Molecular cloning and expression profiles of MnSOD and CAT genes from the turbot <em>Scophthalmus maximus</em>

Manganese superoxide dismutase (MnSOD) and catalase (CAT) could eliminate reactive oxygen species (ROS) and maintain the reduction-oxidation balance in cells. This study aimed to investigate their functions in turbot (Scophthalmus maximus) response to the *Vibro anguillarum* challenge. SmMnSOD, the full-length liver cDNA of MnSOD from *S. maximus*, was cloned by fast amplification of cDNA ends (RACE). Sequencing of nucleotides indicated that the SmMnSOD cDNA was 1267 base pairs with a 684-base-pair open reading frame, encoding a 228 amino acid protein with 28 amino acid residues. The SmMnSOD sequence contains MnSOD signatures (DVWEHAYY) and probable N-glycosylation sites (NVT, NHT, and NLS). The deduced sequence of SmMnSOD revealed sequence homology between 85.3% and 92.9% with those of other species. A phylogenetic study found that SmMnSOD clustered with other fish MnSOD, indicating that SmMnSOD was a member of the MnSOD family. The SmMnSOD transcript was discovered by qRT-PCR in the gill, stomach, head-kidney, muscle, liver, intestine, and heart of *S. maximus*, with the highest expression in the liver. Upon intervention by *V. anguillarum*, the liver and head kidney transcript levels of SmMnSOD were up-regulated at 12 and 48 h, whereas the temporal expression profiles of the CAT transcript increased at 6 and 24 h. As the pathogenic bacterial stress processing was prolonged to 72 h, the liver and head kidney transcript levels of SmMnSOD and CAT decreased gradually. Thus, SmMnSOD was triggered and may be related to *S. maximus*' immunological responses against *V. anguillarum*

Mn-doped CoSe2 nanosheets as high-efficiency catalysts for the oxygen evolution reaction.

In this work, we introduce for the first time an aqueous solution method followed by a selenization step to prepare Mn-doped CoSe2 nanosheets supported on nickel foam for the oxygen evolution reaction. These findings provide us highly efficient electrocatalysts instead of noble metal catalysts for the oxygen evolution reaction

Association of Mitochondrial DNA Variations with Lung Cancer Risk in a Han Chinese Population from Southwestern China

Mitochondrial DNA (mtDNA) is particularly susceptible to oxidative damage and mutation due to the high rate of reactive oxygen species (ROS) production and limited DNA-repair capacity in mitochondrial. Previous studies demonstrated that the increased mtDNA copy number for compensation for damage, which was associated with cigarette smoking, has been found to be associated with lung cancer risk among heavy smokers. Given that the common and “non-pathological” mtDNA variations determine differences in oxidative phosphorylation performance and ROS production, an important determinant of lung cancer risk, we hypothesize that the mtDNA variations may play roles in lung cancer risk. To test this hypothesis, we conducted a case-control study to compare the frequencies of mtDNA haplogroups and an 822 bp mtDNA deletion between 422 lung cancer patients and 504 controls. Multivariate logistic regression analysis revealed that haplogroups D and F were related to individual lung cancer resistance (OR = 0.465, 95%CI = 0.329–0.656, p<0.001; and OR = 0.622, 95%CI = 0.425–0.909, p = 0.014, respectively), while haplogroups G and M7 might be risk factors for lung cancer (OR = 3.924, 95%CI = 1.757–6.689, p<0.001; and OR = 2.037, 95%CI = 1.253–3.312, p = 0.004, respectively). Additionally, multivariate logistic regression analysis revealed that cigarette smoking was a risk factor for the 822 bp mtDNA deletion. Furthermore, the increased frequencies of the mtDNA deletion in male cigarette smoking subjects of combined cases and controls with haplogroup D indicated that the haplogroup D might be susceptible to DNA damage from external ROS caused by heavy cigarette smoking

Effects of MoO3 and CeO2 doping on the decomposition and reactivity of NH4HSO4 on V2O5/TiO2 catalysts

The deposition of NH4HSO4 on catalysts is one of the key issues for selective catalytic reduction of NOx. In this study, NH4HSO4 was preloaded on catalysts, and the effects of MoO3 and CeO2 doping on the decomposition and reactivity of NH4HSO4 on V2O5/TiO2 catalysts are studied. The results show that the introduction of MoO3 and CeO2 significantly promoted NOx conversion on the V2O5/TiO2 catalysts. Doping with MoO3 could effectively enhance the S and H2O resistance of the catalysts. Fourier transform infrared spectroscopy (FTIR) and X-ray photoelectron spectroscopy (XPS) analysis indicate that it is the strong chemical interactions between NH4HSO4 and the catalysts that are adverse to the decomposition of NH4HSO4. However, doping with MoO3 apparently inhibits these interactions, which significantly decrease the decomposition temperature of NH4HSO4. In situ FTIR experiments show that the NH4+ in preloaded NH4HSO4 could react with gaseous NO on catalysts, and doping with MoO3 could facilitate the reaction rate

Flow characteristics in free impinging jet reactor by particle image velocimetry (PIV) investigation

The flow characteristics in free impinging jet reactors (FIJRs) were investigated using particle image velocimetry (PIV). The effects of the Reynolds number (Re) and the ratio of jet distance to jet diameter (w/d) on flow behavior were discussed for equal volumetric flow rates of the two jets. The impingement plane, instantaneous velocity, mean velocity, and turbulent kinetic energy (TKE) distribution of FIJRs are measured from captured images using the PIV technique. As Re increases, the average diameter of the impingement plane linearly increases. The instability of the liquid is closely related to the jet velocity or the Re. However, the stagnation point is insensitive to the variation of the Re. The droplets break up from the turbulent liquid in the 'wall-free' environment of FIJRs, so that the liquid back-flow found in confined impinging jet reactors (CIJRs) is not observed. Increasing the Re from 1800-4100 or decreasing the w/d from 20-6 plays a similar role in increasing the TKE values and intensifying turbulence, which promotes the momentum transfer and mixing efficiency in FIJRs

Multi-Block Mixed Sample Semi-Supervised Learning for SAR Target Recognition

In recent years, synthetic aperture radar (SAR) automatic target recognition has played a crucial role in multiple fields and has received widespread attention. Compared with optical image recognition with massive annotation data, lacking sufficient labeled images limits the performance of the SAR automatic target recognition (ATR) method based on deep learning. It is expensive and time-consuming to annotate the targets for SAR images, while it is difficult for unsupervised SAR target recognition to meet the actual needs. In this situation, we propose a semi-supervised sample mixing method for SAR target recognition, named multi-block mixed (MBM), which can effectively utilize the unlabeled samples. During the data preprocessing stage, a multi-block mixed method is used to interpolate a small part of the training image to generate new samples. Then, the new samples are used to improve the recognition accuracy of the model. To verify the effectiveness of the proposed method, experiments are carried out on the moving and stationary target acquisition and recognition (MSTAR) data set. The experimental results fully demonstrate that the proposed MBM semi-supervised learning method can effectively address the problem of annotation insufficiency in SAR data sets and can learn valuable information from unlabeled samples, thereby improving the recognition performance

CFD Simulation of Dry Pressure Drop in a Cross-Flow Rotating Packed Bed

The cross-flow rotating packed bed (RPB) has attracted wide attention in recent years because of its advantages of large gas capacity, low pressure drop and lack of flooding limitation. However, the complex structure of the packing makes it difficult to obtain the gas flow characteristics in the cross-flow RPB by experiments. In this study, the dry pressure drop in the cross-flow RPB was investigated by computational fluid dynamics (CFD). The packing was modeled by the porous media model and the rotation of the packing was simulated by the sliding mesh model. The simulation results obtained by three turbulence models were compared with experimental results, and the RNG k-ε model was found to best describe the turbulence behaviors in the cross-flow RPB. Then, the effects of gas flow rate and rotating speed on dry pressure drop in different parts of the cross-flow RPB were analyzed. The results of this study can provide important insights into the design and scale-up of cross-flow RPB

Use of neighborhood unhomogeneity to detect the edge of hyperspectral spatial stray light region

Since hyperspectral images contain fine spectral information of the target objects, there is continuous demand for the detailed analysis about such images. A somewhat neglected but critically important challenge regarding hyperspectral image is the presence of "spatial stray light" - a phenomenon caused by scattering of photons from target objects. In this study, neighborhood unhomogeneity method is used to detect the edge of spatial stray light region in hyperspectral images. Analyses were conducted on reflectance datasets of standard card, potato leaf, and corn kernels from three inbred lines. By using neighborhood unhomogeneity method, the edge of spatial stray light region could be detected obviously and experimental results show the effectiveness of the proposed method. © 2014 Elsevier GmbH