Prediction of Reynolds Stresses in High-Mach-Number Turbulent Boundary Layers using Physics-Informed Machine Learning

Modeled Reynolds stress is a major source of model-form uncertainties in Reynolds-averaged Navier-Stokes (RANS) simulations. Recently, a physics-informed machine-learning (PIML) approach has been proposed for reconstructing the discrepancies in RANS-modeled Reynolds stresses. The merits of the PIML framework has been demonstrated in several canonical incompressible flows. However, its performance on high-Mach-number flows is still not clear. In this work we use the PIML approach to predict the discrepancies in RANS modeled Reynolds stresses in high-Mach-number flat-plate turbulent boundary layers by using an existing DNS database. Specifically, the discrepancy function is first constructed using a DNS training flow and then used to correct RANS-predicted Reynolds stresses under flow conditions different from the DNS. The machine-learning technique is shown to significantly improve RANS-modeled turbulent normal stresses, the turbulent kinetic energy, and the Reynolds-stress anisotropy. Improvements are consistently observed when different training datasets are used. Moreover, a high-dimensional visualization technique and distance metrics are used to provide a priori assessment of prediction confidence based only on RANS simulations. This study demonstrates that the PIML approach is a computationally affordable technique for improving the accuracy of RANS-modeled Reynolds stresses for high-Mach-number turbulent flows when there is a lack of experiments and high-fidelity simulations.Comment: 28 pages, 12 figure

Bioadhesive drug delivery system of diltiazem hydrochloride for improved bioavailability in cardiac therapy

Purpose: To prepare and evaluate bioadhesive buccal films of diltiazem  hydrochloride (a L-type calcium channel blocker) for overcoming the limitations of frequent dosing, low bioavailability and gastrointestinal discomfort of oral delivery.Methods: Buccal films were prepared by solvent casting technique using sodiumcarboxymethylcellulose, polyvinyl pyrrolidone K-30 and polyvinyl alcohol. The films were evaluated for weight, thickness, surface pH, swelling index, in vitro residence time, folding endurance, in vitro release, ex-vivo permeation (across porcine buccal mucosa) and drug content uniformity.Results: The drug content of the formulations was uniform with a range of 18.94 ± 0.066 (F2) to 20.08 ± 0.07 mg per unit film (F1). The films exhibited controlled release ranging from 58.76 ± 1.62 to 91.45 ± 1.02 % over a period > 6 h. The films containing 20 mg diltiazem hydrochloride, polyvinyl alcohol (10 %) and polyvinyl pyrrolidone (1 % w/v) i.e. formulation F5, showed moderate swelling, convenientresidence time and promising drug release, and thus can be selected for further development of a buccal film for potential therapeutic uses.Conclusion: The developed formulation is a potential bioadhesive buccal system for delivering diltiazem directly to systemic circulation, circumventing first-pass metabolism, avoiding gastric discomfort and improving bioavailability at a minimal dose.Keywords: Bioadhesive, Cardiac, Diltiazem, Calcium channel blocker, Buccal film, Bioavailability, Sodium carboxymethylcellulose, Polyvinyl pyrrolidone, Polyvinyl  alcoho

Bayesian Conditional Diffusion Models for Versatile Spatiotemporal Turbulence Generation

Turbulent flows have historically presented formidable challenges to predictive computational modeling. Traditional numerical simulations often require vast computational resources, making them infeasible for numerous engineering applications. As an alternative, deep learning-based surrogate models have emerged, offering data-drive solutions. However, these are typically constructed within deterministic settings, leading to shortfall in capturing the innate chaotic and stochastic behaviors of turbulent dynamics. We introduce a novel generative framework grounded in probabilistic diffusion models for versatile generation of spatiotemporal turbulence. Our method unifies both unconditional and conditional sampling strategies within a Bayesian framework, which can accommodate diverse conditioning scenarios, including those with a direct differentiable link between specified conditions and generated unsteady flow outcomes, and scenarios lacking such explicit correlations. A notable feature of our approach is the method proposed for long-span flow sequence generation, which is based on autoregressive gradient-based conditional sampling, eliminating the need for cumbersome retraining processes. We showcase the versatile turbulence generation capability of our framework through a suite of numerical experiments, including: 1) the synthesis of LES simulated instantaneous flow sequences from URANS inputs; 2) holistic generation of inhomogeneous, anisotropic wall-bounded turbulence, whether from given initial conditions, prescribed turbulence statistics, or entirely from scratch; 3) super-resolved generation of high-speed turbulent boundary layer flows from low-resolution data across a range of input resolutions. Collectively, our numerical experiments highlight the merit and transformative potential of the proposed methods, making a significant advance in the field of turbulence generation.Comment: 37 pages, 31 figure

Gene-MOE: A sparsely gated prognosis and classification framework exploiting pan-cancer genomic information

Benefiting from the advancements in deep learning, various genomic analytical techniques, such as survival analysis, classification of tumors and their subtypes, and exploration of specific pathways, have significantly enhanced our understanding of the biological mechanisms driving cancer. However, the overfitting issue, arising from the limited number of patient samples, poses a challenge in improving the accuracy of genome analysis by deepening the neural network. Furthermore, it remains uncertain whether novel approaches such as the sparsely gated mixture of expert (MOE) and self-attention mechanisms can improve the accuracy of genomic analysis. In this paper, we introduce a novel sparsely gated RNA-seq analysis framework called Gene-MOE. This framework exploits the potential of the MOE layers and the proposed mixture of attention expert (MOAE) layers to enhance the analysis accuracy. Additionally, it addresses overfitting challenges by integrating pan-cancer information from 33 distinct cancer types through pre-training.We pre-trained Gene-MOE on TCGA pan-cancer RNA-seq dataset with 33 cancer types. Subsequently, we conducted experiments involving cancer classification and survival analysis based on the pre-trained Gene-MOE. According to the survival analysis results on 14 cancer types, Gene-MOE outperformed state-of-the-art models on 12 cancer types. Through detailed feature analysis, we found that the Gene-MOE model could learn rich feature representations of high-dimensional genes. According to the classification results, the total accuracy of the classification model for 33 cancer classifications reached 95.8%, representing the best performance compared to state-of-the-art models. These results indicate that Gene-MOE holds strong potential for use in cancer classification and survival analysis

Functional variant of the carboxypeptidase M (CPM) gene may affect silica-related pneumoconiosis susceptibility by its expression: a multistage case-control study.

ObjectivesIn a genome-wide association study, we discovered chromosome 12q15 (defined as rs73329476) as a silica-related pneumoconiosis susceptibility region. However, the causal variants in this region have not yet been reported.MethodsWe systematically screened eight potentially functional single-neucleotide polymorphism (SNPs) in the genes near rs73329476 (carboxypeptidase M (CPM) and cleavage and polyadenylation specific factor 6 (CPSF6)) in a case-control study including 177 cases with silicosis and 204 healthy controls, matched to cases with years of silica dust exposure. We evaluated the associations between these eight SNPs and the development of silicosis. Luciferase reporter gene assays were performed to test the effects of selected SNP on the activity of CPM in the promoter. In addition, a two-stage case-control study was performed to investigate the expression differences of the two genes in peripheral blood leucocytes from a total of 64 cases with silicosis and 64 healthy controls with similar years of silica dust exposure as the cases.ResultsWe found a strong association between the mutant rs12812500 G allele and the susceptibility of silicosis (OR=1.45, 95% CI 1.03 to 2.04, p=0.034), while luciferase reporter gene assays indicated that the mutant G allele of rs12812500 is strongly associated with increased luciferase levels compared with the wild-type C allele (p<0.01). Moreover, the mRNA (peripheral blood leucocytes) expression of the CPM gene was significantly higher in subjects with silicosis compared with healthy controls.ConclusionsThe rs12812500 variant of the CPM gene may increase silicosis susceptibility by affecting the expression of CPM, which may contribute to silicosis susceptibility with biological plausibility

Efficacy, Safety, and Immunogenicity of an Escherichia coliProduced Bivalent Human Papillomavirus Vaccine: An Interim Analysis of a Randomized Clinical Trial

HPV是一种常见的生殖道感染病毒，高危型HPV持续性感染能够导致几乎所有的宫颈癌，其中HPV 16型和18型危害最大，可导致约70%的宫颈癌。预防性HPV疫苗有望减少甚至最终消灭由疫苗型别导致的宫颈癌，降低HPV相关的疾病负担。该研究是在全国4个中心5个现场的18-45岁健康女性中进行的多中心、随机、双盲、对照（戊肝疫苗）的三期临床试验，该研究结果证实我校自主研发的双价人乳头瘤病毒疫苗（大肠杆菌）具有良好的安全性、免疫原性和免疫持久性，可有效地预防HPV 16型和/或18型相关的宫颈高度癌前病变及持续性感染。 该论文报告了我校和厦门万泰沧海生物技术有限公司自主研发的双价人乳头瘤病毒疫苗（大肠杆菌）三期临床试验的期中分析结果。这是第一个进入临床试验并提交药品注册申请的国产人乳头瘤病毒疫苗（HPV疫苗），有望成为世界上第四个上市的HPV疫苗，受到世界卫生组织和盖茨基金会等国际组织的高度关注。 中国医学科学院肿瘤医院乔友林教授、我校吴婷教授、广西壮族自治区疾病预防控制中心李荣成主任医师、江苏省疾病预防控制中心胡月梅主任医师、北京大学人民医院魏丽惠教授、中国食品药品检定研究院李长贵研究员、中国医学科学院肿瘤医院陈汶教授为该论文的共同第一作者，我校张军教授、夏宁邵教授和中国医学科学院肿瘤医院乔友林教授为该论文的共同通讯作者。【Abstract】Background The high cost and insufficient supply of human papillomavirus (HPV) vaccines have slowed the pace of controlling cervical cancer. A phase 3 clinical trial was conducted to evaluate the efficacy, safety and immunogenicity of a novel Escherichia coli-produced bivalent HPV-16/18 vaccine. Methods A multi-centre, randomized, double-blind trial started on November 22, 2012, in China. In total, 7372 eligible women aged 18-45 years were age-stratified and randomly assigned to receiving 3 doses of the test or control (hepatitis E) vaccine at months 0, 1 and 6. Co-primary endpoints included high-grade genital lesions and persistent infection (over 6 months) associated with HPV-16/18. The primary analysis was performed on a per-protocol susceptible population of individuals who were negative for relevant HPV type-specific neutralizing antibodies (at day 0) and DNA (at day 0 through month 7) and who received 3 doses of the vaccine. This report presents data from a pre-specified interim analysis used for regulatory submission. Results In the per-protocol cohort, the efficacies against high-grade genital lesions and persistent infection were 100.0% (95% confidence interval [CI] = 55.6% to 100.0%, 0/3306 in the vaccine group vs. 10/3296 in the control group) and 97.8% (95% CI = 87.1% to 99.9%, 1/3240 vs. 45/3246), respectively. The side effects were mild. No vaccine-related serious adverse events were noted. Robust antibody responses for both types were induced and persisted for at least 42 months. Conclusions The Escherichia coli-produced HPV-16/18 vaccine is well tolerated and highly efficacious against HPV-16/18 associated high-grade genital lesions and persistent infection in women.This work was supported by grants from the Chinese National High-tech R&D Program (863 program, 2012AA02A408), the Chinese National Major Scientific and Technological Special Project for “Significant New Drug Development” (2018ZX09308010 and 2012ZX09101316), the National Natural Science Foundation of China (81673240 and U1705283), the Fujian Provincial Major Scientific and Technological Project (2015YZ0002), the Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences (CIFMS, 2017-I2M-B&R-03, and 2016-I2M-1-019) and Xiamen Innovax. 该研究获得了国家高技术研究发展计划（863计划）、新药创制国家科技重大专项、国家自然科学基金、福建省科技重大专项、中国医学科学院医学与健康科技创新工程基金以及厦门万泰沧海生物技术有限公司的资助

Roadmap on energy harvesting materials

Ambient energy harvesting has great potential to contribute to sustainable development and address growing environmental challenges. Converting waste energy from energy-intensive processes and systems (e.g. combustion engines and furnaces) is crucial to reducing their environmental impact and achieving net-zero emissions. Compact energy harvesters will also be key to powering the exponentially growing smart devices ecosystem that is part of the Internet of Things, thus enabling futuristic applications that can improve our quality of life (e.g. smart homes, smart cities, smart manufacturing, and smart healthcare). To achieve these goals, innovative materials are needed to efficiently convert ambient energy into electricity through various physical mechanisms, such as the photovoltaic effect, thermoelectricity, piezoelectricity, triboelectricity, and radiofrequency wireless power transfer. By bringing together the perspectives of experts in various types of energy harvesting materials, this Roadmap provides extensive insights into recent advances and present challenges in the field. Additionally, the Roadmap analyses the key performance metrics of these technologies in relation to their ultimate energy conversion limits. Building on these insights, the Roadmap outlines promising directions for future research to fully harness the potential of energy harvesting materials for green energy anytime, anywhere

Stratigraphic subdivision and correlation of the Carboniferous System in South China

<div><p>The Carboniferous System of South China is famous for its well-developed rock sequence, variety of depositional types, and abundant fossils. Three established Global Boundary Stratotype Section and Point (GSSP) markers have been identified in several sections in South China. Of these sections, the Pengchong section is the GSSP for the base of the Visean Stage, whereas the Dapoushang and Naqing (Nashui) sections are excellent reference sections for the bases of the Tournaisian and Bashkirian stages, respectively. Other sections have good potential for the four unestablished GSSPs and the Devonian–Carboniferous boundary in South China. The Naqing (Nashui) section is a candidate for the GSSPs of four stages: the Serpukhovian, Moscovian, Kasimovian, and Gzhelian stages. The regional stages of China include the Tangbagouan, Jiusian, Shangsian, Dewuan, Luosuan, Huashibanian, Dalaun, and Xiaodushanian. The history, definitions, reference sections, sedimentary characteristics, biostratigraphy, and correlations of these Chinese regional stages are summarized. A Carboniferous stratigraphic chart of South China is provided, showing the correlation of global chronostratigraphic and biostratigraphic units with those in South China and the lithostratigraphic units of various areas in South China. The chart is presented as a new practical framework for the stratigraphic subdivision and correlation of the Carboniferous System in South China.</p></div