基于输入-输出流分析的生态网络φ模式能流、 ρ模式能流测度方法

提出了生态网络能量传递的两类路径,即φ和ρ模式能流传递,运用输入-输出流方法推导了φ和ρ模式下的能量流通量计算公式。以Pilette和Kincaid提出的生态网络系统为例,计算了两种模式下系统能量通量的大小,评估了φ模式能流、ρ模式能流对生态网络能量传递的影响程度。研究表明:该生态系统每天能量流通量为31g C,其中90.23%的能量流通量是通过φ模式传递的,9.77%的能量流通量是通过ρ模式传递的;针对网络中每个节点,分析了φ和ρ模式对各自能量流通量的影响程度。     

地方政府托管办院模式SWOT分析

为满足新兴城区和欠发达地区优质医疗资源需求,突破大型医院发展瓶颈,地区政府与大型医院合作办院越来越多。文章根据协作双方对土地、基本建筑、医护人员、医疗设备等项目的不同投入程度,对办院模式分为托管、接管、合作三种模式。以中山大学附属第三医院岭南医院为例,通过SWOT分析法对托管办院模式的优势、劣势、威胁与机会进行了分析,充分认可了托管办院这一模式的合理性,并提出在吸引、留住人才和产权问题两个方面的建议,以期对协作办院的进一步完善提供思路。     

名医素质特征与培养规律的初步研究

目的 探索名医的基本素质特征和培养规律。方法 在文献检索和专家访谈的基础上,采用自设问卷方式进行调查,并对调查结果数据进行统计分析。结果 知名医学专家与患者及家属在名医的内涵、培养目标、成长历程等问题上的观点是一致的,但在名医的培养周期、评价标准、培养方式等问题上存在着不同的观点。结论 名医不仅要拥有精湛的医术和高尚的医德,还要得到老百姓和医师同行的认可。名医的成才需要良好的成长环境和自由发展的空间,在成长的过程中我们可以通过发挥个人主观能动性,增强科室内部凝聚力,健全医师的考核体系,缓解紧张的医患关系,改革医学的教育模式等途径来培养名医。     

医院门诊自助服务系统使用率的多因素分析

目的 探索医院门诊一站式自助服务系统在不同干预措施下的使用情况和使用患者的反馈。方法 2015年1—12月通过对门诊进行未干预、3种单独干预各1月、两种较强联合干预和全线干预后,计算自助服务系统的使用人次和使用人次占比,之后对患者进行问卷随访,比较患者的满意度、机器正常运行率和节省的时间。结果 在入口处设置醒目标识提示自助服务系统,多途径宣传一站式服务并且在自助机旁配备充足的指导人员的自助服务系统使用率相对最高。结论 自助服务系统使用率的提升不仅需要多途径、多层次,还需要门诊管理者在必要的时机进行适当的策略调整以取得有效模式来配合门诊运转。

     

香菜CsEF 1α基因克隆与表达分析

翻译延伸因子EF 1α(elongation factor 1 alpha)是细胞中最丰富的蛋白质之一,其在确保mRNA正确解码以产生细胞蛋白质方面发挥重要作用。该研究采用RT PCR扩增方法克隆香菜CsEF 1α基因序列,利用生物信息学对CsEF 1α基因结构、序列特征及系统进化等进行分析,并采用qPCR探究CsEF 1α基因在香菜不同生长时期和非生物胁迫下的表达模式,为进一步揭示EF 1α基因调控机制的研究奠定基础。结果显示：(1)成功克隆获得香菜CsEF 1α基因序列;CsEF 1α基因包含1个1 344 bp的开放阅读框,编码447个氨基酸,分子式为C₂₂₀₂H₃₅₄₄N₅₉₄O₆₄₄S₂₀,蛋白质分子量为49.29 kD,等电点为9.12;氨基酸序列组成中赖氨酸数量最多(49个,占11.0%),色氨酸数量最少(3个,占0.7%);属碱性蛋白。(2)CsEF 1α蛋白主要由无规则卷曲(36.91%)和α 螺旋(30.43%)构成,定位于细胞质;系统进化树分析显示,CsEF 1α与胡萝卜、野生番茄、青蒿素和非洲菊的亲缘关系较接近;启动子分析包括4种植物生长发育元件、3种激素响应元件和3种胁迫响应元件。(3)qRT PCR结果显示,CsEF 1α基因的表达量随着香菜生长发育时间的延长而升高,并且与转录丰度的变化一致;CsEF 1α基因对4种不同非生物胁迫的响应表达模式有所差异;随着胁迫时间的延长,在盐胁迫下CsEF 1α基因表现出先升高后降低趋势,而在低温、高温和干旱胁迫下表现出先降低再升高的趋势。研究表明,CsEF 1α基因参与了香菜对非生物胁迫的应答,在香菜生长发育和非生物胁迫中具有重要调控作用。     

后医改时期医院后勤社会化管理存在的问题与对策

随着医改的深化与推进,医院后勤既有的供给式服务模式弊端日渐突显,旧观念与新形势的冲突引发一系列新型后勤管理问题。因此,要从根本上“治愈”医院后勤管理的顽疾,必须从转变思想开始,进而改革现有的运行机制、人才任用与培养模式和建立完整而有力的规章制度。     

医院虚拟学科的建设思路与实践探索

?????? 随着医学科学技术的快速发展和学科之间不断交叉融合,虚拟学科已成为医学学科发展的一个重要方向。从虚拟学科的定义出发,探讨了虚拟学科的构建原则和组织特征,结合医院实践介绍了4种虚拟学科模式,即星型模式、互补模式、平行模式和混合模式,并指出医院虚拟学科建设有利于促进医学科学技术的发展、充分利用有限的医学资源、促进医学研究成果的转化、促进各学科间的良性合作。

     

公立医院院长绩效考核与评价研究

目的 通过对哈尔滨市14家公立医院院长2010年工作绩效进行考核和评价,完善公立医院院长绩效评价工具和方法。方法 运用专家咨询法构建院长绩效考核评价指标体系,运用专题小组法制订评价方案,采用直接评分法对14家医院的绩效进行评价。结果 构建了包含6个关键维度、27个指标的公立医院院长绩效考核指标体系,通过绩效评价发现薄弱环节,对体系的适用性与可操作性进行验证。结论 考核体系具有良好的适用性与可操作性。     

C差异与气体交换参数

在苗木生长的不同时期对13个毛白杨(Populus tomentosa)杂种无性系叶片碳同位素δ¹³C和气体交换参数(净光合速率P_n、蒸腾速率T_r、瞬时水分利用效率WUE_i、气孔导度G_s和胞间CO₂浓度C_i)的差异进行研究, 分析不同无性系间δ¹³C与气体交换参数的相互关系, 目的在于探求δ¹³C在筛选高光合及高水分利用效率毛白杨杂种无性系中的应用价值。结果表明: 不同生长时期和不同无性系间δ¹³C、T_r、WUE_i、G_s和C_i的差异均显著, δ¹³C和WUE_i表现为9月＞7月, T_r、G_s和C_i表现为7月＞9月, P_n在不同生长时期差异不显著。季节变化是引起毛白杨杂种无性系叶片δ¹³C差异的主要原因。同一时期, 无性系间δ¹³C和WUE_i表现出较好的一致性, 即WUE_i较高的无性系30、42、46、83、BL2和BL5, 其δ¹³C值也较高, WUE_i较低的无性系B331和TG34, 其δ¹³C值也较低, 且不同时期(7月和9月) δ¹³C和WUE_i呈较强的正相关, 相关系数r分别为0.739 0和0.545 8, 高δ¹³C可以作为筛选高WUE_i毛白杨的有效指标, 且在苗木生长旺盛时期选育能得到更为可靠的结果。对毛白杨而言, 高WUE_i的无性系, 一般具有适中或较低的G_s和C_i, 但不一定具有很高的P_n, 气孔调节使得毛白杨在不影响光合作用的同时保持较高的WUE。     

C的开度与方位差异

受太阳活动的影响, 树冠不同方位以及内外部的叶片接受到的光照存在差异, 造成温度、湿度等小气候因子也存在差异。叶片的形态解剖结构和生理特性等会对外界环境条件的改变发生响应。为了更好地了解树木生长的局部小环境条件差异对树木生长的影响, 该文选择国槐(Sophora japonica)、悬铃木(Platanus orientalis)、银杏(Ginkgo biloba)、榕树(Ficus microcarpa)和黄葛榕(F. lacor)5种冠幅较大的树种, 通过测定树冠内外部及4个方位上的比叶重(leaf mass per area, LMA)、叶绿素a (chlorophyll a, Chl a)、叶绿素b (chlorophyll b, Chl b)及类胡萝卜素(carotenoid, Car)的含量及碳稳定同位素比率(carbon isotope ratio, δ¹³C)等指标, 研究叶片形态、生理指标等随树冠开度的变化以及方位差异。结果表明, 叶片LMA和δ¹³C均随树冠开度增加而增大, 光合色素含量则相反; 叶片LMA和δ¹³C的方位变化则是南向>西向>北向>东向, 与叶片所接受到的光强变化规律一致, 而光合色素含量的方位差异较复杂、且因树种而异, 总的来说, 以受光最弱的东向含量最高。上述结果表明, 树冠外围和南向、西向的叶片由于接受到的光能较多、温度高、相对湿度小等, 其叶片会增大单位面积的重量、减小气孔开度和光合色素含量, 从而减少对光能的吸收, 也使光合作用降低、δ¹³C增大, 而不同方位光照对光合色素含量的影响机制较为复杂, 这些都表明了叶片对周围小气候的形态和生理上的适应。     

Frequent and occasional species and the shape of relative-abundance distributions

Recently, three different models have been proposed to explain the distribution of abundances in natural communities: the self‐similarity model; the zero‐sum ecological drift model; and the occasional–frequent species model of Magurran and Henderson. Here we study patterns of relative abundance in a large community of forest Hymenoptera and show that it is indeed possible to divide the community into a group of frequent species and a group of occasional species. In accordance with the third model, frequent species followed a lognormal distribution. Relative abundances of the occasional species could be described by the self‐similarity model, but did not follow a log‐series as proposed by the occasional–frequent model. The zero‐sum ecological drift model makes no explicit predictions about frequent and occasional species but the abundance distributions of the hymenopteran species did not show the excess of rare species predicted by this model. Separate fits of this model to the frequent and to the occasional species were worse than the respective fits of the lognormal and the self‐similarity model.     

广义模型及分类回归树在物种分布模拟中的应用与比较

比较3个应用较广的模拟物种地理分布模型:广义线性模型(GLM)、广义加法模型(GAM)与分类回归树(CART)对中国树种地理分布模拟的优劣,以提出更为合适的模拟物种地理分布模型,并用于预测气候变化对物种地理分布的影响。3个模型对中国15种树种地理分布的模拟研究表明:除对油松、辽东栎分布的模拟精度稍差外,对其余树种分布的模拟精度均较高,其中以GAM模型最好。结合地理信息系统(GIS),比较分析了这3个模型对青冈、木荷、红松和油松4种树种的地理分布模拟效果,结果亦表明:这3个模型均能很好模拟青冈和木荷的地理分布,而GLM模型对红松分布的模拟结果不太理想,3个模型对油松分布的模拟结果均不甚理想,其中以GLM模型最差。基于3个模型对未来气候变化下青冈与蒙古栎地理分布的预测表明:GLM模型与GAM模型对青冈分布的预测结果较为接近,青冈在未来气候变化情景下向西和向北扩展,而CART模型预测青冈在未来气候变化情景下除有向西、向北扩展趋势外,广东和广西南部的青冈分布区将消失;3个模型均预测蒙古栎在未来气候变化情景下向西扩展,扩展面积的大小为:模型的模拟面积>模型>模型。     

Simple parametric and nonparametric models for excess and relative mortality

This paper studies two classes of hazard-rate-based models for the mortality in a group of individuals taking normal life expectancy into account. In a multiplicative hazard model, the estimate for the relative mortality generalises the standardised mortality ratio, and the adequacy of a model with constant relative mortality can be tested using a type of total time on test statistic. In an additive hazard model, continuous-time generalisations of a "corrected" survival curve and a "normal" survival curve are obtained, and the adequacy of a model with constant excess mortality can again be tested using a type of total time on test statistic. A model including both the multiplicative hazard model and the additive hazard model is briefly considered. The use of the models is illustrated on a set of data concerning survival after operation for malignant melanoma.     

农田土壤水分预测模型的研究进展及应用

本文对国内外土壤湿度的监测,预报发展情况进行了回顾,总结了国内外土壤水分监测方法及其原理,介绍了国内外土壤湿度预测模型的研究进展及其应用情况,讨论了传统的土壤水分平衡方程统计模型法,从土壤水分运动方程出发的物理学模型法,利用气象要素与土壤水相关关系为基础的统计预报法、及新兴的人工神经元网络和遥感数据估测法的优缺点,并对土壤水分研究工作所面临的问题进行了必要的阐述。     

Identifiability analysis and improvement of a tree water flow and storage model

A recently published tree water flow and storage model (RCGro) for simulating water transport dynamics in trees and related stem diameter variations was improved in order to better describe a data set gathered under mild drought stress conditions. Model improvements were carried out based on the results of a mathematical identifiability analysis. This analysis provided important information with respect to the balance between model complexity and data availability. Using the identifiability analysis results, we were able to (1) highlight weaknesses of the model; (2) obtain information on how the model could be reduced in some places, to improve its identifiability properties, and extended in others, to enhance model performance; (3) identify which measurements are necessary to optimally calibrate the model. The resulting improved model was less complex (contained less unidentifiable parameters), had better dynamic properties and was able to better describe the stress data set.     

设施葡萄萌芽调控中需冷量和需热量及其相互关系

采用3种需冷量估算模型（≤7．2℃模型、0～7．2℃模型和犹他模型）和2种需热量估算模型（生长度小时模型和有效积温模型）分别测定了14个设施葡萄品种的需冷量和需热量,并分析了两者的相互关系。结果表明,不同葡萄品种的需冷量和需热量存在一定差异,需冷量值介于754～1489h（≤7_2℃模型）、497-757h（0～7．2℃模型）或192～755．5CU（犹他模型）,需热量值为18491～24070GDH℃（生长度小时模型）或120～377D℃（有效积温模型）,且欧亚种品种需热量普遍高于欧美杂种品种。另外,本研究还表明,用生长度小时模型估算出来的需热量值与需冷量值之间呈负相关关系,而有效积温模型估算出来的需热量值与需冷量值之间则呈正相关关系。     

景观空间动态模型研究现状和应重点解决的问题

分析了景观空间动态模型研究的现状及今后的重点发展方向。论文重点介绍了随机景观模型、邻域规则模型和景观过程模型(包括渗透模型、个体行为模型和空间生态系统模型)3类景观空间模型的发展现状、存在的主要问题以及对这些模型途径进行完善的有关工作,并从确证性分析、有效性分析与敏感性分析等3个方面阐述了模型检验技术的发展现状。最后,总结了未来景观空间动态模型发展中应重点解决的主要问题,即模型算法的优化、尺度转换、模型的复杂化与简化、模型检验与评价,通用模型的建立以及传统模型与社会经济因素衔接问题。     

Simulating Daily and Half-Hourly Fluxes of Forest Carbon Dioxide and Water Vapor Exchange with a Simple Model of Light and Water Use

For the large-scale application of simple, aggregated models, it is important to be able to link the values of model parameters to easily measurable ecosystem characteristics. However, the aggregation of model inputs and outputs over time and space can hamper this linkage. In this paper, two temporal versions of the same simple carbon dioxide (CO₂) and water exchange model, based on the concepts of water- and light-use efficiencies, were used to simulate the half-hourly and daily CO₂ and water exchange of a Douglas fir forest (Pseudotsuga menziesii (Mirb.) Franco) in the Netherlands for 2 years, before and after a thinning. We tested the performance of the models and the interpretability of changes in optimized parameter values, due to the thinning, in terms of ecosystem functioning. The performance of the half-hourly model was satisfactory, whereas the performance of the daily model was high for water exchange but clearly lower for CO₂ exchange. A comparison of the model parameters before and after the thinning showed that the coefficients of the half-hourly model could be separated into more physiologically determined and stand-determined characteristics, but this separation was not clear for the daily model. These results show that if the temporal resolution of the model is high enough, the effects of a major ecosystem manipulation, such as thinning, can be detected and interpreted using eddy flux data and a very simple biophysical model. The model parameters have an unambiguous interpretation and can be inferred from basic ecosystem observables, such as leaf area index (LAI) and aboveground biomass. A sensitivity analysis found strong correlations between parameter sets with similar model performance. For any comparison of the parameter values of different studies, ranges of parameter values and their correlations should be presented rather than one optimized value. Received 2 May 2001; accepted 15 February 2002.     

Combining model structure identification and hybrid modelling for photo-production process predictive simulation and optimisation

Integrating physical knowledge and machine learning is a critical aspect of developing industrially focused digital twins for monitoring, optimisation, and design of microalgal and cyanobacterial photo-production processes. However, identifying the correct model structure to quantify the complex biological mechanism poses a severe challenge for the construction of kinetic models, while the lack of data due to the time-consuming experiments greatly impedes applications of most data-driven models. This study proposes the use of an innovative hybrid modelling approach that consists of a simple kinetic model to govern the overall process dynamic trajectory and a data-driven model to estimate mismatch between the kinetic equations and the real process. An advanced automatic model structure identification strategy is adopted to simultaneously identify the most physically probable kinetic model structure and minimum number of data-driven model parameters that can accurately represent multiple data sets over a broad spectrum of process operating conditions. Through this hybrid modelling and automatic structure identification framework, a highly accurate mathematical model was constructed to simulate and optimise an algal lutein production process. Performance of this hybrid model for long-term predictive modelling, optimisation, and online self-calibration is demonstrated and thoroughly discussed, indicating its significant potential for future industrial application.     

Process model comparison and transferability across bioreactor scales and modes of operation for a mammalian cell bioprocess

A Monod kinetic model, logistic equation model, and statistical regression model were developed for a Chinese hamster ovary cell bioprocess operated under three different modes of operation (batch, bolus fed‐batch, and continuous fed‐batch) and grown on two different bioreactor scales (3 L bench‐top and 15 L pilot‐scale). The Monod kinetic model was developed for all modes of operation under study and predicted cell density, glucose glutamine, lactate, and ammonia concentrations well for the bioprocess. However, it was computationally demanding due to the large number of parameters necessary to produce a good model fit. The transferability of the Monod kinetic model structure and parameter set across bioreactor scales and modes of operation was investigated and a parameter sensitivity analysis performed. The experimentally determined parameters had the greatest influence on model performance. They changed with scale and mode of operation, but were easily calculated. The remaining parameters, which were fitted using a differential evolutionary algorithm, were not as crucial. Logistic equation and statistical regression models were investigated as alternatives to the Monod kinetic model. They were less computationally intensive to develop due to the absence of a large parameter set. However, modeling of the nutrient and metabolite concentrations proved to be troublesome due to the logistic equation model structure and the inability of both models to incorporate a feed. The complexity, computational load, and effort required for model development has to be balanced with the necessary level of model sophistication when choosing which model type to develop for a particular application. © 2012 American Institute of Chemical Engineers Biotechnol. Prog., 2013