Embedded Operating Systems (OSs) are often developed in the C programming language. Developers justify this choice by the performance that can be achieved, the low memory footprint, and the ease of mapping hardware to software, as well as the strong adoption by industry of this programming language. The downside is that C is prone to security vulnerabilities unknowingly introduced by the software developer. Examples of such vulnerabilities are use-after-free, and buffer overflows. Like C, Rust is a compiled programming language that guarantees memory safety at compile time by adhering to a set of rules. There already exist a few OSs and frameworks that are entirely written in Rust, targeting sensor nodes. In this work, we give an overview of these OSs and frameworks and compare them on the basis of the features they provide, such as application isolation, scheduling, inter-process communication, and networking. Furthermore, we compare the OSs on the basis of the performance they provide, such as cycles and memory usage.
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http://dx.doi.org/10.3390/s24175818 | DOI Listing |
J Environ Manage
January 2025
Geotechnologies in Soil Sciences Research Group - GeoCiS, Department of Soil Science, Luiz de Queiroz College of Agriculture - Esalq, University of São Paulo - USP, Piracicaba, São Paulo, Brazil. Electronic address:
Analyzing soil in large and remote areas such as the Amazon River Basin (ARB) is unviable when it is entirely performed by wet labs using traditional methods due to the scarcity of labs and the significant workforce requirements, increasing costs, time, and waste. Remote sensing, combined with cloud computing, enhances soil analysis by modeling soil from spectral data and overcoming the limitations of traditional methods. We verified the potential of soil spectroscopy in conjunction with cloud-based computing to predict soil organic carbon (SOC) and particle size (sand, silt, and clay) content from the Amazon region.
View Article and Find Full Text PDFJMIR Public Health Surveill
January 2025
Division of Global HIV and TB, Centers for Disease Control and Prevention, 1600 Clifton Rd, Atlanta, GA, 30322, United States, 1 8103383534.
Background: Population size estimation (PSE) for key populations is needed to inform HIV programming and policy.
Objective: This study aimed to examine the utility of applying a recently proposed method using Google Trend (GT) internet search data to generate PSE (Google Trends Population Size Estimate [GTPSE]) for men who have sex with men (MSM) in 54 countries in Africa, Asia, the Americas, and Europe.
Methods: We examined GT relative search volumes (representing the relative internet search frequency of specific search terms) for "porn" and, as a comparator term, "gay porn" for the year 2020.
Front Oncol
December 2024
Department of Pharmacy, Xinjiang Key Laboratory of Neurological Diseases, Xinjiang Clinical Research Center for Nervous System Diseases, Second Affiliated Hospital of Xinjiang Medical University, Ürümqi, Xinjiang, China.
Purpose: This study seeks to systematically analyze the research literature pertaining to breast cancer surgery from 2010 to 2024, as indexed in the PubMed database, employing bibliometric methodologies.
Methods: Employing the "bibliometrix" package in the R programming language, alongside VOSviewer and CiteSpace software, this research conducted a comprehensive visual analysis of 1,195 publications. The analysis encompassed publication trends, collaborative networks, journal evaluation, author and institutional assessments, country-specific analyses, keyword exploration, and the identification of research hotspots.
J Cheminform
January 2025
Research Programme On Biomedical Informatics (GRIB), Department of Medicine and Life Sciences, Universitat Pompeu Fabra, Hospital del Mar Medical Research Institute, Barcelona, Spain.
This article introduces StreamChol, a software for developing and applying mechanistic models to predict cholestasis. StreamChol is a Streamlit application, usable as a desktop application or web-accessible software when installed on a server using a docker container.StreamChol allows a seamless integration of pharmacokinetic analyses with Machine Learning models.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Clinical Pharmacy, School of Pharmacy, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia.
Integrating machine learning (ML) models into healthcare systems is a rapidly evolving field with the potential to revolutionize care delivery. This study aimed to classify fertility rates and identify significant predictors using ML models among reproductive women in Ethiopia. This study utilized eight ML models in 5864 reproductive-age women using Ethiopian Demographic Health Survey (EDHS), 2019 data.
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