Multilocation trials are often used to analyse the adaptability of genotypes in different environments and to find for each environment the genotype that is best adapted; i.e. that is highest yielding in that environment. For this purpose, it is of interest to obtain a reliable estimate of the mean yield of a cultivar in a given environment. This article compares two different statistical estimation procedures for this task: the Additive Main Effects and Multiplicative Interaction (AMMI) analysis and Best Linear Unbiased Prediction (BLUP). A modification of a cross validation procedure commonly used with AMMI is suggested for trials that are laid out as a randomized complete block design. The use of these procedure is exemplified using five faba bean datasets from German registration trails. BLUP was found to outperform AMMI in four of five faba bean datasets. 相似文献
A gas-tight chamber has been constructed to calibrate the 15N isotope dilution method against direct 15N2 measurements. The theoretical basis for such estimates is given, and the practical problems associated with the experiments are discussed. 相似文献
Risk is by no means a simple concept. Natural variability and definitional problems with the concept of probability complicate the measurement and use of risk as an analytical tool. Variability requires that risk assessment methods separate natural from total risk when attempting to estimate anthropogenic risk. Failure to do so results in the over estimation of anthropogenic risk and the eventual loss of credibility for risk assessment methodologies. The common frequentist approach to probability is not consistent with anything but a modelling approach to risk assessment. When combined with its ability to account for natural variability, incorporate laboratory-assay data and offer complete statistical and experimental control, modelling is a promising approach to risk assessment. Modelling, however, is not without its drawbacks. Initialization bias can result in the over, or under, estimation of both natural and anthropogenic risk. Furthermore, model estimates are time dependent. The convergence of natural and anthropogenic risk poses problems for modelling-based risk assessment and requires clear statements as to the importance of the time dimension in risk assessment. When combined, the drawbacks to modelling-based risk assessment argue that risk should never be stated as a scalar quantity. Instead, modelling-based risk assessment should provide estimates of the complete range of risk measures (total, natural, and anthropogenic) as well as indications of convergence time. Only then can the modelling-based approach be viewed as the most appropriate means of carrying out scientifically credible risk assessment. 相似文献
This is the first report on the isolation ofCryptococcus neoformans from pigeon droppings in China and their serotypes.C. neoformans colonies which produced brown colonies on caffeic acid-cornmeal agar were found in Twenty-five out of thirty-six samples of pigeon droppings. Fifty-one colonies randomly picked from the positive samples were identified asC. neoformans by a commercially available kit for carbon source assimilation test and Christensen's urea agar. Forty (78%) out of the 51 strains were serotyped as A and 11 (22%) as AD. At the same time, seventeen out of nineteen clinical isolates were serotyped as A and 2 as B. There are three findings in our results. One is that onlyC. neoformans var.neoformans strains could be isolated from pigeon droppings, although the varietygattii strains were found in the clinical isolates obtained in the same geographic site in China. The second is that serotype A strains were most frequently seen in natural and clinical materials in the southeast part of China, and serotype AD strains were isolated in pigeon droppings but not in clinical materials. The third is that the coexistence of serotype A and AD cells ofC. neoformans strains in same samples of pigeon droppings were observed. 相似文献
1. 1. The writers present the general theory of evaluation that is being developed by their group.
2. 2. The evaluation of a human environment is a complex mental process.
3. 3. In an effort to express numerically the quality of an environment, one tends to oversimplify the complex aspects of it and the entailing problems in relation to its inhabitants.
4. 4. In this paper, some examples are taken in the evaluation of thermal environments, wherein much has been said and done in setting up numerical scales to express human comfort, and yet neither clear-cut explanations nor convincing logic seem to exist to terminate the argument over the widely scattered and sometimes seemingly contradicting experimental data.
5. 5. The writers suggest that many of the reasons for this confusion may be traced back to the oversimplified notion of evaluation.
6. 6. It is shown that there are various possibilities when looking at the scales of evaluation.
7. 7.|The nominal scale, least studied of all the four traditional scales, may be given a prominent place in evaluating a thermal environment. The pseudo-interval order scale is another example.
Author Keywords: evaluation; scales; thermal environment; classification; pseudo-interval order 相似文献
The transition toward a circular economy (CE) is key in decarbonizing the built environment. Despite this, knowledge of—and engagement with—CE philosophies remains limited within the construction industry. Discussion with practitioners reveals this to be contributed to by a lack of clarity regarding CE principles, with numerous organizations recommending implementation of differing and sometimes conflicting principles. In addition, a systematic assessment of how building designs consider CE is made difficult by the multiple design areas required to be considered and the large amount of design data required to do so. The absence of a systematic CE assessment causes a lack of comparability across designs, preventing benchmarking of CE practices in building design at present. This paper details the development of Regenerate, a CE engagement tool for the assessment of new and existing buildings, established in an effort to overcome the aforementioned barriers to the adoption of CE within the construction sector. A CE design workflow for the built environment is proposed, comprising four overarching circularity principles (Design for Adaptability; Design for Deconstructability; Circular Material Selection; Resource Efficiency) and contributing design actions. In addition to engaging stakeholders by enabling the assessment of building designs, the tool retrieves key data for further research. Information on completed design actions as well as recycling and waste metrics is collected to facilitate future CE benchmarking. “Bill of materials” data (i.e., material quantities) is also compiled, with this being key in material stock modeling research and embodied carbon benchmarking. 相似文献