High quality 3D reconstruction based on fusion of polarization imaging and binocular stereo vision

Polarization imaging can retrieve inaccurate objects’ 3D shapes with fine textures, whereas coarse but accurate depths can be provided by binocular stereo vision. To take full advantage of these two complementary techniques, we investigate a novel 3D reconstruction method based on the fusion of polarization imaging and binocular stereo vision for high quality 3D reconstruction. We first generate the polarization surface by correcting the azimuth angle errors on the basis of registered binocular depth, to solve the azimuthal ambiguity in the polarization imaging. Then we propose a joint 3D reconstruction model for depth fusion, including a data fitting term and a robust low-rank matrix factorization constraint. The former is to transfer textures from the polarization surface to the fused depth by assuming their relationship linear, whereas the latter is to utilize the low-frequency part of binocular depth to improve the accuracy of the fused depth considering the influences of missing-entries and outliers. To solve the optimization problem in the proposed model, we adopt an efficient solution based on the alternating direction method of multipliers. Extensive experiments have been conducted to demonstrate the efficiency of the proposed method in comparison with state-of-the-art methods and to exhibit its wide application prospects in 3D reconstruction.     

TiO2/MXene-Assisted LDI-MS for Urine Metabolic Profiling in Urinary Disease

Cancer remains an intractable medical problem. Rapid diagnosis and identification of cancer are critical to differentiate it from nonmalignant diseases. High-throughput biofluid metabolic analysis has potential for cancer diagnosis. Nevertheless, the present metabolite analysis method does not meet the demand for high-throughput screening of diseases. Herein, a high-throughput, cost-effective, and noninvasive urine metabolic profiling method based on TiO₂/MXene-assisted laser desorption/ionization mass spectrometry (LDI-MS) is presented for the efficient screening of bladder cancer (BC) and nonmalignant urinary disease. Combined with machine learning, TiO₂/MXene-assisted LDI-MS enables high diagnostic accuracy (96.8%) for the classification of patient groups (including 47 BC and 46 ureteral calculus (UC) patients) from healthy controls (113 cases). In addition, BC patients can also be identified from noncancerous UC individuals with an accuracy of 88.3% in the independent test cohort. Furthermore, metabolite variations between BC and UC individuals are investigated based on relative quantification, and related pathways are also discussed. These results suggest that this method, based on urine metabolic patterns, provides a potential tool for rapidly distinguishing urinary diseases and it may pave the way for precision medicine.     

Bioactive compounds and antioxidant activities of the Korean lotus leaf (Nelumbo nucifera) condiment: volatile and nonvolatile metabolite profiling during fermentation

Recent studies have shown that lotus (Nelumbo nucifera) leaf has various pharmacological effects. However, there have been no scientific investigations into these leaves as a fermented crude liquid. This study compared the in vitro antioxidant capacity of lotus leaf‐fermented broth (LLFB) with that of 57° Brix sugar broth (SB) as a control over a period of 6 months based on 1,1‐diphenyl‐2‐picrylhydrazyl radical scavenging activity, ferric ion reducing power, superoxide dismutase‐like activity, tyrosinase inhibition and nitrite scavenging activity. The dominant species during fermentation process were Leuconostoc lactis and Saccharomyces cerevisiae for LLFB. A total of thirty‐six metabolites such as alkaloids, fatty acids, organic acids, phenolics, sugar and sugar derivatives, ethyl esters and monoterpenoids differed between SB and LLFB using gas chromatography–mass spectrometry. Meanwhile, nine volatile compounds in LLFB contributed pleasant, slightly sweetish and fruity odour of condiment and sensory evaluation score of 4.06 ± 1.52 in the proportion of 1:9 LLFB/water.     

Impact of an Engineered Copper-Titanium Dioxide Nanocomposite and Parent Substrates on the Bacteria Viability,Antioxidant Enzymes and Fatty Acid Profiling

Due to the systematic increase in the production of nanomaterials (NMs) and their applications in many areas of life, issues associated with their toxicity are inevitable. In particular, the performance of heterogeneous NMs, such as nanocomposites (NCs), is unpredictable as they may inherit the properties of their individual components. Therefore, the purpose of this work was to assess the biological activity of newly synthesized Cu/TiO₂-NC and the parent nanoparticle substrates Cu-NPs and TiO₂-NPs on the bacterial viability, antioxidant potential and fatty acid composition of the reference Escherichia coli and Bacillus subtilis strains. Based on the toxicological parameters, it was found that B. subtilis was more sensitive to NMs than E. coli. Furthermore, Cu/TiO₂-NC and Cu-NPs had an opposite effect on both strains, while TiO₂-NPs had a comparable mode of action. Simultaneously, the tested strains exhibited varied responses of the antioxidant enzymes after exposure to the NMs, with Cu-NPs having the strongest impact on their activity. The most considerable alternations in the fatty acid profiles were found after the bacteria were exposed to Cu/TiO₂-NC and Cu-NPs. Microscopic images indicated distinct interactions of the NMs with the bacterial outer layers, especially in regard to B. subtilis. Cu/TiO₂-NC generally proved to have less distinctive antimicrobial properties on B. subtilis than E. coli compared to its parent components. Presumably, the biocidal effects of the tested NMs can be attributed to the induction of oxidative stress, the release of metal ions and specific electrochemical interactions with the bacterial cells.     

Evaluation of passive microwave snow water equivalent algorithms in the depth hoar-dominated snowpack of the Kuparuk River Watershed, Alaska, USA

This research investigates the utility of passive microwave remote sensing instruments to accurately determine snow water equivalent (SWE) over large spatial extents. Three existing Special Sensor Microwave Imager (SSM/I) snow water equivalent algorithms produced by Chang, Tait and Goodison were evaluated for their ability to determine snow water equivalent in a snowpack containing substantial depth hoar, large faceted snow crystals. The Kuparuk River Watershed (8140 km²) test site on the North Slope of Alaska was chosen for its snowpack containing a think depth hoar layer and long history of ground truth data. A new regional snow water equivalent algorithm was developed to determine if it could produce better results than the existing algorithms in an area known to contain significant depth hoar. The four algorithms were tested to see how well they could determine snow water equivalent: (1) on a per pixel basis, (2) across swath-averaged spatial bands of approximately 850 km², and (3) on a watershed scale. The algorithms were evaluated to see if they captured the annual spatial distribution in snow water equivalent over the watershed. Results show that the algorithms developed by Chang and from this research are generally within 3 cm of the spatially averaged snow water equivalents over the entire watershed. The algorithms produced by Chang, Tait, and in this research were able to predict the basin-wide ground measured snow water equivalent value within a percent error range from −32.4% to 24.4% in the years with a typical snowpack. None of the algorithms produce accurate results on a pixel-by-pixel scale, with errors ranging from −26% to 308%.     

条形码中距离动态识别技术研究

本文讨论了条形码中距离动态识别技术中扫描景深与扫描光束波长和条宽等要素之间的关系，提出了改善条形码读取距离的３种方法。为扩大条形码在工业过程控制、企业管理等领域的应用范围提供了理论依据。     

人支气管上皮靶细胞形态学参数的测量

支气管上皮靶细胞形态学参数对计算受氡子体照射的支气管的剂量是很重要的。本文介绍利用奥尔新兰-PAS 染色的外科切除人肺组织切片,测量基底细胞粘液细胞和的胞核深度与数目。结果表明,叶、段和小支气管的粘液细胞核深度分别为相应节段基底细胞的61%、69%和73%;此三节段粘液细胞的数目分别为基底细胞的53%、29%和28%,平均为37%。     

Accurate depth profiling through energy-dependent pulse height deficit compensation in gas ionization detectors

The impact of the pulse height deficit effect in gas ionization detectors on the accurate extraction of depth information from heavy ion elastic recoil detection spectra has been investigated. Thin GaN films and Ge_xSi_1−x/Si heterostructures have been analyzed with a 200 MeV ¹⁹⁷Au beam. Employing an empirical parameterisation of the pulse height deficit, a global energy calibration of the detector can be achieved. Energy spectra have been compared, calibrated with either a constant or a full energy-dependent compensation for the deficit. A constant compensation results in significant distortion of the extracted depth profile for heavier ions, whereas an energy-dependent compensation yields true concentration–depth profiles.