First-order Process Research Articles

River levels from multi mission altimetry, a statistical approach

Satellite altimetry is a key technique to measure water level change in continental water bodies. Altimetry-based water level time series of rivers are typically constructed at locations where the satellite ground tracks intersect the rivers, the so-called virtual stations. The relatively low sampling frequency (10–27 days) of the repeat missions may result in an under-sampling of the hydrological regime in rivers with sub-monthly to weekly events. We are currently in a unique position with more than a handful satellite altimetry missions simultaneously mapping the surface elevation of the Earth. In combination, these missions contain an unexploited potential to obtain a more detailed picture of the hydrological regime of many of the Earth's rivers. The task of combining water levels measured at different locations and/or by satellites with different orbits is however, challenging due to e.g. topography, intermission biases, variation in river morphology, and other unidentified causes.In this work, we present a new method to combine multi-mission altimetry-based water levels from a river reach. This will also enable the use of geodetic missions like CryoSat-2 and SARAL/AltiKa (after June 2016) in water level time series. To combine the data we set up a state-space model where the process part is a first-order autoregressive process. The observations as a function of time and distance along the reach are described as a sum of the water level at a given time scaled by a distance-dependent factor, the mean water level at the given distance, and an error term. The scale factor and the mean water level are modeled with spline functions. We employ the model for the six rivers Lena, Solimões, Mississippi, Danube, Po, and Red, which range in width from 3 km to a few hundred meters. For each river, we consider a reach of 200–300 km and apply water levels from the satellite altimetry missions CryoSat-2, Sentinel-3A/3B, and SARAL/AltiKa. The selected reach must have a continuous elevation profile and preferable no major tributaries, which might alter the hydrological regime considerably. The length of the reach is a compromise of ensuring enough data but not violating the aforementioned criteria.When validated against in situ data we find a root mean square error ranging from 0.34 m (Solimões River) to 2.53 m (Lena River) and a correlation ranging from 0.83 (Danube River) to 0.99 (Solimões River). These summary statistics are based on approximately 2000–3000 pairs of in situ and modeled water levels. We find the largest increase in detail for the reconstructed water levels for the Danube, Po, and Red Rivers, where the water level variations are under-sampled at the virtual stations. For the Po River, we can detect sub-weekly events with the model and for the Lena River, the spring flood related to ice and snowmelt is better captured when combining the data. An additional advantage of the approach is that the water level time series can be reconstructed at all locations along the considered reach.

Superlattice ordering transitions driven by short-range structure in barium calcium carbonates.

Balcite (BaxCa1-xCO3) is a synthetic analog of rhombohedral carbonate minerals like calcite and dolomite that is disordered on both the cation and anion sublattices. Here, we show that multiple exotic superlattice structures, including a dolomite analog that we call balcomite, can form from balcite at elevated temperatures. The second-order balcite-to-balcomite conversion at temperatures between 150-600 °C is driven by the preference of barium and calcium for different oxygen coordination numbers and facilitated by local carbonate reorientation. At elevated pressure, further superlattice order arises from cation segregation in all three dimensions, producing a supercell with the same R3̄m symmetry as balcite but 6× larger. This highly ordered structure relaxes back to the balcomite structure upon returning to ambient conditions. None of the three naturally occurring polymorphs of Ba0.5Ca0.5CO3 (alstonite, paralstonite, barytocalcite) formed from balcite despite being putatively energetically favored. Instead, alstonite transformed to a balcomite-like structure via a first-order process after transiently converting to a paralstonite-like structure via a second-order process. Together, these results show that high temperature transformation pathways between structures in the barium calcium carbonate system can be driven by coarsening and are facilitated by similarity in short-range order, conceptually analogous to previously described low-temperature transformations. Many of the exotic high temperature carbonate structures are unstable, but may participate in transformation pathways between naturally observed metastable mineral phases, suggesting important roles for ephemeral phases in shaping past and current mineral distributions.

Fundamental physical features of resonant spontaneous bremsstrahlung radiation of ultrarelativistic electrons on nuclei in strong laser fields

Theoretically predicted fundamental features in the process of resonant spontaneous bremsstrahlung radiation during the scattering of ultrarelativistic electrons with energies of the order by the nuclei in strong laser fields with intensities up to I ∼ 1024 W cm−2. Under resonant conditions, an intermediate electron in the wave field enters the mass shell. As a result, the initial second-order process by the fine structure constant is effectively reduced to two first-order processes: laser-stimulated Compton effect and laser-assisted Mott process. The resonant kinematics for two reaction channels (A and B) is studied in detail. An analytical resonant differential cross-section with simultaneous registration of the frequency and the outgoing angle of a spontaneous gamma-quantum for channels A and B is obtained. The resonant differential cross section takes the largest value with a small number of absorbed laser photons. In this case, the resonant cross-section is determined by one parameter, depending on the small transmitted momenta, as well as the resonance width. In strong fields, spontaneous gamma quanta of small energies are most likely to be emitted compared to the energy of the initial electrons. At the same time, the angular width of the radiation of such gamma quanta is the largest. With an increase in the number of absorbed laser photons, the resonant cross-section decreases quite quickly, and the resonant frequency of spontaneous gamma quanta increases. It is shown that the resonant differential cross-section has the largest value in the region of average laser fields (I ∼ 1018 W cm−2) and can be of the order of in units . With an increase in the intensity of the laser wave, the value of the resonant differential cross-section decreases and for the intensity I ∼ 1024 W cm−2 is in units . The obtained results reveal new features of spontaneous emission of ultrarelativistic electrons on nuclei in strong laser fields and can be tested at international laser installations.

Markov Multi-Beamtracking on 60 GHz Mobile Channel Measurements

Beamforming training refers to the exhaustive scan over which the transmitter and receiver jointly steer their beams along a predefined set of double-directional angles to determine the beam pairs that coincide with the dominant propagation paths of the channel, for spatial multiplexing at millimeter-wave. When mobile, training necessitates a high refresh rate to maintain connectivity and so, to reduce overhead, beamtracking algorithms exploit the spatial-temporal consistency of the channel to localize the scan around the beam pairs determined at a previous time. The algorithms&#x2019; true performance, however, is still unknown since results reported to date are based on oversimplified channel models. In this paper, we propose a novel beamtracking algorithm formulated as a first-order Markov process that supports multiple beam pairs. The algorithm is evaluated through actual channel measurements &#x2013; <i>not a channel model</i> &#x2013; recorded with our high-precision 3D double-directional 60 GHz channel sounder. The measurement campaign, to our knowledge, is unprecedented: with 10, 895 large-scale measurements, spaced 8.8 cm apart on average to emulate continuous motion, over which the mobile receiver traversed a total of 900.2 m. We demonstrate that four beam pairs can be sustained always and that eight pairs can be sustained 57&#x0025; of the time.

Novel design of PID controllers for minimum and non-minimum phase time delay processes for enhanced performance

A new technique is proposed for the design of PID controllers for minimum and non-minimum phase (NMP) stable first-order and second-order processes. The idea is to make the open-loop transfer function model equal to an integrating model with which the closed loop consists of first order dynamics. The resulting controller settings are functions of the tuning factor δ and process model parameters. The tuning parameter is selected based on the stability and robustness margins. Different case studies for simulation and experimental implementation are considered and the closed loop responses are examined. The proposed technique gives enhanced closed-loop performance for both set point and regulatory problems compared to the current techniques in both perfect and perturbed model conditions. Performance metrics such as integral error, control variation, stability margins, and sensitivity peak are compared and it is noted that the enhanced responses are achieved with the proposed simple method, which has straightforward simple analytical relations for design of the controller.

Globally Optimal Centralized and Sequential Fusion Filters for Uncertain Systems With Time-Correlated Measurement Noises

This paper is concerned with the fusion filtering problem for stochastic uncertain multi-sensor systems with time-correlated measurement noises, where the stochastic uncertainties are described by white multiplicative noises, and the additive measurement noises are first-order Gauss-Markov Processes. By introducing the recursive measurement noise estimators, the centralized fusion filter (CFF) based on the idea of batch process and sequential fusion filter (SFF) based on the idea of sequential process are designed in the linear minimum variance (LMV) sense by an innovation analysis approach, respectively. The proposed SFF can achieve the same estimation accuracy as the CFF. It is also globally optimal. The equivalence on estimation accuracy of the SFF and CFF is strictly proved by mathematical induction method. The stability and steady-state properties of the proposed fusion filters are analyzed. Two examples show the effectiveness of the proposed fusion algorithms.

Dissipation of spiroxamine residues in open field cucumber and dietary risk assessment

Summary Spiroxamine is one of the most used fungicides in the Mediterranean region, in significant uses such as open field cucumber. Residue trials in the Northern part of Egypt were conducted to investigate the dissipation of spiroxamine (SPX) in cucumbers according to the authorized Good Agricultural Practice (GAP) (1 × 75 g a.i. ha−1 at BBCH 85 to 89) and more critical use patterns. SPX was extracted from cucumbers using a modified QuEChERS protocol and residues were analyzed by liquid chromatography with tandem mass spectrometry (LC–MS/MS). The method was successfully validated with an LOQ of 0.001 mg kg−1. A steep decline of SPX residues in cucumbers fit a first-order decay process with a calculated t1/2 of approximately 2 days and almost complete degradation (99%) after 14 days. Chronic and acute exposure calculations were performed for cucumbers treated with SPX according to all tested GAPs employing two different approaches. In all cases a health risk after consumption of cucumbers was not identified.

Nationwide Radar-Based Precipitation Nowcasting—A Localization Filtering Approach and its Application for Germany

One approach to improve advection methods is the short-term ensemble prediction system (STEPS). STEPS decomposes precipitation fields into different spatial scales and filters those having a short lifetime. The latter is achieved by using an auto-regressive (AR) model that considers a sequence of observations. However, such a model tends to smooth nowcasting fields especially in small but convective precipitation areas and at longer lead-times. With focus on the deterministic configuration of STEPS, i.e., the spectral prognosis model (SPROG), this article 1) extends the STEPS approach by estimating spatially localized parameters of the AR process, 2) conducts a sensitivity analysis of the SPROG model to the order of the AR process, the spatial decomposition levels, and post-processing, and 3) analyzes the forecast skill of the extended STEPS. For such purpose, the performance of the localized AR model was demonstrated and evaluated at several precipitation thresholds and window sizes using a varied set of precipitation events collected by the radar network of the German Weather Service. The statistical results exhibited an improved performance of the localized AR model over SPROG when both are evaluated at precipitation thresholds and window sizes larger than 0.1 mm h <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^{-1}$</tex-math></inline-formula> and 1 km, respectively, and for lead-times up to 2 h. The analysis suggested a first-order AR process, six cascade levels, and a mean adjustment post-processing procedure. Our results show a key role of the localization aspect when generating nationwide forecasts in scenarios that include large precipitation areas which are non-uniformly distributed having isolated convective features.

On one family of first passage times of a Markov random walk described by an autoregressive process AR(1) for nonlinear boundaries

The consider one family of first passage times of a Markov random walk described by a first-order autoregressive process AR(1) for nonlinear boundaries. Limit theorems are proved for a Markov random walk and a family of first passage times of this walk for nonlinear boundaries.

Solute Transport Control at Channel Junctions Using Adjoint Sensitivity

Water quality control and the control of contaminant spill in water in particular are becoming a primary need today. Gradient descent sensitivity methods based on the adjoint formulation have proved to be encouraging techniques in this context for river and channel flows. Taking into account that most channels and rivers include junctions with other branches, the objective of this study is to explore the adjoint technique on a channel network to reconstruct the upstream boundary condition of the convection-reaction equation. For this purpose, the one-dimensional shallow water equations and the transport equation for a reactive solute are considered. The control is formulated through the gradient-descent technique supplied with a first-order iterative process. Both the physical and the adjoint equations are supplied with suitable internal boundary conditions at the junction and are numerically solved using a finite volume upwind scheme. The results reveal that the adjoint technique is capable of reconstructing the inlet solute concentration boundary condition in an acceptable number of iterations for both steady state and transient configurations using a downstream measurement location. It was also observed that the reconstruction of the boundary condition tends to be less effective the further away the measurement station is from the target.

A matrix approach to get the variance of the square of the fluctuation function of the DFA

The fluctuation analysis (FA) and the detrended fluctuation analysis (DFA) make it possible to estimate the Hurst exponent H, which characterizes the self-similarity of a signal. Both are based on the fact that the so-called fluctuation function, which can be seen as an approximation of the standard deviation of the process scaled in time by multiplying the time variable by a positive constant, depends on H. The main novelty of the paper is to provide the expression of the variance of the square of the fluctuation function, by using a matrix formulation. We show that it depends on the correlation function of the signal under study when it is zero-mean and Gaussian. Illustrations are given when dealing with a zero-mean white Gaussian noise. Moving average processes and first-order autoregressive processes are also addressed.

Degradation Characteristics of Carbon Tetrachloride by Granular Sponge Zero Valent Iron.

Granular sponge zero valent iron (ZVI) was employed to degrade carbon tetrachloride (CCl4). The effects of acidic washing, initial solution pH, and ZVI dosage on CCl4 degradation were investigated. Results showed that CCl4 was effectively removed by ZVI and approximately 75% of CCl4 was transformed into chloroform through hydrogenolysis. The rate of chloroform transformation was slower compared to that of CCl4, resulting in chloroform accumulation. CCl4 degradation was a pseudo first-order process. The observed pseudo first-order reaction rate constant (kobs) for CCl4 and chloroform were 0.1139 and 0.0109 h−1, respectively, with a ZVI dosage of 20 g/L and an initial CCl4 concentration of 20 mg/L. Surface acidic washing had a negligible effect on CCl4 degradation with ZVI. The kobs for CCl4 degradation increased linearly with increasing ZVI dosage and the optimal dosage of ZVI was 20 g/L based on the surface area-normalized rate constants. The negative relationship between kobs and the solution pH indicated that the degradation of CCl4 by ZVI performed better under weakly acidic conditions.

Preparation, characterization and properties of the ternary composite β2-SiW11/polyaniline/graphene oxide

The composites β2-SiW11/GO and β2-SiW11/PANI/GO were prepared by using graphene oxide as a carrier. Properties of the composites were characterized by UV-visible spectroscopy (UV-vis), infrared spectroscopy (FT-IR), X-ray powder diffraction (XRD), scanning electron microscopy (SEM-EDS), transmission electron microscopy (TEM), N2 adsorption desorption and thermal gravimetric analysis. Properties of the composites were investigated by using methyl violet simulated industrial wastewater. The results showed that this composite had photocatalytic activities for many dyes, and the activity was higher than that of Degussa P25(TiO2). The photocatalytic performance of β2-SiW11/PANI/GO had a higher activity than that of PANI, β2-SiW11 and β2-SiW11/GO, with photodegradation reaching 95.98% under 30 W ultraviolet light for 150 min. The reaction kinetics for photocatalytic degradation of methyl violet followed a first-order process. The prepared composite was recyclable and the performance remained good. The possible mechanism of photocatalytic activity of dopant material is discussed and schematized.

Discrete Pseudo Lindley Distribution: Properties, Estimation and Application on INAR(1) Process

In this paper, we introduce a discrete version of the Pseudo Lindley (PsL) distribution, namely, the discrete Pseudo Lindley (DPsL) distribution, and systematically study its mathematical properties. Explicit forms gathered for the properties such as the probability generating function, moments, skewness, kurtosis and stress–strength reliability made the distribution favourable. Two different methods are considered for the estimation of unknown parameters and, hence, compared with a broad simulation study. The practicality of the proposed distribution is illustrated in the first-order integer-valued autoregressive process. Its empirical importance is proved through three real datasets.

Temporal analysis of the heavy metal concentration in road sediment and dust using statistical models

The objective of this paper is to show a temporal analysis using autoregressive integrated moving average models of the heavy metal concentration in road sediment and dust of Soacha, a Colombian locality. The representative size fractions in the road sediment and dust were <250 μm and ⩽10 μm, respectively. The results suggest that lead is the best metallic element to study the relationship between the heavy metal concentration in the road sediment and dust (r-Pearson = 0.90). Univariate models (R2 ⩾ 0.58) suggest that the time series of lead concentrations in road sediment and dust have the same temporal structure. Namely, because they are first-order autoregressive processes, concentrations at a given moment of time are influenced by the immediately preceding concentrations. The transfer function model (R2 = 0.91) suggests that there is no delay in impulse transfer from road dust concentration to lead concentration in the road sediment. The effect is immediate for a sampling interval of 3 days. The results show that modeling has a better fit during the rainy season compared to the dry season. In the context of the simulation of physical phenomena in engineering, this study is relevant to deepen knowledge in relation to the use of autoregressive integrated moving average models.

A Beidou + UWB + inertial Navigation Integrated Indoor and Outdoor Multi-Source Information Fusion Positioning System

The article analyses the high-precision indoor and outdoor positioning system and its positioning method based on Beidou/UWB. And analyse the principles and characteristics of UWB technology. The article proposes a sequential filtering fusion algorithm for the ship’s integrated navigation system. The basic idea of the algorithm is to use the first-order Markov process to establish the noise model of ship motion, and use the state expansion method to transform the state equation into a basic equation that conforms to the standard Kalman filter. Theoretical research and experimental simulation prove that the filter introduced in the article is matched with the system and has high filtering performance and accuracy.

Statistical analysis of one-compartment pharmacokinetic models with drug adherence.

Pharmacokinetics is a scientific branch of pharmacology that describes the time course of drug concentration within a living organism and helps the scientific decision-making of potential drug candidates. However, the classical pharmacokinetic models with the eliminations of zero-order, first-order and saturated Michaelis-Menten processes, assume that patients perfectly follow drug regimens during drug treatment, and the significant factor of patients' drug adherence is not taken into account. In this study, therefore, considering the random change of dosage at the fixed dosing time interval, we reformulate the classical deterministic one-compartment pharmacokinetic models to the framework of stochastic, and analyze their qualitative properties including the expectation and variance of the drug concentration, existence of limit drug distribution, and the stochastic properties such as transience and recurrence. In addition, we carry out sensitivity analysis of drug adherence-related parameters to the key values like expectation and variance, especially for the impact on the lowest and highest steady state drug concentrations (i.e. the therapeutic window). Our findings can provide an important theoretical guidance for the variability of drug concentration and help the optimal design of medication regimens. Moreover, The developed models in this paper can support for the potential study of the impact of drug adherence on long-term treatment for chronic diseases like HIV, by integrating disease models and the stochastic PK models.

High-yield helicity-resolved Raman scattering with in-plane propagation of light in monolayer MoS2

In-plane propagation of excited light in layered materials boosts the observation of novel phenomena, which differ from out-of-plane propagation. In this work, we perform the Raman study with light propagation parallel to the plane of layered MoS2. The Raman signal is unveiled at least an order of magnitude larger than that perpendicular to the plane when the excitation photon energy at ∼2.81 eV. We attribute this high-yield Raman spectra to the stronger photon–exciton coupling with in-plane propagation of light. Furthermore, we show that the exciton-mediated phonon excitation in the first-order Raman process is dominant with consideration of angular momentum transfer between phonons and photons through the measurements of the circularly polarized Raman spectra. This experimental setup configuration paves a way with high efficiency to investigate the phonon information in layered materials.

An MSI-VAR Approach on investigating the broad money supply and consumer price index in Malaysia

According to monetarism, the money supply is the leading cause of increasing price level in the short and long run. Previous works investigated the effect of money supply on inflation in several countries; however, inconsistent arguments from these studies resulted in the exploration of the correlations between money supply and inflation via a different approach in this work. This study investigates the broad money supply and consumer price index (CPI) using the Markov switching vector autoregressive model. The CPI, with 2010 as its base year, was used as a proxy for Malaysia's inflation. The broad money supply is defined as the sum of money and quasi-money. Other countries use different measurements; therefore, M3 was selected based on the monetary authority measurement of the money supply in this study. The transition probabilities and expected duration of the recession and upturn/normal states were examined using a two-regime switching VAR model. Furthermore, the Augmented Dickey-Fuller test, Johansen cointegration, and intercept adjusted MS-VAR model with the first-order Markov process was also used in this study to estimate the observables variables. The results confirmed significant transition probabilities in the state shifting and an asymmetric economic model representing broad money and inflation correlations in Malaysia. Keywords: Broad Money; Consumer Price Index, Malaysia, Regime Switching, MS-VAR

Two-stage procedure in a first-order autoregressive process and comparison with a purely sequential procedure

A two-stage procedure in a first-order autoregressive model is considered that investigates the point and the interval estimation of parameters based on the least squares estimator. The two-stage procedure is shown to be as effective as the best fixed-sample-size procedure. In this regard, the significant properties of the procedure, such as asymptotic risk efficiency, asymptotic efficiency, and asymptotic consistency, are established. A Monte Carlo simulation study is conducted to compare the performance of the two-stage procedure and the purely sequential procedure. Finally, real-time series data are considered to illustrate the applicability of the two-stage procedure.