Long-range Component Research Articles

Триплетные сверхпроводящие корреляции гибридной меза-структуры с двухслойной ферромагнитной прослойкой

We present results on electron transport in hybrid Josephson mesa-structure Sd/F1F2/S, consisting of epitaxial films of cuprate superconductor YBa2Cu3O7-δ (Sd), bi-layer ferromagnetic interlayer (F1F2), thin film of metallic Nb was deposited on the top of a thin protective Au film layer used as the upper superconducting electrode (S). The long-range triplet component of superconducting correlations arises when strontium ruthenate SrRuO3 F1 and manganiteLa0.7Sr0.3MnO3 with non-collinear magnetizations are used as ferromagnetic material F2. Superconducting current took place up to the thickness d = 52 nm of the F1F2 interlayer. Superconducting current disappeared in the case of a single ferromagnetic interlayer of manganite (La0.7Sr0.3MnO3 or La0.7Ca0.3MnO3) and SrRuO3 with minimized thicknesses, limited by the occurrence of pinholes. The magnetic field properties of mesa-structure are discussed as well, along with the impact of the second harmonic in the superconducting current-phase relation.

The stabilized supralinear network accounts for the contrast dependence of visual cortical gamma oscillations.

When stimulated, neural populations in the visual cortex exhibit fast rhythmic activity with frequencies in the gamma band (30-80 Hz). The gamma rhythm manifests as a broad resonance peak in the power-spectrum of recorded local field potentials, which exhibits various stimulus dependencies. In particular, in macaque primary visual cortex (V1), the gamma peak frequency increases with increasing stimulus contrast. Moreover, this contrast dependence is local: when contrast varies smoothly over visual space, the gamma peak frequency in each cortical column is controlled by the local contrast in that column's receptive field. No parsimonious mechanistic explanation for these contrast dependencies of V1 gamma oscillations has been proposed. The stabilized supralinear network (SSN) is a mechanistic model of cortical circuits that has accounted for a range of visual cortical response nonlinearities and contextual modulations, as well as their contrast dependence. Here, we begin by showing that a reduced SSN model without retinotopy robustly captures the contrast dependence of gamma peak frequency, and provides a mechanistic explanation for this effect based on the observed non-saturating and supralinear input-output function of V1 neurons. Given this result, the local dependence on contrast can trivially be captured in a retinotopic SSN which however lacks horizontal synaptic connections between its cortical columns. However, long-range horizontal connections in V1 are in fact strong, and underlie contextual modulation effects such as surround suppression. We thus explored whether a retinotopically organized SSN model of V1 with strong excitatory horizontal connections can exhibit both surround suppression and the local contrast dependence of gamma peak frequency. We found that retinotopic SSNs can account for both effects, but only when the horizontal excitatory projections are composed of two components with different patterns of spatial fall-off with distance: a short-range component that only targets the source column, combined with a long-range component that targets columns neighboring the source column. We thus make a specific qualitative prediction for the spatial structure of horizontal connections in macaque V1, consistent with the columnar structure of cortex.

Local Energy Decomposition Analysis of London Dispersion Effects: From Simple Model Dimers to Complex Biomolecular Assemblies.

ConspectusLondon dispersion (LD) forces are ubiquitous in chemistry, playing a pivotal role in a wide range of chemical processes. For example, they influence the structure of molecular crystals, the selectivity of organocatalytic transformations, and the formation of biomolecular assemblies. Harnessing these forces for chemical applications requires consistent quantification of the LD energy across a broad and diverse spectrum of chemical scenarios. Despite the great progress made in recent years in the development of experimental strategies for LD quantification, quantum chemical methods remain one of the most useful tools in the hand of chemists for the study of these weak interactions. Unfortunately, the accurate quantification of LD effects in complex systems poses many challenges for electronic structure theories. One of the problems stems from the fact that LD forces originate from long-range electronic dynamic correlation, and hence, their rigorous description requires the use of complex, highly correlated wave function-based methods. These methods typically feature a steep scaling with the system size, limiting their applicability to small model systems. Another core challenge lies in disentangling short-range from long-range dynamic correlation, which from a rigorous quantum mechanical perspective is not possible.In this Account, we describe our research endeavors in the development of broadly applicable computational methods for LD quantification in molecular chemistry as well as challenging applications of these schemes in various domains of chemical research. Our strategy lies in the use of local correlation theories to reduce the computational cost associated with complex electronic structure methods while providing at the same time a simple means of decomposition of dynamic correlation into its long-range and short-range components. In particular, the local energy decomposition (LED) scheme at the domain-based local pair natural orbital coupled cluster (DLPNO-CCSD(T)) level has emerged as a powerful tool in our research, offering a clear-cut quantitative definition of the LD energy that remains valid across a plethora of different chemical scenarios. Typical applications of this scheme are examined, encompassing protein-ligand interactions and reactivity studies involving many fragments and complex electronic structures. In addition, our research also involves the development of novel cost-effective methodologies, which exploit the LED definition of the LD energy, for LD energy quantification that are, in principle, applicable to systems with thousands of atoms. The Hartree-Fock plus London Dispersion (HFLD) scheme, correcting the HF interaction energy using an approximate CCSD(T)-based LD energy, is a useful, parameter-free electronic structure method for the study of LD effects in systems with hundreds of molecular fragments. However, the usefulness of the LED scheme reaches beyond providing an interpretation of the calculated DLPNO-CCSD(T) or DLPNO-MP2 interaction energies. For example, the dispersion energies obtained from the LED can be fruitfully used in order to parametrize semiempirical dispersion models. We will demonstrate this in the context of an emerging semiempirical method, namely, the Natural Orbital Tied Constructed Hamiltonian (NOTCH) method. NOTCH incorporates LED-derived LD energies and shows promising accuracy at a minimum amount of empiricism. Thus, it holds substantial promise for large and complex systems.

Latitudinal and temporal distribution of aerosols and precipitable water vapor in the tropical Andes from AERONET, sounding, and MERRA-2 data

The aerosol and precipitable water vapor (PW) distribution over the tropical Andes region is characterized using Aerosol Robotic Network (AERONET) observations at stations in Medellin (Colombia), Quito (Ecuador), Huancayo (Peru), and La Paz (Bolivia). AERONET aerosol optical depth (AOD) is interpreted using PM2.5 data when available. Columnar water vapor derived from ozone soundings at Quito is used to compare against AERONET PW. MERRA-2 data are used to complement analyses. Urban pollution and biomass burning smoke (BBS) dominate the regional aerosol composition. AOD and PM2.5 yearly cycles for coincident measurements correlate linearly at Medellin and Quito. The Andes cordillera’s orientation and elevation funnel or block BBS transport into valleys or highlands during the two fire seasons that systematically impact South America. The February–March season north of Colombia and the Colombian-Venezuelan border directly impacts Medellin. Possibly, the March aerosol signal over Quito has a long-range transport component. At Huancayo and La Paz, AOD increases in September due to the influence of BBS in the Amazon. AERONET PW and sounding data correlate linearly but a dry bias with respect to soundings was identified in AERONET. PW and rainfall progressively decrease from north to south due to increasing altitude. This regional diagnosis is an underlying basis to evaluate future changes in aerosol and PW given prevailing conditions of rapidly changing atmospheric composition.

An Empirical Mode Decomposition-Based Hybrid Model for Sub-Hourly Load Forecasting

Sub-hourly load forecasting can provide accurate short-term load forecasts, which is important for ensuring a secure operation and minimizing operating costs. Decomposition algorithms are suitable for extracting sub-series and improving forecasts in the context of short-term load forecasting. However, some existing algorithms like singular spectrum analysis (SSA) struggle to decompose high sampling frequencies and rapidly changing sub-hourly load series due to inherent flaws. Considering this, we propose an empirical mode decomposition-based hybrid model, named EMDHM. The decomposition part of this novel model first detrends the linear and periodic components from the original series. The remaining detrended long-range correlation series is simplified using empirical mode decomposition (EMD), generating intrinsic mode functions (IMFs). Fluctuation analysis is employed to identify high-frequency information, which divide IMFs into two types of long-range series. In the forecasting part, linear and periodic components are predicted by linear and trigonometric functions, while two long-range components are fitted by long short-term memory (LSTM) for prediction. Four forecasting series are ensembled to find the final result of EMDHM. In experiments, the model’s framework we propose is highly suitable for handling sub-hourly load datasets. The MAE, RMSE, MARNE, and R2 of EMDHM have improved by 20.1%, 26.8%, 22.1%, and 5.4% compared to single LSTM, respectively. Furthermore, EMDHM can handle both short- and long-sequence, sub-hourly load forecasting tasks. Its R2 only decreases by 4.7% when the prediction length varies from 48 to 720, which is significantly lower than other models.

Size-classified aerosol-bound heavy metals and their effects on human health risks in industrial and remote areas in Japan

Airborne aerosols were collected in six size classes (PM<0.1, PM0.1–0.5, PM0.5–1, PM1–2.5, PM2.5–10 and PM>10) to investigate aerosol health risks in remote and industrial areas in Japan. We focused on heavy metals and their water-dispersed fractions. The average concentration of heavy metals was 18 ± 25–86 ± 48 ngm−3 for PM<0.1, 46 ± 19–154 ± 80 for PM0.5–1 ngm−3, 98 ± 49–422 ± 186 ngm−3 for PM1–2.5, 321 ± 305–1288 ± 727 ngm−3 for PM2.5–10 and 65 ± 52–914 ± 339 ngm−3 or PM>10, and these concentrations were higher in industrial areas. Heavy metals emitted from domestic anthropogenic sources were added to the long-range transport component of the aerosols. The water-dispersed fraction of heavy metals contained 3.3–40.1% of the total heavy metals in each size class. The relative contribution of Zn and other species (As, Cd, Cr, Ni, Pb, Mn, V and Cu) increased in the water-dispersed fraction. Smaller particles contained greater proportions of the water-dispersed heavy metal fraction. Carcinogenic risk (CR) and the hazard index (HI) were estimated for each size class. The CR of carcinogens was at acceptable levels (<1 ×10−6) for five particle size fractions. The HI values for carcinogens and noncarcinogens were also below acceptable levels (<1) for the same five size fractions. The estimated CR and HI values were dominated by contributions from the inhalation process.

Efficient Hartree–Fock exchange algorithm with Coulomb range separation and long-range density fitting

Separating the Coulomb potential into short-range and long-range components enables the use of different electron repulsion integral algorithms for each component. The short-range part can be efficiently computed using the analytical algorithm due to the locality in both the Gaussian-type orbital basis and the short-range Coulomb potentials. The integrals for the long-range Coulomb potential can be approximated with the density fitting method. A very small auxiliary basis is sufficient for the density fitting method to accurately approximate the long-range integrals. This feature significantly reduces the computational efforts associated with the N4 scaling in density fitting algorithms. For large molecules, the range separation and long-range density fitting method outperforms the conventional analytical integral evaluation scheme employed in Hartree–Fock calculations and provides more than twice the overall performance. In addition, this method offers a higher accuracy compared to conventional density fitting methods. The error in the Hartree–Fock energy can be easily reduced to 0.1 μEh per atom or smaller.

Non-equilibrium dynamics of dipole-charged fields in the Proca theory

We discuss the dynamics of field configurations encoded in the certain class of electric (magnetic) dipole-charged states in the Proca theory of the real massive vector field. We construct such states so as to ensure that the long-distance structure of the mean electromagnetic field in them is initially set by the formula describing the electromagnetic field of the electric (magnetic) dipole. We analyze then how such a mean electromagnetic field evolves in time. We find that far away from the center of the initial field configuration, the long-range component of the mean electromagnetic field harmonically oscillates, which leads to the phenomenon of the periodic oscillations of the electric (magnetic) dipole moment. We also find that near the center of the initial field configuration, the mean electromagnetic field escapes from its initial arrangement and a spherical shock wave propagating with the speed of light appears in the studied system. A curious configuration of the axisymmetric mean electric field is found to accompany the mean magnetic field in magnetic dipole-charged states.

Effect of charge transfer on the first hyper-polarizability of N,N-dimethylaniline and julolidine: a DFT based comparative study.

Quantum mechanical calculations involving electron correlation, frequency dispersion, and solvent effects were carried out to examine the second-order nonlinear optical response ofvarious acceptor, X (-CF3, -CN, -NO2) substituted in N,N-dimethylaniline (DMA) and julolidine(JLD). Here, both DMA and JLD acts as donor and the three substituted groups, X (-CF3, -CNand -NO2) at the para position of both the ring systems as acceptor. The NLO response (βHRS) of -CF3 and -CN substituted DMA and JLD is relatively lower compared to DMA-NO2 andJLD-NO2. The charge distribution is found higher in case of -NO2substituted DMA and JLD (±443 and ±449) compared to their -CF3 or -CN substitution. Electronic characteristics such asUV-Vis absorption spectra, crucial excited state parameters and charge transfer contribution to βHRS have been used to explain the NLO parameter of DMA-X and JLD-X. Variation of theincident optical frequency of light shows fluctuation of βHRS value and highest values of βHRS are obtain at the λmax frequency of each compound. Solvent polarity variation study on βHRSshows that βHRS varies linearly with the Kirkwood-Onsagar dielectric factor (D). All computational studies have been carried out using density functional theory (DFT) based method. Since CAM-B3LYP based hybrid functional improves the asymptotic behavior of theexchange interaction by dividing into short-range and long-range components, first hyperpolarizability values in the present study were computed using DFT/ CAM-B3LYP/ 6-31G+(d,p) level oftheory.

Factorized structure of the long-range two-electron integrals tensor and its application in quantum chemistry

We introduce two new approximation methods for the numerical evaluation of the long-range component of the range-separated Coulomb potential and the approximation of the resulting high dimensional Two-Electron Integrals tensor (TEI) with long-range interactions arising in molecular simulations. The first method exploits the tensorized structure of the compressed two-electron integrals obtained through two-dimensional Chebyshev interpolation combined with Gaussian quadrature. The second method is based on the Fast Multipole Method (FMM). Numerical experiments for different medium size molecules on high quality basis sets outline the efficiency of the two methods. Detailed algorithmic is provided in this paper as well as numerical comparison of the introduced approaches.

Azimuthal anisotropy of dijet events in PbPb collisions at sqrt{s_{textrm{NN}}} = 5.02 TeV

The path-length dependent parton energy loss within the dense partonic medium created in lead-lead collisions at a nucleon-nucleon center-of-mass energy of sqrt{s_{textrm{NN}}} = 5.02 TeV is studied by determining the azimuthal anisotropies for dijets with high transverse momentum. The data were collected by the CMS experiment in 2018 and correspond to an integrated luminosity of 1.69 nb−1. For events containing back-to-back jets, correlations in relative azimuthal angle and pseudorapidity (η) between jets and hadrons, and between two hadrons, are constructed. The anisotropies are expressed as the Fourier expansion coefficients vn, n = 2–4 of these azimuthal distributions. The dijet vn values are extracted from long-range (1.5 < |∆η| < 2.5) components of these correlations, which suppresses the background contributions from jet fragmentation processes. Positive dijet v2 values are observed which increase from central to more peripheral events, while the v3 and v4 values are consistent with zero within experimental uncertainties.

Store and Fetch Immediately: Everything Is All You Need for Space-Time Video Super-resolution

Existing space-time video super-resolution (ST-VSR) methods fail to achieve high-quality reconstruction since they fail to fully explore the spatial-temporal correlations, long-range components in particular. Although the recurrent structure for ST-VSR adopts bidirectional propagation to aggregate information from the entire video, collecting the temporal information between the past and future via one-stage representations inevitably loses the long-range relations. To alleviate the limitation, this paper proposes an immediate storeand-fetch network to promote long-range correlation learning, where the stored information from the past and future can be refetched to help the representation of the current frame. Specifically, the proposed network consists of two modules: a backward recurrent module (BRM) and a forward recurrent module (FRM). The former first performs backward inference from future to past, while storing future super-resolution (SR) information for each frame. Following that, the latter performs forward inference from past to future to super-resolve all frames, while storing past SR information for each frame. Since FRM inherits SR information from BRM, therefore, spatial and temporal information from the entire video sequence is immediately stored and fetched, which allows drastic improvement for ST-VSR. Extensive experiments both on ST-VSR and space video super-resolution (S-VSR) as well as time video super-resolution (T-VSR) have demonstrated the effectiveness of our proposed method over other state-of-the-art methods on public datasets. Code is available https://github.com/hhhhhumengshun/SFI-STVR

Harmonic oscillator seasonal trend (HOST) model for hydrological drought pattern identification and analysis

Droughts, due to their complex nature, are difficult to predict; however, research is showing that there are often clearly defined patterns to their occurrence. The temporal aspects are usually more apparent when comparing regions with defined climatic characteristics, such as those with recognized wet or dry seasons, but recognizing these patterns can help in defining and understanding the overall processes influencing drought occurrence. Especially in the context of climate change, it is crucial to recognize temporal patterns and quantify them to help diagnose current and future event probabilities. The objective of this work is to introduce a new tool for assessing temporal patterns of streamflow drought, based on the harmonic oscillator theorem called the harmonic oscillator seasonal trend (HOST) model. The testing dataset consists of monthly minimal flows and drought occurrence information calculated based on daily flows from the National Water Model (NWM) retrospective v.2.1 dataset for the period 1979–2020. The model framework allows for trend and seasonality signal decomposition as well as the extraction of the first five harmonics by means of a Fast Fourier Transform (FFT)-based machine learning algorithm. The model framework enables the extraction and evaluation of five different harmonic models based on short and long-range components as well as linear regression sloped harmonics. The results show that the best-fit models are based on two superimposed sinusoidal functions with an accuracy of around 70–90 % for streamflow drought occurrence, with different spatial parameters reflecting varied environmental conditions. The models were able to capture two patterns: (1) annual precipitation variation and (2) longer-term inertia, the latter of which is likely driven by large-scale circulation with a roughly-eight year period.

Halide Substitution Effects on Lithium-Ion Diffusion in Protonated Antiperovskites

Solid-state electrolytes (SSEs) for all-solid-state lithium-ion batteries are generating intense interest because these batteries can improve the safety and performance compared with devices fabricated with conventional, flammable liquid electrolytes. In these SSEs, it has been suggested that Li+ ion diffusion in the grain boundaries is hindered and is a critical determinant of the overall ionic conductivity (σ). However, Li+ ion diffusivities in the grain (DG) and the grain boundary (DGB) are difficult to determine experimentally, with few techniques capable of distinguishing the individual contributions. Here, we distinguished the DG and DGB for the protonated lithium antiperovskites (pLiAPs) SSEs: Li2OHCl, Li2OHBr, Li2OHF0.1Cl0.9, Li2OHF0.1Br0.9, and Li2OHCl0.37Br0.63. The measurements were obtained directly from 7Li pulsed-field gradient nuclear magnetic resonance (PFG-NMR) at 353 K. The 7Li PFG-NMR echo profiles were composed of two primary components with additional secondary oscillatory components – the so-called NMR diffraction phenomenon. The length scale separating the two main components corresponds to a diffusion length of ∼1.7 μm, which is thought to be the average grain size (by diameter). The short-range (≤1.7 μm) diffusion component associated with DG (≈10–11 m2/s) varied minimally with halide substitution, while the long-range (≥1.7 μm) component DGB (≈10–12 to 10–15 m2/s) was highly sensitive to the substitution of halides and closely correlated with σ. In addition, from the comparison of the ratio DGB/DG to Dτ (the Li+ ion diffusion coefficient estimated from the rotational correlation time, τc), it was determined that the fractional contribution of DG to σ is negligible; 0.01–0.04 in the pLiAPs studied here. These insights provide a fundamental understanding of the halide substitution effects on Li+ ion grain vs grain boundary diffusion and suggest that careful engineering of the grain boundaries at the microscopic level is necessary to achieve high-performance pLiAP SSEs.

Results of Many Years’ Measurements Conducted at the Czech State Long Distances Measuring Standard Koštice

Currently, electronic total stations based on the principles of laser long-range distance measurement are used for collecting geospatial information. As time goes, in the process of using the electronic total stations, their technical parameters vary, necessitating periodic calibration of the instruments. Calibration of the long-range distance measurement laser component of the electronic total stations is carried out at specialized baselines and consists in testing the constant component of an electronic total station, determining the scale error and determining the cyclic error. In the territory of the Czech Republic, two geodetic baselines are operated, the National Calibration Baseline Hvězda and Koštice. Koštice is the Czech State Long Distances Measuring Standard, where electronic total stations are calibrated. From 2017 to 2020, about 600 electronic total stations by different manufacturers Leica Geosystems, Trimble, Topcon, Sokkia, Nikon, Pentax, South and Geomax were calibrated. The total number of measurements performed under the program in all combinations has equaled about 40000. In this paper, results of analysis many years’ measurements performed at the geodetic baseline Koštice from 2017 to 2020 with electronic total stations manufactured by Leica Geosystems are presented. In total, 9186 measurements between the baseline sections 1–2, 1–3, 1–4, 1–5, 1–6, 1–7 and 1–8 have been analyzed. For each section, measurements have been detected which did not pass the Grubbs test criterion (the Smirnov – Grubbs test). Altogether, 261 outliers have been detected, totaling 3 % of the total number of measurements. After excluding the detected outliers with the algorithm of the parametric version of least squares optimization, the length of each section of the baseline was found, and the accuracy of the results obtained was evaluated. The calculated values of the length of the baseline sections are in generally good agreement with the results of the measurements performed at the geodetic baseline Koštice by the specialists from the laboratory of the Bundeswehr University in Munich (Germany) and the results of similar measurements conducted at the same baseline by the specialists from the Research Institute of Geodesy, Topography and Cartography (Czech Republic). For section 1–5, based on the results of both verifications, differences have been obtained exceeding the permissible values of the accuracy of determining baseline characteristics. This may be related to the fact that there are displacements of certain pillars, which mainly have a periodic character and depend on the season. To allow more specific assumptions regarding instability of certain pillars, it is recommended to verify the lengths of the baseline sections once in three months, according to the program in all combinations, which will allow comparison of the values of the confidence limits of the baseline section lengths and putting forward hypotheses regarding variations in the position of individual centers, so that the deviations revealed should be included into the residual uncertainty of length measurement.

Local Molecular Field Theory for Coulomb Interactions in Aqueous Solutions

Coulomb interactions play a crucial role in a wide array of processes in aqueous solutions but present conceptual and computational challenges to both theory and simulations. We review recent developments in an approach addressing these challenges─local molecular field (LMF) theory. LMF theory exploits an exact and physically suggestive separation of intermolecular Coulomb interactions into strong short-range and uniformly slowly varying long-range components. This allows us to accurately determine the averaged effects of the long-range components on the short-range structure using effective single particle fields and analytical corrections, greatly reducing the need for complex lattice summation techniques used in most standard approaches. The simplest use of these ideas in aqueous solutions leads to the short solvent (SS) model, where both solvent-solvent and solute-solvent Coulomb interactions have only short-range components. Here we use the SS model to give a simple description of pairing of nucleobases and biologically relevant ions in water.

Interference phenomena in Josephson junctions with ferromagnetic bilayers: Spin-triplet correlations and resonances

We study the Josephson effect in planar $\mathrm{S}{\mathrm{F}}_{1}{\mathrm{F}}_{2}\mathrm{S}$ junctions that consist of conventional $s$-wave superconductors (S) connected by two metallic monodomain ferromagnets (${\mathrm{F}}_{1}$ and ${\mathrm{F}}_{2}$) with an arbitrary transparency of interfaces. We solve the scattering problem in the clean limit based on the Bogoliubov--de Gennes equation for both spin-singlet and odd in frequency spin-triplet pairing correlations. We calculate numerically the Josephson current-phase relation $I(\ensuremath{\phi})$. While the first harmonic of $I(\ensuremath{\phi})$ is completely generated by spin-singlet and short-range spin-triplet superconducting correlations, for noncollinear magnetizations of ferromagnetic layers the second harmonic has an additional long-range spin-triplet component. Therefore, for a strong ferromagnetic influence, the long-range spin-triplet contribution to the second harmonic dominates. We find an exception due to the geometric resonance for equal ferromagnetic layers when the first harmonic is strongly enhanced. Both first and second harmonic amplitudes oscillate with ferromagnetic layer thicknesses due to $0\text{\ensuremath{-}}\ensuremath{\pi}$ transitions. We study the influence of interface transparencies and find additional resonances for finite transparency of the interface between ferromagnetic layers.

Symmetry-dependent analytical all-electron potential for helium atom

Electron–electron interaction is the origin of the many-body problems usually encountered in physics and chemistry. Helium atom and other two-electron systems are the simplest many-body systems in nature. The Schrödinger equation even for such simple systems cannot be solved exactly without resorting to approximate methods. In this study, we have suggested a symmetry-dependent analytical all-electron potential for helium atom derived using an alternative multipole expansion, a variational technique, and a mean-field approximation. We have calculated the non-relativistic groundstate energy for helium atom to be −2.90422284. The suggested all-electron potential has a local Coulomb potential with embedded nuclear charge screening effect in the leading term of the multipole potential. A non-local component of the potential emanates from the higher-order angular momentum terms of the multipole series expansion. The higher-order multipole interactions are fully included through the exchange correlation processes where the interacting electrons exchange their angular momenta via the operator. With the derived potential, the effects of the local long-range and non-local short-range components, and the finite nuclear mass corrections are tested. Our results are in reasonable agreement with literature values. Indeed with the finite nuclear mass correction, we obtain the groundstate energy of helium atom to be −2.90382769.

Coarse-Grained Model Incorporating Short- and Long-Range Effective Potentials for the Fast Simulation of Micelle Formation in Solutions of Ionic Surfactants.

A coarse-grained model comprising short- and long-range effective potentials, parametrized with the iterative Boltzmann inversion (IBI) method, is presented for capturing micelle formation in aqueous solutions of ionic surfactants using as a model system sodium dodecyl sulfate (SDS). In the coarse-grained (CG) model, each SDS molecule is represented as a sequence of four beads while each water molecule is modeled as a single bead. The proposed CG scheme involves ten potential energy functions: four of them describe bonded interactions and control the distribution functions of intramolecular degrees of freedom (bond lengths, valence angles, and dihedrals) along an SDS molecule while the other six account for intermolecular interactions between pairs of SDS and water beads and control the radial distribution functions. The nonbonded effective potentials between coarse-grained SDS molecules extend up to about 12 nm and capture structural and morphological features of the micellar solution both at short and long distances. The long-range component of these potentials, in particular, captures correlations between surfactant molecules belonging to different micelles and is essential to describe ordering associated with micelle formation. A new strategy is introduced for determining the effective potentials through IBI by using information (target distribution functions) extracted from independent atomistic simulations of a micellar reference system (a salt-free SDS solution at total surfactant concentration cT equal to 103 mM, temperature T equal to 300 K, and pressure P equal to 1 atm) obtained through a multiscale approach described in an earlier study. It employs several optimization steps for bonded and nonbonded interactions and a gradual parametrization of the short- and long-range components of the latter, followed by reparametrization of the bonded ones. The proposed CG model can reproduce remarkably accurately the microstructure and morphology of the reference system within only a few hours of computational time. It is therefore very promising for future studies of structural and morphological behavior of various liquid surfactant formulations.

A systematic data-driven approach to analyze sensor-level EEG connectivity: Identifying robust phase-synchronized network components using surface Laplacian with spectral-spatial PCA.

Although conventional averaging across predefined frequency bands reduces the complexity of EEG functional connectivity (FC), it obscures the identification of resting-state brain networks (RSN) and impedes accurate estimation of FC reliability. Extending prior work, we combined scalp current source density (CSD; spherical spline surface Laplacian) and spectral-spatial PCA to identify FC components. Phase-based FC was estimated via debiased-weighted phase-locking index from CSD-transformed resting EEGs (71 sensors, 8min, eyes open/closed, 35 healthy adults, 1-week retest). Spectral PCA extracted six robust alpha and theta components (86.6% variance). Subsequent spatial PCA for each spectral component revealed seven robust regionally focused (posterior, central, and frontal) and long-range (posterior-anterior) alpha components (peaks at 8, 10, and 13 Hz) and a midfrontal theta (6Hz) component, accounting for 37.0% of FC variance. These spatial FC components were consistent with well-known networks (e.g., default mode, visual, and sensorimotor), and four were sensitive to eyes open/closed conditions. Most FC components had good-to-excellent internal consistency (odd/even epochs, eyes open/closed) and test-retest reliability (ICCs ≥ .8). Moreover, the FC component structure was generally present in subsamples (session × odd/even epoch, or smaller subgroups [n= 7-10]), as indicated by high similarity of component loadings across PCA solutions. Apart from systematically reducing FC dimensionality, our approach avoids arbitrary thresholds and allows quantification of meaningful and reliable network components that may prove to be of high relevance for basic and clinical research applications.