Article
Agronomy
Hao Liang, Junzeng Xu, Lina Chen, Baoguo Li, Kelin Hu
Summary: The study successfully estimated model parameters and quantified uncertainties of agroecosystem models using the two-step method of global sensitivity analysis and the DREAM algorithm. The simulation results were consistent with measured values, demonstrating the effectiveness of this approach.
EUROPEAN JOURNAL OF AGRONOMY
(2022)
Article
Computer Science, Interdisciplinary Applications
Jinfeng Ma, Jing Zhang, Ruonan Li, Hua Zheng, Weifeng Li
Summary: The study developed a framework integrating BO and high-performance computing, with model evaluations on a Hadoop cluster to automate model calibration. The case study showed that the framework can reduce execution times effectively while maintaining accuracy, and provides evaluation of different surrogate models and acquisition functions with real-time visualization.
ENVIRONMENTAL MODELLING & SOFTWARE
(2022)
Article
Engineering, Civil
Eneko Madrazo-Uribeetxebarria, Maddi Garmendia Antin, Jabier Almandoz Berrondo, Ignacio Andres-Domenech
Summary: This article provides a global sensitivity analysis for the PP type of LID control in SWMM, aiming to support practitioners in calibration tasks by identifying the most influential parameters and those that can be neglected. The analysis focuses on flow volume and peak, while also exploring the influence of storm length and drain layer. Ultimately, it shows that fewer parameters can be focused on during calibration than initially expected.
JOURNAL OF HYDROLOGY
(2021)
Article
Plant Sciences
Najeeb H. Alharbi, Salem S. Alghamdi, Hussein M. Migdadi, Ehab H. El-Harty, Kedar N. Adhikari
Summary: The study identified different faba bean genotypes with varying levels of frost resistance, with early and mid-season sowings being more susceptible to frost damage, while late sowings could reduce the impact. Additionally, flowers formed at the beginning of flowering had a faster and higher pod formation rate, contributing significantly to yields. Frost-tolerant genotypes and faster pod formation rates identified in this study could be utilized in breeding better varieties in the future.
Article
Energy & Fuels
Carmen Maria Calama-Gonzalez, Phil Symonds, Giorgos Petrou, Rafael Suarez, Angel Luis Leon-Rodriguez
Summary: This paper presents the application of a Bayesian calibration approach to improve the energy efficiency of buildings, showing that the combination of sensitivity analysis and Bayesian calibration techniques can enhance the agreement between on-site measurements and simulated outputs.
Article
Computer Science, Information Systems
B. Asvija, R. Eswari, M. B. Bijoy
Summary: This article discusses the importance of designing security mechanisms for cloud computing infrastructures, particularly focusing on virtualization security in the context of public clouds. The use of Bayesian networks and attack graphs is highlighted for sensitivity analysis on virtualization security in IaaS cloud infrastructures. The evaluation of the Bayesian attack graph model is aimed at identifying sensitive regions and assisting administrators in securing high-risk components in the stack.
JOURNAL OF ORGANIZATIONAL AND END USER COMPUTING
(2021)
Article
Ecology
Francesco Piccioni, Celine Casenave, Meili Baragatti, Bertrand Cloez, Brigitte Vincon-Leite
Summary: This study proposes an automated calibration method that combines Approximate Bayesian Computation, Random Forest, and Sensitivity Analysis for the complex hydro-ecological model Delft3D-BLOOM. The method is validated using real-time monitoring data and demonstrates its accuracy in calibrating the model.
ECOLOGICAL INFORMATICS
(2022)
Review
Forestry
Anastasia-Ainhoa Atucha Zamkova, Katherine A. Steele, Andrew R. Smith
Summary: Measuring frost tolerance involves various steps, with different techniques used and the gold standard being field observation studies. Equipment that allows controlling freezing rate, frost exposure time, and thawing rate would obtain results similar to field studies. Other important factors in study design include the number of test temperatures used, the range of temperatures selected, and the decrements between the temperatures, all based on expected frost tolerance of the tissue and species.
Article
Horticulture
Jianke Dong, Jingwen Li, Gaofeng Deng, Cheng Chen, Shenglin Jing, Botao Song, Xingkui Cai
Summary: In this study, four frost tolerance loci were identified through field experiments and genetic mapping. Additionally, a genetic linkage map was constructed for chromosome 02, and two loci were found to be associated with frost resistance. These results suggest that the genetic control of frost resistance in potato plants varies under different low temperature conditions.
SCIENTIA HORTICULTURAE
(2023)
Article
Biotechnology & Applied Microbiology
Timothy Barry, Xuran Wang, John A. Morris, Kathryn Roeder, Eugene Katsevich
Summary: SCEPTRE is a method that analyzes single-cell perturbation screens through conditional resampling, effectively addressing calibration issues in these screens and yielding new regulatory relationships supported by orthogonal biological evidence.
Article
Materials Science, Multidisciplinary
Soumya Nag, Yiming Zhang, Sreekar Karnati, Lee Kerwin, Alex Kitt, Eric MacDonald, Dora Cheung, Neil Johnson
Summary: The study uses a feature-based qualification method to reduce the cost and time of DED process qualification. A hybrid-physics-based multi-objective optimization tool is used to predict processing-structure-property relationships in thin-walled builds. The probabilistic ML models achieved targeted predictions with higher reliability compared to conventional methods.
Article
Engineering, Industrial
Jianjun Wang, Ting Mao, Yiliu Tu
Summary: This paper proposes an integrated total cost model to address the simultaneous optimisation of parameter and tolerance design, considering the uncertainty in model parameters and design factors through Bayesian modelling, and minimising the total cost function using a hybrid genetic algorithm. The method shows advantages over existing approaches in providing more reasonable solutions considering the variability of predictive responses and the change of design factors.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2021)
Article
Engineering, Mechanical
Parthasakha Das, Sk Shahid Nadim, Samhita Das, Pritha Das
Summary: This study proposes and explores a mathematical framework for studying the transmission dynamics of COVID-19 with comorbidity, analyzing the fluctuation dynamics of the force of infection and factors related to infection. The increased risk of COVID-19 complications due to comorbidity may result in more susceptible individuals becoming infected.
NONLINEAR DYNAMICS
(2021)
Article
Physiology
Sam Coveney, Cesare Corrado, Jeremy E. Oakley, Richard D. Wilkinson, Steven A. Niederer, Richard H. Clayton
Summary: Calibration of cardiac electrophysiology models is crucial for predicting cardiac therapies outcomes, testing device performance and researching cardiac function. Restitution curve emulators, based on principal component analysis and Gaussian processes, can explore models, analyze sensitivity, and calibrate models to noisy data, providing a promising tool for parameter identifiability and prediction uncertainty.
FRONTIERS IN PHYSIOLOGY
(2021)
Article
Biology
Silvia Hervas-Raluy, Barbara Wirthl, Pedro E. Guerrero, Gil Robalo Rei, Jonas Nitzler, Esther Coronado, Jaime Font de Mora Sainz, Bernhard A. Schrefler, Maria Jose Gomez-Benito, Jose Manuel Garcia-Aznar, Wolfgang A. Wall
Summary: In order to understand the growth of solid tumors, it is crucial to link knowledge of cancer biology with the physical properties of the tumor and its interaction with the surrounding microenvironment. Computational physics-based models were developed to incorporate these interactions using porous media theory. However, experimental validation of these models is challenging for clinical use. This study combines a physics-based model with in vitro experiments using microfluidic devices to mimic a three-dimensional tumor microenvironment, validating the proposed workflow.
COMPUTERS IN BIOLOGY AND MEDICINE
(2023)
Article
Biodiversity Conservation
John Connolly, Maria-Teresa Sebastia, Laura Kirwan, John Anthony Finn, Rosa Llurba, Matthias Suter, Rosemary P. Collins, Claudio Porqueddu, Aslaug Helgadottir, Ole H. Baadshaug, Gilles Belanger, Alistair Black, Caroline Brophy, Jure Cop, Sigridur Dalmannsdottir, Ignacio Delgado, Anjo Elgersma, Michael Fothergill, Bodil E. Frankow-Lindberg, An Ghesquiere, Piotr Golinski, Philippe Grieu, Anne-Maj Gustavsson, Mats Hoglind, Olivier Huguenin-Elie, Marit Jorgensen, Zydre Kadziuliene, Tor Lunnan, Paivi Nykanen-Kurki, Angela Ribas, Friedhelm Taube, Ulrich Thumm, Alex De Vliegher, Andreas Luescher
JOURNAL OF APPLIED ECOLOGY
(2018)
Article
Plant Sciences
Caroline Brophy, John A. Finn, Andreas Luscher, Matthias Suter, Laura Kirwan, Maria-Teresa Sebastia, Aslaug Helgadottir, Ole H. Baadshaug, Gilles Belanger, Alistair Black, Rosemary P. Collins, Jure Cop, Sigridur Dalmannsdottir, Ignacio Delgado, Anjo Elgersma, Michael Fothergill, Bodil E. Frankow-Lindberg, An Ghesquiere, Barbara Golinska, Piotr Golinski, Philippe Grieu, Anne-Maj Gustavsson, Mats Hoglind, Olivier Huguenin-Elie, Marit Jorgensen, Zydre Kadziuliene, Paivi Kurki, Rosa Llurba, Tor Lunnan, Claudio Porqueddu, Ulrich Thumm, John Connolly
JOURNAL OF ECOLOGY
(2017)
Article
Agronomy
Panu Korhonen, Taru Palosuo, Tomas Persson, Mats Hoglind, Guillaume Jego, Marcel Van Oijen, Anne-Maj Gustavsson, Gilles Belanger, Perttu Virkajarvi
FIELD CROPS RESEARCH
(2018)
Article
Agriculture, Dairy & Animal Science
Haldis Kismul, Eva Sporndly, Mats Hoglind, Geir Naess, Torsten Eriksson
Article
Agronomy
T. Persson, M. Hoglind, M. Van Oijen, P. Korhonen, T. Palosuo, G. Jego, P. Virkajarvi, G. Belanger, A. -M. Gustavsson
FIELD CROPS RESEARCH
(2019)
Article
Chemistry, Analytical
Victor P. Rueda-Ayala, Jose M. Pena, Mats Hoglind, Jose M. Bengochea-Guevara, Dionisio Andujar
Article
Agriculture, Dairy & Animal Science
H. Kismul, E. Sporndly, M. Hoglind, T. Eriksson
JOURNAL OF DAIRY SCIENCE
(2019)
Article
Ecology
Mats Hoglind, David Cameron, Tomas Persson, Xiao Huang, Marcel van Oijen
ECOLOGICAL MODELLING
(2020)
Article
Agronomy
Victor P. Rueda-Ayala, Mats Hoglind
Article
Plant Sciences
Victor Rueda-Ayala, Luis Ramos-Guerrero, Paul Vargas-Jentzsch, Betty Hernandez, Mats Hoglind, Ingrid Toscano, Dayana Borja, Lorena Goetschel, Dionisio Andujar
ACTA PHYSIOLOGIAE PLANTARUM
(2020)
Article
Environmental Sciences
Xiao Huang, Hanna Silvennoinen, Bjorn Klove, Kristiina Regina, Tanka P. Kandel, Arndt Piayda, Sandhya Karki, Poul Erik Laerke, Mats Hoglind
Summary: The study developed a model to simulate the dynamics of water table levels and carbon emissions in cultivated peatlands in the Nordic countries, and proposed methods to improve water table management for reducing carbon emissions.
SCIENCE OF THE TOTAL ENVIRONMENT
(2021)
Article
Agronomy
Xiao Huang, Gang Zhao, Conrad Zorn, Fulu Tao, Shaoqiang Ni, Wenyuan Zhang, Tongbi Tu, Mats Hoglind
Summary: This study combines satellite data with process-based grass models, testing a range of data assimilation methods across different locations. The results suggest the importance of optimizing parameters specific to grass species and cultivars, as well as the effectiveness of MODIS data in constraining model simulations and improving predictive accuracy.
FIELD CROPS RESEARCH
(2021)
Article
Agriculture, Multidisciplinary
Tomas Persson, Wieslaw Szulc, Beata Rutkowska, Mats Hoglind, Hans Martin Hanslin, Arne Saebo
AGRICULTURAL AND FOOD SCIENCE
(2020)
Article
Agriculture, Multidisciplinary
Seyda Ozkan Gulzari, Bente Aspeholen Aby, Tomas Persson, Mats Hoglind, Klaus Mittenzwei
AGRICULTURAL SYSTEMS
(2017)
Article
Agriculture, Multidisciplinary
Klaus Mittenzwei, Tomas Persson, Mats Hoglind, Sigrun Kvaerno
AGRICULTURAL SYSTEMS
(2017)
Article
Agronomy
Wenyi Xu, Bo Elberling, Per Lennart Ambus
Summary: The frequency and extent of wildfires in the Arctic have been increasing due to climate change. In this study, researchers conducted experiments in West Greenland to investigate the long-term impacts of climate warming on post-fire carbon dioxide exchange in arctic tundra ecosystems. They found that fire increased soil organic phosphorus concentrations and burned areas remained a net CO2 source five years after the fire. However, with four to five years of summer warming, the burned areas turned into a net CO2 sink.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Yuanhang Yang, Jiabo Yin, Shengyu Kang, Louise J. Slater, Xihui Gu, Aliaksandr Volchak
Summary: This study investigates the impacts of water and heat stress on carbon uptake in China and explores the driving mechanisms of droughts using a machine learning model. The results show that droughts are mostly driven by atmospheric dryness, with precipitation, relative humidity, and temperature playing dominant roles. Water and heat stress have negative impacts on carbon assimilation, and drought occurrence is projected to increase significantly in the future. Improving ecosystem resilience to climate warming is crucial in mitigating the negative effects of droughts on carbon uptake.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Ningbo Cui, Shunsheng Zheng, Shouzheng Jiang, Mingjun Wang, Lu Zhao, Ziling He, Yu Feng, Yaosheng Wang, Daozhi Gong, Chunwei Liu, Rangjian Qiu
Summary: This study proposes a method to partition evapotranspiration (ET) into its components in agroforestry systems. The method is based on water-carbon coupling theory and flux conservation hypothesis. The results show that the partitioned components agree well with measurements from other sensors. The study also finds that atmospheric evaporation demand and vegetation factors greatly influence the components of ET, and increased tree leaf area limits understory grass transpiration.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Xinhao Li, Tianshan Zha, Andrew Black, Xin Jia, Rachhpal S. Jassal, Peng Liu, Yun Tian, Chuan Jin, Ruizhi Yang, Feng Zhang, Haiqun Yu, Jing Xie
Summary: With the rapid increase of urbanization, evapotranspiration (ET) in urban forests has become increasingly important in urban hydrology and climate. However, there is still a large uncertainty regarding the factors that regulate ET in urban areas. This study investigates the temporal variations of ET in an urban forest park in Beijing using the eddy-covariance technique. The results show that daily ET is close to zero during winter but reaches 3-6 mm day-1 in summer. Daily ET increases with vapor pressure deficit (VPD) and soil water content (SWC). Monthly ET increases linearly with normalized difference vegetation index and shows a strong correlation with surface conductance (gs), while exhibiting saturated responses to increasing monthly precipitation (PPT). Annual ET ranges from 326 to 566 mm, and soil water replenishment through PPT from the previous year is responsible for the generally higher monthly ET in spring relative to PPT. Biotic factors and PPT seasonality play essential roles in regulating ET at different scales.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Zhaogang Liu, Zhi Chen, Meng Yang, Tianxiang Hao, Guirui Yu, Xianjin Zhu, Weikang Zhang, Lexin Ma, Xiaojun Dou, Yong Lin, Wenxing Luo, Lang Han, Mingyu Sun, Shiping Chen, Gang Dong, Yanhong Gao, Yanbin Hao, Shicheng Jiang, Yingnian Li, Yuzhe Li, Shaomin Liu, Peili Shi, Junlei Tan, Yakun Tang, Xiaoping Xin, Fawei Zhang, Yangjian Zhang, Liang Zhao, Li Zhou, Zhilin Zhu
Summary: This study investigates the responses of temperate grassland (TG) and alpine grassland (AG) to climate change by studying carbon (C) fluxes across different regions in China. The results reveal that water factors consistently increase C fluxes, while temperature factors have opposite effects on TG and AG. The study enhances our understanding of C sinks and grassland sensitivity to climate change.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Peng Li, Huijie Li, Bingcheng Si, Tao Zhou, Chunhua Zhang, Min Li
Summary: This study mapped the distribution of forest age on the Chinese Loess Plateau using the LandTrendr algorithm. The results show that the LT algorithm is a convenient, efficient, and reliable method for identifying forest age. The findings have important implications for assessing and quantifying biomass and carbon sequestration in afforestation efforts on the Chinese Loess Plateau.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Review
Agronomy
Yean-Uk Kim, Heidi Webber, Samuel G. K. Adiku, Rogerio de S. Noia Junior, Jean-Charles Deswarte, Senthold Asseng, Frank Ewert
Summary: As climate change is expected to increase the intensity and frequency of extreme weather events, it is crucial to assess their impact on cropping systems and explore adaptation options. Process-based crop models (PBCMs) have improved in simulating the impacts of major extreme weather events, but still struggle to reproduce low crop yields under wet conditions. This article provides an overview of the yield-loss mechanisms of excessive rainfall in cereals and the associated modelling approaches, aiming to guide improvements in PBCMs.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Xiaodong Liu, Yingjie Feng, Xinyu Zhao, Zijie Cui, Peiling Liu, Xiuzhi Chen, Qianmei Zhang, Juxiu Liu
Summary: Understanding the impact of climate on litterfall production is crucial for simulating nutrient cycling in forest ecosystems. This study analyzed a 14-year litterfall dataset from two subtropical forests in South China and found that litterfall was mainly influenced by wind speed during the wet season and by temperature during the dry season. These findings have potential significance in improving our understanding of carbon and nutrient cycling in subtropical forest ecosystems under climate change conditions.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Ruonan Chen, Liangyun Liu, Zhunqiao Liu, Xinjie Liu, Jongmin Kim, Hyun Seok Kim, Hojin Lee, Genghong Wu, Chenhui Guo, Lianhong Gu
Summary: Solar-induced chlorophyll fluorescence (SIF) has the potential to estimate gross primary production (GPP), but the quantitative relationship between them is not constant. In this study, a mechanistic model for SIF-based GPP estimation in evergreen needle forests (ENF) was developed, considering the seasonal variation in a key parameter of the model. The GPP estimates from this model were more accurate compared to other benchmark models, especially in extreme conditions.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Jingyi Zhu, Yanzheng Yang, Nan Meng, Ruonan Li, Jinfeng Ma, Hua Zheng
Summary: This study developed a random forest model using climate station and satellite data to generate high-precision precipitation datasets for the Qinghai-Tibet Plateau. By incorporating multisource satellite data, the model achieved a significant enhancement in precipitation accuracy and showed promising results in regions with limited meteorological stations and substantial spatial heterogeneity in precipitation patterns.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Yulin Yan, Youngryel Ryu, Bolun Li, Benjamin Dechant, Sheir Afgen Zaheer, Minseok Kang
Summary: Sustainable rice farming practices are urgently needed to meet increasing food demand, cope with water scarcity, and mitigate climate change. Traditional farming methods that prioritize a single objective have proven to be insufficient, while simultaneously optimizing multiple competing objectives remains less explored. This study optimized farm management to increase rice yield, reduce irrigation water consumption, and tackle the dilemma of reducing GHG emissions. The results suggest that the optimized management can maintain or even increase crop yield, while reducing water demand and GHG emissions by more than 50%.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Sasha D. Hafner, Jesper N. Kamp, Johanna Pedersen
Summary: This study compared micrometeorological and wind tunnel measurements using a semi-empirical model to understand wind tunnel measurement error. The results showed differences in emission estimates between the two methods, but the ALFAM2 model was able to reproduce emission dynamics for both methods when considering differences in mass transfer. The study provides a template for integrating and comparing measurements from different methods, suggesting the use of wind tunnel measurements for model evaluation and parameter estimation.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Wenfang Xu, Wenping Yuan, Donghai Wu, Yao Zhang, Ruoque Shen, Xiaosheng Xia, Philippe Ciais, Juxiu Liu
Summary: In the summer of 2022, China experienced record-breaking heatwaves and droughts, which had a significant impact on plant growth. The study also found that heatwaves were more critical than droughts in limiting vegetation growth.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Jiaqi Guo, Xiaohong Liu, Wensen Ge, Liangju Zhao, Wenjie Fan, Xinyu Zhang, Qiangqiang Lu, Xiaoyu Xing, Zihan Zhou
Summary: Vegetation photosynthetic phenology is an important indicator for understanding the impacts of climate change on terrestrial carbon cycle. This study evaluated and compared the abilities of different spectral indices to model photosynthetic phenology, and found that NIRv and PRI are effective proxies for monitoring photosynthetic phenology.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Arango Ruda Elizabeth, M. Altaf Arain
Summary: Temperate deciduous forests have significant impacts on regional and global water cycles. This study examined the effects of climate change and extreme weather events on the water use and evapotranspiration of a temperate deciduous forest in eastern North America. The results showed that photosynthetically active radiation and air temperature were the primary drivers of evapotranspiration, while vapor pressure deficit regulated water use efficiency. The study also found a changing trend in water use efficiency over the years, influenced by extreme weather conditions.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)