In this paper, we present a comprehensive study of gestation length (GL) in 16 cattle breeds by using large genotype and animal record databases. Data included over 20 million gestations since 2000 ...and genotypes from one million calves. The study addressed the GL variability within and between breeds, estimation of its direct and maternal heritability coefficients, association with fitness and several economic traits, and QTL detection. The breed average GL varied from 279.7 to 294.4 d, in Holstein and Blonde d'Aquitaine breeds, respectively. Standard deviations per breed were similar and ranged from 5.2 to 5.8 d. Direct heritability (i.e., for GL defined as a trait of the calf) was moderate to high (h2 = 0.40 to 0.67), whereas the maternal heritability was low (0.04 to 0.06). Extreme breeding values for GL were strongly associated with a higher mortality during the first 2 d of life and were associated with milk production of dams for dairy breeds and precocity of females. Finally, several QTL were detected affecting GL with cumulated effects up to a few days, and at least 2 QTL were found to be shared between different breeds. Our study highlights the risks that would be associated with selection toward a reduced gestation length. Further genomic studies are needed to identify the causal variants, and their association with juvenile mortality and other economic traits.
The ΛCDM expansion can be mimicked by dark energy coupled to matter. In this case, the equation of state
$\bar{w}$
and coupling
$\bar{Q}$
of this coupled dark energy cannot be constrained by ...observations of the Hubble function alone. In this article, we determine the constraints on two such coupled dark energy models, considering some current and forecast Euclid-like growth-rate data and assuming the prior on the ΛCDM dark matter density parameter today, Ωm0 = 0.295 ± 0.04. The first model is defined by a constant equation of state. We find that, at 2σ,
$\bar{w}=-1.02_{-0.22}^{+0.06}$
and the coupling function
$\bar{Q}_0$
today is
$\bar{Q}_0H_0^{-3}=0.057_{-0.148}^{+0.353}$
, with H
0 the Hubble constant. The second model is defined by a varying equation of state
$\bar{w}=\bar{w}_{\rm a}-\bar{w}_{\rm b}\ln (1+z)$
, with z the redshift and
$(\bar{w}_{\rm a},\bar{w}_{\rm b})$
two constants. We find that, at 2σ,
$\bar{w}_{\rm a}=-0.99_{-0.90}^{+0.17}$
,
$\bar{w}_{\rm b}=-0.04_{-1.17}^{+0.31}$
and
$\bar{Q}_0H_0^{-3}=0.0002_{-0.18}^{+1.35}$
. These constraints on coupled dark energy agree with a ΛCDM model but are too poor to discard with confidence coupled dark energy different from a vacuum but mimicking a ΛCDM expansion.
In order to improve the dynamics of the surface-mounted permanent magnet synchronous motors (SPMSM) used in servo systems, finite control set model predictive current control (FCS-MPCC) methods have ...been widely adopted. However, because the FCS-MPCC is a model-based strategy, its performance highly depends on the machine parameters, such as the winding resistance, inductance and flux linkage. Unfortunately, the parameter mismatch problem is common due to the measurement precision and environmental impacts (e.g., temperature). To enhance the robustness of the SPMSM FCS-MPCC systems, this paper proposes a Lundberg perturbation observer that is seldom used in the FCS model predictive control situations to remove the adverse effects caused by resistance and inductance mismatch. Firstly, the system model is established, and the FCS-MPCC mechanism is illustrated. Based on the machine model, the sensitivity of the control algorithm to the parameter mismatch is discussed. Then, the Luenberger perturbation observer that can estimate the general disturbance arising from the parameter uncertainties is developed, and the stability of the observer is analyzed by using the discrete pole assignment technique. Finally, the proposed disturbance observer is incorporated into the FCS-MPCC prediction plant model for real-time compensation. Both simulation and experiments are conducted on a three-phase SPMSM, verifying that the proposed strategy has marked control performance and strong robustness.
Three‐dimensional solubility parameters (HSP) of the acrylonitrile‐butadiene rubber (NBR) were determined by combining a software program with equilibrium swelling test. Then, a modified ...Flory‐Huggins interaction parameter (χHSP) was calculated and compared with the traditional one (χ) in characterizing the swelling behavior of NBR. NBR exhibits quite different swelling responses in the selected seven kinds of organic solvents, which can be differentiated by the energy difference (Ra) and be further correlated with χHSP value between rubber and solvent. The results turn out that the swelling ratio (q) decreases with increasing χHSP value. By mathematical fitting, an exponential relationship between q and χHSP is achieved to predict the swelling behaviors of NBR in the increasing used bio‐fuels, bio‐diesel, and IRM903 being selected for examples. From the prediction model, we can get that there is a high swelling area for bio‐diesel/ethanol system and both a high and low swelling areas for IRM903/ethanol system. Hereby, it is expected that the swelling behavior or oil resistance of NBR based rubber parts can be predicted quantitatively in a concise way now.
We present the determination of stellar parameters and individual elemental abundances for 6 million stars from ∼8 million low-resolution (R ∼ 1800) spectra from LAMOST DR5. This is based on a ...modeling approach that we dub the data-driven Payne (DD-Payne), which inherits essential ingredients from both the Payne and the Cannon. It is a data-driven model that incorporates constraints from theoretical spectral models to ensure the derived abundance estimates are physically sensible. Stars in LAMOST DR5 that are in common with either GALAH DR2 or APOGEE DR14 are used to train a model that delivers stellar parameters (Teff, log g, Vmic) and abundances for 16 elements (C, N, O, Na, Mg, Al, Si, Ca, Ti, Cr, Mn, Fe, Co, Ni, Cu, and Ba) over a metallicity range of −4 dex < Fe/H < 0.6 dex when applied to the LAMOST spectra. Cross-validation and repeat observations suggest that, for S/Npixel ≥ 50, the typical internal abundance precision is 0.03-0.1 dex for the majority of these elements, with 0.2-0.3 dex for Cu and Ba, and the internal precision of Teff and log g is better than 30 K and 0.07 dex, respectively. Abundance systematics at the ∼0.1 dex level are present in these estimates but are inherited from the high-resolution surveys' training labels. For some elements, GALAH provides more robust training labels, for others, APOGEE. We provide flags to guide the quality of the label determination and identify binary/multiple stars in LAMOST DR5. An electronic version of the abundance catalog is made publicly available.12
•An efficient scheme for reliability-based design optimization by integrating the probability density evolution method and the variance-based sensitivity analysis.•Reliability assessment of the IMB ...base-isolated structure under earthquake ground motions by means of the probability density evolution method.•Application of variance-based sensitivity analysis to identify the critical parameters of the base isolation system for facilitating the design optimization.•Reliability-based design optimization of the base isolation system for enhanced adaptive seismic mitigation of the base-isolated structure.
The reliability-based design optimization (RBDO) of base-isolated structures by means of the state-of-the-art methods has been confronted with the high computational cost because the base isolation system often exhibits intrinsic nonlinearities and has to be modelled using a number of parameters in practice. In this regard, the present study aims at developing an efficient scheme for the RBDO of base isolation systems by integrating the probability density evolution method (for global reliability solution) and the variance-based sensitivity analysis (for design parameter reduction).To attain an adaptive seismic mitigation, the newly developed sliding implant-magnetic bearings are employed for constituting the base isolation system. It is shown that although the deployment of sliding implant-magnetic bearings allows a safer structure, the base isolation system still suffers from an unexpected failure probability of deflection under the rarely-occurring earthquake. As a result, the design optimization for strengthening the reliability of the base isolation system needs to be carried out. For identification of the critical design parameters to be optimized, the variance-based sensitivity analysis is performed, showing that the parameters of the exponential function that represents the Coulomb sliding friction associated with the sliding implant-magnetic bearing are mostly of concern. Furthermore, the RBDO of the base isolation system is carried out by employing the genetic algorithm. It is revealed that the global reliability of the base-isolated structure after optimization gains a significant improvement compared to that before optimization.
The massive growth of mobile users will spread to significant numbers of small cells for the Fifth Generation (5G) mobile network, which will overlap the fourth generation (4G) network. A tremendous ...increase in handover (HO) scenarios and HO rates will occur. Ensuring stable and reliable connection through the mobility of user equipment (UE) will become a major problem in future mobile networks. This problem will be magnified with the use of suboptimal handover control parameter (HCP) settings, which can be configured manually or automatically. Therefore, the aim of this study is to investigate the impact of different HCP settings on the performance of 5G network. Several system scenarios are proposed and investigated based on different HCP settings and mobile speed scenarios. The different mobile speeds are expected to demonstrate the influence of many proposed system scenarios on 5G network execution. We conducted simulations utilizing MATLAB software and its related tools. Evaluation comparisons were performed in terms of handover probability (HOP), ping-pong handover probability (PPHP) and outage probability (OP). The 5G network framework has been employed to evaluate the proposed system scenarios used. The simulation results reveal that there is a trade-off in the results obtained from various systems. The use of lower HCP settings provides noticeable enhancements compared to higher HCP settings in terms of OP. Simultaneously, the use of lower HCP settings provides noticeable drawbacks compared to higher HCP settings in terms of high PPHP for all scenarios of mobile speed. The simulation results show that medium HCP settings may be the acceptable solution if one of these systems is applied. This study emphasises the application of automatic self-optimisation (ASO) functions as the best solution that considers user experience.
Optimal methods for incorporating soil microbial mechanisms of carbon (C) cycling into Earth system models (ESMs) are still under debate. Specifically, whether soil microbial physiology parameters ...and residual materials are important to soil organic C (SOC) content is still unclear. Here, we explored the effects of biotic and abiotic factors on SOC content based on a survey of soils from 16 locations along a ~4000 km forest transect in eastern China, spanning a wide range of climate, soil conditions, and microbial communities. We found that SOC was highly correlated with soil microbial biomass C (MBC) and amino sugar (AS) concentration, an index of microbial necromass. Microbial C use efficiency (CUE) was significantly related to the variations in SOC along this national‐scale transect. Furthermore, the effect of climatic and edaphic factors on SOC was mainly via their regulation on microbial physiological properties (CUE and MBC). We also found that regression models on explanation of SOC variations with microbial physiological parameters and AS performed better than the models without them. Our results provide the empirical linkages among climate, microbial characteristics, and SOC content at large scale and confirm the necessity of incorporating microbial biomass and necromass pools in ESMs under global change scenarios.
We investigated the roles of microorganisms in regulating soil organic carbon (SOC) storage along a national‐scale forest transect. We found that the statistical models considering microbial carbon use efficiency and microbial necromass in predicting SOC performed better than the models that only include climatic and soil variables.
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