Two-Layer Predictive Control of a Continuous Biodiesel Transesterification Reactor

A novel two-layer predictive control scheme for a continuous biodiesel transesterification reactor is presented. Based on a validated mechanistic model, the least squares (LS) algorithm is used to identify the finite step response (FSR) process model adapted in the controller. The two-layer predictive control method achieves the steady-state optimal setpoints and resolves the multivariable dynamic control problems synchronously. Simulation results show that the two-layer predictive control strategy leads to a significant improvement of control performance in terms of the optimal set-points tracking and disturbances rejection, as compared to conventional PID controller within a multiloop framework

Single-Tooth Modeling for 3D Dental Model

An integrated single-tooth modeling scheme is proposed for the 3D dental model acquired by optical digitizers. The cores of the modeling scheme are fusion regions extraction, single tooth shape restoration, and single tooth separation. According to the “valley” shape-like characters of the fusion regions between two adjoining teeth, the regions of the 3D dental model are analyzed and classified based on the minimum curvatures of the surface. The single tooth shape is restored according to the bioinformation along the hole boundary, which is generated after the fusion region being removed. By using the extracted boundary from the blending regions between the teeth and soft tissues as reference, the teeth can be separated from the 3D dental model one by one correctly. Experimental results show that the proposed method can achieve satisfying modeling results with high-degree approximation of the real tooth and meet the requirements of clinical oral medicine

Research on ordered charge and discharge of cluster electric vehicle based on index selection

The basic characteristics of electric vehicles are important basis for studying the behavior of electric vehicles. According to the basic characteristics of electric vehicles, this paper establishes an electric vehicle convergence model and its control strategy with demand-side response. Taking into account the demand for electric vehicles, electric vehicle aggregators and power companies, reducing the cost of control, while reducing the impact on electric vehicles. Based on the real-time state of charge, the conditions of electric vehicle in the network and other factors to build the assessment model of the scheduling potential, and then put forward the demand response indicators of electric vehicles, and give the corresponding aggregation strategy. considering the multiple constraints , such as the cost constraints of electric vehicles participating in grid regulation, the charging requirements of electric vehicle owners, and the battery consumption of electric vehicles, a control strategy model is proposed for electric vehicles participating in demand response of power systems. The simulation test shows that the aggregation strategy can not only meet the travel needs of electric vehicle owners, but also reduce the impact on the electric vehicle caused by frequent switching of charge and discharge status. In addition, it can also reduce the cost of grid regulation

The Function of Fucosylation in Progression of Lung Cancer

Lung cancer is a disease that influences human health and has become a leading cause of cancer mortality worldwide. However, it is frequently diagnosed at the advanced stage. It is necessary by means of biology to identify specific lung tumor biomarkers with high sensitivity. Glycosylation is one of the most important post-translational modifications and is related to many different diseases. It is involved in numerous essential biological processes, such as cell proliferation, differentiation, migration, cell-cell integrity and recognition, and immune modulation. However, little was known about deregulation of glycosylation in lung cancer and contribution to tumor–microenvironment interactions. Among the numerous glycosylations, fucosylation is the most common modification of glycoproteins and glycosylated oligosaccharides. Increased levels of fucosylation have been detected in various pathological conditions, as well as in lung cancer. In this article, we reviewed the role of fucosylation in lung cancer. We highlighted some of the fucosylation alterations currently being pursued in sera or tissues of lung cancer patients. Moreover, we elaborated on the regulation mechanism of fucosylation in proliferative invasion and metastasis of lung tumor cells. In summary, alterations in fucosylation provide potential biomarkers and therapeutic targets in lung cancer

Correlation analysis of anthropometric indices and type 2 diabetes mellitus in residents aged 60 years and older

Background and purposeIn recent years, the incidence of obesity in people aged 60 and over has increased significantly, and abdominal obesity has been recognized as an independent risk factor for diabetes. Aging causes physiologic decline in multiple body systems, leading to changes in obesity indicators such as BMI. At present, the relationship between abdominal obesity markers and Diabetes mellitus (DM) in people aged 60 years and older remains unclear. Therefore, it is necessary to study the correlation between anthropometric indices and diabetes and explore potential predictors.MethodsThe basic demographic information of participants aged 60 and above in Zhongshan City in 2020 was collected. Physical parameters, blood glucose and other biochemical indices were measured comprehensively. Binary logistic regression analysis was used to explore the relationship between abdominal obesity indicators [Waist circumference, Neck Circumference, Waist-to-hip ratio, Chinese Visceral Obesity Index (CVAI), and visceral obesity index] and diabetes mellitus. ROC characteristic curve was used to analyze the predictive ability of abdominal obesity indicators to DM, and the non-restrictive cubic spline graph was used to visualize the screened obesity indicators and diabetes risk.ResultsAmong 9,519 participants, the prevalence of diabetes was 15.5%. Compared with low CVAI, High CVAI level was significantly associated with increased prevalence of DM in males and females (all p < 0.05), in males (OR, 2.226; 95%CI: 1.128–4.395), females (OR, 1.645; 95%CI: 1.013–2.669). After adjusting for potential confounding factors, there were gender differences between neck circumference and the prevalence of DM, and above-normal neck circumference in males was significantly associated with increased prevalence of DM (OR, 1.381; 95% CI: 1.091–1.747) (p < 0.05).ConclusionAmong these anthropometric indices, CVAI is consistent with the features of fat distribution in older individuals and shows superior discriminative power as a potential predictor of DM, compared to traditional anthropometric parameters

Research on ordered charge and discharge of cluster electric vehicle based on index selection

The basic characteristics of electric vehicles are important basis for studying the behavior of electric vehicles. According to the basic characteristics of electric vehicles, this paper establishes an electric vehicle convergence model and its control strategy with demand-side response. Taking into account the demand for electric vehicles, electric vehicle aggregators and power companies, reducing the cost of control, while reducing the impact on electric vehicles. Based on the real-time state of charge, the conditions of electric vehicle in the network and other factors to build the assessment model of the scheduling potential, and then put forward the demand response indicators of electric vehicles, and give the corresponding aggregation strategy. considering the multiple constraints , such as the cost constraints of electric vehicles participating in grid regulation, the charging requirements of electric vehicle owners, and the battery consumption of electric vehicles, a control strategy model is proposed for electric vehicles participating in demand response of power systems. The simulation test shows that the aggregation strategy can not only meet the travel needs of electric vehicle owners, but also reduce the impact on the electric vehicle caused by frequent switching of charge and discharge status. In addition, it can also reduce the cost of grid regulation

Activating Mn3O4 by Morphology Tailoring for Oxygen Reduction Reaction

Oxygen reduction reaction (ORR) is becoming increasingly important with the development of fuel cells and metal-air batteries. Manganese oxides have been one of the focuses of recent research for Pt-alternative ORR catalysts. However, the structure-activity relationships of manganese oxides have not been well studied or understood. In the present work, we report a new finding that there is a strong dependence of the ORR activity of Mn3O4 on its morphology. By adopting different solvents in the wet-chemical synthesis, we are able to tailor the morphology of Mn3O4 from nanoparticles (NP-L, 12.5 nm and NP-S, 5.95 nm) to nanorods (NR, exposure of Mn3O4 (101)) and nanoflake (NF, exposure of Mn3O4 (001)). Surprisingly, surface-specific activity of NF toward the ORR was found to be one order of magnitude higher than NP-L. The morphology-activity relationships of Mn3O4 were further studied through a combination of electrochemical experiments and density functional theory (DFT) calculations. It was discovered that the formation of *OOH, concomitant with the first electron transfer, is the potential determining step, which is thermo-dynamically more facile on Mn3O4 (001) than (101) plane. The underlying mechanism could be ascribed to the strong interaction between O-2 and Mn3O4 (001) surface as indicated by the DFT calculations. The study enlarges our understanding of Mn3O4 catalysis and provides clues for rational design of highly efficient transitional metal oxide electrocatalysts for the ORR. (C) 2016 Published by Elsevier Ltd

Effects of Growth Regulator and Planting Density on Cotton Yield and N, P, and K Accumulation in Direct-Seeded Cotton

[Objective] This study aims to analyze the effects of the plant growth regulator Miantaijin (N,N-dimethyl piperidinium chloride and 2-N,N-diethylaminoethyl caproate) and planting density on yield and nitrogen (N), phosphorus (P), and potassium (K) uptake and accumulation in cotton. The results will clarify the high-yield cultivation techniques in the cotton direct seeding after wheat harvesting cropping system in the Yangtze River Basin. [Method] In 2017 and 2018, the cotton cultivar Guoxinzao 11-1 was planted at 3 densities (75,000, 90,000, and 105,000 plants·ha−1), and 3 Miantaijin doses (0, 1170, and 2340 mL·ha−1) were imposed. [Results] The results show that the highest yield (3551.3–3687.5 kg·ha−1) was achieved with a 90,000 and 105,000 plant·ha−1 density and 1170 mL·ha−1 of Miantaijin (seedling stage: 90 mL·ha−1, peak squaring stage: 180 mL·ha−1, peak flowering stage: 360 mL·ha−1, and peak bolling stage: 540 mL·ha−1). Under these conditions, the uptakes of N, P, and K were also the highest, up to 117.8 kg·ha−1, 77.4 kg·ha−1, and 116.4 kg·ha−1, respectively. N uptake was the highest from the peak flowering to peak squaring stage, while the highest uptakes of P and K were both detected from the peak squaring to peak flowering stages. We also found significant linear positive correlations between yield and the total absorptions and accumulations of N, P, and K, especially during the peak flowering–peak bolling stage. [Conclusions] The optimum dose of Miantaijin with a medium and high density could enhance the absorption of N, P, and K during the whole growth period of the cotton population, especially in the peak flowering–boll opening stage. This resulted in the highest yield of direct-seeded cotton after wheat harvesting