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Accurate quantitative 13C NMR spectra can be accelerated by using EXACT (EXtended ACquisition Time) NMR methods which reduce Nuclear Overhauser Enhancement (NOE) during the FID. This allows 30–50% shorter experiment times to be used when achieving a given level of quantitative accuracy. [ABSTRACT FROM AUTHOR]

In this article we define the role of innovation in the economy of knowledge and in providing social and economic wellbeing to the population. The innovation resistance is defined as a complex phenomenon and as a result of agent-object relationships. Then the article is focused on consumer innovation resistance as a main obstacle to development of knowledge-based economy. Two types of consumer innovation resistance are revealed. The source of active consumer innovation resistance is the result of non-compliance of consumer expectations and characteristics of a new product. Passive consumer innovation resistance comes from the lack of desire to change stable behavior patterns and from unwillingness to learn. Also we classify the deterministic factors of consumer innovation resistance as exogenous indirect and direct factors and as endogenous factors, what can help to work out a general approach to overcoming the innovation resistance. Innovations can be considered as habits and routines to changes, which can be developed and distributed both to the young population and to the elderly. Some insights in this direction are offered.

There are many different types of economic systems used through the world. The government attempts to control and regulate economic branches of strategic importance. Property is a fundamental element of economic power, it is a basis required to fulfill the state functions and tasks, to provide society with vital benefits such as health care, education, high living standard, life quality and well-being of citizens. A major part of production of public goods is carried out by the public sector of the country. Stateowned corporations in Russia are relatively new business structures. They have a market leading position to deal with global economic and social problems of the state.

NMR spectroscopy is a particularly informative method for studying protein structures and dynamics in solution; however, it is also one of the most time‐consuming. Modern approaches to biomolecular NMR spectroscopy are based on lengthy multidimensional experiments, the duration of which grows exponentially with the number of dimensions. The experimental time may even be several days in the case of 3D and 4D spectra. Moreover, the experiment often has to be repeated under several different conditions, for example, to measure the temperature‐dependent effects in a spectrum (temperature coefficients (TCs)). Herein, a new approach that involves joint sampling of indirect evolution times and temperature is proposed. This allows TCs to be measured through 3D spectra in even less time than that needed to acquire a single spectrum by using the conventional approach. Two signal processing methods that are complementary, in terms of sensitivity and resolution, 1) dividing data into overlapping subsets followed by compressed sensing reconstruction, and 2) treating the complete data set with a variant of the Radon transform, are proposed. The temperature‐swept 3D HNCO spectra of two intrinsically disordered proteins, osteopontin and CD44 cytoplasmic tail, show that this new approach makes it possible to determine TCs and their non‐linearities effectively. Non‐linearities, which indicate the presence of a compact state, are particularly interesting. The complete package of data acquisition and processing software for this new approach are provided. [ABSTRACT FROM AUTHOR]

Pure-shift NMR enhances spectral resolution, but the optimal resolution can only be obtained at the cost of acquisition time. We propose to accelerate pure-shift acquisition using optimised ‘burst’ non-uniform sampling schemes [I. E. Ndukwe, A. Shchukina, K. Kazimierczuk and C. P. Butts, Chem. Commun., 2016, 52, 12769] and then reconstruct the undersampled signal mathematically. Here, we focus on the reliability of this reconstruction depending on the sampling scheme and present a workflow for the sampling optimization. It is ready to be implemented in routine measurements and yields a great improvement in reconstruction of challenging cases. [ABSTRACT FROM AUTHOR]

NMR spectroscopy, used routinely for structure elucidation, has also become a widely applied tool for process and reaction monitoring. However, the most informative of NMR methods—correlation experiments—are often useless in this kind of applications. The traditional sampling of a multidimensional FID is usually time‐consuming, and thus, the reaction‐monitoring toolbox was practically limited to 1D experiments (with rare exceptions, e.g., single‐scan or fast‐sampling experiments). Recently, the technique of time‐resolved non‐uniform sampling (TR‐NUS) has been proposed, which allows to use standard multidimensional pulse sequences preserving the temporal resolution close to that achievable in 1D experiments. However, the method existed only as a prototype and did not allow on‐the‐fly processing during the reaction. In this paper, we introduce TReNDS: free, user‐friendly software kit for acquisition and processing of TR‐NUS data. The program works on Bruker, Agilent, and Magritek spectrometers, allowing to carry out up to four experiments with interleaved TR‐NUS. The performance of the program is demonstrated on the example of enzymatic hydrolysis of sucrose. Time‐resolved non‐uniform sampling (TR‐NUS) allows for reaction monitoring using multidimensional experiments. Here, we present TReNDS ‐ the program for convenient setup and processing of TR‐NUS measurement. The software performs spectral reconstruction and analysis including peak‐peaking and tracking. [ABSTRACT FROM AUTHOR]

Accurate quantitative 13 C NMR spectra can be accelerated by using EXACT (EXtended ACquisition Time) NMR methods which reduce Nuclear Overhauser Enhancement (NOE) during the FID. This allows 30-50% shorter experiment times to be used when achieving a given level of quantitative accuracy.

NMR spectroscopy offers unique benefits for ligand binding studies on isotopically labelled target proteins. These benefits include atomic resolution, direct distinction of binding sites and modes, a lowest detectable affinity limit, and function independent setup. Yet, retracing protein signal assignments from apo to holo states to derive exact dissociation constants and chemical shift perturbation amplitudes (for ligand docking and structure-based optimization) requires lengthy titration series of 2D heteronuclear correlation spectra at variable ligand concentration that may exceed the protein's lifetime and available spectrometer time. We present a novel method to overcome this critical limitation, based on non-stationary complementary non-uniform sampling (NOSCO NUS) combined with a robust particle swarm optimization algorithm. We illustrate its potential in two challenging studies with very distinct protein sizes and binding affinities, showing that NOSCO NUS can reduce measurement times by an order of magnitude to make such highly informative NMR titration studies more broadly feasible., (© 2020 Wiley-VCH GmbH.)

Pure-shift NMR enhances spectral resolution, but the optimal resolution can only be obtained at the cost of acquisition time. We propose to accelerate pure-shift acquisition using optimised 'burst' non-uniform sampling schemes [I. E. Ndukwe, A. Shchukina, K. Kazimierczuk and C. P. Butts, Chem. Commun., 2016, 52, 12769] and then reconstruct the undersampled signal mathematically. Here, we focus on the reliability of this reconstruction depending on the sampling scheme and present a workflow for the sampling optimization. It is ready to be implemented in routine measurements and yields a great improvement in reconstruction of challenging cases.