Variable Time Research Articles

Reaction Kinetics using a Chemputable Framework for Data Collection and Analysis.

Automated chemistry platforms have been widely explored, but many focus on fixed tasks for chemical synthesis or analysis. However, a typical synthetic chemistry workflow utilizes both, such as kinetic measurements for reaction development and optimization. Due to their repetitive and time-consuming nature, kinetic measurements are often omitted, which limits the mechanistic investigation of reactions. Herein, we present a "Chemputer" platform with on-line analytics (UV/Vis, NMR) which automates routine kinetic measurements. The system's capabilities are showcased by exploring an inverse electron-demand Diels-Alder using initial rate measurements, a metal complexation using variable time normalization analysis (VTNA), and formation of a series of tosylamide derivatives using Hammett analysis. Over 60 individual experiments are presented which required minimal intervention, highlighting the significant time savings of automation. Owing to the modular design of the platform, which facilitates rapid integration of commercial analytical tools, our approach is widely accessible and adjustable to the reaction under investigation. The platform is operated using the chemical programming language, XDL, hence experimental procedures and results are stored in a precise, computer-readable format. We propose that widespread adoption of this reporting protocol in the chemical community could build a database of validated kinetic data beneficial for Machine Learning.

Platelet Modeling in DHF Patients Using Local Polynomial Semiparametric Regression on Longitudinal Data

Regression analysis is one of the statistical methods used to model the relationship between response variables and predictor variables. Semiparametric regression is a combination of parametric and nonparametric regression. The estimator used in estimating the semiparametric regression model in this research is the Local Polynomial. Longitudinal data can be found in the health sector, including dengue hemorrhagic fever (DHF) data. The laboratory criteria for indication of DHF is thrombocytopenia. This research aims to obtain platelets model for DHF patients that can be used for forecasting so that it is hoped that it can provide information to the medical team in treating DHF patients. The estimated model used is Local Polynomial semiparametric regression on longitudinal data. The response variables in this research were platelets of DHF patients, which were influenced by hemoglobin as parametric predictor variable and examination time while hospitalized as nonparametric predictor variable. In the local polynomial regression model, it is necessary to select the optimal bandwidth and polynomial order method, GCV. The optimum bandwidth selection based on the GCV method obtained is 1.5 and polynomial order of 2, then applied to DHF patient platelet data, producing an estimated local polynomial semiparametric regression model that follows the actual data pattern. Modeling the platelets of DHF patients obtained using a local polynomial estimator resulted in an R2 value of 84.25% and MAPE of 4.5%, indicating highly accurate forecasting, so it can be concluded that the resulting model is better at predicting.

How aging shapes our sense of agency

The sense of agency refers to the feeling of controlling one’s actions and their effects on the external environment. Here, we tested how the physiological process of aging affects the agency experience by taking advantage of a validated ecological experimental paradigm and exploring the different dimensions of agency. We tested 60 young and older adults during active and passive movements, causing, after a variable time delay, an external sensorial event. We collected overt agency judgments (i.e., explicit agency dimension), and we measured the perceived compression of the time interval between the active/passive movements and outcomes (to quantify the intentional binding phenomenon, an implicit index of agency). Our results indicate that the sense of agency significantly changes across the adult life span, with older participants exhibiting a reduced sense of agency, both at the explicit and implicit level. Crucially, the temporal dimension of the action outcome did not affect their agency experience. We suggest that elderly adults are more reliant on internal predictions, making them less sensitive to cognitive biases and external manipulations. We discuss these results in the domain of neurocognitive models of motor control, with reference to how aging affects the weighting process of predictive and sensory signals for efficient sensorimotor integration.

Robust passivity-based nonlinear controller design for bilateral teleoperation system under variable time delay and variable load disturbance

Abstract This research focuses on implementing a robust passivity-based nonlinear control method for bilateral/teleoperation systems. The key challenge is addressing communication pathways between the master and slave, control delays, and load disturbances, which can lead to instability and reduced transparency. To tackle these issues, the proposed controller incorporates a second-order super-twisting sliding-mode observer to counteract communication and control delays. A sliding mode assist disturbance observer compensates for load torque variations. The approach aims to ensure stability and transparency by handling time-varying delays. The system model comprises two interconnected direct-drive motors, simulating robotic configurations without a physical robot. The nonlinear controller framework simplifies the complex bilateral control problem, significantly improving stability and transparency performance. Computer simulations with step and sinusoidal inputs demonstrate the effectiveness of the approach, providing a satisfactory level of accuracy and transparency between estimated and actual slave positions, even with varying delays and load variations. The research contributes to control engineering by offering a robust method to enhance bilateral system performance, ensuring stable and transparent communication between the master and slave, particularly suitable for real-time internet-based bilateral control systems.

Damage creep model and application for sandy mudstone considering the effect of immersion deterioration

Abstract Aiming at the problem of performance degradation and large deformation of sandy mudstone after immersion in water, the compression test is carried out. The damage and deterioration law of strength and elastic modulus of immersed rock mass is analyzed, and the function relationship between rock damage variable and soaking time is obtained by fitting. Combined with the Hoek-Brown criterion and Mohr-Coulomb criterion, the calculation method of instantaneous cohesion and instantaneous internal friction angle of damaged rock mass is derived based on the tangent method, and the equivalent Mohr-Coulomb criterion which can effectively characterize the nonlinear strength characteristics of damaged rock mass is given. Based on the built-in creep model Cvisc of Flac3D, a damage creep model is given by introducing the damage factor and nonlinear strength criterion of immersed rock mass, which is more suitable for describing the creep characteristics of immersed sandy mudstone. The validity of the model is verified by comparing with the measured results.

Multi-Year Time Series Transfer Learning: Application of Early Crop Classification

Crop classification is an important task in remote sensing with many applications, such as estimating yields, detecting crop diseases and pests, and ensuring food security. In this study, we combined knowledge from remote sensing, machine learning, and agriculture to investigate the application of transfer learning with a transformer model for variable length satellite image time series (SITS). The objective was to produce a map of agricultural land, reduce required interventions, and limit in-field visits. Specifically, we aimed to provide reliable agricultural land class predictions in a timely manner and quantify the necessary amount of reference parcels to achieve these outcomes. Our dataset consisted of Sentinel-2 satellite imagery and reference crop labels for Slovenia spanning over years 2019, 2020, and 2021. We evaluated adaptability through fine-tuning in a real-world scenario of early crop classification with limited up-to-date reference data. The base model trained on a different year achieved an average F1 score of 82.5% for the target year without having a reference from the target year. To increase accuracy with a new model trained from scratch, an average of 48,000 samples are required in the target year. Using transfer learning, the pre-trained models can be efficiently adapted to an unknown year, requiring less than 0.3% (1500) samples from the dataset. Building on this, we show that transfer learning can outperform the baseline in the context of early classification with only 9% of the data after 210 days in the year.

Shallow defects and variable photoluminescence decay times up to 280 µs in triple-cation perovskites.

Quantifying recombination in halide perovskites is a crucial prerequisite to control and improve the performance of perovskite-based solar cells. While both steady-state and transient photoluminescence are frequently used to assess recombination in perovskite absorbers, quantitative analyses within a consistent model are seldom reported. We use transient photoluminescence measurements with a large dynamic range of more than ten orders of magnitude on triple-cation perovskite films showing long-lived photoluminescence transients featuring continuously changing decay times that range from tens of nanoseconds to hundreds of microseconds. We quantitatively explain both the transient and steady-state photoluminescence with the presence of a high density of shallow defects and consequent high rates of charge carrier trapping, thereby showing that deep defects do not affect the recombination dynamics. The complex carrier kinetics caused by emission and recombination processes via shallow defects imply that the reporting of only single lifetime values, as is routinely done in the literature, is meaningless for such materials. We show that the features indicative for shallow defects seen in the bare films remain dominant in finished devices and are therefore also crucial to understanding the performance of perovskite solar cells.

Effects of rotation and temperature‐dependent viscosity on thermal convection in Oldroydian fluid saturating porous media: A modified stability analysis

AbstractThe onset of thermal convection in an incompressible Oldroydian fluid‐saturating porous media is examined to study the combined impact of uniform rotation and temperature‐dependent viscosity. A characteristic equation from the basic hydrodynamic equations governing the Brinkman–Oldroyd model is derived using linear stability theory and modified Boussinesq approximation. For various combinations of stress‐free and slip‐free boundaries, the expressions for the Darcy–Rayleigh numbers for both non‐oscillatory as well as oscillatory convection with linear and exponential temperature‐dependent viscosity are derived, using the “weighted residual method.” The effects of rotation, variable viscosity parameter, strain retardation and stress relaxation time parameters and other fluid parameters on non‐oscillatory and oscillatory convection are investigated numerically and the results are presented graphically. From the analysis, it is found that overstability is the preferred mode of onset of convection. The rotation, the coefficient of specific heat variations (due to temperature variation), and the strain retardation time have a stabilizing influence on the stability of the system, whereas the stress relaxation imparts a destabilizing effect. Additionally, it is noticed that the variable viscosity parameter and Brinkman‐Darcy number stabilize the system for each set of boundary conditions.

River-floodplain connectivity and residence times controlled by topographic bluffs along a backwater transition

The morphology of river levees and floodplains is an important control on river-floodplain connectivity within a river system under sub-bankfull conditions, and this morphology changes as a river approaches the coast due to backwater influence. Floodplain width can also vary along a river, and floodplain constrictions in the form of bluffs adjacent to the river can influence inundation extent. However, the relative controls of backwater-influenced floodplain topography and bluff topography on river-floodplain connectivity have not been studied. We measure discharge along the lower Trinity River (Texas, USA) during high flow to determine which floodplain features are associated with major river-floodplain flow exchanges. We develop a numerical model representing the transition to backwater-dominated river hydraulics, and quantify downstream changes in levee channelization, inundation, and fluxes along the river-floodplain boundary. We model passive particle transport through the floodplain, and compute residence times as a function of location where particles enter the floodplain. We find that bluff topography controls flow from the floodplain back to the river, whereas levee topography facilitates flow to the floodplain through floodplain channels. Return flow to the river is limited to locations just upstream of bluffs, even under receding flood conditions, whereas outflow locations are numerous and occur all along the river. Residence times for particles entering the floodplain far upstream of bluffs are as much as two orders of magnitude longer than those for particles entering short distances upstream of bluffs. This study can benefit floodplain ecosystem management and restoration plans by informing on the key locations of lateral exchange and variable residence time distributions in river-floodplain systems.

Evaluation of ancient DNA imputation: a simulation study

Ancient genomic data is becoming increasingly available thanks to recent advances in high-throughput sequencing technologies. Yet, post-mortem degradation of endogenous ancient DNA often results in low depth of coverage and subsequently high levels of genotype missingness and uncertainty. Genotype imputation is a potential strategy for increasing the information available in ancient DNA samples and thus improving the power of downstream population genetic analyses. However, the performance of genotype imputation on ancient genomes under different conditions has not yet been fully explored, with all previous work primarily using an empirical approach of downsampling high coverage paleogenomes. While these studies have provided invaluable insights into best practices for imputation, they rely on a fairly limited number of existing high coverage samples with significant temporal and geographical biases. As an alternative, we used a coalescent simulation approach to generate genomes with characteristics of ancient DNA in order to more systematically evaluate the performance of two popular imputation software, BEAGLE and GLIMPSE, under variable divergence times between the target sample and reference haplotypes, as well as different depths of coverage and reference sample size. Our results suggest that for genomes with coverage <=0.1x imputation performance is poor regardless of the strategy employed. Beyond 0.1x coverage imputation is generally improved as the size of the reference panel increases, and imputation accuracy decreases with increasing divergence between target and reference populations. It may thus be preferable to compile a smaller set of less diverged reference samples than a larger more highly diverged dataset. In addition, the imputation accuracy may plateau beyond some level of divergence between the reference and target populations. While accuracy at common variants is similar regardless of divergence time, rarer variants are better imputed on less diverged target samples. Furthermore, both imputation software, but particularly GLIMPSE, overestimate high genotype probability calls, especially at low coverages. Our results provide insight into optimal strategies for ancient genotype imputation under a wide set of scenarios, complementing previous empirical studies based on imputing downsampled high-coverage ancient genomes.

Global Existence and Uniqueness of Solutions of Integral Equations with Multiple Variable Delays and Integro Differential Equations: Progressive Contractions

In this work, we delve into a nonlinear integral equation (IEq) with multiple variable time delays and a nonlinear integro-differential equation (IDEq) without delay. Global existence and uniqueness (GEU) of solutions of that IEq with multiple variable time delays and IDEq are investigated by the fixed point method using progressive contractions, which are due to T.A. Burton. We prove four new theorems including sufficient conditions with regard to GEU of solutions of the equations. The results generalize and improve some related published results of the relevant literature.

Modeling Study of Factors Determining Efficacy of Biological Control of Adventive Weeds

We model the spatiotemporal dynamics of a community consisting of competing weed and cultivated plant species and a population of specialized phytophagous insects used as the weed biocontrol agent. The model is formulated as a PDE system of taxis–diffusion–reaction type and computer-implemented for one-dimensional and two-dimensional cases of spatial habitat for the Neumann zero-flux boundary condition. In order to discretize the original continuous system, we applied the method of lines. The obtained system of ODEs is integrated using the Runge–Kutta method with a variable time step and control of the integration accuracy. The numerical simulations provide insights into the mechanism of formation of solitary population waves (SPWs) of the phytophage, revealing the factors that determine the efficacy of combined application of the phytophagous insect (classical biological method) and cultivated plant (phytocenotic method) to suppress weed foci. In particular, the presented results illustrate the stabilizing action of cultivated plants, which fix the SPW effect by occupying the free area behind the wave front so that the weed remains suppressed in the absence of a phytophage.

Variable time steps in the numerical implementation of viscoelastic fractional models for laminated glass

Abstract We elaborate numerical approaches to calculate the rheological response of laminated glass beams, whose viscoelastic interlayer is modelled via fractional calculus. This mathematical description is very effective when the relaxation function of the polymer can be expressed by continuously connected branches of power-laws, as is the case for most materials used to laminate glass. The classical approach uses the Grünwald-Letnikov approximation of fractional derivatives, but it requires constant time steps, which would become very large to reasonably cover the entire observation time, thus losing accuracy. We propose to use the L1 algorithm with increasing time steps, which is well suited to the power law character of the relaxation function. This allows to follow the long-term creep response, providing a better approximation when needed. The method is implemented for beams laminated with viscolastic interlayers whose relaxation is described by four branches of power laws, to cover most practical cases. Numerical experiments shows its advantages over the Grünwald-Letnikov approach for characterizing the long-term structural response.

Refined Evolutionary Trees Through an Exceptionally Compatible Alignment-Substitution Model

A phylogenetic tree commonly represents evolutionary relationships within a set of protein sequences. Various methods and strategies have been used to improve the accuracy of phylogenetic trees, but their capacity to derive a biologically credible relationship appears to be overestimated. Although the quality of the protein sequence alignment and the choice of substitution matrix are preliminary constraints to define the biological accuracy of the overlapped residues, the alignment is not iteratively optimized through the statistical testing of residue-substitution models. The exact alignment protocol and substitution model information are by default used for every sequence set by a server to construct an often-irrelevant phylogenetic tree, and no sequence-based tailoring of phylogenetic strategy is implemented by any server. Rigorously constructing 270 evolutionary trees, constructed using IQ-TREE based on 13 different alignments (Clustal-Omega, Kalign, MAFFT, MUSCLE, TCoffee, and Promals3D, as well as their HHPred-based hidden Markov model [HMM] alignments using HHPred) and nine substitution models (Dayhoff, JJT, block substitution matrix62, WAG, probability matrix from blocks [PMB], direct computation with mutability [DCMUT], JTTDCmut, LG, and variable time), the present study highlights the failure of the current methods and emphasizes the need for a more accurate scrutiny of the entire phylogenetic methodology. MUSCLE alignment and the LG and Dayhoff matrices yield more accurate phylogenetic results for sequences shorter than 500 residues for the log-likelihood measure. Moreover, Kalign 1 HMM alignment yields the top-ranked tree with the lowest tree length score with only the PMB matrix, making this substitution model more accurate in terms of total tree length score. The suggested strategy would be beneficial for understanding the potential pitfalls of phylogenetic inference and would aid us in deriving a more accurate evolutionary relationship for a sequence dataset.

Reconstruction of self-oscillating systems with delay time modulation

The aim of our research is to study the possibility of reconstruction from time series the self-oscillating systems with variable time delay, demonstrating regimes of turbulent and laminar chaos. Methods. The object of study is self-oscillating systems described by delay-differential equations, in which the delay time is modulated by an external periodic signal. The possibility of estimating the parameters of systems with delay time modulation from their time series is considered using the known method for reconstructing systems with constant delay time, which is based on statistical analysis of time intervals between all possible pairs of extrema in time series. A new method for estimating the parameters of systems with variable delay time is proposed, based on statistical analysis of time intervals between two successive extrema in time series. Results. It is shown that in some cases the known methods for reconstructing systems with constant delay time are also effective for reconstructing systems with varying delay time. With their help, one can estimate the mean delay time and recove the nonlinear function of the system. The proposed method, aimed at application to time-delay systems with delay time modulation, allows one to estimate the frequency and amplitude of delay time modulation. Conclusion. The obtained results are of interest to various scientific disciplines that study systems with variable delay times based on their time series.

Clinically relevant differences in spinal mobility related to daytime performance in patients with axial spondyloarthritis

ObjectivePatients with axial spondyloarthritis (axSpA) suffer from clinical symptoms like morning stiffness and back pain. Mobility of patients with axSpA is often impaired. The aim of this study is to...

A variable future-time-steps method for solving nonlinear unsteady inverse heat conduction problems

In some non-linear unsteady inverse problems, the inverse solution will oscillate violently in the whole time domain due to the sharp change of the sensitivity coefficients. To deal with this problem, a new sequential function specification method with variable future time steps is proposed in this paper. The future time steps are adjusted by the error amplification coefficients which are defined as the reciprocal of the square sum of the sensitivity coefficients. When the error amplification coefficients are small, a small number of future time steps is used to reduce the deterministic error. While in the period with large error amplification coefficient, a large number of future time steps is used to reduce stochastic error. Finally, the total error of estimated heat flux is reduced. Avoid the sharp fluctuation of estimated heat flux in time domain due to the sharp change of sensitivity coefficients. The variable future-time-steps method is applied to the estimation of 1-D non-linear unsteady heat flux without and with ablation through numerical experiments. Numerical experiments show that the proposed method can not only estimate various forms of heat flux, but also its inversion results are significantly better than those of the fixed future time steps method based on the discrepancy principle, and also better than those of the fixed future time step method based on the minimum relative error of heat flux.

A Variable Fractional Delay Filter Based True-Time-Delay Array Architecture for Wideband Beamforming

True-time delay (TTD) units are critical in Wideband Large-Scale Antenna Systems (LSASs) for resolving beam squint and frequency selective fading. In this paper, we propose a TTD array architecture for wideband beamforming that addresses the challenges posed by LSASs by utilizing variable fractional delay (VFD) filters and time delay estimations (TDEs). This study introduces a convex optimization problem to develop a novel method for designing VFD filters that can achieve high precision time delay resolution while maintaining an acceptable frequency response peak error. Using these VFD filters, we present a TDE approach with Newton-Raphson iteration update that corrects the difference in arrival time between sensors. Due to the implementation of VFD filters and fast TDE modules, the new architecture can complete beam steering and tracking in 10 ms with MATLAB simulation. Furthermore, an example was designed to demonstrate that the proposed architecture is capable of producing precise beam pointing while maintaining the bit error rate (BER) that is extremely close to the theoretical curve over the entire bandwidth.

People in a Biodiverse Region Experienced Varying Types and Timing of Conflict With Multiple Wildlife Species

Background & Research Aims: Understanding how people and wildlife coexist is crucial to informing conservation and management of biodiverse areas, supporting both wildlife conservation and human well-being. Yet, most studies of human-wildlife conflict and coexistence focus on a limited number of wildlife species. Methods: This study characterizes patterns of reported human-wildlife conflict in the Okavango region of Botswana based on records for all species from the Botswana Department of Wildlife and National Parks (2008 – 2016). Results: The reported incidents implicated a diverse range of wildlife species in conflict. The patterns indicated that for conflicts like crop and property damage, only a few main species were implicated, while livestock damage reports had more diversity of conflict species. Additionally, people in this region faced wildlife challenges throughout the year. Conclusion & Implications for Conservation: Having such variable types and timing of conflict, and from diverse species, may make it particularly difficult for people to mitigate costs and prevent further conflicts.

Влияние конфигурации и топографических особенностей поля фермы Целот (Эритрея) на производительность посевного агрегата

It is difficult to choose an optimal energy means and a suitable set of technological equipment due to the diversity of production conditions (size and configuration of fields, energy intensity of technological process, presence of stones, obstacles and a headland) and specific natural and climatic factors. In order to assess the influence of topographical features of the fields of the Celot farm (Eretria) on the performance of a seeding unit, including a pneumatic seeder Nardi Dora (DORA 600) and a tractor New Holland T6090, the authors studied 23 plots of about 107 ha. They analyzed variations of the seeding unit efficiency index depending on the size and shape indices of the plot (area, convexity, perimeter-to-area ratio, compactness index, square perimeter index, rectangularity and roughness of the field surface profile). Field area was determined with ArcGIS10.7.1, Locus GIS offline land survey was used to obtain spatial information. The obtained data were exported to the Google Earth Pro and ArcGIS software for further processing. The relationship between indices was studied using the multivariate regression analysis. A bivariate study of parameters responding to these indices was carried out to find out the effect of field size and shape indices on the seeding unit performance. The conducted experiment showed variation in the shift time efficiency ratio from 30.1 to 65.7% for low and variable shift time indices. Topographical features of the field significantly affect the field time efficiency factor. When designing fields it is recommended to take into account topographical features to provide suitable turn lanes for maneuvering and eliminate obstacles within the working area.