We propose an efficient scheme for parametric fitting expressed in terms of the Legendre polynomials. For continuous systems, our scheme is exact and the derived explicit expression is very helpful for further analytical studies. For discrete systems, our scheme is almost as accurate as the method of singular value decomposition. Through a few numerical examples, we show that our algorithm costs much less CPU time and memory space than the method of singular value decomposition. Thus, our algorithm is very suitable for a large amount of data fitting. In addition, the proposed scheme can also be used to extract the global structure of fluctuating systems. We then derive the exact relation between the correlation function and the detrended variance function of fluctuating systems in arbitrary dimensions and give a general scaling analysis.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1103/PhysRevE.78.011112 | DOI Listing |
Zhonghua Wei Zhong Bing Ji Jiu Yi Xue
December 2024
Department of Critical Care Medicine, the Second Affiliated Hospital of Xingtai Medical College, Xingtai 054000, Hebei, China.
Objective: To construct a risk prediction model for elderly severe patients with pneumonia infection, and analyze the prevention effect of 1M3S nursing plan under early warning mode.
Methods: Firstly, 180 elderly severe patients admitted to the department of intensive care unit (ICU) of the Second Affiliated Hospital of Xingtai Medical College from September 2020 to September 2021 were enrolled. Their clinical data were collected and retrospectively analyzed, and they were divided into infected group and non-infected group according to whether they developed severe pneumonia.
ACS Appl Mater Interfaces
January 2025
Institute of Optoelectronic Technology, Fuzhou University, Fuzhou 350116, China.
Anticounterfeiting technologies meet challenges in the Internet of Things era due to the rapidly growing volume of objects, their frequent connection with humans, and the accelerated advance of counterfeiting/cracking techniques. Here, we, inspired by biological fingerprints, present a simple anticounterfeiting system based on perovskite quantum dot (PQD) fingerprint physical unclonable function (FPUF) by cooperatively utilizing the spontaneous-phase separation of polymers and selective in situ synthesis PQDs as an entropy source. The FPUFs offer red, green, and blue full-color fingerprint identifiers and random three-dimensional (3D) morphology, which extends binary to multivalued encoding by tuning the perovskite and polymer components, enabling a high encoding capacity (about 10, far surpassing that of biometric fingerprints).
View Article and Find Full Text PDFAppl Clin Inform
January 2025
Institute for Artificial Intelligence in Medicine, University Hospital Essen, Essen, Germany.
Objective: Commercially available large language models such as Chat Generative Pre-Trained Transformer (ChatGPT) cannot be applied to real patient data for data protection reasons. At the same time, de-identification of clinical unstructured data is a tedious and time-consuming task when done manually. Since transformer models can efficiently process and analyze large amounts of text data, our study aims to explore the impact of a large training dataset on the performance of this task.
View Article and Find Full Text PDFEnviron Sci Pollut Res Int
January 2025
Materials Industrial Research and Technology Center S.A. - Environmental Lab, 76thKm of Athens-Lamia National Road, 32009, Schimatari, Greece.
The assessment of soil contamination by heavy metals is of high importance due to its impact on the environment and human health. Standard high-sensitivity spectroscopic techniques for this task such as atomic absorption spectrometry (AAS) and inductively coupled plasma spectrometry (ICP-OES and ICP-MS) are effective but time-consuming and costly, mainly due to sample preparation and lab consumables, respectively. In the present study, a laser-based spectroscopic approach is proposed, laser-induced breakdown spectroscopy (LIBS), which, combined with machine learning (ML), can provide a tool for rapid assessment of soil contamination by heavy metals.
View Article and Find Full Text PDFNanoscale
January 2025
Department of Chemistry, Faculty of Science, Umm Al-Qura University, 21955 Makkah, Saudi Arabia.
With the growing threat of organic pollutants in water bodies, there is an urgent need for sustainable and efficient water decontamination methods. This research focused on synthesizing a novel Z-scheme ternary heterostructure composed of graphene oxide (GO)-mediated polyaniline (PANI) with α-FeO and investigated its potential in brilliant green (BrG) and ciprofloxacin (CIP) degradation tests under visible light. The ternary composite demonstrated exceptional photocatalytic activity, with the optimized 10%PANI/GO/α-FeO (10PGF) photocatalyst achieving 99.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!