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The application of exogenous paclobutrazol (PP 333 ) can improve the ability of winter warming to promote flowering in Chaenomeles speciosa , but the underlying mechanism is unclear. In this study, the cultivar ‘Changshouguan’ was sprayed with different concentrations of PP 333 during flower bud differentiation, and the changes in the anatomical structures and physiological characteristics of the flower buds during the differentiation process, as well as the growth state of the flower buds and the effect on flowering promotion after winter warming treatment, were comprehensively investigated. The results showed that different concentrations of PP 333 could advance the flowering time of ‘Changshouguan’ by 15–24 d under the warming treatment and increase the flowering duration to 17 d compared with those under the warming treatment alone (CK), and 1000 mg/L was the best treatment. Compared with the CK treatment, the PP 333 treatment decreased the contents of indole acetic acid (IAA) and gibberellic acid (GAs) and increased the contents of zeatin ribosides (ZRs) and abscisic acid (ABA), thus changing the balance of hormones during flower bud differentiation. The inflection point (low point) of the curve shapes of the ZRs/GAs and ZRs/IAA ratios appeared significantly earlier, which showed a pattern consistent with soluble sugar and protein content and antioxidant activity. Interestingly, the above changes also corresponded to earlier flowering times during the warming process. Taken together, these results indicate that spraying an appropriate concentration of PP 333 in the early stage of ‘Changshouguan’ flower bud differentiation promotes the early differentiation of flower buds and early flowering under winter warming treatment by altering their endogenous hormone content and homeostasis and changing their physiological state. The key to maintaining a relatively long flowering period in plants in the PP 333 treatment group after flowering promotion was the increased accumulation of sugars and proteins.

Machining quality prediction is the critical link of quality control in parts machining. With the advent of the Industry 4.0 era, intelligent manufacturing and data-driven technologies bring new ideas for quality control in complex machining processes. Quality control is complicated for multi-process, multi-condition, small-batch, and high-precision parts processing requirements. To solve this problem, this paper proposes a machining quality prediction method based on the machining error transfer network and the grey neural network. Initially, by constructing a processing error transfer network, the error transfer law in part processing is described, and the PageRank algorithm and the influence degree of the nodes are used to determine the critical quality features. Additionally, the problem of low prediction accuracy due to small sample data and multiple coupling relationships is solved using the grey neural network algorithm, and a high accuracy prediction of critical quality features is achieved. Finally, the effectiveness and reliability of the method are verified by the case of medium-speed marine diesel engine fuselage processing. The results indicate that this method not only effectively identifies critical quality features in the machining process of complex parts, but it also maintains a high predictive accuracy for these features, even with small samples and limited data.

To address the problem of predicting machining quality for critical features in the manufacturing process of mechanical products, a method that combines information entropy and XGBoost (version 2.1.1) hyperparameter optimization is proposed. Initially, machining data of mechanical products are analyzed based on information entropy theory to identify critical quality characteristics. Subsequently, a quality prediction model for these critical features is established using the XGBoost machine learning framework. The model’s hyperparameters are then optimized through Bayesian optimization. This method is applied as a case study to a medium-speed marine diesel engine piston. After the critical quality characteristics in the machining process are identified, the machining quality of these vital characteristics is predicted, and the results are compared with those obtained from a machine learning model without hyperparameter optimization. The findings demonstrate that the proposed method effectively predicts the machining quality of mechanical products.

This study focused on the physiological regulation and mechanism of exogenous 5-aminolevulinic acid (5-ALA) in the late growth of P. heterophylla. In the middle of May, different concentrations of 5-ALA (0, 10, 20, 50 mg·L−1) were sprayed on the leaves. The effects of 5-ALA on tuberous root growth, antioxidant enzyme system, gas exchange, photosynthetic pigment contents and photosynthetic characteristics were measured from 23 May to 13 June. A concentration of 20 mg·L−1 of 5-ALA led to a significant increase in the yield of fresh root and biomass allocation at 38.12% and 25.07%, respectively, in comparation with the control (0 mg·L−1). The moderate concentration of 5-ALA statistically stimulated antioxidation activities. 5-ALA treatment enhanced photosynthetic activity and reduced photodamage. Compared to the control, there were increases in the chlorophyll fluorescence parameters of P. heterophylla under 5-ALA treatment. Moreover, 20 mg·L−1 of 5-ALA significantly changed the kinetic parameters of fluorescence. It enhanced the light absorption and distribution efficiency of PSII and the activities of leaves, resulting in alleviating photoinhibition by the excess excitation energy. The correlation indicated that there was a significant positive correlation between the yield of tuberous roots and biomass allocation, Pn and catalase (CAT), and a negative correlation between the yield of tuberous roots and malondialdehyde (MDA). The appropriate 5-ALA concentration in the late growth stage of P. heterophylla effectively enhanced the net photosynthetic capacity, mainly resulting from the enhancement of PSII photochemical activity to promote the increases in excitation energy absorption, capture and electron transfer efficiency of the leaves. Finally, 5-ALA treatment can increase the photochemical activity of PSII in the whole leaf and ultimately delay the senescence of P. heterophylla.

Aiming at the difficulty in effectively identifying critical quality features in the complex machining process, this paper proposes a critical quality feature recognition method based on a machining process network. Firstly, the machining process network model is constructed based on the complex network theory. The LeaderRank algorithm is used to identify the critical processes in the machining process. Secondly, the Entropy-CRITIC method is used to calculate the weight of the quality features of the critical processes, and the critical quality features of the critical processes are determined according to weight ranking results. Finally, the feasibility and effectiveness of the method are verified by taking the medium-speed marine diesel engine coupling rod machining as an example. The results show that the method can still effectively identify the critical quality features in the case of small sample data and provide support for machining process optimization and quality control, thus improving product consistency, reliability, and machining efficiency.

Considering rotation-induced centrifugal stiffening, spin softening, and Coriolis effects, the reduced dynamic model of a rotating blade with a dovetail fixture is established in the ANSYS environment via the fixed-interface method for higher computational efficiency and lower memory consumption. Then some parameters such as rotating speed, friction factor, and stator blade number affecting the nonlinear vibration responses of the system under the combined actions of aerodynamic force, centrifugal force, and gravity are elaborately discussed. The results show that: (1) the contact-induced nonlinearity between the tenon and the mortise mainly results in the frequency multiplications of the aerodynamic excitation frequency; (2) a larger friction factor results in a lower magnitude of contact pressure and a higher resonance frequency, while a larger stator blade number results in a lower magnitude of the uniform and continuous contact pressure distribution; (3) the excitation of the resonant mode caused by the aerodynamic force is primarily characterized by the first-order bending mode of the system.

This study focused on the physiological regulation and mechanism of exogenous 5-aminolevulinic acid (5-ALA) in the late growth of P. heterophylla. In the middle of May, different concentrations of 5-ALA (0, 10, 20, 50 mg·L[sup.−1] ) were sprayed on the leaves. The effects of 5-ALA on tuberous root growth, antioxidant enzyme system, gas exchange, photosynthetic pigment contents and photosynthetic characteristics were measured from 23 May to 13 June. A concentration of 20 mg·L[sup.−1] of 5-ALA led to a significant increase in the yield of fresh root and biomass allocation at 38.12% and 25.07%, respectively, in comparation with the control (0 mg·L[sup.−1] ). The moderate concentration of 5-ALA statistically stimulated antioxidation activities. 5-ALA treatment enhanced photosynthetic activity and reduced photodamage. Compared to the control, there were increases in the chlorophyll fluorescence parameters of P. heterophylla under 5-ALA treatment. Moreover, 20 mg·L[sup.−1] of 5-ALA significantly changed the kinetic parameters of fluorescence. It enhanced the light absorption and distribution efficiency of PSII and the activities of leaves, resulting in alleviating photoinhibition by the excess excitation energy. The correlation indicated that there was a significant positive correlation between the yield of tuberous roots and biomass allocation, P[sub.n] and catalase (CAT), and a negative correlation between the yield of tuberous roots and malondialdehyde (MDA). The appropriate 5-ALA concentration in the late growth stage of P. heterophylla effectively enhanced the net photosynthetic capacity, mainly resulting from the enhancement of PSII photochemical activity to promote the increases in excitation energy absorption, capture and electron transfer efficiency of the leaves. Finally, 5-ALA treatment can increase the photochemical activity of PSII in the whole leaf and ultimately delay the senescence of P. heterophylla.

* Retrofitting from CAS to MBR increased effluent quality and environmental benefits. * Retrofitting from CAS to MBR increased energy consumption but not operating cost. * Retrofitting from CAS to MBR increased the net profit and cost efficiency. * The advantage of MBR is related to the adopted effluent standard. * The techno-economy of MBR improves with stricter effluent standards. While a growing number of wastewater treatment plants (WWTPs) are being retrofitted from the conventional activated sludge (CAS) process to the membrane bioreactor (MBR) process, the debate on the techno-economy of MBR vs. CAS has continued and calls for a thorough assessment based on techno-economic valuation. In this study, we analyzed the operating data of 20 large-scale WWTPs (capacity≥10000 m 3/d) and compared their techno-economy before and after the retrofitting from CAS to MBR. Through cost-benefit analysis, we evaluated the net profit by subtracting the operating cost from the environmental benefit (estimated by the shadow price of pollutant removal and water reclamation). After the retrofitting, the removal rate of pollutants increased (e.g., from 89.0% to 93.3% on average for NH 3-N), the average energy consumption increased from 0.40 to 0.57 kWh/m 3, but the operating cost did not increase significantly. The average marginal environmental benefit increased remarkably (from 0.47 to 0.66 CNY/g for NH 3-N removal), leading to an increase in the average net profit from 19.4 to 24.4 CNY/m 3. We further scored the technical efficiencies via data envelopment analysis based on non-radial directional distance functions. After the retrofitting, the relative cost efficiency increased from 0.70 to 0.73 (the theoretical maximum is 1), while the relative energy efficiency did not change significantly. The techno-economy is closely related to the effluent standard adopted, particularly when truncating the extra benefit of pollutant removal beyond the standard in economic modeling. The modeling results suggested that MBR is more profitable than CAS given stricter effluent standards.

This dissertation presents 2-D submicron semiconductor device simulation by both the Hydrodynamic (HD) and the Numerical Boltzmann models. First a new numerical formulation for solving the hydrodynamic model of semiconductor devices which is specially tailored for a block-Gummel iterative approach is presented. Instead of using standard variables$n,pT\\sb{e},T\\sb{p},$new state variables are introduced. When used in conjunction with the Gummel method, the new variables facilitate transformation of the HD equations into linear forms. To help resolve rapid variations in the state variables, a Scharfetter-Gummel type discretization has been developed. The discretization yields a discrete system with coefficient matrices which are well conditioned. The discrete equations are solved using a fixed-point algorithm and a block-Gummel iterative technique. The new approach is used to model a 0.35 $\\mu$ m two-dimensional LDD MOSFET. Second we present a new 2-D MOSFET simulation method achieved by directly solving the Boltzmann Transport Equation (BTE) for electrons, the Hole-Current Continuity Equation and the Poisson Equation self-consistently. The Spherical Harmonic expansion method is used for the solution of the Boltzmann equation. The solution directly gives the electron distribution function, electrostatic potential, and the hole concentration for the entire 2-D MOSFET. Average quantities such as electron concentration and electron temperature are obtained directly from the integration of the distribution function. The collision integral is formulated to arbitrarily high Spherical Harmonic order, and new collision terms are included that incorporate effects of surface scattering and electron-hole pair recombination/generation, I-V characteristics, which agree with experiment, are calculated directly from the distribution function for an LDD submicron MOSFET. Electron-hole pair generation due to impact ionization is also included by direct application of the collision integral. Excellent agreement is achieved between the calculated substrate current and experimental measurement. The calculations are efficient enough for day-to-day engineering design on workstation-type computers.

The accumulation of myelin debris may be a major contributor to the inlfammatory response after diffuse axonal injury. In this study, we examined the accumulation and clearance of myelin debris in a rat model of diffuse axonal injury. Oil Red O staining was performed on sections from the cerebral cortex, hippocampus and brain stem to identify the myelin debris. Seven days after diffuse axonal injury, many Oil Red O-stained particles were observed in the cerebral cortex, hippocampus and brain stem. In the cerebral cortex and hippocampus, the amount of myelin debris peaked at 14 days after injury, and decreased signiifcantly at 28 days. In the brain stem, the amount of myelin debris peaked at 7 days after injury, and decreased signiifcantly at 14 and 28 days. In the cortex and hippocampus, some myelin debris could still be observed at 28 days after diffuse axonal injury. Our ifndings suggest that myelin debris may persist in the rat central ner-vous system after diffuse axonal injury, which would hinder recovery.