A comparative study on in vitro behavior of calcium silicate ceramics synthesized from biowaste resources

Calcium silicate ceramics have received significant attention for biomedical applications for their excellent bioactivity and osteoconduction properties. Sol-gel process is extensively used for the fabrication of calcium silicates. In sol-gel process, calcium nitrate tetra hydrate (Ca(NO₃)₂·4H₂O) and tetraethylorthosilicate (TEOS) are used as precursors. However, these precursors are expensive. The objective of this work was to compare in vitro behavior of calcium silicate (CaSiO₃) produced using biowaste such as rice husk ash (RHA) and eggshells (coded; NCS) with CaSiO₃ prepared using TEOS and Ca(NO₃)₂·4H₂O (coded; CCS). Thermal investigation results revealed that the crystallization temperature for NCS is relatively lower (772°C) than for CCS (870°C). Bioactivity was studied in vitro using simulated body fluid (SBF) with respect to mineralization rate of hydroxyapatite. Mineralization of a greater hydroxyapatite was observed on NCS ceramics than CCS ceramics after incubation for 3, 7, 14 days in SBF solution, which was confirmed using X-ray diffractometer, Fourier transform infrared spectroscopy, scanning electron microscopy-energy dispersive spectroscopy. Degradation studies were conducted in Tris-HCl solution and the test results revealed that NCS ceramics has lower dissolution rate than CCS ceramics. The antimicrobial assay has shown that NCS samples exhibit significant zone of inhibition against Escherichia coli and Staphylococcus aureus which confirmed that the CaSiO₃ prepared from RHA and eggshell can prevent bacteria from adhering to the surface. In addition cell culture studies revealed that NCS ceramics possess good cytocompatibility with MG-63 cells and significantly promoted cell proliferation.     

RESIDENCE TIME DISTRIBUTION (RTD) AND GOODNESS OF MIXING (GM) DURING CO2-INJECTION IN TWIN-SCREW EXTRUSION PART II: GM STUDIES

Experimental residence-time distribution (RTD) characteristics of an extrusion process may be used to estimate the extent of mixing experienced in the extruder. Using earlier theories of laminar mixing and striation thickness reduction, a new approach to estimate efficacy of mixing of two phases in the mixing zone of the extruder is proposed. Predicting the time required to achieve complete mixing and comparing it with the minimum time (plug flow time) that the extrudate spends in the mixing zone gives a ratio that can be used to evaluate the adequacy of extruder operating conditions for good mixing of gas/fluid injection and extrudate. Twin-screw extrusion of cornmeal with carbon dioxide injection were used to investigate the effect of CO₂ injection pressure and extruder screw speeds on mixing. Lower CO₂ injection pressures (25 bars) and lower screw speeds (150 rpm) were theoretically shown to enhance mixing. Scanning electron micrographs (SEMs) of experimental samples taken showed smaller and more uniform cell structures for those conditions which were predicted to favor better mixing.     

Benchmarking performance of machine and deep learning-based methodologies for Urdu text document classification

Neural Computing and Applications - In order to provide benchmark performance for Urdu text document classification, the contribution of this paper is manifold. First, it provides a publicly...     

基于深度卷积神经网络的两阶段肺结节检测

针对传统肺结节检测中存在灵敏度低、假阳性高、小结节难检测的问题,提出一种基于深度卷积神经网络的两阶段肺结节检测框架.第一阶段使用特征金字塔子网提取肺部影像的多层次特征,引入多尺度区域建议子网用于在高灵敏度下检测出所有的候选结节;第二阶段设计级联卷积神经网络模型减少假阳性,通过保留分类错误样本用于重新训练模型,将多个模型结果进行投票选出最终分类结果.LUNA16数据集上的实验结果表明,所提框架灵敏度达到95.9％,检测效果优于其它算法,能够有效实现肺结节的准确检测.     

Simplified and efficient calibration of a mechanistic cutting force model for ball-end milling

Accurate evaluation of the empirical coefficients of a mechanistic cutting force model is critical to the reliability of the predicted cutting forces. This paper presents a simplified and efficient method to determine the cutting force coefficients of a ball-end milling model. The unique feature of this new method is that only a single half-slot cut is to be performed to calibrate the empirical force coefficients that are valid over a wide range of cutting conditions. The instantaneous cutting forces are used with the established helical cutting edge profile on the ball-end mill. The half-slot calibration cut enables successive determination of the lumped discrete values of the varying cutting mechanics parameters along the cutter axis whereas the size effect parameters are determined from the known variation of undeformed chip thickness with cutter rotation. The effectiveness of the present method in determining the cutting force coefficients has been demonstrated experimentally with a series of verification test cuts.     

Local calibration of rigid pavement performance models using resampling methods

The performance prediction models in the Pavement-ME design software are nationally calibrated using in-service pavement material properties, pavement structure, climate and truck loadings, and performance data obtained from the Long-Term Pavement Performance programme. The nationally calibrated models may not perform well if the inputs and performance data used to calibrate those do not represent the local design and construction practices. Therefore, before implementing the new M-E design procedure, each state highway agency (SHA) should evaluate how well the nationally calibrated performance models predict the measured field performance. The local calibrations of the Pavement-ME performance models are recommended to improve the performance prediction capabilities to reflect the unique conditions and design practices. During the local calibration process, the traditional calibration techniques (split sampling) may not necessarily provide adequate results when limited number of pavement sections are available. Consequently, there is a need to employ statistical and resampling methodologies that are more efficient and robust for model calibrations given the data related challenges encountered by SHAs. The main objectives of the paper are to demonstrate the local calibration of rigid pavement performance models and compare the calibration results based on different resampling techniques. The bootstrap is a non-parametric and robust resampling technique for estimating standard errors and confidence intervals of a statistic. The main advantage of bootstrapping is that model parameters estimation is possible without making distribution assumptions. This paper presents the use of bootstrapping and jackknifing to locally calibrate the transverse cracking and IRI performance models for newly constructed and rehabilitated rigid pavements. The results of the calibration show that the standard error of estimate and bias are lower compared to the traditional sampling methods. In addition, the validation statistics are similar to that of the locally calibrated model, especially for the IRI model, which indicates robustness of the local model coefficients.     

On l∞ and l2 robustness of spatially invariant systems

We consider spatiotemporal systems and study their l_∞ and l₂ robustness properties in the presence of spatiotemporal perturbations. In particular, we consider spatially invariant nominal models and provide necessary and sufficient conditions for system robustness for the cases when the underlying perturbations are linear spatiotemporal varying, and nonlinear spatiotemporal invariant, unstructured or structured. It turns out that these conditions are analogous to the scaled small gain condition (which is equivalent to a spectral radius condition and a linear matrix inequality for the l_∞ and l₂ cases, respectively) derived for standard linear time‐invariant models subject to time‐varying linear and time‐invariant nonlinear perturbations. Copyright © 2009 John Wiley & Sons, Ltd.