Featured
-
-
Article
| Open AccessSelective knowledge sharing for privacy-preserving federated distillation without a good teacher
While federated learning is promising for efficient collaborative learning without revealing local data, it remains vulnerable to white-box privacy attacks, suffers from high communication overhead, and struggles to adapt to heterogeneous models. Here, the authors show a federated distillation method to tackle these challenges, which leverages the strengths of knowledge distillation in a federated learning setting.
- Jiawei Shao
- , Fangzhao Wu
- & Jun Zhang
-
Article
| Open AccessCost-effectiveness requirements for implementing artificial intelligence technology in the Women’s UK Breast Cancer Screening service
AI technology has the potential to substitute a human reader to aid services struggling to recruit staff or meet patient demand. Here, the authors show that the technology is a viable and potentially cost-effective strategy for use in the NHS.
- Armando Vargas-Palacios
- , Nisha Sharma
- & Gurdeep S. Sagoo
-
Article
| Open AccessDigital twin based monitoring and control for DC-DC converters
In this work, authors explore DC-DC converter monitoring and control and demonstrate a generalizable digital twin based buck converter system that enables dynamic synchronization even under reference value changes, physical system model variation, and physical controller failure.
- Zhongcheng Lei
- , Hong Zhou
- & Guo-Ping Liu
-
Article
| Open AccessTruck platooning reshapes greenhouse gas emissions of the integrated vehicle-road infrastructure system
Truck platooning allows for trucks to travel synchronously in close proximity to improve fuel efficiency. Here, authors evaluate the decarbonization effects of platooning on the vehicle-road system at a large-scale road network level revealing a trade-off between emission reduction and cost rise.
- Huailei Cheng
- , Yuhong Wang
- & Tian Jin
-
Comment
| Open AccessToward the effective and fair funding of CO2 removal technologies
Carbon dioxide removal technologies are gaining prominence in academia, industry and policy, yet the need for substantial funding raises serious challenges. This comment discusses these issues and offers suggestions for future funding efforts in this area.
- Matthias Honegger
-
Article
| Open AccessTechnology readiness levels for machine learning systems
The development of machine learning systems has to ensure their robustness and reliability. The authors introduce a framework that defines a principled process of machine learning system formation, from research to production, for various domains and data scenarios.
- Alexander Lavin
- , Ciarán M. Gilligan-Lee
- & Yarin Gal
-
Comment
| Open AccessA Just Digital framework to ensure equitable achievement of the Sustainable Development Goals
While the technological revolution is accelerating, digital poverty is undermining the Sustainable Development Goals. This article introduces a justice-oriented digital framework which considers how fair access to digital capabilities, commodities, infrastructure, and governance can reduce global inequality and advance the SDGs.
- Katriona O’Sullivan
- , Serena Clark
- & Malcolm MacLachlan
-
Article
| Open AccessNeutral bots probe political bias on social media
Social media platforms moderating misinformation have been accused of political bias. Here, the authors use neutral social bots to show that, while there is no strong evidence for such a bias, the content to which Twitter users are exposed depends strongly on the political leaning of early Twitter connections.
- Wen Chen
- , Diogo Pacheco
- & Filippo Menczer
-
Article
| Open AccessEfficiency stagnation in global steel production urges joint supply- and demand-side mitigation efforts
The effectiveness of large historical efforts for decarbonizing steel production is unclear. Here, the authors show that such efficiency gains were offset by a booming steel demand increase. This has led to a stagnating decarbonization progress over past decades, which jeopardizes realization of future climate targets.
- Peng Wang
- , Morten Ryberg
- & Wei-Qiang Chen
-
Article
| Open AccessMarket-oriented job skill valuation with cooperative composition neural network
The value assessment of job skills is critical for companies to select and retain the right talent and for individuals to develop them. Here the authors show that a data-driven method based on an enhanced neural network can assign meaningful value to job skills in a quantitative way and outperforms benchmark models for job salary prediction.
- Ying Sun
- , Fuzhen Zhuang
- & Hui Xiong
-
Article
| Open AccessPattern recognition based on machine learning identifies oil adulteration and edible oil mixtures
Fraudulent adulteration of edible oils is based on the fact that their characteristic fatty acid profile can be mimicked with mixtures of other oil types. Here, the authors use a deep learning method to uncover fatty acid patterns discriminative for ten different plant oil types and to discern composition of mixtures.
- Kevin Lim
- , Kun Pan
- & Rong Hui Xiao
-
Article
| Open AccessThe spread of low-credibility content by social bots
Online misinformation is a threat to a well-informed electorate and undermines democracy. Here, the authors analyse the spread of articles on Twitter, find that bots play a major role in the spread of low-credibility content and suggest control measures for limiting the spread of misinformation.
- Chengcheng Shao
- , Giovanni Luca Ciampaglia
- & Filippo Menczer
-
Article
| Open AccessSerendipity and strategy in rapid innovation
Organizations can take different approaches to innovation: they can either follow a strategic process or a serendipitous perspective. Here Fink et al. develop a statistical model to analyse how components combine to obtain a product and thus explain the mechanism behind the two approaches.
- T. M. A. Fink
- , M. Reeves
- & R. S. Farr
-
Article
| Open AccessPrinting of small molecular medicines from the vapor phase
Traditional approaches used in the pharmaceutical industry are not precise or versatile enough for customized medicine formulation and manufacture. Here the authors produce a method to form coatings, with accurate dosages, as well as a means of closely controlling dissolution kinetics.
- Olga Shalev
- , Shreya Raghavan
- & Max Shtein
-
Article
| Open AccessLife cycle assessment needs predictive spatial modelling for biodiversity and ecosystem services
Life cycle assessments are used by corporations to determine the sustainability of raw source materials. Here, Chaplin-Krameret al. develop an improved life cycle assessment approach incorporating spatial variation in land-use change, and apply this framework to a bioplastic case study.
- Rebecca Chaplin-Kramer
- , Sarah Sim
- & Gretchen Daily