Whole-lesion-aware network based on freehand ultrasound video for breast cancer assessment: a prospective multicenter study.

Background: The clinical application of artificial intelligence (AI) models based on breast ultrasound static images has been hindered in real-world workflows due to operator-dependence of standardized image acquisition and incomplete view of breast lesions on static images. To better exploit the real-time advantages of ultrasound and more conducive to clinical application, we proposed a whole-lesion-aware network based on freehand ultrasound video (WAUVE) scanning in an arbitrary direction for predicting overall breast cancer risk score.

Methods: The WAUVE was developed using 2912 videos (2912 lesions) of 2771 patients retrospectively collected from May 2020 to August 2022 in two hospitals.

Lubricating Grease Thickness Classification of Steel Wire Rope Surface Based on GEMR-MobileViT.

Proper surface lubrication with optimal grease thickness is essential for extending steel wire rope service life. To achieve automated lubrication quality control and address challenges like variable lighting and motion blur that degrade recognition accuracy in practical settings, this paper proposes an improved lightweight GEMR-MobileViT. The model is designed to identify the grease thickness on steel wire rope surfaces while mitigating the high parameters and computational complexity of existing models.

Brain-guided convolutional neural networks reveal task-specific representations in scene processing.

Scene categorization is the dominant proxy for visual understanding, yet humans can perform a large number of visual tasks within any scene. Consequently, we know little about how different tasks change how a scene is processed, represented, and its features ultimately used. Here, we developed a novel brain-guided convolutional neural network (CNN) where each convolutional layer was separately guided by neural responses taken at different time points while observers performed a pre-cued object detection task or a scene affordance task on the same set of images.

Multi-Objective Optimization Method for High-Efficiency and Low-Consumption Wire Rope Greasing Process.

Wire rope greasing is essential for protecting wire ropes from corrosion and wear. To address issues such as low maintenance efficiency and excessive grease usage, this study proposes a high-efficiency, low-consumption optimization control method for the wire rope greasing process. A time objective function for the greasing process and a consumption objective function for grease are established.

A Multi-Strategy Hybrid Sparse Reconstruction Method Based on Spatial-Temporal Sparse Wave Number Analysis for Enhancing Pipe Ultrasonic-Guided Wave Anomaly Imaging.

Ultrasonic-guided waves (UGWs) in defective pipes are subject to severe coherent noise caused by imperfect detection conditions, mode conversion, and intrinsic characteristics (dispersion and multiple modes), inducing the limited performance of anomaly imaging. To achieve the high resolution and accuracy of anomaly imaging, a multi-strategy hybrid sparse reconstruction (MHSR) method based on spatial-temporal sparse wavenumber analysis (ST-SWA) is proposed. MHSR leverages the capability of ST-SWA to extract the wavenumber dispersion curves, thereby providing a more refined and precise search space for MHSR.

Ultrasound Viscosity Imaging in Breast Lesions: A Multicenter Prospective Study.

Rationale And Objectives: To explore and validate the clinical value of ultrasound (US) viscosity imaging in differentiating breast lesions by combining with BI-RADS, and then comparing the diagnostic performances with BI-RADS alone.

Materials And Methods: This multicenter, prospective study enrolled participants with breast lesions from June 2021 to November 2022. A development cohort (DC) and validation cohort (VC) were established.

Reconstruction of Water-Filled Pipe Ultrasonic Guided Wave Signals in the Distance Domain by Orthogonal Matching Pursuit Based on Dispersion and Multi-Mode.

Ultrasonic guided waves (UGWs) in water-filled pipes are subject to more severe dispersion and attenuation than vacant pipes, posing significant challenges for defect identification and localization. To this end, a novel sparse signal decomposition method called orthogonal matching pursuit based on dispersion and multi-mode (DMOMP) was proposed, which utilizes the second-order asymptotic solution of dispersion curves and the conversion characteristics of asymmetric UGWs in the defect contact stage to reconstruct the dispersive signals and converts the time-domain dispersive signals to distance-domain non-dispersive signals by dispersion compensated time-distance mapping. The synthesized simulation results indicate that DMOMP not only exhibits higher reconstruction accuracy compared to OMP, but also reveals more accurate and stable mode recognition and localization compared to DOMP, which only considers the dispersion under perturbation and noise.

Different responses of the rhizosphere microbiome to infection in two cotton cultivars.

Verticillium wilt is a disastrous disease caused by that severely damages the production of cotton in China. Even under homogeneous conditions, the same cotton cultivar facing tends to either stay healthy or become seriously ill and die. This binary outcome may be related to the interactions between microbiome assembly and plant health.

Genetic Mapping and Analysis of a Compact Plant Architecture and Precocious Mutant in Upland Cotton.

With the promotion and popularization of machine cotton-picking, more and more attention has been paid to the selection of early-maturity varieties with compact plant architecture. The type of fruit branch is one of the most important factors affecting plant architecture and early maturity of cotton. Heredity analysis of the cotton fruit branch is beneficial to the breeding of machine-picked cotton.

High-density genetic variation maps reveal the correlation between asymmetric interspecific introgressions and improvement of agronomic traits in Upland and Pima cotton varieties developed in Xinjiang, China.

The two new world tetraploid cottons, Gossypium hirsutum and Gossypium barbadense, are cultivated worldwide and are characterised by a high yield and superior fibre quality, respectively. Historical genetic introgression has been reported between them; however, the existence of introgression and its genetic effects on agronomic traits remain unclear with regard to independent breeding of G. hirsutum (Upland cotton) and G.

Effects of Non-Covalent Functionalized Graphene Oxide with Hyperbranched Polyesters on Mechanical Properties and Mechanism of Epoxy Composites.

In order to improve the interfacial properties of graphene oxide (GO) and epoxy resin (EP), hyperbranched polyesters with terminal carboxyl (HBP) non-covalently functionalized graphene oxide (HBP-GO) was achieved by strong π-π coupling between hyperbranched polyesters and GO nanosheets. The effects of non-covalent functionalization of GO on the dispersibility, wettability and interfacial properties were analyzed. The mechanical properties and enhancement mechanism of HBP-GO/EP composites were investigated.