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To improve the scientific accuracy and precision of children's physical fitness evaluations, this study proposes a model that combines self-organizing maps (SOM) neural networks with cluster analysis. Existing evaluation methods often rely on traditional, single statistical analyses, which struggle to handle the complexity of high-dimensional, nonlinear data, resulting in a lack of precision and personalization. This study uses the SOM neural network to reduce the dimensionality of high-dimensional health data.

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G-SET-DCL: a guided sequential episodic training with dual contrastive learning approach for colon segmentation.

Int J Comput Assist Radiol Surg

January 2025

Computer Vision and Image Processing Lab., UofL, Louisville, KY, 40292, USA.

Purpose: This article introduces a novel deep learning approach to substantially improve the accuracy of colon segmentation even with limited data annotation, which enhances the overall effectiveness of the CT colonography pipeline in clinical settings.

Methods: The proposed approach integrates 3D contextual information via guided sequential episodic training in which a query CT slice is segmented by exploiting its previous labeled CT slice (i.e.

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The carbon footprint associated with cement production, coupled with depletion of natural resources and climate change, underscores the need for sustainable alternatives. This study explores the effect of metakaolin (MK) and nano-silica (NS) on concrete's engineering performance and environmental impact. Initially, compressive, tensile, and flexural strength tests, along with durability assessments like water absorption, sorptivity, rapid chloride permeability, and resistance to acid and sulphate attacks, were conducted.

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Charge-transfer complexation of coordination cages for enhanced photochromism and photocatalysis.

Nat Commun

January 2025

State Key Laboratory of Petroleum Molecular & Process Engineering, Shanghai Key Laboratory of Green Chemistry and Chemical Processes, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai, China.

Intensified host-guest electronic interplay within stable metal-organic cages (MOCs) presents great opportunities for applications in stimuli response and photocatalysis. Zr-MOCs represent a type of robust discrete hosts for such a design, but their host-guest chemistry in solution is hampered by the limited solubility. Here, by using pyridinium-derived cationic ligands with tetrakis(3,5-bis(trifluoromethyl)phenyl)borate (BAr) as solubilizing counteranions, we report the preparation of soluble Zr-MOCs of different shapes (1-4) that are otherwise inaccessible through a conventional method.

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Finite element investigation for improving chest wall reconstruction process using ceramic and polymeric implants.

Sci Rep

January 2025

Biomedical Engineering Department, Faculty of Engineering, Helwan University, Cairo, Egypt.

Car accidents, infections caused by bacteria or viruses, metastatic lesions, tumors, and malignancies are the most frequent causes of chest wall damage, leading to the removal of the affected area. After excision, artificial bone or synthetic materials are used in chest wall reconstruction to restore the skeletal structure of the chest. Chest implants have traditionally been made from metallic materials like titanium alloys due to their biocompatibility and durability.

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