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This study aims to perform the surface treatment of synthetic α-Fe₂O₃ red iron oxide pigment with hydrolysate 3-aminopropyl silane (A) and colloidal silica (CS) and investigate the effects of surface-treated pigment on the styrene acrylic (SA) emulsion and polyurethane (PU) dispersion.

For this purpose, firstly red iron oxide particles were modified with A and CS separately in an aqueous medium. After isolation of the modified iron oxide were characterized by Fourier transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS) and scanning electron microscopy with energy dispersive spectroscopy (SEM-EDS). Moreover, the degree of the dispersion stability of the modified pigment in coatings with SA emulsion and PU dispersion was investigated by using an oscillation rheometer. Loss (G''), storage (G') modulus, loss factor [tan(δ)] and yield stress (τ⁰) values were determined by performing amplitude and frequency sweep tests.

The τ⁰ in SA coatings decreases with the amount of used A and increases with the amount of used CS. The τ⁰ decreases as the amount of used A and CS in PU coatings increases. The use of CS on red iron oxide pigments causes storage modulus to increase in SA coatings at low angular frequencies, while it causes a decrease in PU coatings.

To the best of the authors’ knowledge, for the first time, the suspended state of the iron oxide hybrid pigment formed with CS in the coating was investigated rheologically in this study.

Though academic study on the subject is still in its early stages, there is growing interest in using blockchain technology for transforming the supply chain. The academic literature is divided and yet only includes studies evaluating how the supply chain has changed organizations. To comprehend the new phenomena, this study aims to investigate the factors of blockchain technology in driving supply chain transformation. To be more precise, the authors developed from the literature the most prevalent criteria for determining if supply chain transformations are ready to be scaled up.

This study followed a combination of two multi-criteria decision making methods evaluation based on distance from average solution and complex proportional assessment) methodology in this research: planning, investigating, executing out, establishing a rating of the criteria and evaluating it.

The study shows that the “organizational driver” and the “technology driver” are the factors most important to the transformation of the supply chain, whereas the “financial driver” and the “regulatory driver” are less important. This study also makes some managerial recommendations to address the factors impeding the supply chain’s transformation. Each factor’s significance was explored, and a proposed study agenda was also presented.

Although the main forces behind the transformation of the supply chain have been recognized, further research into statistical correlation is required to confirm how the various elements interact.

This research aids decision-makers in comprehending the key forces behind supply chain transformation. Managers and decision-makers might better predict and allocate the necessary resources to start the road toward digitization and make well-informed choices once these aspects have been investigated and understood.

In light of the pandemic’s effects on the world and the increase in businesses embracing the digital economy, the supply chain transformation is more important than ever. Beyond blockchain deployment and the pilot studies on digital transformation, there is a gap. The topics and factors this study uncovered will operate as a framework and recommendations for more theoretical investigation and practical applications.

Global construction has been affected by COVID-19 unprecedently. The construction sectors in the least developed countries are considered as vulnerable, but the covid made the countries experience the worst situation ever. To minimize the losses by effective measures, there needs to assess the COVID-19 impacts on the construction sector. So, the aim of this study is to investigate the most critical impacts of COVID-19 on construction in the least developed countries by considering the case study of Bangladesh.

The authors adopted multistep research methods, including (1) literature analysis and discussion with experts to establish a comprehensive list of COVID-19 impacts; (2) through a questionnaire survey, data were collected from 217 construction professionals by email, Google Form and Skype for quantifying the significance of covid impacts; (3) reliability of the survey checked by the Cronbach Alpha test; (4) Relative Importance Index (RII) to determine the ranks of the impacts based on their significance; (5) Interpretive Structural Model (ISM) to explore the corelations and the hierarchical structure; and (6) cross-impact matrix multiplication applied to classification (MICMAC) analysis to classify the COVID-19 impacts.

The study identified a total of 18 COVID-19 impacts on the construction sector. Among them, the job cuts, schedule delays, project suspension, cost overrun and effects on mental health are more influential and significant than others. Further, this study found that unpaid leave and job cuts are the two most fundamental impacts which influence other succeeding significant impacts. And ultimately all the impacts lead to hampering the national economy and development. Finally, MICMAC analysis suggested that unpaid leave and job cuts should be addressed first to resolve and effects on the national economy and development should be later.

This study does not consider all the COVID-19 impacts due to the relevant context and simplicity of the ISM method. Also, the respondent's attitude might be slightly different during the post-mass vaccination period.

This study will help the company's management, employees and government to develop effective strategies to understand the insight of their interrelations and ultimately overcome the identified covid effects. This will must contribute to the industry, its employees, the government and society by ensuring the national economy and development, construction operations, investment, employment and social security.

This study will contribute to the knowledge body (practitioners and researchers) by providing the list of significant covid impacts and insight into their interrelations for further deep analysis of the pandemic effects. This will also help the authorities and stakeholders in developing policies and strategies to minimize or avoid these effects and avoid future consequences due to any pandemic like covid.

In response to the challenge of reduced efficiency or failure of robot motion planning algorithms when faced with end-effector constraints, this study aims to propose a new constraint method to improve the performance of the sampling-based planner.

In this work, a constraint method (TC method) based on the idea of cross-sampling is proposed. This method uses the tangent space in the workspace to approximate the constrained manifold pattern and projects the entire sampling process into the workspace for constraint correction. This method avoids the need for extensive computational work involving multiple iterations of the Jacobi inverse matrix in the configuration space and retains the sampling properties of the sampling-based algorithm.

Simulation results demonstrate that the performance of the planner when using the TC method under the end-effector constraint surpasses that of other methods. Physical experiments further confirm that the TC-Planner does not cause excessive constraint errors that might lead to task failure. Moreover, field tests conducted on robots underscore the effectiveness of the TC-Planner, and its excellent performance, thereby advancing the autonomy of robots in power-line connection tasks.

This paper proposes a new constraint method combined with the rapid-exploring random trees algorithm to generate collision-free trajectories that satisfy the constraints for a high-dimensional robotic system under end-effector constraints. In a series of simulation and experimental tests, the planner using the TC method under end-effector constraints efficiently performs. Tests on a power distribution live-line operation robot also show that the TC method can greatly aid the robot in completing operation tasks with end-effector constraints. This helps robots to perform tasks with complex end-effector constraints such as grinding and welding more efficiently and autonomously.

This study aims to fabricate multiwalled carbon nanotubes (MWCNTs)-mediated polyvinyl alcohol (PVA) composite films using the solution casting approach.

The prepared films were evaluated for diverse structural, surface, optical and electrical attributes using advanced analytical techniques, i.e. electron microscopy for surface morphology, Fourier transform infrared spectroscopy for tracing chemical functionalities, x-ray diffraction (XRD) for crystal patterns, water contact angle (WCA) analysis for surface wettability and UV visible spectroscopy for optical absorption parameters. The specimens were also investigated for certain rheological, mechanical and electrical properties, where applicable.

The surface morphology results expressed a better dispersion of MWCNTs in the resultant PVA-based nanocomposite film. The XRD analysis exhibited that the nanocomposite film was crystalline. The surface wettability analysis indicated that with the inclusion of MWCNTs, the WCA of the resultant nanocomposite film improved to 89.4° from 44° with the pristine PVA film. The MWCNTs (1.00%, w/w) incorporated PVA-based film exhibited a tensile strength of 54.0 MPa as compared to that of native PVA as 25.3 MPa film. There observed a decreased bandgap (from 5.25 to 5.14 eV) on incorporating the MWCNTs in the PVA-based nanocomposite film.

The MWCNTs’ inclusion in the PVA matrix could enhance the AC conductivity of the resultant nanocomposite film. The prepared nanocomposite film might be useful in designing certain optoelectronic devices.

The results demonstrated the successful MWCNTs mediation in the PVA-based composite films expressed good intercalation of the precursors; this resulted in decreased bandgap, usually, desirable for optoelectronic applications.

The manufacture of polymer composites with a lower environmental footprint requires incorporation of sustainably sourced components. In addition, the incorporation of novel components should not compromise the material properties. The purpose of this paper is to demonstrate the use of a synthetic amine functional toluidine acetaldehyde condensate (AFTAC) as a modifier for fiber-reinforced epoxy composites. One of the fiber components was sourced from agricultural byproducts, and glass fiber was used as the fiber component for comparison.

The AFTAC condensate was synthesized via an acid-catalyzed reaction between o-toluidine and acetaldehyde. To demonstrate its efficacy as a toughening agent for diglycidyl ether bisphenol A resin composites and for the comparison of reinforcing materials of interest, composites were fabricated using a natural fiber (mat stick) and a synthetic glass fiber as the reinforcing material. A matched metal die technique was used to fabricate the composites. Composites were prepared and their mechanical and thermal properties were evaluated.

The inclusion of AFTAC led to an improvement in the mechanical strengths of these composites without any significant deterioration of the thermal stability. It was also observed that the fracture strengths for mat stick fiber-reinforced composites were lower than that of glass fiber-reinforced composites.

To the best of the authors’ knowledge, the use of the AFTAC modifier as well as incorporation of mat stick fibers in epoxy composites has not been demonstrated previously.

In the supply chain disruption risk, the issue of supplier evaluation and selection is solved by an extended VIKOR method based on regret theory.

Considering the influence of irrational emotions of decision makers, an evaluation model is designed by the regret theory and VIKOR method, which makes the decision-making process closer to reality.

The paper has some innovations in the evaluation index system and evaluation model construction. The method has good stability under the risk of supply chain interruption.

The mixed evaluation information is used to describe the attributes, and the evaluation index system is constructed by the combined method of the social network analysis method and the literature research method to ensure the accuracy and accuracy of the extracted attributes. The issue of supplier evaluation and selection is solved by an extended VIKOR method based on regret theory.

In this paper we talk about complex matrix quaternions (biquaternions) and we deal with some abstract methods in mathematical complex matrix analysis.

We introduce and investigate the complex space HC consisting of all 2 × 2 complex matrices of the form ξ=z1+iw1z2+iw2−z‾2−iw‾2z‾1+iw‾1, (z1,w1,z2,w2)∈C4.

We develop on HC a new matrix holomorphic structure for which we provide the fundamental operational calculus properties.

We give sufficient and necessary conditions in terms of Cauchy–Riemann type quaternionic differential equations for holomorphicity of a function of one complex matrix variable ξ∈HC. In particular, we show that we have a lot of holomorphic functions of one matrix quaternion variable.

The aim of this study is to determine the fracture behavior of wool felt and fabric based epoxy composites and their responses to electromagnetic waves.

Notched and unnotched tensile tests of composites made of wool only and hybridized with a glass fiber layer were carried out, and fracture behavior and toughness at macro scale were determined. They were exposed to electromagnetic waves between 8 and 18 GHz frequencies using two horn antennas.

The keratin and lignin layer on the surface of the wool felt caused lower values to be obtained compared to the mechanical values given by pure epoxy. However, the use of wool felt in the symmetry layer of the laminated composite material provided higher mechanical values than the composite with glass fiber in the symmetry layer due to the mechanical interlocking it created. The use of wool in fabric form resulted in an increase in the modulus of elasticity, but no change in fracture toughness was observed. As a result of the electromagnetic analysis, it was also seen in the electromagnetic analysis that the transmittance of the materials was high, and the reflectance was low throughout the applied frequency range. Hence, it was concluded that all of the manufactured materials could be used as radome material over a wide band.

Sheep wool is an easy-to-supply and low-cost material. In this paper, it is presented that sheep wool can be evaluated as a biocomposite material and used for radome applications.

The combined evaluation of felt and fabric forms of a natural and inexpensive reinforcing element such as sheep wool and the combined evaluation of fracture mechanics and electromagnetic absorption properties will contribute to the evaluation of biocomposites in aviation.

The purpose of this review is to comprehensively consider the material properties and processing of additive titanium alloy and provide a new perspective for the robotic grinding and polishing of additive titanium alloy blades to ensure the surface integrity and machining accuracy of the blades.

At present, robot grinding and polishing are mainstream processing methods in blade automatic processing. This review systematically summarizes the processing characteristics and processing methods of additive manufacturing (AM) titanium alloy blades. On the one hand, the unique manufacturing process and thermal effect of AM have created the unique processing characteristics of additive titanium alloy blades. On the other hand, the robot grinding and polishing process needs to incorporate the material removal model into the traditional processing flow according to the processing characteristics of the additive titanium alloy.

Robot belt grinding can solve the processing problem of additive titanium alloy blades. The complex surface of the blade generates a robot grinding trajectory through trajectory planning. The trajectory planning of the robot profoundly affects the machining accuracy and surface quality of the blade. Subsequent research is needed to solve the problems of high machining accuracy of blade profiles, complex surface material removal models and uneven distribution of blade machining allowance. In the process parameters of the robot, the grinding parameters, trajectory planning and error compensation affect the surface quality of the blade through the material removal method, grinding force and grinding temperature. The machining accuracy of the blade surface is affected by robot vibration and stiffness.

This review systematically summarizes the processing characteristics and processing methods of aviation titanium alloy blades manufactured by AM. Combined with the material properties of additive titanium alloy, it provides a new idea for robot grinding and polishing of aviation titanium alloy blades manufactured by AM.