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D-p-hydroxyphenylglycine (D-HPG) is an important intermediate for the synthesis of sweeteners and drugs. An innovative continuous chromatographic process was developed to recover D-HPG from crystallization mother liquor, with the aim of reducing the process cost and improving the quality of D-HPG. The thickening properties of different nanofiltration membranes on mother liquor were investigated by pre-treatment test, and the Applexion NF200 nanofiltration membrane was selected to enrich D-HPG. The separation properties of different resins were analyzed by single column experiment, and the separation degree of Applexion XA945 resin to D-HPG and ammonium sulfate could reach 16. Based on the results, the way of sequential simulated moving bed separation was further studied. The results showed that after separation by the sequential simulated moving bed, the average purity of D-HPG in feeding was increased from 42.2% to 96.3%, and the average yield was 91%. The continuous chromatographic system is a promising method for the recovery of D-HPG from crystallization mother liquor. Compared with the traditional process, the new process not only ensures the total yield of D-HPG, but also greatly reduces the process cost and improves the product quality.

To apply anti-marine biofouling agents in the fields of marine engineering and ships, not only the antifouling effectiveness, but also their impact on the corrosion safety of engineering structural materials should be seriously considered and evaluated. Effects of the addition of an agent that would be applied to the anti-marine biofouling of the ship’s sea-access structure on the corrosion behavior and rate of two representative ship metal structural materials, TA24 titanium alloy and 907A alloy steel, in seawater environment were studied. From the comprehensive analysis and evaluation of corrosion morphology, weight loss rate, open circuit potential, polarization curve and alternating-current impedance, it could be obtained that the agent had little effect on the corrosion behavior of these two materials and would not accelerate the corrosion significantly.

A closed gas-up reactor was selected for self-cultured Chlorella pyrenoidosa, the ventilation of carbon dioxide from carbon source obtained by univariate optimization was 2%, and the sodium nitrate of nitrogen source was 10 g/L. More suitable medium components were obtained through the uniform design of Chlorella pyrenoidosa culture medium: K2HPO4 of 0.6 g/L, MgSO4 of 0.2 g/L, NaNO3 of 11 g/L, K2SO4 of 0.8 g/L, ammonium ferric citrate of 0.006 g/L, CaCl2 of 0.05 g/L, vitaminB1 of 0.11 g/L, EDTANa2 of 0.01 g/L, Na2WO4 of 0.08×10–3 g/L, NiCl2 of 0.02×10–3 g/L; In the experiment, a suitable light source with intermediate white light and surrounding colored light was used, and the oxygen was maintained at about 20% with an oxygen scavenger, under which 8.648 g/L dry cell was obtained finally. The protein content of Chlorella pyrenoidosa is as high as 58 g/100 g, and the amino acid and mineral elements of Chlorella pyrenoidosa is also rich by analysis. We studied the replacement of wormwood powder with Chlorella pyrenoidosa, and produced Chlorella pyrenoidosa qingtuan.

The quality of molten iron not only has a significant impact on the strength, toughness, smelting cost and service life of cast iron but also directly affects the satisfaction of users. The establishment of timely and accurate blast furnace molten iron quality prediction models is of great significance for the improvement of the production efficiency of blast furnace. In this paper, Si, S and P content in molten iron is taken as the important index to measure the quality of molten iron, and the 989 sets of production data from a No.1 blast furnace from August to October 2020 are selected as the experimental data source, predicting the quality of molten iron by the I-GWO-CNN-BiLSTM model. First of all, on the basis of the traditional data processing method, the missing data values are classified into correlation data, temporal data, periodic data and manual input data, and random forest, the Lagrangian interpolation method, the KNN algorithm and the SVD algorithm are used to complete them, so as to obtain a more practical data set. Secondly, CNN and BiLSTM models are integrated and I-GWO optimized hyperparameters are used to form the I-GWO-CNN-BiLSTM model, which is used to predict Si, S and P content in molten iron. Then, it is concluded that using the I-GWO-CNN-BiLSTM model to predict the molten iron quality can obtain high prediction accuracy, which can provide data support for the regulation of blast furnace parameters. Finally, the MCMC algorithm is used to analyze the influence of the input variables on the Si, S and P content in molten iron, which helps the steel staff control the quality of molten iron in a timely manner, which is conducive to the smooth running of blast furnace production. [ABSTRACT FROM AUTHOR]

Blast furnace ironmaking plays an important role in modern industry and the development of the economy. A reasonable ingredient scheme is crucial for energy efficiency and emission reduction in blast furnace production. Determining the right blast furnace ingredients is a complicated process; therefore, this study examines the optimization of the ingredient ratio. In this paper a model of the blast furnace ingredients is established by considering cost of per ton iron, CO2 emissions, and the theoretical coke ratio as the objective functions; ingredient parameters, process parameters, main and by-product parameters as variables; and the blast furnace smelting theory and equilibrium equation as constraints. Then, the model is solved by using an improved grey wolf optimization algorithm and an improved multi-objective grey wolf optimization algorithm. Using the data collected from the steel mill, the conclusion is that multi-objective optimization can consider the indexes of each target, so that the values of all the targets are excellent; we also compared the multi-objective solution results with the original production scheme of the steel mill, and we found that using the blast furnace ingredient scheme optimized in this study can reduce the cost of iron per ton, CO2 emissions per ton, and the theoretical coke ratio in blast furnace production by 350 CNY/t, 1000 kg/t, and 20 kg/t, respectively, compared with the original production plan. Thus, steel mill decision makers can choose the blast furnace ingredients according to different business strategies and the actual needs of steel mills can be better met. [ABSTRACT FROM AUTHOR]

Minamata disease (MD) is a form of intoxication involving the central nervous system and is caused by ingesting seafood from methylmercury-contaminated areas in Japan. In MD, cerebellar ataxia is a cardinal feature observed in approximately 80% of MD patients. Although cerebellar transcranial magnetic stimulation (TMS) has recently been used for treating cerebellar ataxia, the optimal stimulation conditions remain unclear. Here, we report the first case of cerebellar ataxia in an MD patient that was significantly improved after high-frequency cerebellar TMS. To determine the optimal stimulation conditions, we examined the excitability of the primary motor cortex (M1) using resting-state functional magnetic resonance imaging (rs-fMRI). rs-fMRI revealed M1 hyperconnectivity, which was indicative of activation of the dentato-thalamo-cortical (DTC) pathway. Thus, high-frequency cerebellar TMS was applied to inhibit the DTC pathway. Improvement of cerebellar ataxia was only observed after real TMS, not sham stimulation. As this effect was consistent with inhibition of hyperconnectivity of M1, the effectiveness of high-frequency cerebellar TMS for cerebellar ataxia was thought to be caused by inhibition of the DTC pathway. Therefore, we suggest that the evaluation of M1 excitability using rs-fMRI can be effective for determining the optimal TMS stimulation conditions for cerebellar ataxia.

According to the technological process of extracting rare earth in Bao Tou Mine, the content of total rare earth ranges from x%-xx%. The national standard of the oxalate gravimetric method is applied to detecting high content of rare earth, which yields between 20% and 80%, but the operation of the method separating interference elements is complex. In fact, Inductively Coupled Plasma-Atomic Emission Spectrometry (ICP-AES) could quickly determine each rare earth element content, and avoid complicated separating steps. However, it was difficult to obtain accurate results by ICP-AES, as a consequence of unfavourable precision for high contents rare earth. The method of alkali fusion combined with ICP-AES was applied to overcome problems of complex components and difficult decomposition in acid for rare earth ores from Bao Tou Mine and is reported herein. The sample was melted by sodium hydroxide and sodium peroxide, and leached with deionized water, in order to transfer all kinds of elements into solution as forms of ions or hydroxide. The interference of elements in the solution was reduced by filtering aluminum, silicon, phosphorus, and a mass of sodium ion. During determination of rare earth contents with ICP-AES, the instrument stability and matrix effect were adjusted by adding an internal standard with scandium. When rare earth content in the sample was 2%, RSD was less than 1.2%. When rare earth content in the sample was between 30% and 50%, the method was successfully used with RSD < 0.7%. The recoveries were in the range of 98.0%-103.3%. The method is simpler than the national standard. Compared with ICP-AES reported in the literatur, the precision of the method was significantly improved. Rare earth content in Bao Tou Mine between 2%-50% was quickly and accurately measured using this method.

The element Al is determined frequently in rare earth ore since Al is a common impurity element in this ore. At present, the Inductively Coupled Plasma-Atomic Emission Spectrometric (ICP-AES) method, which has certain requirements of the Al blank and the matrix concentration, is used to determine the content of Al in ore with a matrix matching calibration. Because Al has complicated patterns in many kinds of rare earth ores, it is difficult to dissolve Al completely into solution for determination by a routine acid-leaching method. In this paper, a new method is described, whereby the sample is digested by alkali fusion and the filtrate acidulated before the content Al in rare earth ore is determined by ICP-AES. The effect of spectrum interferences of REEs and Th on the Al was studied. The detection limit was reduced effectively by eliminating the interferences of coexisting elements. The matrix correction mode was undertaken to eliminate the salt influence. The determination limit of the method was from 0.021 mg/g to 0.035 mg/g and the determination content range was from 0.50 % to 8.00%. The RSD was less than 7.1%. The result of the samples with the presented method is consistent with the volumetric method. The method is fast with a wide measuring range and extremely high precision.