Segmentation of Tricuspid Valve Leaflets From Transthoracic 3D Echocardiograms of Children With Hypoplastic Left Heart Syndrome Using Deep Learning

Hypoplastic left heart syndrome (HLHS) is a severe congenital heart defect in which the right ventricle and associated tricuspid valve (TV) alone support the circulation. TV failure is thus associated with heart failure, and the outcome of TV valve repair are currently poor. 3D echocardiography (3DE) can generate high-quality images of the valve, but segmentation is necessary for precise modeling and quantification. There is currently no robust methodology for rapid TV segmentation, limiting the clinical application of these technologies to this challenging population. We utilized a Fully Convolutional Network (FCN) to segment tricuspid valves from transthoracic 3DE. We trained on 133 3DE image-segmentation pairs and validated on 28 images. We then assessed the effect of varying inputs to the FCN using Mean Boundary Distance (MBD) and Dice Similarity Coefficient (DSC). The FCN with the input of an annular curve achieved a median DSC of 0.86 [IQR: 0.81–0.88] and MBD of 0.35 [0.23–0.4] mm for the merged segmentation and an average DSC of 0.77 [0.73–0.81] and MBD of 0.6 [0.44–0.74] mm for individual TV leaflet segmentation. The addition of commissural landmarks improved individual leaflet segmentation accuracy to an MBD of 0.38 [0.3–0.46] mm. FCN-based segmentation of the tricuspid valve from transthoracic 3DE is feasible and accurate. The addition of an annular curve and commissural landmarks improved the quality of the segmentations with MBD and DSC within the range of human inter-user variability. Fast and accurate FCN-based segmentation of the tricuspid valve in HLHS may enable rapid modeling and quantification, which in the future may inform surgical planning. We are now working to deploy this network for public use.

Simulation for Fitting the Bending Shape of Fruit Branches of Lycium barbarum Based on the Finite Element Method

The accurate modeling of wolfberry plant morphology is the basis for theoretical and simulation analyses of the wolfberry picking process. The curved shape of the fruit branches makes it challenging to model Lyciumbarbarum (wolfberry) plants. This paper establishes a three-dimensional model of the branches under no gravity through field measurements, and then assesses the morphology of the branches under gravity load, fruit load, and branch load using finite element simulation. An orthogonal rotation combination experiment determined the relationship between branch morphology, length, growth angle, and growth mode parameters. The p-values of the prediction model were 0.0001, 0.0067, and 0.0203, respectively. Finally, the bending shape of the actual branches was verified against the branches generated by the prediction model. The experimental results show that the prediction model accurately models the fruit-bearing branches of Lycium barbarum. This paper introduces a method to quickly predict the bending shape of fruit-bearing branches of Lycium barbarum, providing a theoretical basis for rapid modeling of the L. barbarum plant and a simulation analysis for its harvesting.

Hamster organotypic modeling of SARS-CoV-2 lung and brainstem infection

SARS-CoV-2 has caused a global pandemic of COVID-19 since its emergence in December 2019. The infection causes a severe acute respiratory syndrome and may also spread to central nervous system leading to neurological sequelae. We have developed and characterized two new organotypic cultures from hamster brainstem and lung tissues that offer a unique opportunity to study the early steps of viral infection and screening antivirals. These models are not dedicated to investigate how the virus reaches the brain. However, they allow validating the early tropism of the virus in the lungs and demonstrating that SARS-CoV-2 could infect the brainstem and the cerebellum, mainly by targeting granular neurons. Viral infection induces specific interferon and innate immune responses with patterns specific to each organ, along with cell death by apoptosis, necroptosis, and pyroptosis. Overall, our data illustrate the potential of rapid modeling of complex tissue-level interactions during infection by a newly emerged virus.

A Glider Simulation Model Based on Optimized Support Vector Regression for Efficient Coordinated Observation

Multi-gliders have been widely deployed as an array in nowadays ocean observation for fine and long-term ocean research, especially in deep-sea exploration. However, the strong, variable ocean currents and the delayed information feedback of gliders are remaining huge challenges for the deployment of glider arrays which may cause that the observed data cannot meet the study needs and bring a prohibitive cost. In this paper, we develop a Glider Simulation Model (GSM) based on the support vector regression with the particle swarm optimization (PSO)-SVR algorithm to integrate the information feedback from gliders and ocean current data for rapid modeling to effectively predict the gliders’ trajectories. Based on the real-time predictive information of the trajectories, each glider can select future movement strategies. We utilize the in-suit datasets obtained by sea-wing gliders in ocean observation to train and test the simulation model. The results show that GSM has an effective and stable performance. The information obtained from the modeling approaches can be utilized for the optimization of the deployment of the glider arrays.

Surprising simplicity in the modeling of dynamic granular intrusion

Granular intrusions, such as dynamic impact or wheel locomotion, are complex multiphase phenomena where the grains exhibit solid-like and fluid-like characteristics together with an ejected gas-like phase. Despite decades of modeling efforts, a unified description of the physics in such intrusions is as yet unknown. Here, we show that a continuum model based on the simple notions of frictional flow and tension-free separation describes complex granular intrusions near free surfaces. This model captures dynamics in a variety of experiments including wheel locomotion, plate intrusions, and running legged robots. The model reveals that one static and two dynamic effects primarily give rise to intrusion forces in such scenarios. We merge these effects into a further reduced-order technique (dynamic resistive force theory) for rapid modeling of granular locomotion of arbitrarily shaped intruders. The continuum-motivated strategy we propose for identifying physical mechanisms and corresponding reduced-order relations has potential use for a variety of other materials.

Rapid preliminary modeling of transport reactor cores

At the present time, JSC Baltiskiy zavod has built and transported to the deployment site at Pevek Akademik Lomonosov, a floating nuclear power unit (FNPU), project 20870. There are also three multi-purpose nuclear icebreakers of project 22220 (Arktika, Sibir, Ural) under construction at Baltiskiy being at different readiness stages. A decision has been made to build a nuclear icebreaker, Lider, of even a higher power. Integral reactors developed by JSC OKBM Afrikantov are installed in the nuclear icebreakers using new assembly-type cores which have not been used earlier in floating facilities. A great deal of preliminary calculation is required to give these cores as advantageous characteristics as possible. The paper proposes a procedure for rapid modeling of floating cores with varied operating and design characteristics. This procedure can be used as part of preliminary modeling. The procedure is based on using a combined dimensionless parameter proposed by the author in (Korolev 2009). A chart is presented to model the key performance of cores for floating objects with a nuclear reactor NPPs. Eight assembly-type core options, which can be installed in transport reactors of a modular or integral design, are analyzed.

A rapid flood inundation model in the floodplain area due to an extreme rainfall event

Extreme rainfall in East Jakarta on February 19, 2021 caused flooding in a number of subdistricts. The research was conducted in the central part of Kali Sunter, which flows through three subdistricts, namely Cipinang Melayu, Cipinang Muara, and Pondok Bambu. The purpose of the study was to do flood hazard modeling and analyze the characteristics of flood-affected areas based on land use and topography. Inundation and flood hazard maps is done by: calculating the flood discharge using the SCS-CN method, flood inundation modelling using HEC-RAS, and analyzing the characteristics of the inundated area. This combination is effective for rapid modeling during extreme rainfall events. Based on the research, the distribution of the highest flood hazard area is in RW 004 Cipinang Melayu, with the widest inundation affecting small and medium-sized houses. The characteristics of the affected area are that there is green and empty land which reduces the potential for water to inundate buildings or other land uses. Buildings located in low-hazard housing areas tend to be more organized and relatively medium to large in size. While the types of housing in the Cipinang Melayu with a high level of danger tend to be dense and small to medium in size, but the majority have two floors as a form of flood adaptation.