Morphological evolution on the surface of hydrothermally synthesized hydroxyapatite microspheres in the presence of EDTMP

Well-ordered and surface engineered hierarchical hydroxyapatite microspheres (HAM) were prepared via a template free hydrothermal process. Ethylene diamine tetra (methylene phosphonic acid) (EDTMP) was used as chelating or regulating agent for the first time in this study. The results indicated the formation of sheet-like particles in the absence of EDTMP. On the other hand, microspheres with radially grown nanorods (HAMNR) or nanosheets (HAMNS) on the surface were obtained (with average diameter of 5?µm) in the presence of EDTMP. X-ray diffraction (XRD) and Fourier transform infrared (FTIR) spectroscopy were used to characterize the crystalline phases in the synthesized samples. Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) showed that EDTMP concentration played an important part in regulating the morphology to form well organized microspheres with nanosheets or nanorods on the surface. Brunauer-Emmett-Teller (BET) revealed an increase in the specific surface area with the change in morphology from the HAMNS to HAMNR. Possible mechanisms are proposed to account for the formation of different morphologies based upon thermodynamic and kinetic theories.     

Application of Acoustic Wave Propagation Analysis Methods for Monitoring a Miscible Mixing Zone in Porous Media

The Biot's acoustics theory, which describes acoustic wave propagation in a porous medium, and computer simulation techniques were utilized to model the behavior of acoustic waves entering and leaving a mixing zone in a miscible displacement in porous media. The results indicate that the angles of waves produced by a mixing zone are equal to angles of waves produced by an abrupt fluid-fluid interface. Therefore, acoustic methods and a relationship between the incident, reflection, and transmission angles can be used to determine the location and thickness of the mixing zone during a miscible displacement process in porous media.     

pHEMA: An Overview for Biomedical Applications

Poly(2-hydroxyethyl methacrylate) (pHEMA) as a biomaterial with excellent biocompatibility and cytocompatibility elicits a minimal immunological response from host tissue making it desirable for different biomedical applications. This article seeks to provide an in-depth overview of the properties and biomedical applications of pHEMA for bone tissue regeneration, wound healing, cancer therapy (stimuli and non-stimuli responsive systems), and ophthalmic applications (contact lenses and ocular drug delivery). As this polymer has been widely applied in ophthalmic applications, a specific consideration has been devoted to this field. Pure pHEMA does not possess antimicrobial properties and the site where the biomedical device is employed may be susceptible to microbial infections. Therefore, antimicrobial strategies such as the use of silver nanoparticles, antibiotics, and antimicrobial agents can be utilized to protect against infections. Therefore, the antimicrobial strategies besides the drug delivery applications of pHEMA were covered. With continuous research and advancement in science and technology, the outlook of pHEMA is promising as it will most certainly be utilized in more biomedical applications in the near future. The aim of this review was to bring together state-of-the-art research on pHEMA and their applications.     

纳米碳酸钙的制备及表征

研究了以氧化钙和二氧化碳为原料,化学法制备纳米碳酸钙的工艺条件、添加剂的影响及形态。结果表明:中间体氢氧化钙的初始浓度、二氧化碳的流量、反应温度、搅拌速度及添加剂等在控制制备纳米碳酸钙颗粒的形状和尺寸中均十分重要。透射电镜观察结果表明:通过控制反应及添加剂,可以得到尺寸规整的链锁形、纺锤形和球形纳米碳酸钙。表面能谱证实产品为高纯的碳酸钙。X射线衍射和电子衍射的结果进一步表明:所制纳米碳酸钙均属方解石型六方晶系,a0=0.498 9 nm,c0=1.706 2 nm;为多晶结构。     

Optimized scenario for rainfall forecasting using genetic algorithm coupled with artificial neural network

Rainfall forecasting plays many important role in water resources studies such as river training works and design of flood warning systems. Recent advancement in artificial intelligence and in particular techniques aimed at converting input to output for highly nonlinear, non-convex and dimensionalized processes such as rainfall field, provide an alternative approach for developing rainfall forecasting model. Artificial neural networks (ANNs), which perform a nonlinear mapping between inputs and outputs, are such a technique. Current literatures on artificial neural networks show that the selection of network architecture and its efficient training procedure are major obstacles for their daily usage. In this paper, feed-forward type networks will be developed to simulate the rainfall field and a so-called back propagation (BP) algorithm coupled with genetic algorithm (GA) will be used to train and optimize the networks. The technique will be implemented to forecast rainfall for a number of times using rainfall hyetograph of recording rain gauges in the Upper Parramatta catchment in the western suburbs of Sydney, Australia. Results of the study showed the structuring of ANN network with the input parameter selection, when coupled with GA, performed better compared to similar work of using ANN alone.     

Effect study of hexagonal mesoporous silica/polyaniline nanocomposite on the structural properties of polysulfone membranes and its heavy metal removal efficiency

New mixed matrix membranes of polysulfone were synthesized by different content of hexagonal mesoporous silica coated by polyaniline and used for nickel and lead ion removal. The membranes were characterized by FESEM, XRD, BET, TGA, and FTIR, and zeta potential measurements. The results showed that PANi/HMS particles enhanced the membrane porosity and permeability. These effects were explained according to an increase of the membrane hydrophilicity due to the formation of new functional groups during membrane casting. The results showed that metal ion rejection was performed by a filtration–adsorption mechanism, resulting in fixation of metal ions on the active sites of membranes.     

Bi-objective optimization approaches to many-to-many hub location routing with distance balancing and hard time window

Neural Computing and Applications - This study addresses a many-to-many hub location-routing problem where the best-found locations of hubs and the best-found tours for each hub are determined with...     

A Cluster-based Stratified Hybrid Decision Support Model under Uncertainty: Sustainable Healthcare Landfill Location Selection

Applied Intelligence - Nowadays, healthcare waste management has become one of the significant environmental, health, and social problems. Due to population and urbanization growth and an increase...