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This research addresses the crucial problem of collision avoidance decision making for autonomous ships under diverse encounter situations. Building upon the Deep Deterministic Policy Gradient (DDPG) algorithm, appropriate reward functions based on the International Regulations for Preventing Collisions at Sea (COLREGS) have been designed to effectively guide intelligent agents in acquiring optimal strategies. By incorporating the concept of potential reward shaping, the proposed approach ensures efficient obstacle avoidance while adhering strictly to the established rules. Moreover, extensive simulations have been conducted to validate the algorithm’s performance in collision avoidance for both dual-ship and multi-ship scenarios under varying encounter situations, and a comparative analysis with the TD3 algorithm has been undertaken. The obtained results demonstrate that the proposed algorithm exhibits rapid convergence and stable training performance. The resulting models successfully achieve collision-free navigation while strictly adhering to the COLREGS. Particularly, in two-ship encounter situations, the proposed algorithm outperforms the trajectory planned by the TD3 algorithm in terms of shorter path length and higher efficiency.

Oil and gas pipelines use coating and cathodic protection methods to prevent corrosion, and a micro-corrosive environment will be formed where the coating is damaged and peeled off, causing pipeline steel corrosion accidents. The corrosion behavior of X80 steel under the disbonded coating was studied based on the microelectrode technique, and the local open circuit potential (OCP), electrochemical impedance spectroscopy (EIS) and the linear polarization impedance of X80 steel were measured in NS4 solution under the disbonded coating with different cathodic protection potentials. Results showed that when no cathodic protection was applied, the potential at the opening was the highest, the charge transfer resistance and linear polarization impedance were the smallest, and the corrosion rate was the fastest. When the cathodic protection potential of -870 mV was applied, the potential at the opening was the lowest and was not corroded, and the charge transfer resistance and linear polarization impedance were high in the middle of the gap and were not corroded, the bottom of the gap was not subjected to cathodic protection, and the corrosion rate was the fastest. When the cathodic protection potential of -1 000 mV was applied, as the distance from the opening increased, the potential moved forward, the charge transfer resistance and linear polarization resistance increased, and the gap was over-protected state. When the cathodic protection potential was insufficient, the corrosion behavior of the specimen from the opening to the bottom of the gap was different. Besides, increasing the cathodic protection potential could prevent corrosion in the gap, but too high cathodic protection potential caused the gap in an over-protection state.

Hub-based relay networks for long haul trucking offer an opportunity to improve the work–life balance of drivers while simultaneously supporting faster delivery through near-continuous flow of containers from source to destination. In this paper, we develop a model for deciding hub location and sizing along with the routing of loads. Costs of hub construction and operation, transportation and penalties for multi-day driver trips are included. Both deterministic and two-stage stochastic programming models have been formulated in this paper. The goal is to determine the optimal hub and route decisions so that overall cost is minimised. A case study on the highway network for the Western United States demonstrates the computational tractability of the approach along with the importance of considering demand uncertainty. [ABSTRACT FROM AUTHOR]

Background. This study identified the expression and prognosis significance of secretory or membrane-associated proteins in KRAS lung adenocarcinoma (LUAD) and depicted the characteristics between the immune cell infiltration and the expression of these genes. Methods. Gene expression data of LUAD samples (n = 563) were accessed from The Cancer Genome Atlas (TCGA). The expression of secretory or membrane-associated proteins was compared among the KRAS-mutant, wild-type, and normal groups, as well as the subgroup of the KRAS-mutant group. We identified the survival-related differentially expressed secretory or membrane-associated proteins and conducted the functional enrichment analysis. Then, the characterization and association between their expression and the 24 immune cell subsets were investigated. We also constructed a scoring model to predict KRAS mutation by LASSO and logistic regression analysis. Results. Secretory or membrane-associated genes with differential expression (n = 74) across three groups (137 KRAS LUAD, 368 wild-type LUAD, and 58 normal groups) were identified, and the results of GO and KEGG indicated that they were strongly associated with immune cell infiltrations. Among them, ten genes were significantly related to the survival of patients with KRAS LUAD. The expression of IL37, KIF2, INSR, and AQP3 had the most significant correlations with immune cell infiltration. In addition, eight DEGs from the KRAS subgroups were highly correlated with immune infiltrations, especially TNFSF13B. Using LASSO-logistic regression, a KRAS mutation prediction model based on the 74 differentially expressed secretory or membrane-associated genes was built, and the accuracy was 0.79. Conclusion. The research investigated the relationship between the expression of KRAS-related secretory or membrane-associated proteins in LUAD patients with prognostic prediction and immune infiltration characterization. Our study demonstrated that secretory or membrane-associated genes were closely associated with the survival of KRAS LUAD patients and were strongly correlated to immune cell infiltration. [ABSTRACT FROM AUTHOR]

Background: Lung adenocarcinoma is one of the most commonly diagnosed malignancies worldwide. Macrophage plays crucial roles in the tumor microenvironment, but its autocrine network and communications with tumor cell are still unclear.Methods: We acquired single-cell RNA sequencing (scRNA-seq) (n = 30) and bulk RNA sequencing (n = 1480) samples of lung adenocarcinoma patients from previous literatures and publicly available databases. Various cell subtypes were identified, including macrophages. Differentially expressed ligand-receptor gene pairs were obtained to explore cell-to-cell communications between macrophages and tumor cells. Furthermore, a machine-learning predictive model based on ligand-receptor interactions was built and validated.Results: A total of 159,219 single cells (18,248 tumor cells and 29,520 macrophages) were selected in this study. We identified significantly correlated autocrine ligand-receptor gene pairs in tumor cells and macrophages, respectively. Furthermore, we explored the cell-to-cell communications between macrophages and tumor cells and detected significantly correlated ligand-receptor signaling pairs. We determined that some of the hub gene pairs were associated with patient prognosis and constructed a machine-learning model based on the intercellular interaction network.Conclusion: We revealed significant cell-to-cell communications (both autocrine and paracrine network) within macrophages and tumor cells in lung adenocarcinoma. Hub genes with prognostic significance in the network were also identified. [ABSTRACT FROM AUTHOR]

Background. The tumor immune microenvironment (TIME) played an important role in immunotherapy prognosis and treatment response. Immune cells constitute a large part of the tumor microenvironment and regulate tumor progression. Our research is dedicated to studying the infiltrating immune cell in lung adenocarcinoma (LUAD) and seeking potential targets. Methods. The scRNA-seq data were collected from our FDZSH and two public datasets. The code for cell-type mapping algorithms was downloaded from the CIBERSORTx portal. The bioinformatics data of LUAD patients could be approached from The Cancer Genome Atlas (TCGA) portal. Weighted gene coexpression network analysis (WGCNA) and least absolute shrinkage and selection operator (LASSO) analyses were performed to construct a risk model. TIMER2 and TIDE helped with the immune infiltration estimation, while PROGENy helped the cancer-related pathways' enrichment analysis. GSE31210 dataset and IMVigor ICB therapy cohort validated our findings as the external validation datasets. Results. We clustered the scRNA-seq dataset (integrating our FDZSH datasets and other public datasets) into 23 subpopulations. After curated cell annotation, we implemented Cibersort and WGCNA analysis to anchor the brown module and natural killer cell cluster1 due to the most relationship with tumor trait. The overlap of the brown module gene, natural killer cell signature, and DEGs of tumor and adjacent normal samples was screened by LASSO Cox regression. The obtained 5-gene risk model showed an excellent prognostic performance in the validation dataset. Furthermore, there was a correlation between risk score and tumor-infiltrating immune cells and tumor genomics abnormity. Patients with higher risk scores had a significantly lower immunotherapy response rate. Conclusion. Our observations implied that immune cells played a pivotal role in TIME and established a 5-gene signature (including IDH2, ADRB2, SFTPC, CCDC69, and CCND2) on the basement of nature killer markers targeted by WGCNA analysis. The significance of clinical outcome and immunotherapy response prediction was validated robustly. [ABSTRACT FROM AUTHOR]

Objectives: To explore the clinical features, molecular characteristics, and immune landscape of lung adenocarcinoma patients with KEAP1/NFE2L2/CUL3 mutations. Methods: The multi‐omics data from the GDC‐TCGA LUAD project of The Cancer Genome Atlas (TCGA) database were downloaded from the Xena browser. The estimate of the immune infiltration was implemented by using the GSVA analysis and CIBERSORT. The status of KEAP1/NFE2L2/CUL3 mutation in 50 LUAD samples of our department was detected by using Sanger sequencing, following the relative expression level of differentially expressed genes (DEGs), miRNAs (DEmiRNAs), and lncRNAs (DElncRNAs) was validated by IHC and real‐time quantitative polymerase chain reaction (RT‐qPCR). Results: The Kaplan–Meier and multivariable Cox regression analyses demonstrated that KEAP1/NFE2L2/CUL3 mutations had independent prognostic value for OS and PFS in LUAD patients. The differential analysis detected 207 upregulated genes (like GSR/UGT1A6) and 447 downregulated genes (such as PIGR). GO, KEGG, and GSEA analyses demonstrated that DEGs were enriched in glutamate metabolism and the immune response. The constructed ceRNA network shows the linkage of differential lncRNAs and mRNAs. Three hundred and nine somatic mutations were detected, alterations in immune infiltration DNA methylations and stemness scores were also founded between the two groups. Eight mutated LUAD patients were detected by Sanger DNA sequencing in 50 surgical patients. GSR and UGT1A6 were validated to express higher in the Mut group, whereas the expression of PIGR was restrained. Furthermore, the IHC staining conducted on paraffin‐embedded tissue emphasizes the consistency of our result. Conclusion: This research implemented the comprehensive analysis of KEAP1/NFE2L2/CUL3 somatic mutations in the LUAD patients. Compared with the wild type of LUAD patients, the Mut group shows a large difference in clinical features, RNA sequence, DNA methylation, and immune infiltrations, indicating complex mechanism oncogenesis and also reveals potential therapeutic targets. [ABSTRACT FROM AUTHOR]

Background: Differences in genetics and microenvironment of LUAD patients with or without TP53 mutation were analyzed to illustrate the role of TP53 mutation within the carcinogenesis of LUAD, which will provide new concepts for the treatment of LUAD.Methods: In this study, we used genetics and clinical info from the TCGA database, including somatic mutations data, RNA-seq, miRNA-seq, and clinical data. More than one bioinformatics tools were used to analyze the unique genomic pattern of TP53-related LUAD.Results: According to TP53 gene mutation status, we divided the LUAD patients into two groups, including 265 in the mutant group (MU) and 295 in the wild-type group (WT). 787 significant somatic mutations were detected between the groups, including mutations in titin (TTN), type 2 ryanodine receptor (RYR2) and CUB and Sushi multiple domains 3(CSMD3), which were up-regulated in the MU. However, no significant survival difference was observed. At the RNA level, we obtained 923 significantly differentially expressed genes; in the MU, α-defensin 5(DEFA5), pregnancy-specific glycoprotein 5(PSG5) and neuropeptide Y(NPY) were the most up-regulated genes, glucose-6-phosphatase (G6PC), alpha-fetoprotein (AFP) and carry gametocidal (GC) were the most down-regulated genes. GSVA analysis revealed 30 significant pathways. Compared with the WT, the expression of 12 pathways in the mutant group was up-regulated, most of which pointed to cell division. There were significant differences in tumor immune infiltrating cells, such as Macrophages M1, T cells CD4 memory activated, Mast cells resting, and Dendritic cells resting. In terms of immune genes, a total of 35 immune-related genes were screened, of which VGF (VGF nerve growth factor inducible) and PGC (peroxisome proliferator-activated receptor gamma coactivator) were the most significant up-regulated and down-regulated genes, respectively. Research on the expression pattern of immunomodulators found that 9 immune checkpoint molecules and 6 immune costimulatory molecules were considerably wholly different between the two groups.Conclusions: Taking the mutant group as a reference, LUAD patients in the mutant group had significant differences in somatic mutations, mRNA-seq, miRNA-seq, immune infiltration, and immunomodulators, indicating that TP53 mutation plays a crucial role in the occurrence and development of LUAD. [ABSTRACT FROM AUTHOR]

Background: Lung adenocarcinoma (LUAD) patients with different American Joint Committee on Cancer stages have different overall 5‐year survival rates. The tumor microenvironment (TME) and intra‐tumor heterogeneity (ITH) have been shown to play a crucial role in the occurrence and development of tumors. However, the TME and ITH in different lesions of LUAD have not been extensively explored. Methods: We present a 204,157‐cell catalog of the TME transcriptome in 29 lung samples to systematically explore the TME and ITH in the different stages of LUAD. Traditional RNA sequencing data and complete clinical information were downloaded from publicly available databases. Results: Based on these high‐quality cells, we constructed a single‐cell network underlying cellular and molecular features of normal lung, early LUAD, and advanced LUAD cells. In contrast with early malignant cells, we noticed that advanced malignant cells had a remarkably more complex TME and higher ITH level. We also found that compared with other immune cells, more differences in CD8+/CTL T cells, regulatory T cells, and follicular B cells were evident between early and advanced LUAD. Additionally, cell‐cell communication analyses, revealed great diversity between different lesions of LUAD at the single‐cell level. Flow cytometry and qRT‐PCR were used to validate our results. Conclusion: Our results revealed the cellular diversity and molecular complexity of cell lineages in different stages of LUAD. We believe our research, which serves as a basic framework and valuable resource, can facilitate exploration of the pathogenesis of LUAD and identify novel therapeutic targets in the future. [ABSTRACT FROM AUTHOR]

To guarantee the frequency stability of renewable energy sources (RESs) generation integrated into the power system, primary frequency regulation (PFR) for RES generation controlled by virtual synchronous generator (VSG) has been concerned extensively. This study mainly focuses on the dynamic and steady-state characteristics of VSG in the PFR dead-band. Based on the typical structure of VSG, small-signal model of the conventional VSG is established to analyse the issue of the sharp change of angular frequency. Consequently, a novel modified VSG (M-VSG) controller is proposed, which can ensure a stable angular frequency and synchronise with the grid without the phase-locked-loop. The inertia and damping properties of M-VSG are studied theoretically by eigenvalue analysis, and the design procedure of control parameters is presented. To enhance the practicability, a flexible PFR strategy of M-VSG is added considering inertia mode, bidirectional mode, and unidirectional mode according to the operation state of RES generation. Moreover, after PFR is added, the proposed controller is analysed with eigenvalue loci to guarantee the stability and dynamic characteristics outside the dead-band. Finally, hardware-in-the-loop experiment results based on RT-LAB demonstrate the validity of the theoretical analysis and the superiority of M-VSG in participating in flexible PFR. [ABSTRACT FROM AUTHOR]

Background: Some lung diseases are cell type-specific. It is essential to study the cellular anatomy of the normal human lung for exploring the cellular origin of lung disease and the cell development trajectory. Methods: We used the Seurat R package for data quality control. The principal component analysis (PCA) was used for linear dimensionality reduction. UMAP and tSNE were used for dimensionality reduction. Muonocle2 was used to extract lung epithelial cells to analyze the subtypes of epithelial cells further and to study the development of these cell subtypes. Results: We showed a total of 20154 high quality of cells from human normal lung tissue. They were initially divided into 17 clusters cells and then identified as seven types of cells, namely macrophages, monocytes, CD8 + T cells, epithelial cells, endothelial cells, adipocytes, and NK cells. 4240 epithelial cells were extracted for further analysis and they were divided into seven clusters. The seven cell clusters include alveolar cell, alveolar endothelial progenitor, ciliated cell, secretory cell, ionocyte cell, and a group of cells that are not clear at present. We show the development track of these subtypes of epithelial cells, in which we speculate that alveolar epithelial progenitor (AEP) is a kind of progenitor cells that can develop into alveolar cells, and find six essential genes that determine the cell fate, including AGER, RPL10, RPL9, RPS18, RPS27, and SFTPB. Conclusion: We provide a transcription map of human lung cells, especially the in-depth study on the development of epithelial cell subtypes, which will help us to study lung cell biology and lung diseases. [ABSTRACT FROM AUTHOR]

The main objective of this study is to develop a two-stage stochastic programming framework for lot-sizing and scheduling the production activities at a kitting facility to support a manufacturing plant. The novelty of the study lies in modeling multiple uncertainties using two-stage stochastic programming to solve a kitting specific production planning problem in a manufacturing setting. The demand for the kits and the yield of the kitting workers are the two sources of uncertainties considered in this study. The first-stage decisions include the baseline production schedule and the workforce requirement, while the second stage makes recourse decisions on overtime production. The proposed decision-making framework is validated on a multi-period, multi-product case study involving a kitting facility supporting a manufacturing plant producing braking equipment. The main conclusion of the study is that uncertainties have significant impacts on kitting planning decisions and that the proposed two-stage stochastic programming model was robust in determining optimal production plans under uncertainty. [ABSTRACT FROM AUTHOR]

Background: Zhen Wu Decoction (ZWD) is a prescription from the classical text "Treatise on Exogenous Febrile Disease" and has been extensively used to control kidney diseases since the time of the Eastern Han Dynasty.Hypothesis: We hypothesized that ZWD limits tubular fibrogenesis by reinvigorating tubular bio-energetic capacity.Study Design/ Methods: A mouse model of chronic kidney disease (CKD) was established using unilateral ureteral obstruction (UUO). Three concentrations of ZWD, namely 25.2 g/kg (high dosage), 12.6 g/kg (middle dosage), and 6.3 g/kg (low dosage), were included to study the dose-effect relationship. Real-time qPCR was used to observe gene transcription in blood samples from patients with CKD. Different siRNAs were designed to study the role of mitochondrial transcription factor A (TFAM) and nuclear factor (erythroid-derived 2)-related factor 2 (NRF2) in transforming growth factor (TGF)-β1 induced fibrogenesis and mitochondrial damage.Results: We showed that ZWD efficiently attenuates renal function impairment and reduces renal interstitial fibrosis. TFAM and NRF2 were repressed, and the stimulator of interferon genes (STING) was activated in CKD patient blood sample. We further confirmed that ZWD activated TFAM depended on NRF2 as an important negative regulator of STING in mouse kidneys. Treatment with ZWD significantly reduced oxidative stress and inflammation by regulating the levels of oxidative phosphorylation (OXPHOS) and pro-inflammatory factors, such as interleukin-6, interleukin-1β, tumor necrosis factor receptor 1, and mitochondrial respiratory chain subunits. NRF2 inhibitors can weaken the ability of ZWD to increase TFAM expression and heal injured mitochondria, playing a similar role to that of STING inhibitors. Our study showed that ZWD elevates the expression of TFAM and mitochondrial respiratory chain subunits by promoting NRF2 activation, after suppressing mitochondrial membrane damage and cristae breakdown and restricting mitochondrial DNA (mtDNA) leakage into the cytoplasm to reduce STING activation.Conclusion: ZWD maintains mitochondrial integrity and improves OXPHOS which represents an innovative insight into "strengthening Yang-Qi" theory. ZWD limits tubular fibrogenesis by reinvigorating tubular bioenergetic capacity. [ABSTRACT FROM AUTHOR]

• Reveals multi-omics differences between lung squamous cell carcinoma with high PD-1/PD-L1 expression levels and low expression. • Gene enrichment results show that the differential pathways were mainly focused on immune regulation, especially T cell related immune activities. Immunotherapy has achieved excellent results in patients with lung squamous cell carcinoma. However, in which population it can exert the greatest effect is still unknown. Some studies have suggested that its effect is related to the expression level of PD1. Analyzing the relationship between PD1 expression level and genetic differences in lung squamous cell carcinoma patients will be helpful in understanding the underlying causes of this immunotherapy effect and provide a reference for clinical practice. In this study, we used RNA-seq, miRNA-seq, methylation array, mutation profiles, and copy number variation data from the TCGA database and RNA-seq data from the GEO database to analyze the distinctive genomic patterns associated with PD1 and PDL1 expression. RNA-seq data from 44 LUSC patients who underwent surgery at Zhongshan Hospital were also included in the study. After grouping LUSC patients according to the expression levels of PD1 and PDL1, we found no significant difference in survival between the two groups. However, 178 genes, including IL-21, KLRC3, and KLRC4, were significantly upregulated in both the TCGA and GEO databases in the high expression group, and there was a precise correlation between gene expression and epigenetic changes in the two groups. At the same time, the overall level of somatic mutations was not significantly different between the two groups. It is worth noting that the gene enrichment results showed that the differential pathways were mainly enriched in immune regulation, especially T cell-related immune activities. We found that the differences in gene expression between the two groups were related to immunity, which may affect the effectiveness of immunotherapy. We hope our results can provide a reference for further research and help in finding other targets to improve the efficacy of immunotherapy. [ABSTRACT FROM AUTHOR]

Recommender system (RS) plays an important role in Big Data research. Its main idea is to handle huge amounts of data to accurately recommend items to users. The recommendation method is the core research content of the whole RS. However, the existing recommendation methods still have the following two shortcomings: (1) Most recommendation methods use only one kind of information about the user's interaction with items (such as Browse or Purchase), which makes it difficult to model complete user preference. (2) Most mainstream recommendation methods only consider the final consistency of recommendation (e.g., user preferences) but ignore the process consistency (e.g., user behavior), which leads to the biased final result. In this article, we propose a recommendation method based on the Entity Interaction Knowledge Graph (EIKG), which draws on the idea of collaborative filtering and innovatively uses the similarity of user behaviors to recommend items. The method first extracts fact triples containing interaction relations from relevant data sets to generate the EIKG; then embeds the entities and relations in the EIKG; finally, uses link prediction techniques to recommend items for users. The proposed method is compared with other recommendation methods on two publicly available data sets, Scholat and Lizhi, and the experimental result shows that it exceeds the state of the art in most metrics, verifying the effectiveness of the proposed method.