98%
921
2 minutes
20
As research progresses, the surface texture tool can significantly reduce the cutting heat and cutting force. However, the tool surface texture width, depth, and spacing also have an impact on the cutting performance. Using the Taguchi method and finite element analysis, the changing laws of cutting temperature, pressure, stress distribution, and cutting force were studied. The results showed that the tool texture width had the greatest influence on the cutting performance, followed by the tool texture depth and spacing. The increase of tool texture width lead to the decrease of cutting temperature, stress distribution, and cutting force, while the effect of texture depth on cutting stress distribution was more significant. Cutting performance could be improved by optimizing the texture size and structure of the cutting tool. This research has theoretical significance for improving the cutting performance of cutting tools.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9317305 | PMC |
http://dx.doi.org/10.3390/mi13071091 | DOI Listing |
Biomaterials
August 2025
Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA, 90095, USA. Electronic address:
Wearable bioelectronics have transformed modern biomedical applications by enabling seamless integration with biological tissues, providing continuous, comprehensive, and personalized healthcare. Skin cancer, particularly melanoma, poses a significant clinical challenge due to its high metastatic potential and associated mortality. Traditional diagnostic approaches face limitations in accuracy, accessibility, and reproducibility, while existing treatments are often constrained by systemic toxicity and therapeutic resistance.
View Article and Find Full Text PDFAppl Biochem Biotechnol
September 2025
School of Biological Sciences, University of the Punjab, Quaid-E-Azam Campus, P.O. 54590, Lahore, Pakistan.
Recombinant DNA technology is widely used to produce industrially and pharmaceutically important proteins. In silico analysis, performed before executing wet lab experiments has been greatly helpful in this connection. A shift in protein analysis has been observed over the past decade, driven by advancements in bioinformatics databases, tools, software, and web servers.
View Article and Find Full Text PDFAdv Mater
September 2025
Suzhou Institute of Nano-tech and Nano-bionics, Chinese Academy of Sciences, Suzhou, 215123, P. R. China.
Despite significant advancements in aerogels science, the fabrication of high-performance aerogels with their plastic processability remains unexplored owing to their inherent trade-off between skeletal rigidity and transformable processability. Herein, a universal solubility-pKa coupling-effect to engineer high-performance thermoplastic nylon aerogel family with excellent thermomechanical processing performance is proposed. By modulating solubility parameters and acid dissociation constants in nylon-solvent systems, it is precisely control crystallization to assemble interlaced 1D nanofiber skeletons, yielding nylon aerogels that integrate a high specific surface area (226 m g), exceptional compressive modulus (12.
View Article and Find Full Text PDFClin Nutr ESPEN
September 2025
Department of Pediatrics, School of Medicine, Arak University of Medical Sciences, Arak, Iran.
Background And Aims: The increasing number of non-communicable diseases, such diabetes and obesity, makes it even more important to have accurate and personalized dietary solutions. Based on a lot of research, standard diet advice may not be accurate enough to meet individual health demands. The Intelligent Diet Recommendation System is an artificial intelligence-powered platform that gives personalized dietary recommendations based on extensive body composition data and cultural eating habits.
View Article and Find Full Text PDFRep Pract Oncol Radiother
August 2025
University Teaching Department, Chhattisgarh Swami Vivekanand Technical University, Bhilai, India.
Cervical cancer continues to pose a significant global health challenge, highlighting the urgent need for accurate and efficient diagnostic techniques. Recent progress in deep learning has demonstrated considerable potential in improving the detection and classification of cervical cancer. This review presents a thorough analysis of deep learning methods utilized for cervical cancer diagnosis, with an emphasis on critical approaches, evaluation metrics, and the ongoing challenges faced in the field.
View Article and Find Full Text PDF