Optical differentiation is a promising tool in biomedical diagnosis mainly because of its safety. The optical parameters’ values of biological tissues differ according to the histopathology of the tissue and hence could be used for differentiation. The optical fluence rate distribution on tissue boundaries depends on the optical parameters. So, providing image displays of such distributions can provide a visual means of biomedical diagnosis. In this work, an experimental setup was implemented to measure the spatially-resolved steady state diffuse reflectance and transmittance of native and coagulated chicken liver and native and boiled breast chicken skin at 635 and 808 nm wavelengths laser irradiation. With the measured values, the optical parameters of the samples were calculated in vitro using a combination of modified Kubelka-Munk model and Bouguer-Beer-Lambert law. The estimated optical parameters values were substituted in the diffusion equation to simulate the fluence rate at the tissue surface using the finite element method. Results were verified with Monte-Carlo simulation. The results obtained showed that the diffuse reflectance curves and fluence rate distribution images can provide discrimination tools between different tissue types and hence can be used for biomedical diagnosis.

Exudates are one of the earliest and most prevalent symptoms of diseases leading to blindness such as diabetic retinopathy and wet macular degeneration. Certain areas of the retina with such conditions are to be photocoagulated by laser to stop the disease progress and prevent blindness. Outlining these areas is dependent on outlining the exudates, the blood vessels, the optic disc and the macula and the region between them. The earlier the detection of exudates in fundus images, the stronger the kept sight level. So, early detection of exudates in fundus images is of great importance for early diagnosis and proper treatment. In this paper, we provide a feature-based method for early detection of exudates. The method is based on segmenting all objects that have contrast with the background including the exudates. The exudates could then be extracted after eliminating the other objects from the image. We proposed a new method for extracting the blood vessel tree based on simple morphological operations. The circular structure of the optic disc is obtained using Hough transform. The regions representing the blood vessel tree and the optic disc are set to zero in the segmented image to get an initial estimate of exudates. The final estimation of exudates are obtained by morphological reconstruction. This method is shown to be promising as we can detect the very small areas of exudates.

Understanding gene interactions in complex living systems can be seen as the ultimate goal of the systems biology revolution. Hence, to elucidate disease ontology fully and to reduce the cost of drug development, gene regulatory networks (GRNs) have to be constructed. During the last decade, many GRN inference algorithms based on genome-wide data have been developed to unravel the complexity of gene regulation. Time series transcriptomic data measured by genome-wide DNA microarrays are traditionally used for GRN modelling. One of the major problems with microarrays is that a dataset consists of relatively few time points with respect to the large number of genes. Dimensionality is one of the interesting problems in GRN modelling.

Wireless power transmission (WPT) is commonly used today in many important daily applications, such as electric vehicles, mobile phones, and implanted medical devices. The transmitter and receiver coils are essential elements in the WPT system, and the coupling coefficient between these coils plays an important role in increasing the power transfer efficiency. In this work, we introduce a new approach to optimizing the coupling coefficient between the transmitter and the receiver coils by changing the geometries and locations of the coil turns. In the optimization process, the geometry of the turns varies from a rhombus to a circular and then a rectangular shape according to a quasi-elliptical parameter value. The Neuman formula is used to calculate the self-inductance, mutual inductance, and coupling coefficient for each specific geometry and turn location. The configuration with the highest coupling coefficient is then selected at the end of the optimization process. The final WPT coils are tested and verified using Ansys software through electromagnetic and AC analysis simulations. The results show that the new approach could achieve smooth and easily manufacturable coils with higher coupling coefficients, thereby increasing the power transfer efficiency of WPT.