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The aim of the study is to interpret the effects of air‐impingement jet drying (AIJD) on drying kinetics, color, polyphenols, and antioxidation ability of Boletus aereus slices. Page model was most suitable for expressing and predicting AIJD curves of B. aereus slices. The moisture‐effective diffusion coefficient of AIJD ranged from 7.8876 × 10−10 to 2.1426 × 10−9 m2/s, and AIJD also showed high efficiency due to its low activation energy (45.37 kJ/mol). AIJD is better for B. aereus slices than hot air drying (HAD) in accelerating the drying rate (DR) and shortening drying time, and maintaining color. p‐hydroxybenzoic acid, protocatechuic acid, and rutin were identified in B. aereus slices by ultra high‐performance liquid chromatography coupled with triple quadrupole mass spectrometry (UHPLC‐QqQ‐MS). Total polyphenols, flavanone, phenolic acids, and antioxidant activities were significantly lower in dried B. aereus slices than those in fresh B. aereus slices. In AIJD, drying temperature had the greatest effect on the quality of B. aereus slices, and AIJD at 50 °C is the optimum drying condition for B. aereus slices. Practical Application Boletus aereus occurs in many countries all over the world. In this paper, the effect of AIJD on color, polyphenols, and antioxidation ability in B. aereus slices and its drying kinetics were studied. AIJD is an efficient drying method for B. aereus by decreasing its drying time, increasing DR, and protecting the color of B. aereus. These findings have provided important reference basis for people to have a better understanding of AIJD method, which was used to dry B. aereus. This study also provides a new technique for drying B. aereus, which could improve dry efficiency and reduce drying cost.

Purpose This study aimed to translate the English version of the Action Research Arm Test (ARAT) into Chinese and to evaluate the initial validation of the Chinese version (C-ARAT) in patients with a first stroke. Methods An expert group translated the original ARAT from English into Chinese using a forward-backward procedure. Forty-four patients (36 men and 8 women) aged 22–80 years with a first stroke were enrolled in this study. The participants were evaluated using 3 stroke-specific outcome measures: C-ARAT, the upper extremity section of the Fugl–Meyer assessment (UE-FMA), and the Wolf Motor Function Test (WMFT). Internal consistency was analysed using Cronbach's α coefficients and item-scale correlations. Concurrent validity was determined using Spearman's rank correlation coefficients. Floor and ceiling effects were considered to be present when more than 20% of patients fell outside the preliminarily set lower or upper boundary, respectively. Results The C-ARAT items yielded excellent internal consistency, with a Cronbach's α of 0.98 (p < 0.001) and item-total correlations ranging from 0.727 to 0.948 (p < 0.001). The C-ARAT exhibited good-to-excellent correlations with the UE-FMA and WMFT functional ability (WMFT-FA) scores, with respective ρ values of 0.824 and 0.852 (p < 0.001), and an excellent negative correlation with the WMFT performance time (WMFT-time), with a ρ value of -0.940 (p < 0.001). The C-ARAT subscales generally exhibited good-to-excellent correlations with stroke-specific assessments, with ρ values ranging from 0.773 to 0.927 (p < 0.001). However, the gross subscale exhibited moderate-to-good correlations with the UE-FMA and WMFT-FA scores, with respective ρ values of 0.665 and 0.720 (p < 0.001). No significant floor effect was observed, and a significant ceiling effect was observed only on the WMFT-time. Conclusions The C-ARAT demonstrated excellent internal consistency and good-to-excellent concurrent validity. This test could be used to evaluate upper extremity function in stroke patients without cognitive impairment.

To avoid the limitation of conventional vehicle magnetorheological (MR) suspension, a variable damping and inertia device is applied in the vehicle suspension with MR technology. A semi-active adaptive MR inerter (AMRI) is discussed. A quarter car suspension model with an AMRI installed in parallel with a double-ended MR damper (D-MRD) is considered. First, the vehicle suspension with variable damping and inertia is analyzed. The prototype of D-MRD and MR variable inertia flywheel (MRVIF) are fabricated and tested respectively. Then, the control model of D-MRD and MRVIF is developed on the basis of test data. An improved Fuzzy PID controller for the semi-active suspension with D-MRD and AMRI is formulated. Numerical simulation is investigated to validate the proposed variable damping and inertia device. The results demonstrate that the performance of the semi-active suspension with D-MRD and AMRI can achieve much better ride comfort than the semi-active suspension with only D-MRD or AMRI.

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Substance flow analysis (SFA) is applied to a case study of chlorine metabolism in a chlor-alkali industrial chain. A chain-level SFA model is constructed, and eight indices are proposed to analyze and evaluate the metabolic status of elemental chlorine. The primary objectives of this study are to identify low-efficiency links in production processes and to find ways to improve the operational performance of the industrial chain. Five-year in-depth data collection and analysis revealed that system production efficiency and source efficiency continued increasing since 2008, i.e., when the chain was first formed, at average annual growth rates of 21.01 % and 1.01 %, respectively. In 2011, 64.15 % of the total chlorine input was transformed into final products. That is, as high as 98.50 % of the chlorine inputs were utilized when other by-products were counted. Chlorine loss occurred mostly in the form of chloride ions in wastewater, and the system loss rate was 0.54 %. The metabolic efficiency of chlorine in this case was high, and the chain system had minimal impact on the environment. However, from the perspectives of processing depth and economic output, the case study of a chlor-alkali industrial chain still requires expansion.

Tunnel lining crack is the most common disease and also the manifestation of other diseases, which widely exists in plain concrete lining structure. Proper evaluation and classification of engineering conditions directly relate to operation safety. Particle flow code (PFC) calculation software is applied in this study, and the simulation reliability is verified by using the laboratory axial compression test and 1 : 10 model experiment to calibrate the calculation parameters. Parameter analysis is carried out focusing on the load parameters, structural parameters, dimension, and direction which affect the crack diseases. Based on that, an evaluation index system represented by tunnel buried depth (H), crack position (P), crack length (L), crack width (W), crack depth (D), and crack direction (A) is put forward. The training data of the back propagation (BP) neural network which takes load-bearing safety and crack stability as the evaluation criteria are obtained. An expert system is introduced into the BP neural network for correction of prediction results, realizing classified dynamic optimization of complex engineering conditions. The results of this study can be used to judge the safety state of cracked lining structure and provide guidance to the prevention and control of crack diseases, which is significant to ensure the safety of tunnel operation.