Generic characterization method for nano-gratings using deep-neural-network-assisted ellipsometry.

As a non-destructive and rapid technique, optical scatterometry has gained widespread use in the measurement of film thickness and optical constants. The recent advances in deep learning have presented new and powerful approaches to the resolution of inverse scattering problems. However, the application of deep-neural-network-assisted optical scatterometry for nanostructures still faces significant challenges, including poor stability, limited functionalities, and high equipment requirements.

A deep learning-based method enables the automatic and accurate assembly of chromosome-level genomes.

The application of high-throughput chromosome conformation capture (Hi-C) technology enables the construction of chromosome-level assemblies. However, the correction of errors and the anchoring of sequences to chromosomes in the assembly remain significant challenges. In this study, we developed a deep learning-based method, AutoHiC, to address the challenges in chromosome-level genome assembly by enhancing contiguity and accuracy.

Contralateral renal change in a unilateral ureteral obstruction rat model using intravoxel incoherent motion diffusion-weighted imaging.

Objectives: Most functional magnetic resonance research has primarily examined alterations in the affected kidney, often neglecting the contralateral kidney. Our study aims to investigate whether imaging parameters accurately depict changes in both the renal cortex and medulla in a unilateral ureteral obstruction rat model, thereby showcasing the utility of intravoxel incoherent motion (IVIM) in evaluating contralateral renal changes.

Methods: Six rats underwent MR scans and were subsequently sacrificed for baseline histological examination.

Nanoimprint-induced strain engineering of two-dimensional materials.

The high stretchability of two-dimensional (2D) materials has facilitated the possibility of using external strain to manipulate their properties. Hence, strain engineering has emerged as a promising technique for tailoring the performance of 2D materials by controlling the applied elastic strain field. Although various types of strain engineering methods have been proposed, deterministic and controllable generation of the strain in 2D materials remains a challenging task.

Clinical and imaging predictors for hemorrhagic transformation of acute ischemic stroke after endovascular thrombectomy.

Background And Purpose: Hemorrhagic transformation (HT) is a common complication of endovascular thrombectomy (EVT) in patients with acute ischemic stroke (AIS). Our study aims to investigate the clinical and imaging predictors of HT and symptomatic intracranial hemorrhage (sICH) in patients who underwent EVT.

Methods: A retrospective analysis of 118 patients undergoing EVT for acute anterior circulation stroke was performed.

The Competing Endogenous RNAs Regulatory Genes Network Mediates Leaf Shape Variation and Main Effector Gene Function in Mulberry Plant ().

Mulberry plants () have leaf shapes, ranging from unlobed to lobed, which are crucial for yield, growth, and adaptability, indicating their ability to adapt to their environment. Competing endogenous RNAs (ceRNAs) constitute a web of RNAs within the organism's transcriptional regulatory system, including protein-coding genes (mRNAs), microRNAs (miRNAs), long non-coding RNAs (lncRNAs), circular RNAs (circRNAs), and others. In this study, samples for ceRNA sequencing were categorized into two groups: whole leaves and lobed leaves, each group with three replicates.

Multi-Level Optimization for Data-Driven Camera-LiDAR Calibration in Data Collection Vehicles.

Accurately calibrating camera-LiDAR systems is crucial for achieving effective data fusion, particularly in data collection vehicles. Data-driven calibration methods have gained prominence over target-based methods due to their superior adaptability to diverse environments. However, current data-driven calibration methods are susceptible to suboptimal initialization parameters, which can significantly impact the accuracy and efficiency of the calibration process.

The impact of boron nutrient supply in mulberry (Morus alba) response to metabolomics, enzyme activities, and physiological parameters.

Boron (B) is essential for normal and healthy plant growth. Therefore, Boron stress is a common abiotic stress that limits plant growth and productivity. However, how mulberry copes with boron stress remains unclear.

A molecular atlas reveals the tri-sectional spinning mechanism of spider dragline silk.

The process of natural silk production in the spider major ampullate (Ma) gland endows dragline silk with extraordinary mechanical properties and the potential for biomimetic applications. However, the precise genetic roles of the Ma gland during this process remain unknown. Here, we performed a systematic molecular atlas of dragline silk production through a high-quality genome assembly for the golden orb-weaving spider Trichonephila clavata and a multiomics approach to defining the Ma gland tri-sectional architecture: Tail, Sac, and Duct.