Search

Currently, complex scene classification strategies are limited to high-definition image scene sets, and low-quality scene sets are overlooked. Although a few studies have focused on artificially noisy images or specific image sets, none have involved actual low-resolution scene images. Therefore, designing classification models around practicality is of paramount importance. To solve the above problems, this paper proposes a two-stage classification optimization algorithm model based on MPSO, thus achieving high-precision classification of low-quality scene images. Firstly, to verify the rationality of the proposed model, three groups of internationally recognized scene datasets were used to conduct comparative experiments with the proposed model and 21 existing methods. It was found that the proposed model performs better, especially in the 15-scene dataset, with 1.54% higher accuracy than the best existing method ResNet-ELM. Secondly, to prove the necessity of the pre-reconstruction stage of the proposed model, the same classification architecture was used to conduct comparative experiments between the proposed reconstruction method and six existing preprocessing methods on the seven self-built low-quality news scene frames. The results show that the proposed model has a higher improvement rate for outdoor scenes. Finally, to test the application potential of the proposed model in outdoor environments, an adaptive test experiment was conducted on the two self-built scene sets affected by lighting and weather. The results indicate that the proposed model is suitable for weather-affected scene classification, with an average accuracy improvement of 1.42%. [ABSTRACT FROM AUTHOR]

In addition to traditional linear Doppler shift, the angular Doppler shift in vortex electromagnetic wave (VEMW) radar systems carrying orbital angular momentum (OAM) can provide more accurate target identification micro-motion parameters, especially the detailed features perpendicular to the radar line-of-sight (LOS) direction. In this paper, a micro-motion feature extraction method for a spinning target with multiple scattering points based on VEMW radar is proposed. First, a multi-scattering-point spinning target detection model using vortex radar is established, and the mathematical mechanism of echo signal flash shift in time-frequency (TF) domain is deduced. Then, linear Doppler shift is eliminated by interference processing with opposite dual-mode VEMW. Subsequently, the shift in TF flicker is focused on the reference zero frequency by the iterative phase compensation method, and the number of scattering points is estimated according to the focusing effect. After this, through the constructed compensation phase, the angular Doppler shift is separated, then the angular velocity, rotation radiusand initial phase of the target are estimated. Theoretical and simulation results verify the effectiveness of the proposed method, and more accurate rotation parameters can be obtained in the case of multiple scattering points using the VEMW radar system. [ABSTRACT FROM AUTHOR]

In cognitive radio (CR) networks, it is crucial for secondary users to quickly detect spectrum holes when prior information of primary users is unknown. This paper proposes a new cooperative spectrum sensing (CSS) scheme based on nonparametric cumulative sum (NCUSUM) to reduce the mean detection delay under the condition of unknown prior information. The proposed scheme consists of secondary users and fusion center. Secondary users preprocess the observation data of spectrum to get positive drifts and negative drifts and only transmit positive drifts to fusion center. Fusion center uses the NCUSUM to accumulate positive drifts to make a fast decision about whether the primary signal is present or not. To ensure the false alarm probability low enough, this scheme notes that the decision can be made in certain time interval. The simulation results show that the proposed cooperative spectrum sensing scheme has better performance in reducing mean detection delay with respect to conventional soft combination schemes. [ABSTRACT FROM AUTHOR]

Neurotoxic effects of MPTP(1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine) were evaluated in vitro using a human neuronal cell line, SH-SY5Y, that contained features contributing to expression of MPTP toxicity in vivo, namely, a transport system for dopamine (DA) and monamine oxidase (MAO) activity. In this model system,MPTPwas found toreducelevels of catecholamines (DA,norepinephrine, epinephrine), serotonin (5-HT), and the 5-HT metabolite 5-hydroxyindoleacetic acid (5-HIAA). MPTP enhanced 3H-DA release, which could contribute to the reduction in DA concentrations seen in these cells. In addition, MPTP inhibited MAO activity (Ki 2.26 10 5 M). Pretreatment with the MAO inhibitor pargyline protected the cells from MPTP-induced alterations of catecholamines and the decrease in 5-HT. In this in vitro model, the cholinergic antagonists atropine and d -tubocurarine also protected cells from MPTP-induced alterations of catecholamines. The capability of cholinergic antagonists to prevent the MPTPinduced alterations of catecholamineconcentrations suggests a possiblecholinergic contribution to MPTP neurotoxicity in this cell line. [ABSTRACT FROM AUTHOR]

Induced resistance responses play a potent role in plant defense system against pathogen attack. Bacillus cereus AR156 is a plant growth promoting rhizobacterium (PGPR) that installs induced systemic resistance (ISR) to Pseudomonas syringae pv. tomato ( Pst ) in Arabidopsis . Here, we show that AR156 leaf infiltration enhances disease resistance in Arabidopsis through the activation of a systemic acquired resistance (SAR). PR1 protein expression and reactive oxygen species (ROS) burst are strongly induced in plants treated with AR156 and inoculated with Pst than that in plants inoculated with Pst only. Moreover, AR156 can trigger SAR in jar1 or ein2 mutants, but not in the NahG transgenic and NPR1 mutant plants. Our results indicate that AR156-induced SAR depends on SA-signaling pathway and NPR1 , but not JA and ET. Also, AR156-treated plants are able to rapidly activate MAPK signaling and FRK1 gene expression, which are involved in pathogen associated molecular pattern (PAMP)-triggered immunity (PTI). Altogether, our results indicate that AR156 can induce SAR by the SA-signaling pathways in an NPR1 -dependent manner and involves multiple PTI components. [ABSTRACT FROM AUTHOR]

Small RNA (sRNA) is a class of noncoding RNA that can silence the expression of target genes. In rice, the majority of characterized sRNAs are within the range of 21 to 24 nucleotides (nt) long, whose biogenesis and function are associated with a specific sets of components, such as Dicer-like (OsDCLs) and Argonaute proteins (OsAGOs). Rice sRNAs longer than 24 nt are occasionally reported, with biogenesis and functional mechanism uninvestigated, especially in a context of defense responses against pathogen infection. By using deep sequencing, we identified a group of rice long small interfering RNAs (lsiRNAs) that are within the range of 25 to 40 nt in length. Our results show that some rice lsiRNAs are differentially expressed upon infection of Rhizoctonia solani, the causal agent of the rice sheath blight disease. Bioinformatic analysis and experimental validation indicate that some rice lsiRNAs can target defense-related genes. We further demonstrate that rice lsiRNAs are neither derived from RNA degradation nor originated as secondary small interfering RNAs (siRNAs). Moreover, lsiRNAs require OsDCL4 for biogenesis and OsAGO18 for function. Therefore, our study indicates that rice lsiRNAs are a unique class of endogenous sRNAs produced in rice, which may participate in response against pathogens.