Article
Engineering, Environmental
Kegong Diao, Donghwi Jung, Raziyeh Farmani, Guangtao Fu, David Butler, Kevin Lansey
Summary: This study focuses on the interdependency among modules in water distribution systems, measuring and visualizing the impact of changes in one module on another. The research reveals that most modules have low interdependencies, with only a few critical modules significantly affecting others. Highly interconnected topologies do not necessarily result in strong and complex module interdependencies, which simplifies various analyses for practical applications in WDSs.
Article
Environmental Sciences
Jurjen Rooze, Mary A. Zeller, Mayya Gogina, Patricia Roeser, Jens Kallmeyer, Mischa Schonke, Hagen Radtke, Michael Ernst Bottcher
Summary: In this study, the effects of bottom-contact fishing by otter trawls on the geochemistry and macrofauna in sandy silt sediment were examined. The results showed limited loss of organic matter due to trawling and no clear geochemical footprint of bottom-trawling in sediments actively reworked by tenacious macrofauna.
SCIENCE OF THE TOTAL ENVIRONMENT
(2024)
Article
Engineering, Multidisciplinary
Benjamin W. Stirgwolt, Thomas A. Mazzuchi, Shahram Sarkani
Summary: This research demonstrates how to incorporate the assessment of system architecture modularity into the architecting process using MBSE, providing guidance and evaluation through modularity ontology and DSM analysis. This approach allows for a more comprehensive understanding of the system and its modularity by considering non-functional characteristics in the formation of modules.
JOURNAL OF ENGINEERING DESIGN
(2022)
Review
Meteorology & Atmospheric Sciences
Yiqi Luo, Yuanyuan Huang, Carlos A. Sierra, Jianyang Xia, Anders Ahlstrom, Yizhao Chen, Oleksandra Hararuk, Enqing Hou, Lifen Jiang, Cuijuan Liao, Xingjie Lu, Zheng Shi, Benjamin Smith, Feng Tao, Ying-Ping Wang
Summary: Land ecosystems play an important role in mitigating climate change by absorbing approximately 30% of anthropogenic carbon emissions. However, the uncertainty in estimating the amount and distribution of carbon uptake across different ecosystems or biomes hinders a comprehensive understanding of the mechanisms and drivers of land carbon uptake, as well as predictions of future land carbon sink. In order to advance land carbon cycle modeling, researchers have developed a matrix approach that organizes carbon balance equations into a single matrix equation, allowing for a theoretical framework to understand the behavior of the land carbon cycle. This matrix approach offers computational efficiency, helping to address key issues in modeling and improve predictions using increasingly available data.
JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS
(2022)
Article
Chemistry, Multidisciplinary
Peter Juma Ochieng, Jozsef Dombi, Tibor Kalmar, Miklos Kresz
Summary: In this article, a special structural-based weighted network approach called WECALM is introduced for the analysis of protein complexes. Experimental results indicate that WECALM performs relatively better than existing algorithms in terms of accuracy, computational time, and p-value, and is able to identify a large number of biologically significant protein complexes.
APPLIED SCIENCES-BASEL
(2023)
Article
Meteorology & Atmospheric Sciences
Cuijuan Liao, Xingjie Lu, Yuanyuan Huang, Feng Tao, David M. Lawrence, Charles D. Koven, Keith W. Oleson, William R. Wieder, Erik Kluzek, Xiaomeng Huang, Yiqi Luo
Summary: This study introduces a new Semi-Analytical Spin-Up (SASU) method to tackle the problem of steady state initialization in global biogeochemical cycle models. The experiments at the Brazil site showed that SASU is computationally 7 times more efficient than the traditional native dynamics (ND) spin-up method and globally it is 8 times more efficient than the accelerated decomposition spin-up and 50 times more efficient than ND. In summary, SASU achieves the highest computational efficiency for spin-up compared to other methods, making computationally costly studies possible for a better understanding of biogeochemical cycling under climate change.
JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS
(2023)
Article
Computer Science, Interdisciplinary Applications
Marlene Kuhn, Joerg Franke
Summary: The research introduces a graph-based traceability modeling methodology that focuses on the relationships between traceability-relevant data objects, which enables capturing multi-hierarchical product structures in customized and complex manufacturing environments.
INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING
(2021)
Article
Mathematics, Interdisciplinary Applications
Yuqi Gu
Summary: This article proposes a new family of DeepCDMs models that hunt for deep discrete diagnostic information using deep generative modeling. These models are identifiable, parsimonious, and interpretable. They have transparent identifiability conditions, Bayesian formulations, and efficient sampling algorithms.
Article
Business
Dongmei Zha, Reza Marvi, Pantea Foroudi
Summary: The purpose of this paper is to review and analyze the customer experience (CX) literature using a modularity approach. The paper tracks the transformation of the CX literature from 1984 to 2021 with 546 articles published in business and management journals. The results reveal a diverse and evolving landscape of the CX literature, involving three major marketing systems - service marketing logic, experiential marketing logic, and branding logic - and their corresponding intellectual inputs.
JOURNAL OF BUSINESS RESEARCH
(2023)
Article
Multidisciplinary Sciences
Shouchen Liu, Zhaoyu Yu
Summary: This study improves the reliability and validity of e-commerce cold chain traceability by constructing a blockchain traceability model. It also investigates the best optimization link, the best synergism scale, and the adaptive ability of the system, providing valuable insights for enhancing cold chain traceability capability.
Article
Biochemistry & Molecular Biology
Zachery D. Zbinden, Marlis R. Douglas, Tyler K. Chafin, Michael E. Douglas
Summary: This study evaluated the genetic beta-diversity of 31 co-distributed native stream fishes in the White River Basin using SNP genotyping. The study identified general spatial patterns corresponding to river network architecture and found that a significant proportion of intraspecific genetic variation was explained by the stream hierarchy model. These findings have important implications for conservation and management in the ecosystem.
Article
Operations Research & Management Science
Ayushi Srivastava, Kavya Dashora
Summary: This study explores the enablers for implementing electronic traceability in the agri-food supply chain in India. Through literature review and expert opinions, the study found that electronic traceability can assist agri-food firms in improving performance, reducing food fraud activities, efficient recall of products, and contribute to overall supply chain management.
ANNALS OF OPERATIONS RESEARCH
(2022)
Article
Computer Science, Interdisciplinary Applications
Zhenhai Chang, Zhong-Yuan Zhang, Huimin Cheng, Chao Yan, Xianjun Yin
Summary: The paper discusses a community structure detection method based on nonnegative matrix factorization, and proposes a new algorithm that reformulates modularity maximization under the Frobenius norm framework. Experimental results show that the new method outperforms existing methods in clustering quality.
INTERNATIONAL JOURNAL OF MODERN PHYSICS C
(2021)
Article
Automation & Control Systems
Udayakumar Kanniyappan, Einstein Gnanatheepam, Karthikeyan Subramani, Mangaiyarkarasi Rajendran, Shanmugavel Chinnathambi, Prakasarao Aruna, Singaravelu Ganesan
Summary: Excitation-emission matrix (EEM) is utilized for extracting the biochemical fingerprint of intrinsic fluorophores in oral tissues. Through Parallel factor analysis (PARAFAC), seven intrinsic fluorophores were extracted and effectively discriminated between normal, premalignant, and malignant tissues based on their excitation and emission spectra. The study also demonstrated the potential of PARAFAC analysis as a useful diagnostic tool in oral cancer diagnosis, achieving 100% classification accuracy in normal vs. premalignant group.
JOURNAL OF CHEMOMETRICS
(2021)
Article
Computer Science, Artificial Intelligence
Rajeev Kumar Saha, Raman Kumar, Nikhil Dev, Rajender Kumar, Raul M. Del Toro, Sofia Haber, Jose E. Naranjo
Summary: A fuel cell, as an energy conversion system, requires analysis of its performance under design and off-design conditions during real-time operation. This study presents a method combining graph theory and matrix method for analyzing fuel cell system structure, aiming to facilitate informed decision-making. The proposed methodology includes a quantitative evaluation of a mathematical model and is validated through case studies.
PEERJ COMPUTER SCIENCE
(2023)
Article
Meteorology & Atmospheric Sciences
Tao Tang, Xuhui Lee, Keer Zhang, Lei Cai, David M. Lawrence, Elena Shevliakova
Summary: This study examines the impact of land-use and land-cover change (LULCC) on air temperature using CMIP6 model simulations. It finds that croplands are generally warmer in the tropics and cooler in the mid-high latitudes compared to primary and secondary land. However, the surface heating potential fails to accurately predict the subgrid temperature variation for different land tile configurations under SSP5-8.5 forcing scenarios. The study proposes using the relationship between latitudinal subgrid temperature variation and surface energy redistribution factor as a benchmark for land surface parameterizations and temperature prediction.
JOURNAL OF HYDROMETEOROLOGY
(2023)
Article
Meteorology & Atmospheric Sciences
Yi Yao, Inne Vanderkelen, Danica Lombardozzi, Sean Swenson, David Lawrence, Jonas Jaegermeyr, Luke Grant, Wim Thiery
Summary: Previous studies have emphasized the impacts of irrigation on the global and regional water cycle, energy budget, and near-surface climate. In this study, the representation of irrigation in the Community Land Model is expanded to include six different irrigation methods. A combination of irrigation methods is found to perform best, and is selected as the new irrigation scheme. The new scheme substantially reduces bias and error in simulated irrigation water withdrawals, and has varying impacts on surface fluxes at the global scale. The results highlight the importance of incorporating human water management in Earth system models.
JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS
(2022)
Article
Environmental Sciences
A. Al-Yaari, A. Ducharne, W. Thiery, F. Cheruy, D. Lawrence
Summary: Irrigation plays an important role in global and regional climate, but it is often overlooked in current Earth system models. Only three models in the Coupled Model Intercomparison Project phase 6 (CMIP6) include irrigation. This study found that the models with irrigation show different behavior from the models without irrigation in intensively irrigated areas, with an increase in latent heat flux and soil moisture over time.
Article
Geosciences, Multidisciplinary
Yu Wang, Yuanyuan Huang, Lian Song, Jiahui Yuan, Wei Li, Yongguan Zhu, Scott X. Chang, Yiqi Luo, Philippe Ciais, Josep Penuelas, Julie Wolf, Barbara J. Cade-Menun, Shuijin Hu, Lei Wang, Dengjun Wang, Zengwei Yuan, Yujun Wang, Jishuang Zhang, Ye Tao, Shenqiang Wang, Gang Liu, Xiaoyuan Yan, Chunwu Zhu
Summary: Long-term free air carbon dioxide enrichment experiments on rice plants show that plant-available phosphorus declines in paddy soils as atmospheric CO2 increases. The decline in phosphorus concentration is attributed to the production of soil organic phosphorus that is not readily available to plants, as well as increased loss through crop harvest. These findings suggest that future CO2 scenarios may lead to reduced rice yields, particularly in low-income countries, unless additional phosphorus fertilizers are applied.
Article
Environmental Sciences
Yifan Cheng, Keith N. Musselman, Sean Swenson, David Lawrence, Joseph Hamman, Katherine Dagon, Daniel Kennedy, Andrew J. Newman
Summary: This study aims to develop a generalizable optimization methodology and workflow for the Community Terrestrial Systems Model (CTSM) in order to make complex land models more applicable in regional studies. By applying CTSM and using multi-objective optimization, improvements were made in river flow simulation accuracy while limited progress was achieved in snow simulation.
WATER RESOURCES RESEARCH
(2023)
Editorial Material
Environmental Sciences
Uta Kloenne, Alexander Nauels, Pam Pearson, Robert M. M. DeConto, Helen S. Findlay, Gustaf Hugelius, Alexander Robinson, Joeri Rogelj, Edward A. G. Schuur, Julienne Stroeve, Carl-Friedrich Schleussner
Summary: Taking into account uncertainties in the cryosphere and climate warming, there is a significantly higher risk of threshold crossing in the cryosphere, even with lower emissions. This emphasizes the need to reduce emissions by 50% by 2030 in order to meet the 1.5 degrees Celsius limit set by the Paris Agreement.
NATURE CLIMATE CHANGE
(2023)
Article
Biodiversity Conservation
Yan Sun, Daniel S. Goll, Yuanyuan Huang, Philippe Ciais, Ying-Ping Wang, Vladislav Bastrikov, Yilong Wang
Summary: Global change ecology is facing a bottleneck in the development of large-scale ecological models due to high computational requirements. To address this challenge, a machine-learning acceleration (MLA) tool is introduced to reduce the computation demand for equilibrating biogeochemical cycles in terrestrial biosphere models (TBMs). The MLA achieved a 77%-80% reduction in computation time by interpolating the equilibrated state of biogeochemical variables. Although there were minor biases in the MLA-derived equilibrium, it had a minimal impact on the predicted regional carbon balance.
GLOBAL CHANGE BIOLOGY
(2023)
Article
Multidisciplinary Sciences
Feng Tao, Yuanyuan Huang, Bruce A. Hungate, Stefano Manzoni, Serita D. Frey, Michael W. I. Schmidt, Markus Reichstein, Nuno Carvalhais, Philippe Ciais, Lifen Jiang, Johannes Lehmann, Ying-Ping Wang, Benjamin Z. Houlton, Bernhard Ahrens, Umakant Mishra, Gustaf Hugelius, Toby D. Hocking, Xingjie Lu, Zheng Shi, Kostiantyn Viatkin, Ronald Vargas, Yusuf Yigini, Christian Omuto, Ashish A. Malik, Guillermo Peralta, Rosa Cuevas-Corona, Luciano E. Di Paolo, Isabel Luotto, Cuijuan Liao, Yi-Shuang Liang, Vinisa S. Saynes, Xiaomeng Huang, Yiqi Luo
Summary: Soils store more carbon than other terrestrial ecosystems, but how soil organic carbon (SOC) forms and persists remains uncertain, making it challenging to predict its response to climate change. This study investigates the role of microbial carbon use efficiency (CUE) in SOC persistence and finds that it is at least four times more important than other factors in determining SOC storage. Understanding the environmental dependence of microbial processes underlying CUE may help predict SOC feedback to a changing climate.
Article
Environmental Sciences
Catherine Hirst, Arthur Monhonval, Elisabeth Mauclet, Maxime Thomas, Maelle Villani, Justin Ledman, Edward. A. G. Schuur, Sophie Opfergelt
Summary: The permafrost active layer is an important source of soil organic carbon and mineral nutrients for Arctic rivers. Previous studies assumed that soil pore waters are connected during summer and isolated during winter, but this new research shows that there is no connection between isolated pockets of soil pore water in shallow active layer soils during late winter. However, soils with a deeper active layer are biogeochemically connected for longer than previously thought.
COMMUNICATIONS EARTH & ENVIRONMENT
(2023)
Article
Environmental Sciences
Claudia Tebaldi, Michael Wehner, Ruby Leung, David Lawrence
Summary: We used six Earth system models to study changes in climate extremes under different land use change scenarios. The results show that changes in precipitation extremes are not significant, while temperature extremes show mixed results. Overall, our analysis suggests that the hypothesis to pair SSPs to RCPs in a flexible fashion is defensible, but further investigation is needed for some locations and indices.
ENVIRONMENTAL RESEARCH LETTERS
(2023)
Article
Meteorology & Atmospheric Sciences
Cuijuan Liao, Xingjie Lu, Yuanyuan Huang, Feng Tao, David M. Lawrence, Charles D. Koven, Keith W. Oleson, William R. Wieder, Erik Kluzek, Xiaomeng Huang, Yiqi Luo
Summary: This study introduces a new Semi-Analytical Spin-Up (SASU) method to tackle the problem of steady state initialization in global biogeochemical cycle models. The experiments at the Brazil site showed that SASU is computationally 7 times more efficient than the traditional native dynamics (ND) spin-up method and globally it is 8 times more efficient than the accelerated decomposition spin-up and 50 times more efficient than ND. In summary, SASU achieves the highest computational efficiency for spin-up compared to other methods, making computationally costly studies possible for a better understanding of biogeochemical cycling under climate change.
JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS
(2023)
Article
Environmental Sciences
Leah P. Marshall, Darrell S. Kaufman, R. Scott Anderson, Nicholas P. McKay, Edward A. G. Schuur
Summary: This study investigates the accumulation and degradation of organic matter in permafrost over the Holocene. The results show that the preservation of organic matter in upland areas is influenced by hillslope geomorphic processes, cryoturbation, and climatic variations. The findings provide insights into the carbon dynamics in permafrost environments and their potential feedback on climate change.
JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES
(2023)
Article
Environmental Sciences
Danny M. Leung, Jasper F. Kok, Longlei Li, Gregory S. Okin, Catherine Prigent, Martina Klose, Carlos Perez Garcia-Pando, Laurent Menut, Natalie M. Mahowald, David M. Lawrence, Marcelo Chamecki
Summary: Desert dust is a major component of the atmosphere's aerosol burden and has significant impacts on the Earth system. However, current global climate models and land-surface models struggle to accurately represent dust emission processes due to inadequate representations of soil particle sizes, surface roughness elements, and boundary-layer characteristics. In this study, we address these issues by developing improved descriptions of these factors and propose a methodology to rescale lower-resolution dust emission simulations. Our revised dust emission parameterization shows substantial improvement in simulating dust emissions in both models.
ATMOSPHERIC CHEMISTRY AND PHYSICS
(2023)
Article
Environmental Sciences
Wenfu Tang, Simone Tilmes, David M. Lawrence, Fang Li, Cenlin He, Louisa K. Emmons, Rebecca R. Buchholz, Lili Xia
Summary: This study quantifies the future changes in wildfire burned area and carbon emissions under different socio-economic and solar geoengineering scenarios. The results show that geoengineering can effectively reduce wildfire occurrence globally by decreasing surface temperature and wind speed, and increasing relative humidity and soil water content. However, it also leads to a reduction in precipitation, which partially offsets the fire reduction effect. The impact on burned area is larger than on fire carbon emissions, and the stratospheric sulfate aerosol approach has a stronger fire-reducing effect compared to the solar irradiance reduction approach.
ATMOSPHERIC CHEMISTRY AND PHYSICS
(2023)
Article
Geosciences, Multidisciplinary
Yongzhe Chen, Xiaoming Feng, Bojie Fu, Haozhi Ma, Constantin M. Zohner, Thomas W. Crowther, Yuanyuan Huang, Xutong Wu, Fangli Wei
Summary: By integrating multiple types of remote sensing observations with intensive field measurements, we characterized the changes in above- and belowground forest biomass carbon in China between 2002 and 2021 at a spatial resolution of 1 km. The total forest biomass carbon pool in China has increased at a rate of 114.5 +/- 16.3 TgC yr(-1) (approximately 1.1% yr(-1)) over the past 20 years. The most significant gains in forest biomass carbon stock occurred in central to southern China, including the southern Loess Plateau, Qinling mountains, southwestern karsts, and southeastern forests. The combined use of multi-source remote sensing data provides a valuable tool for assessing forest biomass carbon changes, but further research is needed to understand the drivers of observed woody biomass trends and their impact on biodiversity and ecosystem sustainability.
EARTH SYSTEM SCIENCE DATA
(2023)