Zobrazeno 71 - 80
of 261
pro vyhledávání: ''
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-17 (2024)
Abstract Energy consumption of constructed educational facilities significantly impacts economic, social and environment sustainable development. It contributes to approximately 37% of the carbon dioxide emissions associated with energy use and proce
Externí odkaz:
https://doaj.org/article/8b907f2717b548ccae630e91819e55a9
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-12 (2024)
Abstract Predicting physical properties of complex multi-scale systems is a common challenge and demands analysis of various temporal and spatial scales. However, physics alone is often not sufficient due to lack of knowledge on certain details of th
Externí odkaz:
https://doaj.org/article/5b74438be157410abce20b73a90d2fae
Autor:
Sayed Gomaa, Mohamed Abdalla, Khalaf G. Salem, Karim Nasr, Ramadan Emara, Qingsheng Wang, A. N. El-hoshoudy
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-42 (2024)
Abstract The accurate estimation of gas viscosity remains a pivotal concern for petroleum engineers, exerting substantial influence on the modeling efficacy of natural gas operations. Due to their time-consuming and costly nature, experimental measur
Externí odkaz:
https://doaj.org/article/276309e49ec1445da40425975f7c28b6
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-11 (2024)
Abstract In this work, we combine the advantages of virtual Small Angle Neutron Scattering (SANS) experiments carried out by Monte Carlo simulations with the recent advances in computer vision to generate a tool that can assist SANS users in small an
Externí odkaz:
https://doaj.org/article/d3b8626e67524383b5bf2bef1cf34c04
Autor:
Marcello Di Giammarco, Fabio Martinelli, Antonella Santone, Mario Cesarelli, Francesco Mercaldo
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-11 (2024)
Abstract Early detection of the adenocarcinoma cancer in colon tissue by means of explainable deep learning, by classifying histological images and providing visual explainability on model prediction. Considering that in recent years, deep learning t
Externí odkaz:
https://doaj.org/article/ccc9a3ce6fc54db184bff451d3f4866b
Autor:
Nguyen Ky Anh, Nguyen Ky Phat, Nguyen Quang Thu, Nguyen Tran Nam Tien, Cho Eunsu, Ho-Sook Kim, Duc Ninh Nguyen, Dong Hyun Kim, Nguyen Phuoc Long, Jee Youn Oh
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-12 (2024)
Abstract Nontuberculous mycobacteria (NTM) infection diagnosis remains a challenge due to its overlapping clinical symptoms with tuberculosis (TB), leading to inappropriate treatment. Herein, we employed noninvasive metabolic phenotyping coupled with
Externí odkaz:
https://doaj.org/article/de915f3b0bdb4d9dafe37f8e2f10215a
Autor:
Muhammad Faisal Javed, Majid Khan, Muhammad Fawad, Hisham Alabduljabbar, Taoufik Najeh, Yaser Gamil
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-25 (2024)
Abstract The use of waste foundry sand (WFS) in concrete production has gained attention as an eco-friendly approach to waste reduction and enhancing cementitious materials. However, testing the impact of WFS in concrete through experiments is costly
Externí odkaz:
https://doaj.org/article/6aa3d3f00c1c445abe03006f49bddcd2
Autor:
Hooman H. Rashidi, Aamer Ikram, Luke T. Dang, Adnan Bashir, Tanzeel Zohra, Amna Ali, Hamza Tanvir, Mohammad Mudassar, Resmi Ravindran, Nasim Akhtar, Rana I. Sikandar, Mohammed Umer, Naeem Akhter, Rafi Butt, Brandon D. Fennell, Imran H. Khan
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-9 (2024)
Abstract Accurate screening of COVID-19 infection status for symptomatic patients is a critical public health task. Although molecular and antigen tests now exist for COVID-19, in resource-limited settings, screening tests are often not available. Fu
Externí odkaz:
https://doaj.org/article/4adbf614c982480c9cf92dc0df122c95
Autor:
Wenwei Zuo, Xuelian Yang
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-8 (2024)
Abstract Stroke is the leading cause of death and disability worldwide. Cadmium is a prevalent environmental toxicant that may contribute to cardiovascular disease, including stroke. We aimed to build an effective and interpretable machine learning (
Externí odkaz:
https://doaj.org/article/7bf5deea7b9e4dc2aff5916cb5cf0efd
Autor:
Cheng-Chun Lee, Lipai Huang, Federico Antolini, Matthew Garcia, Andrew Juan, Samuel D. Brody, Ali Mostafavi
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-12 (2024)
Abstract Timely, accurate, and reliable information is essential for decision-makers, emergency managers, and infrastructure operators during flood events. This study demonstrates that a proposed machine learning model, MaxFloodCast, trained on physi
Externí odkaz:
https://doaj.org/article/b9de94c31408443e8782d15020a1e664