Search

Cs2LiLaBr6: Ce (CLLB) scintillator with the size of Φ 21mm × 25 mm coupled with PMT was used to detect neutron and gamma rays. The pulse shape discrimination (PSD) of neutrons and gamma rays by charge comparison method, the neutrons and gamma rays from AmBe source and fast neutron beam can be separated with figure-of-merit (FOM) values of 0.9 and 1.3, respectively. However, some neutron and gamma rays are difficult to distinguish, so new algorithms need to be investigated to improve the PSD performance of neutron and gamma. Artificial neural networks (ANN) have a very good image recognition capability, thus the ANN model was constructed to discriminate the waveforms of neutron and gamma rays. After ANN model training, the neutron and gamma signals of the CLLB detector were recognized with an accuracy of 98%, and the FOM value of the ANN method was calculated to be 19.4. This result is much higher than the charge comparison method, indicating better discrimination between neutrons and gamma rays with the ANN method.

Although most of the damage caused by lepidopteran insects to plants is caused by the larval stage, chemosensory systems have been investigated much more frequently for lepidopteran adults than for larvae. The fall armyworm Spodoptera frugiperda (J. E. Smith) (Lepidoptera: Noctuidae) is a polyphagous and worldwide pest. To understand the larval chemosensory system in S. frugiperda, we sequenced and assembled the antennae and maxillae transcriptome of larvae in the sixth instar (larval a-m) using the Illumina platform. A total of 30 putative chemosensory receptor genes were identified, and these receptors included 11 odorant receptors (ORs), 4 gustatory receptors (GRs), and 15 ionotropic receptors/ionotropic glutamate receptors (IRs/iGluRs). Phylogeny tests with the candidate receptors and homologs from other insect species revealed some specific genes, including a fructose receptor, a pheromone receptor, IR co-receptors, CO2 receptors, and the OR co-receptor. Comparison of the expression of annotated genes between S. frugiperda adults and larvae (larval a-m) using RT-qPCR showed that most of the annotated OR and GR genes were predominantly expressed in the adult stage, but that 2 ORs and 1 GR were highly expressed in both the adult antennae and the larval a-m. Although most of the tested IR/iGluR genes were mainly expressed in adult antennae, transcripts of 3 iGluRs were significantly more abundant in the larval a-m than in the adult antennae of both sexes. Comparison of the expression levels of larval a-m expressed chemosensory receptors among the first, fourth, and sixth instars revealed that the expression of some of the genes varied significantly among different larval stages. These results increase our understanding of the chemosensory systems of S. frugiperda larvae and provide a basis for future functional studies aimed at the development of novel strategies to manage this pest.

Diagnosability is often considered as an important factor for measuring the self-diagnostic ability of network systems. However, classic system-level diagnosis focuses only on processor faults and ignores the objective reality of communication faults. Under real circumstances, missing edges and node failures usually occur simultaneously in multiprocessor systems (called hybrid fault circumstances). Therefore, it is important to study the diagnosability of multiprocessor systems under hybrid fault circumstances. In this paper, we propose several diagnosabilities of interconnection networks with missing edges and faulty nodes. By exploring some important relationships between diagnosability and the minimum degree of a network under hybrid fault circumstances, we present and prove the diagnosability of several classic interconnection networks, including BC (bijective connection) networks, star graphs, folded hypercubes, exchanged hypercubes, exchanged crossed cubes, k-ary n-cubes, bubble-sort star graphs and balanced hypercubes, with missing edges and broken-down nodes under the PMC (Preparata, Metze and Chien) and MM* (Maeng and Malek) models. [ABSTRACT FROM AUTHOR]