A novel multi-dimensional coal and gangue X-ray sorting algorithm based on CdZnTe photon counting detectors.

BACKGROUND: The gangue content in coal seriously affects the calorific value produced by its combustion. In practical applications, gangue in coal needs to be completely separated. The pseudo-dual-energy X-ray method does not have high sorting accuracy. OBJECTIVE: This study aims to propose a novel multi-dimensional coal and gangue X-ray sorting algorithm based on CdZnTe photon counting detectors to solve the problem of coal and gangue sorting by X-ray. METHODS: This complete algorithm includes five steps: (1) Preferred energy bins, (2) transmittance sorting, (3) one-dimensional R-value sorting, (4) two-dimensional R-value sorting, and (5) three-dimensional R-value sorting. The output range of each step is determined by prior information from 65 groups of coal and gangue. An additional 110 groups of coal and gangue are employed experimentally to validate the algorithm's accuracy. RESULTS: Compared with the 60% sorting accuracy of the Pseudo-dual-energy method, the new algorithm reached a sorting accuracy of 99%. CONCLUSIONS: Study results demonstrate the superiority of this novel algorithm and its feasibility in practical applications. This novel algorithm can guide other two-substance X-ray sorting applications based on photon counting detectors.

A novel multi-view X-ray digital imaging stitching algorithm.

BACKGROUND: In fan beam X-ray imaging applications, several X-ray images sometimes need to be stitched together into a panoramic image because of the size limitations of the detector. OBJECTIVE: This study aims to propose a novel multi-view X-ray digital imaging stitching algorithm (MVS) based on the CdZnTe photon counting linear array detectors to solve the problem of fan beam X-ray stitching deformation. METHODS: The panoramic image is generated in four steps including (1) multi-view projection data acquisition, (2) overlapping positioning, (3) weighted fusion and (4) projected pixel value calculation. Images of a globe and foot are scanned by fan beam X-rays and a CdZnTe detector. The proposed method is applied to stitch together the scanned images of the globe. Three other methods are also used for comparison. Finally, this MVS algorithm is also used in the stitching of scanned images of the foot. RESULTS: Compared with the 50% stitching accuracy of other methods, the new MVS algorithm reached a stitching accuracy of 94.4%. Image distortion on the globe and feet is also eliminated and thus image quality is significantly improved. CONCLUSIONS: This study proposes a new multi-view X-ray digital imaging stitching algorithm. Study results demonstrate the superiority of this new algorithm and its feasibility in practical applications.

Jianpi-yangwei decoction inhibits DNA damage repair in the drug resistance of gastric cancer by reducing FEN1 expression.

BACKGROUND: Flap Endonuclease 1(FEN1) has been considered as a new tumor marker in recent years and Jianpi Yangwei Decoction (JPYW) is a basic Traditional Chinese Medicine (TCM) for the treatment of gastric cancer. This study aimed to explore the role of FEN1-mediated DNA damage repair in the drug resistance of gastric cancer and the effect of JPYW on it by employing BGC823/5-Fu drug-resistant cell model. METHODS: The DNA repair efficiency of BGC823 and BGC823/5-Fu was compared intracellularly and extracellularly using an extrachromosomal assay system and the reconstituted base excision repair assay. By comparing gene and protein expression and identifying cell survival rates after knockdown or high expression of FEN1, the correlation between FEN1 high expression and 5-Fluorouracil (5-Fu) drug resistance was revealed. The effect of JPYW on DNA damage repair and FEN1 expression was observed by the degree of γ-H2AX phosphorylation in the cells, DNA repair efficiency and enzyme activity, et al. RESULTS: BGC823/5-Fu had a higher DNA repair efficiency than BGC823(P < 0.001), which proved to be both intracellular and extracellular. FEN1 was highly expressed in BGC823/5-Fu regardless of gene level(P < 0.001) or protein level. Furthermore, manipulating FEN1 altered the sensitivity of cancer cells to chemotherapeutic drug 5-Fu. Different concentrations of JPYW were used to investigate the inhibitory effect on the expression of FEN1 and DNA damage repair. JPYW inhibited DNA damage repair both intracellularly and extracellularly: the phosphorylation of γ-H2AX increased, with more DNA damage in the cells; the synthetic 8-oxo dG damage repair was reduced; and the ability of cell lysates to repair DNA damage decreased. The decrease of FEN1 expression in BGC823/5-Fu had a concentration dependent relationship with JYPW. In addition, JPYW inhibited the activity of FEN1 at the enzymatic level, as the amount of cut-off synthetic 32p labeled DNA substrates were decreased. CONCLUSION: FEN1 was highly expressed in drug-resistance gastric cancer cells BGC823/5-Fu, which leading to BGC823 resistant to (5-Fu) by acting on DNA damage repair. JPYW inhibited DNA damage repair and reversed 5-Fu drug resistance by reducing FEN1 expression and inhibiting FEN1 functional activity.

Enhancing Received Signal Strength-Based Localization through Coverage Hole Detection and Recovery.

In wireless sensor networks (WSNs), Radio Signal Strength Indicator (RSSI)-based localization techniques have been widely used in various applications, such as intrusion detection, battlefield surveillance, and animal monitoring. One fundamental performance measure in those applications is the sensing coverage of WSNs. Insufficient coverage will significantly reduce the effectiveness of the applications. However, most existing studies on coverage assume that the sensing range of a sensor node is a disk, and the disk coverage model is too simplistic for many localization techniques. Moreover, there are some localization techniques of WSNs whose coverage model is non-disk, such as RSSI-based localization techniques. In this paper, we focus on detecting and recovering coverage holes of WSNs to enhance RSSI-based localization techniques whose coverage model is an ellipse. We propose an algorithm inspired by Voronoi tessellation and Delaunay triangulation to detect and recover coverage holes. Simulation results show that our algorithm can recover all holes and can reach any set coverage rate, up to 100% coverage.