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An increase in moisture content within GIS （gas insulated switchgear） can compromise its insulation integrity. To monitor insulation gas humidity inside GIS， a humidity sensor using dual-cone microfibers is developed. Firstly， utilizing beam propagation method （BPM）， the optical field of the dual-cone microfibers is simulated to investigate their field distribution and mode interference theory. This analysis reveals the correlation between SF6 and moisture content. Subsequently， the fused biconical taper （FBT） is used to fabricate the dual-cone microfiber humidity sensor and conduct humidity sensing experiments. Based on the experimental data， it is determined that the humidity sensor using dual-cone microfibers exhibits a detection sensitivity of -51.75 pm/%RH， enabling continuous online monitoring of humidity levels in electrical equipment.

The effects of mixed culture fermentation with yeast, Lactobacillus bulgaricus and Streptococcus thermophilus on the quality of non-fried instant noodles were studied by rehydration test, texture analysis, electronic nose analysis and scanning electron microscopic (SEM) observation. The results showed that yeast largely affected the rehydration property and texture, while L. bulgaricus and S. thermophilus were mainly responsible for improving the flavor of non-fried instant noodles. The primary fermentation process was conducive to maintaining the cooking tolerance of non-fried instant noodles, while the secondary fermentation process was beneficial to improve the rehydration property and flavor, reducing the rehydration time to 4.0 min; the R(2) and R(7) responses of the rehydrated sample were 2.8 and 2.9, respectively. The SEM results showed that the samples had a uniform pore distribution after the secondary fermentation. Taken collectively, the optimal starter culture for the primary and secondary fermentation was 1.5% yeast + 0.075% L. bulgaricus + 0.075% S. thermophilus.

In clinical practice, early diagnosis, accurate assessment and effective management of rare skin diseases are difficult. The Big Data gives rise to the exponential growth of biomedical data, including medical images, multi-omics information and electronic health records. Artificial intelligence (AI), particularly machine learning, has its advantage in processing complex and abundant information. Researches have applied AI in the field of rare skin diseases. In this paper, we briefly describe, discuss, and foresee the research on AI based image data, multi-omics data & text data and AI in assisting rare skin disease drug development, in order to improve the awareness of dermatologist understanding of this field and actively promote the development of AI usage on rare skin diseases.

In order to solve the problem of underwater in-situ measurement of fuel assembly bending and twisting deformation, an underwater in-situ deformation measurement method of fuel assembly based on line laser 3D vision is proposed. The calibration of single-layer refraction-based underwater camera and plane-constrained optical plane calibration algorithms are used to solve the calibration problem of single measurement unit; ten groups of measurement units based on three-dimensional calibration tooling are quickly calibrated in situ to solve the problem of global coordinate unification of the measurement system and the bending and torsion accuracy of the calibration tooling is measured by laser tracking instrument or the comparative experimental verification of the measurement accuracy. The study shows that the developed underwater n-situ deformation measurement system for fuel assemblies based on line laser 3D vision has an error limit of 0.15° for twist measurement and 0.3 mm for bending measurement, and the whole measurement time is about 1 s, which is better than that of the existing measurement system in terms of the measurement efficiency and measurement error limit. [ABSTRACT FROM AUTHOR]

The biogas fermentation is easy to fail resulting from high sensibility of methanogens to environmental change. So how to ensure the activity of methanogens is the key for anaerobic fermentation stability. A methanogenic microbial inoculant was constructed based on the physiological, biochemical characteristics and antagonisms of strain RY3, SH4, G1, G2 and G3. The performances of the inoculant under different pH values, temperatures and application rates of the methanogenic microbial inoculant were evaluated. It showed that the 5 strains had different physiological and biochemical characteristics as well as complementary roles. There were no antagonisms among 5 strains. The methanogenic microbial inoculant grew at pH value 5.5-10.5. Methane productions were 1 706.7-2 026.7 μmols at pH value 5.5-9.5 after 3 days' culture, that of different pH values showed no significant difference respectively. The results indicated that the methanogenic microbial inoculant is resistant to acid and alkali changes. The inoculant grew at 15-70°C and methane productions were 1 906.9- 2 028 μmols at 30-60°C after 3 days' culture, that of different temperatures treatment showed no significant difference respectively. The results indicated that the methanogenic microbial inoculant is adapted to a wide temperature range. At 20°C, total biogas yield of treatments 2%, 5%, 10% before 14 day were 234, 422 and 950 mL, and the methane concentration of treatments 2%, 5%, 10% on the 14th day were 46.9%, 51.2% and 58.9% respectively corresponding the treatments with 2%, 5% and 10% inoculation dosages of the methanogenic microbial inoculant. At 50°C, total biogas yield before 14 d were 2728, 3291 and 3 832 mL and the methane concentration on 14th day were 62.7%, 63.1% and 63.8% respectively corresponding the treatments with 2%, 5% and 10% inoculation dosages of the methanogenic microbial inoculant. The results indicated that the inoculation could shorten the starting time for methane production compared to the controls without inoculant at 20 and 50°C. Pilot tests by kinetic analysis indicated that inoculant could still shorten the starting time for methane production compared to the control using anaerobic active sludge as inoculant. At 20°C, total biogas and methane yields of 21 day of the treatment with 10% inoculation dosages of the methanogenic microbial inoculant were both 1.6 times of the control group with 10% inoculation dosages of anaerobic active sludge. At 50°C, total biogas and methane yields of 21 d of the treatment with 10% inoculation dosages of the methanogenic microbial inoculant were 2.7 and 2.8 times of control group with 10% inoculation dosages of anaerobic active sludge, respectively. Overall, this study showed that the methanogenic microbial inoculant could significantly improve the efficiency of biogas production at low temperature and high temperature, and it will provide a new technical way for optimal control on biogas fermentation. [ABSTRACT FROM AUTHOR]