Response hierarchical

Greene, B.A., Allred, D.R., Morishige, D. and Staehelin, L.A. (1988). Hierarchical response of light-harvesting chlorophyll-proteins in a light-sensitive chlorophyll 6-deficient mutant of maize. Plant Physiol. 87, 357-364... 

These unknown hierarchical response levels and the ways they are interconnected are undoubtedly the key when designing the interphase between the components of any organic polymer-based heterogeneous material. It is then obvious that establishing the above mentioned hierarchical range of the interconnection parameters between the macro-, micro-, meso-, and nanoscales is necessary before a great effort in the study for an efficient control of the ultimate properties of the material is made. 

The primal advantage of hierarchical databases is that the relationship between the data at the different levels is easy. The simplicity and efficiency of the data model is a great advantage of the hierarchical DBS. Large data sets (scries of measurements where the data values are dependent on different parameters such as boiling point, temperature, or pressure) could be implemented with an acceptable response time. 

These scientists and engineers represent a special challenge to leadership in that the values and motivations may at times be at odds with corporate cultures that emphasise seniority, authority based on hierarchical influence, allegiance to corporate direction, a strict proprietary view of the results of science and technology, and expectations of instantaneous organisational response to changes in direction. 

The objectives of the inflammatory response can be viewed as a hierarchical ordered panel of events. The most successful consequence of an inflammatory response is the complete restoration of function and structure of the affected tissue, also denoted as resolution. If this is not possible, inflammation aims for healing by repair and replacement of lost tissue by scar tissue. 

This hierarchical list also conveys the notion of a range of system response times and sensitivities, with the atmospheric cases being fast and sensitive to perturbations and the oceans being slowest and least subject to short-term changes. 

Often the demand for such a complement of properties requires a hierarchical strategy in which only the broadest possible limits are satisfied by the less demanding design requirements. For example, topical administration assists in limiting toxicity while improving targeting and pharmacokinetic response. On the other hand, the requirements for effective... 

The potential of modern chemical instrumentation to detect and measure the conposition of coirplex mixtures has made it necessary to consider the use of methods of multivariable data analysis in the overall evaluation of environmental measurements. In a number of instances, the category (chemical class) of the compound that has given rise to a series of signals may be known but the specific entity responsible for a given signal may not be. This is true, for example, for the polychlorinated biphenyls (PCB s) in which the clean-up procedure and use of specific detectors eliminates most possibilities except PCB s. Such hierarchical procedures simplify the problem somewhat but it is still advantageous to apply data reduction methods during the course of the interpretation process. 

SSDs are being routinely used for the display and interpretation of effects data (Parkhurst et al. 1996 Posthuma et al. 2002). An SSD for atrazine (shown in Figure 7.3) displays the typical S-shaped curve associated with many chemical dose-response relationships. Each point on the curve represents an LC50 for a particular species exposed to atrazine under standard toxicity test protocols. The SSD approach uses only a single statistically derived endpoint from each available toxicity test (e.g., the LC50 or EC50). In contrast, all data collected during any specific toxicity test can be used in a hierarchical model. The ability to use all available data to make inferential decisions is a marked improvement over the standard SSD effects distribution. 

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