Academic Articles & Research Papers

Machine learning and soil sciences: a review aided by machine learning tools

Abstract. The application of machine learning (ML) techniques in various fields of science has increased rapidly, especially in the last ten years. The increasing availability of soil data that can be efficiently acquired remotely and proxi...

Increased Atmospheric Aridity and Reduced Precipitation Drive the 2023 Extreme Wildfire Season in Canada

Abstract Canada experienced an unprecedented wildfire season in 2023. Here, we analyzed the exceptional scale, dominant driving factors, and potential impacts on permafrost of these wildfires using Moderate Resolution Imaging Spectroradiome...

Machine learning for advanced energy materials

The screening of advanced materials coupled with the modeling of their quantitative structural-activity relationships has recently become one of the hot and trending topics in energy materials due to the diverse challenges, including low su...

An Overview of Machine Learning

Real-time tracking of carbon corrosion by atomic force microscopy reveals the impact of defect topography on degradation dynamics.

Optimization of Operational Parameters for Bio‑Oil Production from Municipal Solid Waste via Microwave Pyrolysis

The efficiency of bio-oil production from municipal solid waste was investigated using microwave-assisted pyrolysis. The effects of temperature, pyrolysis time, and microwave power on bio-oil yield were evaluated using Response Surface Meth...

Spatially contextualized analysis of energy use for commuting in India

India’s land transport GHG emissions are small in international comparison, but growing exponentially. Understanding of geographically-specific determinants of GHG emissions is crucial to devise low-carbon sustainable development strategies...

Proceedings of the 23rd international conference on Machine learning

This volume, which is also available from http://www.machinelearning.org, the home page of the International Machine Learning Society, contains the technical papers accepted for presentation at ICML-2006, the 23rd International Conference o...

Mapping drivers of tropical forest loss with satellite image time series and machine learning

The rates of tropical deforestation remain high, resulting in carbon emissions, biodiversity loss, and impacts on local communities. To design effective policies to tackle this, it is necessary to know what the drivers behind deforestation ...

MATCHA, a novel regional hydroclimate-chemical reanalysis: System description and evaluation

We present MATCHA (Model for Atmospheric Transport and Chemistry in Asia), a 17-year (2003–2019) regional hydroclimate-chemical reanalysis for Asia (58–140° E, 4– 40° N) at 12 km resolution. MATCHA couples the Weather Research and Forecasti...

Use of machine learning algorithms to determine the relationship between air pollution and cognitive impairment in Taiwan

Air pollution has become a major global threat to human health. Urbanization and industrialization over the past few decades have increased the air pollution. Plausible connections have been made between air pollutants and dementia. This st...

Unlocking pseudocapacitors prolonged electrode fabrication via ultra-short laser pulses and machine learning

Summary: Pseudocapacitors outperform lithium-ion batteries in terms of charging rate and power density. However, their electrode manufacturing procedures are prolonged and environmentally unfriendly, posing a research challenge. To address ...

Directed Evolution of Near-Infrared Serotonin Nanosensors with Machine Learning-Based Screening

In this study, we employed a novel approach to improve the serotonin-responsive ssDNA-wrapped single-walled carbon nanotube (ssDNA-SWCNT) nanosensors, combining directed evolution and machine learning-based prediction. Our iterative optimiz...

Machine Learning

Plasma radicals control synthesis of platinum supported on nitrogen-doped graphitic carbon for ambient-pressure ammonia synthesis.

Ride the green: How does the national carbon market affect corporate breakthrough green innovation?

Automated, economical, and environmentally-friendly asphalt mix design based on machine learning and multi-objective grey wolf optimization

The increasing impact of the greenhouse effect on ecosystems is prompting transportation agencies to seek methods for reducing CO2 emissions during pavement construction and maintenance. Additionally, the laboratory mix design process, whic...

Precision Microalgae: A New Conceptual Framework for Bioengineering Applications

Microalgae are promising platforms for biomass production, carbon capture, biofuels, and high-value bioproducts. However, despite significant advances in cultivation technologies, reactor engineering, and metabolic engineering, industrial i...

Artificial intelligence for waste management in smart cities: a review

The rising amount of waste generated worldwide is inducing issues of pollution, waste management, and recycling, calling for new strategies to improve the waste ecosystem, such as the use of artificial intelligence. Here, we review the appl...

Assessing carbon and economic loss from oak decline in Iran’s Zagros forests using Sentinel-2 and machine learning

Over recent decades, the decline of oak trees, which has emerged as the most significant challenge to the Zagros forests (ZFs), poses serious threats to carbon storage (CS) and economic valuation, jeopardizing the ecological and economic su...