Search results

The purpose of this study is to develop a new protective coating formulation for industrial use, using new eco-friendly succinimide linseed oil resin.

Epoxidized linseed oil and N-(4-hydroxy phenyl) succinimide are reacted to create succinimide-modified epoxy (SIE) compounds. The synthesized compound was confirmed by different analyses, gas chromatography, Fourier transform infrared, proton nuclear magnetic resonance and scanning electron microscopy. The prepared compound has been blended with a primer paint formulation, then their physical and mechanical properties have been studied. Density function theory is used to calculate Frontier molecular orbital including highest occupied molecular orbital and least unoccupied molecular orbital to indicate the charge transfer from molecule to biological media and molecular electrostatic potential map was used to indicate the chemically reactive zone suitable for drug action.

The results of the paint formulation confirmed their best performance and provided good mechanical properties and high chemical and corrosion resistance.

Resin compounds are the most used antimicrobial additives. Other functionalities of these compounds, such as corrosion inhibitors, might be studied to see if they are suited for these applications.

Because of the efficiency of the SIE when incorporated with primer, paint against microbial has also been examined in silico using the docking study which contributed to the analysis of their protein binding. This type of epoxy compound is environmentally friendly and can be used as a biocide with different paint formulations. As a result, paint compositions including this compound as additives can be used as dual-purpose paint and for a variety of industrial applications.

This research demonstrates how a low-cost paint composition based on synthesized SIE compounds may be used as a dual-function paint for industrial use.

Paper aims to preparation of new acid disperse dyes based on thiadiazol derivatives and evaluation of their use as antimicrobial colorants in digital transfer-printing ink formulations for printing onto polyester fabric substrates.

New disperse dyes based on 1,3,4 - thiadiazol derivative (dyes 1–3) were prepared and evaluated by different analysis then formulated as colored materials in the ink formulations. The viscosity, dynamic surface tension and particle size distribution of the prepared inks were measured. The printed polyester fabric substrates were tested using a variety of tests, including light fastness, washing, alkali perspiration and Crock fastness, as well as depth of penetration. Density-functional theory (DFT) calculations were carried out at the Becke3-Lee-Yang-parr (B3LYP) level using the 6–311** basis set, and the biological activity of the prepared disperse dyes was investigated.

The obtained results of the physical of the prepared ink revealed that thiadiazol disperse ink is a promising ink formulation for polyester printing and agrees with the quality of the printed polyester fabric. The optimization geometry for molecular structures agreed with the analysis of these compounds. The HOMO/LUMO and energy gap of the studied system were discussed. The molecular docking analysis showed strong interaction with DNA Gyrase and demonstrated to us the high ability of these inks to act as antimicrobial agents.

The prepared inks containing the prepared thiadiazol disperse dye were high-performance and suitable for this type of printing technique, according to the results. The prepared inks resist the growth of microorganisms and thus increase the ink's storage stability.

The prepared disperse dyes based on 1,3,4 - thiadiazol derivative (dyes 1–3) can be a promising colorant in different applications, like some types of paint formulations and as a colorant in printing of different fabric substrates.

The paper aims to the preparation of novel disperse dye based on azo salicylaldehyde derivatives TF-A [2-hydroxy-5-((3-(trifluoromethyl)phenyl)diazenyl)benzaldehyde] and full evaluation of their use as disperse dye TF-ASC [bis 2-hydroxy-5-((3-(trifluoromethyl)phenyl)diazenyl)benzaldehyde Schiff base with 4,4'-methylenedianiline] for dyeing polyester fabric at various conditions.

The dispersed dye was synthesized via Schiff base condensation in the presence of ceric ammonium nitrate cerium ammonium nitrate 10 mmole% as an eco-friendly catalyst at room temperature. The chemical structure of the prepared dye was characterized via elemental analysis, Fourier-transform infrared spectroscopy, 1H- and 13 C-NMR spectroscopic analysis tools. This study thoroughly examined the dyeing of disperse dye TF-ASC on polyester at various conditions. The characteristics of dyed polyester fabric were measured by colour measurements, as well as light, washing, crock fastness and finally, colour strength. The discrete fourier transform (DFT) theoretical studies, including E_HOMO, E_LUMO and optimized geometrical structure, were assumed and discussed in detail.

The results showed that the synthesized organic dye TF-ASC was highly functional and appropriate for this kind of dyeing method. The dyeing fabrics obtained from disperse dye TF-ASC, properties possess high colour strength as well as good overall fastness properties. These dyes had a high affinity for polyester fabric, with just a tiny change in dye affinity when the pH was changed, even under alkaline circumstances. The dye levelness and shade depth of the colour results were good, and there were a variety of hues from light brownish yellow to deep brownish yellow. The results obtained from DFT computational studies such as E_HOMO, E_LUMO, optimized structure, diploe moment µ and electrophilicity index deduced that prepared organic dye TF-ASC is more applicable as a dispersed dye.

This research is significant because it provides a new dye for dyeing polyethylene terephthalate fibres with exceptional brightness and levelness; the method of preparation is a useful pathway due to its being known as a green chemistry method.

In this study, human activity with finite and specific ranking is modeled with finite state machine, and an application for human–robot interaction was realized. A robot arm was designed that makes specific movements. The purpose of this paper is to create a language associated to a complex task, which was then used to teach individuals by the robot that knows the language.

Although the complex task is known by the robot, it is not known by the human. When the application is started, the robot continuously checks the specific task performed by the human. To carry out the control, the human hand is tracked. For this, the image processing techniques and the particle filter (PF) based on the Bayesian tracking method are used. To determine the complex task performed by the human, the task is divided into a series of sub-tasks. To identify the sequence of the sub-tasks, a push-down automata that uses a context-free grammar language structure is developed. Depending on the correctness of the sequence of the sub-tasks performed by humans, the robot produces different outputs.

This application was carried out for 15 individuals. In total, 11 out of the 15 individuals completed the complex task correctly by following the different outputs.

This type of study is suitable for applications to improve human intelligence and to enable people to learn quickly. Also, the risky tasks of a person working in a production or assembly line can be controlled with such applications by the robots.

This paper aims to synthesize new screen-printing ink formula based on new derivatives of azo thiadiazol disperse dyes and evaluate their characteristics after being printed on polyester fabric substrates.

New dispersed dyes based on 1, 3, 4-Thiadiazole derivatives (dyes 1 and 2) were prepared and confirmed by different analyses, infrared (IR), mass and nuclear magnetic resonance (NMR) spectroscopy, and then formulated as colored materials in the screen-printing ink formulations. Printing pastes containing the prepared dyestuffs and other ingredients were used for printing polyester using screen-printing or traditional printing. The characteristics of printed polyester fabric substrates were measured by color measurements such as a*, b*, L*, C*, E, Ho, R% and color strength, as well as light, washing, crock and alkali perspiration fastness, and finally, the depth of penetration was evaluated.

The prepared 1, 3, 4-Thiadiazole derivatives (dyes 1 and 2) were obtained from the reaction of 5,5’-(1,4-phenylene)bis(1,3,4-Thiadiazole-2-amine) with resorcinol and m-toluidine as a coupling component. The suitability of the prepared dyestuffs for silk screen-printing on polyester fabrics has been investigated. The prints obtained from a formulation containing dye 1 possess high color strength as well as good overall fastness properties if compared to those obtained using dye 2.

The method of synthesis of the new dyestuffs and screen-printing ink provides a simple and practical solution to prepare some new heterocyclic disperse azo dyes, and they are formulated in the screen-printing inks for printing on a polyester fabric substrate.

The prepared disperse dyes based on 1,3,4-Thiadiazole derivatives (dyes 1 and 2) could be used in textile printing of polyester on an industrial scale.

This study aims to evaluate linear mixed data sampling (MIDAS), nonlinear artificial neural networks (ANNs) and a hybrid approach for exploiting high-frequency information to improve low-frequency gross domestic product (GDP) forecasting. Their capabilities are assessed through direct forecasting comparisons.

This study compares quarterly GDP forecasts from unrestricted MIDAS (UMIDAS), standalone ANN and ANN-enhanced MIDAS models using five monthly predictors. Rigorous empirical analysis of recent US data is supplemented by Monte Carlo simulations to validate findings.

The empirical results and simulations demonstrate that the hybrid ANN-MIDAS performs best for short-term predictions, whereas UMIDAS is more robust for long-term forecasts. The integration of ANNs into MIDAS provides modeling flexibility and accuracy gains for near-term forecasts.

The model comparisons are limited to five selected monthly indicators. Expanding the variables and alternative data processing techniques may reveal further insights. Longer analysis horizons could identify structural breaks in relationships.

The findings guide researchers and policymakers in leveraging mixed frequencies amidst data complexity. Appropriate modeling choices based on context and forecast horizon can maximize accuracy.

Enhanced GDP forecasting supports improved policy and business decisions, benefiting economic performance and societal welfare. More accurate predictions build stakeholder confidence and trust in statistics underlying critical choices.

This direct forecasting comparison offers unique large-scale simulation evidence on harnessing mixed frequencies with leading statistical and machine learning techniques. The results elucidate their complementarity for short-term versus long-term modeling.

Strategic planning is an organization’s process of describing its strategy, or direction, and making decisions on allocating its resources to track this strategy. SWOT analysis is one of the most commonly used techniques for strategic planning. SWOT examines the strengths (S) and weaknesses (W) agents of the community together with opportunities (O) and threats (T), for selecting and implementing the best strategy which helps in achieving its goals. The purpose of this paper is to enhance the performance of SWOT analysis regarding the quantitative side of strategies, select the best strategy from different strategies and deal effectively with vague and incompatible information, which occurs usually in actual life.

This study used the neutrosophic analytic hierarchy process (AHP) incorporated with SWOT analysis.

By adding the neutrosophic AHP to SWOT analysis, the performance of SWOT analysis is enhanced through determining the quantitative values and dealing with vague and inconsistent information effectively leading to improved decisions.

The developed integrated methodology is validated in a real-life case of Starbucks company. For the case study of Starbucks company, the proposed model helps in determining different strategic plans and, further, ranking these plans effectively, which will help the company to compete with its competitors and develop itself by obtaining a competitive advantage over its competitors in an uncertain business environment.

In the case study of Starbucks company, the proposed model helps to determine the different strategic plans, rank these plans which help the company compete with its competitors, develop itself and grow.

This research is the first to address SWOT analysis with neutrosophic AHP.