Impact of bismuth oxide on the structure,optical features and ligand field parameters of borosilicate glasses doped with nickel oxide

Understanding the impact of bismuth cations on the optical properties of borosilicate glass is significant for manipulating borate glass applications. In this paper, the influence of bismuth cations on both structural and optical properties of borosilicate glass doped with NiO was investigated. Different glass samples, containing different amounts of Bi₂O₃ and a constant amount of NiO, were prepared and studied. Infrared (IR) analysis was carried out to study the internal structure within the investigated glass samples. Optical absorption studies were performed to investigate the impact of Bi₂O₃ content on optical properties of the BiBaNiB-glasses. Astonishingly, with Bi₂O₃ addition, an absorption band at 380 nm has appeared. Moreover, this band is overlapped with the Urbach edge; which regularly produced an artificial edge-like feature at ~450 nm. A detailed deconvolution protocol has been implemented for an appropriate understanding of these spectra and unraveling the hidden Urbach edge. Optical band gap energy, linear and nonlinear refractive index for each BiBaNiB sample were calculated. Furthermore, the metallization criterion was calculated to examine the metallic or insulating nature of the BiBaNiB-glasses. The values of the nonlinear third-order susceptibility and nonlinear refractive index were increased with Bi₂O₃ doping. The BiBaNiB-glasses exhibited outstanding stability and optical band gap than the pristine glass sample, which makes it possible for practical applications.     

Synthesis,characterization and adsorption studies of h-BN crystal for efficient removal of Cd2+ from aqueous solution

In the present study, hexagonal boron nitride (h-BN) was synthesized from boric acid and melamine by thermal annealing method in a nitrogen atmosphere. The pure h-BN was used as an efficient sorbent for the uptake of Cd²⁺ ions from the solution phase. The kinetics and sorption studies of metal ions onto the h-BN were carried out in batch adsorption experiments at different temperature, time, pH, sorbent dosage, and concentration of metal ions. The optimum pH for the removal of the Cd²⁺ ions was found to be pH 7. The effect of temperature showed that the process of Cd²⁺ sorption remained endothermic in the range of 298 K–328 K. The Lagergren's first and Ho's second kinetic models were tested to interpret the adsorption kinetic data, however the present data was explained well by Ho's model for kinetics. The thermodynamic perameters ΔG, ΔS and ΔH were determined using the available adsorption data at different temperatures. The physicochemical properties of the synthesized product were also characterized before and after adsorption by different analytical techniques like FT-IR, TGA, XRD and Point of Zero Charge (PZC). The morphology of the surface was analyzed with the help of Scanning Electron Microscopy. The h-BN proved to be an efficient adsorbent for the uptake of the Cd²⁺ ions from aqueous media.     

Nonmonotonic Coupled Dissolution-Precipitation Reactions at the Mineral–Water Interface

Dissolution is inherent to fluid-mineral systems. Yet its impact on minerals reacting with electrolytes is overlooked. Here, a novel nonmonotonic behavior for the surface interactions of carbonates (calcite and Mg-calcite) with organic acids is reported. Applying a bioinspired approach, Mg-calcite sensors via amorphous precursors, avoiding any preconditioning with functional groups are synthesized. A quartz crystal microbalance is used to study the mass changes of the mineral on contact with organic acids under varying ionic conditions, temperatures, and flow velocities. Supported by confocal Raman microscopy and potentiometric titrations, nonmonotonous mass developments are found as a function of Ca²⁺ concentration and flowrate, and attributed to three coupled chemical reactions: i) carbonate dissolution via Ca²⁺ ion complexation with organic molecules, and the formation of organo-calcium compounds as ii) a surface phase at the mineral–water interface, and iii) particles in the bulk fluid. These processes depend on local ion contents and the precipitation onset (i.e., saturation index) of organo-calcium salts, both of which substantially differ in the bulk fluid and in the fluid boundary layer at mineral interfaces. This continuum between dissolution and precipitation provides a conceptual framework to address reactions at mineral interfacial across disciplines including biomineralization, ocean acidification and reservoir geochemistry.     

H∞ filtering of discrete-time interconnected systems with failed interconnections

The H_∞ filtering problem for interconnected systems is addressed in this paper. In order to facilitate the stability analysis of interconnected systems under the conditions of failed interconnections, a strategy related to switched systems is introduced. Assume that the interconnections among these subsystems disconnect based on the mode-dependent average dwell time (MDADT), a switching signal is implemented to denote the failed interconnections cases. In the aid of the MDADT method, a filter is designed such that the fault detection (FD) system is asymptotically stable and satisfies the weighted H_∞ performance. Finally, a numerical simulation is provided to show the effectiveness of the proposed filter.     

On an influence of thermal stresses and magnetic field in thermoelastic half-space without energy dissipation

In this article, a two-dimensional problem for a homogeneous, isotropic, and thermoelastic half-space subjected to magnetic field and time-dependent heat source is investigated. The boundary conditions at the surface have been considered in the context of Green-Naghdi’s second model (GN-II) of thermoelasticity. The normal mode analysis and eigenvalue approach techniques are used to solve the nondimensional coupled equations. The effect of magnetic field, frequency, wave number, and time is analyzed theoretically and computed numerically. Comparison was made with the results obtained in the presence and absence of the magnetic field. Numerical results for the displacement components, mean value of normal stresses, dilatation, and temperature have been represented graphically to show the physical meaning of the external parameters. The results indicate that the effect of magnetic field, frequency, wave number, and time is very pronounced and effective on the phenomena.     

NUMERICAL SIMULATION OF THE THERMAL CONTROL OF HEAT EXCHANGERS

The temperature control of outlet air by changing the water flow rate in a single-pass waterto-air cross-flow heat exchanger is investigated. The conservation laws are applied to finite control volumes and an implicit formulation is used for transient numerical solutions. Conjugate forced convection heat transfer from the tube is solved to calculate the temperatures of the air and water coming out of the heat exchanger. In the simulations the outlet air temperature is controlled by changing the water flow rate entering the heat exchanger using a proportional-integral (PI) controller. The range of controllability of the heat exchanger was studied first. Then disturbances in the form of step changes in the inlet air temperature, the air flow rate, and the set point temperature were separately introduced. The effects of the limiting-condition constraints and different control parameters on controlling the outlet air temperature are presented. The results show that the control behavior can be simulated numerically and that this control methodology is effective within limits.     

Speech recognition

The authors have designed, successfully trained and tested an Arabic speech recognition system. This system was implemented using C++ programming language on Windows 95. It can be partitioned into five main modules. These modules are the front-end, feature extraction, training, pattern recognition and decision making and display. The front-end module functions as signal preparation and calibration. This includes: setting the signal sampling rate, removing the DC component from the signal, setting the scaling factor of the signal and detecting the endpoints of the utterance. The endpoint task removes the non-speech signal portions created by the speaker's pauses. This reduces the system computation time needed and the memory requirements. The feature extraction module is mainly a digital signal processor. The training module is the one that finds the best templates for every word or sound (phonemes) in the system's database. In short, this module needs to be executed only one time before users can utilize the system. The next module is the pattern recognition module. Its function is to compare the given utterance (test utterance) to all the stored templates (the reference module). The decision and display module functions as an interface between the user and the hidden system modules. In other words, after getting the recognition module results, this module displays the best candidate(s) and/or their likelihood percentage. The error rates are computed and displayed in this module     

Combustion synthesis of NbC/ZrO2 composites: Influence of Cr additives on the microstructure and mechanical properties

Composites of NbC/ZrO₂ reinforced with different weight ratios of Cr metal were prepared by dynamic compaction combustion from a blend of Nb₂O₅–Zr–Cr powders. Factors controlling the synthesis process, the microstructure, and the mechanical properties of the samples, such as Cr wt% and the compression loads were studied. The samples were characterized by XRD, SEM, porosity, and hardness measurements. The porosity value of the sample with no additives was high and reached 31.6 vol%. A sudden decrease in the sample porosity to 2.4 vol % was noticed for the sample containing 3.0 wt% of Cr. A high-density sample with less than 2.0 vol % porosity and maximum hardness of 1038 HV was produced using 5.0 wt% Cr under 300 MPa compression load. Detailed thermodynamic calculations for the effect of Cr additives on the physicochemical properties of the system were introduced.     

Study on pharyngeal and uvular consonants in foreign accented Arabic for ASR

This paper investigates the unique pharyngeal and uvular consonants of Arabic from the point of view of automatic speech recognition (ASR). Comparisons of the recognition error rates for these phonemes are analyzed in five experiments that involve different combinations of native and non-native Arabic speakers. The most three confusing consonants for every investigated consonant are discussed. All experiments use the Hidden Markov Model Toolkit (HTK) and the Language Data Consortium (LDC) WestPoint Modern Standard Arabic (MSA) database. Results confirm that these Arabic distinct consonants are a major source of difficulty for Arabic ASR. While the recognition rate for certain of these unique consonants such as // can drop below 35% when uttered by non-native speakers, there is advantage to include non-native speakers in ASR. Besides, regional differences in pronunciation of MSA by native Arabic speakers require the attention of Arabic ASR research.     

Suggestion Mining from Opinionated Text of Big Social Media Data

Social media data are rapidly increasing and constitute a source of user opinions and tips on a wide range of products and services. The increasing availability of such big data on biased reviews and blogs creates challenges for customers and businesses in reviewing all content in their decision-making process. To overcome this challenge, extracting suggestions from opinionated text is a possible solution. In this study, the characteristics of suggestions are analyzed and a suggestion mining extraction process is presented for classifying suggestive sentences from online customers’ reviews. A classification using a word-embedding approach is used via the XGBoost classifier. The two datasets used in this experiment relate to online hotel reviews and Microsoft Windows App Studio discussion reviews. F1, precision, recall, and accuracy scores are calculated. The results demonstrated that the XGBoost classifier outperforms—with an accuracy of more than 80%. Moreover, the results revealed that suggestion keywords and phrases are the predominant features for suggestion extraction. Thus, this study contributes to knowledge and practice by comparing feature extraction classifiers and identifying XGBoost as a better suggestion mining process for identifying online reviews.