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A crane system often works in a complex environment. It is difficult to model or learn its true dynamics by traditional system identification approaches. If a dynamics model is created by minimizing its prediction error, its use tends to introduce inaccuracies and thus lead to suboptimal performance. Is it possible to learn the dynamics model of a crane that can achieve the best performance, instead of learning its true dynamics? This work answers the question by presenting a performance-driven model predictive control (P-MPC) algorithm for a two-dimensional underactuated bridge crane. In the proposed dual-layer control architecture, an inner-loop controller uses a proportional–integral–derivative controller to achieve anti-sway rapidly. An outer-loop controller uses MPC to ensure accurate trolley positioning under control constraints. Compared with classical MPC, this work proposes a data-driven method for plant modeling and controller parameter updating. By considering the control target at the learning stage, the method can avoid adjusting the controller to deal with uncertainty. We use Bayesian optimization in an active learning framework where a locally linear dynamics model is learned with the intent of maximizing control performance and then used in conjunction with optimal control schemes to efficiently design a controller for a given task. The model is updated directly based on the performance observed in experiments on the physical system in an iterative manner till a desired performance is achieved. The controller parameters and prediction models of the best closed-loop performance can be found through continuous experiments and iterative optimization. Simulation and experiment results show that we can explicitly find the dynamics model that produces the best performance for an actual system, and the method can quickly suppress swing and realize accurate trolley positioning. The results verified its effectiveness, feasibility, and superior performance on comparing it with state-of-the-art methods.

In the petrochemical industry, multiphase flow, including oil–water two-phase stratified laminar flow, is more common and can be easily obtained through mathematical analysis. However, there is limited mathematical analytical model for the simulation of oil–water flow under turbulent flow. This paper introduces a two-dimensional (2D) numerical simulation method to investigate the pressure gradient, flow field, and oil–water interface height of a pipeline cross-section of horizontal tube in an oil–water stratified smooth flow. Three Reynolds average N–S equation models (k−ε, k−ω, SST k−ω) are involved to simulate oil–water stratified smooth flow according to the finite volume method. The pressure gradient and oil–water interface height can be computed according to the given volume flow rate using the iteration method. The predicted result of oil–water interface height and velocity profile by the model fit well with several published experimental data, except that there is a large error in pressure gradient. The SST k−ω turbulence model appears higher accuracy for simulating oil–water two-phase stratified flow in a horizontal pipe.

The Concus-Finn condition, based on the local microscopic contact angle, can be used to predict discontinuous behavior of a liquid drop in an ideally sharp corner. However, since ideally sharp corners do not exist in reality, it is important to understand the effect of rounded corners on the behavior of liquid drops. In this paper, we use theoretical calculations to study the behavior of two-dimensional liquid drops in rounded corners, including the case in which the contact angles on the two sides of the corner may differ. A new discontinuous behavior was discovered in our study, which is different from the case in sharp corners. Comparing the situation in sharp corners, our study shows that the behavior of a drop in a rounded corner depends on the dimensionless volume of the drop, in addition to its dependence on the opening angle and contact angles that is covered by the Concus-Finn condition. We also use energy-minimization approach to successfully explain why this discontinuous behavior occurs in rounded corners.

Background Schizophrenia (SCZ) is a complex and severe mental illness. There is a lack of effective biomarkers for SCZ diagnosis. The aim of this study was to explore the possibility of using serum peptides for the diagnosis of SCZ as well as analyze the association of variants in genes coding for these peptides and SCZ. Methods After bead-based fractionation, the matrix-assisted laser desorption ionization/time-of-flight mass spectrometry technique was used to identify peptides that showed different expressions between 166 SCZ patients and 201 healthy controls. Differentially expressed peptides were verified in a second set of samples (81 SCZ patients and 103 healthy controls). The association of SCZ and three tagSNPs selected in genes coding for differentially expressed peptides was performed in 1,126 SCZ patients and 1,168 controls. Results The expression level of peptides with m/z 1,945.07 was significant lower in SCZ patients than in healthy controls (P < 0.000001). The peptide with m/z 1,945.07 was confirmed to be a fragment of Kininogen-1. In the verification tests, Kininogen-1 had a sensitivity of 95.1% and a specificity of 97.1% in SCZ prediction. Among the three tagSNPs (rs13037490, rs2983639, rs2983640) selected in the Cystatin 9 gene (CST9) which encodes peptides including Kininogen-1, tagSNP rs2983640 had its genotype distributions significantly different between SCZ patients and controls under different genetic models (P < 0.05). Haplotypes CG (rs2983639–rs2983640) and TCG (rs13037490–rs2983639–rs2983640) were significantly associated with SCZ (CG: OR = 1.21, 95% CI [1.02–1.44], P = 0.032; TCG: OR = 24.85, 95% CI [5.98–103.17], P < 0.0001). Conclusions The present study demonstrated that SCZ patients had decreased expression of Kininogen-1 and genetic variants in Kininogen-1 coding gene CST9 were significantly associated with SCZ. The findings from both protein and genetic association studies suggest that Kininogen-1 could be a biomarker of SCZ.

Surface tension tanks are the most widely used satellite propellant tanks, which use liquid surface tension for liquid transportation and gas-liquid separation to provide pure propellant for thruster. As the second generation surface tension tank, the plate type tank has characteristics of simple structure, easy processing and high reliability, and represents development direction of surface tension tanks. In this paper, drop tower experiments are used to investigate transfer speed of deflectors in plate type tanks, and corresponding numerical simulation is carried out in Fluent with Volume of Fluid method.

Sirtuin 5 (SIRT5) is a member of the NAD+-dependent sirtuin family of protein deacylase that catalyzes removal of post-translational modifications, such as succinylation, malonylation, and glutarylation on lysine residues. In light of the SIRT5's roles in regulating mitochondrion function, we show here that SIRT5 deficiency leads to suppression of mitochondrial NADH oxidation and inhibition of ATP synthase activity. As a result, SIRT5 deficiency decreases mitochondrial ATP production, increases AMP/ATP ratio, and subsequently activates AMP-activated protein kinase (AMPK) in cultured cells and mouse hearts under energy stress conditions. Moreover, Sirt5 knockout attenuates transverse aortic constriction (TAC)-induced cardiac hypertrophy and cardiac dysfunction in mice, which is associated with decreased ATP level, increased AMP/ATP ratio and enhanced AMPK activation. Our study thus uncovers an important role of SIRT5 in regulating cellular energy metabolism and AMPK activation in response to energy stress.

Cetaceans are a group of secondary aquatic mammals whose ancestors returned to the ocean from land, and during evolution, their immune systems adapted to the aquatic environment. Their skin, as the primary barrier to environmental pathogens, supposedly evolved to adapt to a new living environment. However, the immune system in the skin of cetaceans and the associated molecular mechanisms are still largely unknown. To better understand the immune system, we extracted RNA from the sperm whale’s (Physeter macrocephalus) skin and performed PacBio full-length sequencing and RNA-seq sequencing. We obtained a total of 96,350 full-length transcripts with an average length of 1705 bp and detected 5150 genes that were associated with 21 immune-related pathways by gene annotation enrichment analysis. Moreover, we found 89 encoding genes corresponding to 33 proteins were annotated in the NOD-like receptor (NLR)-signaling pathway, including NOD1, NOD2, RIP2, and NF-κB genes, which were discussed in detail and predicted to play essential roles in the immune system of the sperm whale. Furthermore, NOD1 was highly conservative during evolution by the sequence comparison and phylogenetic tree. These results provide new information about the immune system in the skin of cetaceans, as well as the evolution of immune-related genes.

The glucagon receptor (GCGR) is a G-protein-coupled receptor (GPCR) that mediates the activity of glucagon. Disruption of GCGR results in many metabolic alterations, including increased glucose tolerance, decreased adiposity, hypoglycemia, and pancreatic α-cell hyperplasia. To better understand the global transcriptomic changes resulting from GCGR deficiency, we performed whole-organism RNA sequencing analysis in wild type and gcgr-deficient zebrafish. We found that the expression of 1645 genes changes more than two-fold among mutants. Most of these genes are related to metabolism of carbohydrates, lipids, and amino acids. Genes related to fatty acid β-oxidation, amino acid catabolism, and ureagenesis are often downregulated. Among gcrgr-deficient zebrafish, we experimentally confirmed increases in lipid accumulation in the liver and whole-body glucose uptake, as well as a modest decrease in total amino acid content. These results provide new information about the global metabolic network that GCGR signaling regulates in addition to a better understanding of the receptor’s physiological functions.

In order to solve issues concerning performance induction and in-cylinder heat accumulation of a certain heavy-duty diesel engine in a plateau environment, working state parameters and performance indexes of diesel engine are calculated and optimized using the method of artificial neural network and genetic algorithm cycle multi-objective optimization. First, with an established diesel engine simulation model and an orthogonal experimental method, the influence rule of five performance indexes affected by five working state parameters are calculated and analyzed. Results indicate the first four of five working state parameters have a more prominent influence on those five performance indexes. Subsequently, further calculation generates correspondences among four working state parameters and five performance indexes with the method of radial basis function neural network. The predicted value of the trained neural network matches well with the original one. The approach can fulfill serialization of discrete working state parameters and performance indexes to facilitate subsequent analysis and optimization. Next, we came up with a new algorithm named RBFNN & GACMOO, which can calculate the optimal working state parameters and the corresponding performance indexes of the diesel engine working at 3700 m altitude. At last, the bench test of the diesel engine in a plateau environment is employed to verify accuracy of the optimized results and the effectiveness of the algorithm. The research first combined the method of artificial neural network and genetic algorithm to specify the optimal working state parameters of the diesel engine at high altitudes by focusing on engine power, torque and heat dissipation, which is of great significance for improving both performance and working reliability of heavy-duty diesel engine working in plateau environment.

AIMS:There have been few studies on the disparities within the population with disabilities, especially in China. The aim of this study was to evaluate the differences in some health conditions among people with different types of disabilities in Shanghai. METHODS:This study was conducted using data from the Shanghai Disabled Persons' Rehabilitation Comprehensive Information Platform. The records of 31,082 persons with disabilities who had undergone professional health examination were analyzed, and the prevalence and number of five diseases and five risk factors were examined. Logistic regression was used to explore disparities from two perspectives: 1) basic differences, unadjusted for other factors, and 2) differences after adjusting for key demographic covariates. A p-value < 0.05 was considered significant. RESULTS:Individuals with visual disability had a high rate of refractive error (60.0%), and averaged 1.75 diseases of interest, which was the highest value among all disability types. The mean number of risk factors we measured was greatest (1.96) in the population with mental disability. There were significant differences (p < 0.05) between the hearing and speech impairment group and the other groups with respect to most health outcomes, except chronic pharyngitis, hepatic cysts, and high blood pressure. CONCLUSION:Significant differences of selected health outcomes between groups with different types of disabilities remained after controlling for key demographic indicators. Further research is needed to explore the relationships between health conditions and disability types.

This paper is concerned with the effect of capacity constraints on the locations of terror response facilities. We assume that the state has limited resources, and multiple facilities may be involved in the response until the demand is satisfied consequently. We formulate a leader-follower game model between the state and the terrorist and prove the existence and uniqueness of the Nash equilibrium. An integer linear programming is proposed to obtain the equilibrium results when the facility number is fixed. The problem is demonstrated by a case study of the 19 districts of Shanghai, China.