We present a flow cytometer on a microfluidic chip that integrates an inline lens-free holographic microscope. High-speed cell analysis necessitates that cells flow through the microfluidic channel at a high velocity, but the image sensor of the in-line holographic microscope needs a long exposure time. Therefore, to solve this problem, this paper proposes an S-type micro-channel and a pulse injection method. To increase the speed and accuracy of the hologram reconstruction, we improve the iterative initial constraint method and propose a background removal method. The focus images and cell concentrations can be accurately calculated by the developed method. Using whole blood cells to test the cell counting precision, we find that the cell counting error of the proposed method is less than 2%. This result shows that the on-chip flow cytometer has high precision. Due to its low price and small size, this flow cytometer is suitable for environments far away from laboratories, such as underdeveloped areas and outdoors, and it is especially suitable for point-of-care testing (POCT).

Routine blood tests provide important basic information for disease diagnoses. The proportions of three subtypes of white blood cells (WBCs), which are neutrophils, monocytes, lymphocytes, is key information for disease diagnosis. However, current instruments for routine blood tests, such as blood cell analyzers, flow cytometers, and optical microscopes, are cumbersome, time consuming and expensive. To make a smaller, automatic low-cost blood cell analyzer, much research has focused on a technique called lens-less shadow imaging, which can obtain microscopic images of cells in a lens-less system. Nevertheless, the efficiency of this imaging system is not satisfactory because of two problems: low resolution and imaging diffraction phenomena. In this paper, a novel method of classifying cells with the shadow imaging technique was proposed. It could be used for the classification of the three subtypes of WBCs, and the correlation of the results of classification between the proposed system and the reference system (BC-5180, Mindray) was 0.93. However, the instrument was only 10 × 10 × 10 cm, and the cost was less than $100. Depending on the lens-free shadow imaging technology, the main hardware could be integrated on a chip scale and could be called an on-chip instrument.

This paper advocates the importance of selecting appropriate measures of effectiveness (MOE) for evacuation planning and optimization purposes. In addition to evacuation time, which is often the choice MOE used by many practitioners, this paper also presents several increasingly more complex and useful MOEs that consider average evacuee travel time, delay, and temporal–spatial-based exposure risks. By studying a real-world transportation network in the event of a hypothetical nuclear power plant incident, the paper demonstrates that the superiority of one evacuation plan (or an optimization strategy) over others is highly dependent on the MOE selected for evaluation. Optimization efforts based on a single and ill-chosen MOE may not yield the best evacuation plan, as one might expect. The overall space-based or time- and space-based risk exposure may be increased if the optimization process is focused on travel time or some other time-based measure alone. Depending on the specifics of an emergency scenario (e.g., disaster type, risk components, and time constraints), an appropriate MOE should be chosen judiciously to make sure the optimization process for the evacuation plan is not wasted. This paper also demonstrates a multiobjective optimization approach for planning and designing an evacuation plan. With combined space-based risk and the travel time in route searching and traffic assignment, better destination assignment (and improved evacuation efficiency) may be obtained. The findings here should provide insights for future efforts toward assessing, improving, and optimizing evacuation plans.

An interesting segmentation method for low-resolution cell images captured by a lens-free imaging system is presented in this paper. The resolution of this cell images is low and its quality has also greatly impacted by the experimental environments, and the traditional cell segmentation methods to solve the original cell images is not robust and sensitive to noise. So based on the convolutional neural network, an optimized CSnet method is proposed in this paper for automatically segmenting cell. In the proposed method, the produced data set will be sent into the convolutional neural network firstly for training to obtain an optimized convolution neural network segmentation model. And then, the pre-divided images acquired by the lens-free imaging system are loaded into the segmentation model to get the segmentation images. Finally, our proposed method in this paper is tested in a neural network framework built in keras. The experimental results show that the accuracy of our proposed method can reach about 96%. At the same time, it also can implement batch segmentation automatically and make the problem of heavy task for segmentation better.

The lensless imaging technique, which integrates a microscope into a complementary metal oxide semiconductor (CMOS) digital image sensor, has become increasingly important for the miniaturization of biological microscope and cell detection equipment. However, limited by the pixel size of the CMOS image sensor (CIS), the resolution of a cell image without optical amplification is low. This is also a key defect with the lensless imaging technique, which has been studied by a many scholars. In this manuscript, we propose a method to improve the resolution of the cell images using the Brownian motion of living cells in liquid. A two-step algorithm of motion estimation for image registration is proposed. Then, the raw holographic images are reconstructed using normalized convolution super-resolution algorithm. The result shows that the effect of the collected cell image under the lensless imaging system is close to the effect of a 10× objective lens.

With the rise of mobile technology, the library reference service has dramatically changed. Targeting the new requirements, this paper aims to design a new library reference service system in Cordova-based hybrid frameworks, which caters...