Computational fluid dynamics-based hull form optimization using approximation method

With the rapid development of the computational technology, computational fluid dynamics (CFD) tools have been widely used to evaluate the ship hydrodynamic performances in the hull forms optimization. However, it is very time consuming since a great number of the CFD simulations need to be performed for one single optimization. It is of great importance to find a high-effective method to replace the calculation of the CFD tools. In this study, a CFD-based hull form optimization loop has been developed by integrating an approximate method to optimize hull form for reducing the total resistance in calm water. In order to improve the optimization accuracy of particle swarm optimization (PSO) algorithm, an improved PSO (IPSO) algorithm is presented where the inertia weight coefficient and search method are designed based on random inertia weight and convergence evaluation, respectively. To improve the prediction accuracy of total resistance, a data prediction method based on IPSO-Elman neural network (NN) is proposed. Herein, IPSO algorithm is used to train the weight coefficients and self-feedback gain coefficient of ElmanNN. In order to build IPSO-ElmanNN model, optimal Latin hypercube design (Opt LHD) is used to design the sampling hull forms, and the total resistance (objective function) of these hull forms are calculated by Reynolds averaged Navier–Stokes (RANS) method. For the purpose of this paper, this optimization framework has been employed to optimize two ships, namely, the DTMB5512 and WIGLEY III ships, and these hull forms are changed by arbitrary shape deformation (ASD) technique. The results show that the optimization framework developed in this study can be used to optimize hull forms with significantly reduced computational effort

Impacts of CaO solid particles in carbon dioxide absorption process from ship emission with NaOH solution

CO2 emitted from ship exhaust is one of the major sources of atmospheric pollution. In order to reduce ship CO2 emissions, this paper comes up with the idea of recovering CO2 from ship exhaust by NaOH solution and improves the absorption rate by adding CaO solid particles. The effect mechanism of CaO solid particles on CO2 absorption efficiency is analyzed in detail, and the mathematical model is deduced and the CaO enhancement factor is calculated through experiments. Experiment result demonstrates that the effect of CaO solid particles on the absorption of CO2 in alkali solution is significant. The absorption rate of pure CO2 gas, the simulated ship exhaust gas and 6135AZG marine diesel engine emission can be increased by 10%, 15.85% and 10.30%, respectively. So it can be seen that CaO solid particles play an important role in improving the absorption efficiency of ship CO2 emission

Regulation of apoptosis of rbf mutant cells during Drosophila development

AbstractInactivation of the retinoblastoma gene Rb leads to defects in cell proliferation, differentiation, or apoptosis, depending on specific cell or tissue types. To gain insights into the genes that can modulate the consequences of Rb inactivation, we carried out a genetic screen in Drosophila to identify mutations that affected apoptosis induced by inactivation of the Retinoblastoma-family protein (rbf) and identified a mutation that blocked apoptosis induced by rbf. We found this mutation to be a new allele of head involution defective (hid) and showed that hid expression is deregulated in rbf mutant cells in larval imaginal discs. We identified an enhancer that regulates hid expression in response to developmental cues as well as to radiation and demonstrated that this hid enhancer is directly repressed by RBF through an E2F binding site. These observations indicate that apoptosis of rbf mutant cells is mediated by an upregulation of hid. Finally, we showed that bantam, a miRNA that regulates hid translation, is expressed in the interommatidial cells in the larval eye discs and modulates the survival of rbf mutant cells

Hull form optimization in waves based on CFD technique

The seakeeping behavior of a ship in waves is different from its behavior in calm water. The resistance and seakeeping performance of a ship are of great importance and must be considered in the early-stage design of a ship’s hull form design. Therefore, this paper proposes a hull form optimization framework aiming to achieve the minimum total resistance in waves using a CFD technique. A sinusoidal wave is adopted to establish the numerical wave tank and the overset mesh technique is used to facilitate the motions of the ships in question. Considering the motions of pitching and heaving, the total resistance of the hull in waves is regarded as the objective function which is calculated using the Reynolds averaged Navier–Stokes (RANS) method. The arbitrary shape deformation (ASD) technique is used to change the geometry. Under displacement and design variables, a hybrid algorithm is developed to evaluate the objective function combining the optimal Latin hypercube design (Opt LHD) and the non-linear programming by quadratic Lagrangian (NLPQL) algorithm. Finally, two examples of hull form optimization are presented and discussed for David Taylor Model Basin (DTMB) model 5512 and WIGLEY III cases. The results show the effectiveness of the optimization framework developed in the present study, which can lay the foundation for further optimization of full-scale ships

Does Serum Vitamin D Level Affect COVID-19 Infection and Its Severity?-A Case-Control Study

Background: As effective medication to treat COVID-19 is currently unavailable, preventive remedies may be particularly important. Objective: To examine the relationship between serum 25-hydroxy vitamin D (25(OH)D) level and COVID-19 infection, its severity, and its clinical case characteristics. Methods: This case-control study compared serum 25(OH)D levels and rates of vitamin D deficiency (VDD) between 80 healthy controls and 62 patients diagnosed with COVID-19 and admitted to Guangxi People’s Hospital, China, 2/16/2020–3/16/2020. Cases were categorized into asymptomatic, mild/moderate, and severe/critical disease. Logistic regression analysis was conducted to examine the associations between 25(OH)D level, or VDD, and case status/severity of COVID-19 while controlling for demographics and comorbidities. A threshold level of vitamin D for conveying COVID-19 risk was estimated. Results: Severe/critical COVID-19 cases were significantly older and had higher percentages of comorbidity (renal failure) compared to mild cases. The serum 25(OH)D concentration in COVID-19 patient was much lower than that in healthy control. And 25(OH)D level was the lowest in severe/ critical cases, compared with mild cases. In further, significantly higher rates of VDD were found in COVID-19 cases (41.9%) compared to healthy controls (11.1%). And VDD was the greatest in severe/critical cases (80%), compared with mild cases (36%). These statistically significant associations remained even after controlling for demographics and comorbidities. A potential threshold of 25(OH)D (41.19nmol/L) to protect against COVID-19 was identified. Conclusion: Elderly and people with comorbidities were susceptible to severe COVID-19 infection. VDD was a risk factor for COVID-19, especially for severe/critical cases. While further confirmation is needed, vitamin D supplementation may have prevention or treatment potential for COVID- 19 disease

Haploinsufficiency of SIRT1 Enhances Glutamine Metabolism and Promotes Cancer Development

SIRT1, the most conserved mammalian NAD+-dependent protein deacetylase, plays a vital role in the regulation of metabolism, stress responses, and genome stability. However, the role of SIRT1 in the multi-step process leading to transformation and/or tumorigenesis, as either a tumor suppressor or tumor promoter, is complex and maybe dependent upon the context in which SIRT1 activity is altered, and the role of SIRT1 in tumor metabolism is unknown. Here we demonstrate that SIRT1 dose-dependently regulates cellular glutamine metabolism and apoptosis, which in turn differentially impact cell proliferation and cancer development. Heterozygous deletion of Sirt1 induces c-Myc expression, enhancing glutamine metabolism and subsequent proliferation, autophagy, stress resistance and cancer formation. In contrast, homozygous deletion of Sirt1 triggers cellular apoptotic pathways, increases cell death, diminishes autophagy, and reduces cancer formation. Consistent with the observed dose-dependence in cells, intestine-specific Sirt1 heterozygous mice have enhanced intestinal tumor formation, whereas intestine-specific Sirt1 homozygous knockout mice have reduced development of colon cancer. Furthermore, SIRT1 reduction but not deletion is associated with human colorectal tumors, and colorectal cancer patients with low protein expression of SIRT1 have a poor prognosis. Taken together, our findings indicate that the dose-dependent regulation of tumor metabolism and possibly apoptosis by SIRT1 mechanistically contributes to the observed dual roles of SIRT1 in tumorigenesis. Our study highlights the importance of maintenance of a suitable SIRT1 dosage for metabolic and tissue homeostasis, which will have important implications in SIRT1 small molecule activators/inhibitors based therapeutic strategies for cancers

An investigation into fishing boat optimisation using a hybrid algorithm

The optimisation of high-speed fishing boats is different from the optimisation of other displacement type vessels as, for high-speed fishing boats, the wave-making resistance decreases while the splashed resistance increases sharply. To reduce fuel consumption and operating costs in the current economic climate, this paper presents a fishing boat optimisation approach using a Computational Fluid Dynamics (CFD) technique. The RANS-VoF solver was utilised to calculate total resistance, sinkage and trim for a fishing boat in calm water. The Arbitrary Shape Deformation (ASD) technique was used to smoothly alter the geometry. A hybrid algorithm was presented to solve the complicated nonlinear optimisation problem. Herein, a Design of Experiments (DoE) method was applied to find an optimal global region and a mathematical programme was employed to determine an optimal global solution. Under the same displacement with the original hull, two optimisation loops were built with different design variables. After completion of the optimisation, two optimal hull forms were obtained. The optimisation results show that the optimisation loop presented in this study can be used to design a suitable fishing boat in the reduction of the total resistance in calm water

Efficiently identifying genome-wide changes with next-generation sequencing data

We propose a new and effective statistical framework for identifying genome-wide differential changes in epigenetic marks with ChIP-seq data or gene expression with mRNA-seq data, and we develop a new software tool EpiCenter that can efficiently perform data analysis. The key features of our framework are: (i) providing multiple normalization methods to achieve appropriate normalization under different scenarios, (ii) using a sequence of three statistical tests to eliminate background regions and to account for different sources of variation and (iii) allowing adjustment for multiple testing to control false discovery rate (FDR) or family-wise type I error. Our software EpiCenter can perform multiple analytic tasks including: (i) identifying genome-wide epigenetic changes or differentially expressed genes, (ii) finding transcription factor binding sites and (iii) converting multiple-sample sequencing data into a single read-count data matrix. By simulation, we show that our framework achieves a low FDR consistently over a broad range of read coverage and biological variation. Through two real examples, we demonstrate the effectiveness of our framework and the usages of our tool. In particular, we show that our novel and robust ‘parsimony’ normalization method is superior to the widely-used ‘tagRatio’ method. Our software EpiCenter is freely available to the public

Identification of common molecular signatures of SARS-CoV-2 infection and its influence on acute kidney injury and chronic kidney disease

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the main cause of COVID-19, causing hundreds of millions of confirmed cases and more than 18.2 million deaths worldwide. Acute kidney injury (AKI) is a common complication of COVID-19 that leads to an increase in mortality, especially in intensive care unit (ICU) settings, and chronic kidney disease (CKD) is a high risk factor for COVID-19 and its related mortality. However, the underlying molecular mechanisms among AKI, CKD, and COVID-19 are unclear. Therefore, transcriptome analysis was performed to examine common pathways and molecular biomarkers for AKI, CKD, and COVID-19 in an attempt to understand the association of SARS-CoV-2 infection with AKI and CKD. Three RNA-seq datasets (GSE147507, GSE1563, and GSE66494) from the GEO database were used to detect differentially expressed genes (DEGs) for COVID-19 with AKI and CKD to search for shared pathways and candidate targets. A total of 17 common DEGs were confirmed, and their biological functions and signaling pathways were characterized by enrichment analysis. MAPK signaling, the structural pathway of interleukin 1 (IL-1), and the Toll-like receptor pathway appear to be involved in the occurrence of these diseases. Hub genes identified from the protein–protein interaction (PPI) network, including DUSP6, BHLHE40, RASGRP1, and TAB2, are potential therapeutic targets in COVID-19 with AKI and CKD. Common genes and pathways may play pathogenic roles in these three diseases mainly through the activation of immune inflammation. Networks of transcription factor (TF)–gene, miRNA–gene, and gene–disease interactions from the datasets were also constructed, and key gene regulators influencing the progression of these three diseases were further identified among the DEGs. Moreover, new drug targets were predicted based on these common DEGs, and molecular docking and molecular dynamics (MD) simulations were performed. Finally, a diagnostic model of COVID-19 was established based on these common DEGs. Taken together, the molecular and signaling pathways identified in this study may be related to the mechanisms by which SARS-CoV-2 infection affects renal function. These findings are significant for the effective treatment of COVID-19 in patients with kidney diseases

An Integrated Pipeline for the Genome-Wide Analysis of Transcription Factor Binding Sites from ChIP-Seq

ChIP-Seq has become the standard method for genome-wide profiling DNA association of transcription factors. To simplify analyzing and interpreting ChIP-Seq data, which typically involves using multiple applications, we describe an integrated, open source, R-based analysis pipeline. The pipeline addresses data input, peak detection, sequence and motif analysis, visualization, and data export, and can readily be extended via other R and Bioconductor packages. Using a standard multicore computer, it can be used with datasets consisting of tens of thousands of enriched regions. We demonstrate its effectiveness on published human ChIP-Seq datasets for FOXA1, ER, CTCF and STAT1, where it detected co-occurring motifs that were consistent with the literature but not detected by other methods. Our pipeline provides the first complete set of Bioconductor tools for sequence and motif analysis of ChIP-Seq and ChIP-chip data