Research error avoidance

In defining a human error avoidance program, the Consortiumconstitutes three partners NTNU Social Research, SINTEF and ARGOTEC. The former has been project manager and prime contractor. 

High-level DAE software (e.g., Dassl) makes a time-step selection based on an estimate of the local truncation error, which depends on the difference between a predictor and a corrector step [13,46]. If the difference is too great, the time step is reduced. In the limit of At 0, the predictor is just the initial condition. For the simple linear problem illustrated here, the corrector will always converge to the correct solution y2 = 1, independent of the time step. However, if the initial condition is y2 1, then there is simply no time step for which the predictor and corrector values will be sufficiently close, and the error estimate will always fail. Based on this simple problem, it may seem like a straightforward task to build software that identifies and avoids the problem, and there is current research on the subject [13], The problem is that in highly nonlinear, coupled, problems the inconsistent initial conditions can be extremely difficult to identify and fix in a general way. 

Sample preparation in NLC and NCE is the most important step in analysis due to the nano nature of these modalities. The sampling should be carried out in such a way as to avoid changes in the chemical composition of the sample. The quantitative values of species depend on the strategy adopted in sample preparation. Extraction recoveries may vary from one species to another and they should, consequently, be assessed independently for each compound as well as for the compounds together. Materials with an integral analyte, that is, bound to the matrix in the same way as the unknown, which is preferably labeled (radioactive labeling) would be necessary, which is called method validation. As discussed above few papers described off- and online sample preparation methods on microfluidic devices. Of course, online methods are superior due to lower risk of contamination and error of methods. Not much work been carried out on online nanosample preparation devices, which need more research. Briefly, to get maximum extraction of analytes, sample preparation should be handled very carefully. 

Robust errors result from disrupting basic conditions for measuring, researcher s error, etc. A researcher is asked to check the probability of appearance of a robust error. A robust error appears as a measured value that is drastically different from others. This error may be avoided if another researcher who is ignorant of former measurements repeats it. The same effect may be achieved when the same researcher repeats measurements after some time when he has already forgotten the results the of first ones. Such a result has to be rejected if a robust error has been discovered. 

However, without a sound knowledge of chemistry (viz. the ability to solve the problem without the computer) no PC hardware and its software can help. So why use computers at all The answer is straightforward it avoids trivial errors, looks at all possibilities, excludes biased conclusions, it provides suggestions, complex information retrieved from data collections, which allows the time saved to be spent in streamlining the research. 

In this review, research in the field of van der Waals molecules accomplished by our group in the last few years was summarised. On the basis of the results obtained so far, it appears that the modification of the Roothaan equations to avoid basis set superposition error at the Hartree-Fock level of theory is a promising approach. The fundamental development of the SCF-MI strategy to deal with electron correlation treatments in the framework of the valence bond theory has been described. A compact multistructure and size... 

How can we avoid errors such as those discussed in this chapter All researchers must maintain a calm and peaceful state of mind in order to judge their results correctly. A nonrigorous and too optimistic interpretation of the analytical or biological data is always a dangerous stumbling block. All research leaders must carefully examine the results obtained by their coworkers. Too competitive an atmosphere among coworkers may lead to misconduct. 

GMP is the enforcement of rigorous control of purity and consistency of the production of any substance that is to be administered to a human. It is designed to avoid human error that could lead to contamination of the final product. It does not apply to process research, but does when any process on any scale is used for the preparation of any batch of drug for clinical use. It is the responsibility of the manufacturer, under potential scrutiny from the regulatory authorities, and adds dramatically to the cost of the process, particularly at the small-scale early stages. 

Statistics is not concerned with gross errors. In fact, the science to treat such mistakes has yet to appear. Little can be done, other than learn the lesson and pay more attention next time. Everyone makes mistakes. The conscientious researcher should strive to do everything possible to avoid committing them. 

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