Article
Environmental Sciences
Chengcheng Zhang, Danrong Jing, Xiaoyan Huang, Yi Xiao, Zhihao Shu, Dan Luo, Yanying Duan, Meian He, Shuiyuan Xiao, Xiang Chen, Zhijun Huang, Minxue Shen
Summary: Exposure to multiple metals is associated with an increased risk of childhood behavioral problems in China, and there may be interaction effects between specific metals on children's behavior.
SCIENCE OF THE TOTAL ENVIRONMENT
(2022)
Article
Chemistry, Multidisciplinary
Franciele Cicconet, Rui Silva, Paulo M. Mendes
Summary: This study evaluates the use of machine learning models to reduce the computational effort required for predicting the behavior of antennas with complex modeling. The proposed method utilizes convolutional neural networks and a Bayesian optimizer, allowing for analysis of more positions and radiation patterns in a shorter time, leading to a reduction in simulation time and search time.
APPLIED SCIENCES-BASEL
(2023)
Editorial Material
Biochemical Research Methods
Vivien Marx
Summary: Wrangling big data is a requirement for biomedical scientists, and regulations on data sharing have been established. While regulations can change behavior, incentives and a shift in scientific culture are also necessary for successful data sharing.
Article
Geosciences, Multidisciplinary
Albert Scrieciu, Alessandro Pagano, Virginia Rosa Coletta, Umberto Fratino, Raffaele Giordano
Summary: There is a growing interest in the potential of nature-based solutions worldwide, but barriers such as lack of stakeholder engagement and knowledge integration still hinder their wider implementation. A combined approach involving fuzzy cognitive maps, hydraulic modeling, and participatory Bayesian belief networks is proposed to facilitate stakeholder engagement and knowledge integration in NBS design and assessment.
FRONTIERS IN EARTH SCIENCE
(2021)
Review
Green & Sustainable Science & Technology
Jianxin Fang, Brenda Cheang, Andrew Lim
Summary: Machine scheduling problems associated with semiconductor manufacturing operations (SMOs) are difficult to tackle theoretically and computationally. This paper reviews different variants of SMOs' scheduling problems and their performance measures based on various processing constraints. It emphasizes the need for a systematic survey to identify research problems, trends, and solution methods, and hopes to provide insights for researchers and practitioners in this field.
Article
Economics
Prateek Anupriya, Prateek Bansal, Daniel J. Graham
Summary: Road network congestion is a major issue in urban areas worldwide, and building more roads to reduce congestion is controversial. This paper uses causal statistical modeling to quantify congestion technology in road networks in twenty-four cities globally, and finds that increasing network capacity is generally not an efficient solution to manage congestion.
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE
(2023)
Article
Computer Science, Artificial Intelligence
Niknaz Nakhaei, Morteza Ebrahimi, Ahmad Hosseini
Summary: The study of complex networks is a powerful tool for understanding technology-related phenomena and interactions between components. Predicting the behavior of such systems is challenging, and the failure of a few elements can have catastrophic effects. Developing predictive mathematical techniques for complex networks is a major challenge. This study proposes a method based on Bayesian Belief Networks and TOPSIS to predict link failures in complex networks, providing insights for effective solutions in various networks.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Robotics
Miguel Zamora, Roi Poranne, Stelian Coros
Summary: This paper proposes an efficient and numerically robust control problem solution, which formalizes the process of learning solution manifolds as minimization of energy terms, by combining Monte Carlo-inspired sampling strategies with derivatives used for solving individual control task instances.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2022)
Article
Engineering, Multidisciplinary
Dhruv Patel, Deep Ray, Assad A. Oberai
Summary: Inverse problems are common in various fields of science and engineering, and Bayesian inference provides a principled approach to overcome their ill-posed nature. This work presents a novel method for efficient and accurate Bayesian inversion using deep generative models. The method effectively tackles the curse of dimensionality and limited prior information, and produces accurate results with reliable uncertainty estimates.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2022)
Article
Computer Science, Information Systems
Chao Lyu, Yuhui Shi, Lijun Sun
Summary: This paper empirically evaluates and compares the performance of common machine learning models in smoothing high-dimensional fitness landscapes. It proposes a data-driven multi-task optimization (DDMTO) framework to enhance the search abilities of evolutionary algorithms in complex solution spaces. Experimental results show that, by embedding an appropriate smoothing model into the DDMTO framework, the exploration ability and global optimization performance of evolutionary algorithms can be significantly improved without increasing the computational cost.
INFORMATION SCIENCES
(2023)
Article
Environmental Studies
A. George Assaf, Mike Tsionas
Summary: This paper introduces novel Bayesian techniques based on Markov Chain Monte Carlo to test and mitigate the unobserved common factor multicollinearity problem proposed by Kalnins (2018). This approach is not ad hoc, but part of a common framework that can be used to address multicollinearity issues effectively.
TOURISM MANAGEMENT
(2021)
Article
Robotics
Philip Arm, Gabriel Waibel, Jan Preisig, Turcan Tuna, Ruyi Zhou, Valentin Bickel, Gabriela Ligeza, Takahiro Miki, Florian Kehl, Hendrik Kolvenbach, Marco Hutter
Summary: This study presents a team of legged robots with complementary skills for exploration missions in challenging planetary analog environments. The legged robots are equipped with efficient locomotion control, mapping pipeline for visualization, instance segmentation to identify scientific targets, and scientific instruments for remote and in situ investigation. The integration of a robotic arm enables high-precision measurements. The results show that the team of legged robots can conduct successful missions in a short time and explore planetary target sites that are currently inaccessible.
Article
Materials Science, Multidisciplinary
Si Yue Guo, Pascal Friederich, Yudong Cao, Tony C. Wu, Christopher J. Forman, Douglas Mendoza, Matthias Degroote, Andrew Cavell, Veronica Krasecki, Riley J. Hickman, Abhishek Sharma, Leroy Cronin, Nathan Gianneschi, Randall H. Goldsmith, Alan Aspuru-Guzik
Summary: This passage discusses the use of molecular computers to solve combinatorial optimization problems, exploring the advantages and implementation methods of molecular computers compared to traditional semiconductor computers.
Article
Materials Science, Multidisciplinary
Kyohei Hanaoka
Summary: This article introduces a benchmark protocol to compare the performance of different MOBO methods, and comprehensively compares the performances of various methods using multiple design problems and performance metrics. The results show that there is no single best method for all cases, and using an inappropriate method can hinder the efficiency of MOBO.
MATERIALS TODAY COMMUNICATIONS
(2022)
Article
History & Philosophy Of Science
Joshua Gert
Summary: Twin Earth thought experiments are used to explain why referring words have the particular referents they have. These experiments describe a planet and population similar to Earth, but with some crucial differences. The paper introduces a metasemantic view, neopragmatism, which provides plausible explanations for these cases.
Article
Construction & Building Technology
Jordi Pallares, Alexandre Fabregat
Summary: A simple model is proposed to predict the short-term indoor turbulent dispersion of aerosol clouds produced by violent expiratory events. The model can provide estimates for the shape and dimensions of the cloud composed of lighter droplets based on the density difference between exhaled and ambient air, with predictions agreeing with simulations and experiments. This model can be used as an operational tool to determine the short-term spatial range of expelled droplets and provide initial conditions for long-term dispersion simulations in indoor environments.
INDOOR AND BUILT ENVIRONMENT
(2022)
Article
Physics, Multidisciplinary
Oscar Fajardo-Fontiveros, Roger Guimera, Marta Sales-Pardo
Summary: Network inference is the process of learning complex network properties from data. Metadata, including node attributes and other network information, can improve inference in probabilistic network models. This study investigates the impact of metadata on the inference process and finds that the addition of metadata can dramatically change the accuracy of predictions. When data and metadata are correlated, metadata has the most significant contribution to the inference process.
Article
Mechanics
J. S. David, A. Vernet, F. X. Grau, J. Pallares
Summary: This study investigates the flow characteristics in a cylindrical cavity with an aspect ratio of 2, where the top lid rotates with a sinusoidal time-varying speed. It is found that at low Reynolds numbers, the flow frequencies match the frequency imposed on the rotating lid, while at high Reynolds numbers, the flow frequencies significantly decrease compared to the lid frequency.
Article
Mechanics
MohammadJavad Norouzi, Jelena Andric, Anton Vernet, Jordi Pallares
Summary: This study numerically investigates the dynamics and shape evolution of long flexible fibers in a Newtonian viscous cellular flow using particle-level fiber simulation. The results show that stiffness, equilibrium shape, and aspect ratio influence the shape evolution of the fibers. The fiber's stiffness, initial positions, and orientations also affect fiber transport. Deviation from a straight shape significantly impacts the early-stage evolution and bending behavior of the fibers.
Article
Engineering, Chemical
Jordi Pallares, Alexandre Fabregat, Salvatore Cito
Summary: In the wake of the COVID-19 pandemic, there has been an increased interest in understanding the dispersion of airborne pathogen-laden particles. This study analyzes the impact of buoyancy force, upper airway geometry, and head rotation during exhalation on short-term dispersion. The results suggest that buoyancy forces have a moderate role in particle dispersion, head rotation notably affects the size and shape of the cloud, and upper airway geometry has the largest impact when considered along with head rotation.
JOURNAL OF AEROSOL SCIENCE
(2022)
Article
Mathematics, Interdisciplinary Applications
Lluc Font-Pomarol, Angelo Piga, Rosa Maria Garcia-Teruel, Sergio Nasarre-Aznar, Marta Sales-Pardo, Roger Guimera
Summary: Laws and legal decision-making continuously adapt to new social paradigms, reflecting changes in culture and social norms. Using an information-theoretic approach, we track trends in judicial decisions to identify periods of disruptive topics. Analyzing over 100,000 Spanish court decisions, we detect an abrupt change in housing-related decisions around 2016. Our approach allows us to interpret the results in terms of legislative changes, landmark decisions, and social movements.
Article
Mechanics
Jordi Pallares, Alexandre Fabregat, Akim Lavrinenko, Hadifathul Akmal bin Norshamsudin, Gabor Janiga, David F. Fletcher, Kiao Inthavong, Marina Zasimova, Vladimir Ris, Nikolay Ivanov, Robert Castilla, Pedro Javier Gamez-Montero, Gustavo Raush, Hadrien Calmet, Daniel Mira, Jana Wedel, Mitja Strakl, Jure Ravnik, Douglas Fontes, Francisco Jose de Souza, Cristian Marchioli, Salvatore Cito
Summary: This paper discusses the results of the 2022 International Computational Fluid Dynamics Challenge on violent expiratory events and evaluates the ability of different computational codes and turbulence models to reproduce the flow and dispersion of aerosol cloud. 7 research teams from different countries performed 11 numerical simulations using different techniques. The models predicted the shape and range of the buoyant thermal cloud generated by warm exhalation accurately, but underestimated the vertical turbulent mixing and overpredicted the horizontal range covered by the small particle cloud.
Article
Multidisciplinary Sciences
Oscar Fajardo-Fontiveros, Ignasi Reichardt, Harry R. De Los Rios, Jordi Duch, Marta Sales-Pardo, Roger Guimera
Summary: Learning analytical models from noisy data is challenging and depends on the noise level. The authors analyze the transition of the model-learning problem from a low-noise phase to a phase where the noise is too high for the model to be learned. They also estimate upper bounds for the transition noise.
NATURE COMMUNICATIONS
(2023)
Article
Mathematics, Interdisciplinary Applications
Lluis Danus, Carles Muntaner, Alexander Krauss, Marta Sales-Pardo, Roger Guimera
Summary: Scientists collaborate through intricate networks, which are influenced by funding, institutional arrangements, and cultural factors. We compared the collaboration networks of prominent researchers in North America and Europe and found that European researchers have denser networks, while those in North America have more decentralized networks. The impact of publications by North American researchers is significantly higher than that of European researchers, even when collaborating with other prominent researchers.
Article
Thermodynamics
Jordi Pallares, Alexandre Fabregat, Chengwang Lei
Summary: We conducted direct numerical simulations of fully developed turbulent natural convection flow in a vertical channel using Boussinesq fluid. One wall was heated with a constant heat flux, while the other wall was perfectly insulated. The simulations were performed at three different Rayleigh numbers and the results matched the experimental data. The study found that the shear stress is greater on the thermally active wall, but the turbulent intensity and shear stress are greater near the insulated wall. Similarly, the temperature fluctuations and turbulent heat fluxes are higher near the thermally active wall compared to the adiabatic wall.
INTERNATIONAL JOURNAL OF THERMAL SCIENCES
(2023)
Article
Multidisciplinary Sciences
Sergio Cobo-Lopez, Vinod K. Gupta, Jaeyun Sung, Roger Guimera, Marta Sales-Pardo
Summary: This study reveals the robust structural patterns underlying the human gut microbiome using whole metagenomic datasets. The taxonomic composition of the gut microbiome is associated with a combination of generalist and specialist species, which play distinct ecological roles. The findings suggest that there is a nested structure within the gut microbiomes of individuals.