The main goal of this paper is studying the composite material behavior under microwave which they used in antennas reflectors. For that, a transmission line method based on X- band WR90 rectangular waveguide is used. The Bi-anisotropic electrical properties are defined as tensors in finite element model. The fibers of the single layer composite are oriented in different directions. The S-parameters (S11 and S12) are calculated using COMSOL Multiyphysics, the S-parameters and currents density behavior show that they very affected by the orientations of the fibers which mean must be considered in any design of RF equipments, more the fibers are parallel with the electrical field more the reflection coefficient get higher.

Cellulose nanofibre (CNF) is a biorenewable and biodegradable nanomaterial and belongs to fibrous based carbohydrate polymers applied in the fabrication of various functional materials such as coating, nanocomposite, flexible electronics substrates and biomedical devices. Recently, CNF can be used as coating material for papers and paperboards to replace synthetic plastics, wax and aluminum foil which is not recyclable and also a threat to environment. The coating of CNF on the paper substrates enhances their barrier and mechanical properties. Spray coating is a newly proposed technique to deposit CNF on the paper and produce CNF laminates on the surface of paper to block their surface pores and allowing improve their barrier performance against water vapor, air and oxygen. Various concentration of CNF was sprayed on various paper substrates such as newsprint papers, packaging paper (brown paper) and blotting papers. The air permeability of CNF laminated paper substrates is completely impermeable against air. The SEM micrograph reveals that the surface pores in the paper substrates are filled with sprayed CNF and formed a barrier film as a laminate on the paper substrates. As a result, a considerable drop in the air permeability of the paper substrates was observed. Given this correspondence, spraying of cellulose nanofiber on the paper substrates allows the improvement of barrier performance and proof of concept for coating CNF on the paper and paperboard.

The kinetics, equilibrium and thermodynamic study of the adsorption of Ni²⁺, Pb²⁺ and Cu²⁺ions from aqueous solution by the leaf of Mangiferaindica were investigated at different experimental conditions. Optimum conditions of initial metal ion concentration, pH, adsorbent dose, contact time and temperature were determined. The kinetics studies indicate that the adsorption process of the metals ions followed the pseudo second-order model with R² value of 0.9938, 1.00 and 1.00 respectively. Equilibrium studies showed that the adsorption of Ni²⁺, Pb²⁺ and Cu²⁺ ions are well represented by both Langmuir and Freundlich isotherm but the Langmuir model gave a better fit for Pb²⁺ ions with R² value of 0.9950 and Langmuir constant K_L of 4.3383 while Freundlich isotherm model best fit the experimental data of lead(II) and nickel(II) with a R² value of 0.976 and 0.9973 and Freundlich constant K_F value of 4.2677 and 0.0874. The calculated thermodynamics parameters of Ni²⁺, Pb²⁺and Cu²⁺ ions are ( ΔG^o -1182.49,-5479.1 and 613.48 KJ/mol) showed that the adsorption of Ni²⁺ and Pb²⁺are spontaneous while Cu²⁺non-spontaneous. The findings indicate that the leaf of Mangiferaindica could be used for the adsorption of Ni²⁺, Pb²⁺ and Cu²⁺ ions from industrial effluents.

A new parameter was proposed, with the help of which a specific disperse system was characterized. In addition, a regularity was found showing the relationship between the structural characteristics of structural units (particle size distribution, standard deviation, intensity and average diameter). Various highly dispersed systems have been investigated, including polystyrene latex, Sucrose and latex.

The increasing popularity of carbon nanotubes has created a demand for greater scientific understanding of the characteristics of thermal transport in nanostructured materials. However, the effects of impurities, misalignments, and structure factors on the thermal conductivity of carbon nanotube films and fibers are still poorly understood. Carbon nanotube films and fibers were produced, and the parallel thermal conductance technique was employed to determine the thermal conductivity. The effects of carbon nanotube structure, purity, and alignment on the thermal conductivity of carbon films and fibers were investigated to understand the characteristics of thermal transport in the nanostructured material. The importance of bulk density and cross-sectional area was determined experimentally. The results indicated that the prepared carbon nanotube films and fibers are very efficient at conducting heat. The structure, purity, and alignment of carbon nanotubes play a fundamentally important role in determining the heat conduction properties of carbon films and fibers. Single-walled carbon nanotube films and fibers generally have high thermal conductivity. The presence of non-carbonaceous impurities degrades the thermal performance due to the low degree of bundle contact. The thermal conductivity may present power law dependence with temperature. The specific thermal conductivity decreases with increasing bulk density. At room temperature, a maximum specific thermal conductivity is obtained but Umklapp scattering occurs. The specific thermal conductivity of carbon nanotube fibers is significantly higher than that of carbon nanotube films due to the increased degree of bundle alignment.

The evolution of supply chains (SC) from a linear to a network structure created an opportunity for new processes, product/service offerings, and provider-business. Rising customer service expectations have led to the need for innovative SC designs to develop and sustain competitive performance globally. Firms are forced to respond and adapt accordingly, thereby leading to design, network, operational, and performance dynamics. Traditionally, SCs are treated as static structures, focusing solely on design and/or operational optimization. Such perspectives are not viable options for SC domains, as they address only a portion of the dynamic problem space, use a deterministic assumption of dominant design variables, capitalize on past data to predict future decisions, and offer pre-classified forecasting options complemented with a limited comprehension of systemic SC elasticity. Novel self-learning agentic systems are proposed that blend the sciencematics of SC decisions and dynamics. The designs guide firms seeking to build adaptive SCs using operational decision processes. The designs address the agentic nature of SC, embedding computational interaction models of firm SC networks. The designs contrast the stochastic action-taking and thereby the performance outcomes, discovering opportunities for adaptive operational designs of SC tasks. Fine-tuning and meta-learning are new design capabilities that adapt to evolving dynamic environments. Frameworks for behavioral customization and systematic exploration of the design space are provided as user guides. Exemplar designs are also provided to serve as a translation template for users to express operational models of their own contexts. To account for the dynamics of supply chains (SC), agent-based models are increasingly adopted. Such models exhibit SC structure and/or formulation dynamics. Though existing efforts commence adjacent-only structural changes, dynamism with respect to tasks is crucial for SC design and operational strategy development. Proposed is a process modeling library and workflow for discovering intricate designs of adaptive agentic systems. The library revises Dataflow and Structure, concealing sequencing and context designs of processes. Prompted specifications describe and enact designs. Applications in SC formulation discovery are provided.

Technological advances have had a transformative impact on the retail landscape. Challenges arise with guaranteeing technological changes lead to, rather than detract from, increased efficiency and positive experiences. First, integrating technology into the supply chain in an aggressive way is costly. It requires vast changes to existing systems and developments of cross-industry communication protocols. Secondly, the public is often quick to reject technological changes or slow to become users. Finally, ensuring that technological advancements do not only benefit the top few retailers and are accessible to those of any size poses a challenge, as has been seen in the fate of only a handful of radical changes in retail technology. On the other hand, an integral aspect of technology, particularly that used for big data collection and processing, is that it can account for these and other variables. It can predict the success of ventures into modernizing or developing new systems and can identify more effective and efficient ways to do so. Of course, the concerns of job loss or technological monopoly still loom. But, it would seem, the continued advancement of technology in the retail landscape is inevitable.