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Acute detection and high-resolution imaging of microRNAs (miRNAs) in living cancer cells have attracted great attention in clinical diagnosis and therapy. However, current methods suffer from low detection sensitivity or heavy dependence on expensive and sophisticated spectrometers. Herein, a novel algorithm-assisted system of detecting and imaging miRNAs in living cancer cells was developed via the disassembly of plasmonic core-satellite probes coupled with strand displacement amplification (SDA). The target miRNAs in the system could trigger the disassembly of plasmonic core-satellite probes, leading to the color change in the scattering light of the probes, which could be captured by dark-field microscopy (DFM). The concentration of the target miRNAs was obtained by analyzing the dark-field image based on the proposed algorithm with a detection limit of 2 pM for miRNA-21. Thus, the performance in terms of simplicity and sensitivity of the system compared with one of the conventional spectrophotometers was well presented, which could inspire more clinical applications of inexpensive, intelligent, and rapid screening of cancer cells. The application software based on the proposed algorithm running on the Android platform was also developed, demonstrating the potential of remote diagnosis.

In recent years, the number of elevators has increased dramatically as the increase of high-rise buildings. The safety monitoring of elevators, a matter of people’s security, becomes more and more important. This paper proposed a real-time elevator monitoring system, which can rapidly and accurately diagnose the faults and abnormal states of the elevator based on the real-time operation data acquired from multi sensors. The proposed multi-sensor fusion algorithm effectively ensured the stability and reliability of the system. The real-time monitoring result was easily accessed using web client on various platforms via the local network, which also can be sent to the cloud platform realizing the remote access. The test result of the system demonstrated its usefulness.

Positron emission tomography (PET) scanners with new features, such as open structure, compact size, and adaptive field of view (FOV), have attracted significant attention. Among these novel designs, panel PET has the potential to combine the open structure and variable FOV into a compact form. In this paper, we would like to further exploit these structural advantages by proposing a modified version, called the panel PET with window (PPW). A PPW is a panel PET with a rectangular opening in the center of one detector panel, which inherts the advantages of the compact size and adjustable FOV of the panel PET. Meanwhile, it utilizes fewer detector modules and offers additional flexibility and convenience in practical applications. We quantitatively evaluated the imaging performance of the PPW based on Monte Carlo simulations and real data experiments using a prototype system. The results show that the PPW system sensitivity, spatial resolution, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) deteriorate, and the effective FOV narrows down. However, the deterioration is not linear to the increase of window size. In our extreme case with 69.4% of detectors removed from a panel, the degradation of SNR, CNR, and spatial resolution are 42.4%, 43.1%, and 25.0%, respectively. Meanwhile, the contrast recovery coefficient of PPW remains almost constant.

Based on various adsorption characteristics of resins, a novel method for purifying and preparing moenomycin A from fermentation broth was established by combining different chromatographic modes into a three-step preparative chromatography process. Fermentation broth of moenomycins was firstly prepurified by macroporous adsorbent XAD7HP to remove most strong polar impurities, then further purified by anion exchange resin FPA98Cl, and finally refined moenomycin A was obtained by use of semi-preparative reversed-phase chromatographic column packed with Chromtorex C8 silica gel. As the main indicators, purity and yield of moenomycin A were examined in order to optimise the chromatographic process for each step. Under optimized chromatographic conditions, the purity and total yield of moenomycin A were 95.0 and 22.2 %, and the biological potency of moenomycin A was 2232 U mg−1, significantly higher than 1395 U mg−1, which is the potency of the standard from Agriculture Ministry of China. Three-step preparative chromatographic mode could gradually and effectively remove impurities. The present method is practical, easy to be operated with less solvent consumption, and provides a new idea for the preparation of moenomycin A with high purity.

Rail surface scratching occurs with increasing frequency, seriously threatening the safety of vehicles and humans. Online repair of rail-surface scratches on damaged rails with scratch depths &gt, 1 mm is of increased importance, because direct rail-replacement has the disadvantages of long operation time, high manpower and high material costs. Advanced online repair of rail-surface scratch using three-dimensional (3D) metal printing technology such as laser cladding has become an increasing trend, desperately demanding a solution for the fast and precise establishment of a complete closed mesh model of rail-surface scratch data. However, there have only been limited studies on the topic so far. In this paper, the complete closed mesh model is well established based on a novel triangulation algorithm relying on the topological features of the point-cloud model (PCM) of scratch-data, which is obtained by implementing a scratch-data-computation process following a rail-geometric-feature-fused algorithm of random sample consensus (RANSAC) performed on the full rail-surface PCM constructed by 3D laser vision. The proposed method is universal for all types of normal-speed rails in China. Experimental results show that the proposed method can accurately acquire the complete closed mesh models of scratch data of one meter of 50 Kg/m-rails within 1 min.

With high specificity of tumor necrosis, hypoxia tissues and subclinical lesions, PET may have great potential for tumor surgery guidance. PET images in surgery will tell us how tissues change during the operation and whether the lesion has been cleared. We did research on panel PET guided therapy, and we have developed 3-dimensional reconstruction methods for panel PET systems. However we meet the requirement of a larger open space for operation, because a body covered with two enclosed panels could barely be operated in most tumor surgeries. And the weak performance of images perpendicular to panels leads to invalid guidance in some applications such as radiotherapy guidance. In order to apply the better images to guidance, we designed a panel PET with window for tumor surgery guidance, and it showed good performance of the images parallel to the panels. It is surprising that we took 12 seconds for scanning and acquired images parallel to the panels with good performance in the actual system experiment.