Multi-task learning with multi-gate mixture of transformer-based experts for predictive process monitoring in manufacturing.

Manufacturing industries involve both business processes and complex manufacturing processes. Predictive process monitoring techniques are effective for managing process executions by making multi-perspective real-time predictions, preventing issues such as delivery delays. Conventional predictive process monitoring for business processes focuses on predicting the next activity, next event time, and remaining time using single-task learning, which is costly and complex.

New Insights into the Genetic Basis of Lysine Accumulation in Rice Revealed by Multi-Model GWAS.

Lysine is an essential amino acid that cannot be synthesized in humans. Rice is a global staple food for humans but has a rather low lysine content. Identification of the quantitative trait nucleotides (QTNs) and genes underlying lysine content is crucial to increase lysine accumulation.

Knockdown of ChREBP ameliorates retinal microvascular endothelial cell injury and angiogenic responses in diabetic retinopathy.

Purpose: To examine whether and how carbohydrate response element-binding protein (ChREBP) plays a role in diabetic retinopathy.

Methods: Western blotting was used to detect ChREBP expression and location following high glucose stimulation of Human Retinal Microvascular Endothelial Cells (HRMECs). Flow cytometry, TUNEL staining, and western blotting were used to evaluate apoptosis following ChREBP siRNA silencing.

Genome-wide association studies using multi-models and multi-SNP datasets provide new insights into pasmo resistance in flax.

Introduction: Flax ( L.) is an economically important crop due to its oil and fiber. However, it is prone to various diseases, including pasmo caused by the fungus .

Genome-Wide Association Studies Using 3VmrMLM Model Provide New Insights into Branched-Chain Amino Acid Contents in Rice Grains.

Rice ( L.) is a globally important food source providing carbohydrates, amino acids, and dietary fiber for humans and livestock. The branched-chain amino acid (BCAA) level is a complex trait related to the nutrient quality of rice.

C-Alkylated flavonoids from the whole plants of Desmodium caudatum and their anti-TMV activity.

Background: Natural products are important sources of biopesticides to control plant virus, and flavonoids are identified as promising anti-tobacco mosaic virus (TMV) agents. Since Desmodium caudatum is a rich source of flavonoids, this study focuses on the discovery of the new anti-TMV active flavonoids from D. caudatum and their possible mode of action.

Genome-wide association studies of five free amino acid levels in rice.

Rice ( L.) is one of the important staple foods for human consumption and livestock use. As a complex quality trait, free amino acid (FAA) content in rice is of nutritional importance.

Toward evaluation of multiresolution cortical thickness estimation with FreeSurfer, MaCRUISE, and BrainSuite.

Advances in Magnetic Resonance Imaging hardware and methodologies allow for promoting the cortical morphometry with submillimeter spatial resolution. In this paper, we generated 3D self-enhanced high-resolution (HR) MRI imaging, by adapting 1 deep learning architecture, and 3 standard pipelines, FreeSurfer, MaCRUISE, and BrainSuite, have been collectively employed to evaluate the cortical thickness. We systematically investigated the differences in cortical thickness estimation for MRI sequences at multiresolution homologously originated from the native image.

Effect of 0.02% and 0.01% atropine on astigmatism: a two-year clinical trial.

Background: To evaluate the effects of 0.02% and 0.01% atropine eye drops on ocular and corneal astigmatism over 2 years.

[Retrospective and cost-effective analysis of the result of Changsha Municipal Public Welfare Program by Noninvasive Prenatal Testing].

Objective: To assess the practical and health economical values of non-invasive prenatal test (NIPT) in Changsha Municipal Public Welfare Program.

Methods: A retrospective analysis was carried out on 149 165 women undergoing NIPT test from April 9, 2018 to December 31, 2019. For pregnant women with high risks, invasive prenatal diagnosis and follow-up of pregnancy outcome were conducted.

Scan-Specific Generative Neural Network for MRI Super-Resolution Reconstruction.

The interpretation and analysis of Magnetic resonance imaging (MRI) benefit from high spatial resolution. Unfortunately, direct acquisition of high spatial resolution MRI is time-consuming and costly, which increases the potential for motion artifact, and suffers from reduced signal-to-noise ratio (SNR). Super-resolution reconstruction (SRR) is one of the most widely used methods in MRI since it allows for the trade-off between high spatial resolution, high SNR, and reduced scan times.

MRI Super-Resolution Through Generative Degradation Learning.

Spatial resolution plays a critically important role in MRI for the precise delineation of the imaged tissues. Unfortunately, acquisitions with high spatial resolution require increased imaging time, which increases the potential of subject motion, and suffers from reduced signal-to-noise ratio (SNR). Super-resolution reconstruction (SRR) has recently emerged as a technique that allows for a trade-off between high spatial resolution, high SNR, and short scan duration.

Super-resolution reconstruction of T2-weighted thick-slice neonatal brain MRI scans.

Background And Purpose: Super-resolutionreconstruction (SRR) can be used to reconstruct 3-dimensional (3D) high-resolution (HR) volume from several 2-dimensional (2D) low-resolution (LR) stacks of MRI slices. The purpose is to compare lengthy 2D T2-weighted HR image acquisition of neonatal subjects with 3D SRR from several LR stacks in terms of image quality for clinical and morphometric assessments.

Methods: LR brain images were acquired from neonatal subjects to reconstruct isotropic 3D HR volumes by using SRR algorithm.

Fast and High-Resolution Neonatal Brain MRI Through Super-Resolution Reconstruction From Acquisitions With Variable Slice Selection Direction.

The brain of neonates is small in comparison to adults. Imaging at typical resolutions such as one cubic mm incurs more partial voluming artifacts in a neonate than in an adult. The interpretation and analysis of MRI of the neonatal brain benefit from a reduction in partial volume averaging that can be achieved with high spatial resolution.

Gradient-Guided Isotropic MRI Reconstruction from Anisotropic Acquisitions.

The trade-off between image resolution, signal-to-noise ratio (SNR), and scan time in any magnetic resonance imaging (MRI) protocol is inevitable and unavoidable. Super-resolution reconstruction (SRR) has been shown effective in mitigating these factors, and thus, has become an important approach in addressing the current limitations of MRI. In this work, we developed a novel, image-based MRI SRR approach based on anisotropic acquisition schemes, which utilizes a new gradient guidance regularization method that guides the high-resolution (HR) reconstruction via a spatial gradient estimate.

Learning a Gradient Guidance for Spatially Isotropic MRI Super-Resolution Reconstruction.

In MRI practice, it is inevitable to appropriately balance between image resolution, signal-to-noise ratio (SNR), and scan time. It has been shown that super-resolution reconstruction (SRR) is effective to achieve such a balance, and has obtained better results than direct high-resolution (HR) acquisition, for certain contrasts and sequences. The focus of this work was on constructing images with spatial resolution higher than can be practically obtained by direct Fourier encoding.

An Autograft for Anterior Cruciate Ligament Reconstruction Results in Better Biomechanical Performance and Tendon-Bone Incorporation Than Does a Hybrid Graft in a Rat Model.

Background: The biomechanical and tendon-bone incorporation properties of allograft-augmented hybrid grafts for anterior cruciate ligament (ACL) reconstruction compared with traditional autografts are unknown.

Hypothesis: Using an autograft for ACL reconstruction yields better results on biomechanical testing, radiographic analysis, and histological evaluation versus using a hybrid graft.

Study Design: Controlled laboratory study.

SLIMM: Slice localization integrated MRI monitoring.

Functional MRI (fMRI) is extremely challenging to perform in subjects who move because subject motion disrupts blood oxygenation level dependent (BOLD) signal measurement. It has become common to use retrospective framewise motion detection and censoring in fMRI studies to eliminate artifacts arising from motion. Data censoring results in significant loss of data and statistical power unless the data acquisition is extended to acquire more data not corrupted by motion.

Isotropic MRI Super-Resolution Reconstruction with Multi-scale Gradient Field Prior.

In this work, we proposed a novel image-based MRI super-resolution reconstruction (SRR) approach based on anisotropic acquisition schemes. We achieved superior reconstruction to state-of-the-art work by introducing a new multi-scale gradient field prior that guides the reconstruction of the high-resolution (HR) image. The prior improves both spatial smoothness and edge preservation.

Toward Precise Osteotomies: A Coarse-to-Fine 3D Cut Plane Planning Method for Image-Guided Pelvis Tumor Resection Surgery.

Surgical resection is the main clinical method for the treatment of bone tumors. A critical procedure for bone tumor resection is to plan a set of cut planes that enable resecting the bone tumor with a safe margin while preserving the maximum amount of healthy bone. Currently, the surgeons rely on manual methods to plan the cut planes, which highly depend on the surgeons' experiences and have been demonstrated to be error-prone, and in turn, increase the recurrence rate or resect much healthy bone.

Exploiting Spatial-Temporal Locality of Tracking via Structured Dictionary Learning.

In this paper, a novel spatial-temporal locality is proposed and unified via a discriminative dictionary learning framework for visual tracking. By exploring the strong local correlations between temporally obtained target and their spatially distributed nearby background neighbors, a spatial-temporal locality is obtained. The locality is formulated as a subspace model and exploited under a unified structure of discriminative dictionary learning with a subspace structure.

Correlation Filter Learning Toward Peak Strength for Visual Tracking.

This paper presents a novel visual tracking approach to correlation filter learning toward peak strength of correlation response. Previous methods leverage all features of the target and the immediate background to learn a correlation filter. Some features, however, may be distractive to tracking, like those from occlusion and local deformation, resulting in unstable tracking performance.

[Role of angiogenic T cells and EPC in the pathogenesis of preeclampsia and the relationship between angiogenic T cells and EPC].

Objectives: To investigate the role of angiogenic T cells (Tang) and endothelial progenitor cells (EPC) in the pathogenesis of preeclampsia. To explore the relationship between Tang and EPC.

Methods: From Mar 2013 to Aug 2014, 40 patients diagnosed preeclampsia (PE) and delivered in Hunan Provincial People's Hospital.

Single Object Tracking With Fuzzy Least Squares Support Vector Machine.

Single object tracking, in which a target is often initialized manually in the first frame and then is tracked and located automatically in the subsequent frames, is a hot topic in computer vision. The traditional tracking-by-detection framework, which often formulates tracking as a binary classification problem, has been widely applied and achieved great success in single object tracking. However, there are some potential issues in this formulation.