Recent Submissions 

  1. Interlaboratory study of the operational stability of automated sorption balances 

    Zelinka, Samuel L.; Glass, Samuel V.; Lazarcik, Eleanor Q. D.; et al. (2024)
    Adsorption
    Automated sorption balances are widely used for characterizing the interaction of water vapor with hygroscopic materials. These instruments provide an efficient way to collect sorption isotherm data and kinetic data. A typical method for defining equilibrium after a step change in relative humidity (RH) is using a particular threshold value for the rate of change in mass with time. Recent studies indicate that commonly used threshold ...
    Journal Article
  2. Examining Atmospheric River Life Cycles in East Antarctica 

    Wille, Jonathan D.; Pohl, Benjamin; Favier, Vincent; et al. (2024)
    Journal of Geophysical Research: Atmospheres
    During atmospheric river (AR) landfalls on the Antarctic ice sheet, the high waviness of the circumpolar polar jet stream allows for subtropical air masses to be advected toward the Antarctic coastline. These rare but high-impact AR events are highly consequential for the Antarctic mass balance; yet little is known about the various atmospheric dynamical components determining their life cycle. By using an AR detection algorithm to retrieve ...
    Journal Article
  3. Substantial cooling effect from aerosol-induced increase in tropical marine cloud cover 

    Chen, Ying; Haywood, Jim; Wang, Yu; et al. (2024)
    Nature Geoscience
    With global warming currently standing at approximately +1.2 degrees C since pre-industrial times, climate change is a pressing global issue. Marine cloud brightening is one proposed method to tackle warming through injecting aerosols into marine clouds to enhance their reflectivity and thereby planetary albedo. However, because it is unclear how aerosols influence clouds, especially cloud cover, both climate projections and the effectiveness ...
    Journal Article
  4. A Comparison between Predictions of the Miller-Macosko Theory, Estimates from Molecular Dynamics Simulations, and Long-Standing Experimental Data of the Shear Modulus of End-Linked Polymer Networks 

    Tsimouri, Ioanna Ch.; Schwarz, Fabian; Bernhard, Tim; et al. (2024)
    Macromolecules
    Long-standing experimental data on the elastic modulus of end-linked poly(dimethylsiloxane) (PDMS) networks are employed to corroborate the validity of the Miller-Macosko theory (MMT). The validity of MMT is also confirmed by molecular dynamics (MD) simulations that mimic the experimentally realized networks. It becomes apparent that for a network formed from bulk, where the fractions of the loops are small, it is sufficient to account ...
    Journal Article
  5. Fast computation and characterization of forced response surfaces via spectral submanifolds and parameter continuation 

    Li, Mingwu; Jain, Shobhit; Haller, George (2024)
    Nonlinear Dynamics
    For mechanical systems subject to periodic excitation, forced response curves (FRCs) depict the relationship between the amplitude of the periodic response and the forcing frequency. For nonlinear systems, this functional relationship is different for different forcing amplitudes. Forced response surfaces (FRSs), which relate the response amplitude to both forcing frequency and forcing amplitude, are then required in such settings. Yet, ...
    Journal Article
  6. Vision Transformers with Hierarchical Attention 

    Liu, Yun; Wu, Yu-Huan; Sun, Guolei; et al. (2024)
    Machine Intelligence Research
    This paper tackles the high computational/space complexity associated with multi-head self-attention (MHSA) in vanilla vision transformers. To this end, we propose hierarchical MHSA (H-MHSA), a novel approach that computes sell-attention in a hierarchical fashion. Specifically, we first divide the input image into patches as commonly done, and each patch is viewed as a token. Then, the proposed H-MHSA learns token relationships within ...
    Journal Article
  7. Effect-Invariant Mechanisms for Policy Generalization 

    Saengkyongam, Sorawit; Pfister, Niklas; Klasnja, Predrag; et al. (2024)
    Journal of Machine Learning Research
    Policy learning is an important component of many real -world learning systems. A major challenge in policy learning is how to adapt efficiently to unseen environments or tasks. Recently, it has been suggested to exploit invariant conditional distributions to learn models that generalize better to unseen environments. However, assuming invariance of entire conditional distributions (which we call full invariance) may be too strong of an ...
    Journal Article
  8. Research ethics and artificial intelligence for global health: perspectives from the global forum on bioethics in research 

    Shaw, James; Ali, Joseph; Atuire, Caesar A.; et al. (2024)
    BMC Medical Ethics
    Background The ethical governance of Artificial Intelligence (AI) in health care and public health continues to be an urgent issue for attention in policy, research, and practice. In this paper we report on central themes related to challenges and strategies for promoting ethics in research involving AI in global health, arising from the Global Forum on Bioethics in Research (GFBR), held in Cape Town, South Africa in November 2022.Methods ...
    Journal Article
  9. Environmental DNA: The next chapter 

    Blackman, Rosetta; Couton, Marjorie; Keck, Francois; et al. (2024)
    Molecular Ecology
    Molecular tools are an indispensable part of ecology and biodiversity sciences and implemented across all biomes. About a decade ago, the use and implementation of environmental DNA (eDNA) to detect biodiversity signals extracted from environmental samples opened new avenues of research. Initial eDNA research focused on understanding population dynamics of target species. Its scope thereafter broadened, uncovering previously unrecorded ...
    Journal Article
  10. Effect-Invariant Mechanisms for Policy Generalization 

    Saengkyongam, Sorawit; Pfister, Niklas; Klasnja, Predrag; et al. (2024)
    Journal of Machine Learning Research
    Policy learning is an important component of many real -world learning systems. A major challenge in policy learning is how to adapt efficiently to unseen environments or tasks. Recently, it has been suggested to exploit invariant conditional distributions to learn models that generalize better to unseen environments. However, assuming invariance of entire conditional distributions (which we call full invariance) may be too strong of an ...
    Journal Article
  11. Synthesis and characterization of water-soluble C60-peptide conjugates 

    Ma, Yue; Persi, Lorenzo; Yamakoshi, Yoko (2024)
    Beilstein Journal of Organic Chemistry
    With the aim of developing biocompatible and water-soluble C60 derivatives, three types of C60-peptide conjugates consisting of hydrophilic oligopeptide anchors (oligo-Lys, oligo-Glu, and oligo-Arg) were synthesized. A previously reported Prato reaction adduct of a biscarboxylic acid-substituted C60 derivative was subjected to a solid phase synthesis for amide formation with N-terminal amines of peptides on resin to successfully provide ...
    Journal Article
  12. Hotspots of biogeochemical activity linked to aridity and plant traits across global drylands 

    Eldridge, David J.; Ding, Jingyi; Dorrough, Josh; et al. (2024)
    Nature Plants
    Perennial plants create productive and biodiverse hotspots, known as fertile islands, beneath their canopies. These hotspots largely determine the structure and functioning of drylands worldwide. Despite their ubiquity, the factors controlling fertile islands under conditions of contrasting grazing by livestock, the most prevalent land use in drylands, remain virtually unknown. Here we evaluated the relative importance of grazing pressure ...
    Journal Article
  13. Stochastic gradient descent without full data shuffle: with applications to in-database machine learning and deep learning systems 

    Xu, Lijie; Qiu, Shuang; Yuan, Binhang; et al. (2024)
    The VLDB Journal
    Modern machine learning (ML) systems commonly use stochastic gradient descent (SGD) to train ML models. However, SGD relies on random data order to converge, which usually requires a full data shuffle. For in-DB ML systems and deep learning systems with large datasets stored on block-addressable secondary storage such as HDD and SSD, this full data shuffle leads to low I/O performance-the data shuffling time can be even longer than the ...
    Journal Article
  14. Rethinking Global Context in Crowd Counting 

    Sun, Guolei; Liu, Yun; Probst, Thomas; et al. (2024)
    Machine Intelligence Research
    This paper investigates the role of global context for crowd counting. Specifically, a pure transformer is used to extract features with global information from overlapping image patches. Inspired by classification, we add a context token to the input sequence, to facilitate information exchange with tokens corresponding to image patches throughout transformer layers. Due to the fact that transformers do not explicitly model the tried-and-true ...
    Journal Article
  15. Weakened effective connectivity between salience network and default mode network during resting state in adolescent depression 

    Willinger, David; Haberling, Isabelle; Ilioska, Iva; et al. (2024)
    Frontiers in Psychiatry
    Adolescent major depressive disorder (MDD) is associated with altered resting-state connectivity between the default mode network (DMN) and the salience network (SN), which are involved in self-referential processing and detecting and filtering salient stimuli, respectively. Using spectral dynamical causal modelling, we investigated the effective connectivity and input sensitivity between key nodes of these networks in 30 adolescents with ...
    Journal Article
  16. Running in the FAMILY: understanding and predicting the intergenerational transmission of mental illness 

    van Houtum, Lisanne A. E. M.; Baare, William F. C.; Beckmann, Christian F.; et al. (2024)
    European Child & Adolescent Psychiatry
    Over 50% of children with a parent with severe mental illness will develop mental illness by early adulthood. However, intergenerational transmission of risk for mental illness in one's children is insufficiently considered in clinical practice, nor is it sufficiently utilised into diagnostics and care for children of ill parents. This leads to delays in diagnosing young offspring and missed opportunities for protective actions and ...
    Journal Article
  17. Identification and quantification of phosphate turnover indicators after long-term compost application - long-term and single season effects 

    Wanke, Daniel J.; Nkebiwe, Peteh Mehdi; Guenther, Johannes; et al. (2024)
    Plant and Soil
    Background and aims Soil organic phosphorus (P-org) is of interest for plant nutrition because it can comprise between 20 and 80% of total soil phosphate (P). This study aims to examine the effect of compost application on soil phosphatases and microbial biomass, which influence the P turnover and, furthermore, to examine the speciation of P-org. Methods Soil from a long-term field experiment (since 1997) which compares compost application ...
    Journal Article
  18. Higher paracetamol levels are associated with elevated glucocorticoid concentrations in hair: findings from a large cohort of young adults 

    Johnson-Ferguson, Lydia; Shanahan, Lilly; Loher, Michelle; et al. (2024)
    Archives of Toxicology
    Paracetamol is one of the most commonly used over-the-counter medications. Experimental studies suggest a possible stress-suppressing effect of paracetamol in humans facing experimental stress-inducing paradigms. However, no study has investigated whether paracetamol and steroid hormones covary over longer time frames and under real-life conditions. This study addresses this gap by investigating associations between steroid hormones ...
    Journal Article
  19. A generalization of Bondy's pancyclicity theorem 

    Draganic, Nemanja; Correia, David Munha; Sudakov, Benny (2024)
    Combinatorics, Probability & Computing
    The bipartite independence number of a graph $G$ , denoted as $\tilde \alpha (G)$ , is the minimal number $k$ such that there exist positive integers $a$ and $b$ with $a+b=k+1$ with the property that for any two disjoint sets $A,B\subseteq V(G)$ with $|A|=a$ and $|B|=b$ , there is an edge between $A$ and $B$ . McDiarmid and Yolov showed that if $\delta (G)\geq \tilde \alpha (G)$ then $G$ is Hamiltonian, extending the famous theorem of ...
    Journal Article
  20. Incorporating uncertainty within dynamic interoceptive learning 

    Brand, Katja; Wise, Toby; Hess, Alexander J.; et al. (2024)
    Frontiers in Psychology
    Introduction Interoception, the perception of the internal state of the body, has been shown to be closely linked to emotions and mental health. Of particular interest are interoceptive learning processes that capture associations between environmental cues and body signals as a basis for making homeostatically relevant predictions about the future. One method of measuring respiratory interoceptive learning that has shown promising results ...
    Journal Article

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