Model averaging based on weighted generalized method of moments with missing responses

Model averaging based on the least squares estimator or the maximum likelihood estimator has been widely followed, while model averaging based on the generalized method of moments is almost rarely addressed. This paper is concerned with a model averaging method based on the weighted generalized method of moments for missing responses problem. The weight vector for model averaging is obtained via minimizing the leave-one-out cross validation criterion. With some mild conditions, the asymptotic optimality of the proposed method in the sense that it can achieve the lowest squared error asymptotically is proved. Some numerical experiments are conducted to evaluate the proposed method with the existing related ones, and the results suggest that the proposed method performs relatively well

Uniaxial Tension Simulation Using Real Microstructure-based Representative Volume Elements Model of Dual Phase Steel Plate

AbstractDual-phase steels have become a favored material for car bodies. In this study, the deformation behavior of dual-phase steels under uniaxial tension is investigated by means of 2D Representative Volume Elements (RVE) model. The real metallographic graphs including particle geometry, distribution and morphology are considered in this RVE model. Stress and strain distributions between martensite and ferrite are analyzed. The results show that martensite undertakes most stress without significant strain while ferrite shares the most strain. The tensile failure is the result of the deforming inhomogeneity between martensite phase and ferrite phase, which is the key factor triggering the plastic strain localization on specimen section during the tensile test

Inhibiting Receptor of Advanced Glycation End Products Attenuates Pressure Overload-Induced Cardiac Dysfunction by Preventing Excessive Autophagy

The receptor for advanced glycation end products (RAGE) is involved in heart failure (HF) by mediating diverse pathologic processes, including the promotion of inflammation and autophagy. However, the role of RAGE in pressure overload-induced HF is not well understood. We found that stimulation of RAGE triggered the death of neonatal rat ventricular myocytes (NRVMs), while cell death was alleviated by ATG5 knockdown. Using transverse aortic constriction (TAC) in mice as a model of pressure overload-induced HF, we demonstrated that RAGE knockout or RAGE blockade attenuated cardiac hypertrophy and fibrosis as well as cardiac dysfunction at 8 weeks after TAC. Importantly, RAGE knockout reversed upregulation of autophagy related proteins (LC3BII/I and Beclin 1) and reduced cardiomyocyte death, indicating that excessive autophagy after TAC was inhibited. Moreover, RAGE knockout or blockade reduced the upregulation of pp65-NFκB and BNIP3, which mediate autophagy. Taken together, these results suggest that RAGE plays an important role in the progression of HF by regulating autophagy. Therefore, inhibition of the RAGE-autophagy axis could be a promising new strategy for treatment of heart failure

Integrated Genomic Analysis of the Ubiquitin Pathway across Cancer Types

Protein ubiquitination is a dynamic and reversibleprocess of adding single ubiquitin molecules orvarious ubiquitin chains to target proteins. Here,using multidimensional omic data of 9,125 tumorsamples across 33 cancer types from The CancerGenome Atlas, we perform comprehensive molecu-lar characterization of 929 ubiquitin-related genesand 95 deubiquitinase genes. Among them, we sys-tematically identify top somatic driver candidates,including mutatedFBXW7with cancer-type-specificpatterns and amplifiedMDM2showing a mutuallyexclusive pattern withBRAFmutations. Ubiquitinpathway genes tend to be upregulated in cancermediated by diverse mechanisms. By integratingpan-cancer multiomic data, we identify a group oftumor samples that exhibit worse prognosis. Thesesamples are consistently associated with the upre-gulation of cell-cycle and DNA repair pathways, char-acterized by mutatedTP53,MYC/TERTamplifica-tion, andAPC/PTENdeletion. Our analysishighlights the importance of the ubiquitin pathwayin cancer development and lays a foundation fordeveloping relevant therapeutic strategies

Integrated Genomic Analysis of the Ubiquitin Pathway across Cancer Types

Protein ubiquitination is a dynamic and reversible process of adding single ubiquitin molecules or various ubiquitin chains to target proteins. Here, using multidimensional omic data of 9,125 tumor samples across 33 cancer types from The Cancer Genome Atlas, we perform comprehensive molecular characterization of 929 ubiquitin-related genes and 95 deubiquitinase genes. Among them, we systematically identify top somatic driver candidates, including mutated FBXW7 with cancer-type-specific patterns and amplified MDM2 showing a mutually exclusive pattern with BRAF mutations. Ubiquitin pathway genes tend to be upregulated in cancer mediated by diverse mechanisms. By integrating pan-cancer multiomic data, we identify a group of tumor samples that exhibit worse prognosis. These samples are consistently associated with the upregulation of cell-cycle and DNA repair pathways, characterized by mutated TP53, MYC/TERT amplification, and APC/PTEN deletion. Our analysis highlights the importance of the ubiquitin pathway in cancer development and lays a foundation for developing relevant therapeutic strategies. Ge et al. analyze a cohort of 9,125 TCGA samples across 33 cancer types to provide a comprehensive characterization of the ubiquitin pathway. They detect somatic driver candidates in the ubiquitin pathway and identify a cluster of patients with poor survival, highlighting the importance of this pathway in cancer development

Molecular characterization and clinical relevance of metabolic expression subtypes in human cancers.

Metabolic reprogramming provides critical information for clinical oncology. Using molecular data of 9,125 patient samples from The Cancer Genome Atlas, we identified tumor subtypes in 33 cancer types based on mRNA expression patterns of seven major metabolic processes and assessed their clinical relevance. Our metabolic expression subtypes correlated extensively with clinical outcome: subtypes with upregulated carbohydrate, nucleotide, and vitamin/cofactor metabolism most consistently correlated with worse prognosis, whereas subtypes with upregulated lipid metabolism showed the opposite. Metabolic subtypes correlated with diverse somatic drivers but exhibited effects convergent on cancer hallmark pathways and were modulated by highly recurrent master regulators across cancer types. As a proof-of-concept example, we demonstrated that knockdown of SNAI1 or RUNX1—master regulators of carbohydrate metabolic subtypes-modulates metabolic activity and drug sensitivity. Our study provides a system-level view of metabolic heterogeneity within and across cancer types and identifies pathway cross-talk, suggesting related prognostic, therapeutic, and predictive utility

Influence mechanism of machining parameters on surface quality and subsurface damage of single crystal γ-TiAl

To study the influence mechanism of machining process parameters on surface quality and subsurface damage of nano-cutting single crystal γ-TiAl alloy, molecular dynamics(MD) was used as the basic theory. Using a non-rigid diamond tool, a three-dimensional nano-cutting model was established, and the influence of different cutting speeds and depths of cut on the surface and subsurface structure were analyzed in detail by studying chip volume, surface roughness, workpiece hydrostatic pressure distribution, dislocation density, dislocation evolution, and phase transitions atomic number. The results showed that with the increase of cutting speed, the chip volume increases, the machining efficiency improves and there is a critical value of the cutting speed of 100 m/s, the surface roughness first decreases and then increases and there is also a critical value of the cutting speed of 100 m/s, the complexity of dislocations reduces, the density of dislocations decreases, and the degree of plastic deformation increases. However, with the increase of cutting depth, the chip volume increases, the machining efficiency improves, the surface roughness, the density of dislocations and the degree of plastic deformation increase significantly, and it was found that the dislocations were mainly distributed in front of and below the tool during cutting process, and there were V-shaped dislocations and stair rod dislocations in the direction of 45o in front of the tool, as well as dislocations reacting with each other, and stable defects such as vacancies and atomic clusters remained after the cutting process

Data-Driven Model-Free Adaptive Sliding Mode Control Based on FFDL for Electric Multiple Units

The electric multiple units (EMUs) have become a very convenient and powerful means of transportation in our daily life. Safe and punctual trajectory tracking control is the key to improve the performance of the EMUs system, but it is difficult to realize due to the influence of environmental uncertainty, coupling and nonlinearity. In this paper, a model-free adaptive sliding mode control (MFASMC) method is proposed for the EMUs. This method can solve the dependence of the model-based control method on the train model and eliminate the influence of external disturbances on the robust performance of the system. In this method, the running process of the EMUs is equivalent to a full format dynamic linearization (FFDL) data model, and a model-free adaptive controller (MFAC) is designed based on the data model. Then, to reduce the influence of measurement disturbance and improve the robustness of the system, a discrete sliding mode control (SMC) algorithm is introduced. Furthermore, to prevent the control input from being too large, the parameter estimation error is introduced as an additional correction term of the algorithm. In the end, the simulation experiment is carried out with CRH380A EMUs as the object. Compared with the traditional MFAC and the traditional SMC, the speed tracking effect of each power unit of the MFASMC algorithm is more effective, the change of control force is stable, the acceleration meets the requirements of driving, and has a strong inhibitory effect on external disturbances

What Are the Impacts of Urbanisation on Carbon Emissions Efficiency? Evidence from Western China

The contributions of this research are making the theoretical analysis of the impact mechanism of urbanisation on carbon emissions efficiency (CEE), and then empirically analysing the effects of urbanisation on CEE in Western China from 2010 to 2019 by applying the super-efficiency epsilon-based measure model with undesirable outputs and the Tobit model. Major findings are: (1) The mean CEE of the 11 western provinces show a trend of declining and then increasing over those 10 years, demonstrating U-shaped change characteristics. (2) The CEE of Guangxi has the most significant decrease, while the CEE of Chongqing showed only a small fluctuation; the CEE of Guizhou has the characteristic that first it rises, then descends, then rises again; the CEEs of Inner Mongolia and Yunnan have been in the production frontier surface from 2010 to 2015, and presents the trend of declining, then increasing after 2015. The CEEs of the other six western provinces present a trend of declining, then increasing. (3) Chongqing, Sichuan, Inner Mongolia, and Yunnan have a high level of CEE, followed by Shaanxi, Xinjiang, Guangxi, and Guizhou, with an intermediate level of CEE, and Gansu, Ningxia, and Qinghai, with the lowest level of CEE. (4) The effects of urbanisation on CEE in Western China present a U-shaped relationship, meaning that the process of influence was first inhibition, then stimulation. At present, the process of urbanisation shows negative impacts on the CEE, while the tipping point has not yet arrived. The western provinces of China should follow the path of high-quality urbanisation to quickly shift the impact of urbanisation on CEE to the right side of the U-shaped curve