AIMC Topic: Carbon

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Low-complexity fetal heart rate monitoring from carbon-based single-channel dry electrodes maternal electrocardiogram.

Physiological measurement
. Fetal and maternal health during pregnancy can be monitored with sensors such as Doppler or scalp fetal ECG. This study focuses on single-channel dry electrode maternal abdominal ECG () to extract fetal heart rate () using a low-complexity algorith...

Divergent Ozone Predictions in China Under Carbon Neutrality: Why Chemical Mechanisms Disagree.

Environmental science & technology
Uncertainty in air quality models can lead to divergent assessments of emission control policies. Here, we investigate why two widely used chemical mechanisms in the Weather Research and Forecasting model with Chemistry (WRF-Chem) predict inconsisten...

Stage-Specific Drivers of Carbon-Sequestration Dynamics in Mariculture and Responses to Global Warming.

Environmental science & technology
Seaweed mariculture represents a promising blue-carbon strategy, but its carbon-sequestration dynamics and resilience to warming remain insufficiently constrained. Here, we conducted a comprehensive field assessment at a representative (nori) maricu...

Deep Learning-Assisted G4 Nanowire-Enhanced Carbon Dot Biosensor for Exosomal LncRNA Artificial Intelligence Diagnosis.

Analytical chemistry
Exosomal long noncoding RNAs (lncRNA) have significant potential as a biomarker for early cancer diagnosis. Accurate and sensitive detection of this abnormal expression remains challenging. Herein, we develop an innovative dual-mode photoelectrochemi...

Biochar Lifecycle Contribution to Carbon Neutrality: Key Factors and Regulatory Mechanisms.

Environmental science & technology
Biochar, a carbon-enriched material derived from pyrolyzed biomass, has evolved from an ancient farming practice into a mature carbon sequestration technology, emerging as a pivotal strategy for achieving carbon neutrality. Nevertheless, heterogeneou...

Machine learning-assisted multicolor identification and quantification of antidepressant drugs by waste-derived fluorescent nanoprobes: Towards green AI-based electronic tongue.

Analytica chimica acta
Recently, the severe side effects related to the widespread consumption of antidepressants (ADs) have alarmingly created a global challenge for clinics and forensic laboratories. This study introduces a machine learning-empowered multicolor fluoresce...

Green Bond Issuance and Carbon Emissions: Can Causal Machine Learning Inform Forward-Looking Policy Decisions?

Environmental science & technology
Green bonds finance projects intended to deliver environmental benefits, including reductions in greenhouse gas emissions. However, evidence that municipal green bond issuance lowers local carbon emissions remains limited and lacks the spatial and te...

A Satellite-Driven Model for Monitoring Urban Material Metabolism, Embodied Emissions, and Carbonation.

Environmental science & technology
Urban systems are central to global material consumption and carbon emissions. However, systematically understanding urban metabolism remains a challenge due to the reliance on aggregated, top-down data which fails to capture fine-scale urban dynamic...

Global Meta-Analysis Integrated with Machine Learning Assesses Context-Dependent Microplastic Effects on Soil Microbial Biomass Carbon and Nitrogen.

Environmental science & technology
Microplastics (MPs) in soil can paradoxically stimulate microbial biomass in a highly context-dependent manner, potentially inducing decomposition and affecting carbon and nitrogen cycles. We conducted a global meta-analysis with 90 studies (710 obse...

Carbon dots meet artificial intelligence: applications in biomedical engineering.

Journal of materials chemistry. B
Carbon dots (CDs) are fluorescent carbon nanomaterials typically less than 10 nm in size with excellent water solubility, low toxicity, high biocompatibility, favorable optical properties, and modifiable surface. CDs have great promise in various fie...