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This study systematically explored the underlying mechanism of ginseng's active ingredients in improving diabetes through network pharmacology combing with molecular docking technology. In this work, we retrieved and screened active compounds of ginseng and corresponding diabetes 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 (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) 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 by modulating related proteins such as VEGFA, Caspase 3, and TNF. Among the 28 ginsenosides, 20(R)-Protopanaxatriol (PPT), (20R)-Protopanaxadiol (PPD), and Ginsenoside Rg1 (Rg1) might play a significant role. KEGG and GO enrichment analysis showed that the improvement of diabetes 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 showed that all ginsenosides could stably bind to the core target, mainly hydrogen bonding. This study suggests the improvement of ginseng on diabetes. We believe that our results can contribute to the systematic study of the mechanism of ginsenosides in improving diabetes. At the same time, it can provide a theoretical basis for subsequent studies on the improvement of ginsenosides in diabetes.

Background. The mode of combining mobile terminals and mobile digital music has gradually entered a bottleneck period while promoting the development of the mobile terminal industry. Proposing personalized solutions for specific groups of people including subhealthy people has become the current direction for the further long-term development of this mode. Understanding the influencing factors that affect subhealthy people’s selection of mobile digital music is an urgent problem that needs to be solved in the development of personalized solutions. Objective. This article analyzes the influencing factors of the purchase intent to buy mobile digital music for subhealthy people and provides suggestions for mobile terminal vendors on how to design personalized solutions for this group of people. Methods. In order to achieve the above goals, this article constructs an influencing factor model based on the theory of perceived value, collects data by means of questionnaires, and uses the method of structural equations to verify the proposed model. Results. The results show that perceived quality, perceived price, social value, and emotional value all have a significant effect on users’ purchase intention. Meanwhile, the conditional value and epistemic value have a negative moderating effect on the relationship between the social value and subhealthy people’s digital music purchase intention but strengthen the positive relationship between the emotional value and subhealthy people’s digital music purchase intention. Conclusions. The analysis shows that mobile terminal vendors should have their own unique attitudes and feelings when designing personalized mobile digital music solutions for subhealthy people, clarify their position, find strategies to improve the experience of subhealthy people, and win the reputation of subhealthy people. Let subhealthy people have a sense of belongingness.

UNSTRUCTURED We evaluate a Bluetooth-based mobile contact-confirming app, COVID-19 Contact-Confirming Application (COCOA), which is being used in Japan to contain the spread of COVID-19, the disease caused by the novel virus termed SARS-COV-2. The app prioritizes the protection of users’ privacy from a variety of parties (eg, other users, potential attackers, and public authorities), enhances the capacity to balance the current load of excessive pressure on health care systems (eg, local triage of exposure risk and reduction of in-person hospital visits), increases the speed of responses to the pandemic (eg, automated recording of close contact based on proximity), and reduces operation errors and population mobility. The peer-to-peer framework of COCOA is intended to provide the public with dynamic and credible updates on the COVID-19 pandemic without sacrificing the privacy of their information. However, cautions must be exercised to address critical concerns, such as the rate of participation and delays in data sharing. The results of a simulation imply that the participation rate in Japan needs to be close 90% to effectively control the spread of COVID-19.

Diamondback moth (DBM), Plutella xylostella, is an important pest of crucifers worldwide. The extensive use of flubendiamide has led to the development of resistance in field populations and reports of control failures. In this study, the lab-selected (Rf) and field-collected (Rb) flubendiamide-resistant strains of P. xylostella with LC50 resistance ratios of 1890-fold and 1251-fold, respectively, were used, as well as a lab-reared flubendiamide-susceptible strain (S). The results showed that the fecundity of the Rf and Rb-resistant strains was significantly lower than that of S strain. The contents of vitellin and transcripts of P. xylostella vitellogenin (PxVg) and P. xylostella vitellogenin receptor (PxVgR) genes in the Rf and Rb strains were significantly higher than those of S strains at 0–48 h after adult eclosion. At 96 h after eclosion, the content of vitellin in the Rf and Rb strains did not differ significantly from those of S strains, whereas transcripts of the PxVg and PxVgR genes in the Rf and Rb strains were significantly lower than that of the S strain. The content of the juvenile hormone III (JH III), β-ecdysone (20E), and the gene expression level of P. xylostella methoprene tolerant (PxMet) in the Rf and Rb strains were significantly higher than that of the S strain. The activity of trehalase was significantly higher in the Rf and Rb strains than that of the S strain in the first to the third instar larvae, whereas in the fourth instar larvae, there was no significantly difference in the three strains. At different times after adult eclosion, the differences in trehalase activity were erratic between the strains. The transcripts of P. xylostella trehalase (PxTre) gene in the Rf and Rb strains were significantly higher than that of the S strain in most developmental stages. Here, we report differences in fecundity between flubendiamide-resistant and susceptible strains of P. xylostella and discuss gene expression of several reproductive factors, which provides a possible explanation for the mechanism of fecundity reduction concurrent with flubendiamide-resistance in P. xylostella.

In this numerical work, a Mach–Zehnder interferometer device with sample and reference arms composed of microstructured chalcogenide optical fibres with AsSe2 core and As2S5 cladding is presented to generate single and double pulses. An unchirped hyperbolic secant-shaped pulse with enough high peak power centered at 1958 nm wavelength and a continuous wave with a very weak power level at 2070 nm wavelength are simultaneously introduced into the sample arm, in which stimulated Raman scattering and strong cross-phase modulation induced by two co-propagating waves give rise to a significant phase shift for a continuous wave. In the reference arm, the continuous wave directly passes through the fibre, where the transmitted wave has a slight phase shift due to the influence of self-phase modulation. Therefore, at the output port of the configuration, the re-combined optical fields at 2070 nm wavelength have a significant phase difference. As a result, both single and double pulses caused by the optical interference at the output port are achieved by judiciously adjusting the phase difference which is mainly controlled by the peak power and temporal width of the input optical pulse, as well as the length of a microstructured optical fibre. In addition, both widths of the single pulse and spacing of the double pulses are directly dependent on the temporal width of the input pulse and the fibre length of the arm.

We evaluate a Bluetooth-based mobile contact-confirming app, COVID-19 Contact-Confirming Application (COCOA), which is being used in Japan to contain the spread of COVID-19, the disease caused by the novel virus termed SARS-COV-2. The app prioritizes the protection of users’ privacy from a variety of parties (eg, other users, potential attackers, and public authorities), enhances the capacity to balance the current load of excessive pressure on health care systems (eg, local triage of exposure risk and reduction of in-person hospital visits), increases the speed of responses to the pandemic (eg, automated recording of close contact based on proximity), and reduces operation errors and population mobility. The peer-to-peer framework of COCOA is intended to provide the public with dynamic and credible updates on the COVID-19 pandemic without sacrificing the privacy of their information. However, cautions must be exercised to address critical concerns, such as the rate of participation and delays in data sharing. The results of a simulation imply that the participation rate in Japan needs to be close 90% to effectively control the spread of COVID-19.

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.

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.

Nowadays, Intelligent Transportation Systems (ITS) technologies are exploring a wide range of services such as freeway management, crash prevention & safety, driver assistance, and infotainment of drivers and/or passengers. In this paper, an agile urban parking recommendation service for vehicular intelligent guiding system is designed to facilitate city citizens with fully efficient, real-time and precise parking lot guiding suggestions for the sustainability of the future green city. The system offers drivers a friendly parking lot recommendation sequence and saves driver's time circling around by the accurate prediction of the successful parking probability in each parking lot. The proposed cost model constructs an optimal recommendation sequence considering successful parking probability and time to reach the parking lot. Through the collection and analysis of realistic records from parking lots in Taipei city, a prediction algorithm is developed to estimate the successful parking probability by using current available space counts. Extensive experiments are conducted to demonstrate the effectiveness of the prediction algorithm.

Phenoloxidase (PO) is an important enzyme in insect life, which is involved in important physical functions, such as defensive encapsulation and melanization of foreign organisms and wound healing. In this study, we obtained a cDNA sequence of 2838 bp with 2049 open reading frames encoding 682 amino acids. The protein sequence deduced from the cDNA has high homology with the known PPO1 sequences of other lepidopterous insects. There were three conserved regions, including the two copper-binding sites characteristic of arthropod PPOs. The whole PxPPO1 DNA was also obtained with 7202 bp when the five fragments were stitched together and the overlapping sequences were deleted. The PxPPO1 DNA consists of 11 introns and 12 exons, and the homology is 99.9% when the exons are compared with the above cDNA. Moreover, the gene expression levels were also determined by semiquantitative polymerase chain reaction (PCR), Western blotting, and real-time quantitative PCR; the results indicated that PxPPO1 transcripts in the eggs and the fourth instar larvae were more abundant, followed by the second and the third instar larvae, prepupae, and pupa.