GMPSO-VMD Algorithm and Its Application to Rolling Bearing Fault Feature Extraction.

The vibration signal of an early rolling bearing is nonstationary and nonlinear, and the fault signal is weak and difficult to extract. To address this problem, this paper proposes a genetic mutation particle swarm optimization variational mode decomposition (GMPSO-VMD) algorithm and applies it to rolling bearing vibration signal fault feature extraction. Firstly, the minimum envelope entropy is used as the objective function of the GMPSO to find the optimal parameter combination of the VMD algorithm. Then, the optimized VMD algorithm is used to decompose the vibration signal of the rolling bearing and several intrinsic mode functions (IMFs) are obtained. The envelope spectrum analysis of GMPSO-VMD decomposed rolling bearing fault signal IMF1 was carried out. Moreover, the feature frequency of the four fault states of the rolling bearing are extracted accurately. Finally, the GMPSO-VMD algorithm is utilized to analyze the simulation signal and rolling bearing fault vibration signal. The effectiveness of the GMPSO-VMD algorithm is verified by comparing it with the fixed parameter VMD (FP-VMD) algorithm, complete ensemble empirical mode decomposition adaptive noise (CEEMDAN) algorithm and empirical mode decomposition (EMD) algorithm.

The grapevine basic helix-loop-helix (bHLH) transcription factor positively modulates CBF-pathway and confers tolerance to cold-stress in Arabidopsis.

Basic helix-loop-helix (bHLH)-type transcription factors play diverse roles in plant physiological response and stress-adaptive regulation network. Here, we identified one grapevine bHLH transcription factor from a cold-tolerant accession 'Heilongjiang seedling' of Chinese wild Vitis amurensis (VabHLH1) as a transcriptional activator involved in cold stress. We also compared with its counterpart from a cold-sensitive Vitis vinifera cv. Cabernet Sauvignon (VvbHLH1). These two putative proteins are characterized by the presence of the identically conserved regions of 54 amino acid residues of bHLH signature domain, and shared 99.1% amino acid identity, whereas several stress-related cis-regulatory elements located in both promoter regions differed in types and positions. Expressions of two bHLHs in grapevine leaves were induced by cold stress, but evidently differ between two grapevine genotypes upon cold exposure. Two grapevine bHLH proteins were exclusively localized to the nucleus and exhibited strong transcriptional activation activities in yeast cells. Overexpression of either VabHLH1 or VvbHLH1 transcription factor did not affect the growth and development of transgenic Arabidopsis plants, but enhanced tolerance to cold stress. The improved tolerance in VabHLH1- or VvbHLH1-overexpressing Arabidopsis plants is associated with multiple physiological and biochemical changes that occurred during the time-course cold stress. These most common changes include the evaluated levels of proline, decreased amounts of malondialdehyde and reduced membrane injury as reflected by electrolyte leakage. VabHLH1 and VvbHLH1 displayed overlapping, but not identical, roles in activating the corresponding CBF cold signaling pathway, especially in regulating the expression of CBF3 and RD29A. Our findings demonstrated that two grapevine bHLHs act as positive regulators of the cold stress response, modulating the level of COR gene expression, which in turn confer tolerance to cold stress.

Multi-omics analysis reveals a macrophage-related marker gene signature for prognostic prediction, immune landscape, genomic heterogeneity, and drug choices in prostate cancer.

Introduction: Macrophages are components of the innate immune system and can play an anti-tumor or pro-tumor role in the tumor microenvironment owing to their high heterogeneity and plasticity. Meanwhile, prostate cancer (PCa) is an immune-sensitive tumor, making it essential to investigate the value of macrophage-associated networks in its prognosis and treatment. Methods: Macrophage-related marker genes (MRMGs) were identified through the comprehensive analysis of single-cell sequencing data from GSE141445 and the impact of macrophages on PCa was evaluated using consensus clustering of MRMGs in the TCGA database. Subsequently, a macrophage-related marker gene prognostic signature (MRMGPS) was constructed by LASSO-Cox regression analysis and grouped based on the median risk score. The predictive ability of MRMGPS was verified by experiments, survival analysis, and nomogram in the TCGA cohort and GEO-Merged cohort. Additionally, immune landscape, genomic heterogeneity, tumor stemness, drug sensitivity, and molecular docking were conducted to explore the relationship between MRMGPS and the tumor immune microenvironment, therapeutic response, and drug selection. Results: We identified 307 MRMGs and verified that macrophages had a strong influence on the development and progression of PCa. Furthermore, we showed that the MRMGPS constructed with 9 genes and the predictive nomogram had excellent predictive ability in both the TCGA and GEO-Merged cohorts. More importantly, we also found the close relationship between MRMGPS and the tumor immune microenvironment, therapeutic response, and drug selection by multi-omics analysis. Discussion: Our study reveals the application value of MRMGPS in predicting the prognosis of PCa patients. It also provides a novel perspective and theoretical basis for immune research and drug choices for PCa.

Global adaptive control for uncertain nonaffine nonlinear hysteretic systems.

In this paper, the global output tracking is investigated for a class of uncertain nonlinear hysteretic systems with nonaffine structures. By combining the solution properties of the hysteresis model with the novel backstepping approach, a robust adaptive control algorithm is developed without constructing a hysteresis inverse. The proposed control scheme is further modified to tackle the bounded disturbances by adaptively estimating their bounds. It is rigorously proven that the designed adaptive controllers can guarantee global stability of the closed-loop system. Two numerical examples are provided to show the effectiveness of the proposed control schemes.

Chinese wild-growing Vitis amurensis ICE1 and ICE2 encode MYC-type bHLH transcription activators that regulate cold tolerance in Arabidopsis.

Winter hardiness is an important trait for grapevine breeders and producers, so identification of the regulatory mechanisms involved in cold acclimation is of great potential value. The work presented here involves the identification of two grapevine ICE gene homologs, VaICE1 and VaICE2, from an extremely cold-tolerant accession of Chinese wild-growing Vitis amurnensis, which are phylogenetically related to other plant ICE1 genes. These two structurally different ICE proteins contain previously reported ICE-specific amino acid motifs, the bHLH-ZIP domain and the S-rich motif. Expression analysis revealed that VaICE1 is constitutively expressed but affected by cold stress, unlike VaICE2 that shows not such changed expression as a consequence of cold treatment. Both genes serve as transcription factors, potentiating the transactivation activities in yeasts and the corresponding proteins localized to the nucleus following transient expression in onion epidermal cells. Overexpression of either VaICE1 or VaICE2 in Arabidopsis increase freezing tolerance in nonacclimated plants. Moreover, we show that they result in multiple biochemical changes that were associated with cold acclimation: VaICE1/2-overexpressing plants had evaluated levels of proline, reduced contents of malondialdehyde (MDA) and decreased levels of electrolyte leakage. The expression of downstream cold responsive genes of CBF1, COR15A, and COR47 were significantly induced in Arabidopsis transgenically overexpressing VaICE1 or VaICE2 upon cold stress. VaICE2, but not VaICE1 overexpression induced KIN1 expression under cold-acclimation conditions. Our results suggest that VaICE1 and VaICE2 act as key regulators at an early step in the transcriptional cascade controlling freezing tolerance, and modulate the expression levels of various low-temperature associated genes involved in the C-repeat binding factor (CBF) pathway.

An integrated approach of topology optimized design and selective laser melting process for titanium implants materials.

The load-bearing bone implants materials should have sufficient stiffness and large porosity, which are interacted since larger porosity causes lower mechanical properties. This paper is to seek the maximum stiffness architecture with the constraint of specific volume fraction by topology optimization approach, that is, maximum porosity can be achieved with predefine stiffness properties. The effective elastic modulus of conventional cubic and topology optimized scaffolds were calculated using finite element analysis (FEA) method; also, some specimens with different porosities of 41.1%, 50.3%, 60.2% and 70.7% respectively were fabricated by Selective Laser Melting (SLM) process and were tested by compression test. Results showed that the computational effective elastic modulus of optimized scaffolds was approximately 13% higher than cubic scaffolds, the experimental stiffness values were reduced by 76% than the computational ones. The combination of topology optimization approach and SLM process would be available for development of titanium implants materials in consideration of both porosity and mechanical stiffness.