Search Results (4)

This study aimed to analyze the structural requirements for di- and tripeptides exhibiting a DPP IV-inhibitory effect. The sequences of 46 di- and 33 tripeptides, including their bioactivity (IC₅₀; μM), were implemented from the BIOPEP-UWM database, whereas modeling was performed using SCIGRESS Explorer: Version FJ 3.5.1 software. Models included 336 (dipeptide dataset) and 184 descriptors (tripeptide dataset). The values of the determination coefficient (R²) defining model reliability were 0.782 and 0.829 for di- and tripeptides, respectively. Based on the implemented descriptors, it was concluded that increased numbers of nitrogen atoms, as well as the methyl groups, are required for dipeptides to enhance the DPP IV-inhibitory effect. This was indicated by the presence of amino acids with an aliphatic side chain (e.g., Leu, Val, Ile) and an aromatic ring (Trp). In the case of tripeptides, a correlation was found between their molecular weight (MW) and studied bioactivity. A tripeptide with a molecular weight of up to 500 Da was found suitable for the sequence to act as the DPP IV inhibitor. Although there is still a gap in explaining the relations between the structural nature and the DPP IV-inhibitory activity of peptides, and certain issues related to this topic still remain unknown, the results are in line with those reported by other authors. Additionally, the suitability of the SCIGRESS tool in the QSAR analysis of peptides derived from foods can be confirmed. Interpretable descriptors enabled the achievement of more unequivocal results concerning the main structural factors affecting the DPP IV inhibition of di- and tripeptides. Full article

The widespread application of screen content images (SCIs) has met the needs of remote display and online working. It is a topic that is challenging and worthwhile discussing in research on quality assessment for SCIs. However, existing methods focus on extracting artificial features to predict image quality, which are subjective and incomplete, or lack good interpretability. To overcome these problems, we propose an effective quality assessment method for SCIs based on human visual perceptual characteristics. The proposed method simulates the multi-channel working mechanism of the human visual system (HVS) through pyramid decomposition and the information extraction process of brains with the help of dictionary learning and sparse coding. The input SCIs are first decomposed at multiple scales, and then dictionary learning and sparse coding are applied to the images at each scale. Furthermore, the sparse representation results are analyzed from multiple perspectives. First, a pooling scheme about generalized Gaussian distribution and log-normal distribution is designed to describe the sparse coefficients with and without zero values, respectively. Then the sparse coefficients are used to characterize the energy characteristics. Additionally, the probability of each atom is calculated to describe the statistical property of SCIs. Since the above process only deals with brightness, color-related features are also added to make the model more general and robust. Experimental results on three public SCI databases show that the proposed method can achieve better performance than existing methods. Full article

Three-times ionized xenon Xe IV spectrum in the 1070–6400 Å region was analyzed using a pulsed discharge light source. A set of 163 transitions was classified for the first time, and 36 new energy levels belonging to the 5s²5p²6d and 5s²5p²7s even configurations were determined. The relativistic Hartree–Fock method, including core-polarization effects, were used. In these calculations, the electrostatic parameters were optimized by a least-square procedure in order to improve the adjustment to experimental energy levels. We also present a calculation based on a relativistic multiconfigurational Dirac–Fock approach. Full article

Orthogonal operators can successfully be used to calculate eigenvalues and eigenvector compositions in complex spectra. Orthogonality ensures least correlation between the operators and thereby more stability in the fit, even for small interactions. The resulting eigenvectors are used to transform the pure transition matrix into realistic intermediate coupling transition probabilities. Calculated transition probabilities for close lying levels illustrate the power of the complete orthogonal operator approach. Full article