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Summary: Legume crops contribute a great portion of clean nitrogen (N) to agro‐ecosystems through symbiotic N2 fixation in the nodule; however, the nodulation is always inhibited by high N availability which is known as the N inhibitory effect through largely unknown mechanisms.We functionally investigated miR169c‐GmNFYA‐C‐GmENOD40 under multiple N conditions in soybean (Glycine max) (ENOD, Early Nodulin; NFYA, Nuclear Factor‐Y Subunit A). We elucidated their regulatory roles in soybean nodulation through analyzing expression patterns, micro–messenger RNA (miRNA–mRNA) interactions, phenotypes of transgenic soybean plants and genetic interactions.We found that miR169c expression was induced by high N, whereas its target GmNFYA‐C was preferentially expressed in nodules and induced by rhizobium inoculation. Overexpression of miR169c inhibited nodulation through targeting 3′‐UTR of GmNFYA‐C, whereas knockout miR169c through CRISPR‐cas9 promoted nodulation. However, overexpression of GmNFYA‐C promoted soybean nodulation through facilitating rhizobium infection and increasing the expression of symbiotic signaling gene GmENOD40. Besides, GmNFYA‐C directly induced the expression of GmENOD40. In addition, overexpression of GmNFYA‐C without the target site of miR169c partially attenuated the inhibitory effect of high N on soybean nodulation.We discovered a new regulatory pathway involving the miR169c‐NFYA‐C‐ENOD40 module that regulates soybean nodulation in response to N availability. This pathway provides substantial new insights into the mechanisms underlying the N inhibitory effect on nodulation. [ABSTRACT FROM AUTHOR]

In order to achieve the effect of pressure sensitization of optical fiber sensor, a photonic crystal fiber structure with high birefringence was designed. The effective refractive index of photonic crystal fiber was calculated by the finite element method when it was applied different stress. Based on the pressure-sensitive characteristics of photonic crystal fiber, the mode of photonic crystal fiber was analyzed. An air hole in the structure was selected and filled with the liquid of specific refractive index. A new pressure sensor was formed by above structures. The pressure sensitivity of the structure was simulated by COMSOL. The simulation results show that the polarization phase sensitivity of photonic crystal fiber sensor increases from 72rad/( MPa ⋅ m) to 128rad/( MPa ⋅ m). The sensitivity is improved by 77. 7% significantly, which contributes to enhance the properties of the sensor. [ABSTRACT FROM AUTHOR]

A design of large-mode area photonic crystal fiber (LMA-PCF) was proposed to improve the non-linear effect of high-power fiber laser, which has the properties as large effective mode area, single mode, passive component, and low loss. The perfect matched layer was set as the boundary condition, and the effect of wavelength and structure on the effective mode area of PCF were analyzed by the finite difference time domain method. Further, a program of LMA-PCF was proposed. The results indicate that the transmission of single mode is obtained. At the wavelength of 1. 064 µm, the effective mode area is able to reach 3118. 4µm², and the non-linear coefficient is only 5. 68 x 10 5m-1 ⋅ W 1 Besides, the confinement loss can be reduced to 4.55 x 10-7 dB ⋅ m 1 Therefore, the high-power and high-beam of laser output is realized. [ABSTRACT FROM AUTHOR]

Background: Unlike β1- and β2-adrenergic receptors (ARs), β3-AR stimulation inhibits cardiac contractility and relaxation. In the failing left ventricular (LV) myocardium, β3-ARs are upregulated, and can be maladaptive in the setting of decompensation by contributing to LV dysfunction. This study examined the effects of intravenous infusions of the β3-AR antagonist APD418 on cardiovascular function and safety in dogs with systolic heart failure (HF).Methods and Results: Three separate studies were performed in 21 dogs with coronary microembolization-induced HF (LV ejection fraction [LVEF] of approximately 35%). Studies 1 and 2 (n = 7 dogs each) were APD418 dose escalation studies (dosing range, 0.35-15.00 mg/kg/h) designed to identify an effective dose of APD418 to be used in study 3. Study 3, the sustained efficacy study, (n = 7 dogs) was a 6-hour constant intravenous infusion of APD418 at a dose of 4.224 mg/kg (0.70 mg/kg/h) measuring key hemodynamic endpoints (e.g., EF, cardiac output, the time velocity integral of the mitral inflow velocity waveform representing early filling to time-velocity integral representing left atrial contraction [Ei/Ai]). Studies 1 and 2 showed a dose-dependent increase of LVEF and Ei/Ai, the latter being an index of LV diastolic function. In study 3, infusion of APD418 over 6 hours increased LVEF from 31 ± 1% to 38 ± 1% (P < .05) and increased Ei/Ai from 3.4 ± 0.4 to 4.9 ± 0.5 (P < .05). Vehicle had no effect on the LVEF or Ei/Ai. In study 3, APD418 had no significant effects on the HR or the systemic blood pressure.Conclusions: Intravenous infusions of APD418 in dogs with systolic HF elicit significant positive inotropic and lusitropic effects. These findings support the development of APD418 for the in-hospital treatment of patients with an acute exacerbation of chronic HF. [ABSTRACT FROM AUTHOR]

Global Navigation Satellite Systems (GNSS) have been proved to be an excellent technology for retrieving precipitable water vapor (PWV). In GNSS meteorology, PWV at a station is obtained from a conversion of the zenith wet delay (ZWD) of GNSS signals received at the station using a conversion factor which is a function of weighted mean temperature (Tm) along the vertical direction in the atmosphere over the site. Thus, the accuracy of Tm directly affects the quality of the GNSS-derived PWV. Currently, the Tm value at a target height level is commonly modelled using the Tm value at a specific height and a simple linear decay function, whilst the vertical nonlinear variation in Tm is neglected. This may result in large errors in the Tm result for the target height level, as the variation trend in the vertical direction of Tm may not be linear. In this research, a new global grid-based Tm empirical model with a horizontal resolution of 1°×1°, named GGNTm, was constructed using ECMWF ERA5 monthly mean reanalysis data over the 10-year period from 2008 to 2017. A three-order polynomial function was utilized to fit the vertical nonlinear variation in Tm at the grid points, and the temporal variation in each of the four coefficients in the Tm fitting function was also modelled with the variables of the mean, annual and semi-annual amplitudes of the 10-year time series coefficients. The performance of the new model was evaluated using its predicted Tm values in 2018 to compare with the following two references in the same year 1) Tm from ERA5 hourly reanalysis with the horizontal resolution of 5°×5°; 2) Tm from atmospheric profiles from 428 globally distributed radiosonde stations. Compared to the first reference, the mean RMSEs of the model predicted Tm values over all global grid points at the 950 hPa and 500 hPa pressure levels were 3.35 K and 3.94 K respectively. Compared to the second reference, the mean bias and mean RMSE of the model predicted Tm values over the 428 radiosonde stations at the surface level were 0.34 K and 3.89 K respectively; the mean bias and mean RMSE of the model's Tm values at all pressure levels in the height range from the surface to 10 km altitude were -0.16 K and 4.20 K respectively. The new model results were also compared with that of the GPT3, GTrop and GWMT_D models in which different height correction methods were also applied. Results indicated that significant improvements made by the new model were at high-altitude pressure levels; in all five height ranges, GGNTm results were generally unbiased, and their accuracy varied little with height. The impact of Tm on GNSS-PWV was evaluated in terms of relative error, and significant improvement was found compared to the widely used GPT3 model. These results suggest that considering the vertical nonlinear variation in Tm and the temporal variation in the coefficients of the Tm model can significantly improve the accuracy of model-predicted Tm for a GNSS receiver that is located in anywhere below the tropopause (assumed to be 10 km), which has significance for applications needing real-time or near real-time PWV converted from GNSS signals. [ABSTRACT FROM AUTHOR]

In order to break the limitation of high Young' s modulus of quartz material on the sensitivity improvement of fiber optic sensor in uniform radial direction, a doped double-core photonic crystal fiber sensing structure was proposed. The circular air holes were arranged on the fiber cladding to form hexagonal lattice. Polymethyl methacrylate was doped into the base-material area surrounded by the air holes on one side of the double-core photonic crystal fiber. The influence of cross-section parameters on sound pressure sensitivity under uniform stress was analyzed by COMSOL and the optimal structure was obtained. At the kPa level, the free spectral width is about 13nm. At the MPa level, the free spectral width is about 2.5465nm. The results show that the sensitivity of x polarized sound pressure is 0.15942nm/kPa at 1550µm. Compared with the Sagnac PCF pressure sensor, the size of this sensor is smaller, and the sensitivity at uniform radial direction is increased about 46. 6 times. This work contributes to the design of the next generation underwater sound pressure sensor. [ABSTRACT FROM AUTHOR]

Coal separation based on computer vision has attracted substantial attention in recent years. However, developing reliable object detection models relies on large-scale annotated dataset, which in industrial practice is time-consuming and labor-intensive to obtain. In this paper, we propose a novel data augmentation model called dual attention deep convolutional generative adversarial network (DADCGAN) to expand dataset scale and improve object detection. For the first time, the proposed DADCGAN, which adopts DCGAN as its foundation architecture, introduces efficient channel attention and external attention mechanisms to capture essential feature information from the channel and spatial dimensions of images, respectively. Moreover, spectral normalization and two time-scale update rule strategies are incorporated to stabilize the training process. The implementation of our proposed data augmentation strategy includes two steps. First, traditional pixel transformation is used to expand an original small dataset. Then, our GAN-based data augmentation is executed to further expand the dataset by generating synthetic images. Experimental results show that our DADCGAN model achieves the lowest FID value, decreasing the FID by 21.30–71.96 % compared to other baseline GAN models, showcasing its ability to produce more realistic coal-gangue images. Finally, the data augmentation strategies are applied to the YOLOv4 model, enhancing the mAP by 9.26 %, highlighting its significance in enhancing coal-gangue object detection. These results have important implications for the development and implementation of computer vision-based technologies, enabling the realization of cleaner and more efficient coal separation methods. • Propose GAN-based data augmentation to generate synthetic coal-gangue images. • Apply efficient channel and external attention to capture key features of images. • Use spectrum normalization and imbalanced learning rate to stabilize GAN training. • Produce more realistic images using DADCGAN with lower FID than regular GAN models. • Improve coal-gangue detection accuracy with our data augmentation strategies. [ABSTRACT FROM AUTHOR]

Deoxynivalenol (DON) is the most common mycotoxin in food and feed, which can cause undesirable effects, including diarrhea, emesis, weight loss, and growth delay in livestock. Intestinal epithelial cells were the main target of DON, which can cause oxidative stress and inflammatory injury. Tanshinone IIA (Tan IIA) is fat-soluble diterpene quinone, which is the most abundant active ingredient in salvia miltiorrhiza plant with antioxidant and anti-inflammatory characteristics. However, it is not clear whether Tan IIA can protect against or inhibit intestinal oxidative stress and inflammatory injury under DON exposure. This study aimed to explore the protective effect of Tan IIA on DON-induced toxicity in porcine jejunum epithelial cells (IPEC-J2). Cells were exposed to 0, 0.5, 1.0, 2.0 µM DON and/or 45 µg/mL TAN ⅡA to detect oxidative stress indicators. inflammatory cytokines, NF-κB expression, NLRP3 inflammasome and pyroptosis-related factors. In this study, DON exposure caused IPEC-J2 cells oxidative stress by elevating ROS and 8-OHdG content, inhibited GSH-Px activity. Furthermore, DON increased pro-inflammatory factor (TNF-α, IL-1β, IL-18 and IL-6) expression and decreased the anti-inflammatory factor (IL-10) expression, causing inflammatory response via triggering NF-κB pathway. Interestingly, above changes were alleviated after Tan IIA treatment. In addition, Tan IIA relieved DON-induced pyroptosis by suppressing the expression of pyroptosis-related factors (NLRP3, Caspase-1, GSDMD, IL-1β, and IL-18). In general, our data suggested that Tan IIA can ameliorate DON-induced intestinal epithelial cells injury associated with suppressing the pyroptosis signaling pathway. Our findings pointed that Tan IIA could be used as the potential therapeutic drugs on DON-induced enterotoxicity. • DON exposure caused ROS accumulation and oxidative stress in IPEC-J2 cells. • DON exposure induced IPEC-J2 cells inflammation via NF-κB pathway. • Tan IIA mitigated DON-induced NLRP3 inflammasome-mediated pyroptosis in IPEC-J2 cell. [ABSTRACT FROM AUTHOR]

The ionosphere has been considered as one of the major error sources in GNSS signal propagation, and it is still difficult to be modeled precisely, especially for real-time positioning applications. The commonly used ionospheric models are usually based on the one-layer approximation, which neglects the ionospheric variation in the vertical domain and limits the scope of improvement over one-layer models. A new ionospheric model based on the two-layer approximation and two spherical harmonic (SH) functions is proposed in this contribution, where a quasi-globe projection is designed to avoid the inherent ill-posed problem and retain the physical meaning of the SH when regional data are used. GPS and BDS data from the National Positioning Infrastructure of Australia and Crustal Movement Observation Network of China are used for validating the new model's performance in different areas and different periods. Results show (1) the precision of ionospheric TEC estimates from the new model can be improved by about 26% and 31% in the cross-validation experiment compared to the traditional one-layer model in Australian and Chinese regions, respectively; (2) the positioning accuracy of kinematic single-frequency precise point positioning (SF-PPP) in the experimental regions using the new model reaches about 0.7 m and 0.8 m in the horizontal and vertical components, respectively, in comparison with the one-layer model's 1.0 m (horizontal) and 1.4 m (vertical); (3) the convergence time of the SF-PPP using the new model is 5–10 min for achieving a sub-meter level of positioning accuracy in both horizontal and vertical components, whereas it needs 30–40 min in case the one-layer model is used. [ABSTRACT FROM AUTHOR]

Vertical total electron content (VTEC) global ionospheric maps (GIM) are commonly used to correct the ionospheric delay of global navigation satellite system (GNSS) signals for single-frequency positioning and other ionospheric studies. The measurements observed by inhomogeneously distributed ground reference stations are the only data used to generate the GIMs. Thus the accuracy of the GIMs over ocean and polar regions is relatively poor due to the lack of measurements over these regions. In this study, space-borne VTECs obtained from ocean-altimetry and GNSS radio occultation measurements are incorporated into the modelling process. Since the three types of VTEC data have different qualities, the weight for each type of data is determined using the Helmert-variance component estimation (Helmert-VCE) method. In addition, unlike the traditional weighted least squares (WLS) estimation method in which the design matrix of observation equations is fixed, in this study, the design matrix, especially those elements in design matrix that are derived from the coordinates of either tangent point or ionospheric pierce point, are considered to be inaccurate. Thus they are adjusted together with the unknown coefficient parameters of the fitting model using the fast-weighted total least squares (fast-WTLS) technique. The proposed approach, named Helmert-WTLS, was tested using the data in the period of day of year (DOY) 217–224, 2016 and validated using GIMs produced by the research team for ionosphere and precise positioning based on BDS/GNSS (GIPP) at the Academy of Opto-Electronics, Chinese Academy of Sciences (CAS). Comparison results showed that the GIMs (with a 2 h temporal resolution) generated using the new approach can improve the determination of ionospheric TEC by 0.28 TEC units (TECU) over those from the Helmert-VCE-aided WLS approach (w.r.t CAS references, respectively) and by 1.61 TECU better than those from WLS, in terms of the mean of all root-mean-squares errors of all 2 h time slots in the 8-day testing period. In addition, in comparison with out-of-sample Jason-3 observations, results from the proposed method also outperformed Helmert-VCE-aided WLS, CAS and CODE models by 1.5, 2.4 and 2.4 TECU, respectively. [ABSTRACT FROM AUTHOR]

Abstract With the rapid increase in the numbers of new generation Global Navigation Satellite Systems (GNSS) satellites, signal frequencies and ground tracking stations, the burden on data processing increases significantly, especially for those real-time or near real-time applications, e.g. generating ultra-rapid satellite orbit and Earth rotation parameters (ERP) products. In order to reduce the number of observations used to estimate the orbit and ERP unknown parameters for better computational efficiency, this study first introduced a parameter called orbit and ERP dilution of precision (OEDOP) factor and a method in "optimally" selecting multi-GNSS tracking stations based on the OEDOP factor is investigated to minimize the data processing burden without significantly sacrificing the accuracy and precision of the satellite orbit and ERP determination. The trade-off between computational efficiency and quality of results is primary focus of this research. The contribution of each tracking station to the precision of the parameter estimates is investigated first, according to the location and multi-GNSS data measurement capacity of the station as well as the length of observations, then those stations that contribute least will be identified and excluded in the estimation system. It aims to use as a fewer number of tracking stations as possible but the degradation in the precision of the solution is still under a desired level. The method was tested using GNSS observations from 409 International GNSS service (IGS) stations over a one-month period. Results showed that when the "degradation" factor of the precision of satellite orbit and ERPs solutions is 5%, 10%, 15% and 20% the accuracy of the satellites orbit and polar motion parameters estimated from an optimal minimum number of stations (in comparison with the results from all stations) reduced about 0.33–9.92 cm and 5.77–41.53 μas respectively, and the accuracy of UT1–UTC reduced 10.63–15.50 μs; while their computational speed was improved by 196%, 332%, 527% and 617% respectively. This suggests that our method is a good trade-off method and an ideal option in cases that rapid solutions are required, e.g. ultra-rapid determination of orbit and ERP using multi-GNSS measurements from global ground tracking stations. [ABSTRACT FROM AUTHOR]