Influence of metabolic dysfunction-associated fatty liver disease on the prognosis of patients with HBV-related acute-on-chronic liver failure.

OBJECTIVES: Metabolic-associated fatty liver disease (MAFLD) has clinical relevance in patients with acute-on-chronic liver failure (ACLF). We investigated the association between MAFLD and prognosis in patients with ACLF. METHODS: We included patients with ACLF with available clinical data who visited our hospital for nearly 9 years. We compared the prognosis of patients in the different subgroups of ACLF and predicted the incidence of adverse outcomes. Moreover, a new model based on MAFLD was established. RESULTS: Among 339 participants, 75 had MAFLD. The prognosis of patients with ACLF was significantly correlated with MAFLD. Patients with ACLF with concomitant MAFLD tended to have a lower cumulative survival rate (p = 0.026) and a higher incidence of hepatorenal syndrome (9.33% versus 3.40%, p = 0.033) than those without MAFLD. We developed an TIM2 model and the area under the ROC curve of the new model for 30-day and 60-day mortality (0.759 and 0.748) was higher than other predictive methods. CONCLUSION: The presence of MAFLD in patients with HBV-related ACLF was associated with an increased risk of in-hospital mortality. Moreover, The TIM2 model is a high-performance prognostic score for HBV-related ACLF.

[The calibration of instrument response function during passive FTIR measurement].

In order to obtain infrared spectral radiance distribution of some infrared sources, such as spectral radiant flux density, spectral radiant intensity, spectral radiance and spectral irradiance, the instrument response function under different conditions must be known. In the present paper, the calibration of instrument response function during passive FTIR measurement has been discussed. The experimental results illustrate that under different experimental conditions, the instrument response function varies not only with the temperature of the blackbody but also with the signal amplitude received by the infrared instrument. So, during passive FTIR measurement, the temperature and the emission signal amplitude of the source must be observed carefully in order to get satisfactory instrument response function.

[Automated recognition of VOCs using artificial neural networks].

Quantitative analysis of FTIR spectra, which are seriously overlapped in the spectral bands, was studied by artificial neural networks. The optimum network was chosen by a new criterion, i. e. the degree of approximation. After the network was established, two kinds of spectra were resolved. It was demonstrated that accurate results could be obtained when two components were both included. In addition, the unknown spectrum could be identified and quantified. It was showed that the artificial neural network has excellent non-linear ability of solution. Meanwhile, the method provides an efficient approach to the identification and quantification of the unknown samples.

[Remote passive detection of flame temperature of solid propellant adulterating nanoparticles].

The flame temperature of three kinds of solid propellants was measured by passive remote sensing FTIR with the resolution of 1 cm(-1). These three kinds of solid propellants are adulterate nano-scale metal oxide particles, adulterate normal metal oxide particles, and propellant without any adulterations. The main components of the solid propellant are nitrocellulose and nitroglycerin. The metallic oxides, including 6 nm CuO, 56 nm Fe2O3, 16 nm NiO, and correspondingly the normal particles, were adulterated into the solid propellants respectively. The flame temperature was calculated through the fine structure of the emission fundamental band of H2O at 2.75 microm. The results of the flame temperature of the solid propellants adulterating nano-scale CuO, Fe2O3 and NiO are 3089, 3193 and 3183 K, respectively. The temperatures of the three kinds of solid propellants were compared, and it was shown that there is no obvious difference in the flame temperature among the three kinds of solid propellants.

[Application and improvement of partial-least-squares in Fourier transform infrared spectroscopy].

Partial least squares(PLS) algorithm is an effective chemometric tool. It takes the advantages of multipal linear regression (MLR) and principal component regression (PCR), which makes Fourier transform infrared spectrometry (FTIR) more powerful and useful. Accompanied with increasing use of FTIR, the algorithm is modified and corrected under different circumstances. The applications of PLS to FTIR were mentioned. Improved algorithms were presented, such as moving windows PLS(MWPLS), robust PLS (RPLS), weighted PLS(WPLS), and non-linear PLS. Data pre-processing, selection of variable, noise elimination and non-linear model of PLS were introduced.

[Advances in passive OP-FTIR].

As an OP-FTIR(Open Path FTIR) technology, passive OP-FTIR not only has the advantages of OP-FTIR, but also has the ability to collect data from any direction without prior background information. This technology allows mobile, fast, man-held and stand-off detection of hazardous chemical cloud.The present paper presents some developments of passive OP-FTIR, including high altitude atmospheric pollution detection, auto-detection of toxic cloud, hot gases detection (such as the determination of major combustion products in aircraft exhausts, remote sensing of smoke plumes, and remote sensing of volcano emissions), temperature and combustion products determination (including cloud temperature determination). The present paper also gives the application of passive OP-FTIR in the military. With the development of FTIR and computer science, more and more applications of OP-FTIR to environment supervision, aviation and space flight, engine exhausts, combustion and military will be fulfilled.