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Grain crops are easily contaminated by fungi due to the existence of various microorganisms in the storage process, especially in humid and warm storage conditions. Compared with conventional methods, surface-enhanced Raman scattering (SERS) has paved the way for the detection of fungi in grain crops as it is a rapid, nondestructive, and sensitive analytical method. In this work, Aspergillus niger, Saccharomyces cerevisiae, Fusarium moniliforme and Trichoderma viride in grain crops were detected using colloidal Au nanoparticles and SERS. The results indicated that different fungi showed different Raman phenotypes, which could be easily characterized by SERS. Combined with multivariate statistical analysis, identification of a variety of fungi could be accomplished rapidly and accurately. This research can be applied for the rapid detection of fungi in the food and biomedical industries. [ABSTRACT FROM AUTHOR]

In order to solve the ill-posed problem in the process of reconstructing the spectral reflectance of the traditional matrix R method, a regularization matrix R method was proposed in this paper. Through analyzing the ill-posed equation of matrix R to reconstruct the spectral reflectance, the Tikhonov regularization method was researched to restrict the ill-posed problem to solve the Moore-Penrose pseudo inverse matrix. The L-curve method was used to obtain the optimal regularization parameter by training samples data in order to effectively restrict the ill-posed situation which was caused by the equation solving of spectral reconstruction. The experimental results verified that the proposed regularization matrix R method had higher spectral and chromatic accuracy of reconstructed spectrum than traditional matrix R method. At the same time, the proposed regularization matrix R method achieved good performance for color reproduction of real mural in practical application. [ABSTRACT FROM AUTHOR]

Cloud and snow in remote sensing images typically block the underlying surface information and interfere with the extraction of available information, so detecting cloud and snow becomes a critical problem in remotely sensed image processing. The current methods for detecting clouds and snow are susceptible to interference from complex background, making it difficult to recover cloud edge details and causing missing and false detection phenomena. To address these issues, a cross-dimensional feature attention aggregation network is suggested to realize the segmentation of clouds and snow. To address the problem of interference induced by the similar spectral characteristics of clouds and snow, the context attention aggregation module is added to conflate feature maps of various dimensions and screen the information. Multi-scale strip convolution module (MSSCM) and its improved version MSSCMs are used to extract edge characteristics at different scales and improve the harsh segmentation border. Also, adding deep feature semantic information extraction module to deep features to guide the classification of the model to avoid the interference of complex background. Finally, a 'los beatles' module is used to replace the traditional linear combination in the decoding stage, and the feature information of different granularity is fused and extracted to enhance the model's detection efficiency. In this paper, experiments are carried out on the public datasets: CSWV, HRC _ WHU and L8 _ SPARCS. The MIOU scores on the three datasets are 89.507 % , 91.674 % and 80.722 % , respectively. Comparative experiment findings demonstrate that the network presented in this article can attain the highest detection accuracy and good detection efficiency with low parameters. [ABSTRACT FROM AUTHOR]

In order to solve the geometric offset caused by replacing the filter during imaging of multichannel spectral image data, a multichannel spectral image registration method based on SURF feature merged with maximum submatrix is proposed. Firstly, the feature of multichannel spectral image is extracted by SURF. Then, a perspective transformation is performed to obtain a preliminary registration image. For the problem of invalid areas with zero pixel values appearing at the boundary of the image after registration, the largest submatrix is used to detect the maximum inscribed rectangle of the image to remove the invalid boundary region, and maximize the reserved effective region information. Experimented was processed with multichannel imaging data of murals. Experimental results agree with the theoretic analysis and verified that the proposed registration method is better adapted to image scale and brightness changing. At the same time, it can avoid the influence of invalid regions generated by other registration methods on subsequent spectral reconstruction and color restoration which has better performance. [ABSTRACT FROM AUTHOR]

This document is a correction notice for an article titled "Exogenous Adenosine Antagonizes Excitatory Amino Acid Toxicity in Primary Astrocytes" published in the journal Cellular & Molecular Neurobiology. The correction addresses errors in Figure 3A and a typo in the funding section. The corrected version of Figure 3 is provided, showing the effects of gap junction intercellular communication in the OGD/R model. The funding section has also been corrected. The original article has been updated. [Extracted from the article]

Excitatory toxicity is still a hot topic in the study of ischemic stroke, and related research has focused mainly on neurons. Adenosine is an important neuromodulator that is known as a "biosignature" in the central nervous system (CNS). The protective effect of exogenous adenosine on neurons has been confirmed, but its mechanism remains elusive. In this study, astrocytes were pretreated with adenosine, and the effects of an A2a receptor (A2aR) inhibitor (SCH58261) and A2b receptor (A2bR) inhibitor (PSB1115) on excitatory glutamate were investigated. An oxygen glucose deprivation/reoxygenation (OGD/R) and glutamate model was generated in vitro. Post-model assessment included expression levels of glutamate transporters (glt-1), gap junction protein (Cx43) and glutamate receptor (AMPAR), Na+-K+-ATPase activity, and diffusion distance of dyes. Glutamate and glutamine contents were determined at different time points. The results showed that (1) adenosine could improve the function of Na+-K+-ATPase, upregulate the expression of glt-1, and enhance the synthesis of glutamine in astrocytes. This effect was associated with A2aR activation but not with A2bR activation. (2) Adenosine could inhibit the expression of gap junction protein (Cx43) and reduce glutamate diffusion. Inhibition of A2aR attenuated adenosine inhibition of gap junction intercellular communication (GJIC) in the OGD/R model, while it enhanced adenosine inhibition of GJIC in the glutamate model, depending on the glutamate concentration. (3) Adenosine could cause AMPAR gradually entered the nucleus from the cytoplasm, thereby reducing the expression of AMPAR on the cell membrane. Taken together, the results indicate that adenosine plays a role of anti-excitatory toxicity effect in protection against neuronal death and the functional recovery of ischemic stroke mainly by targeting astrocytes, which are closely related to A2aR. The present study provided a scientific basis for adenosine prevention and ischemic stroke treatment, thereby providing a new approach for alleviating ischemic stroke. [ABSTRACT FROM AUTHOR]

Densities, viscosity and bubble-point vapor pressures for binary mixtures of dimethoxy methane and a hydrocarbon fuel (exo-tetrahydrodicyclopentadiene) were measured over the whole composition range. The excess molar volumes ( V m E ) and viscosity deviations (Δη) for the binary systems were calculated from the density and viscosity data. The Antoine equation was fitted with the experimental vapor pressures, and the corresponding parameters were calculated. Positive values of excess molar volumes, negative viscosity deviations and positive deviations from Raoult's law for the vapor pressures are observed. The three physical properties and the corresponding calculation results provide valuable information on the application and study of mixed liquid hydrocarbon fuels. [ABSTRACT FROM AUTHOR]

Measurements of density, viscosity and vapor pressure for binary mixtures of exo-tetrahydrodicyclopentadiene (JP-10) with isopropyl ether are reported at temperatures of (293.15, 298.15, 303.15, 308.15, and 313.15) K over the entire composition range. The excess molar volumes, viscosity deviation and excess Gibbs energies of activation for the binary systems were calculated from the experimental values and fitted with the Redlich-Kister equation. Isopropyl ether was added to enhance the vapor pressure of JP-10. Experimental vapor pressure data were correlated by the Antoine equation. Several semi-empirical equations were used to correlate the viscosity data. The McAllister equation gives relatively satisfactory results for the correlation. The experimental and correlated data could be used in the development of models for mixtures of hydrocarbons with oxygenates. [ABSTRACT FROM AUTHOR]