Patients diagnosed with glioblastoma have poor prognosis. Conventional treatment strategies such as surgery, chemotherapy, and radiation therapy demonstrated limited clinical success and have considerable side effects on healthy tissues. A central challenge in treating brain tumors is the poor permeability of the blood–brain barrier (BBB) to therapeutics. Recently, various methods based on immunotherapy and nanotechnology have demonstrated potential in addressing these obstacles by enabling precise targeting of brain tumors to minimize adverse effects, while increasing targeted drug delivery across the BBB. In addition to treating the tumors, these approaches may be used in conjunction with imaging modalities, such as magnetic resonance imaging and positron emission tomography to enhance the prognosis procedures. This review aims to provide mechanistic understanding of immune system regulation in the central nervous system and the benefits of nanoparticles in the prognosis of brain tumors. This article is characterized under: Diagnostic Tools > in vivo Nanodiagnostics and Imaging Nanotechnology Approaches to Biology > Cells at the Nanoscale Nanotechnology Approaches to Biology > Nanoscale Systems in Biology

A new license plate localization algorithm is presented. Execution times of these operations can rather be long, especially where the image consists of large amount of either vehicle's linked components or the other existing objects. This algorithm combines the image processing techniques with some statistical methods and eventually a pattern checking method is also added. Here, minimum rectangle bounding box has been used instead of common bounding box methods, detaching essential details out of blobs and performance improvement, combined with a defined quantity called license plate possibility ratio (LPPR) and standard deviation, we present a robust method of license plate localization. New way of finding license plate's location out of so many rectangles, considering "Sensitive to angle" conditions for characters has also been presented, specifically. It should be noted that the proposed algorithm is regardless of plate's location. This paper presents a different approach on thresholding utilization called "Dynamic Thresholding" which would be obtained by orderly scan of various and sequential ranges of threshold values, confronting probable drawbacks of image lighting caused by lack of light and brightness or another light source radiation, in which, the most desirable threshold value for detection procedure is unknown. Pattern checking phase consists of "Character-Separator" system, using predefined libraries, allows us to detect and specialize state or the city where the license plate's pattern is getting utilized. Presenting the best percent accuracy (95.33%) among relevant well-known algorithms, and also the 25ms run time of the program, would be strong proofs of algorithm's efficiency.

Image enhancement methods are known among the most important image processing techniques. Here, image enhancement is considered as an optimization problem and a new heuristic optimization algorithm namely the Black Hole is used to solve it. Image enhancement is a nonlinear optimization problem with its particular constraints and the enhancement process will be done by intensifying each pixel's content. In this paper, BH is employed to find the image's optimum parameters of the transfer function in order to get the best results. BH is used here for its simplicity, ease of implementation, and also its invincibility against the parameter tuning issues. Performance of the proposed enhancement algorithm is tested against some of the well-known enhancement techniques viz. GA, PSO, HE and CS, and the obtained results indicate the robustness and also the outperformance of the proposed algorithm among its other counterparts. Enhancement in opaque images consisting of immense dominant gray values can be listed as one of the proposed method's superiority to that of the other available in literature, which will turn the input image into an enhanced image, featuring embossed textures.

A new Persian license plate recognition algorithm is presented. These operations are highly susceptible to error, especially where the image consists of large amount of either vehicle's linked components or the other existing objects. Although the proposed character recognition procedure is highly optimized for Persian plates, the localization parts can be employed for all types of vehicles. Minimum rectangle bounding box is replaced the common bounding box methods, compensating normal bounding box's inherent flaws. License plate possibility ratio (LPPR) is a robust method proposed here to localize the plate. New method of finding plate's location out of so many rectangles, considering "Sensitive to angle" criterions for characters has also been presented. It should be noted that the process is regardless of the plate's location. Different approach on thresholding namely: "Dynamic Thresholding" is used to overcome the probable drawbacks caused by inappropriate lighting. From OCR point of view, a graph, consisting of two specifications will be formed and a set of rules will be defined to capture the character's label. An automated harassment section is added as the denoising filter, in order to omit the grinning ramifications. Presenting the best percent accuracy (95.33%) among relevant well-known algorithms in localization procedure with 25ms run time of the program, and also the outstanding results with over 97% of percent accuracy in character recognition of Persian plates with 30ms run time of the program on Linux and also average of 90ms on Android, can be listed as strong proofs of algorithm's efficiency.

Subwavelength planar structured interfaces, also known as metasurfaces, are ultra-thin optical elements modulating the amplitude, phase, and polarization of incident light using nanostructures called meta-atoms. The optical properties of such metasurfaces can be controlled across wavelengths by selecting geometries and materials of the meta-atoms. Given recent technological developments in optical device miniaturization, components for beam splitting and beam combining are sought for use within these devices as two quintessential components of every optical setup. However, realizing such devices using metasurfaces typically leads to poor uniformity of diffraction orders and narrow-band operation. Using a modified version of particle swarm optimization, we propose and numerically demonstrate a broadband, reciprocal metasurface beam combiner/splitter with uniformity > 97% and diffraction efficiency > 90% in the continuous band from λ=1525 nm to λ=1575 nm. The proposed approach significantly extends the current state of the art of metasurfaces design in terms of uniformity, bandwidth, and efficiency, and opens the door for devices requiring high power or near-unit uniformity.