Kayahaas9739

We carried out extensive experiments under different settings to verify the efficacy of the proposed method. The experimental results demonstrate that our method can yield more realistic simulation of thrombus and is superior to peer method in terms of computational efficiency, maintaining the stability of the dynamic particle motion, and preventing particle penetration at the boundary.

The proposed method can simulate the formation mechanism of thrombus and the interaction between blood flow and thrombus both efficiently and effectively.

The proposed method can simulate the formation mechanism of thrombus and the interaction between blood flow and thrombus both efficiently and effectively.

Mammography is an X-ray imaging technique used for breast cancer screening. Each breast is usually screened at two different angles generating two views known as mediolateral oblique (MLO) and craniocaudal (CC), which are clinically used by radiologists to detect suspicious masses and diagnose breast cancer. Previous studies applied deep learning models to process each view separately and concatenate the features from the two views to detect and classifying masses. However, direct concatenation is not enough to uncover the relationship between the masses that appear in the two views because they can substantially vary in terms of shape, size, and texture. The relationship between the two views should be established by matching correspondence between their extracted masses. This paper presents a dual-view deep convolutional neural network (DV-DCNN) model for matching masses detected from the two views by establishing correspondence between their extracted patches, which leads to more robust mass detection.

een two different views of the same breast leads to more robust mass detection. Experimental results demonstrate the efficacy of a dual-view deep learning model in matching masses, which helps in increasing the accuracy of mass detection and decreasing the false positive rates.

Matching potential masses between two different views of the same breast leads to more robust mass detection. Experimental results demonstrate the efficacy of a dual-view deep learning model in matching masses, which helps in increasing the accuracy of mass detection and decreasing the false positive rates.

In order to solve the problem of accurate and effective segmentation of the patient's lung computed tomography (CT) images, so as to improve the efficiency of treating lung cancer.

We propose a U-Net network (DC-U-Net) fused with dilated convolution, and compare the results of segmented lung CT with DC-U-Net, Otsu and region growth. We use Intersection over Union (IOU), Dice coefficient, Precision and Recall to evaluate the performance of the three algorithms.

Compared with the common segmentation algorithm Otsu and region growing, the segmented image of DC-U-Net is closer to the Ground truth. The IOU of DC-U-Net is 0.9627, and the Dice coefficient is 0.9743, which is close to 1 and much higher than the other two algorithms.

We propose that the model can directly segment the original image automatically, and the segmentation effect is good. This model speeds up the segmentation, simplifies the steps of medical image segmentation, and provides better segmentation for subsequent lung blood vessels, trachea and other tissues.

We propose that the model can directly segment the original image automatically, and the segmentation effect is good. This model speeds up the segmentation, simplifies the steps of medical image segmentation, and provides better segmentation for subsequent lung blood vessels, trachea and other tissues.

The objective of this study was to synthesise evidence from primary care-based interventions for the treatment of obesity in adults and the elderly.

Systematic review.

Eight electronic databases (MEDLINE, Lilacs, Embase, Psycinfo, Cochrane, WHOLIS, Open Gray and Scholar Google) were searched. There was no limitation on publication period; articles published in English, Portuguese or Spanish were included. The selection, data extraction and quality analyses were performed by three reviewers.

A literature search retrieved 6464 publications, of which 5120 publications were excluded after reading the title/abstract and 293 after reading the full text. In total, 56 publications, representing 72 interventions were included. All studies were published between 2000 and 2020. Most studies were conducted in high-income countries. The mean duration of interventions was 11.5 months (SD 7.5), ranging from 3 to 44 months. Most interventions were effective for body mass index reduction, weight loss and waist circumference change.

Our study showed that most interventions were effective for outcomes analysed in adults and the elderly. We also found some literature gaps, such as the need to implement and evaluate obesity after intervention and the requirement to carry out more studies in low- and middle-income countries.

Our study showed that most interventions were effective for outcomes analysed in adults and the elderly. We also found some literature gaps, such as the need to implement and evaluate obesity after intervention and the requirement to carry out more studies in low- and middle-income countries.CO2-driven ocean acidification (OA) affects many aspects of sea urchin biology. https://www.selleckchem.com/products/AC-220.html However, even in the same species, OA effects are often not univocal due to non-uniform exposure setups or different ecological history of the experimental specimens. In the present work, two groups of adult sea urchins Paracentrotus lividus from different environments (the Lagoon of Venice and a coastal area in the Northern Adriatic Sea) were exposed to OA in a long-term exposure. Animals were maintained for six months in both natural seawater (pHT 8.04) and end-of-the-century predicted condition (-0.4 units pH). Monthly, physiological (respiration rate, ammonia excretion, ON ratio) and behavioural (righting, sheltering) endpoints were investigated. Both pH and time of exposure significantly influenced sea urchin responses, but differences between sites were highlighted, particularly in the first months. Under reduced pH, ammonia excretion increased and ON decreased in coastal specimens. Righting and sheltering were impaired in coastal animals, whereas only righting decreased in lagoon ones.