微纳层叠聚丙烯腈凝胶流动特性的数值模拟研究

建立了层叠流道的三维模型和有限元网格模型，根据流变测试数据，采用Polymat对物料的黏度模型参数进行拟合，并利用Polyflow软件对聚丙烯腈（PAN）凝胶在层叠流道内的三维等温流动过程进行了数值模拟分析。研究发现，当入口流量增大时，层叠流道出口速度的不均匀性增加；沿流动方向流道内压力逐渐降低，并在出口处降低至同一最低值；流道进出口压力差与入口流量大小具有正相关性；在流道的中心截面上剪切速率分布均匀，波动较小。     

Spontaneous Cell Detachment and Reattachment in Cancer Cell Lines: An In Vitro Model of Metastasis and Malignancy

There is an unmet need for simplified in vitro models of malignancy and metastasis that facilitate fast, affordable and scalable gene and compound analysis. “Adherent” cancer cell lines frequently release “free-floating” cells into suspension that are viable and can reattach. This, in a simplistic way, mimics the metastatic process. We compared the gene expression profiles of naturally co-existing populations of floating and adherent cells in SW620 (colon), C33a (cervix) and HeLa (cervix) cancer cells. We found that 1227, 1367 and 1333 genes were at least 2-fold differentially expressed in the respective cell lines, of which 122 were shared among the three cell lines. As proof of principle, we focused on the anti-metastatic gene NM23-H1, which was downregulated both at the RNA and protein level in the floating cell populations of all three cell lines. Knockdown of NM23-H1 significantly increased the number of floating (and viable) cells, whereas overexpression of NM23-H1 significantly reduced the proportion of floating cells. Other potential regulators of these cellular states were identified through pathway analysis, including hypoxia, mTOR (mechanistic target of rapamycin), cell adhesion and cell polarity signal transduction pathways. Hypoxia, a condition linked to malignancy and metastasis, reduced NM23-H1 expression and significantly increased the number of free-floating cells. Inhibition of mTOR or Rho-associated protein kinase (ROCK) significantly increased cell death specifically in the floating and not the adherent cell population. In conclusion, our study suggests that dynamic subpopulations of free-floating and adherent cells is a useful model to screen and identify genes, drugs and pathways that regulate the process of cancer metastasis, such as cell detachment and anoikis.     

Marine Phospholipids from Fishery By-Products Attenuate Atherosclerosis

In this study, the anti-atherosclerotic properties of three marine phospholipids (MPLs) extracts from fishery by-products including codfish roe, squid gonad, and shrimp head are verified. Their effects on key factors involved in atherosclerosis are examined and compared to explore whether the differences in their constitutions lead to the differences in the function. All three MPLs dampen oxidation of low- density lipoproteins (LDL) in vitro. Treating RAW264.7 macrophages and HUVECs endothelial cells with each MPLs ranging 10–100 µg mL⁻¹ does not decrease cell viability, yet ox-LDL caused cytotoxicity of both cells are alleviated by 50 or 100 µg mL⁻¹ MPLs treatment. In addition, the three MPLs reduce ox-LDL induced macrophage foam-like transition, mainly through inhibition of lipid uptake. Of the three MPLs, the one from squid gonad exhibits the best effect. On the other hand, all three MPLs modulate inflammatory responses, equally, by inhibiting the adhesion of monocytes to endothelial cells, and decreasing secretion of pro-inflammatory cytokines IL-6 and MCP-1. Using a high-cholesterol diet induced zebrafish model, it is found that all three MPLs, especially the one from squid gonad, alleviates cholesterol accumulation in early plaques, and decreases total cholesterol as well as lipid peroxide in vivo. Practical Applications: As a way of making the best of the increasingly scarce marine resources, valuable lipid components can be recovered from by-products and wastes from the fishery industry. Here, we tested the anti-atherosclerotic effects and the mechanisms of three MPLs extracted from codfish roe, squid gonad, and shrimp head. Our study provides further evidence that marine phospholipids extracted from fishery by-products could protect against atherosclerosis, and helps to elucidate the structure-function relationship of MPLs.     

Predictive process mapping for laser powder bed fusion: A review of existing analytical solutions

One of the main challenges in the laser powder bed fusion (LPBF) process is making dense and defect-free components. These porosity defects are dependent upon the melt pool geometry and the processing conditions. Power-velocity (PV) processing maps can aid in visualizing the effects of LPBF processing variables and mapping different defect regimes such as lack-of-fusion, under-melting, balling, and keyholing. This work presents an assessment of existing analytical equations and models that provide an estimate of the melt pool geometry as a function of material properties. The melt pool equations are then combined with defect criteria to provide a quick approximation of the PV processing maps for a variety of materials. Finally, the predictions of these processing maps are compared with experimental data from the literature. The predictive processing maps can be computed quickly and can be coupled with dimensionless numbers and high-throughput (HT) experiments for validation. The present work provides a boundary framework for designing the optimal processing parameters for new metals and alloys based on existing analytical solutions.     

MP PFGun脉冲爆燃压裂技术在阿曼SSM-XX井的应用

简要叙述了MP PFGun技术工作原理、系统结构特点以及PropFrac脉冲压裂模拟器软件基本功能,并对SSM-XX井的模拟计算P-T曲线和井下压力仪实测曲线进行了对比。结果表明:SM-XX井采用MP PFGun电缆输送工艺安全,脉冲压裂持续时间长,且利用PropFrac模拟软件指导施工设计,取得了较好的应用效果。     

Green Measurements for Software Product Based on Sustainability Dimensions

Software is a central component in the modern world and vastly affects the environment’s sustainability. The demand for energy and resource requirements is rising when producing hardware and software units. Literature study reveals that many studies focused on green hardware; however, limited efforts were made in the greenness of software products. Green software products are necessary to solve the issues and problems related to the long-term use of software, especially from a sustainability perspective. Without a proper mechanism for measuring the greenness of a particular software product executed in a specific environment, the mentioned benefits will not be attained. Currently, there are not enough works to address this problem, and the green status of software products is uncertain and unsure. This paper aims to identify the green measurements based on sustainable dimensions in a software product. The second objective is to reveal the relationships between the elements and measurements through empirical study. The study is conducted in two phases. The first phase is the theoretical phase, where the main components, measurements and practices that influence the sustainability of a software product are identified. The second phase is the empirical study that involved 103 respondents in Malaysia investigating current practices of green software in the industrial environment and further identifying the main sustainability dimensions and measurements and their impact on achieving green software products. This study has revealed seven green measurements of software product: Productivity, Usability, Cost Reduction, Employee Support, Energy Efficiency, Resource Efficiency and Tool Support. The relationships are statistically significant, with a significance level of less than 0.01 (p = 0.000). Thus, the hypothesised relationships were all accepted. The contributions of this study revolve around the research perspectives of the measurements to attain a green software product.     

Tabular data: Deep learning is not all you need

A key element in solving real-life data science problems is selecting the types of models to use. Tree ensemble models (such as XGBoost) are usually recommended for classification and regression problems with tabular data. However, several deep learning models for tabular data have recently been proposed, claiming to outperform XGBoost for some use cases. This paper explores whether these deep models should be a recommended option for tabular data by rigorously comparing the new deep models to XGBoost on various datasets. In addition to systematically comparing their performance, we consider the tuning and computation they require. Our study shows that XGBoost outperforms these deep models across the datasets, including the datasets used in the papers that proposed the deep models. We also demonstrate that XGBoost requires much less tuning. On the positive side, we show that an ensemble of deep models and XGBoost performs better on these datasets than XGBoost alone.     

单增李斯特菌生态行为模型构建及机制研究进展

目的 探究食品中的单增李斯特菌随食品链相关条件的变化而发生的"生长-失活-再生长"生态行为规律.方法 以热加工为失活条件,综述单增李斯特菌生态行为的影响因素、模型构建和相关机制.结果 单增李斯特菌在"生长-失活"过程中,细胞的历史生长条件会对其失活特性产生影响,在"失活-再生长"过程中,细胞的历史生理状态会影响其修复再生长的延滞期.结论 食品链中细菌的生长和失活是连续的过程,有必要研究在连续的环境条件变化过程中细胞的生态行为,以期为食品风险评估和食品安全防控提供支持.     

Quasi‐Bayesian Estimation of Time‐Varying Volatility in DSGE Models

We propose a novel quasi‐Bayesian Metropolis‐within‐Gibbs algorithm that can be used to estimate drifts in the shock volatilities of a linearized dynamic stochastic general equilibrium (DSGE) model. The resulting volatility estimates differ from the existing approaches in two ways. First, the time variation enters non‐parametrically, so that our approach ensures consistent estimation in a wide class of processes, thereby eliminating the need to specify the volatility law of motion and alleviating the risk of invalid inference due to mis‐specification. Second, the conditional quasi‐posterior of the drifting volatilities is available in closed form, which makes inference straightforward and simplifies existing algorithms. We apply our estimation procedure to a standard DSGE model and find that the estimated volatility paths are smoother compared to alternative stochastic volatility estimates. Moreover, we demonstrate that our procedure can deliver statistically significant improvements to the density forecasts of the DSGE model compared to alternative methods.     

新型地锚张弦梁式泥石流格栅坝构件受力的简化计算方法

针对常见泥石流防治结构被冲击破坏的问题，基于“柔性消能”理念，结合张弦梁结构和竖向预应力锚杆技术，提出一种既能改善结构受力性能、增加结构整体抗冲击能力、保证结构安全可靠，又能减小结构构件截面尺寸、节约成本、便于现场施工组装和后期运营维护的新型地锚张弦梁式泥石流格栅坝，并阐述其技术原理。根据泥石流荷载分布和新型地锚张弦梁式泥石流格栅坝的受力特征，给出其简化的内力计算方法；并利用SAP2000建立新结构有限元模型，分析了结构的整体受力，验证了构件简化计算方法的合理性；结合Python语言和Qt De? signer软件开发了相应的设计计算软件，对新型地锚张弦梁式泥石流格栅坝的内力进行求解。结果表明：提出的新结构抗冲击性能好，构件受力均匀；以后设计中应关注竖杆的剪切脆性破坏和立柱偏心受力情况，保证结构安全；变形协调仅使底层张弦梁与竖杆内力偏大，实际工程应用时，应着重验算底层构件，防止其破坏；文中提出的简化计算方法能较准确的反映结构的受力特性，具有一定的合理性，研究可为新型地锚张弦梁式泥石流格栅坝的设计计算和推广应用提供理论依据和技术支持。