Article
Multidisciplinary Sciences
Jan Kessler, Francesco Calcavecchia, Thomas D. Kuehne
Summary: Inspired by the universal approximation theorem and the widespread adoption of artificial neural network techniques, feed-forward neural networks are proposed as a general purpose trial wave function for quantum Monte Carlo simulations of continuous many-body systems. The accuracy of the trial wave functions was demonstrated by studying an exactly solvable model system of two trapped interacting particles and the hydrogen dimer. The whole many-body wave function can be represented by a neural network for simple model systems, while the antisymmetry condition of non-trivial fermionic systems is incorporated by means of a Slater determinant.
ADVANCED THEORY AND SIMULATIONS
(2021)
Article
Chemistry, Physical
Aditya Kumar, Abhijit Chatterjee
Summary: We introduce a probabilistic microkinetic modeling (MKM) framework that integrates the short-ranged order (SRO) evolution of adsorbed species on a catalyst surface. The model incorporates adsorbate-adsorbate interactions, surface diffusion, adsorption, desorption, and catalytic reaction processes using a system of ordinary differential equations. By accurately describing the adspecies ordering/arrangement with SRO parameters and utilizing the reverse Monte Carlo (RMC) method, the relevant local environment probability distributions are extracted and applied to the MKM. The resulting reaction kinetics is comparable to the kinetic Monte Carlo (KMC) method but with significantly faster computational time.
JOURNAL OF CHEMICAL PHYSICS
(2023)
Article
Multidisciplinary Sciences
Sophie Schrader, Andreas Westhoff, Maria Carla Piastra, Tuuli Miinalainen, Sampsa Pursiainen, Johannes Vorwerk, Heinrich Brinck, Carsten H. Wolters, Christian Engwer
Summary: DUNEuro is a free and open-source C++ software toolbox designed for numerical computation of forward solutions in bioelectromagnetism using modern finite element methods. It offers various source models, extendable and user-friendly interfaces, integration with Python and MATLAB, as well as detailed installation instructions and example scripts for practical use.
Article
Materials Science, Multidisciplinary
Owen Bradley, George G. Batrouni, Richard T. Scalettar
Summary: The Holstein Hamiltonian describes fermions interacting with phonons on a lattice. It predicts the behavior of dressed quasiparticles and the formation of superconducting and charge density wave phases at different densities. Quantum Monte Carlo calculations have been used to determine critical temperatures for these phase transitions in various lattice geometries.
Article
Materials Science, Multidisciplinary
S. Tarat, Bo Xiao, R. Mondaini, R. T. Scalettar
Summary: This paper investigates the two mechanisms for the vanishing of the sign problem in quantum simulations: whether randomly chosen field configurations have negative det[M(h)], or if the specific subset of configurations chosen by the weighting function have a greater preponderance of negative values. By conducting auxiliary field quantum Monte Carlo simulations of interacting fermions, the relative importance of these two mechanisms can be better understood.
Article
Polymer Science
Jiang Zhang, Wenbing Hu
Summary: The effects of specific chain-end hydrogen-bonding interactions on the once-folding crystallization of 16-mers in PEG were investigated. It was found that these interactions have little influence on the kinetics of nucleation and lateral growth, but create a significant gap at the growth front, leading to the double-lamella phenomenon. The chain-end hydrogen-bonding interactions are abundant at the surfaces of once-folded lamellar crystals, enhancing their metastability and hindering their thickening into chain-extended crystals. Additionally, intra- and inter-molecular secondary nucleation at the folded and extended growth fronts exhibit different growth rate dependencies on the interaction strengths. The study reveals the role of specific chain-end interactions in PEG crystallization.
Article
Energy & Fuels
Armaghan Cheema, M. F. Shaaban, Mahmoud H. Ismail
Summary: Stochastic PV modeling is essential for future renewable power generation, with one prevalent issue being dust accumulation on PV panels. This study introduces a dynamic model incorporating a Markov chain model to account for dust accumulation in the PV output power profile, helping investors decide on system size and cleaning frequency.
Article
Chemistry, Physical
Dilimulati Aierken, Michael Bachmann
Summary: We systematically investigate the effect of bending stiffness on the ground-state conformations of semiflexible polymers. The formation of different conformations depends strongly on the strength of the bending restraint, as observed through detailed analysis of contact and distance maps.
JOURNAL OF CHEMICAL PHYSICS
(2023)
Article
Astronomy & Astrophysics
William Detmold, Gurtej Kanwar, Henry Lamm, Michael L. Wagman, Neill C. Warrington
Summary: Path integral contour deformations have been proposed as a solution to sign and signal-to-noise problems in lattice field theories, particularly those related to phase fluctuations. By defining a family of contour deformations suitable for SU(N) lattice gauge theory, these problems associated with complex actions and observables can be significantly reduced. Experimental results show that this approach can achieve a significant reduction in variance.
Article
Engineering, Biomedical
Marcin Pietrzak, Monika Mietelska, Aleksandr Bancer, Antoni Rucinski, Beata Brzozowska
Summary: This study validated the calculation accuracy of nanodosimetric quantities in the Geant4-DNA track structure simulation code by implementing the Jet Counter nanodosimeter geometry and assessing the impact of physics models and detector performance on ionization cluster size distributions (ICSD). The findings showed that ICSD in JC geometry obtained from Geant4-DNA simulations corresponded well to measurements in nitrogen gas, with the best agreement for Geant4-DNA physics option 4, indicating the potential application of track structure simulation methods for treatment planning in particle therapy.
PHYSICS IN MEDICINE AND BIOLOGY
(2021)
Article
Mechanics
M. Beljin-Cavic, I Loncarevic, Lj Budinski-Petkovic, Z. M. Jaksic, S. B. Vrhovac
Summary: This study uses Monte Carlo simulations to investigate the random sequential adsorption of mixtures of objects with varying shapes on a three-dimensional cubic lattice. The research focuses on the influence of geometrical properties of the shapes on the jamming coverage and temporal evolution of density. The results show that the coverage approaches the jamming limit exponentially and the relaxation time is determined by the number of orientations the objects can take on the lattice. The jamming coverage of a mixture can be greater than or in between the jamming coverages of the single-component shapes, depending on the local geometry.
JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT
(2022)
Article
Mathematics
Athena Papargiri, George Fragoyiannis, Vasileios S. S. Kalantonis
Summary: In this paper, we discuss the forward problem of EEG and MEG. A spherical two-shell piecewise-homogeneous conductor is used to model the head, with the exterior shell representing the brain tissue and the interior shell portraying a cerebral edema. We assume constant conductivity and use spherical harmonics to represent the expansions of the electric potential and the magnetic field. Furthermore, we demonstrate the efficiency of the model by showing that the magnetic field outside the conductor is only dependent on the dipole moment and its position and does not depend on the inhomogeneity dictated by the interior shell.
Article
Mechanics
V Dossetti, G. M. Viswanathan, V. M. Kenkre
Summary: This article presents numerical investigations on the validity of the Boltzmann prescription in statistical mechanics for large systems. The study focuses on whether the extensivity of energy implies the extensivity of the Boltzmann entropy. Based on simulations considering a large number of states, the results suggest that the systems studied are still too small to conclusively settle the issues raised. However, the new approach outlined in this study represents a first step towards addressing the question of non-extensive statistical mechanics from first principles.
JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT
(2022)
Article
Multidisciplinary Sciences
Alicia N. M. Kraay, Kristin N. Nelson, Conan Y. Zhao, David Demory, Joshua S. Weitz, Benjamin A. Lopman
Summary: The study found that widespread serological testing during the COVID-19 pandemic could not only reduce the number of deaths, but also slow down subsequent waves of transmission, increase social interaction levels, and remain relevant in the face of emerging new variants.
NATURE COMMUNICATIONS
(2021)
Article
Environmental Sciences
Amin Mohammadpour, Mohammad Reza Samaei, Mohammad Ali Baghapour, Hamzeh Alipour, Siavash Isazadeh, Abooalfazl Azhdarpoor, Amin Mousavi Khaneghah
Summary: Excessive nitrate consumption can have potential health risks for humans. This study examined nitrate concentrations in cow milk samples from different farming systems in Iran and used various methods to assess health risks. The results showed that children are more vulnerable to nitrate-related health threats, and the interaction between nitrate concentration and consumption rate plays a significant role. Gaussian Naive Bayes algorithm was optimal for predicting health risks in children, while eXtreme Gradient Boosting algorithm was optimal for adults.
ENVIRONMENTAL POLLUTION
(2024)
Article
Clinical Neurology
Seok Lew, Matti S. Hamalainen, Seppo P. Ahlfors, Yoshio Okada
Summary: Unfused cranial bones have minor effects on MEG signals, but can have significant impacts for certain deep sources, thicker skulls, and larger fontanels. It is important to consider fontanel effects in MEG analysis for accurate quantitative analysis.
CLINICAL NEUROPHYSIOLOGY
(2021)
Article
Engineering, Biomedical
Sergey N. Makarov, Matti Hamalainen, Yoshio Okada, Gregory M. Noetscher, Jyrki Ahveninen, Aapo Nummenmaa
Summary: A new numerical modeling approach combining boundary element and fast multipole methods was proposed, providing unprecedented spatial resolution for noninvasive and higher-resolution intracranial recordings. The algorithm demonstrated efficient and accurate forward-problem solutions, making it suitable for modern high-resolution and submillimeter iEEG applications.
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
(2021)
Article
Neurosciences
John G. Samuelsson, Noam Peled, Fahimeh Mamashli, Jyrki Ahveninen, Matti S. Hamalainen
Summary: The limitation of low spatial resolution in magneto- and electroencephalography has not been unified quantified, with previous studies focusing on linear estimation methods without noise. A new approach is presented here to quantify the spatial fidelity of source estimates, allowing for evaluation of different methods under various conditions. Results show that spatial fidelity varies significantly with signal-to-noise ratio, providing insights for interpreting M/EEG source estimates and methods development.
Article
Behavioral Sciences
Fahimeh Mamashli, Nataliia Kozhemiako, Sheraz Khan, Adonay S. Nunes, Nicole M. McGuiggan, Ainsley Losh, Robert M. Joseph, Jyrki Ahveninen, Sam M. Doesburg, Matti S. Hamalainen, Tal Kenet
Summary: Our study revealed alterations in neurophysiological responses to inverted faces in children with ASD, including reduced local functional connectivity in FFA and decreased long-range alpha-band modulated functional connectivity between FFA and left IFG. The magnitude of long-range functional connectivity between FFA and IFG was correlated with the severity of ASD.
Article
Cell Biology
Fahimeh Mamashli, Sheraz Khan, Matti Hamalainen, Mainak Jas, Tommi Raij, Steven M. Stufflebeam, Aapo Nummenmaa, Jyrki Ahveninen
Summary: This study found that in auditory working memory, memorized sound content is strongly represented by phase-synchronization patterns between subregions of auditory and frontoparietal cortices. Additionally, there are more local, activity silent representations in the auditory cortices, where the decoding accuracy of working memory content significantly increases after task-irrelevant impulse stimuli.
Article
Biochemistry & Molecular Biology
Hari Bharadwaj, Fahimeh Mamashli, Sheraz Khan, Ravinderjit Singh, Robert M. Joseph, Ainsley Losh, Stephanie Pawlyszyn, Nicole M. McGuiggan, Steven Graham, Matti S. Hamalainen, Tal Kenet
Summary: Organizing sensory information into coherent perceptual objects is crucial for everyday perception and communication. This study aimed to investigate the neural mechanisms underlying auditory scene segregation in children with ASD. The results showed that children with ASD exhibited abnormal growth of cortical neural responses with increasing temporal coherence of the auditory figure, providing new insights into the pathophysiology of auditory perceptual deficits and sensory overload in ASD.
Article
Neuroimaging
Elizabeth R. Spencer, Dhinakaran Chinappen, Britt C. Emerton, Amy K. Morgan, Matti S. Hamalainen, Dara S. Manoach, Uri T. Eden, Mark A. Kramer, Catherine J. Chu
Summary: Rolandic epilepsy is a common form of epileptic encephalopathy characterized by sleep-potentiated inferior Rolandic epileptiform spikes, seizures, and cognitive deficits in school-age children that resolve by adolescence. Recent research suggests that there is a lack of sleep spindles, which are thalamocortical rhythms associated with sleep-dependent learning, in the Rolandic cortex during active epilepsy. This disruption in spindle activity extends beyond the epileptic cortex and may contribute to the broad cognitive deficits observed in this condition.
NEUROIMAGE-CLINICAL
(2022)
Article
Clinical Neurology
Teppei Matsubara, Steven Stufflebeam, Sheraz Khan, Jyrki Ahveninen, Matti Haemaelaeinen, Yoshinobu Goto, Toshihiko Maekawa, Shozo Tobimatsu, Kuniharu Kishida
Summary: The mismatch response (MMR) is a neurophysiological measure that can be used as a biomarker for neurological diseases. Traditional methods of extracting MMR have some problems, and the novel weighted-BSST/k method may be more sensitive. Experimental results with healthy adults suggest that the weighted-BSST/k method accurately extracts the MMR.
FRONTIERS IN NEUROLOGY
(2022)
Article
Clinical Neurology
Dimitrios Mylonas, Martin Sjogard, Zhaoyue Shi, Bryan Baxter, Matti Hamalainen, Dara S. Manoach, Sheraz Khan
Summary: Sleep spindles, oscillations defining stage II non-rapid eye movement sleep, play a crucial role in sleep-dependent memory consolidation and are disrupted in cognitive impairment-related disorders. Increasing spindles can enhance memory, making them a potential target for cognitive enhancing therapies. A novel method combining EEG and MEG data allows for more spatially specific source estimation of spindles compared to using either modality alone.
FRONTIERS IN NEUROLOGY
(2022)
Article
Clinical Neurology
Sheraz Khan, Javeria Ali Hashmi, Fahimeh Mamashli, Matti S. Hamalainen, Tal Kenet
Summary: This study investigated the maturation trajectories of resting-state networks (RSNs) and their hubs from ages 7 to 29 using magnetoencephalography (MEG). The results showed that RSNs mediated by the beta band became more locally efficient with maturation, while RSNs mediated by the gamma band became more globally efficient. Different sets of hubs were associated with each network. Further analysis revealed that maturing hubs in gamma band RSNs were more likely to be associated with bottom-up processes, while maturing hubs in beta band RSNs were more likely to be associated with top-down functions.
FRONTIERS IN NEUROLOGY
(2022)
Article
Psychiatry
Seppo P. Ahlfors, Steven Graham, Jussi Alho, Robert M. Joseph, Nicole M. McGuiggan, Zein Nayal, Matti S. Hamalainen, Sheraz Khan, Tal Kenet
Summary: Autism Spectrum (AS) is primarily defined by social interaction differences and sensory processing impairments. This study found that differences in sensory processing between individuals with AS and neurotypically developing individuals can be detected using both magnetoencephalography (MEG) and scalp electroencephalography (EEG), suggesting potential clinical applications for diagnosing and treating AS.
FRONTIERS IN PSYCHIATRY
(2022)
Editorial Material
Clinical Neurology
Rafeed Alkawadri, Rei Enatsu, Matti Hamalainen, Anto Bagic
FRONTIERS IN NEUROLOGY
(2022)
Article
Clinical Neurology
Karin Westin, Sandor Beniczky, Christoph Pfeiffer, Matti Haemaelaeinen, Daniel Lundqvist
Summary: The study demonstrates the potential of on scalp magnetoencephalography (osMEG) as an important clinical tool for epilepsy surgery. It shows that osMEG has superior ability to localize seizure onset zones (SOZ) and detect seizure activity compared to conventional magnetoencephalography (convMEG) and electroencephalography (EEG).
CLINICAL NEUROPHYSIOLOGY
(2023)
Article
Neurosciences
Thomas Jochmann, Marc S. Seibel, Elisabeth Jochmann, Sheraz Khan, Matti S. Haemaelaeinen, Jens Haueisen
Summary: This study investigates a convolutional neural network that detects sex from clinical EEG and finds that electrocardiac artifacts leak into the classifier. However, even after removing these artifacts, the sex can still be determined from the EEG, with topographies being critical but waveforms and frequencies not important for sex detection.
HUMAN BRAIN MAPPING
(2023)
Article
Neuroimaging
Adonay S. Nunes, Fahimeh Mamashli, Nataliia Kozhemiako, Sheraz Khan, Nicole M. McGuiggan, Ainsley Losh, Robert M. Joseph, Jyrki Ahveninen, Sam M. Doesburg, Matti S. Hamalainen, Tal Kenet
Summary: This study used a multivariate machine learning approach to investigate the neurophysiological responses of individuals with ASD and TD when processing upright and inverted faces. Results showed that individuals with ASD had lower classification accuracies when processing inverted neutral faces compared to TD participants, both in the temporal and spatial domains, but there were no group differences when processing upright neutral faces.
NEUROIMAGE-CLINICAL
(2021)