Two-dimensional Process Research Articles

Fluidized Electrooxidation Process Using Three-Dimensional Electrode for Decolorization of Reactive Blue 221

With the addition of a particle electrode to the two-dimensional electrooxidation process using Pt coated titanium electrodes, the decolorization of reactive blue 221, one of the reactive dyes that are frequently used in the textile industry, has been studied. Experimental matrix was determined according to Box Behnken Design and evaluated with ANOVA results and surface plots. The selected independent variables were selected as color concentration, current density and time. Accordingly, it has been determined that the optimum condition 20 mA/cm2 of current density, 20.5min of reaction time for the sample containing 60.6 mg/L color concentration. In addition, a separate study was carried out to determine the accuracy of the model with the experimental results, and it was compared with the adsorption and 2D electrooxidation process. Accordingly, it was obtained that the activated carbon in the 3D process, other than adsorption, acts as a carbocatalyst. The results of the study were evaluated according to Langmuir and Freundlich isotherms, pseudo-first-order and pseudo-second-order kinetic models, and it was found to be compatible with Langmuir and pseudo-second-order kinetic model. Maximum adsorption capacity was calculated as 5.93 mg/g from Langmuir isotherm.

Analysis of gravity and aeromagnetic data to determine structural trend and basement depth beneath the Ajdabiya Trough in northeastern Libya

In this study, we analyse both ground gravity and aeromagnetic data in order to delineate structural trends, fault systems and deduce sedimentary thicknesses within the Ajdabiya Trough in Libya’s northeast. A high-pass filter and a reduced-to-the-pole (RTP) transformation are applied to the gravity and aeromagnetic data respectively. Different filters are used to enhance the structural signatures and fault trends within the study area. The Werner deconvolution and source parameter imaging (SPI) techniques are applied to the RTP magnetic data for source depth estimation. Four well-data within the area are used as constraints in the two-dimensional forward modelling process. The results show that the Ajdabiya Trough is characterised by gravity anomaly highs and magnetic anomaly lows. The analysis of gravity data shows predominant Northeast–Southwest structural trends, whereas the analysis of magnetic data shows predominant North–South magnetic lineaments within the Ajdabiya Trough. The Euler deconvolution depth estimates of faults depths range between 1500 and 9500 m. The SPI estimates of the magnetic basement range between 2500 and 11,500 m beneath the study area (deepest beneath the Ajdabiya Trough). Constrained by the well-data, six major layers characterize the four profiles that are taken within the area. One of the profiles shows a high-density intrusion (about 4 km from the surface) within the sedimentary sequence. The intrusion may be the result of the rifting Sirt Basin which caused a weakening of the crust to allow for mantle intrusion.

Method for Overflow Attack Defense of SDN Network Flow Table Based on Stochastic Differential Equation

In order to avoid the overflow problem of network flow table caused by hackers attacking the network in the process of using the network, a method for overflow attack defense of SDN network flow table based on stochastic differential equation is proposed. In this method, the stochastic differential equation is first proposed, and the drift coefficient and diffusion coefficient of the equation are expanded and adjusted by Taylor. By using the limit theorem, the spillover attack of SDN network is weakly converged to an approximate two-dimensional Markov diffusion process, and the improved stochastic differential equation is obtained. Then, according to the stochastic nature of SDN network attack, the stochastic differential equation is transformed into an amplitude equation, which is based on the amplitude. The equation establishes a SDN attack detection scheme based on flow table statistics, which detects the spillover attacks of SDN network flow tables. Finally, according to the test results, it is proposed to use other switches instead of network flow table overflow switches to control the data upload rate, thus reducing the possibility of network crash and meeting the attack defense requirements of flow table overflow. The simulation results show that the proposed method has better detection performance and shorter running time, and can provide help for network security related work.

A high accurate scheme for numerical simulation of two-dimensional mass transfer processes in food engineering

This paper contributes to develop a highly accurate numerical method for solving two-dimensional mass transfer equations during convective air drying of apple slices. The numerical scheme is based on the interpolating the solution of the mentioned equations over the roots of the orthogonal Jacobi polynomials (i.e., the Jacobi-Gauss-Lobatto points) in a nodal form. Moreover, for speeding up the procedure of numerical technique, operational matrices of differentiation are applied to discretize the derivatives of both spatial and temporal variables. After implementing the proposed technique, two-dimensional mass transfer equations would be transferred into the associated systems of linear algebraic equations which can be solved by appropriate iterative solvers such as robust Krylov subspace iterative methods. Some constructed artificial examples are provided to show the efficiency and applicability of the Jacobi pseudo-spectral method for solving two-dimensional mass transfer equations. Finally, a real example is considered and numerical results are validated by the experimental data which confirm the accuracy of the presented numerical approach.

Assembly of multidimensional MXene-carbon nanotube ultrathin membranes with an enhanced anti-swelling property for water purification

Severe stacking and swelling properties are critical issues in two-dimensional (2D) lamellar membrane fabrication and separation processes that can result in low flux and poor rejection. Herein, we propose the assembly of multidimensional MXene-carbon nanotube (CNT) ultrathin membranes by loading a MXene intercalated with CNTs onto a tubular ceramic membrane. Benefiting from the modes of van der Waals interactions (hydrogen bond) and repulsion forces between the MXene and functionalized CNTs, the one-dimensional (1D) CNTs are well dispersed and intercalated into the 2D MXene nanosheets, forming a uniform network and continuous three-dimensional (3D) labyrinthine short mass transfer channels, which can considerably improve the permeability and rejection performance of the membranes. Furthermore, the membranes exhibit a distinct suppressed swelling property via a facile thermal crosslinking process (-OH + -OH = -O- + H2O and -COOH + -OH = -COO + H2O), accompanied by the formation of new chemical bonds (Ti-O-C and Ti-COO-C) due to dehydroxylation between the neighboring MXene nanosheets and CNTs. Additionally, 50 h long-term operation studies also indicate the promising anti-swelling property and stability of the MXene-CNT membranes. This multidimensional (1D and 2D) assembly and thermal crosslinking strategy represents a new avenue for the facile and scalable development of MXene-based and other 2D material-derived high-performance membranes for water purification.

Kinematic-wave analysis of particle settling in tube centrifuges

The kinematic-wave theory of particle settling in tube centrifuges has become a subject of scientific discussion. Specifically, the common assumption was made that the flow in a rotating tube of large length/diameter ratio can be treated in one-dimensional approximation. The respective results have been found in agreement with measurements. However, an analysis of the two-dimensional settling process performed in the limit of vanishing particle concentration led to some results that are not in accordance with the one-dimensional flow approximation, irrespective of the length/diameter ratio. It is the aim of the present investigation to gain a better understanding of the process. According to the analysis presented here, quasi-one-dimensional kinematic waves are embedded in a two-dimensional bulk flow that is governed by the continuity equation for the mixture plus the boundary conditions at the walls of the tube. The results based on simplification assumptions are compared with those of the one-dimensional flow approximation. Limiting cases, based on an elaborate analysis of three distinct settling models, are investigated analytically, and the plausibility of some of the respective results is evaluated also in the context of the one-dimensional approximation. Experimental observations, reported in the time span 2001 through 2008, are compared with analytical results obtained and presented. Further experimental work beyond this time span is also analyzed.

Two-curve Green’s function for 2-SLE: the boundary case

We prove that for $\kappa\in(0,8)$, if $(\eta_1,\eta_2)$ is a $2$-SLE$_\kappa$ pair in a simply connected domain $D$ with an analytic boundary point $z_0$, then $\lim_{r\to 0^+}r^{-\alpha} \mathbb{P}[\mbox{dist}(z_0,\eta_j)<r,j=1,2]$ converges to a positive number for some $\alpha>0$, which is called the two-curve Green's function. The exponent $\alpha$ equals $\frac{12}{\kappa}-1$ or $2(\frac{12}{\kappa}-1)$ depending on whether $z_0$ is one of the endpoints of $\eta_1$ and $\eta_2$. We also find the convergence rate and the exact formula of the Green's function up to a multiplicative constant. To derive these results, we construct two-dimensional diffusion processes and use orthogonal polynomials to obtain their transition density.

A Model of a System With Stream and Elastic Traffic

This paper presents a multi-service model of a communications system with stream and elastic traffic. The idea of the model is based on an analysis of a two-dimensional Markov process, which approximates the real process in the considered system. Such an approach allows us to describe the use of system resources by stream and elastic traffic with high accuracy. An appropriate simulation model has been developed and implemented in order to verify the proposed model. The presented results have confirmed the validity of all the theoretical assumptions adopted in the study.

On copulas of self-similar Ito processes

Abstract We characterize the cumulative distribution functions and copulas of two-dimensional self-similar Ito processes, with randomly correlated Wiener margins, as solutions of certain elliptic partial differential equations.

A Stochastic Geometry Approach to EMF Exposure Modeling

Downlink exposure to electromagnetic fields due to cellular base stations in urban environments is studied using the stochastic geometry framework. A two-dimensional Poisson Point Process is assumed for the base station distribution. Mathematical expressions of statistics of exposure are derived from a simple propagation model taking into account the height of the base stations. The error on exposure made by taking a limited number of base stations, instead of the whole set, is quantified. The relative impact of the model parameters on the statistics of exposure is highlighted. The method is then applied and the model parameters are calibrated using experimental data obtained by drive-tests in two Brussels municipalities, in Belgium, for the 2100 MHz and 2600 MHz frequency bands. It is shown that the proposed model fits experimental values, paving the way to a new methodology to assess general public exposure to electromagnetic fields, for any frequency band. An insight is given on how to apply the methodology to a real case without access to experimental data.

Growth of ultra-thin large sized 2D flakes at air–liquid interface to obtain 2D-WS2 monolayers

Atomically thin two-dimensional (2D) transition metal dichalcogenides (TMDs) are promising candidates for future electronics. Currently, the growth of TMD large area thin films/flakes is one of the biggest challenges. A novel method for the growth of ultra-thin and large area WS2 monolayer flakes has been developed by introducing a solution-based temperature-dependent process. This two-dimensional WS2 growth process is low cost and environmentally friendly. WO3 flakes are grown at the air–liquid interface using ammonium tetrathiotungstate ((NH4)2WS4, ATTW) as WS2 precursor. The process requires a moderate activation temperature as no flakes are formed at room temperature. Successful growth of flakes was observed in an aqueous solution of the precursor at a temperature between 70 °C and 90 °C. These flakes could be transferred to any substrate by a controlled dip-coating process. Large 2D WS2 flakes with a lateral size of up to 100 μm were obtained after sulfurization. The thickness ranged from a WS2 monolayer to five monolayers, as verified by atomic force microscope. The chemical reaction mechanism behind the formation of the flakes was investigated by FTIR, Raman, UV–Vis and x-ray photoelectron spectroscopy. The initial flakes were found to be made of WO3, which were successfully converted to WS2 by a post annealing step at 500 °C–900 °C. This simple and environmentally friendly growth technique can be used to produce large WS2 flakes for next generation electronics.

The Performance Analysis of Spectrum Sharing Between UAV Enabled Wireless Mesh Networks and Ground Networks

Unmanned aerial vehicle (UAV) has the advantages of large coverage and flexibility, which could be applied in disaster management to provide wireless services to the rescuers and victims. When UAVs forms an aerial mesh network, line-of-sight (LoS) air-to-air (A2A) communications have long transmission distance, which extends the coverage of multiple UAVs. However, the capacity of UAV is constrained due to the multiple hop transmissions in aerial mesh networks. In this paper, spectrum sharing between UAV enabled wireless mesh networks and ground networks is studied to improve the capacity of UAV networks. Considering two-dimensional (2D) and three-dimensional (3D) homogeneous Poisson point process (PPP) modeling for the distribution of UAVs within a vertical range $\Delta \textit h$ , stochastic geometry is applied to analyze the impact of the height of UAVs, the transmit power of UAVs, the density of UAVs and the vertical range, etc., on the coverage probability of ground network user and UAV network user. Besides, performance improvement of spectrum sharing with directional antenna is verified. With the object function of maximizing the transmission capacity, the optimal altitude of UAVs is obtained. This paper provides a theoretical guideline for the spectrum sharing of UAV enabled wireless mesh networks, which may contribute significant value to the study of spectrum sharing mechanisms for UAV enabled wireless mesh networks.

Fluctuation-induced forces in driven systems with a diffusivity anomaly.

We show that Casimir-like forces in boundary-driven systems with a bulk diffusivity anomaly are enhanced by cooperative dynamical effects and can be made locally attractive or repulsive depending on the boundary densities. Theoretical predictions based on mean-field arguments and the explicit evaluation of the Casimir force in the fluctuating hydrodynamics framework are supported by Monte Carlo simulation of a two-dimensional (2D) exclusion process with selective kinetic constraints. Consistent with the entropic interpretation of the Casimir effect, we find that local repulsive forces do appear whenever finite-size transverse density fluctuations exceed their infinite-size value. Our results suggest that the bulk diffusivity anomaly is a crucial ingredient in the small-scale design of driven soft-matter systems with tunable fluctuation-induced forces.

Investigations of the Potential Application of k-out-of-n Systems in Oil and Gas Industry Objects

The purpose of this paper was to demonstrate the possibilities of assessing the reliability of oil and gas industry structures with the help of mathematical models of k-out-of-n systems. We show how the reliability of various structures in the oil and gas complex can be described and investigated using k-out-of-n models. Because the initial information about the life and repair time of components of systems is only usually known on the scale of one and/or two moments, we focus on the problem of the sensitivity analysis of the system reliability indices to the shape of its components repair time distributions. To address this problem, we used the so-called markovization method, based on the introduction of supplementary variables, to model the system behavior with the help of the two-dimensional Markov process with discrete-continuous states. On the basis of the forward Kolmogorov equations for the time-dependent process’ state probabilities, relevant balance equations for the process’ stationary probabilities are presented. Using these equations, stationary probabilities and some reliability indices for two examples from the oil and gas industry were calculated and their sensitivity to the system component’s repair time distributions was analyzed. Calculations show that under “rare” component failures, most system reliability indices become practically insensitive to the shape of the components repair time distributions.

The role of sample preparation in multidimensional gas chromatographic separations for non‐targeted analysis with the focus on recent biomedical, food, and plant applications

In this review, we consider and discuss the affinity and complementarity between a generic sample preparation technique and the comprehensive two-dimensional gas chromatography process. From the initial technical development focus (e.g., on the GC×GC and solid-phase microextraction techniques), the trend is inevitably shifting toward more applied challenges, and therefore, the preparation of the sample should be carefully considered in any GC×GC separation for an overreaching research. We highlight recent biomedical, food, and plant applications (2016-July 2020), and specifically those in which the combination of tailored sample preparation methods and GC×GC-MS has proven to be beneficial in the challenging aspects of non-targeted analysis. Specifically on the sample preparation, we report on gas-phase, solid-phase, and liquid-phase extractions, and derivatization procedures that have been used to extract and prepare volatile and semi-volatile metabolites for the successive GC×GC analysis. Moreover, we also present a milestone section reporting the early works that pioneered the combination of sample preparation techniques with GC×GC for non-targeted analysis.

Physical Layer Security Enhancement Using Artificial Noise in Cellular Vehicle-to-Everything (C-V2X) Networks

The secure transmission of confidential information in cellular vehicle-to-everything (C-V2X) communication networks is vitally important for user's personal safety. However, for C-V2X there have not been much studies on the physical layer security (PLS). Since artificial noise (AN) and secure beamforming are popular PLS techniques for cellular communications, in this paper we investigate the potential of these PLS techniques for enhancing the security of C-V2X networks. In particular, leveraging stochastic geometry, we study the PLS of an AN assisted C-V2X network, where the locations of legitimate vehicular nodes, malicious vehicular nodes and road side units (RSUs) are modeled by Cox processes driven by a common Poisson line process (PLP), and the locations of cellular base stations (BSs) are modeled by a two-dimensional (2D) Poisson point process (PPP). Based on the maximum signal-to-interference-ratio (SIR) association scheme, we calculate the coverage probability of the network. We also derive bounds on the secrecy probability, which are validated by simulation results. Moreover, we obtain an analytical result of the effective secrecy throughput for characterizing the reliability and security of wiretap channels. Simulation results are given to validate the analytical result, and provide interesting insights into the impact of network parameters on the achievable secrecy performance. Simulation results show that a larger array antenna can provide a better robustness of the secure transmission strategy, and the optimal power allocation ratio between confidential information and AN remains almost unchanged for different numbers of antennas.

Virtual Environments Utilization for ECG Signals Analysis and Evaluation: Towards Heart Condition Assessment

The utilization of heart Electrocardiograms (ECGs) is to measure irregular heart rate and regularity and detection of an arrhythmia. Various ways are submitted and utilized for cardiogram feature extraction with a reasonable percentage of right detection. Although the problem stays open, especially with respect to superior detection accuracy in ECGs. In nature, The ECG signals are very sensitive signals, having voltage-level as low as 0.5-5 mv and frequency-elements fall into the range of 0.05-100Hz and the largest amount of the information received in the range of 0.05-45Hz. The recorded ECG signal includes various kinds of noises such as baseline wander, channel noise which becomes very critical to eliminating for the best clinical finding which assists in the patient. The utilization of the discrete wavelet transform (DWT) as wavelet transforms can be utilized to be a two-dimensional time scale process technique for feature extraction and classification task, therefore it’s appropriate for the non- stationary ECG signals (because of the sufficient range values and the shift in a timely) in LabVIEW. To implement the feature extraction and classification tasks, a separating wavelet transformation (consonant), and the wavelet transform can be two-dimensional time-scale practical technique was utilized. Hence, it is relevant for non-constant ECG signals (because of sufficient scale-values and transformation in timely) in LabVIEW. The flexibility, standard nature and simplicity to utilizing programming possible with LabVIEW, makes it less complex. The pro-posed algorithm is executed in two steps. First step, de-noises the signal from the cardiogram signal to get rid of the noise, then detects the pulse, our extracted parameters are heart rate, P wave amplitude, T wave amplitude, S value, Q value, R-value, P offset location, P onset location, T onset location, T offset location and the location of P, Q, R, S and T wave.

A Fast, Two-dimensional Gaussian Process Method Based on Celerite: Applications to Transiting Exoplanet Discovery and Characterization

Abstract Gaussian processes (GPs) are commonly used as a model of stochastic variability in astrophysical time series. In particular, GPs are frequently employed to account for correlated stellar variability in planetary transit light curves. The efficient application of GPs to light curves containing thousands to tens of thousands of data points has been made possible by recent advances in GP methods, including the celerite method. Here we present an extension of the celerite method to two input dimensions where, typically, the second dimension is small. This method scales linearly with the total number of data points when the noise in each large dimension is proportional to the same celerite kernel and only the amplitude of the correlated noise varies in the second dimension. We demonstrate the application of this method to the problem of measuring precise transit parameters from multiwavelength light curves and show that it has the potential to improve transit parameters measurements by orders of magnitude. Applications of this method include transit spectroscopy and exomoon detection, as well a broader set of astronomical problems.

Markov chain approximation and measure change for time-inhomogeneous stochastic processes

In this paper, we propose a general time-inhomogeneous continuous-time Markov chain (CTMC) framework for the approximation of the general one-dimensional and two-dimensional time-inhomogeneous diffusion processes. For the approximating CTMC, we can perform a change of measure, choose the minimal relative entropy measure to determine the measure uniquely, and finally establish the convergence. Therefore, the proposed methodology covers the stochastic processes that are hard to perform a change of measure, and is applicable to valuation problems driven by models not only under the risk-neutral probability measure but also under the physical probability measure.

Exploring the Function of Ion-Exchange Membrane in Membrane Capacitive Deionization via a Fully Coupled Two-Dimensional Process Model

In the arid west, the freshwater supply of many communities is limited, leading to increased interest in tapping brackish water resources. Although reverse osmosis is the most common technology to upgrade saline waters, there is also interest in developing and improving alternative technologies. Here we focus on membrane capacitive deionization (MCDI), which has attracted broad attention as a portable and energy-efficient desalination technology. In this study, a fully coupled two-dimensional MCDI process model capable of capturing transient ion transport and adsorption behaviors was developed to explore the function of the ion-exchange membrane (IEM) and detect MCDI influencing factors via sensitivity analysis. The IEM enhanced desalination by improving the counter-ions’ flux and increased adsorption in electrodes by encouraging retention of ions in electrode macropores. An optimized cycle time was proposed with maximal salt removal efficiency. The usage of the IEM, high applied voltage, and low flow rate were discovered to enhance this maximal salt removal efficiency. IEM properties including water uptake volume fraction, membrane thickness, and fixed charge density had a marginal impact on cycle time and salt removal efficiency within certain limits, while increasing cell length and electrode thickness and decreasing channel thickness and dispersivity significantly improved overall performance.