Hyperuniformity with no fine tuning in sheared sedimenting suspensions

Particle suspensions, present in many natural and industrial settings, typically contain aggregates or other microstructures that can complicate macroscopic flow behaviors and damage processing equipment. Recent work found that applying uniform periodic shear near a critical transition can reduce fluctuations in the particle concentration across all length scales, leading to a hyperuniform state. However, this strategy for homogenization requires fine tuning of the strain amplitude. Here we show that in a model of sedimenting particles under periodic shear, there is a well-defined regime at low sedimentation speed where hyperuniform scaling automatically occurs. Our simulations and theoretical arguments show that the homogenization extends up to a finite lengthscale that diverges as the sedimentation speed approaches zero.Comment: 11 pages, 6 figure

Splicing-dependent NMD does not require the EJC in Schizosaccharomyces pombe

Nonsense-mediated mRNA decay (NMD) is a translation-linked process that destroys mRNAs with premature translation termination codons (PTCs). In mammalian cells, NMD is also linked to pre-mRNA splicing, usually PTCs trigger strong NMD only when positioned upstream of at least one intron. The exon junction complex (EJC) is believed to mediate the link between splicing and NMD in these systems. Here, we report that in Schizosaccharomyces pombe splicing also enhances NMD, but against the EJC model prediction, an intron stimulated NMD regardless of whether it is positioned upstream or downstream of the PTC and EJC components are not required. Still the effect of splicing seems to be direct—we have found that the important NMD determinant is the proximity of an intron to the PTC, not just the occurrence of splicing. On the basis of these results, we propose a new model to explain how splicing could affect NMD

Automated Grading of Radiographic Knee Osteoarthritis Severity Combined with Joint Space Narrowing

The assessment of knee osteoarthritis (KOA) severity on knee X-rays is a central criteria for the use of total knee arthroplasty. However, this assessment suffers from imprecise standards and a remarkably high inter-reader variability. An algorithmic, automated assessment of KOA severity could improve overall outcomes of knee replacement procedures by increasing the appropriateness of its use. We propose a novel deep learning-based five-step algorithm to automatically grade KOA from posterior-anterior (PA) views of radiographs: (1) image preprocessing (2) localization of knees joints in the image using the YOLO v3-Tiny model, (3) initial assessment of the severity of osteoarthritis using a convolutional neural network-based classifier, (4) segmentation of the joints and calculation of the joint space narrowing (JSN), and (5), a combination of the JSN and the initial assessment to determine a final Kellgren-Lawrence (KL) score. Furthermore, by displaying the segmentation masks used to make the assessment, our algorithm demonstrates a higher degree of transparency compared to typical "black box" deep learning classifiers. We perform a comprehensive evaluation using two public datasets and one dataset from our institution, and show that our algorithm reaches state-of-the art performance. Moreover, we also collected ratings from multiple radiologists at our institution and showed that our algorithm performs at the radiologist level. The software has been made publicly available at https://github.com/MaciejMazurowski/osteoarthritis-classification

Static coupling effect of a two-degree-of-freedom direct drive induction motor

Two-degree-of-freedom motors are capable of producing linear, rotary, and helical motion, and thus have widespread applications in special industries. In this study, a new concept- static coupling effect is studied in the two-degree-of-freedom direct-drive induction motor (2DoFDDIM). The proposed approach is based on the image method and the three-dimensional (3D) finite-element method. The image method model is established to analyse its reasons and predict the main effects, which are then verified by the proposed 3D finite-element static coupling model and experiments. The induced voltages and currents are produced in the static part and induced torque or force is obtained, even though the static part is not energised. It is concluded that the static coupling effect increases with the supply frequency and is influenced by the stator winding configuration. Thus, the existence of the static coupling effect is confirmed, which must be taken into account in future optimisation and precise control of the 2DoFDDIM

Assessment of intrahepatic blood flow by Doppler ultrasonography: Relationship between the hepatic vein, portal vein, hepatic artery and portal pressure measured intraoperatively in patients with portal hypertension

<p>Abstract</p> <p>Background</p> <p>Abnormality of hepatic vein (HV) waveforms evaluated by Doppler ultrasonography has been widely studied in patients with chronic liver disease. We investigated the correlation between changes in HV waveforms and portal vein velocity (PVVel), the hepatic artery pulsatility index (HAPI), and also the extent of abnormal Doppler HV waveforms expressed as damping index (DI), severity of portal hypertension expressed as Child-Pugh scores and portal pressure (PP) measured directly from patients with portal hypertension (PHT) to evaluate the indicative value of abnormal HV waveforms and discuss the cause of abnormal HV waveform.</p> <p>Methods</p> <p>Sixty patients who had been diagnosed with PHT and accepted surgical therapy of portosystemic shunts were investigated. PP was measured intraoperatively. Thirty healthy volunteers with no history of chronic liver disease were enrolled as the control group. HV waveforms were categorized as triphasic, biphasic or monophasic. DI was compared as the quantitative indicator of abnormal HV waveforms. Another two Doppler parameters, PVVel and HAPI were also measured. These Doppler features were compared with PP, Child-Pugh scores and histological changes assessed by liver biopsy.</p> <p>Results</p> <p>In the patient group, the Doppler flow waveforms in the middle HV were triphasic in 31.6%, biphasic in 46.7%, and monophasic in 21.6% of subjects. These figures were 86.7%, 10.0%, and 3.3%, respectively, in healthy subjects. With the flattening of HV waveforms, the HAPI increased significantly (<it>r </it>= 00.438, <it>p </it>< 0.0001), whereas PVVel decreased significantly (<it>r </it>= -0.44, <it>p <</it>0.0001). Blood flow parameters, HAPI, PVVel and HV-waveform changes showed no significant correlations with Child-Pugh scores. The latter showed a significant correlation with PP (<it>r </it>= 0.589, <it>p </it>= 0.044). Changes of HV waveform and DI significantly correlated with PP (<it>r </it>= 0.579, <it>r </it>= 0.473, <it>p <</it>0.0001), and significant correlation between DI and Child-Pugh scores was observed (<it>r </it>= 0.411, <it>p = </it>0.001). PP was significantly different with respect to nodule size (<it>p </it>< 0.05), but HV-waveform changes were not significantly correlated with pathological changes.</p> <p>Conclusion</p> <p>In patients with PHT, a monophasic HV waveform indicates higher portal pressure. Furthermore, quantitative indicator DI can reflect both higher portal pressure and more severe liver dysfunction. Flattening of HV waveforms accompanied by an increase in the HAPI and decrease in PVVel support the hypothesis that histological changes reducing HV compliance be the cause of abnormality of Doppler HV waveforms from the hemodynamic angle.</p

Genetic Variants in TGF-β Pathway Are Associated with Ovarian Cancer Risk

The transforming growth factor-β (TGF-β) signaling pathway is involved in a diverse array of cellular processes responsible for tumorigenesis. In this case-control study, we applied a pathway-based approach to evaluate single-nucleotide polymorphisms (SNPs) in the TGF-β signaling pathway as predictors of ovarian cancer risk. We systematically genotyped 218 SNPs from 21 genes in the TGF-β signaling pathway in 417 ovarian cancer cases and 417 matched control subjects. We analyzed the associations of these SNPs with ovarian cancer risk, performed haplotype analysis and identified potential cumulative effects of genetic variants. We also performed analysis to identify higher-order gene-gene interactions influencing ovarian cancer risk. Individual SNP analysis showed that the most significant SNP was SMAD6: rs4147407, with an adjusted odds ratio (OR) of 1.60 (95% confidence interval [CI], 1.14–2.24, P = 0.0066). Cumulative genotype analysis of 13 SNPs with significant main effects exhibited a clear dose-response trend of escalating risk with increasing number of unfavorable genotypes. In gene-based analysis, SMAD6 was identified as the most significant gene associated with ovarian cancer risk. Haplotype analysis further revealed that two haplotype blocks within SMAD6 were significantly associated with decreased ovarian cancer risk, as compared to the most common haplotype. Gene-gene interaction analysis further categorized the study population into subgroups with different ovarian cancer risk. Our findings suggest that genetic variants in the TGF-β signaling pathway are associated with ovarian cancer risk and may facilitate the identification of high-risk subgroups in the general population