黄鳍棘鲷标志放流群体的规格适宜性评价

合理选取标志放流鱼的规格是成功监测放流鱼类动态及评估增殖效果的关键步骤。本研究以黄鳍棘鲷为对象,通过2个实验评价标志鱼的适宜规格。实验1对比了4种体长的黄鳍棘鲷(平均体长5、7、11和14 cm)作T型标志后其生长、存活和标志保留情况,并利用逻辑斯蒂回归模型分别分析标志鱼存活率和标志保留率的规格特异性;实验2模拟了不同混合比例下2种体长黄鳍棘鲷标志鱼与不标志鱼的捕捞情况,并利用重抽样方法对捕捞结果作计算机重抽样,分析2种鱼能否充分混合以及标志鱼的规格、比例对捕捞结果的影响。结果显示:(1)7、11和14 cm标志组的特定生长率与对照组无显著差异;(2)标志鱼的存活率随体长的增加而增加(5 cm标志组的鱼在标志后7 d内全部死亡,7、11和14 cm标志组的存活率分别为77.5%、92.5%和100.0%)。标志鱼的存活率与初始体长的逻辑斯蒂回归关系式为P=exp(0.099X-6.900)/[1+exp(0.099X-6.900)];(3)各组的标志保留率较高(7、11和14 cm标志组的标志保留率分别为97.5%、100.0%和100.0%),但与体长无明显关系;(4)模拟捕捞结果与计算机重抽样结果无显著差异,二者均不受鱼体规格的影响,但受标志鱼比例的影响极显著,标志鱼比例越高,其捕获率也越高。综上,建议今后采用T型标志方法开展增殖放流品种(如黄鳍棘鲷)的相关研究时,应综合考虑成本和可接受的误差范围以选择符合研究目的的标志鱼规格,若需标志鱼的存活率高于50.0%,则体长至少为7 cm,高于75.0%则体长至少为8 cm,高于95.0%则体长至少为10 cm。此外,在成本允许的条件下,建议尽可能增加放流鱼类中标志鱼的比例以提高增殖效果评估的代表性,而具体适宜的比例值得深入研究。     

都市餐饮企业的净菜需求影响因素分析——以北京市为例

净菜的广泛使用能提高餐饮企业的出餐率,减少其后厨面积、劳动用工和厨余垃圾.基于北京地区708份餐饮企业净菜需求的问卷调查样本,运用垄断竞争市场理论和二元选择模型分析了影响餐饮企业净菜使用行为的具体因素.研究发现,对净菜了解程度不够和净菜价格偏高是制约餐饮企业使用净菜的主要因素,具有不同个体特征和环境特征的餐饮企业选择净...     

PTC电阻式车用油位传感器控制系统研究

为了提高油位传感器的精确性,避免传统传感器的不足,根据传统的电阻油位传感器提出了在结构上采用PTC探针式电阻来获取油位,实时检测探针两端电压来分析并获取油位,并采用PID控制对数据进行修正。提出了基于压差的合理性范围检测油位评估检测系统并运用Simulink搭建系统的模型,在评估油位时出现不合理错误会报告给DSM系统,并重新测量。用系统标定实验和系统测量实验来验证系统的准确性。系统在一定程度上提高了测量的准确性并能够有效避开温度等其他因素的影响,经实验证明在标定后的检测系统精确性较高,最大相对误差不超过2.90%。     

基于损耗模型的永磁同步电机高效控制参数敏感性分析

针对分析参数变化对电机损耗效率的影响建立了永磁同步电机(Permanent Magnet Synchronous Motor)损耗模型,推导出电机损耗最小的最优定子电流。然后,分析铁损电阻、铜损电阻以及磁链变化对损耗精度的影响。结果表明,当铁损电阻变为原来的1.2倍时,总损耗效率增加1.0%;当铜损电阻变为原来1.5倍时,总损耗效率下降28%;当磁链变为原来的1.4倍时,总损耗效率下降1.4%。通过电机损耗的参数敏感性分析,为基于模型的电机高效率控制提供了重要参考。     

加快可靠性优化设计的迭代收敛速度新方法

本研究阐述了优化设计问题的求解方法,给出基于系统可靠度的结构优化设计数学模型,对以往求解优化模型时用的优化准则法进行了介绍和改进。通过实例的求解过程,验证了改进后的优化准则法的良好效果,即迭代收敛速度加快。这种改进对系统失效模式较多的情况,效果更为明显。     

Predicting soil depth in a large and complex area using machine learning and environmental correlations

Soil depth is critical for eco-hydrological modeling, carbon storage calculation and land evaluation. However, its spatial variation is poorly understood and rarely mapped. With a limited number of sparse samples, how to predict soil depth in a large area of complex landscapes is still an issue. This study constructed an ensemble machine learning model, i.e.,quantile regression forest, to quantify the relationship between soil depth and environmental conditions. The model was then combined with ...     

不结球白菜维生素C和可溶性糖含量的遗传分析

采用主基因—多基因混合遗传模型分析方法,对不结球白菜乌塌菜×矮脚黄、雪克青×矮脚黄两个组合的维生素Ｃ、可溶性糖含量进行单世代和联合世代遗传分析。结果表明,两组合中维生素Ｃ含量遗传符合一个主基因和多基因的混合遗传模型,主基因遗传率为５２６８％～７４１２％。可溶性糖在雪克青×矮脚黄组合中也符合主基因—多基因遗传模型,主基因遗传率为８９７３％～８９７９％。维生素Ｃ和可溶性糖主基因效应均以加性效应为主,在乌塌菜×矮脚黄组合中,两性状主基因有较明显的负向显性效应,在雪克青×矮脚黄组合中,显性效应不明显。育种实践中应注重对主基因加性效应的利用。     

Soil saturation effects on forest dynamics: scaling across a southern boreal/northern hardwood landscape

Patch modeling can be used to scale-up processes to portray landscape-level dynamics. Via direct extrapolation, a heterogeneous landscape is divided into its constituent patches; dynamics are simulated on each representative patch and are weighted and aggregated to formulate the higher level response. Further extrapolation may be attained by coarsening the resolution of or lumping environmental data (e.g., climatic, edaphic, hydrologic, topographic) used to delimit a patch.Forest patterns at the southern boreal/northern hardwood transition zone are often defined by soil heterogeneity, determined primarily by the extent and duration of soil saturation. To determine how landscape-level dynamics predicted from direct extrapolation compare when coarsening soil parameters, we simulated forest dynamics for soil series representing a range of drainage classes from east- central Maine. Responses were aggregated according to the distribution of soil associations comprising a 600 ha area based on local- (1:12,000), county- (1:120,000) and state- (1:250,000) scale soil maps. At the patch level, simulated aboveground biomass accumulated more slowly in poorer draining soils. Different soil series yielded different communities comprised of species with various tolerances for soil saturation. When aggregated, removal of waterlogging caused a 20–60% increase in biomass accumulation during the first 50 years of simulation. However, this early successional increase and the maximum level of biomass accumulation over a 200 year period varied by as much as 40% depending on the geospatial data. This marked discrepancy suggests caution when extrapolating with forest patch models by coarsening parameters and demonstrates how rules used to rescale environmental data need to be evaluated for consistency.     

Model uncertainty in the ecosystem approach to fisheries

Fisheries scientists habitually consider uncertainty in parameter values, but often neglect uncertainty about model structure, an issue of increasing importance as ecosystem models are devised to support the move to an ecosystem approach to fisheries (EAF). This paper sets out pragmatic approaches with which to account for uncertainties in model structure and we review current ways of dealing with this issue in fisheries and other disciplines. All involve considering a set of alternative models representing different structural assumptions, but differ in how those models are used. The models can be asked to identify bounds on possible outcomes, find management actions that will perform adequately irrespective of the true model, find management actions that best achieve one or more objectives given weights assigned to each model, or formalize hypotheses for evaluation through experimentation. Data availability is likely to limit the use of approaches that involve weighting alternative models in an ecosystem setting, and the cost of experimentation is likely to limit its use. Practical implementation of an EAF should therefore be based on management approaches that acknowledge the uncertainty inherent in model predictions and are robust to it. Model results must be presented in ways that represent the risks and trade‐offs associated with alternative actions and the degree of uncertainty in predictions. This presentation should not disguise the fact that, in many cases, estimates of model uncertainty may be based on subjective criteria. The problem of model uncertainty is far from unique to fisheries, and a dialogue among fisheries modellers and modellers from other scientific communities will therefore be helpful.     

Temperature-dependent stock-recruitment model for walleye pollock (Theragra chalcogramma) around northern Japan

Changes in fish year‐class strength have been attributed to year‐to‐year variability in environmental conditions and spawning stock biomass (SSB). In particular, sea temperature has been shown to be linked to fish recruitment. In the present study, I examined the relationship between sea surface temperature (SST), SSB and recruitment for two stocks of walleye pollock (Theragra chalcogramma) around northern Japan [Japanese Pacific stock (JPS) and northern Japan Sea stock (JSS)] using a temperature‐dependent stock‐recruitment model (TDSRM). The recruitment fluctuation of JPS was successfully reproduced by the TDSRM with February and April SSTs, and February SST was a better environmental predictor than April SST. In addition, the JPS recruitment was positively related to February SST and negatively to April SST. The JSS recruitment modeled by the TDSRM incorporating February SST was also consistent with the observation, whereas the relationship between recruitment and February SST was negative, that is the opposite trend to JPS. These findings suggest that SST in February is important as a predictor of recruitment for both stocks, and that higher and lower SSTs in February act favorably on the recruitment of JPS and JSS respectively. Furthermore, Ricker‐type TDSRM was not selected for either of the stocks, suggesting that the strong density‐dependent effect as in the Ricker model does not exist for JPS and JSS. I formulate hypotheses to explain the links between SST and recruitment, and note that these relationships should be considered in any future attempts to understand the recruitment dynamics of JPS and JSS.