The digital revolution has come to microfluidics. In digital microfluidics (DMF), discrete droplets are manipulated by applying electrical fields to an array of electrodes. In contrast to microchannels, in DMF each sample and reagent is individually addressable, which facilitates exquisite control over chemical reactions. Here, we review the state-of-the-art in DMF, with a discussion of device formats, actuation physics, and biological and nonbiological applications. Along the way, we identify the key players in the field, and speculate on the advances and challenges that lie ahead. As with other fronts in the digital revolution, there have been and will be unexpected developments as DMF matures, but we posit that the future is bright for this promising technology.

Digital microfluidics (DMF) is a fluid handling technique that enables manipulation of discrete droplets on an array of electrodes. There is considerable enthusiasm for this method because of the potential for array-based screening applications. A limitation for DMF is nonspecific adsorption of reagents to device surfaces. If a given device is used to actuate multiple reagents, this phenomenon can cause undesirable cross-contamination. A second limitation for DMF (and all other microfluidic systems) is the “world-to-chip” interface; it is notoriously difficult to deliver reagents and samples to such systems without compromising the oft-hyped advantages of rapid analyses and reduced reagent consumption. We introduce a new strategy for digital microfluidics, in which a removable plastic “skin” is used to (a) eliminate cross-contamination and (b) bridge the world-to-chip interface. We demonstrated the utility of this format by implementing on-chip protein digestion on immobilized enzyme depots. This new method has the potential to transform DMF from being a curiosity for aficionados into a technology that is useful for biochemical applications at large.

Evaporation is the process by which water changes from a liquid to a gas or vapor. The evaporation rate is influenced by sun shine hours, temperature, relative humidity and wind speed. Historical data of this factor could be used to predict the evaporation rate by using different technique such as time series modeling, multiple regression analysis and artificial neural networks (ANN). In this paper, the ANNs are used to predict the evaporation rate in a semi-arid region knowing the basic climate factors. The collected data for Abyuha region, Egypt is used to train validate and test the network. Also, multiple linear and nonlinear regression methods are used to develop prediction models for predicting evaporation rates in terms of the same climatic factors. The results of the ANN model are compared to the best multiple linear regression (MLR) models. The analysis of the results indicated that the predictions of ANN are comparable to those of the regression methods and that ANN is a promising tool for modeling evaporation data. Sensitivity analysis indicated that the air temperature has a major effect on the evaporation rates while other factors have fewer effects.

A computationally simple approach is described for obtaining a mathematical model representing the behavior of nonlinear systems over the entire range to which it is subjected. This model is derived using either experimental results or computer simulation of the system under consideration. It is shown that if the information about the nonlinear system is based on experimental results, then the derived model is not affected with the measurement noise.

A damage in a structure alters its dynamic characteristics; namely, natural frequencies, modal damping values, and mode shapes. Changes also occur in some of the structural parameters such as: the mass, damping and stiffness matrices of the structure. Among different algorithms developed for structural damage identification, changes in either mode shape curvature or uniform load surface (ULS) curvature, derived from measured modal properties, have shown promise for locating structural damage. However, to date there is not a study reported in the technical literature that directly compares these two promising methods. The numerical results in this paper attempt to fill this void in the study of damage detection methods. In this paper, a numerical study is investigated to compare the robustness of these two methods in damage detection using the frequencies and mode shapes of the first few modes. Also, the application of a damage localization algorithm to these two methods in detecting and locating damage is demonstrated. The numerical results show that both of the two methods can accurately locate single damage with different damage characteristics (location and severity). However, the two methods have shown less sensitivity to specific types of damage when applied to multiple damage locations. Also, the results of the ULS curvature method contain less noise than that of the results of the mode shape curvature method. Finally, the mode shape curvature can pinpoint damage locations even with one of the lower mode shapes of the structure and it does not require the mode frequency.

The influence of vertical loads on the lateral response of group piles installed in sandy soil and connected together by a concrete cap is studied through finite elements analyses. The analyses focus on the five piles in the middle row of 3× 5 pile groups. The vertical load is applied by enforcing a vertical displacement equivalent to 2% of the pile diameter through the pile cap prior to the application of the lateral loads. The results have shown that the lateral resistance of the leading pile (pile 1) does not appear to vary ...

This paper introduces a new formula for the objective function of the famous fuzzy C-means algorithm. Two weighted terms are added to the objective function to reflect any available information about the class center and class pixels distribution throughout the datasets. The algorithm is evaluated for the task of the segmentation of medical MRI brain volume. The results show that the algorithm has a considerable robustness against noise and partial volume effects, and it needs a smaller number of iterations to reach convergence compared with other similar algorithms.

The two-dimensional functionally graded materials, (2D-FGMs) have been recently introduced in order to significantly reduce the thermal stresses in machine elements that subjected to sever thermal loading. To the author’s knowledge no work was found that investigates the elastic–plastic stress analysis for 2DFGMs. In the current work, a 3D finite element model of 2D-FGM plates made of ZrO2, 6061-T6 and Ti- 6Al-4V with temperature dependent material properties has been proposed to perform such analysis. An elastic plastic stress–strain relation based on the rule of mixture of the 2D-FGM has been introduced in the model. Also, a 3D finite element model of conventional FGM plates, of ZrO2/Ti-6Al-4V and ZrO2/ 6061-T6, with temperature dependent material properties has been proposed for the investigation of these plates too. Then, elastic–plastic stress analysis of the considered four plates (two conventional FGMs and two 2D-FGMs) under the same transient cyclic heating and cooling was carried out. It was found that heat conductivity of the metallic constituents of FGM has great effect on the temperature distributions that resulting from the thermal loads. Minimum temperatures variation and minimum stresses can be obtained using ZrO2/6061-T6/Ti-6Al-4V 2D-FGM. Also, the results indicate that only ZrO2/6061- T6/Ti-6Al-4V 2D-FGM can stand with the adopted sever thermal loading without fracture or plastic deformations.