Collaborative optimization of phase and amplitude of composite signals for acousto-optic beam splitting technology.

Multi-frequency acousto-optic beam splitting plays a significant role in many laser applications due to its advantages of inertia free, fast refreshing speed and high-precision controllable light intensity and direction. How to reduce the intermodulation distortion and improve the uniformity of the beam splitting intensity has become an intensive issue. This paper proposes the collaborative optimization method to co-optimize of the phase and amplitude of acousto-optic device multi-frequency composite signals, which can eliminate the nonlinear distortion of the amplification of multi-frequency composite signals and increase the energy utilization rate and accuracy of intensity control for each sub-beam.

Image Analysis-Based Machine Learning for the Diagnosis of Retinopathy of Prematurity: A Meta-analysis and Systematic Review.

Topic: To evaluate the performance of machine learning (ML) in the diagnosis of retinopathy of prematurity (ROP) and to assess whether it can be an effective automated diagnostic tool for clinical applications.

Clinical Relevance: Early detection of ROP is crucial for preventing tractional retinal detachment and blindness in preterm infants, which has significant clinical relevance.

Methods: Web of Science, PubMed, Embase, IEEE Xplore, and Cochrane Library were searched for published studies on image-based ML for diagnosis of ROP or classification of clinical subtypes from inception to October 1, 2022.

Establishment and validation of a nomogram for predicting immune-related prognostic features in trunk melanoma-specific death.

Background: Trunk melanoma is one of the most common and deadly types of melanomas. Multiple factors are associated with the prognosis of patients with trunk melanoma. Currently, direct, and reliable clinical tools for early assessment of individual specific risk of death are limited, and most of them are prediction models for all-cause death.

Modification of Frictional Properties of Hydrogel Surface via Laser Ablated Topographical Micro-Textures.

Hydrogels and biological cartilage tissues are highly similar in structure and composition due to their unique characteristics such as high-water content and low friction coefficients. The introduction of hydrogel cartilage can effectively reduce the friction coefficient and wear coefficient of the original bone joint and the implanted metal bone joint (generally titanium alloy or stainless steel), which is considered as a perfect replacement material for artificial articular cartilage. How to accurately regulate the local tribological characteristics of hydrogel artificial cartilage according to patient weight and bone shape is one of the important challenges in the current clinical application field of medical hydrogels.

Distinguish the Value of the Benign Nevus and Melanomas Using Machine Learning: A Meta-Analysis and Systematic Review.

Background: Melanomas, the most common human malignancy, are primarily diagnosed visually, beginning with an initial clinical screening and followed potentially by dermoscopic analysis, a biopsy, and histopathological examination. We aimed to systematically review the performance and quality of machine learning-based methods in distinguishing melanoma and benign nevus in the relevant literature.

Method: Four databases (Web of Science, PubMed, Embase, and the Cochrane library) were searched to retrieve the relevant studies published until March 26, 2022.

Printed Diodes: Materials Processing, Fabrication, and Applications.

Printing techniques for the fabrication of diodes have received increasing attention over the last decade due to their great potential as alternatives for high-throughput and cost-effective manufacturing approaches compatible with both flexible and rigid substrates. Here, the progress achieved and the challenges faced in the fabrication of printed diodes are discussed and highlighted, with a focus on the materials of significance (silicon, metal oxides, nanomaterials, and organics), the techniques utilized for ink deposition (gravure printing, screen printing, inkjet printing, aerosol jet printing, etc.), and the process through which the printed layers of diode are sintered after printing.

Recent Advances in Stretchable Supercapacitors Enabled by Low-Dimensional Nanomaterials.

Supercapacitors (SCs) have shown great potential for mobile energy storage technology owing to their long-term durability, electrochemical stability, structural simplicity, as well as exceptional power density without much compromise in the energy density and cycle life parameters. As a result, stretchable SC devices have been incorporated in a variety of emerging electronics applications ranging from wearable electronic textiles to microrobots to integrated energy systems. In this review, the recent progress and achievements in the field of stretchable SCs enabled by low-dimensional nanomaterials such as polypyrrole, carbon nanotubes, and graphene are presented.