Effects of a high milk intake during the pre‐weaning period on nutrient metabolism and growth rate in Japanese Black cattle

This study aimed to determine the effects of feeding an increased volume of high‐fat milk during the early post‐natal life on metabolite concentrations in the blood, the expression of key genes regulating intermediary metabolism in the skeletal muscles, and the rate of growth of Japanese Black cattle. All calves were fed a high‐fat milk replacer (crude protein, 26%; crude fat, 25.5%; total dissolved nitrogen, 116%). Control calves (n = 4) were nursed with 500 g milk replacer until 3 months of age, whereas calves in the experimental group (n = 4) were nursed with 1800 g milk replacer until 3 months, and then the volume was gradually reduced until 5 months. Body weight was significantly higher in the experimental group than in the control group at 7 months. Plasma glucose concentrations were significantly lower in the experimental group. Expression of glucose‐transporter‐4 messenger RNA (mRNA) was lower, whereas that of glucose transporter 1, cluster of differentiation 36, and carnitine palmitoyltransferase‐1b mRNA was significantly higher in the Longissimus thoracis of the experimental group. Nutritional status during early post‐natal life appears to strongly influence the growth rate and glucose and lipid metabolism in Japanese Black cattle.     

Respond of Stock Trading Volume to Earning Report

Earning report is a main accounting report that transmits earning information to users. It is the core of financial reports system. Earning information is significant to users' decision making. This paper studies the respond of stock trading volume to earning report and draws the curve of trading volume before and after earning report. This paper further does a regression analysis of accidental earning and abnormal return rate, and draws the relation curve of them on the earning report date to prove stock trading volume does have remarkable respond to earning report. This research is significant to either lessen small investors blindness investment and help them make reasonable forecast to markets and regulate the disclosure of listed companies.     

基于ALS数据和哑变量技术森林蓄积量估测

基于机载LiDAR数据,分析哑变量对林分蓄积量估测精度的影响。以广西高峰林场为研究对象,借助机载激光雷达点云数据和96个样地数据,将样地数据按7∶3的比例随机划分为建模样本和测试样本,采用随机森林模型(RFR)和支持向量机模型(SVR)对建模样本与对应的点云特征回归建模,将树种组(针叶林和阔叶林)和龄组分别作为哑变量引入到回归模型。利用测试样本的估测精度评价模型的估测精度,引入树种组哑变量,随机森林模型决定系数R2从0.59提高到0.64,支持向量机模型决定系数R2从0.49提高到0.50。引入龄组哑变量,随机森林模型决定系数R2从0.59提高到0.65,支持向量机模型决定系数R2从0.45提高到0.55。根据模型的建模精度和验证精度结果得出,引入哑变量对蓄积量估测模型的精度提升是相对有效的。龄组哑变量对模型精度提升效果优于树种组哑变量。     

基于激光雷达数据的东北林区航空林分材积表编制

利用东北林区云冷杉林、落叶松林、樟子松林、红松林、栎树林、桦树林、杨树林、榆树林、椴树林和水胡黄林10种森林类型的1947个样地的激光雷达数据和地面实测蓄积量数据,首先通过多元线性回归和非线性回归方法,分别建立基于机载激光雷达数据的森林蓄积量回归估计模型,并通过对比分析,确定统一形式的基础回归模型;然后利用哑变量建模方法,建立基于不同森林类型参数和相同激光雷达变量的蓄积量模型。结果表明,研究建立的10种森林类型的线性蓄积量回归模型的解释变量个数在2~7之间,确定系数在0.460~0.858之间;非线性蓄积量回归模型的解释变量个数在2~4之间,确定系数在0.461~0.846之间。基于点云平均高度和平均强度建立的10种森林类型的二元蓄积量模型(研究称之为标准模型),其确定系数在0.440~0.815之间,平均预估误差在2.88%~4.42%之间,平均百分标准误差在16.76%~25.52%之间,预估精度基本达到森林资源规划设计调查技术规定要求。依据研究建立的10种森林类型的蓄积量模型,可以编制基于激光雷达数据的航空林分材积表,在森林资源调查实践中推广应用。     

人工降雨条件下不同坡度红壤坡面迳流泥沙变化特征研究

在人工模拟降雨强度为1.44 mm/min的条件下,研究了不同坡度(β)红壤近似裸地坡面迳流、泥沙的变化特征,研究结果表明:①地表迳流量随坡度的增大而迅速增加。②当β≤23°时,土壤侵蚀量随坡度的增大而迅速增加;当25°≤β≤40°时,土壤侵蚀量随坡度变化较小。③坡面土壤侵蚀的临界坡度则介于23°~25°之间。④坡度与侵蚀量关系可用函数表示为:S=199.1×L1.65×tan1.4β(0°≤β≤23°)。     

补灌量和覆盖量变化对旱地春小麦叶面积指数的影响

免耕覆盖中补灌量和秸秆覆盖量变化对叶片生长有较大影响,以甘肃省定西市安定区1979—2019年历史气象数据为基础,运用APSIM模型对补灌量与覆盖量耦合变化时旱地春小麦的叶面积指数进行模拟,并采用方差分析、二次多项式回归、单因素分析等方法,研究补灌量和覆盖量对旱地春小麦叶面积的影响机制。结果表明：在试验设计范围内,旱地春小麦叶面积指数随着补灌量变化在分蘖—拔节期呈开口向下的二次抛物线先增后减变化,补灌量在252.09 mm时春小麦叶面积指数出现最大值为1.83,其他各个时期均呈开口向上的二次抛物线递增变化。随着秸秆覆盖量变化,叶面积指数在出苗—分蘖期,呈开口向下的二次抛物线先增后减变化,试验设计范围内秸秆覆盖量为2397.09 kg/hm²时春小麦叶面积指数出现最大值为0.59,分蘖—拔节期呈开口向下的二次抛物线递增变化;其他各个时期均呈开口向上的二次抛物线递增变化。相同阶段下,补灌量每增加50 mm,春小麦叶面积指数最大增幅13.95%;秸秆覆盖量每增加1000 kg/hm²,春小麦叶面积指数最大增幅3.7%。补灌量对春小麦叶面积指数的影响...     

Improving wood volume predictions in dry tropical forest in the semi-arid Brazil

The volumetric variability of dry tropical forests in Brazil and the scarcity of studies on the subject show the need for the development of techniques that make it possible to obtain adequate and accurate wood volume estimates. In this study, we analyzed a database of thinning trees from a forest management plan in the Contendas de Sincorá National Forest, southwestern Bahia State, Brazil. The data set included a total of 300 trees with a trunk diameter ranging from 5 to 52 cm. Adjustments, validation and statistical selection of four volumetric models were performed. Due to the difference in height values for the same diameter and the low correlation between both variables, we do not suggest models which only use the diameter at breast height (DBH) variable as a predictor because they accommodate the largest estimation errors. In comparing the best single entry model (Hohenald-Krenn) with the Spurr model (best fit model), it is noted that the exclusion of height as a predictor causes the values of 136.44 and 0.93 for Akaike information criterion (AIC) and adjusted determination coefficient (R2 adj), which are poorer than the second best model (Schumacher-Hall). Regarding the minimum sample size, errors in estimation (root mean square error (RMSE) and bias) of the best model decrease as the sample size increases, especially when a larger number of trees with DBH≥15.0 cm are randomly sampled. Stratified sampling by diameter class produces smaller volume prediction errors than random sampling, especially when considering all trees. In summary, the Spurr and Schumacher-Hall models perform better. These models suggest that the total variance explained in the estimates is not less than 95%, producing reliable forecasts of the total volume with shell. Our estimates indicate that the bias around the average is not greater than 7%. Our results support the decision to use regression methods to build models and estimate their parameters, seeking stratification strategies in diameter classes for the sample trees. Volume estimates with valid confidence intervals can be obtained using the Spurr model for the studied dry forest. Stratified sampling of the data set for model adjustment and selection is necessary, since we find significant results with mean error square root values and bias of up to 70% of the total database.     

播期对河套地区玉米灌浆进度的影响

旨在为玉米的高产栽培提供理论支撑。采用分期播种法,利用试验数据,建立28个生长模型（方程均通过0.01的极显著检验）,将玉米灌浆期百粒干重、百粒体积随灌浆日数增加的时段分为三阶段,即渐增期、快增期和缓增期。适时播种的玉米吐丝后百粒体积、百粒干重增加进入渐增期,终止日分别为吐丝后的6天和20天,此后进入快速增长期,时间分别为22天和18天;其后到籽粒体积和干重增加进入缓慢增长期。适时播种的玉米百粒干重增加逐渐增长期为吐丝后活动积温区间0~502.4℃·d,增幅0.014 g/℃·d;快速增长期为吐丝后活动积温区间502.4~938.4℃·d,增幅0.049 g/℃·d;缓慢增长期为吐丝后活动积温区间938.4~1355.1℃·d,增幅0.018 g/℃·d。     

车-液耦合响应下液罐车稳定性控制仿真

为了提高液罐车行驶安全性、减少液罐车侧翻、失稳所带来的危害,对于液罐车在转向或换道时车-液耦合动态响应对整车稳定性的影响进行了研究。联合液体纳维斯托克斯和流动控制方程,应用计算流体动力学软件ANSYS/Fluent建立并求解液体晃动模型,通过结合液体晃动模型和三自由度液罐车刚体模型获得液罐车车-液耦合动力学模型,分析有无控制策略情况下,液体晃动对液罐车横向稳定性的影响。仿真结果表明:提出的模糊差动制动控制策略能够有效提高车辆抗侧翻能力,减少罐车运输过程中交通事故的发生,对液罐车运输有指导意义。     

短轮伐期桉树人工林个体林木特征研究

利用广东高要和广西扶绥两地14个2~10年生桉树林分样地共287株样木,研究短轮伐期桉树人工林个体林木特征指标,并比较现有广西良种桉二元带皮和去皮材积公式估算个体林木材积的准确性,分析不同年龄、林分和径阶林木的出材率。结果表明:带皮和去皮林木的胸高形数为0.504±0.004 2和0.529±0.004 4、实验形数为0.410±0.002 4和0.427±0.002 7、形率为0.657±0.003 4和0.690±0.003 6、高径比为1.22±0.017和1.43±0.019。用广西良种桉二元带皮和去皮材积公式估算单株林木带皮和去皮材积与实际材积高度相关(r>0.99),但估算值普遍偏低,平均分别小3.7%和21.0%;尤以用带皮材积公式估算去皮材积比用去皮材积公式估计要准确,平均只小2.3%。如以6年生以上样地和尾径4 cm以上的去皮林木为实际出材,5个相关样地林分平均出材率为(73.3±4.31)%,最小为54.6%,最大为81.5%。