ClimateBench v1.0: A Benchmark for Data-Driven Climate Projections

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Forest soils harbor hyper-diverse microbial communities which fundamentally regulate carbon and nutrient cycling across the globe. Directly testing hypotheses on how microbiome diversity is linked to forest carbon storage has been difficult, due to a lack ...

Motivation Many machine learning (ML) models developed to classify phenotype from gene expression data provide interpretations for their decisions, with the aim of understanding biological processes. For many models, including neural networks, interpretati ...

The production of aluminium largely depends on the use of fossil fuels, resulting in the emission of significant amounts of greenhouse gases. As the aluminium industry is working towards decreasing its environmental burdens, the elimination of direct emiss ...

Decentralized learning (DL) is an emerging approach that enables nodes to collaboratively train a machine learning model without sharing raw data. In many application domains, such as healthcare, this approach faces challenges due to the high level of hete ...

Renewable energy sources offer a promising solution for mitigating sustainability and CO2 emissions-related issues due to their vast energy generation capacity. They enable hydrogen production via water electrolysis, as well as carbon capture and utilizati ...

Semi-supervised semantic segmentation methods leverage unlabeled data by pseudo-labeling them. Thus the success of these methods hinges on the reliability of the pseudo-labels. Existing methods mostly choose high-confidence pixels in an effort to avoid err ...

Climate action to achieve the Paris Agreement should respect the United Nations Sustainable Development Goals. Here, we use an integrated assessment modelling framework comprising nine climate policy models and quantify the impacts of decarbonisation pathw ...

Real-time condition monitoring is crucial for the reliable and efficient operation of complex systems. However, relying solely on physical sensors can be limited due to their cost, placement constraints, or inability to directly measure certain critical pa ...

The design and discovery of potential novel materials is critical for the advancement of climate change mitigation technologies. In this respect, metal-organic frameworks (MOFs) have received considerable attention over the last two decades. The combinatio ...

Deriving health indicators of rotating machines is crucial for their maintenance. However, this process is challenging for the prevalent adopted intelligent methods since they may take the whole data distributions, not only introducing noise interference b ...

Understanding the cooling service provided by vegetation in cities is important to inform urban policy and planning. However, the performance of decision-support tools estimating heat mitigation for urban greening strategies has not been evaluated systemat ...

AimPlant senescence largely influences the global carbon cycle by regulating the growing season length. However, the driving mechanisms of plant senescence remain unclear, particularly the role of developmental factors. This study aims to investigate how e ...

A three-region optimal economic growth model is proposed to represent the global energy transition to net-zero emissions when carbon dioxide removal (CDR) technologies are available. The main features of the model are (i) the representation of the economy ...

Affected by both future anthropogenic emissions and climate change, future prediction of PM2.5 and its Oxidative Potential (OP) distribution is a significant challenge, especially in developing countries like China. To overcome this challenge, we estimated ...

Sea salt aerosol (SSaer) significantly impacts aerosol-radiation and aerosol-cloud interactions, and sublimated blowing snow is hypothesized to be an important SSaer source in polar regions. Understanding blowing snow and other wind-sourced aerosols’ clima ...

Climate change is expected to alter the temporal distribution of precipitation events, leading to prolonged drought periods and an increased frequency of extreme precipitation events. Changes in precipitation pattern will directly affect soil moisture dyna ...

Low-light photography produces images with low signal-to-noise ratios due to limited photons. In such conditions, common approximations like the Gaussian noise model fall short, and many denoising techniques fail to remove noise effectively. Although deep- ...

Aerosol-cloud interactions, particularly ice processes in mixed-phase clouds (MPCs), remain a key source of uncertainty in climate change assessments. This study introduces state-of-the-art laboratory-based parameterizations into a global chemistry-transpo ...

Accurately predicting weather and climate in cities is critical for safeguarding human health and strengthening urban resilience. Multimodel evaluations can lead to model improvements; however, there have been no major intercomparisons of urban-focussed la ...

Multi-Object Tracking (MOT) is a fundamental computer vision task that involves detecting objects of interest in video frames and associating detections of the same object across time to form trajectories. For association, appearance cues, extracted throug ...

ClimateBench v1.0: A Benchmark for Data-Driven Climate Projections

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Fungal community composition predicts forest carbon storage at a continental scale

A comparative analysis of gene expression profiling by statistical and machine learning approaches

CO2 Capture and Management Strategies for Decarbonizing Secondary Aluminium Production

Fair Decentralized Learning

Tailoring nanocatalysts and reaction interfaces for water- and CO2-electrolysis

Weighting Pseudo-labels via High-Activation Feature Index Similarity and Object Detection for Semi-supervised Segmentation

The impacts of decarbonization pathways on Sustainable Development Goals in the European Union

Graph neural networks for virtual sensing in complex systems: Addressing heterogeneous temporal dynamics

A diversity-driven discovery of potential nanoporous materials for energy-related applications

Classifier-free diffusion-based weakly-supervised approach for health indicator derivation in rotating machines: Advancing early fault detection and condition monitoring

Calibrating and validating the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) urban cooling model: case studies in France and the United States

Growth Onset Rather Than Photosynthesis Strongly Regulates Autumn Senescence Termination Besides Climate Change

A robust asymptotic control model to analyze climate policy with CDR options

Impact of anthropogenic emission control in reducing future PM2.5 concentrations and the related oxidative potential across different regions of China

Characteristics and effects of aerosols during blowing snow events in the central Arctic

Investigation of microbial community dynamics in soil during variable hydrological forcing

Dark Noise Diffusion: Noise Synthesis for Low-Light Image Denoising

Assessing the Global Contribution of Marine Aerosols, Terrestrial Bioaerosols, and Desert Dust to Ice-nucleating Particle Concentrations

Evaluation of 30 urban land surface models in the Urban-PLUMBER project: Phase 1 results

Person Re-Identification and its Application to Multi-Object Tracking