Article
Biodiversity Conservation
Crinan Jarrett, Kowo Cyril, Daniel T. Haydon, Christel Alain Wandji, Diogo F. Ferreira, Andreanna J. Welch, Luke L. Powell, Jason Matthiopoulos
Summary: Agricultural intensification is causing a shift towards monoculture in cocoa agroforestry across the tropics, which has significant impacts on arthropod communities. The abundance of major pests decreases with increasing farm shade cover, while predatory insects and potential pollinators are more abundant in shady farms.
JOURNAL OF APPLIED ECOLOGY
(2023)
Article
Physics, Multidisciplinary
Omid Kharazmi, Mostafa Tamandi, Narayanaswamy Balakrishnan
Summary: This paper investigates the information generating (IG) function and relative information generating (RIG) function measures associated with maximum and minimum ranked set sampling (RSS) schemes with unequal sizes. It also examines the IG measures for simple random sampling (SRS) and provides comparison results between SRS and RSS procedures in terms of dispersive stochastic ordering. Additionally, the paper discusses the RIG divergence measure between SRS and RSS frameworks.
Review
Multidisciplinary Sciences
Fengyuan Liu, Talal Rahwan, Bedoor AlShebli
Summary: Disparities exist in various aspects of science, including the composition of editorial boards, acceptance delays, and citation rates, with non-White scientists facing significant challenges. A longitudinal study examining the racial composition of editors in relation to scientists is lacking. In this study, a dataset of 1,000,000 papers published between 2001 and 2020 was compiled to analyze the disparities. The findings show underrepresentation of editors from Asia, Africa, and South America, longer acceptance delays for papers from these regions, and significantly fewer citations for Black and Hispanic scientists compared to White scientists.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2023)
Article
Biochemical Research Methods
Christian Staerk, Andreas Mayr
Summary: The study introduces three extensions of statistical boosting algorithms, allowing for multi-variable updates in base-learners selection, random preselection, and adaptive preselection based on predictive performance history. These approaches lead to sparser and more interpretable prediction models with competitive performance.
BMC BIOINFORMATICS
(2021)
Article
Management
Alessandro Di Mattia, Alex Krumer
Summary: This study investigates the impact of reducing the number of high-quality teams in basketball's EuroLeague tournament on stadium attendance. The analysis shows that despite an increase in the number of games per season, there is a significant decrease in attendance per game after the structural change. This decrease is more pronounced in the first half of the season, where games are perceived as less decisive.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Engineering, Electrical & Electronic
Marek W. Rupniewski
Summary: This paper investigates signal reconstruction methods using multiple trains of samples, even in the case of asynchronous sampling. It is shown that with uniformly random starting times within the signal period, an infinite set of sample trains can reconstruct the signal, even without the existence of the signal's derivative. Furthermore, the proposed signal estimator is proven to be consistent in estimating the signal from a finite set of asynchronous trains of samples.
IEEE SIGNAL PROCESSING LETTERS
(2021)
Article
Engineering, Electrical & Electronic
Neharika Jali, Nikhil Karamchandani, Sharayu Moharir
Summary: In this study, we address a variant of the k-center problem in a metric space using an oracle that provides estimates of distances between vertices. We propose active algorithms based on different oracle models and achieve an approximation ratio of two with high probability. Our analytical characterization and numerical evaluations demonstrate significant improvements over naive implementations.
IEEE TRANSACTIONS ON SIGNAL AND INFORMATION PROCESSING OVER NETWORKS
(2022)
Article
Mathematics
Alexander Ulanovskii, Ilya Zlotnikov
Summary: This paper describes a wide family of even kernels, and introduces discrete sets Λ for reconstructing bandlimited signals f.
JOURNAL OF FUNCTIONAL ANALYSIS
(2021)
Article
Green & Sustainable Science & Technology
Clifford Choe Wei Chang, Tan Jian Ding, Tan Jian Ping, Kang Chia Chao, Mohammad Arif Sobhan Bhuiyan
Summary: This review paper presents recent advancements in wind turbine generators and related technologies, providing detailed information on the advantages, drawbacks, and latest research findings of various generator technologies. A comprehensive study is conducted to draw a conclusion and shed new lights on the potential future options in wind turbine generator design for policymakers, researchers, and stakeholders.
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS
(2022)
Article
Psychology, Social
Johannes Prager, Klaus Fiedler
Summary: Research has found that impression judgments are influenced by sample size and sampling method. When sample size is determined by the experimenter, sensitivity of impression judgments to traits increases; however, when sampling is self-truncated, sensitivity is negatively related to sample size, resulting in more extreme judgments for smaller samples.
JOURNAL OF PERSONALITY AND SOCIAL PSYCHOLOGY
(2021)
Article
Geosciences, Multidisciplinary
Haider Ali, Hayley J. Fowler, Benoit Vanniere, Malcolm J. Roberts
Summary: Understanding the impact of climate change on Tropical Storm (TS) activity is crucial for adaptation planning and risk assessment in densely populated low-lying delta rivers basins like the Ganges and Mekong. However, the change in TS characteristics with warming is uncertain due to limitations in global climate models and storm tracking algorithms. This study used multiple models and trackers to estimate the uncertainty in projections of TS characteristics. The results show a decline in the frequency of TS but an increase in the strongest TS and Available Cyclone Energy (ACE) over both basins, with higher-resolution models showing higher intensity values. These findings have important implications for adaptation planning and risk assessment for TS and highlight the need for further high-resolution modeling studies.
Rating: 8/10. The article provides valuable insights into the uncertainty and variability of Tropical Storm characteristics in the context of climate change. The use of multiple models and trackers strengthens the analysis, and the findings have important implications for adaptation planning and risk assessment. However, the summary could have been clearer and more concise in presenting the key findings and their significance
GEOPHYSICAL RESEARCH LETTERS
(2023)
Article
Fisheries
Eva Schemmel, Erin C. Bohaboy, Michael J. Kinney, Joseph M. O'Malley
Summary: The accuracy of fish growth estimates depends on how samples are collected. Random sampling is inefficient and rarely random, while proportional otolith sampling (POS) has been shown to produce more accurate estimates compared to fixed otolith sampling (FOS) under ideal conditions. However, the influence of variables such as sample size, fishery selectivity, and fishing mortality on sampling bias is unclear.
ICES JOURNAL OF MARINE SCIENCE
(2022)
Article
Psychology, Experimental
Jan Dirk Capelle, Carola Grunschel, Olga Bachmann, Miriam Knappe, Stefan Fries
Summary: University students' study motivation increases as exams approach, leading to a decrease in the probability of experiencing motivational conflicts. However, when conflicts do occur, they are more intense the closer the exam is in time. Students are less likely to experience conflicts while studying, but conflicts related to study are more intense.ultiple goals and temporal distance of relevant events should be considered when examining university students' motivation.
MOTIVATION AND EMOTION
(2022)
Article
Environmental Sciences
Shan Jiang, Xuan Wu, Sichan Du, Qin Wang, Dawei Han
Summary: River salinisation and alkalinisation are major environmental problems in the UK, with increasing pH levels and decreasing conductivity levels. These changes show seasonality and regional variations, and are influenced by factors such as road salting, urbanisation, agricultural lands, river discharge, and vegetation cover.
Article
Mathematics, Applied
F. Bozkurt, K. Kornelson
Summary: Vectors in a real finite-dimensional Hilbert space that achieve phase and norm retrieval are studied. The cases of a self-adjoint operator A, a normal operator, or an operator in Jordan canonical form in a real finite-dimensional Hilbert space are considered. In each case, a structure is given to construct norm-retrievable frame sets with a dynamical sampling structure. Given that phase retrieval always implies norm retrieval, particular attention is paid to finding conditions for norm retrieval where phase retrieval is not possible.
JOURNAL OF MATHEMATICAL ANALYSIS AND APPLICATIONS
(2023)
Article
Geochemistry & Geophysics
Shashin Sharan, Rongrong Wang, Felix J. Herrmann
GEOPHYSICAL JOURNAL INTERNATIONAL
(2019)
Article
Geochemistry & Geophysics
Bas Peters, Brendan R. Smithyman, Felix J. Herrmann
Article
Geochemistry & Geophysics
Philipp A. Witte, Mathias Louboutin, Navjot Kukreja, Fabio Luporini, Michael Lange, Gerard J. Gorman, Felix J. Herrmann
Article
Geochemistry & Geophysics
Curt Da Silva, Yiming Zhang, Rajiv Kumar, Felix J. Herrmann
Article
Computer Science, Software Engineering
Curt Da Silva, Felix Herrmann
ACM TRANSACTIONS ON MATHEMATICAL SOFTWARE
(2019)
Article
Geochemistry & Geophysics
Rajiv Kumar, Marie Graff, Ivan Vasconcelos, Felix J. Herrmann
GEOPHYSICAL PROSPECTING
(2019)
Article
Geochemistry & Geophysics
Philipp A. Witte, Mathias Louboutin, Fabio Luporini, Gerard J. Gorman, Felix J. Herrmann
Article
Computer Science, Interdisciplinary Applications
Rajiv Kumar, Bram Willemsen, Felix J. Herrmann, Alison Malcolm
COMPUTATIONAL GEOSCIENCES
(2019)
Article
Computer Science, Software Engineering
Fabio Luporini, Mathias Louboutin, Michael Lange, Navjot Kukreja, Philipp Witte, Jan Huckelheim, Charles Yount, Paul H. J. Kelly, Felix J. Herrmann, Gerard J. Gorman
ACM TRANSACTIONS ON MATHEMATICAL SOFTWARE
(2020)
Article
Geochemistry & Geophysics
Ali Siahkoohi, Gabrio Rizzuti, Felix J. Herrmann
Summary: This article utilizes Bayesian inference and deep neural networks to translate uncertainty in seismic imaging to uncertainty in tasks performed on the image, such as horizon tracking. A systematic approach is developed to address uncertainty due to noise in the data, characterizing it with a convolutional neural network and sampling from the posterior distribution to assess uncertainties.
Article
Geochemistry & Geophysics
Ali M. Alfaraj, D. J. (Eric) Verschuur, Felix J. Herrmann
Summary: This study proposes a low-rank-based residual statics estimation and correction method, which utilizes the low-rank structure of seismic data to estimate statics and overcomes the errors in conventional methods caused by near-surface effects and non-consistent effects. By performing low-rank approximation and crosscorrelation in the midpoint-offset-frequency domain, the method reduces the requirement for accurate rank selection and shares consistent statics across multiple frequency bands. Experimental results demonstrate a significant improvement in short-wavelength statics correction compared to conventional methods.
Article
Geochemistry & Geophysics
Ali Siahkoohi, Gabrio Rizzuti, Rafael Orozco, Felix J. Herrmann
Summary: Bayesian inference for high-dimensional inverse problems is computationally costly and requires selecting a suitable prior distribution. Amortized variational inference addresses these challenges by pretraining a neural network that acts as a surrogate conditional distribution. However, it relies on high-fidelity training data and is prone to errors if evaluated over data that are not from the training data distribution.
Article
Geochemistry & Geophysics
Yijun Zhang, Ziyi Yin, Oscar Lopez, Ali Siahkoohi, Mathias Louboutin, Rajiv Kumar, Felix J. Herrmann
Summary: Modern-day reservoir management and monitoring of geologic carbon storage require costly time-lapse seismic data collection. We demonstrate the use of graph theory techniques to optimize low-cost sparse 4D seismic data acquisition geometries. Our algorithm automatically produces sparse nonreplicated time-lapse acquisition geometries that favor wavefield recovery based on midpoint-offset-domain connectivity arguments.
Article
Computer Science, Artificial Intelligence
Emmanouil Daskalakis, Felix J. Herrmann, Rachel Kuske
SIAM JOURNAL ON IMAGING SCIENCES
(2020)
Article
Geosciences, Multidisciplinary
Mathias Louboutin, Michael Lange, Fabio Luporini, Navjot Kukreja, Philipp A. Witte, Felix J. Herrmann, Paulius Velesko, Gerard J. Gorman
GEOSCIENTIFIC MODEL DEVELOPMENT
(2019)