Data types dependent

Note also that we can move between data types depending on the circumstances. In hypertension we might be interested in ... 

Large data sets such as screening data or results obtained by combinatorial experiments are made up of a large number of data records. Hence a data record may represent a chemical reaction or substance, for example its corresponding variables will define the corresponding reaction conditions or biological activities. Depending on the dimensionality or data type of the information, one-, two-, multidimensional, or specific data types can be identified. 

Raw data is almost always incomplete, being highly dependent on the data production platform and often localized to a platform or regional database. Applications (and processes) generate data. However, applications often use proprietary data types and cannot parse data types from other third-party applications. It is important to consider that there are translation issues plus the host of reasons stated below in the requirements for data standards. 

The method used for the safe installation of pressure relief devices is illustrated in Figure 8-1. The first step in the procedure is to specify where relief devices must be installed. Definitive guidelines are available. Second, the appropriate relief device type must be selected. The type depends mostly on the nature of the material relieved and the relief characteristics required. Third, scenarios are developed that describe the various ways in which a relief can occur. The motivation is to determine the material mass flow rate through the relief and the physical state of the material (liquid, vapor, or two phases). Next, data are collected on the relief process, including physical properties of the ejected material, and the relief is sized. Finally, the worst-case scenario is selected and the final relief design is achieved. 

Recently, it has been shown that cell-permeable cerantides dramatically inhibited the synthesis of the two major membrane phospholipids, PC and PE (Bladergroen et al, 1999b Allan, 2000). The inhibition of phospholipid synthesis was rapid, within 2 h, and resulted in massive apoptosis after 16-24 h. The mechanism by which short-chain cerantides exert their effect on phospholipid synthesis is possibly cell type dependent. In baby-hamster kidney (BHK) fibroblasts rc synthesis was reduced at the level of CT, the putative rate-determining enzyme in the CDP-choline pathway (Allan, 2000). This conclusion was based solely on radio-label studies in combination with an earlier published observation (Wieder et al, 1995) showing that C2-SM (the SM generated from C2-ceramide by SM synthase, which was actively synthesized in the BHK-cells) inhibited CT activity in vitro. On the other hand, data obtained from studies with rat-2 fibroblasts clearly showed that short-chain cerantides regulate the synthesis of PC and PE mainly at the final step of the CDP-pathways. This conclusion was based on the following observations (a) incorporation of [ H]-choline into PC and... 

The fragility of the five data types will depend on the specific circumstances of the incident. It is not possible to offer a prescribed priority. In general, historical paper data such as procedures, maintenance records, and drawings are less fragile than people and physical data. The team should identify time-sensitive data as one of its first tasks, prioritize the data, and implement measures to collect or preserve the data. 

In this chapter a number of preprocessing tools are discussed. They are divided into two ba.sic types depending on whether they operate on samples or variables. Sample preproces.sing tools operate on one sample at a time over all variables. Variable preprocessing tools operate on one variable at a time over all samples. Therefore, if a sample is deleted from a data. set, variable preprocessing calculations must be repeated, while the sample preprocessing calculations will not be affected. 

There are three types of data error random error in the reference laboratory values, random error in the optical data, and systematic error in the relationship between the two. The proper approach to data error depends on whether the affected variables are reference values or spectroscopic data. Calibrations are usually performed empirically and are problem specific. In this situation, the question of data error becomes an important issue. However, it is difficult to decide if the spectroscopic error is greater than the reference laboratory method error, or vice versa. The noise of current NIR instrumentation is usually lower than almost anything else in the calibration. The total error of spectroscopic data includes... 

The type of measurement made, and hence the type of data treatment, depends on the requirements of the test. Thus, measurement of the percent response at the molecular level may be important mechanistically and more precisely measured. However, for the assessment of toxicity, measurement of the population response may be more appropriate. 

As mentioned, the aim of the study is to develop desulfurization equipment of industrial interest so understanding its general performance is important. Several sets of typical operation data measured under stable operations are listed in Table 7.5. The comparable data are depending on coal type, S02 content in flue gas ranges from 1400 to 11400 mg/m while the permitted discharge level in China is normally 1200 mg/m3. The data show that the designed equipment exhibits satisfactory global performance and meets the requirements for desulfurization by wet process. Under moderate operation conditions, the content of S02 in the cleaned gas can achieve a much lower level than that permitted. Even if the mole ratio of Ca/S is as low as 1.0, a sulfur-removal efficiency of nearly 90% can be achieved (see the fourth row in Table 7.5) while the pressure drop across the reactor is very small, ca. 400 Pa only. 

Environmental data may be classified according to the level of associated total error as screening data and definitive data. These two data types are also different with respect to their intended use and QC elements. The selection of the type of data to collect depends on the project DQOs and is made in the planning phase. The realm of possible data uses and methods of data collection are the defining factors in the selection. 

Available calculated ab initio quantum-chemical data are not sufficient for a purely ab initio calculation of the rates of all participating processes. Therefore, a model approach is desirable that incorporates the available quantum-chemical data and depends on a small set of physically reasonable parameters. The model must describe the competing processes of adsorption, desorption, chemical transformations, and energy relaxation into the bulk. A possible model of this type will be described below. 

Data uncertainties depend on the type of data being used in the model, such as surrogate data, expert judgement, default data, modelled (extrapolated) data, etc. ... 

A variable in Verilog HDL can either be of the net data type or the register data type. For synthesis, a variable of net type maps to a wire in hardware and a variable of the register type maps either to a wire or a storage element (flip-flop or latch) depending on the context under which the variable is assigned a value. Let us look at a variable of register type in more detail. 

In a Moore finite state machine, the output of the circuit is dependent only on the state of the machine and not on its inputs. This is described i pictorially in Figure 3-5. Since the outputs are dependent only on the j state, a good way to describe a Moore machine is to use an always state- j ment with a case statement. The case statement is used to switch between j the various states and the output logic for each state is described in the appropriate branch. The always statement can have the clock event in its] event list to indicate that it is a clocked always statement. This models the] condition of a finite state machine going from state to state synchronously j on every clock edge. The machine state itself is modeled using a reg vari-] able (a variable of reg data type). 

According to the porosity data of Uchida et al. [102] the matrix of carbon grains (20-40 nm) forms an agglomerated structure with a bimodal psd. Primary pores (micropores, 5-40 nm) exist within agglomerates, between the carbon grains. Larger, secondary pores (macropores, 40-200 nm) form the pore spaces between agglomerates. The relation between the relative pore volume fractions of the two pore types depends on the contents of PFSI and PTFE. Due to their molecular size these components are not able to penetrate micropores. They affect only the macropore volume. The experimental study revealed that an increased PFSI content leads to a decrease of the macropore volume fraction. The opposite effect was found for PTFE. 

The potential benefit of impedance studies of porous GDEs for fuel applications has been stressed in Refs. 141, 142. A detailed combined experimental and theoretical investigation of the impedance response of PEFC was reported in Ref. 143. Going beyond these earlier approaches, which were based entirely on numerical solutions, analytical solutions in relevant ranges of parameters have been presented in Ref. 144 which are convenient for the treatment of experimental data. It was shown, in particular, how impedance spectroscopy could be used to determine electrode parameters as functions of the structure and composition. The percolation-type approximations used in Ref. 144, were, however, incomplete, having the same caveats as those used in Ref. 17. Incorporation of the refined percolation-type dependencies, discussed in the previous section, reveals effects due to varying electrode composition and, thus, provides diagnostic tools for optimization of the catalyst layer structure. 

In Figure 4 the overall polymerization time is plotted as a function of one or the other active species concentration. A hyperbolic type dependence of tp on [active species] is evident, with a very sharp decrease of tp in the concentration range between 0.3 and 0.7 mole %, and a much slower decrease at higher concentrations. At the highest levels of active species concentrations,tp is very low (ca. 3 min) and this value compares rather well with the usual reaction times for the RIM technology. Non-equimolar concentration conditions roughly follow the same pattern, as evidenced from the data quoted in Table V, and allow to underline the prominent role of [I] on tp, whereas [A] has a much lower relevance on it. 

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