Miracle-dz/UniFAR-FTUs huggingface dataset:
Response surface methodology and adaptive neuro-fuzzy inference system for adsorption of reactive orange 16 by hydrochar

BACKGROUND AND OBJECTIVES: The prediction models, response surface methodology and adaptive neuro-fuzzy inference system are utilized in this study. This study delves into the removal efficiency of reactive orange 16 using hydrochar derived from the Prosopis juliflora roots . Hydrochar dose, pH, temperature, and initial reactive orange 16 concentration were studied in batch processes. The correlation coefficients for the batch processes were found to be 0.978 and 0.9999. The results denote that the adaptive neuro-fuzzy inference system predicted the reactive orange 16 removal efficiency more accurately than the response surface methodology model. METHODS: Prosopis juliflora roots roots are converted into hydrochar to remove azo dye from textile waste water. Prosopis juliflora roots roots were collected from Ramanad District, Southern Tamil Nadu, India. The moisture content was lowered by drying for 24 hours at 103 degree celcius in an oven with hot air. This biomass was thermally destroyed at 300 degree celcius for 15 minutes without oxygen in an autoclave in a muffle furnace (heating rate: 5 degree celcius per minute). As soon as it reaches room temperature, the hydrochar residue of this biomass was used for adsorption investigations. The batch adsorption process was conducted for 6 hours in a 250 milliliter Erlenmeyer conical flask with a 100 milliliter working volume using an orbital shaker. The pH, dosage, concentration, and temperature are the four parameters chosen for this study to find the maximum removal efficiency of the dye from aqueous solutions. This study validated adaptive neuro-fuzzy inference system, an artificial neural network with a fuzzy inference system, using response surface methodology projected experimental run with Box–Behnken method. FINDINGS: The adaptive neuro-fuzzy inference system model is created alongside the response surface methodology model to compare experimental outcomes. Experimental data was evaluated using a hybrid least square and gradient technique. Statistical and residual errors assessed experimental and mathematical model correctness. Experimental data matched the adaptive neuro-fuzzy inference system results. Statistical error analysis verified the model’s accuracy and precision against experimental data. CONCLUSION: Response surface methodology and adaptive neuro-fuzzy inference system optimized process conditions. At pH 2, 2 gram per litre hydrochar dosage, 35 degree celcius , and a reactive orange 16 starting concentration of 250 milligram per liter, removal effectiveness reached 86.1 percent. Adaptive neuro-fuzzy inference system predicted higher values than response surface methodology, with batch correlation coefficients of 0.9999 and 0.9997, respectively. Mathematical techniques can accurately estimate dye removal efficiency from aqueous solutions.
Time Series Artificial Neural Network based Classification Model for Asset Trading Strategy

Best daily trading strategy is meaningful to investors to obtain the maximum return. Financial market plays a key role in the social development. Sufficient funds are of great significance to promote the development of all sectors of society. From the perspective of investors, their purpose is to obtain the maximum income through investing assets in the market. At the same time, the benefit of investors can attract more investors and funds. However, there are huge risks in investment in financial markets. This is mainly because the changes of assets' prices are very complex, and traders cannot predict the changes of assets' prices. Therefore, it is of great significance for investors to determine the trading behavior according to the historical data of asset's price. Aiming at the problem of asset investment strategy, we study from three aspects: asset value accounting, optimal investment strategy and investment decision prediction. A novel method is proposed to represent trading action based on asset state, which represents the current asset state through a 0-1 variable. Then, the change of state indicates the occurrence of transaction. Based on this variable, we propose an evaluation model of the total value of the asset on every day. By maximizing the value of the combination, we establish an optimization model and the Genetic Algorithm (GA) is used to search the best investment combination. Using the prior information of the price, we first solve the combination of asset states of the investor corresponding to the best trading strategy. Then, taking the sequence of states as the supervision information, an Artificial Neural Network (ANN) based classification model for asset state prediction is established. The historical data of Bitcoin daily price is used to predict the asset state on the current day, to realize the decision-making of daily trading strategy. Extensive experiments have been conducted, and the experimental results verify our model can effectively find potential pattern for asset investment and achieve good profits based on the predict investment decisions.
Resolution enhancement of terahertz imaging by incremental Wiener filtering

A two dimensional raster scanning terahertz imaging system based on a continuous backward-wave oscillator (BWO) terahertz source is built up. To improve the spatial resolution of the system, a scanning step smaller than the focused spot size of the terahertz beam is used to get the transmission image. After pre-processing of the image with wavelet filtering, and using incremental Wiener filtering for image restoration, a terahertz image with resolution higher than the diffraction limit of the system can be obtained. Our imaging experiment shows that this method can both enhance spatial resolution and suppress imaging noise effectively.
The effect of eco-label and perceived consumer effectiveness toward green purchase

Although many studies on green marketing were conducted, factors influencing consumers toward their green purchases, for instance, perceived consumer effectiveness, still need to be explored. This study investigates factors such as eco-labels, product attributes, perceived consumer effectiveness, and environmental concern about green product purchases. The study surveyed 200 Indonesian students who purchased and used The Body Shop products. Overall, all the proposed hypotheses are supported. Specifically, eco-labels positively affect both product attributes and perceived consumer effectiveness. While both products attributes and perceived consumer effectiveness positively influence environmental concerns. The last hypothesis related to environmental concerns and green purchases also shows a positive relationship. Lastly, a green marketing strategy is discussed and proposed as the study's implication.
Environmentally-stable wave-breaking-free mode-locked Yb-doped all-fiber laser

We report on experimental generation of wave-breaking-free pulses from an environmentally stable Yb-doped all-fiber laser. The compact linear cavity is constructed with saturable absorber mirror directly glued to the fibers end-facet as nonlinear mode-locking mechanism and chirped fiber Bragg grating (CFBG) for dispersion management, thus, without any free-space optics. Further, the laser was intrinsically environmentally stable, as only polarization maintaining (PM) fibers were used. In the wave-breaking-free regime, the fiber laser directly generates positively-chirped picosecond pulses at a repetition rate of 20.30 MHz. These pulses can be compressed to 218 fs in a HC-PBG providing a femtosecond all-fiber laser system. Adapting the intra cavity dispersion we have also generated chirped pulses with a parabolic spectral profile in the stretched pulse regime. We confirm numerically the wave-breaking-free pulse and stretched pulse evolution and discuss advantages and disadvantages of both regimes in terms of pulse quality.
Calibrating apodizer fabrication techniques for high-contrast coronagraphs on segmented and monolithic space telescopes

High contrast imaging can use pupil apodizers to suppress diffracted starlight from a bright source in order to observe its environs. Metallic half-tone dot transmissive apodizers were developed for the Gemini Planet Imager (GPI) and ESO SPHERE coronagraphs for use in the near-IR. Dot sizes on the scale of the wavelength of the light often result in unexpected variations in the optical transmission vs. superficial dot density relation. We measured 5 and 10 micron half-tone microdot screens' transmissions between 550 -1050 nm to prepare to fabricate apodizations that mitigate diffraction by segments gaps and spiders on future large space telescopes. We utilized slow test beams (f/40, f/80) to estimate the on-axis (far-field, or zero-order) transmission of test patches using a Fourier Transform Spectrograph on Beamline U10B at Brookhaven National Laboratory's National Synchrotron Light Source (BNL NSLS). We also modified our previous GPI IR characterization hardware and methods for this experiment. Our measurements show an internal consistency of 0.1% in transmission, a factor of 5 better than our near-IR GPI work on the NSLS U4IR beamline. The systematics of the set-up appeared to limit the absolute calibration for our f/40 data on the 50-patch, maximum Optical Density 3 (OD3), sample. Credible measurements of transmissions down to about 3% transmission were achieved for this sample. Future work on apodizers for obstructed and segmented primary mirror coronagraphs will require configurations that mimic the intended diffractive configurations closely in order to tune apodizer fabrication to any particular application, and measure chromatic effects in representative diffractive regimes. Further experimental refinements are needed to measure the densest test patches which possess transmissions less than a few percent. The new NSLS-II should provide much greater spectral stability of its synchrotron beam, which will improve measurement accuracy and reduce systematics.
Linking Consumer Innovativeness to the Cryptocurrency Intention: Moderating Effect of the LOHAS (Lifestyle of Health and Sustainability) Lifestyle

: Cryptocurrency is gaining worldwide recognition. This research examines the role of personality and psychological factors in consumers’ cryptocurrency adoption behavior. 452 samples are collected from U.S consumers and the data are analyzed by PLS-SEM. The findings reveal that consumer innovativeness has a positive influence on the intention to use cryptocurrency and its impact is partially mediated by attitude. The LOHAS lifestyle moderated the influence of consumer innovativeness on the cryptocurrency intention as well as the relation of attitude with the intention. This research provides theoretical and practical implications for the cryptocurrency market.
An accurate numerical algorithm for advective transport

The paper describes a new numerical algorithm for pure advection at large Courant numbers. The DISCUS scheme uses an accurate and proven control volume algorithm (QUICKEST) within a Lagrangian treatment of advection. By being in sympathy with the information flow dictated by characteristic lines, the scheme performs exceedingly well at Courant numbers greater than one. In contrast to existing Lagrangian schemes which use the characteristics to determine the grid points from which concentrations are interpolated, in DISCUS the characteristics are used to determine the appropriate location for the control volume. The scheme is of comparable accuracy to Eulerian schemes at Courant numbers less than one, but it increasingly outperforms them as the Courant number increases. Indeed, the results reported illustrate the futility of using an Eulerian scheme at high Courant numbers.
HIGHER-ORDER SPECTRA: THE BISPECTRUM AND TRISPECTRUM

Abstract This paper is concerned with the development of techniques to detect and analyse non-linearities. The methods developed are based on the concepts of higher-order spectra (HOS), in particular the bispectrum and trispectrum. The study of HOS has been dominated by work on the bispectrum. The bispectrum can be viewed as a decomposition of the third moment (skewness) of a signal over frequency and proves useful for analysing systems with asymmetric non-linearities. In studying symmetric non-linearities, the trispectrum is a more powerful tool, as it represents a decomposition of kurtosis over frequency. Techniques are presented that enable the estimation and display of bispectra and trispectra. HOS are studied in detail with particular attention being paid to normalisation methods. Two traditional methods, the bicoherence and skewness function, are studied and these are extended to their fourth-order equivalents, the tricoherence and kurtosis functions. Under certain conditions, notably narrowband signals, the above normalisation methods are shown to fail, and so a new technique based on pre-whitening the signal in the time domain is developed. Examples of these functions are given both for an amplitude modulated process and the Duffing oscillator.
The effect of financial knowledge, financial attitude, and personality on financial management behavior

Financial management for young entrepreneurs needs to be done because disciplined financial arrangements will be able to minimize the risk of uncertainty. Young entrepreneurs have problems with financial management behavior, that is knowledge and skills in managing finances which have an impact on financial decision-making. This study aims to see the effect of financial knowledge, financial attitudes, and personality on financial management behavior in young entrepreneurs in Malang. The approach used in this research is quantitative with an explanatory approach. This study's population is young entrepreneurs in the Brawijaya University environment. The sampling technique used purposive sampling with a sample size of 150 samples. The results of this study prove that partially financial knowledge has no significant effect on Financial Management Behavior. Financial attitudes have a significant effect on Financial Management Behavior, and personality has a significant effect on Financial Management Behavior in Young Entrepreneurs in Malang City.
Rejoinder to the Letter to the Editor from P. S. Albert

Lu, Lin, and Shih (2004) proposed a mixture model for making marginal inferences about clustered continuous data with excess zeros in which a proportion of observations follows a normal distribution with mean zero and variance σ0, and the remainder follow a normal distribution with mean μ1 and variance σ 2 1. When σ 2 0 = 0, their model reduces to the two-part model for clustered data. They proposed a generalized method of moments with an independence working model approach for marginal inference. Parameter estimates were obtained by solving the score equation derived under the assumption that observations within a cluster are independent from each other. Variance estimation and hypothesis tests were formulated using procedures which are robust to misspecification of the correlation structure induced by the clustering. This letter discusses a potential difficulty in interpreting marginal inference with this approach when clustering induces a dependence between the mixing proportion and the conditional mean. As in Lu et al. (2004) we define Yij as the outcome variable and ξij as an indicator of whether Yij = 0. For simplicity, I will illustrate my concern with the two-part model with two groups, logitP (ξij = 1 |Wij ) = γ0 + γ1Wij and μ(Xij ) = E[Yij | ξij = 1, Xij ] = β0 + β1Xij as described in Section 6 of their paper, whereby Wij and Xij are group indicators and γ1 and β1 are interpreted as the effect of group on the marginal probability of a non-zero observation and on the marginal mean response given the observation is non-zero, respectively. Suppose that the true probability mechanism for the clustered data is characterized by a random effect model with correlated subject-specific random intercepts for the two components of the model (Olsen and Schafer, 2001; Tooze, Grunwald, and Jones, 2002). Specifically, define bi and ci as two cluster-specific correlated random effects which induce a dependence between the cluster-specific probability of a nonzero response and the mean cluster-specific response given a positive response through the model pij = P (ξij = 1 | bi ) = logit(γ0 + γ ∗ 1Wij + bi ) and μij = E[Yij | ξij = 1, ci ] = β0 + β ∗ 1Xij + ci , where (bi , ci ) is bivariate normal with mean (0, 0) and covariance structure parameterized as var(bi ) = σ 2 b, var(ci ) = σ 2 c, and cov(bi , ci ) = σcσbρ. It is important to incorporate the potential for correlation between the two random effects since, if there is a sizable cluster effect, it is biologically sensible that clusters with a high proportion of positive responses may be ones with higher means given a positive response (conditional means). For the two-group comparison where Wij = Xij , the marginal mean μ can be written as μ(Xij ) = E[Yij | ξij = 1, Xij ] = β0 + β ∗ 1Xij + E[ci | ξij = 1, Xij ], where E[ci | ξij = 1,Xij ]
Numerical evaluation of two discontinuous Galerkin methods for the compressible Navier–Stokes equations

This paper presents a critical comparison between two recently proposed discontinuous Galerkin methods for the space discretization of the viscous terms of the compressible Navier–Stokes equations. The robustness and accuracy of the two methods has been numerically evaluated by considering simple but well documented classical two‐dimensional test cases, including the flow around the NACA0012 airfoil, the flow along a flat plate and the flow through a turbine nozzle. Copyright © 2002 John Wiley & Sons, Ltd.
Stability of stochastic nonlinear switched systems with average dwell time

This paper concerns the stability of nonlinear stochastic switched systems with delay. By using the Razumikhin method and the average dwell time approach, some sufficient criteria of stability are derived. It is shown that when the Lyapunov-like functions are decreasing in all active subsystems, the switched system is pth-moment exponentially stable. Moreover, it is also shown that under some conditions the system can be pth-moment stable and global asymptotically stable, where the Lyapunov-like functions are increasing on some intervals. The effectiveness of the proposed results is illustrated by two examples.
On a new Theorem Involving Generalized Mellin-Barnes Type of Contour Integral and Srivastava Polynomials

Abstract Motivated by resent work of Agarwal [1], the author is establish the new theorem associated with the H - function (Generalized Mellin-Barnes type of Contour Integral), which was introduced and study in a series of papers by by Inayat -Hussain ([12], [13]). Theorem involves a product of the H -function, Generalized hypergeometric functions and Srivastava polynomials. The convergence and existence condition, basic properties of H -function were given by Buschman and Srivastava ([7]). Next, we obtain certain new integrals by the application of our theorem. These results, besides being of very general character have been put in a compact form avoiding the occurrence of infinite series and thus making them useful in applications. Our findings provide interesting unifications and extensions of a number of new results.
Direct and Indirect Search for Dark Matter

Direct and indirect searches for dark matter (DM) particles are discussed. The search for a diffuse signal from DM annihilation in the Milky Way is presented using the atmospheric neutrino data from Super-Kamiokande-I, -II, -III. The analysis focuses on the model independent scenario with DM particles annihilating directly into pairs of neutrinos and antineutrinos. No signal contribution is allowed by the Super-Kamiokande data for considered masses of DM particles in the range from 3 GeV to 3 TeV. The upper limit on DM-induced neutrino flux has been obtained as a function of the mass of relic particles. The corresponding limit on the DM self-annihilation cross section 〈σAV 〉 has been evaluated. With this analysis, the existing limit on the value of 〈σAV 〉 has been significantly improved for DM particle masses below 100 GeV as compared to previous constraints based on neutrino interactions data. Presented search can be also related to the concept of the decay of DM particles. The limit on DM decay lifetime τDM has been derived. Finally, studies related to direct DM detection are presented. The results of simulations of neutron background for the Argon Dark Matter (ArDM) experiment are shown.
A plane wave diffraction on a pin-hole in a film with a finite thickness and real electrodynamic properties

On a base of the Kirchhoff-Helmholtz method and using the Green function for a half-space which is covered by a film of any thickness and with arbitrary optical properties, amplitude-phase characteristics of diffracted on a pin-hole field were calculated. Analysis was carried out for some materials of the film at radiation wave-length λ0=633 nm using experimental values of the dielectric constants. The diffracted wave front has deformations which dependent on the film thickness and material electrodynamic characteristics, and the observation angle. The deformation determined by the film thickness essentially limits an accuracy provided by point diffraction interferometers.
Spectral and coherence signatures of threshold in random lasers

We investigated the spectral and coherence signatures of threshold in random lasers with incoherent feedback consisting of alumina colloidal nanoparticles suspended in rhodamine 6G methanol solution under nanosecond-pulsewidth pumping, based on measurement of temporal and spatial coherence properties and comparison with emission spectra. Feedback in this random laser was provided by multiple scattering from the alumina particles, and the effects of particle concentration and scattering length were studied for the weakly scattering and diffusive scattering regimes. At threshold, in each regime, the visibility of the interference fringes jumped abruptly, coinciding with a substantial increase in peak emission intensity and decrease in the linewidth of a single dominant emission peak.
On Set-Texture Spaces and Degree-Texture Spaces

A general theory of fuzzy sets was described employing texture spaces. This work aimed to introduce two concepts in texture theory, namely set-texture and degree-texture spaces using topological spaces and new properties. Moreover, many examples were studied to investigate new texture spaces. The new concepts will use in other topological spaces and find another application on it.