Examples of associative algebras for which the T-space of central polynomials is not finitely based
In 1988 (see [7]), S. V. Okhitin proved that for any field k of characteristic zero, the T-space CP(M2(k)) is finitely based, and he raised the question as to whether CP(A) is finitely based for every (unitary) associative algebra A for which 0 ≠ T(A) ⊊ CP(A). V. V. Shchigolev (see [9], 2001) showed that for any field of characteristic zero, every T-space of k0〈X〉 is finitely based, and it follows from this that every T-space of k1〈X〉 is also finitely based. This more than answers Okhitin’s question (in the affirmative) for fields of characteristic zero.For a field of characteristic 2, the infinite-dimensional Grassmann algebras, unitary and nonunitary, are commutative and thus the T-space of central polynomials of each is finitely based.We shall show in the following that if p > 2 and k is an arbitrary field of characteristic p, then neither CP(G0) nor CP(G) is finitely based, thus providing a negative answer to Okhitin’s question.
On the identities of the Grassmann algebras in characteristicp>0
In this note we exhibit bases of the polynomial identities satisfied by the Grassmann algebras over a field of positive characteristic. This allows us to answer the following question of Kemer: Does the infinite dimensional Grassmann algebra with 1, over an infinite fieldK of characteristic 3, satisfy all identities of the algebraM2(K) of all 2×2 matrices overK? We give a negative answer to this question. Further, we show that certain finite dimensional Grassmann algebras do give a positive answer to Kemer's question. All this allows us to obtain some information about the identities satisfied by the algebraM2(K) over an infinite fieldK of positive odd characteristic, and to conjecture bases of theidentities ofM2(K).
Robust solutions of inverse problems in electromagnetic non-destructive evaluation
Non-destructive testing (NDT) is the application of physical measurement technology based on energy interaction with the material and its nonconformities. The material's response is sensed by transducers and sensors which?in most cases?scan the component and document the results in inspection images. However, NDT measures a physically defined quantity or even an intrinsic property. The difference between non-destructive evaluation (NDE) and NDT is in the interpretation of the inspection data. NDE has to discuss the inspection results in terms of quality elements and characteristics which are relevant to describe the fitness of the material for use. In the case of macroscopic defects these are the kind of defect (cracklike, globular) and its size and orientation to the main stress directions; in the case of material property determination the parameters are mainly mechanical properties. Therefore, in NDE one has to solve inverse problems. The solution of inverse problems based on mathematical procedures such as integral equations is a strong developing discipline and most of the articles prepared for this special issue of the journal have the objective of discussing the latest state of the art in that field. However, practical NDE needs robust and quick solutions which are to be applied mainly online. Therefore, we present here inversion procedures based on multiple linear regression algorithms applied to inspection data. We describe the calibration procedure to fit the free parameters of the model functions and give examples of practical applications in industry.