Goal-directed approach

The two examples above show that the structure of a problem determines what type of search to use. In the first example, there is only a limited number of components which could be broken, and a large number of possible symptoms. A data-driven approach to this problem would be to ask the scientist for all the symptoms, some of which may require disassembling the HPLC to determine. The problem, therefore, demands a goal-directed approach. 

In the second example, the scientist began with a set of facts and was looking for all possible conclusions. The goal-directed approach to this problem would be to attempt to prove whether each one of the millions of compounds reported in the chemical literature could be responsible for the observed spectrum. Again, the structure of the problem determines the structure of the expert system. 

MALPAS and the Spark Examiner were used to perform SCA. A four-stage Goal Directed approach was developed ... 

The development of injectable mictocapsules for deUvery of chemotherapy agents remains another active area of research. The ultimate goal is to achieve targeted deUvery of chemotherapy agents to specific sites in the body, ideaUy by injection of dmg-loaded mictocapsules that would seek out and destroy diseased ceUs. Intra-arterial infusion chemotherapy is a direct approach to targeted deUvery. The clinical appHcations of microspheres and mictocapsules in embolization and chemotherapy have been assessed (49) (see Chemotherapeutics, anticancer). 

Advocates of the global approach would argue that human activities are essentially goal-directed (the cognitive view expressed in Chapter 2), and that this cannot be captured by a simple decomposition of a task into its elements. They also state that if an intention is correct (on the basis of an appropriate diagnosis of a situation), then errors of omission in skill-based actions are imlikely, because feedback will constantly provide a comparison between the expected and actual results of the task. From this perspective, the focus would be on the reliability of the cognitive rather than the action elements of the task. 

An important overall approach for treatment of sepsis is goal-directed therapy. Mortality can be reduced by early placement and use of a central venous catheter, increased fluid volume administration, dobutamine therapy if needed, and red blood cell transfusion, to achieve specific physiologic goals in the first 6 hours. Evidence-based treatment recommendations for sepsis and septic shock from the Surviving Sepsis campaign are presented in Table 45-3. 

Many factors and considerations are germane to future research in this area. On the technical side, achieving cluster size selection stands as one of the most important and sought-after goals. It would be most desirable to achieve this while maintaining sufficiently high densities for studies of photoinitiated reactions to be carried out with product state resolution and/or ultrafast time resolution. The two methods that, in our opinion, are most viable are molecular beam deflection, as pioneered by Buck (1994) and coworkers, and laser-based double-resonance methods. Less direct approaches are deemed inferior. 

The ultimate goal of all researchers in this area has been to relate precisely the macroscopic manifestations of protein functionality in its utilization with its molecular properties. Great progress recently has been made in relating particular molecular structure to enzymatic activity. However, in the area of food functionality, the advance has been less rapid. The obvious difficulties are attributable to the mixed nature of food systems. The macroscopic manifestation in these products is usually the result of many interactions between different proteins and between these and nonprotein components. The multiplicity of the reactions under the conditions of food preparation or processing bears little resemblance to the clean-cut, precise reactions of pure proteins in solution. All extrapolations from the latter to the former have met with little success. In absence of this direct approach, we have resorted to various indirect approaches. 

The NH3 can then be further converted into nitrate or nitrite or directly used in the synthesis of amino acids and other essential compounds. This reaction takes place at 0.8 atm N2 pressure and ambient temperatures in Rhizobium bacteria in nodules on the roots of legumes such as peas and beans, as well as in other independent bacteria. In contrast to these mild conditions, industrial synthesis of ammonia requires high temperatures and pressures with iron oxide catalysts, and even then yields only 15% to 20% conversion of the nitrogen to ammonia. Intensive efforts to determine the bacterial mechanism and to improve the efficiency of the industrial process have so far been only moderately successful the goal of approaching enzymatic efficiency on an industrial scale is still only a goal. 

It should be remarked that both, the long-term goals and the principal approach of IMPROVE [343], were not changed within the whole project period, i.e. - if also counting preliminary phases of the project - within a duration of 11 years. This stability of goals and approach shows that we have addressed a fundamental and hard problem which cannot be solved in a short period. It, furthermore, shows that the undertaken approach went in the right direction. Therefore, it was not necessary to revise the approach within the whole project period, neither in total nor in essential parts. 

Protein structure prediction [253,254] is one of the major goals of computational molecular biology. Up to now, homology based and threading methods have been the most successful [185,226,255-264]. However, due to the increasing ratio of the number of known protein sequences to the number of solved protein structures, the development of de novo (or related) methods would be extremely valuable. To date, only limited, nevertheless encouraging, progress has been achieved in such direct approaches [42,254]. Purely de novo predictions are now possible only for peptides... 

SAR has a brilliant future due to its capacity to build on itself by knowledge feedback. There are many different players in the field with personalized methods and mindsets. There will be many more and the variety of approaches will increase with time, as the need to tackle problems of increasing complexity will demand. However diverse the method, the objective remains the same for all, mechanistic insight. This alone guarantees than all approaches, however different, will have a common goal directed vector. 

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