine Loaded Cross-Linked PVA Nanofibrous Scaffold: Design and Characterization and Anticancer Properties

This study focuses on the fabrication, characterization and anticancer properties of biocompatible and biodegradable composite nanofibers consisting of poly(vinyl alcohol) (PVA), oxymatrine (OM), and citric acid (CA) using a facile and high-yield centrifugal spinning process known as Forcespinning. The effects of varying concentrations of OM and CA on fiber diameter and molecular cross-linking are investigated. The morphological and thermo-physical properties, as well as water absorption of the developed nanofiber-based mats are characterized using microscopical analysis, energy dispersive X-ray spectroscopy, Fourier transform infrared spectroscopy, differential scanning calorimetry, and thermogravimetric analysis. In vitro anticancer studies are conducted with HCT116 colorectal cancer cells. Results show a high yield of long fibers embedded with beads. Fiber average diameters range between 462 and 528 nm depending on OM concentration. The thermal analysis results show that the fibers are stable at room temperature. The anticancer study reveals that PVA nanofiber membrane with high concentrations of OM can suppress the proliferation of HCT116 colorectal cancer cells. The study provides a comprehensive investigation of OM embedded into nanosized PVA fibers and the prospective application of these membranes as a drug delivery system.     

Cement Composites with Carbon-Based Nanomaterials for 3D Concrete Printing Applications – A Review

3D concrete printing (3DCP) is an emerging additive manufacturing technology in the construction industry. Its challenges lie in the development of high-performance printable materials and printing processes. Recently developed carbon-based nanomaterials (CBNs) such as graphene, graphene oxide, graphene nanoplatelets, and carbon nanotubes, have various applications due to their exceptional mechanical, chemical, thermal, and electrical characteristics. CBNs also have found potential applications as a concrete ingredient as they enhance the microstructure and modify concrete properties at the molecular level. This paper focuses on state-of-the-art studies on CBNs, 3DCP technology, and CBNs in conventional and 3D printable cement-based composites including CBN dispersion techniques, concrete mixing methods, and fresh and hardened properties of concrete. Furthermore, the current limitations and future perspectives of 3DCP using CBNs to produce high-quality composite mixtures are discussed.     

Synthesis and structural characterisation of a novel tris-methylene bridged compound (NO) 4Fe2 Se(μ-CH2)3

The tris-methylene bridged compound (NO)₄Fe₂Se(μ-CH₂)₃ has been isolated. It has been characterised by IR and ¹H, ¹³C, and ⁷⁷Se NMR spectroscopy. Its structure has been determined by single-crystal X-ray diffraction methods. The structure consists of a heavy atom triangle consisting of one Se and two Fe atoms. The Fe-Fe and the two Fe-Se edges are bridged by methylene groups.     

A novel fuzzy C-means algorithm to generate diverse and desirable cluster solutions used by genetic-based clustering ensemble algorithms

One of the most significant discussions in the field of machine learning today is on the clustering ensemble. The clustering ensemble combines multiple partitions generated by different clustering algorithms into a single clustering solution. Genetic algorithms are known for their high ability to solve optimization problems, especially the problem of the clustering ensemble. To date, despite the major contributions to find consensus cluster partitions with application of genetic algorithms, there has been little discussion on population initialization through generative mechanisms in genetic-based clustering ensemble algorithms as well as the production of cluster partitions with favorable fitness values in first phase clustering ensembles. In this paper, a threshold fuzzy C-means algorithm, named TFCM, is proposed to solve the problem of diversity of clustering, one of the most common problems in clustering ensembles. Moreover, TFCM is able to increase the fitness of cluster partitions, such that it improves performance of genetic-based clustering ensemble algorithms. The fitness average of cluster partitions generated by TFCM are evaluated by three different objective functions and compared against other clustering algorithms. In this paper, a simple genetic-based clustering ensemble algorithm, named SGCE, is proposed, in which cluster partitions generated by the TFCM and other clustering algorithms are used as the initial population used by the SGCE. The performance of the SGCE is evaluated and compared based on the different initial populations used. The experimental results based on eleven real world datasets demonstrate that TFCM improves the fitness of cluster partitions and that the performance of the SGCE is enhanced using initial populations generated by the TFCM.     

Integer linear programming models for grid-based light post location problem

Selecting optimal location is a key decision problem in business and engineering. This research focuses to develop mathematical models for a special type of location problems called grid-based location problems. It uses a real-world problem of placing lights in a park to minimize the amount of darkness and excess supply. The non-linear nature of the supply function (arising from the light physics) and heterogeneous demand distribution make this decision problem truly intractable to solve. We develop ILP models that are designed to provide the optimal solution for the light post problem: the total number of light posts, the location of each light post, and their capacities (i.e., brightness). Finally, the ILP models are implemented within a standard modeling language and solved with the CPLEX solver. Results show that the ILP models are quite efficient in solving moderately sized problems with a very small optimality gap.     

The effect of number of baffles on the improvement efficiency of primary sedimentation tanks

In this study, the effect of different numbers of baffles is investigated using computational simulation. Laboratory measurements using different numbers of constant height baffles in a rectangular primary sedimentation tank are conducted. The velocity fields measured by an Acoustic Doppler Velocimeter (ADV) are used to verify the results of the computational model. The effects of the number of baffles arrangement on the hydraulic performance of primary settling tanks are studied by using two different ways: the parameters of flow pattern and the Flow Through Curves (FTCs) method. The results of both the experimental and computational investigations indicate that increasing the number of baffles in suitable positions provides minimum volume of the recirculation region, dissipates the kinetic energy, creates a uniform flow field in the tank and finally the hydraulic efficiency of the sedimentation tank will be improved.     

On Galerkin models for transport in groundwater

The Galerkin finite element model (GFEM) may provide oscillatory results when employed to predict contaminant transport in groundwater unless a very fine mesh is used. Adaptation of a very fine mesh may make the application of the GFEM impractical to field problems. The Petrov—Galerkin finite element models (PGFEMs) can provide oscillation free results for relatively coarser mesh. However, the PGFEM violates the Galerkin principle and introduces large “numerical” dispersion. The objective of this paper has been to develop accurate criteria to improve the applicability of the GFEM to obtain oscillation free accurate results for coarser mesh and compare its performance with that of the PGFEM. It has been shown that the GFEM provides oscillation free accurate results for coarser mesh with Peclet number Pe 20. Further, the GFEM prediction has always been more accurate than the PGFEM for a variety of source configurations and flow fields.     

Bifurcations and chaos control in a discrete-time predator-prey system of Leslie type

We investigate the dynamics of a discrete-time predator-prey system of Leslie type. We show algebraically that the system passes through a flip bifurcation and a Neimark-Sacker bifurcation in the interior of $\R^{2}_+$ using center manifold theorem and bifurcation theory. Numerical simulations are implimented not only to validate theoretical analysis but also exhibits chaotic behaviors, including phase portraits, period-11 orbits, invariant closed circle, and attracting chaotic sets. Furthermore, we compute Lyapunov exponents and fractal dimension numerically to justify the chaotic behaviors of the system. Finally, a state feedback control method is applied to stabilize the chaotic orbits at an unstable fixed point.     

Nonparametric estimation of location parameter after a preliminary test on regression in the multivariate case

For a simple multivariate regression model, nonparametric estimation of the (vector of) intercept following a preliminary test on the regression vector is considered. Along with the asymptotic distribution of these estimators, their asymptotic bias and dispersion matrices are studied and allied efficiency results are presented.