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In this paper, after analyzing the structural system of the digital resource sharing model in colleges and universities, a shared storage model based on cloud storage is designed, and a digital teaching resource management and sharing platform for colleges and universities based on cloud storage is constructed on this basis. In order to realize accurate sharing, the sharing behaviors of teaching resources are symbolically illustrated, double behavior aggregation is performed, and a multidimensional preference personalized recommendation algorithm, i.e., DB-CGAT model, is designed to construct the personalized sharing module of teaching resources that integrates the behavioral graph. In addition, three types of experiments are conducted on the personalized sharing module of the platform to test its sharing performance and overall performance. The results show that the accuracy of this model is reduced by 0.04 compared with the traditional algorithm; the 90 percent time of login transaction is 2.44, and the time of query transaction is 1.46, which is all up to the standard value. All the action actions are green, and the number of clicks and throughputs in 5~30ss are around 120. Universities can benefit from the digital teaching resource management and sharing platform designed in this paper, which can improve teaching efficiency.

During the operation of the reactor, a large amount of tritium is released into the surrounding air through the waste gas treatment system and the plant ventilation system. Tritium is very easy to replace hydrogen in water molecules, and can enter the human body through breathing, resulting in internal radiation hazards. Therefore, it is necessary to study the measurement of tritium in ambient air. At present, there is no national or industrial standard for the measurement of tritium in air. In this paper, the liquid scintillation counter was used to measure the activity concentration of tritium in air. It is found that the detection limit of the activity concentration of tritium in the air mainly depends on ambient temperature, relative humidity, sample amount, detection efficiency of the instrument, background count rate of the instrument, measurement time, etc. Among them, ambient temperature and relative humidity are inherent characteristics of air samples. Therefore, in order to reduce the detection limit and shorten the measurement time as much as possible, three aspects must be considered which is reducing the background count rate, improving the detection efficiency and increasing the sample volume. Possible approaches include selecting background water and scintillation fluid with the lowest possible counts, selecting the appropriate counting area, and optimizing the mixing ratio of sample and scintillation fluid. In order to reduce the effect of water and scintillation fluid on the background, 11 different sources of background water and 3 types of scintillation fluid were selected for testing. The samples were prepared according to the ratio of 8 mL of water to 12 mL of scintillation fluid, and the long-term counting measurement was carried out after being stored in the dark for 24 h. The measurement results show that the count rate range of the background water sample varies from 2.373 min-1 to 3.441 min-1, and the difference between the maximum value and the minimum value is 1.068 min-1, which also shows that the selection of the background water sample is very critical. For three scintillation fluids including Gold Star Quanta, OtpiPhase HiSafe 3 and UItima Gold LLT, there is no significant difference in background and detection efficiency.In order to further reduce the detection limit, a figure of merit (FOM) was introduced, which is the ratio of the square of the detection efficiency of the radionuclide of interest to the background count rate. To maximize FOM, it is necessary to reduce the sample background count rate while maintaining a high detection efficiency, which can be achieved by optimizing the count area. By changing the lower threshold (LL) and upper threshold (UL) of the pulse height discriminator, a series of counted regions and the corresponding FOM can be obtained. The optimal count interval is 0.35-4.35 keV, which maximizes FOM. For full spectrum counting, the sample detection efficiency is 29.27% and the background counting rate is 6.53 min-1, from which the FOM is calculated to be 131.2. After optimizing the counting area, although the detection efficiency is only 25.62%, the background is only 2.42 min-1, and the FOM reaches 271.2. The optimization of the counting interval reduces the detection efficiency from 29.27% to 25.62%, a decrease of 12.47%. But there is an even bigger reduction in background, at 170%. In terms of optimizing the combination of water and scintillation fluid, samples were prepared and measured with water contents of 35%, 40%, 45%, 50%, and 55%, respectively. The comparison results show that when the water content is 40% and 45%, the quality factor of the measurement system reaches the maximum, and the detection limit reaches the minimum. Tritium in air was measured under optimized conditions. The detection limit of typical samples is 20 mBq/m3, and the measurement time is 16 h, which is 1/2 shorter than that of full spectrum counting.

The effects of different preparation techniques (aqueous enzymatic extraction, aqueous extraction, cold pressing, hot pressing and organic solvent extraction) on the physical and chemical properties, nutritional components and oxidation stability of tiger nut oil from the cultivar ‘Zhongyousha 1’ grown in Xinjiang were investigated. The results showed that organic solvent extraction gave the highest extraction rate (88.31%), and there were significant differences in the physicochemical properties of tiger nut oils prepared by different processes (P < 0.05). Oleic acid accounted for 76.04% of the total fatty acids in the oil prepared by aqueous extraction, which was 1.72–2.34 percentage points higher than that obtained with other preparation processes (P < 0.05). Different preparation techniques had significant effects on the lipid concomitant content and oxidation stability of tiger nut oil (P < 0.05). The oil obtained by organic solvent extraction had the highest contents of tocopherol (370.67 mg/kg), total phenol (168.59 mg/100 g) and phytosterol (271.26 mg/100 g), while the content of squalene was highest (162.04 mg/kg) in the oil obtained by aqueous extraction. The cold pressed oil had the highest oxidation stability index (24.15 h) indicating good oxidation stability. Correlation analysis indicated that the oxidation stability of tiger nut oil was positively correlated with unsaturated fatty acid and oleic acid (r = 0.72, r = 0.48), and the antioxidant capacity (1,1-diphenyl-2-picrylhydrazyl and 2,2’-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) free radical scavenging rate) of polar components was significantly positively correlated with total phenol content (r = 0.91, r = 0.96, P < 0.05). The results of principal component analysis (PCA) revealed that the cold pressed oil was similar to the oil obtained aqueous enzymatic extraction, while the oils prepared by organic solvent extraction, hot pressing and aqueous extraction were differentiated well. These results can provide a theoretical basis for the development of high-quality tiger nut oil.