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Introduction: The development of insecticide resistance in Spodoptera frugiperda populations is a serious threat to the crop industry. Given the spread of invasive resistant populations, prospective monitoring should be accelerated, and the development of diagnostic tools for rapid and accurate assessments of insecticide resistance is essential.Methods: First, the discriminating dose and diagnostic time of the kit were determined by the glass vial method based on a susceptible strain. Then, pests that were collected from field populations were used to determine their susceptibility to seven insecticides by using the diagnostic kit. Finally, the accuracy of the kit was verified based on correlation analyses and the likelihood of insecticide control failure was assessed.Results: Here, we describe a diagnostic kit that enables the rapid detection of resistance to chlorpyrifos, bifenthrin, deltamethrin, lambda-cyhalothrin, phoxim, chlorantraniliprole and chlorfenapyr within 1-2 h in S. frugiperda at diagnostic doses of 0.98, 0.84, 0.38, 1.64, 0.0082, 1.75 and 0.65 μg/cm2, respectively. The linear equation between mortalities under diagnostic doses and actual resistance ratios measured by the diet-overlay bioassay was determined. The high correlation indicates that the insecticide resistance levels diagnosed by the kit were consistent with the results of the diet-overlay bioassay. Moreover, we found a significant negative correlation between diagnostic mortality and the likelihood of control failure for bifenthrin (r = −0.899, p = 0.001), deltamethrin (r = −0.737, p = 0.024) and lambda-cyhalothrin (r = −0.871, p = 0.002).Discussion: The insecticide resistance diagnostic kit for S. frugiperda is a user-friendly tool (portable, short detection time). Its excellent performance qualifies the kit as a reliable screening tool for identifying effective insecticides in sustainable resistance management.

Abstract A large body of literature has shown that ginseng had a role in diabetes mellitus management. Ginsenosides are the main active components of ginseng. But what ginsenosides can manage in diabetic are not systematic. The targets of these ginsenosides are still incomplete. Our aim was to identify which ginsenosides can manage diabetes mellitus through network pharmacology and molecular docking. To identify the targets of these ginsenosides. In this work, we retrieved and screened ginsenosides and corresponding diabetes mellitus targets across multiple databases. PPI networks of the genes were constructed using STRING, and the core targets were screened out through topological analysis. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed by using the R language. Finally, molecular docking was performed after bioinformatics analysis for verification. Our research results showed that 28 ginsenosides in ginseng might be against diabetes mellitus by modulating related proteins such as VEGFA, Caspase 3, and TNF-α. Among the 28 ginsenosides, 20(R)-Protopanaxatriol, 20(R)-Protopanaxadiol, and Ginsenoside Rg1 might play a significant role. Kyoto Encyclopedia of Genes and Genomes and Gene Ontology enrichment analysis showed that the management of diabetes mellitus by ginsenosides may be related to the positive regulation of reactive oxygen metabolic processes, associated with the insulin signaling pathway, TNF signaling pathway, and AMPK signaling pathway. Molecular docking results and molecular dynamics simulation showed that most ginsenosides could stably bind to the core target, mainly hydrogen bonding and hydrophobic bond. This study suggests the management of ginseng on diabetes mellitus. We believe that our results can contribute to the systematic study of the mechanism of ginsenosides for the management of diabetes mellitus. At the same time, it can provide a theoretical basis for subsequent studies on the management of ginsenosides in diabetes mellitus.

ATP-binding cassette transporter C2 (ABCC2) is known to be a receptor for Bacillus thuringiensis (Bt) toxins in several lepidopteran insects. Mutations in the ABCC2 gene have been genetically linked to field-evolved resistance to the Cry1F toxin from Bt in Spodoptera frugiperda. Here we generated a SfABCC2 knockout strain of S. frugiperda using the CRISPR/Cas9 system to provide further functional evidence of the role of this gene in susceptibility and resistance to Cry1F. Results from bioassays showed that the SfABCC2 knockout S. frugiperda strain displayed 118-fold resistance to Cry1F compared with the parental DH19 strain, but no resistance to Vip3A toxin from Bt. These results provide the first reverse genetic evidence for SfABCC2 as a functional receptor for Cry1F.

The fall armyworm, Spodoptera frugiperda, which destroys many economic crops such as rice and maize, has recently invaded China. Insect viruses as biological control agents play important roles in killing pests. One potential viral insecticide is the environmentally highly infective and virulent densovirus. We successfully rescued Junonia coenia densovirus (JcDV) using its infectious clone in different insect cell lines and larvae of three insect species. Results showed that the lysate of cultured insect cells transfected by the JcDV infectious clone killed the 2nd instar S. frugiperda. The LD50 of homogenate from JcDV-infected Spodoptera litura to the 2nd instar S. frugiperda (1.76×108 viral genome copies per larva during 10 d post infection) was higher than that of the 2nd instar S. litura (7.39×107 JcDV genome copies) or Helicoverpa armigera larvae (9.71×107 JcDV genome copies). The LT50 of the S. litura homogenate (2.60×109 viral genome copies each larva) to the 2nd instar S. frugiperda was 6.96 d, longer than that of the S. litura (6.18 d) or the 2nd instar H. armigera (5.94 d). JcDV could infect the fat body of H. armigera, but not S. frugiperda or S. litura. Although JcDV can infect all three lepidopteran species, their susceptibility to the virus differs. JcDV has great potential as a biological control agent against pests such as S. frugiperda.

In this study, we focus on the electronic bus (E-Bus) system developed for Taiwan's mountainous areas. The rural area in Taiwan with its towering mountains has become a sightseeing hot spot. The radio propagation of a (cloud-based) 4G/LTE network may be severely limited by the mountainous geography, leading to unacceptable connection quality. We have built a smart (fog-based) local wireless E-Bus system using a feature-enhanced long-range widearea network (LoRaWAN, also known as GloRa in Taiwan). Since there is no electricity on the mountain roads, the bus stops of this E-Bus system are operated by a dynamo. Furthermore, we present a virtual direction and position algorithm for multiple E-Bus lines. A novel sensing method using the dynamos is proposed to estimate the feasibility of the E-Bus optimization problem. [ABSTRACT FROM AUTHOR]

Indoor positioning systems based on wireless local area networks are growing rapidly in importance and gaining commercial interest. Pedestrian dead reckoning (PDR) systems, which rely on inertial sensors, such as accelerometers, gyroscopes, or even magnetometers to estimate users' movement, have also been widely adopted for real-time indoor pedestrian location tracking. Since both kinds of systems have their own advantages and disadvantages, a maximum likelihood-based fusion algorithm that integrates a typical Wi-Fi indoor positioning system with a PDR system is proposed in this paper. The strength of the PDR system should eliminate the weakness of the Wi-Fi positioning system and vice versa. The intelligent fusion algorithm can retrieve the initial user location and moving direction information without requiring any user intervention. Experimental results show that the proposed positioning system has better positioning accuracy than the PDR system or Wi-Fi positioning system alone. [ABSTRACT FROM PUBLISHER]

Building context-aware services in pervasive computing environments have enabled the wide development of wireless local area network-based indoor positioning systems. In fingerprint localization, radio frequency (RF) signal strengths from access points (APs) are annotated with location labels to build the map of RF fingerprints. However, the newly received signal strength (RSS) variation due to device heterogeneity, which may cause RSS pattern mismatch, could jeopardize positioning accuracy. Solutions based on extra manual calibrations of RSSs for new, individual devices could address the problem. However, they are laborious and unpractical for real-world deployment. In this paper, an indoor positioning algorithm that utilizes two homogeneous features of different devices is proposed to solve the problem of device heterogeneity in fingerprint localization. The features of RSS order and linear dependency between RSSs measured by different devices are extensively investigated. The experimental results show that the proposed positioning algorithm solves the device heterogeneity problem without requiring extra manual calibration for diverse devices. [ABSTRACT FROM PUBLISHER]