Time Dependence Research Articles

Allofus: an R package to facilitate use of the All of Us Researcher Workbench.

Despite easy-to-use tools like the Cohort Builder, using All of Us Research Program data for complex research questions requires a relatively high level of technical expertise. We aimed to increase research and training capacity and reduce barriers to entry for the All of Us community through an R package, allofus. In this article, we describe functions that address common challenges we encountered while working with All of Us Research Program data, and we demonstrate this functionality with an example of creating a cohort of All of Us participants by synthesizing electronic health record and survey data with time dependencies. All of Us Research Program data are widely available to health researchers. The allofus R package is aimed at a wide range of researchers who wish to conduct complex analyses using best practices for reproducibility and transparency, and who have a range of experience using R. Because the All of Us data are transformed into the Observational Medical Outcomes Partnership Common Data Model (OMOP CDM), researchers familiar with existing OMOP CDM tools or who wish to conduct network studies in conjunction with other OMOP CDM data will also find value in the package. We developed an initial set of functions that solve problems we experienced across survey and electronic health record data in our own research and in mentoring student projects. The package will continue to grow and develop with the All of Us Research Program. The allofus R package can help build community research capacity by increasing access to the All of Us Research Program data, the efficiency of its use, and the rigor and reproducibility of the resulting research.

Quantum temporal logic and reachability problems of matrix semigroups

We study the reachability problems of a quantum finite automaton. More precisely, we introduce quantum temporal logic (QTL) that specifies the time-dependent behavior of quantum finite automaton by presenting the time dependence of events temporal operators ◊ (eventually) and □ (always) and employing the projections on subspaces as atomic propositions. The satisfiability of QTL formulae corresponds to various reachability problems of matrix semigroups. We prove that the satisfiability problems for □∨impi, ◊□∨impi and □◊∨impi with atomic propositions pi are decidable. This result solves the open problem of Li and Ying 2014. Notably, the decidability of □◊p can be interpreted as a generalization of Skolem-Mahler-Lech's celebrated theorem based on additive number theory. This paper's last part shows how the quantum finite automaton can model the general concurrent quantum programs, which may involve an arbitrary classical control flow.

Three approaches to modelling heating and evaporation of monocomponent droplets

Three approaches to modelling the heating and evaporation of monocomponent droplets are compared. Firstly, the heat rate supplied to the droplets to raise their internal energy is calculated based on the observation that steady-state equations for heat and mass balance in the gas phase should lead to the same droplet evaporation rates. The direct calculation of the above-mentioned heat rate is used in the second approach; the value of this rate is then used for the estimation of the droplet evaporation rate using the Spalding heat transfer number. In the third approach, the same algorithm as in the second approach is used to calculate the heat rate but the mass evaporation rate in this approach is inferred from the coupled solution to the momentum, mass and energy conservation equations in the gas phase; the gas mixture density in this approach depends on temperature. The predictions of the numerical algorithms for these approaches are compared with experimentally observed time dependencies of the rates of change of radii and average temperatures of n-decane droplets at initial temperatures and radii equal to 300 K and 0.85 mm, respectively, placed in a gas at temperatures 500 K and 760 K. It is shown that the algorithm for the third approach predicts values which are close to the experimental data.

CONTROLLED RELEASE OF ESSENTIAL OILS FROM MICROCAPSULES BASED ON GUM ARABIC AND CHITOSAN PREPARED BY COMPLEX COACERVATION AS MOSQUITO REPELLENT AND ANTIMICROBIAL MATERIAL

Microcapsules loaded with essential oils, namely Litsea cubeba, Cymbopogon nardus and Cymbopogon citratus, in gum arabic and chitosan were prepared to explore their mosquito repelling effects and their antimicrobial function. The encapsulation ratio, along with the materials characterization and release behavior of the essential oils from the microcapsules were studied, together with temperature and time dependences. Mosquito repellency was assessed against Ae. aegypti using the “arm-in-cage” method, and the antibacterial activity was tested against E. coli and S. aureus. The results demonstrated that microcapsules loaded with essential oils were successfully prepared for all three essential oils. Also, the results showed that the highest encapsulation ratio was found for microcapsules loaded with Cymbopogon citratus oil. The microcapsules loaded with all essential oils were effective in prolonging protection time against Ae. aegypti, especially in the case of the Litsea cubeba oil, while the Cymbopogon nardus and Cymbopogon citratus oils yielded the highest antibacterial activity against E. coli and S. aureus.

Local operator quench induced by two-dimensional inhomogeneous and homogeneous CFT Hamiltonians

We explore non-equilibrium processes in two-dimensional conformal field theories (2d CFTs) due to the growth of operators induced by inhomogeneous and homogeneous Hamiltonians by investigating the time dependence of the partition function, energy density, and entanglement entropy. The non-equilibrium processes considered in this paper are constructed out of the Lorentzian and Euclidean time evolution governed by different Hamiltonians. We explore the effect of the time ordering on entanglement dynamics so that we find that in a free boson CFT and RCFTs, this time ordering does not affect the entanglement entropy, while in the holographic CFTs, it does. Our main finding is that in the holographic CFTs, the non-unitary time evolution induced by the inhomogeneous Hamiltonian can retain the initial state information longer than in the unitary time evolution.

A practical vehicle routing problem in small and medium cities for fuel consumption minimization

Today, reducing fossil fuel consumption in the transport sector is one of the important requirements to preserve the ecological environment. In this paper, we investigated a logistics problem in small and medium cities. We proposes the time-dependent vehicle routing problem model in small and medium cities considering heterogeneous fleets, time windows, multi-trip, time dependency, and road network. We conducted a numerical analysis on fuel consumption minimizing path selection between two customer nodes and found that the path selection is independent of the payload in most cases. The model is formulated as a mathematical integer linear programming model, and small problems are solved using a commercial optimization solver. For large-scale instances, we proposed a heuristic algorithm based on the variable neighborhood search and evaluated its performance. The proposed algorithm can decrease fuel consumption by 25 % compared to manual routing and scheduling. Furthermore, for provide useful managerial insights, sensitivity analyses were performed considering different vehicle capacities.

Population Pharmacokinetic Modeling of Adavosertib (AZD1775) in Patients with Solid Tumors.

Adavosertib (AZD1775) is a potent small-molecule inhibitor of Wee1 kinase. This analysis utilized pharmacokinetic data from 8 Phase I/II studies of adavosertib to characterize the population pharmacokinetics of adavosertib in patients (n = 538) with solid tumors and evaluate the impact of covariates on exposure. A nonlinear mixed-effects modeling approach was employed to estimate population and individual parameters from the clinical trial data. The model for time dependency of apparent clearance (CL) was developed in a stepwise manner and the final model validated by visual predictive checks (VPCs). Using an adavosertib dose of 300 mg once daily on a 5 days on/2 days off dosing schedule given 2 weeks out of a 3-week cycle, simulation analyses evaluated the impact of covariates on the following exposure metrics at steady state: maximum concentration during a 21-day cycle, area under the curve (AUC) during a 21-day cycle, AUC during the second week of a treatment cycle, and AUC on day 12 of a treatment cycle. The final model was a linear 2-compartment model with lag time into the dosing compartment and first-order absorption into the central compartment, time-varying CL, and random effects on all model parameters. VPCs and steady-state observations confirmed that the final model satisfied all the requirements for reliable simulation of randomly sampled Phase I and II populations with different covariate characteristics. Simulation-based analyses revealed that body weight, renal impairment status, and race were key factors determining the variability of drug-exposure metrics.

Assessment of Obesity as Risk Factor of Lumbar Disc Surgery: Retrospective Analysis of 598 Cases and Simulated Surgery on 3D-Printed Models.

(1) Background: Obesity poses known risks in surgery, including a prolonged operation time and postoperative complications. Given the rising obesity rates and frequent lumbar disc surgeries, understanding these risks is crucial. This study aims to assess the impact of obesity on operation duration and postoperative complications in lumbar disc prolapse surgery. (2) Methods: We retrospectively analyzed 598 patients with monosegmental disc herniation, correlating their body mass index (BMI) as a surrogate parameter for obesity with operation time. Excluding complex cases (multi-segmental herniations or recurrent herniations), complication rates and hospital stays were recorded. Simulated surgeries on 3D-printed models of varying obesity levels examined operation times and instrument suitability. (3) Results: Of these patients, 438 patients had a BMI of <30, and 160 patients had a BMI of ≥30. Complication rates showed no significant differences between groups. Linear regression analysis failed to establish a sole dependency of operation time on BMI, with R2 = 0.039 for the normal-weight group (BMI < 30) and R2 = 0.059 for the obese group (BMI ≥ 30). The simulation operations on the 3D-printed models of varying degrees of obesity showed a significant increase in the simulated operation time with higher levels of obesity. A geometrically inadequate set of surgical instruments was assumed to be a significant factor in the simulated increase in operating time. (4) Conclusions: While various factors influence operation time, obesity alone does not significantly increase it. However, simulated surgeries highlighted the impact of obesity, particularly on instrument limitations. Understanding these complexities is vital for optimizing surgical outcomes in obese patients.

Universal scaling in far-from-equilibrium quantum systems: An equivalent differential approach

Recent progress in out-of-equilibrium closed quantum systems has significantly advanced the understanding of mechanisms behind their evolution toward thermalization. Notably, the concept of nonthermal fixed points (NTFPs)-responsible for the emergence of spatiotemporal universal scaling in far-from-equilibrium systems-has played a crucial role in both theoretical and experimental investigations. In this work, we introduce a differential equation that has the universal scaling associated with NTFPs as a solution. The advantage of working with a differential equation, rather than only with its solution, is that we can extract several insightful properties not necessarily present in the solution alone. How the differential equation is derived allows physical interpretation of the universal exponents in terms of the time dependence of the amplitude of the distributions and their momentum scaling. Employing two limiting cases of the equation, we determined the universal exponents related to the scaling using the distributions near just two momentum values. We established a solid agreement with previous investigations by validating this approach with three distinct physical systems. This consistency highlights the universal nature of scaling due to NTFPs and emphasizes the predictive capabilities of the proposed differential equation. Moreover, under specific conditions, the equation predicts a power-law related to the ratio of the two universal exponents, leading to implications concerning particle and energy transport. This suggests that the observed power-laws in far-from-equilibrium turbulent fluids could be related to the universal scaling due to NTFPs, potentially offering insights into the study of turbulence.

Multiscale graph based spatio-temporal graph convolutional network for energy consumption prediction of natural gas transmission process

Energy consumption prediction is crucial for planning and managing natural gas networks, enhancing transmission efficiency. However, most of relevant studies fail to consider the topology of natural gas network. Therefore, a multiscale graph based spatio-temporal graph convolutional network model (MG-STGCN) is proposed, which can extract the multi-scale relationship of data. Based on graph convolutional and temporal gated convolution network, data correlation, spatial dependence and time dependence are considered to improve the prediction effect. In order to verify the effect of the model, the model is tested based on two natural gas networks in different region of China. The single step prediction results of MG-STGCN are significantly better than spatio-temporal graph convolutional network (STGCN), long short-term memory (LSTM), gate recurrent unit (GRU) and temporal convolutional network (TCN), which proves the effectiveness and generalization ability of MG-STGCN. The training time of MG-STGCN is reduced by 20.8 % compared with STGCN. In different prediction time step, the average prediction effect of MG-STGCN is better than that of other methods, and the performance improvement rate is not less than 8.6 %. MG-STGCN can well capture the parameter correlation, spatial and temporal dependence of data, and achieve effective prediction of pipeline energy consumption.

On the entanglement of co-ordinate and momentum degrees of freedom in noncommutative space

In this paper, we investigate the quantum entanglement induced by phase-space noncommutativity. Both the position–position and momentum–momentum noncommutativity are incorporated to study the entanglement properties of coordinate and momentum degrees of freedom under the shade of oscillators in noncommutative space. Exact solutions for the systems are obtained after the model is re-expressed in terms of canonical variables, by performing a particular Bopp’s shift to the noncommuting degrees of freedom. It is shown that the bipartite Gaussian state for an isotropic oscillator is always separable. To extend our study for the time-dependent system, we allow arbitrary time dependency on parameters. The time-dependent isotropic oscillator is solved with the Lewis–Riesenfeld invariant method. It turns out that even for arbitrary time-dependent scenarios, the separability property does not alter. We extend our study to the anisotropic oscillator, which provides an entangled state even for time-independent parameters. The Wigner quasi-probability distribution is constructed for a bipartite Gaussian state. The noise matrix (covariance matrix) is explicitly studied with the help of Wigner distribution. Simon’s separability criterion (generalized Peres–Horodecki criterion) has been employed to find the unique function of the (mass and frequency) parameters, for which the bipartite states are separable. In particular, we show that the mere inclusion of non-commutativity of phase-space is not sufficient to generate the entanglement, rather anisotropy is important at the same footing. We explore the experimental viability of our result through the computation of extractable work for the current situation.

Energy Barriers for the Spontaneous Magnetization Reversal of the Atomic Co Chains on Pt(664) Surface in the Model with Dzyaloshinskii–Moriya Interaction

The analytical approach has been developed in the framework of the continuous XY-model. This approach allows calculating the spontaneous magnetization reversal time of finite-length atomic chains on the metallic surface. The interaction of the magnetic moments of atoms is described by the classical Hamiltonian, which includes the Heisenberg exchange interaction, the Dzyaloshinskii–Moriya interaction, and the magnetic anisotropy energy. Using the Co/Pt(664) system as an example, it has been shown that the proposed method is in a good agreement with the results of the numerical simulation in the limit of short and long atomic chains. And for atomic chains of intermediate length, it can be used to estimate an upper bound on the spontaneous magnetization reversal time. We obtained the dependences of the spontaneous magnetization reversal time of finite-length Co chains the value of the exchange integral, parameters of the magnetic anisotropy, and also on the value of the projection of the Dzyaloshinskii vector onto the axis perpendicular to the plane containing the magnetic moments of the atoms. It is shown that the proposed method has a wide range of applicability both in terms of temperature and the values of the physical parameters characterizing the magnetic properties of the atomic chains.

Mass transfer at vapor-liquid interfaces of H2O + CO2 mixtures studied by molecular dynamics simulation

Abstract In many industrial applications as well as in nature, the mass transfer of CO2 at vapor-liquid interfaces in aqueous systems plays an important role. In this work, this process was studied on the atomistic level using non-equilibrium molecular dynamics simulations. In a first step, a molecular model of the system water + CO2 was developed that represents both bulk and interfacial equilibrium properties well. This system is characterized by a very large adsorption and enrichment of CO2 at the vapor-liquid interface. Then, non-equilibrium mass transfer simulations were carried out using a method that was developed recently: CO2 is inserted into the vapor phase of a simulation box which contains a liquid slab. Surprising effects are observed at the interface such as a net repulsion of CO2 particles from the interface and a complex time dependence of the amount of CO2 adsorbed at the interface.

Screened optimally tuned range separated hybrid functional for solvated low bandgap molecular systems.

The description of electronic properties of low bandgap molecular system is often performed by using density functional theory (DFT) and time dependent (TD) DFT calculations with the optimally tuned range-separated hybrid (OT-RSH) functional, as it contains the necessary ingredients to reliably predict charge transfer excitations. However, the range separating parameter (ω) is system-dependent and its optimization, including the chemical environment, is intricate. Refaely-Abramson et al. demonstrated that the gap renormalization in molecular crystals, a ground state property, can be represented by an OT-RSH functional screened by ɛstatic [Phys. Rev. B 88, 081204(R) (2013)], the zero frequency scalar dielectric constant. In this study, we propose the use of an OT-RSH functional screened by the scalar dielectric constant in the high frequency limit (OT-sRSH), ɛ∞, an appropriate constraint for vertical ionization energies or excitations in a dielectric environment. We have performed calculations for S,N-heteroacene derivatives in tetrahydrofuran and dichloromethane. The "unscreened" OT-RSH functional tends to underestimate experimental ionization potentials (IPs) and optical gaps (Egs) by up to 1.5 and 0.5eV, respectively. In contrast, OT-sRSH functional calculations underestimate IPs and Egs by only 0.4 and 0.2eV. We also compared the OT-sRSH results to explicitly solvated OT-RSH functional calculations for oligothiophenes in dioxane, benzene in ammonia, and methylene blue in water. We observe that both the approaches perform similarly for weakly interacting intermolecular systems and deviate for solvent-solute interacting systems, as expected. In conclusion, the OT-sRSH functional can describe molecular systems with environmental polarization effects accurately, a step toward describing realistic molecular systems.

S[formula omitted]T-Net: A novel electroencephalogram signals-oriented emotion recognition model

In this paper, a novel skipping spatial–spectral–temporal network (S3T-Net) is developed to handle intra-individual differences in electroencephalogram (EEG) signals for accurate, robust, and generalized emotion recognition. In particular, aiming at the 4D features extracted from the raw EEG signals, a multi-branch architecture is proposed to learn spatial–spectral cross-domain representations, which benefits enhancing the model generalization ability. Time dependency among different spatial–spectral features is further captured via a bi-directional long-short term memory module, which employs an attention mechanism to integrate context information. Moreover, a skip-change unit is designed to add another auxiliary pathway for updating model parameters, which alleviates the vanishing gradient problem in complex spatial–temporal network. Evaluation results show that the proposed S3T-Net outperforms other advanced models in terms of the emotion recognition accuracy, which yields an performance improvement of 0.23% , 0.13%, and 0.43% as compared to the sub-optimal model in three test scenes, respectively. In addition, the effectiveness and superiority of the key components of S3T-Net are demonstrated from various experiments. As a reliable and competent emotion recognition model, the proposed S3T-Net contributes to the development of intelligent sentiment analysis in human–computer interaction (HCI) realm.

Implementation of Nonadiabatic Molecular Dynamics for Intersystem Crossing Based on a Time-Dependent Density-Functional Tight-Binding Method.

Intersystem crossing (ISC) and internal conversion (IC) are types of nonadiabatic transitions that play important roles in a wide range of fields, including photochemistry, photophysics, and photobiology. The nonadiabatic molecular dynamics (NA-MD) method is a powerful tool for computational simulations of dynamic phenomena involving nonadiabatic transitions. In this study, we implemented the NA-MD method, which treats ISC and IC on an equal footing, where the electronic structure is treated at the level of the time-dependent (TD) density-functional tight-binding (DFTB) method, a low-cost semiempirical analog of TD density functional theory (DFT). In particular, the spin-orbit coupling calculation algorithm was implemented in the TD-DFTB framework, and the results showed trends similar to those obtained using TD-DFT. In addition, the NA-MD method successfully reproduced ultrafast ISC of 2-nitronaphthalene.

Rat-Tail Models for Studying Hand-Arm Vibration Syndrome: A Comparison between Living and Cadaver Rat Tails

Over-exposure of the hand-arm system to intense vibration and force over time may cause degeneration of the vascular, neurological, and musculoskeletal systems in the fingers. A novel animal model using rat tails has been developed to understand the health effects on human fingers exposed to vibration and force when operating powered hand tools or workpieces. The biodynamic responses, such as vibration stress, strain, and power absorption density, of the rat tails can be used to help evaluate the health effects related to vibration and force and to establish a dose-effect relationship. While the biodynamic responses of cadaver rat tails have been investigated, the objective of the current study was to determine whether the biodynamic responses of living rat tails are different from those of cadaver rat tails, and whether the biodynamic responses of both living and cadaver tails change with exposure duration. To make direct comparisons, the responses of both cadaver and living rat tails were examined on four different testing stations. The transfer function of each tail under a given contact force (2 N) was measured at each frequency in the one-third octave bands from 20 to 1000 Hz, and used to calculate the mechanical system parameters of the tails. The transfer functions were also measured at different exposure durations to determine the time dependency of the response. Differences were observed in the vibration biodynamic responses between living and cadaver tails, but the general trends were similar. The biodynamic responses of both cadaver and living rat tails varied with exposure duration.

Hybrid mechanism of electrical breakdown in ferroelectric materials under high-pressure shock loading

The unique ability of ferroelectrics to generate high voltage under shock loading is limited by electrical breakdown within the shock-compressed ferroelectric material. Breakdown is a hybrid process of initiation and growth. The possible mechanisms of electrical breakdown in ferroelectric films and bulk ceramics subjected to high-pressure shock loading are discussed and experiments designed to elucidate which mechanisms govern breakdown. Gigapascal shock loading experiments were performed on poled Pb0.99(Zr0.95Ti0.05)0.98Nb0.02O3 ferroelectric film specimens in the range of 32–156 μm thickness to determine the dependence of the breakdown field on thickness and on film specimens in the range of 4–16 mm length to determine the dependence of the breakdown field on the duration of shock compression. The resulting breakdown-field vs thickness and breakdown-field vs shock transit time dependencies are consistent with a hybrid electron emission initiation and Joule heating microchannel growth mechanism. Further analysis of data previously obtained on shock-compressed 0.27Pb(In1/2Nb1/2)O3–0.47Pb(Mg1/3Nb2/3)O3–0.26PbTiO3 ferrvoelectric single crystals and Pb(Zr0.65Ti0.35)O3, Pb0.99(Zr0.52Ti0.48)0.99Nb0.01O3, Pb0.99(Zr0.95Ti0.05)0.98Nb0.02O3 bulk ceramics is consistent with this dual mechanism. It appears that neither chemical composition nor microstructure (single crystal vs polycrystalline) of the ferroelectric material has a significant effect on the breakdown mechanism in shocked ferroelectrics.

Revisiting shear stress tensor evolution: Nonresistive magnetohydrodynamics with momentum-dependent relaxation time

This study aims to develop second-order relativistic viscous magnetohydrodynamics (MHD) derived from kinetic theory within an extended relaxation time approximation (momentum/energy dependent) for the collision kernel. The investigation involves a detailed examination of shear stress tensor evolution equations and associated transport coefficients. The Boltzmann equation is solved using a Chapman-Enskog-like gradient expansion for a charge-conserved conformal system, incorporating a momentum-dependent relaxation time. The derived relativistic nonresistive, viscous second-order MHD equations for the shear stress tensor reveal significant modifications in the coupling with dissipative charge current and magnetic field due to the momentum dependence of the relaxation time. By utilizing a power law parametrization to quantify the momentum dependence of the relaxation time, the anisotropic magnetic field-dependent shear coefficients in the Navier-Stokes limit have been investigated. The resulting viscous coefficients are seen to be sensitive to the momentum dependence of the relaxation time. Published by the American Physical Society 2024

Polygenic hazard score models for the prediction of Alzheimer's free survival using the lasso for Cox's proportional hazards model.

The prediction of the susceptibility of an individual to a certain disease is an important and timely research area. An established technique is to estimate the risk of an individual with the help of an integrated risk model, that is, a polygenic risk score with added epidemiological covariates. However, integrated risk models do not capture any time dependence, and may provide a point estimate of the relative risk with respect to a reference population. The aim of this work is twofold. First, we explore and advocate the idea of predicting the time-dependent hazard and survival (defined as disease-free time) of an individual for the onset of a disease. This provides a practitioner with a much more differentiated view of absolute survival as a function of time. Second, to compute the time-dependent risk of an individual, we use published methodology to fit a Cox's proportional hazard model to data from a genetic SNP study of time to Alzheimer's disease (AD) onset, using the lasso to incorporate further epidemiological variables such as sex, APOE (apolipoprotein E, a genetic risk factor for AD) status, 10 leading principal components, and selected genomic loci. We apply the lasso for Cox's proportional hazards to a data set of 6792 AD patients (composed of 4102 cases and 2690 controls) and 87 covariates. We demonstrate that fitting a lasso model for Cox's proportional hazards allows one to obtain more accurate survival curves than with state-of-the-art (likelihood-based) methods. Moreover, the methodology allows one to obtain personalized survival curves for a patient, thus giving a much more differentiated view of the expected progression of a disease than the view offered by integrated risk models. The runtime to compute personalized survival curves is under a minute for the entire data set of AD patients, thus enabling it to handle datasets with 60,000-100,000 subjects in less than 1 h.