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This paper aims to determine whether application of graphene layers to cuprammonium filaments affords the latter with excellent mechanical properties and improves their electrical properties. At the same time, a circuit model was established to explore the conductive mechanism of the filament. The actual model is used to verify the correctness of the model.

The cuprammonium filaments were desizing, the graphene oxide layer-by-layer sizing and reduction integration process by a continuous sizing machine. The electrical properties of mono- and multifilaments in the static condition, as well as the dynamic–mechanical properties of multifilaments, were analysed, and the related conductive mechanism of the filaments was deduced.

Cuprammonium filaments coated with graphene layers showed good electrical conductivity, and their volume resistance decreased to 4.35 O·cm with increasing number of graphene coats. The X-ray diffraction and thermogravimetric analysis results showed that the graphene layer treatment changed the crystallinity of the copperammonia filaments and improved the thermal stability of the filaments. In the dynamic case, filament resistance was calculated using the equivalent resistance model, and the fitting difference observed was small. This result confirmed the high fit of this circuit model.

Up to the knowledge from literature review, there are no reports on theoretical research on the relation between the electro-mechanical property and structure of conductive filaments.

This paper aims to optimize cable-stayed force in asymmetric one-tower cable-stayed bridge formation using an improved particle swarm algorithm. It compares results with the traditional unconstrained minimum bending energy method.

This paper proposes an improved particle swarm algorithm to optimize cable-stayed force in bridge formation. It formulates a quadratic programming mathematical model considering the sum of bending energies of the main girder and bridge tower as the objective function. Constraints include displacements, stresses, cable-stayed force, and uniformity. The algorithm is applied to optimize the formation of an asymmetrical single-tower cable-stayed bridge, combining it with the finite element method.

The study’s findings reveal significant improvements over the minimum bending energy method. Results show that the structural displacement and internal force are within constraints, the maximum bending moment of the main girder decreases, resulting in smoother linear shape and more even internal force distribution. Additionally, the tower top offset decreases, and the bending moment change at the tower-beam junction is reduced. Moreover, diagonal cable force and cable force increase uniformly with cable length growth.

The improved particle swarm algorithm offers simplicity, effectiveness, and practicality in optimizing bridge-forming cable-staying force. It eliminates the need for arbitrary manual cable adjustments seen in traditional methods and effectively addresses the optimization challenge in asymmetric cable-stayed bridges.

Aiming at obtaining a high-quality global path for a mobile robot which works in complex environments, a modified particle swarm optimization (PSO) algorithm, named random-disturbance self-adaptive particle swarm optimization (RDSAPSO), is proposed in this paper.

A perturbed global updating mechanism is introduced to the global best position to avoid stagnation in RDSAPSO. Moreover, a new self-adaptive strategy is proposed to fine-tune the three control parameters in RDSAPSO to dynamically adjust the exploration and exploitation capabilities of RDSAPSO. Because the convergence of PSO is paramount and influences the quality of the generated path, this paper also analytically investigates the convergence of RDSAPSO and provides a convergence-guaranteed parameter selection principle for RDSAPSO. Finally, a RDSAPSO-based global path planning (GPP) method is developed, in which the feasibility-based rule is applied to handle the constraint of the problem.

In an attempt to validate the proposed method, it is compared against six state-of-the-art evolutionary methods under three different numerical simulations. The simulation results confirm that the proposed method is highly competitive in terms of the path optimality. Moreover, the computation time of the proposed method is comparable with those of the other compared methods.

Therefore, the proposed method can be considered as a vital alternative in the field of GPP.

This paper aims to study the anodization of aluminum in a mixture solution of 1,3-propanediol solutions and 0.4 mol l⁻¹ H₃PO₄ at a low temperature.

The morphology and composition of the resulting anodic aluminum oxide (AAO) template was characterized by means of a scanning electron microscope in combination with an energy dispersive spectrometer.

Pore density and pore diameter both were found to be dependent on the temperature of anodization.

The resulting AAO templates exhibited uniform and regular pores with diameters that were significantly smaller than those found in AAO templates anodized at room temperature.

The purpose of this paper is to establish the key predictors of Master of Business Administration (MBA) students' performance, considering the interaction between personality type, learning approaches and educational achievement. A structural equation model is formulated to check out the relationship perfection between the construct variables.

The study subjects were 208 MBA students at Zhejiang University. A questionnaire encompassing three sections was presented to the respondents. The first section is the revised two‐factor version of the study process questionnaire (R‐SPQ‐2F) developed by Biggs et al. The second section consists of 20 items developed based on a review of the International Personality Item Pool (IPIP) Five‐Factor Personality Inventory (Buchanan, 2001). The third section is about the respondents' background and personal information such as age, gender and their performance represented by their scores in the National Admission Examination System and their major course grade achieved during the first term of their academic year. A structural equation model was designed to examine the relationship between the study variables. Then covariance structural analyses of collected data were conducted for testing the model.

The main findings are significant correlations between the three personality traits, namely, extraversion, conscientiousness and openness to experience with the deep approach (DA) to learning predicting high MBA students' performance.

Personality type and students' approaches to learning constitute determinant factors impacting upon the education of management graduate students. Thus, institutions providing MBA programs must allocate more interest to examine their students' characteristics, in correlation with their performance rating. In this regard, the present study is designed to provide business education stakeholders with a modest model to depict the key predictors of MBA students' performance, particularly, part‐time MBA program whose participants are, in most cases, fully employed students, struggling to cope with their professional, educational and social duties.

This study empirically investigates the relationship between personality type and students' approaches to learning to find out their influence on MBA students' performance. The model results evidently demonstrate, on the one hand a significant correlation between these factors, and on the other hand their influence on the participants' performance reflecting high rating in pertinence with personality traits of extraversion, conscientiousness and openness to experience and the DA to learning.

Selective jet electrodeposition (SJED) is an emerging additive manufacturing (AM) technology for realizing metallic components of nano and micro sizes. The deposited parts on the substrate form metallurgical bonding, so separating them from the substrate is an unsolved issue. Therefore, this paper aims to propose a method for separating the deposited micro parts from a sacrificial substrate. Furthermore, single and multi-bead optimization is performed to fabricate microparts with varying density.

A typical SJED process consists of a nozzle (to establish a column of electrolytes) retrofitted on a machine tool (to provide relative motion between substrate and nozzle) that deposits material atom-by-atom on a conductive substrate.

A comprehensive study of process parameters affecting the layer height, layer width and morphology of the deposited micro-parts has been provided. The uniformity in the deposited parts can be achieved with the help of low applied voltage and high scanning speed. Multi-bead analysis for the flat surface condition is experimentally performed, and the flat surface condition is achieved when the centre distance between two adjacent beads is kept at half of the width of a single bead.

Although several literatures have demonstrated that the SJED process can be used for the fabrication of parts; however, part fabrication through multi-bead optimization is limited. Moreover, the removal of the fabricated part from the substrate is the novelty of the current work.