Schizophrenia is a severe mental disorder that affects 0.5–1% of the population worldwide. Current diagnostic methods are based on psychiatric interviews, which are subjective in nature. The lack of disease biomarkers to support objective laboratory tests has been a long-standing bottleneck in the clinical diagnosis and evaluation of schizophrenia. Here we report a global metabolic profiling study involving 112 schizophrenic patients and 110 healthy subjects, who were divided into a training set and a test set, designed to identify metabolite markers. A panel of serum markers consisting of glycerate, eicosenoic acid, β-hydroxybutyrate, pyruvate and cystine was identified as an effective diagnostic tool, achieving an area under the receiver operating characteristic curve (AUC) of 0.945 in the training samples (62 patients and 62 controls) and 0.895 in the test samples (50 patients and 48 controls). Furthermore, a composite panel by the addition of urine β-hydroxybutyrate to the serum panel achieved a more satisfactory accuracy, which reached an AUC of 1 in both the training set and the test set. Multiple fatty acids and ketone bodies were found significantly (P<0.01) elevated in both the serum and urine of patients, suggesting an upregulated fatty acid catabolism, presumably resulting from an insufficiency of glucose supply in the brains of schizophrenia patients.

A solid oxide fuel cell (SOFC) stack is a complicated nonlinear power system. Its system model includes a set of partial differential equations that describe species, mass, momentum and energy conservation, as well as the electrochemical reaction models. The validation and verification of the control system by experiment is very expensive and difficult. Based on the distributed and lumped model of a one‐dimensional SOFC, the dynamic performance with different control loops for SOFC is investigated. The simulation result proves that the control system is appropriate and feasible, and can effectively satisfy the requirement of variable load power demand. This simulation model not only can prevent some latent dangers of the fuel cell system but also predict the distributed parameters' characteristics inside the SOFC system.

The most troublesome part in the development of a component-based engine models is the compressor module because of the strong dependence of its performance on rotational speed. For this purpose, a performance characteristics estimation method of multi-stage axial flow compressors are proposed in this paper. The newly proposed estimation technique of average infinitesimal stage characteristics satisfies the analogy criterion perfectly due to the use of a new conception of infinitesimal stage and the improved analogy theory. The overall compressor performance characteristics are estimated through a stage by stage calculation based on the improved analogy theory and the average stage characteristics. To minimize the error between the calculated characteristic and the tested characteristic of the compressor at high rotational speeds, the average stages performance characteristics are identified using an optimization method. The technique improves the traditional scaling method by taking into account the effects of air density change and rotational speeds, and it makes use of available data efficiently. In addition, it reflects the own performance characteristics of the original compressor.

A hardware-in-the-loop simulation of a three-shaft gas turbine engine for ship propulsion was established. This system is composed of computers, actual hardware, measuring instruments, interfaces between actual hardware and computers, and a network for communication, as well as the relevant software, including mathematical models of the gas turbine engine. "Hardware-in-the-loop" and "volume inertia effects" are the two innovative features of this simulation system. In comparison to traditional methods for gas turbine simulation, the new simulation platform can be implemented in real time and also can test the physical hardware's performance through their integration with the mathematical simulation model. A fuel control strategy for a three-shaft gas turbine engine, which can meet the requirement to the acceleration time and not exceeding surge line, was developed using this platform.

Based on the conservation of energy and conservation of mass, as well as considering the mass transfer in the electrodes-electrolyte interface and its effect on Molten Carbonate Fuel Cell (MCFC) thermal characteristics, this paper presents a mathematical model to modify the dynamic performance of MCFC. Using the method of weighted residuals (MWR) which possesses high precision for the solution of partial differential equations, and the Matlab system function which is efficient for numerical resolution and simulation, a dynamic simulation model of MCFC is created. The results of the simulation show that the mass transfer in the electrodes-electrolyte interface notably affects Molten Carbonate Fuel Cell (MCFC) thermal characteristics, and there is a distribution of temperature both in the electrodes-electrolyte and in the fuel gas as well as in the oxidant gas. The temperature of electrodes-electrolyte increases and that of oxidant gas decreases with increments in the flow rate of both the fuel gas and oxidant gas.

This paper presents an extensible object model for gas turbine engine performance simulation. The extension method for gas path balancing is analyzed and a new design rationale is developed to overcome deficiencies of the traditional component-based object modeling method. A class framework implementing this rationale is described and the dynamic performance of a three-shaft gas turbine engine is simulated to evaluate the model’s effectiveness.