Search

Underground rail transit has become one of the most popular transportation modes because of its advantages such as fast running speed, large passenger flow and punctuality. This mode of transportation can alleviate urban traffic congestion to a certain extent, so underground rail transit has been vigorously developed, and the number of rail lines has increased exponentially. However, with the continuous development of underground rail transit, the energy consumption of train operation is also increasing, resulting in a waste of energy. To solve this problem, this paper proposes to improve the energy-saving technology of train operation by using train autopilot control strategy. Firstly, a train operation optimization model considering train position and speed limit is established by using automatic train driving strategy, and the nonlinear problem of the optimization model is solved by genetic algorithm. The micro-field theory is introduced into the control strategy of automatic train driving, and the energy-saving model of underground rail transit is established. The energy consumption is optimized from three aspects: train energy-saving technology, line planning and overall operation planning of rail transit. The simulation results show that the average impact rate and energy consumption of trains under the proposed energy-saving model are significantly reduced compared with the other two groups of trains, and the average impact rate and energy consumption are significantly reduced compared with the other two groups of trains. The running time and energy consumption of the energy-saving model are lower than those of the experimental group. To sum up, the energy-saving model of underground rail transit proposed in this paper not only reduces the operating energy consumption, but also improves the passenger comfort, which can provide low-cost energy-saving technology for underground transportation field, and has positive significance for urban low-carbon development.

Various carbon sources affect the growth of the G. lucidum fruiting body, and the cassava stalk is considered a promising carbon source for G. lucidum. The composition, functional group characteristics, molecular weight distribution, antioxidant activity in vitro, and growth effect of L. rhamnosus LGG of G. lucidum polysaccharides (GLPs) under cassava stalk stress were investigated by gas chromatography-mass spectrometry, near-infrared spectroscopy, and gel chromatography. The results showed that GLPs consisted of D-glucose, D-galactose, and seven other monosaccharides. The end of the sugar chain had β-D-Glc and β-D-Gal configurations. The total sugar content in GLP1 was the highest (4.07%), and GLP1, GLP2, GLP3, and GLP5 had the β-D-Gal configuration, while GLP4 and GLP6 had the β-D-Glc configuration. The greater the proportion of cassava stalk, the greater the maximum molecular weight of GLPs. The total antioxidant capacities of GLPs obtained from different cassava stalks significantly varied, as well as their stimulating effects on the L. rhamnosus LGG growth. Higher concentrations of GLPs corresponded to the more intensive growth of L. rhamnosus LGG. This study provided essential data support for cassava stalk as a carbon source in G. lucidum cultivation.

Abstract Aim This study aimed to investigate the current situation of the spiritual health of maintenance haemodialysis (MHD) patients in China and analyse the influencing factors. Methods A total of 418 patients who underwent maintenance haemodialysis in three grade A tertiary hospitals were selected. The influencing factors were evaluated with demographic questionnaire, the Functional Assessment of Chronic Illness Therapy‐Spiritual Well‐Being (FACIT‐Sp‐12), Family APGAR Index, Herth Hope Index (HHI) and Acceptance of Illness Scale (AIS). Results Spiritual health was positively correlated with the HHI, Family APGAR and AIS scores. Nationality, HHI score, Family APGAR score and AIS score were independent influencing factors of spiritual health. MHD patients had a moderate level of spiritual health. Nationality, hope, family function and acceptance of illness were significant predictors of spiritual health. Patients who have higher hope levels, better family functioning and better illness acceptance may maintain better spiritual health.

Lipid components in green coffee were clarified to provide essential data support for green coffee processing. The types, components, and relative contents of lipids in green coffee were first analyzed by ultra-performance liquid chromatography–time-of-flight tandem mass spectrometry (UPLC-TOF-MS/MS). The results showed that the main fatty acids in green coffee were linoleic acid (43.39%), palmitic acid (36.57%), oleic acid (8.22%), and stearic acid (7.37%). Proportionally, the ratio of saturated fatty acids/unsaturated fatty acids/polyunsaturated fatty acids was close to 5.5:1:5.2. A total of 214 lipids were identified, including 15 sterols, 39 sphingosines, 12 free fatty acids, 127 glycerides, and 21 phospholipids. The main components of sterols, sphingosines, free fatty acids, glycerides, and phospholipids were acylhexosyl sitosterol, ceramide esterified omega-hydroxy fatty acid sphingosine, linoleic acid, and triglyceride, respectively. UPLC-TOF-MS/MS furnished high-quality and accurate information on TOF MS and TOF MS/MS spectra, providing a reliable analytical technology platform for analyzing lipid components in green coffee.