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Endoclita signiferWalker is the most destructive wood-boring pest of Eucalyptusin China, causing significant economic and ecological damage. As an insect of the primitive Lepidoptera family Hepialidae, E. signiferfly and mat for only 10−20 min at dusk. The courtship and mating behavior of E. signiferadults and whether male moths release sex pheromones are still unknown, especially since transitory flight survival strategies in primitive moths differ from advanced moths like noctuids. In this study, we first observed the courtship and mating behavior of E. signiferby considering the effects of space and then analyzed extracts of male hairbrushes using gas chromatography–electroantennogram detection. Our results indicated that during the courtship period, flying males form courtship fields, lekking, and chase flying females before mating with them; E. signiferwere more successful in mating in larger spaces (Length × Width × Height = 9.6 × 7 × 4 m); 5 compounds in the hairbrushes of the male moths which elicited antennal responses of 2 sexes, despite at high concentrations. Combined with it, indicating that communication between male and female may rely on male sex pheromones. These findings can serve as a basis for studying the mechanisms of sex communication in E. signiferand developing sex pheromone-based trapping techniques.

The Standardized Plant Analysis Risk-Human Reliability Analysis (SPAR-H) method is a widely used method in human reliability analysis (HRA). Performance shaping factors (PSFs) refer to the factors that may influence human performance and are used to adjust nominal human error probabilities (HEPs) in SPAR-H. However, the PSFs are assumed to be independent, which is unrealistic and can lead to unreasonable estimation of HEPs. In this paper, a new method is proposed to handle the dependencies among PSFs in SPAR-H to obtain more reasonable results. Firstly, the dependencies among PSFs are analyzed by using decision-making trial and evaluation laboratory (DEMATEL) method. Then, PSFs are assigned different weights according to their dependent relationships. Finally, multipliers of PSFs are modified based on the relative weights of PSFs. A case study is illustrated that the proposed method is effective in handling the dependent PSFs in SPAR-H, where the duplicate calculations of the dependent part can be reduced. The proposed method can deal with a more general situation that PSFs are dependent, and can provide more reasonable results.

In this study, a new series of tetrahydrobenzothiophene derivatives have been designed. Newly designed molecules have been synthesized through a medicinal chemistry route, and their characterization was done by using NMR and HR-MS techniques. Biological evaluation of the synthesized compounds has been done on Gram-negative and Gram-positive bacteria. The marketed antibiotics such as ciprofloxacin and gentamicin were used as controls. The in vitroevaluation results have shown that most of the targeted compounds exhibit good potency in inhibiting the growth of bacteria, including E. coli(MIC: 0.64–19.92 μM), P. aeruginosa(MIC: 0.72–45.30 μM), Salmonella(MIC: 0.54–90.58 μM) and S. aureus(MIC: 1.11–99.92 μM). In particular, compound 3bshowed excellent activity with an MIC value of 1.11 μM against E. coli, 1.00 μM against P. aeruginosa, 0.54 μM against Salmonella, and 1.11 μM against S. aureus. From the results, a promising lead compound was identified for future development.

Since reliability and security of man-machine system increasingly depend on reliability of human, human reliability analysis (HRA) has attracted a lot of attention in many fields especially in nuclear engineering. Dependence assessment among human tasks is a important part in HRA which contributes to an appropriate evaluation result. Most of methods in HRA are based on experts’ opinions which are subjective and uncertain. Also, the dependence influencing factors are usually considered to be constant, which is unrealistic. In this paper, a new model based on Dempster–Shafer evidence theory (DSET) and fuzzy number is proposed to handle the dependence between two tasks in HRA under uncertain and dynamic situations. First, the dependence influencing factors are identified and the judgments on the factors are represented as basic belief assignments (BBAs). Second, the BBAs of the factors that varying with time are reconstructed based on the correction BBA derived from time value. Then, BBAs of all factors are combined to gain the fused BBA. Finally, conditional human error probability (CHEP) is derived based on the fused BBA. The proposed method can deal with uncertainties in the judgments and dynamics of the dependence influencing factors. A case study is illustrated to show the effectiveness and the flexibility of the proposed method.

Dempster-Shafer evidence theory is widely used in the field of information fusion especially when confronting with uncertainties. However, Dempster's rule of combination may lead to counter-intuitive results when dealing with highly conflicting bodies of evidence (BOEs). Numerous methods were proposed to address this problem. Enlightened by the research of interaction among nodes in complex networks, this paper study the combination of evidences from the perspective of networks: BOEs are regarded as nodes, the conflicting degree between BOEs is considered as one possible interaction between nodes. The direct and indirect interactions among nodes in networks are considered together to determine the weights of the BOEs. After process of weighted average, the modified BOEs can be efficiently combined by Dempster's rule of combination. A numerical example is illustrated to show the use and better performance of the proposed method. [ABSTRACT FROM AUTHOR]

The potential threat of domestic dogs to wildlife habitat in China is not widely recognized, despite their large population, lack of regulations regarding their control, and threat they pose to native species. In a case study in 2017, we surveyed villages surrounding Liziping Nature Reserve, the primary site for the release of captive‐born giant pandas (Ailuropoda melanoleuca) into the wild. We conducted surveys of dog owners to assess the population size, demographics, free‐roaming status, and vaccination and sterilization history of their dogs. We collected blood and fecal samples to assess the prevalence of viral and parasite disease threats. At least 370 owned dogs lived near the core giant panda habitat; 64% were free‐roaming, 21% had positive antibody titers for ≥1 of the 4 viruses we tested (canine distemper, parvovirus, rotavirus, rabies), and 67% were positive for gastrointestinal parasites. The high proportion of free‐roaming dogs, uninhibited access to the reserve, and high prevalence of infectious diseases indicate that dogs pose a serious threat to wildlife within Liziping. The extent of this threat throughout the giant panda nature reserve network is unknown and should be assessed. © 2019 The Authors. Journal of Wildlife Managementpublished by Wiley Periodicals, Inc. on behalf of The Wildlife Society. Numerous free‐ranging domestic dogs were located close to Liziping National Nature Reserve, a primary location of giant panda reintroductions and conservation. Viral and parasitic disease threats to giant pandas and other wildlife were present in the population, indicating a need for immediate management action.

Targeting β-catenin has been shown to have great potential therapeutic value in cervical cancer. Because β-catenin is also essential for normal cells, strategies to specifically target cancer will require identification of druggable factors capable of distinguishing β-catenin signaling pathways between cancer and normal cells.

A high degree of energy efficiency and real-time for data transmission is required in cyber-physical systems (CPSs). Data aggregation is an efficient technique to conserve energy by reducing the amount of transmission data. To optimize real-time communication under constraints of power consumption and data aggregation performance of each node in CPS, this paper presents a learning automata (LA)-based degree-bounded bottleneck data aggregation tree (DBBDAT) construction framework to minimize the maximum delay on data aggregation trees with bounded degree, which is an NP-hard problem. We model the network of CPS as a connected weighted and directed graph to form a network of LA. Degree-bounded data aggregation trees are constructed first by the action selection of each automaton. Then, the action vector of each automaton is updated by linear reward-inaction learning algorithm, and at last DBBDAT is constructed based on a threshold. Simulation results show that our approach significantly outperforms integer linear programming (ILP)-based method in terms of time complexity. Compared with ILP-based method, it can obtain an optimal solution or a suboptimal solution with guaranteed approximation ratios, and can control the tradeoff between accuracy and cost by choosing appropriate learning rate and threshold. Its distributed implementation is simple and it can efficiently solve the problem for the sparse graph in practice.

Invasive aspergillosis is a life-threatening infection in immunocompromised patients, and treating these infections at an early stage is often crucial for a favorable outcome. Early diagnosis, however, remains challenging. We performed a retrospective comparison of three methods: real-time quantitative PCR (qPCR), nucleic acid sequence-based amplification (NASBA), and galactomannan enzyme-linked immunosorbent assay (GM-ELISA); these detect circulating AspergillusDNA, RNA, and galactomannan, respectively. Blood samples from 80 patients at high risk for invasive aspergillosis were tested by each assay. The sensitivity of NASBA, qPCR, and GM-ELISA was 76.47% (95% CI, 58.4–88.6%), 67.65% (95% CI, 49.4–82.0%), and 52.94% (95% CI, 35.4–69.8%), respectively, and the specificity was 80.43% (95% CI, 65.6–90.1%), 89.13% (95% CI, 75.6–95.9%), and 80.43% (95% CI, 65.6–90.1%), respectively. We also evaluated the efficiency of the three tests in various combinations. Perfect specificity (100%; 95% CI, 90.4–100%) and perfect positive predictive value (100%; 95% CI, 77.1–100%) were achieved by combining NASBA and qPCR testing in series. Testing with both NASBA and qPCR in parallel was the most sensitive and had the highest Youden index. Our data support the great potential of NASBA and qPCR, singly or in combination, for diagnosis of invasive aspergillosis in high-risk populations.

ABSTRACTPrevious investigations demonstrated that saponins isolated from the root of Panax ginsengC. A. Meyer (i.e., ginseng root saponin [GS-R]) had adjuvant activity. In the present study, the combined effects of rapeseed oil (RO) and GS-R on the immune responses elicited by foot-and-mouth disease (FMD) vaccine were investigated by measuring FMD virus (FMDV)-specific antibody levels, cytokine levels, lymphocyte proliferation, and long-lived IgG-secreting plasma cells from bone marrow in a mouse model. The results indicated that RO in combination with GS-R significantly enhanced serum IgG and isotype concentrations, gamma interferon (IFN-?) and interleukin 5 (IL-5) levels, splenocyte proliferative responses to stimulations with concanavalin A (ConA), lipopolysaccharide (LPS), and FMDV antigen, and the numbers of IgG-secreting plasma cells in the bone marrow, suggesting that RO/GS-R enhanced both Th1 and Th2 immune responses. In addition, no significant difference was found between RO/GS-R and the commercial adjuvant oil ISA 206 in the promotion of FMD vaccine-induced immune responses. Considering the vegetable origin of RO and GS-R and the potent adjuvant activity, RO/GS-R should be studied further for the development of veterinary vaccines, especially for use in food animals in order to promote food safety.

AbstractThe rapid economic growth in China not only has improved people's living standard but changed their way of living as well. The adoption of the National Fitness Program (NFP) in 1995 transformed the government's focus from elite sport to grassroots sport activity. The program aims to improve the health and well-being of the people nationwide by implementing diverse Sports For All (SFA) strategies. Guangzhou is the third biggest city in China. Its economic prosperity, well-developed infrastructure, and residents' traditional enthusiasm for sport are all advantages to promote mass sport. Guangzhou SFA strategies include: 1) developing sport facilities; 2) providing diverse sport activities; 3) establishing a service delivering system; 4) evaluating citizens' physical fitness. The mission of the city is to become a leisure, sports and health center in China as well as a historic, culturally famed city. The future direction of the Guangzhou SFA is to create an integrated model of leisure, sports, and health to meet people's growing need for personal well-being and a higher quality of life.

Mature soybean phenotyping is an important process in soybean breeding; however, the manual process is time-consuming and labor-intensive. Therefore, a novel approach that is rapid, accurate and highly precise is required to obtain the phenotypic data of soybean stems, pods and seeds. In this research, we propose a mature soybean phenotype measurement algorithm called Soybean Phenotype Measure-instance Segmentation (SPM-IS). SPM-IS is based on a feature pyramid network, Principal Component Analysis (PCA) and instance segmentation. We also propose a new method that uses PCA to locate and measure the length and width of a target object via image instance segmentation. After 60,000 iterations, the maximum mean Average Precision (mAP) of the mask and box was able to reach 95.7%. The correlation coefficients R2of the manual measurement and SPM-IS measurement of the pod length, pod width, stem length, complete main stem length, seed length and seed width were 0.9755, 0.9872, 0.9692, 0.9803, 0.9656, and 0.9716, respectively. The correlation coefficients R2of the manual counting and SPM-IS counting of pods, stems and seeds were 0.9733, 0.9872, and 0.9851, respectively. The above results show that SPM-IS is a robust measurement and counting algorithm that can reduce labor intensity, improve efficiency and speed up the soybean breeding process.