Improvement,identification, and target prediction for miRNAs in the porcine genome by using massive,public high-throughput sequencing data

Despite the broad variety of available microRNA (miRNA) research tools and methods, their application to the identification, annotation, and target prediction of miRNAs in nonmodel organisms is still limited. In this study, we collected nearly all public sRNA-seq data to improve the annotation for known miRNAs and identify novel miRNAs that have not been annotated in pigs (Sus scrofa). We newly annotated 210 mature sequences in known miRNAs and found that 43 of the known miRNA precursors were problematic due to redundant/missing annotations or incorrect sequences. We also predicted 811 novel miRNAs with high confidence, which was twice the current number of known miRNAs for pigs in miRBase. In addition, we proposed a correlation-based strategy to predict target genes for miRNAs by using a large amount of sRNA-seq and RNA-seq data. We found that the correlation-based strategy provided additional evidence of expression compared with traditional target prediction methods. The correlation-based strategy also identified the regulatory pairs that were controlled by nonbinding sites with a particular pattern, which provided abundant complementarity for studying the mechanism of miRNAs that regulate gene expression. In summary, our study improved the annotation of known miRNAs, identified a large number of novel miRNAs, and predicted target genes for all pig miRNAs by using massive public data. This large data-based strategy is also applicable for other nonmodel organisms with incomplete annotation information.     

Estimation of irrigation requirements for drip-irrigated maize in a sub-humid climate

Drip-irrigation is increasingly applied in maize (Zea mays L.) production in sub-humid region. It is critical to quantify irrigation requirements during different growth stages under diverse climatic conditions. In this study, the Hybrid-Maize model was calibrated and applied in a sub-humid Heilongjiang Province in Northeast China to estimate irrigation requirements for drip-irrigated maize during different crop physiological development stages and under diverse agro-climatic conditions. Using dimensionless scales, the whole growing season of maize was divided into diverse development stages from planting to maturity. Drip-irrigation dates and irrigation amounts in each irrigation event were simulated and summarized in 30-year simulation from 1981 to 2010. The maize harvest area of Heilongjiang Province was divided into 10 agro-climatic zones based on growing degree days, arid index, and temperature seasonality. The simulated results indicated that seasonal irrigation requirements and water stress during different growth stages were highly related to initial soil water content and distribution of seasonal precipitation. In the experimental site, the average irrigation amounts and times ranged from 48 to 150 mm with initial soil water content decreasing from 100 to 20% of the maximum soil available water. Additionally, the earliest drip-irrigation event might occur during 3- to 8-leaf stage. The water stress could occur at any growth stages of maize, even in wet years with abundant total seasonal rainfall but poor distribution. And over 50% of grain yield loss could be caused by extended water stress during the kernel setting window and grain filling period. It is estimated that more than 94% of the maize harvested area in Heilongjiang Province needs to be irrigated although the yield increase varied (0 to 109%) in diverse agro-climatic zones. Consequently, at least 14% of more maize production could be achieved through drip-irrigation systems in Heilongjiang Province compared to rainfed conditions.     

水流作用下一种养殖金属网衣水阻力特性的数值模拟研究

为保障深远海金属网箱养殖系统的结构安全,进行网箱结构的水动力学研究是一项重要的工作。构成金属网箱主要组成部分的金属网衣是一种小直径多孔的网状结构,在波浪和水流作用下的水动力学特性与一般的海洋工程结构物有显著不同。本文基于有限元基本原理,采用梁单元模拟金属网线结构,采用连接单元模拟网线接触部位的相互作用,并运用ABAQUS软件进行数值计算,在试验验证的基础上,分析了在水流作用下一种金属菱形链网衣在不同网目尺寸、不同网线直径情况下的水阻力变化情况。数值模拟结果表明在各种工况下,当网目尺寸由25 mm增加到35 mm、45 mm时,网衣受力增加幅度的平均值分别为14.71%和38.07%;当网线直径由2.5 mm增加到3.2 mm、4.0 mm时,各工况下网衣受力增加幅度的平均值分别为25.05%和45.06%。研究结果可以为进一步开展深海养殖金属网箱水动力特性研究提供积极的基础。     

粉碎机异形筛片气流场数值模拟及试验研究

针对传统环筛式锤片饲料粉碎机存在气固环流层影响粉碎机性能的问题,采用理论分析、数值模拟、粉碎性能试验相结合的方法,对粉碎机安装异形筛片时粉碎室内物料颗粒受到的气力作用和内部流场运动规律进行研究。分析粉碎机使用异形筛片对粉碎性能的影响。优化后的异形筛片分别命名为B_1(小圆弧半径R_1=51mm)、B_2(R_1=83mm)、B_3(R_1=93mm),利用流体动力学软件对粉碎室安装3种异形筛片的气流场进行数值模拟,获得粉碎室气流场分布信息。在相同工况下,对装有3种异形筛片的CPS-420型粉碎机进行粉碎性能试验,分析不同筛片对物料粉碎效果的影响。模拟结果表明:粉碎机采用间隔分段圆弧筛片后,粉碎室环流区域产生不同强度的涡旋,能够改变物料环流运动规律,提高物料过筛能力;锤片组扫过区域的气流呈现出较为杂乱无序的分布状态,有利于形成湍流运动,从而增加物料颗粒受打击几率。粉碎性能试验结果表明:锤片饲料粉碎机安装B_3筛片的粉碎机生产效率,较B2、B1筛片分别提高8.1%、16.0%,吨料耗电量分别降低10.5%、15.0%,温升分别降低0.6和0.1℃。优化后的3种异形筛片,能够提高粉碎机的生产效率,降低电能的损耗、改善物料温升,对提高锤片饲料粉碎机性能具有积极意义。     

基于灰色-BP神经网络模型的多情景交通用地需求预测——以长江中游城市群为例

为探索科学预测区域交通用地需求的合理途径,指导国土空间规划编制中交通用地规模的划定,拟通过灰色-BP神经网络模型识别主要社会经济影响因素,以长江中游城市群为例,在预测其远景交通用地需求规模的同时,基于城市群发展的阶段特征选取典型城市群样本设置3类情景,对不同情景下的交通用地需求分别进行预测。结果表明:1)城镇化水平、产业结构高度化程度和劳动力资源禀赋是当前影响长江中游城市群交通用地需求的主要社会经济因素。2)通过系统仿真试验对比不同方法的交通用地需求预测结果,可以发现基于灰色-BP神经网络模型的预测方法精度较高,误差较小,该预测方法对于区域交通用地规模的预测具有一定的适用性。预测得到的长江中游城市群2020和2030年交通用地需求分别为31.22万和49.07万hm2。3)不同情景下长江中游城市群交通用地需求预测结果存在明显差异,底线情景可作为划定交通用地规模的底限,一般情景可作为基准,极限情景可作为红线,长江中游城市群交通用地合理规模应以基准为参考,介于底线和红线之间。     

Numerical study on wave attenuation inside and around a square array of biofouled net cages

In this study, waves propagating through a square array of 16 net cages with different levels of biofouling are numerically studied using a three-dimensional computational fluid dynamics (CFD) model. A porous-media fluid model is adopted to simulate both clean and biofouled netting of a cage array in waves. A numerical wave tank is built, and the oscillating-boundary method is adopted to generate waves. The flow motion is solved by the Navier-Stokes equations, and the free water surface is captured using the volume of fluid (VOF) method. The numerical model is validated by comparing the numerical data with corresponding experimental measurements of a net-cage model with clean netting. To analyze wave attenuation, a numerical analysis of wave elevation both inside and around the cage arrays is presented, which considers the effect of biofouling. Based on the results of the present study, the effect of biofouling on wave elevation is noticeable; the damping effect of the cage array increases with increasing level of biofouling. Furthermore, the incident angle of waves has a noticeable effect on the wave field inside and around the cage array.     

Is it possible to differentiate between environmental and fishery effects on abundance‐biomass variation? A case study of blackspot seabream (Pagellus bogaraveo) in the Strait of Gibraltar

We assessed the potential for simulation and modelling of the blackspot seabream (Pagellus bogaraveo) population in the Strait of Gibraltar to discriminate the environmental effects of fishery impacts. A discrete biomass–abundance dynamic model was implemented to obtain a simulated monthly time series of blackspot seabream biomass. On this simulated time series, autoregressive integrated moving average (ARIMA) models were fitted. The best ARIMA fit provided a significant correlation of 0.76 and persistence index higher than 0.85. The proportion of variance non‐explained by the ARIMA models was correlated with a time series of sea surface temperature (SST) and North Atlantic Oscillation (NAO). The analysis of global, annual and winter correlation between the proportion of variance not explained by the ARIMA models and environmental variables showed that significant associations were not detected over the full time series. Our analysis therefore suggests that overexploitation is the main factor responsible for the commercial depletion of blackspot seabream in the Strait of Gibraltar.     

Hybrid breeding for biomass yield in winter triticale: II. Combining ability and hybrid prediction

Accurate hybrid prediction and knowledge about the relative contribution of general (GCA) and specific combining ability (SCA) are of utmost importance for efficient hybrid breeding. We therefore evaluated 91 triticale single-cross hybrids in field trials at seven environments for plant height, heading time, fresh biomass, dry matter content and dry biomass. Fresh and dry biomass showed the highest proportion (23%) of variance due to SCA. Prediction accuracies based on GCA were slightly higher than based on mid-parent values. Utilizing parental kinship information yielded the highest prediction accuracies when both parental lines have been tested in other hybrid combinations, but still moderate-to-low prediction accuracies for two untested parents. Thus, hybrid prediction for biomass traits in triticale is currently promising based on mid-parent values as emphasized by our simulation study, but can be expected to shift to GCA-based prediction with an increasing importance of GCA due to selection in hybrid breeding. Moreover, the performance of potential hybrids between newly developed lines can be predicted with moderate accuracy using genomic relationship information.     

黄河未来输沙量态势及其适用性对策

[目的] 探索黄河输沙预测的新思路，预估黄河未来输沙态势与输沙量水平，为黄河流域生态治理规划提供参考。[方法] 结合黄河流域水土保持生态修复现状，采用单累积曲线法、滑动平均及频率分析方法，分析1950—2019年黄河主要来沙区间的实测输沙量变化特征及其未来态势。[结果] 1950—2019年黄河输沙量呈现阶梯式减少。1950—2019年黄河中游各站累积实测输沙量随时间的变化可用“左半抛物线”表征。黄河输沙量自1997年以来已进入相对稳定态势，目前已达企稳状态；黄河潼关站未来年输沙量在90%频率下为1.00×10⁸ t左右，在10%频率下为5.00×10⁸ t左右，未来多年平均输沙量为1.40×10⁸ t。[结论] 为了维持黄河输沙量低稳状态，提升水土保持措施质量与标准，补齐“后水土保持”短板，构建完善的水沙关系调控体系，维持黄河下游河道冲淤平衡，是黄河流域生态保护与高质量发展的保障。