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Alkali and sulfate effects on mechanical properties and microscopic mechanisms of slag and fly ash geopolymers.
Sci Rep
January 2025
College of Hydraulic and Civil Engineering, Xinjiang Agricultural University, Urumqi, 830052, Xinjiang, People's Republic of China.
Aiming at the problem that it is difficult to realize low-cost, high-performance and large-scale utilization of cementitious materials prepared from bulk solid wastes, this paper constructs a set of composite cementitious system based on alkaline activation of slag and fly ash (FA) by calcium carbide slag (CCS) and synergistic activation of sodium sulfate (NaSO) as a chemical dopant. The influence of factors such as solid waste type, mixing ratio, and NaSO content on the mechanical properties of composite cementitious systems was investigated by assessing compressive strength and analyzing microstructure using XRD, SEM-EDS, and FTIR. The test results indicate that CCS and NaSO exert significant influences on the strength of the composite cementitious system.
View Article and Find Full Text PDFAcetonemic vomiting: a potential complication of treatment with glucagon-like peptide-1 receptor agonists especially in lean type 2 diabetes patients.
Diabetol Int
January 2025
Division of Diabetes and Metabolic Diseases, Department of Internal Medicine, Nihon University School of Medicine, 30-1 Oyaguchi Kami-cho, Itabashi-ku, Tokyo 173-8610 Japan.
Objectives: Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) are now widely used for treating type 2 diabetes mellitus (T2DM) and obesity. We examined their association with acetonemic vomiting, especially when given to patients with low body weight, in hopes of achieving early recognition of this complication which is potentially life-threatening if not dealt with appropriately.
Methods: Cases identified incidentally are described and discussed referring to prior reports.
Identification of strengths and weaknesses of the healthcare system for persons living with rare diseases in Catalonia (Spain), and recommendations to improve its comprehensive attention: the "acERca las enfermedades raras" project.
Orphanet J Rare Dis
January 2025
Laboratory of Neurogenetics and Molecular Medicine, Center for Genomic Sciences in Medicine, Institut de Recerca Sant Joan de Déu, Únicas SJD Center, Hospital Sant Joan de Déu, Barcelona, Spain.
Background: Rare diseases (RDs) are a heterogeneous group of complex and low-prevalence conditions in which the time to establish a definitive diagnosis is often too long. In addition, for most RDs, few to no treatments are available and it is often difficult to find a specialized care team.
Objectives: The project "acERca las enfermedades raras" (in English: "bringing RDs closer") is an initiative primary designed to generate a consensus by a multidisciplinary group of experts to detect the strengths and weaknesses in the public healthcare system concerning the comprehensive care of persons living with a RD (PLWRD) in the region of Catalonia, Spain, where a Network of Clinical Expert Units (Xarxa d'Unitats de Expertesa Clínica or XUEC) was created and is being implemented since 2015.
Re-locative guided search optimized self-sparse attention enabled deep learning decoder for quantum error correction.
Sci Rep
January 2025
Department of Mathematics, School of Advanced Sciences, VIT-AP University, Besides AP Secretariate, Amaravati, Andhra Pradesh, 522237, India.
Heavy hexagonal coding is a type of quantum error-correcting coding in which the edges and vertices of a low-degree graph are assigned auxiliary and physical qubits. While many topological code decoders have been presented, it is still difficult to construct the optimal decoder due to leakage errors and qubit collision. Therefore, this research proposes a Re-locative Guided Search optimized self-sparse attention-enabled convolutional Neural Network with Long Short-Term Memory (RlGS2-DCNTM) for performing effective error correction in quantum codes.
View Article and Find Full Text PDFIdentification and information acquisition of high-value construction solid waste combined millimeter-wave radar and convolutional neural networks.
Waste Manag
January 2025
School of Transportation Science and Engineering, Harbin Institute of Technology, Harbin 150090, China. Electronic address:
The accumulation of construction solid waste (CSW) leads to the waste of land resources and environmental pollution, becoming a significant social problem. Identifying the amount of high-value CSW is essential for assessing the value of accumulated CSW and formulating appropriate recycling strategies. With the development of machine learning technology, CSW recognition techniques combining image acquisition devices and convolutional neural networks have been widely applied.
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