Co-delivery of paclitaxel and α-tocopherol succinate by novel chitosan-based polymeric micelles for improving micellar stability and efficacious combination therapy

The aim of this study was to develop chitosan derivative polymeric micelles for co-delivery of paclitaxel (PTX) and α-tocopherol succinate (α-TS) to the cancer cells to improve the therapeutic efficiency and reduce side effects of PTX. In this study, amphiphilic tocopheryl succinate-grafted chitosan oligosaccharide was synthesized and physically loaded by PTX and α-TS with entrapment efficiency of 67.9% and 73.2%, respectively. Physical incorporation of α-TS into the micelles increased the hydrophobic interaction between PTX and the micelles core, which improved micelle stability, reduced the micelle size and also sustained the PTX release from the micelles. The mean particle size and zeta potential of αTS/PTX-loaded micelles were about 133?nm and +25.2?mV, respectively, and PTX release was completed during 6–9?d from the micelles. Furthermore, the cytotoxicity of α-TS/PTX-loaded micelles against human ovarian cancer cell line cancer cell in vitro was higher than that of PTX-loaded micelles and the free drug solution. Half maximal inhibitory concentration values of PTX after 48-h exposure of the cells to the PTX-loaded micelles modified and unmodified with α-TS were 110 and 188?ng/ml, respectively.     

Replacing stitching and weaving in natural fiber reinforcement manufacturing,part 2: mechanical behavior of flax fiber composite laminates

ABSTRACT

Replacing weaving and stitching used in textile-based reinforcements by using short fibers as a binder was discussed based on the tensile and compressive properties of [0], [± 45], and [0/90] laminates. A slight decrease in the longitudinal properties of the [0] composites was accompanied by a significant reduction of the properties of variability. In the case of [± 45] laminates, the presence of the short flax fiber shows a positive effect on the tensile, shear, and compressive properties. The mechanical properties of [0/90] laminates have shown a limited effect of the short fibers, with a slight decrease of both modulus and strength.     

A Wide Tuning Range Voltage Controlled Oscillator with a High Tunable Active Inductor

This paper presents a wide tuning range CMOS voltage controlled oscillator (VCO) with a high-tunable active inductor circuit. In this VCO circuit, the coarse frequency is achieved by tuning the integrated active inductor circuit. The VCO circuit is designed in 0.18  \(\upmu \hbox {m}\) CMOS process and simulated with Cadence Spectra. The simulation results show the frequency tuning range from 120 MHz to 2 GHz resulting in a tuning range of 94 %. The phase noise variation is from \(-\) 80 to \(-\) 90 dBc/Hz at a 1 MHz frequency offset, and output power variation is from \(-\) 4.7 to \(+\) 11.5 dBm. The active inductor power consumption is 2.2 mW and the total power dissipation is 7 mW from a 1.8 V DC power supply. By comparing the proposed VCO circuit with the general VCO topology, the results show that this VCO architecture by using the novel, high-tunable and low power active inductor circuit, presents a better performance regarding low chip size, low power consumption, high tuning range and high output power.     

Object-Oriented Model for Freeway Work Zone Capacity and Queue Delay Estimation

Abstract:   Existing computer models used to estimate queue delay upstream of the work zone have a number of shortcomings. They do not provide any model to estimate work zone capacity, which has a significant impact on the congestion and traffic queue delays. They cannot be used to perform scenario analysis for work zones with various characteristics such as work zone layout, number of closed lanes, work intensity, and work time. In this article, an object-oriented (OO) model is presented for freeway work zone capacity and queue delay and length estimation. The model is implemented into an interactive software system, called IntelliZone, using Microsoft Foundation Classes (MFC) and a hierarchy of multiple specialized frameworks. A three-layer application architecture is created to separate the application functions and classes from MFC classes. The high-level application domain layer is divided into packages. IntelliZone's capacity estimation engine is based on pattern recognition and neural network models incorporating a large number of factors impacting the work zone capacity. This research provides the foundation for a new generation of advanced decision support systems for effective management of traffic at work zones .     

Hybrid CPN–Neural Dynamics Model for Discrete Optimization of Steel Structures

Abstract: In practical design of steel structures, the designer usually must choose from a limited number of commercially available shapes such as the widely used wide flange shapes. In this article, we present a hybrid counterpropagation-neural dynamics model and a new neural network topology for discrete optimization of large structures subjected to the AISC ASD specifications. The constrained structural optimization problem is formulated in terms of a neural dynamics model with constraint and variable layers. The counterpropagation part of the model consists of the competition and interpolation layers. The CPN network is trained to learn the relationship between the cross-sectional area and the radius of gyration of the available sections. The robustness of the hybrid computational model is demonstrated by application to three examples representing the exterior envelope of high-rise and super-high-rise steel building structures, including a 147-story structure with 8904 members.     

Life‐cycle cost optimization of steel structures

This article addresses the life‐cycle cost optimization of steel structures. The main factors influencing the life‐cycle cost of a structure are delineated and their effects on various cost functions are discussed. A four‐criteria optimization model is presented for the life‐cycle cost optimization of steel structures. These criteria are (i) select discrete commercially available sections with the lowest cost, (ii) select commercially available sections with the lightest weight, (iii) select the minimum number of different types of commercially available sections, and (iv) select commercially available sections with the minimum total perimeter length. The last criterion models a representative type of cost incurred over the life of the structure, that is, preventative maintenance in the form of periodic painting of an exposed steel structure to avoid corrosion. The life‐cycle cost optimization model is based on fuzzy logic with the goal of formalizing the life‐cycle design process but with some input from the design engineer through introduction of weighting coefficients reflecting the relative importance of various criteria. The model is applied to a large steel structure with over 3300 members. Copyright © 2002 John Wiley & Sons, Ltd.     

Wavelet Packet-Autocorrelation Function Method for Traffic Flow Pattern Analysis

Abstract:   Accurate and timely forecasting of traffic flow is of paramount importance for effective management of traffic congestion in intelligent transportation systems. A detailed understanding of the properties of traffic flow is essential for building a reliable forecasting model. The discrete wavelet packet transform (DWPT) provides more coefficients than the conventional discrete wavelet transform (DWT), representing additional subtle details of a signal. In wavelet multiresolution analysis, an important decision is the selection of the decomposition level. In this research, the statistical autocorrelation function (ACF) is proposed for the selection of the decomposition level in wavelet multiresolution analysis of traffic flow time series. A hybrid wavelet packet-ACF method is proposed for analysis of traffic flow time series and determining its self-similar, singular, and fractal properties. A DWPT-based approach combined with a wavelet coefficients penalization scheme and soft thresholding is presented for denoising the traffic flow. The proposed methodology provides a powerful tool in removing the noise and identifying singularities in the traffic flow. The methods created in this research are of value in developing accurate traffic-forecasting models .     

Reductive dissolution of manganese ore in sulfuric acid in the presence of iron metal

The dissolution of a manganese dioxide ore in dilute sulfuric acid facilitated by Fe metal in the form of powdered sponge iron was investigated. Effects of such parameters as molar ratios of sponge iron and sulfuric acid to manganese dioxide, temperature, particle size of sponge iron as well as ore particle size on the dissolution efficiency were studied. The results showed that manganese could be rapidly leached out to a complete degree even at room temperature. Based on both theoretical and experimental facts, it was concluded that the usage of metallic iron for the reductive leaching of manganese dioxide was superior to that of ferrous ion as far as dissolution rate and efficiency were concerned.     

Hybrid Control of Smart Structures Using a Novel Wavelet-Based Algorithm

Abstract:   A tuned liquid column damper (TLCD) system provides the same level of vibration suppression as a conventional tuned mass damper (TMD) system but with several advantages. A new hybrid control system is presented through judicious combination of a passive supplementary damping system with a semi-active TLCD system. The new model utilizes the advantages of both passive and semi-active control systems, thereby improving the overall performance, reliability, and operability of the control system during normal operations as well as a power or computer failure. The robust wavelet-hybrid feedback least mean square (LMS) control algorithm developed recently by the authors is used to find optimal values of the control parameters. The effectiveness and robustness of the proposed hybrid damper-TLCD system in reducing the vibrations under various seismic excitations are evaluated through numerical simulations performed for an eight-story frame using three different simulated earthquake ground accelerations. It is found that the new model is effective in significantly reducing the response of the structure under various seismic excitations.