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Combined organic-inorganic fertilization builds higher stability of soil and root microbial networks than exclusive mineral or organic fertilization
Plant health and performance are highly dependent on the root microbiome. The impact of agricultural management on the soil microbiome has been...
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A Systematic Review of Individual Tree Crown Detection and Delineation with Convolutional Neural Networks (CNN)
Purpose of ReviewCrown detection and measurement at the individual tree level provide detailed information for accurate forest management. To...
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Estimating the seasonally varying effect of meteorological factors on the district-level incidence of acute watery diarrhea among under-five children of Iran, 2014–2018: a Bayesian hierarchical spatiotemporal model
Under-five years old acute watery diarrhea (U5AWD) accounts for most diarrheal diseases’ burden, but little is known about the adjusted effect of...
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Uncertainty quantification for hydrological models based on neural networks: the dropout ensemble
The use of neural networks in hydrology has been frequently undermined by limitations regarding the quantification of uncertainty in predictions....
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Identification of groundwater contamination sources and hydraulic parameters based on bayesian regularization deep neural network
Simultaneous identification of various features of groundwater contamination sources and hydraulic parameters, such as hydraulic conductivities, can...
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A Bayesian game of resource exploitation in hinterland regions: modelling scenarios for sustainable development
To reduce greenhouse gas emissions and mitigate climate change, decision-makers around the world look for alternatives to fossil resources. Among...
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Sporocarp-associated fungal co-occurrence networks in a corn field revealed by long-read high-throughput sequencing
We identified a sporocarp as Agrocybe dura growing next to a living corn using PacBio sequencing.
The mycoparasitism of Trichoderma spp. on A. dura ...
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Regional flood frequency analysis using complex networks
Proper regionalisation (identification of homogeneous regions) is key to reliable regional flood frequency analysis. Several methods have been...
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Assessment of flood risk in Mediterranean catchments: an approach based on Bayesian networks
National and international technical reports have demonstrated the increase of extreme event occurrences which becomes more dangerous in coastal...
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Modeling biosurfactant production from agroindustrial residues by neural networks and polynomial models adjusted by particle swarm optimization
Biosurfactants are molecules with wide application in several industrial processes. Their production is damaged due to inefficient bioprocessing and...
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A Bayesian Modelling Framework for Integration of Ecosystem Services into Freshwater Resources Management
Models of ecological response to multiple stressors and of the consequences for ecosystem services (ES) delivery are scarce. This paper describes a...
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The Use of Artificial Neural Networks for Modeling Color and Chemical Oxygen Demand Removal from Olive Mill Wastewater Using Grape Molasses Soil
Olive mill wastewater (OMW) is classified as highly pollutant-containing wastewater that must be treated to an acceptable level before being...
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Determining the origin and fate of nitrate in the Nanyang Basin, Central China, using environmental isotopes and the Bayesian mixing model
Identifying sources of nitrate contamination has been a long-term challenge in areas with different land uses. We investigated the biogeochemical...
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Temporal Networks: A New Approach to Model Non-stationary Hydroclimatic Processes with a Demonstration for Soil Moisture Prediction
Interactions between different components of the hydrologic cycle show a time-varying characteristic due to the impact of climate change that lead to...
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Optimal design of air quality monitoring networks: A systematic review
The optimal design of air quality monitoring network draws significant attention due to the severity associated with air pollution and constraints...
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A hierarchical Bayesian model for the analysis of space-time air pollutant concentrations and an application to air pollution analysis in Northern China
Air pollution has been an environmental problem exerting serious impact on human health. An accurate prediction of air pollutant concentrations in...
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Probability 2: Alternatives
Probability theory is a core discipline in many fields of science and engineering, including LCA. Yet, its foundations and interpretation are the...
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Deep learning–based neural networks for day-ahead power load probability density forecasting
Energy efficiency is crucial to greenhouse gas (GHG) emission pathways reported by the Intergovernmental Panel on Climate Change. Electrical overload...
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Drivers of Perceived Nuisance Growth by Aquatic Plants
Mass developments of macrophytes occur frequently worldwide and are often considered a nuisance when interfering with human activities. It is crucial...
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Barriers to Closed-Loop Supply Chains Implementation in Irish Medical Device Manufacturers: Bayesian Best–Worst Method Analysis
The medical device manufacturing industry is important to the Irish economy, but it is an industry that produces a lot of waste. Therefore, the...