Adjusted method of penis fixation during boar semi-automatic semen collection aiming to reduce bacterial contamination

Semen collection has an essential role in the initial bacterial load in boar ejaculates and extended semen. The study aimed to explore the efficacy of an adjusted penis fixation in a semi-automatic collection system on reducing bacterial contamination of ejaculates in two-boar studs with different scenarios. Historically, stud A had low levels of bacterial load in raw semen, while stud B had a high level of contamination. A total of 56 mature boars had their semen collected using two methods of penis fixation: (a) Traditional: The penis was fixed directly with the artificial cervix and transferred to the adjustable clamp; (b) Adjusted: The fixation was performed with one gloved-hand, and after exteriorization, the penis was gripped using the artificial cervix with the other gloved-hand and transferred to the adjustable clamp. The bacterial load (p = .0045) and the occurrence of ejaculates >231 CFU/ml (p = .0101) were reduced in the Adjusted compared to the Traditional method. Bacterial load was reduced when using the Adjusted method in stud B (p = .0011), which showed a greater occurrence of critical factors for bacterial contamination (p ≤ .0034). The Adjusted method reduced the occurrence of ejaculates >231 CFU/ml when the preputial ostium was dirty (p = .016) and the duration of semen collection was >7 min (p = .022) compared to the Traditional method. In conclusion, the Adjusted penis fixation was efficient in reducing bacterial load of ejaculates, mainly in boar stud B, which had high contamination challenges.     

遗传算法优化超声辅助低共熔溶剂提取红枣总黄酮工艺研究

本文采用一种新型绿色溶剂提取红枣总黄酮,并对其提取工艺进行优化。通过单因素试验探究含水量、超声功率、提取时间、提取温度和料液比对红枣总黄酮得率的影响。在此基础上,采用遗传算法优化超声辅助低共熔溶剂提取红枣总黄酮工艺。结果表明：超声辅助低共熔溶剂提取红枣总黄酮最优的工艺参数为：含水量37%、超声功率167 W、提取时间30 min、提取温度54 ℃和料液比1∶26（g/mL）。在此条件下,所得红枣总黄酮得率为（29.33±0.37）mg/g。试验值和理论值的相对误差为1.24%。表明遗传算法可较好地模拟和预测不同提取条件下红枣总黄酮得率,且优化工艺参数是可行的。研究发现低共熔溶剂可作为一种新型、绿色溶剂用于高效提取红枣总黄酮。[关键词] 遗传算法|红枣|总黄酮|低共熔溶剂|工艺     

祁连山不同类型草地土壤细菌群落特征研究

祁连山是我国西部重要的生态屏障,拥有大量的草地资源。研究草地土壤细菌群落组成及其与土壤环境因子间的关系,可对维持草地生态及了解祁连山土壤细菌群落组成提供一定的数据基础。采用高通量测序技术检测并分析了祁连山默勒镇3种类型草地 （高寒草甸、人工草地、沼泽化草甸）0~10 cm土壤细菌群落结构及多样性,并对上述土壤细菌群落与土壤理化因子的相关性进行了系统的研究。结果表明：1）沼泽化草甸土壤全氮、全磷、有机质碳、含水量和硝态氮显著高于高寒草甸和人工草地（P<0.05）。2）3地共测得有效序列1022446条,以97%的一致性将序列聚类,高寒草甸、人工草地、沼泽化草甸OTU聚类均值分别是4917、5233、5075条。3）Shannon和Simpson多样性指数3地间差异不显著,Chao1指数表现为人工草地>高寒草甸>沼泽化草甸（P<0.05）。4）在门水平上,3地均以变形菌门、酸杆菌门、放线菌门和浮霉菌门为主要类群;在属水平上,表现出不同类型草地细菌富集类型不同。5）有机质碳、全磷、土壤含水量与土壤细菌群落的组成表现出极显著相关（P<0.01）。综上,祁连山地区小生境内3种草地土壤微生物群落存在差异,有机质碳、全磷、土壤含水量是影响群落的主要驱动因子。     

基于随机森林的高寒草地地上生物量高光谱估算

草地地上生物量（Aboveground biomass,AGB）是衡量草地生产力的关键因素,准确测定草地AGB具有重要意义。高光谱因具有时效性强、不破坏草地等特点被广泛用于草地生理生态指标的测定。本研究提取和计算了海北试验站高寒草地冠层的原始光谱（Original spectrum,OR）反射率、一阶微分光谱（First derivative spectrum,FD）反射率、光谱位置面积参数（Spectral parameters of spectral position and area,PA）和植被指数（Vegetation indices,VI）4种不同类型的特征变量,使用连续投影算法（Successive projections algorithm,SPA）和递归特征消除算法（Recursive feature elimination,RFE）进行特征选择,采用随机森林算法（Random forest,RF）构建草地AGB估测模型。结果表明：在由4种特征变量分别构建的草地AGB估测模型中,基于VI的RF模型精度最高（测试集R²=0.70,RMSE=557.87 kg·ha^-1）,实测AGB与估测AGB的线性R²达到0.72;不同类型特征变量组合构建的草地AGB估测模型中,PA+VI组合的RF模型精度最高（R²=0.71,RMSE=548.97 kg·ha^-1）,实测AGB和估测AGB的线性R²达到0.73。     

基于模拟退火算法优化给水管线造价公式研究

给水管线造价公式的精确性对工程经济分析与给水管网优化的科学性和经济性有重大影响。通过五个地区的铸铁管综合单价数据,采用最小二乘法对各组数据进行多项式一至十次的拟合,确定了给水管线造价公式的最佳拟合次数为三次;进一步采用模拟退火算法对拟合的多项式参数进行优化计算,求解给水管线造价公式。结果表明:凭借模拟退火算法随机全局搜索模式以及不受函数性质影响的优势,能够克服传统算法难以求解多阶导数的困难,提高公式拟合精度。     

基于RAGA的PPC模型在黑土区玉米调亏灌溉评价中的应用

调亏灌溉作为一种行之有效的节水灌溉方式,对黑土区农业水资源的可持续高效利用具有重要意义。而调亏灌溉方案的优劣取决于它的综合效果,难以直观评价。以2013年在黑龙江省红星农场进行的玉米调亏灌溉技术效应的试验研究为基础,选取了8个评价指标,采用投影寻踪分类模型(PPC),利用基于实数编码的加速遗传算法(RAGA)优化其投影方向,根据投影函数值得到各评价指标对综合评价的贡献大小对不同调亏处理的各项指标进行排序。结果表明:苗期水分调亏程度为田间持水量60%的处理为最佳调亏灌溉方案,产量和水分利用效率比适宜调亏灌溉处理分别提高了2.11%和6.42%。研究结果可为黑土区玉米灌溉管理提供科学依据。     

Association between porpoise presence and fish choruses: implications for feeding strategies and ecosystem-based conservation of the East Asian finless porpoise

The associations between feeding activities and environmental variables inform animal feeding tactics that maximize energetic gains by minimizing energy costs while maximizing feeding success. Relevant studies in aquatic animals, particularly marine mammals, are scarce due to difficulties in the observation of feeding behaviors in aquatic environments. This data scarcity concurrently hinders ecosystem-based fishery management in the context of small toothed-cetacean conservation. In the present study, a passive acoustic monitoring station was deployed in an East Asian finless porpoise habitat in Laizhou Bay to investigate potential relationships between East Asian finless porpoises and their prey. The data revealed that porpoises were acoustically present nearly every day during the survey period. Porpoise detection rates differed between spring and autumn in concert with activities of fish choruses. During spring, fish choruses were present throughout the afternoon, and this was the time when porpoise vocalizations were the most frequently detected. During autumn, when fish choruses were absent, porpoise detection rates decreased, and diurnal patterns were not detected. The close association between fish choruses and finless porpoise activities implies an “eavesdropping” feeding strategy to maximize energetic gains, similar to other toothed cetaceans that are known to engage similar feeding strategies. Underwater noise pollution, particularly those masking fish choruses, could interrupt finless porpoises’ feeding success. Fisheries competing soniferous fishes with finless porpoise could impact finless porpoise viability through ecosystem disruption, in addition to fishing gear entanglement.     

考虑陀螺效应的动力总成悬置系统分析和优化

应用陀螺力学理论，对传统动力总成悬置系统的无阻尼动力学方程进行修正，引入陀螺矩阵，得到新的动力学方程。对新的动力总成悬置系统动力学模型进行计算分析，研究了陀螺矩阵对频域、时域响应的影响。使用遗传算法分别对修改前后的方程进行优化计算，并进行比较分析。结果表明，对于低转速发动机，曲轴转动的陀螺效应不明显，而对于高转速的发动机，陀螺效应不能忽略，应以考虑陀螺力矩的方程为基础进行设计分析。     

Wavelet Application in Algorithms of Data Mining

Wavelets have been widely applied in such research areas as image processing, computer vision, network management and data mining. Wavelets have many favorable properties, which are hierarchical and multiresolution decomposition structure, linear time and space complexity of the transformations. The paper presents wavelet application on the algorithms of data mining, in cluding as clustering, classification, distributed data mining, similarity search, approximate query processing, visualization and so on. Finally, the paper concludes by discussing the impact of wavelets on data mining research and outlining potential future research directions and applications.