Microbial electrosynthesis for CO utilization (MESCU) producing valuable chemicals with high energy density has garnered attention due to its long-term stability and high coulombic efficiency. The data-driven approaches offer a promising avenue by leveraging existing data to uncover the underlying patterns. This comprehensive review firstly uncovered the potentials of utilizing data-driven approaches to enhance high-value conversion of CO via MESCU. Firstly, critical challenges of MESCU advancing have been identified, including reactor configuration, cathode design, and microbial analysis. Subsequently, the potential of data-driven approaches to tackle the corresponding challenges, encompassing the identification of pivotal parameters governing reactor setup and cathode design, alongside the decipheration of omics data derived from microbial communities, have been discussed. Correspondingly, the future direction of data-driven approaches in assisting the application of MESCU has been addressed. This review offers guidance and theoretical support for future data-driven applications to accelerate MESCU research and potential industrialization.
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http://dx.doi.org/10.1016/j.biortech.2024.131380 | DOI Listing |
Sci Rep
January 2025
Department of Control Science and Engineering, Harbin Institute of Technology, Harbin, 150001, China.
As a multivariate time series, the prediction of curling trajectories is crucial for athletes to devise game strategies. However, the wide prediction range and complex data correlations present significant challenges to this task. This paper puts forward an innovative deep learning approach, CasLSTM, by introducing integrated inter-layer memory, and establishes an encoder-predictor curling trajectory forecasting model accordingly.
View Article and Find Full Text PDFNeuroimage
January 2025
Center for Mind/Brain Sciences (CIMeC), University of Trento, 38068, Rovereto, (TN), Italy.
Transcranial magnetic stimulation (TMS) has the potential to yield insights into cortical functions and improve the treatment of neurological and psychiatric conditions. However, its reliability is hindered by a low reproducibility of results. Among other factors, such low reproducibility is due to structural and functional variability between individual brains.
View Article and Find Full Text PDFInt J Infect Dis
January 2025
END Fund, New York, USA. Electronic address:
Objectives: Schistosomiasis (SCH) remains a public health challenge in Rwanda despite ongoing interventions. This paper provides an overview of Rwanda's SCH journey, highlighting progress made through mass drug administration (MDA), diagnostic advancements, and strategic partnerships with key stakeholders.
Methods: Since 2014, the point-of-care circulating cathodic antigen (POC-CCA) test has been introduced alongside Kato-Katz (KK), improving mapping accuracy and detecting low-intensity infections.
JMIR Aging
January 2025
Centre of Expertise in Care Innovation, Department of PXL - Healthcare, PXL University of Applied Sciences and Arts, Hasselt, Belgium.
Background: Advancements in mobile technology have paved the way for innovative interventions aimed at promoting physical activity (PA).
Objective: The main objective of this feasibility study was to assess the feasibility, usability, and acceptability of the More In Action (MIA) app, designed to promote PA among older adults. MIA offers 7 features: personalized tips, PA literacy, guided peer workouts, a community calendar, a personal activity diary, a progression monitor, and a chatbot.
Recurrent neural networks (RNNs) have emerged as a prominent tool for modeling cortical function, and yet their conventional architecture is lacking in physiological and anatomical fidelity. In particular, these models often fail to incorporate two crucial biological constraints: i) Dale's law, i.e.
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