In this work, we have used a combination of vibrational spectroscopy (infrared, Raman and inelastic neutron scattering) and periodic density functional theory to investigate the structure of methanesulfonic acid (MSA) in the liquid and solid states. The spectra clearly show that the hydrogen bonding is much stronger in the solid than the liquid state. The structure of MSA is not known; however, mineral acids typically adopt a chain structure in condensed phases. A periodic density functional theory (CASTEP) calculation based on the linear chain structure found in the closely related molecule trifluoromethanesulfonic acid gave good agreement between the observed and calculated spectra, particularly with regard to the methyl and sulfonate groups. The model accounts for the large widths of the asymmetric S-O stretch modes; however, the external mode region is not well described. Together, these observations suggest that the basic model of four molecules in the primitive unit cell, linked by hydrogen bonding into chains, is correct, but that MSA crystallizes in a different space group than that of trifluoromethanesulfonic acid.

In this work, we have used a combination of vibrational spectroscopy (infrared, Raman and inelastic neutron scattering) and periodic density functional theory to investigate six metal methanesulfonate compounds that exhibit four different modes of complexation of the methanesulfonate ion: ionic, monodentate, bidentate and pentadentate. We found that the transition energies of the modes associated with the methyl group (C–H stretches and deformations, methyl rock and torsion) are essentially independent of the mode of coordination. The SO3 modes in the Raman spectra also show little variation. In the infrared spectra, there is a clear distinction between ionic (i.e. not coordinated) and coordinated forms of the methanesulfonate ion. This is manifested as a splitting of the asymmetric S–O stretch modes of the SO3 moiety. Unfortunately, no further differentiation between the various modes of coordination: unidentate, bidentate etc … is possible with the compounds examined. While it is likely that such a distinction could be made, this will require a much larger dataset of compounds for which both structural and spectroscopic data are available than that available here.

Befitting from the interpretability and the capacity in capturing the underlying manifold structure, diffusion process (DP) has attracted increasing attention in the field of image retrieval. Within it, hierarchical diffusion process (HDP) has achieved satisfactory results in retrieved performance and complexity. However, the existing hierarchical diffusion process methods only diffuse the affinity values in low-level visual space without considering the high-level semantic information, which cause the problem of semantic gap. To overcome these problems, we propose a Graph Regularized Hierarchical Diffusion Process (GRHDP) method with relevance feedback, and apply it to retrieve medical images. The proposed algorithm firstly establishes a hierarchical structure of the images in medical image database and spreads the affinity values among query images and top-layer images by graph regularization diffusion. Then relevance feedback is introduced to adjust the similarity between query images and retrieved images in top layer, and the affinity values are diffused again according to labeled information of feedback. Finally, the similarity between queries and others in database can be obtained by interpolating the diffused results on the top layer from top to bottom. The experimental results show that our proposed GRHDP with relevance feedback has achieved better retrieval performance than manifold ranking and regularized diffusion process (RDP) when returning top retrieved images.

This paper proposed a relative value method for measuring the indicators of cardiac reserve and investigated the application on monitoring and evaluating cardiac function for pregnant women. A heart sound sensor is placed at the precordial region to detect phonocardiogram. In order to access the cardiac reserve mobilization level during pregnancy, the cardiac reserve indicators of 1,683 normal pregnant women, 96 abnormal cases with different obstetric complications and 624 non-pregnant women were measured, analyzed and compared. The result shows that the differences between the indicators of pregnant and non-pregnant women were significant (p < 0.05). The ratio of diastolic to systolic duration (D/S) was obviously declined with the increase of gestational weeks and the occurrence of obstetric complication. This very encouraging result indicates that the D/S can be used as an indicator for evaluating the cardiac safety of parturition, which provides a reference for cardiac safety assessment of pregnant women.

Heart murmur recognition and classification play an important role in the auscultative diagnosis. The method based on hidden markov model (HMM) was presented to recognize the heart murmur. The murmur was isolated on basis of the principle of wavelet analysis considering the time-frequency characteristics of the heart murmur. This method uses Mel frequency cepstral coefficient (MFCC) to extract representative features and develops hidden Markov model (HMM) for signal classification. The result shows that this method is able to recognize the murmur efficiently and superior to BP neural network (94.2% vs 82.8%). And the findings suggest that the method may have the potential to be used to assist doctors for a more objective diagnosis.