Error Estimate of a Decoupled Numerical Scheme for the Cahn-Hilliard-Stokes-Darcy System

We analyze a fully discrete finite element numerical scheme for the Cahn-Hilliard-Stokes-Darcy system that models two-phase flows in coupled free flow and porous media. To avoid a well-known difficulty associated with the coupling between the Cahn-Hilliard equation and the fluid motion, we make use of the operator-splitting in the numerical scheme, so that these two solvers are decoupled, which in turn would greatly improve the computational efficiency. The unique solvability and the energy stability have been proved in Chen et al. (2017, Uniquely solvable and energy stable decoupled numerical schemes for the Cahn-Hilliard-Stokes-Darcy system for two-phase flows in karstic geometry. Numer. Math., 137, 229-255). In this work, we carry out a detailed convergence analysis and error estimate for the fully discrete finite element scheme, so that the optimal rate convergence order is established in the energy norm, i.e., in the ℓ ∞(0, T; H1) ∩2 (0, T; H2) norm for the phase variables, as well as in the ℓ ∞ (0, T; H1) ∩ ℓ2 (0, T; H2) norm for the velocity variable. Such an energy norm error estimate leads to a cancelation of a nonlinear error term associated with the convection part, which turns out to be a key step to pass through the analysis. In addition, a discrete ℓ2 (0;T; H3) bound of the numerical solution for the phase variables plays an important role in the error estimate, which is accomplished via a discrete version of Gagliardo-Nirenberg inequality in the finite element setting

Does Co-Location Accelerate Knowledge Outflows from FDI? The Role of MMC Subsidiaries' Technology Sourcing Strategies

Despite the strategic importance of the knowledge outflows from FDI for local firms’ competitiveness, no study has focused on the speed at which this phenomenon takes place. However, this issue is crucial since the speed at which firms absorb external knowledge influences the time they need to carry out subsequent innovations, their ability to adapt to external changes and enter new markets, thus ultimately affecting their chances to achieve a competitive advantage. This paper tries to fill this gap, by investigating the temporal patterns of knowledge outflows between foreign subsidiaries and firms located in host-regions. Combining International Business literature with insights on Innovation Strategy, we provide evidence on the timing of this phenomenon, and discuss the role played by multinational firms’ technology sourcing strategies

Design criteria and applications of multi-channel parallel microfluidic module

The microfluidic technology for function microsphere synthesis has high control precision. However, the throughput is too low for industrial scale-up applications. Current scale-up design focuses on a multi-channel in 2D, in which the distribution uniformity parameter δ increases linearly, resulting in the deterioration of the flow distribution performance. The 3D modular scale-up strategy could greatly alleviate this problem, but no design principles have been developed yet. For the first time, this paper establishes the microfluidic 3D scale-up design criteria. Based on the modular design concept, the design method of 2D and 3D throughput scale-up parameters N and M, distribution uniformity parameters δ and β, and microchannel design parameter KRwere proposed. The equivalent resistance coefficient was defined, and the influence of different parameters on a 2D array and 3D stack was analyzed. Furthermore, the error correction method was studied. It was found that the two-stage scale-up process contradicted each other. A good scale-up performance of one stage led to the limitation of another stage. Increasing the resistance of each channel Rucould both increase the two-stage scale-up performance, which was an important factor. A single-module scale-up system with 8 channels in a single array and 10 arrays in a vertical stack, which had 80 channels in total, was designed and fabricated based on the proposed design criteria for generating Chitosan/TiO2composite microspheres. The average particle size was 539.65 μm and CV value was about 3.59%. The throughput was 480 ml h-1, which effectively increased the throughput scale and the product quality

Clinical Temporal Relation Extraction with Probabilistic Soft Logic Regularization and Global Inference

There has been a steady need in the medical community to precisely extract the temporal relations between clinical events. In particular, temporal information can facilitate a variety of downstream applications such as case report retrieval and medical question answering. Existing methods either require expensive feature engineering or are incapable of modeling the global relational dependencies among the events. In this paper, we propose a novel method, Clinical Temporal ReLation Exaction with Probabilistic Soft Logic Regularization and Global Inference (CTRL-PG) to tackle the problem at the document level. Extensive experiments on two benchmark datasets, I2B2-2012 and TB-Dense, demonstrate that CTRL-PG significantly outperforms baseline methods for temporal relation extraction.Comment: 10 pages, 4 figures, 7 tables, accepted by AAAI 202

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin