加速广义Laguerre多项式级数的Laplace变换的数值反演方法

本文利用Levin t-变换迭代法，对加速广义Laguerre多项式级数，提出了一种新的Laplace变换的数值反演方法，这种方法在精度上和数值稳定性上的效果都较好。     

The use of urban organic wastes in the control of erosion in a semiarid Mediterranean soil

Abstract. A two year field experiment was carried out in a semiarid Mediterranean area in order to evaluate, the effect on soil erosion of adding different urban organic wastes: a stabilized municipal waste (compost), an unstabilized municipal waste, and an aerobic sewage sludge. All the treatments significantly reduced soil erosion, compared to the control soil. The soil amended with compost was the most effective treatment, reducing soil loss by 94% and runoff by 54%.     

两种一年生植物在替代试验中的相互竞争关系

（1）用替代试验研究了燕麦（Aneva sativa）和箭舌豌豆（Vicia sativa）在混播中的竞争相互作用。为了攻混播比例对两种植物在混播条件下的行为影响，田间试验设为5个混播总密度和5种混播比例，共了5次。（2）方差分析表明，相对总生物量（RYT）和竞争平衡指数（CBI）对总密度，混播比例和生长时间的反应敏感。总密度对RYT和CBI的影响高度显著，在大多数情况下，混播比例对RYT和CBI的影响不显著。（3）本文研究的结果表明，持续时间对RYT和CBI很强的影响，在第1次测定时，RYT值接近1而BI值接近0，这一事实表明，种间无竞争或互惠作用。而在生长旺盛期，种间竞争较为剧烈。（4）本研究结果表明，箭舌豌豆的生长严惩受到燕麦的抑制作用，这说明箭舌豌豆在与燕麦混播时表现为竞争上的弱者。     

小麦矮秆育种中性状间关系的多元分析

以7个株高梯度系列的35个系统及5个亲本品种为材料,采用典范分析和逐步回归分析研究了株高及其构成因子与产量因子、产量生理性状间的关系。结果表明:①株高因子通过产量生理性状影响产量因子,一定的生物学产量是获得高产的基础。②矮秆品种的高化对提高产量、千粒重和收获指数有利,对蛋白质含量的影响不明显;高秆品种矮化能显著提高收获指数,对籽粒的蛋白质含量影响不大。③在主要性状符合育种目标的前提下,选择倒二节间较长、第一和第二叶间距略长、穗颈和穗部较长的类型可能对提高产量有利。     

Trends in NE Atlantic landings (southern Portugal): identifying the relative importance of fisheries and environmental variables

Time series of commercial landings from the Algarve (southern Portugal) from 1982 to 1999 were analyzed using min/max autocorrelation factor analysis (MAFA) and dynamic factor analysis (DFA). These techniques were used to identify trends and explore the relationships between the response variables (annual landings of 12 species) and explanatory variables [sea surface temperature, rainfall, an upwelling index, Guadiana river (south‐east Portugal) flow, the North Atlantic oscillation, the number of licensed fishing vessels and the number of commercial fishermen]. Landings were more highly correlated with non‐lagged environmental variables and in particular with Guadiana river flow. Both techniques gave coherent results, with the most important trend being a steady decline over time. A DFA model with two explanatory variables (Guadiana river flow and number of fishermen) and three common trends (smoothing functions over time) gave good fits to 10 of the 12 species. Results of other models indicated that river flow is the more important explanatory variable in this model. Changes in the mean flow and discharge regime of the Guadiana river resulting from the construction of the Alqueva dam, completed in 2002, are therefore likely to have a significant and deleterious impact on Algarve fisheries landings.     

旱地保护性耕作地表径流和土壤水分平衡模型

在田间试验和对现有径流模型及土壤水分平衡模型改进的基础上，建立了适用于保护性耕作的地表径流和土壤水分平衡模型。该模型以日为步长，根据气象数据、土壤水分状况、作物生长发育及耕作管理措施，模拟不同耕作管理体系下地表径流和田间水分平衡的变化。针对保护性耕作的特点，主要对径流曲线数字(USDA—Curve Number)法进行了改进，在PERFECT模型的基础上增加了坡度和降雨强度两因素的影响，从而使模型较全面地考虑了残茬覆盖、耕作、坡度及降雨强度等多种因素对径流的影响；采用简单实用的Priestley—Taylor公式计算潜在蒸散量，并考虑作物覆盖与残茬覆盖对土壤蒸发与作物蒸腾的影响。通过田间径流试验和根层有效贮水量测定数据的验证，证明了地表径流和土壤水分的模拟值与实测值比较接近。     

全球气候暖干化对秦岭南北河流径流泥沙的影响研究

以秦岭南侧汉江和北侧渭河多年的径流泥沙观测资料，分析了全球气候暖干化对秦岭南北径流泥沙的变化。分析指出在80年代后，由于全球气候变化的影响，秦岭南北河流年均径流量均减少，与1935－1980年相比，汉江河流年均径流量减少1.9%，渭河河流年均径流量减少27.4%；同时汉江河流泥沙含量明显减少，但渭河河流泥沙含量呈增加趋势，是汉江河流泥沙含量133倍，表明了秦岭南北两侧在全球气候暖干化表现出明显的区域响应性。     

喀喇昆仑山盖孜河水文水资源特性分析

喀喇昆仑山河流自有水文资料记载以来 ,近 10年洪灾发生频率明显高于以往 ,人民的生命财产损失程度也大幅度增加。在分析了盖孜河流域的径流及气候多年变化过程后 ,认为洪灾频发的原因是近年来流域内降水及气温呈上升趋势 ,导致高山冰川退缩 ,河流径流增加 ,洪灾增大、频率增高 ;小区域多年气候变化过程从侧面印证了我国西北地区气候由暖干向暖湿变化。     

植物化感作用影响因素的再认识

土壤养分、酶、微生物、本底特性,根茬还田、水分、植物根系、种植体系和种植模式与化感作用的互作关系,表明这些因子可通过对土壤养分有效性、微生物种群结构、土壤酶活性和化感物质浓度的影响而对化感作用产生直接或间接影响,这些可为通过化感作用途径构建高效农田生态系统提供新的思路.     

Simulation of future dissolved oxygen distribution in pond culture based on sliding window-temporal convolutional network and trend surface analysis

Dissolved oxygen (DO) is a key ecological factor to measure the quality of water in the aquaculture. As the pond water body is affected by the breeding environment, the spatial distribution of DO shows a certain law in the entire pond. Therefore, to simulate the distribution of DO in aquaculture waters and grasp the temporal and spatial variation of DO is the key to achieving precise regulation of DO. For this purpose, this paper proposed a method for simulating the temporal and spatial distribution of DO in pond culture based on a sliding window-temporal convolutional network together with trend surface analysis (SW-TCN-TSA). This paper first utilized SW to construct DO data sets with different prediction durations, and then used the improved TCN model to realize one-dimensional time series prediction for DO at single monitoring point. Based on the prediction results of DO, a TSA method was performed on the predicted values of DO at the extreme moments of all discrete monitoring points, so as to realize the simulation of the temporal and spatial distribution of DO in the pond. Experimental results show that the SW-TCN model has better prediction performance for one-dimensional time series prediction of DO. Compared with traditional deep networks, such as CNN, GRU, LSTM, CNN-GRU and CNN-LSTM, the values of evaluation indicators (MSE, MAE and RMSE) have been greatly improved. In the process of trend surface fitting, all fitting R² of DO at different water depths are higher than 0.9, indicating that the TSA can accurately reflect the temporal and spatial distribution of DO. This method can provide a basis for the prediction and early warning of DO in the three-dimensional space of the pond and has high practicability in aquaculture.