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Sustainable/Green building materials (SBMs/GBMs) offer a wide range of benefits which cut across the economic, social and environmental dimensions of sustainability. The incorporation of these materials in construction projects in most developing countries is still low owing to some factors. This study assessed the major barriers to the incorporation of SBMs in the delivery of construction projects in developing countries, with Nigeria as a case in point.

The well-structured quantitative questionnaire was used to gather data from the key players in the construction industry, using the snowball sampling method and electronic means of questionnaire administration. Frequencies, percentile, relative importance index, Kruskal–Wallis H test, Kendall's coefficient of concordance and exploratory factor analysis were used to analyse the gathered data.

The study revealed that the major constructs of barriers to SBM adoption in construction projects are: (1) resistance and information barriers (Eigenvalues = 5.237; % of V = 23.806), (2) regulation and funding of R&D (Eigenvalues = 2.741; % of V = 12.457), (3) cost and market barriers (Eigenvalues = 2.223; % of V = 10.105), (4) government incentive and suppliers' availability (Eigenvalues = 1.728; % of V = 7.852) and (5) GB experts and labour barriers (Eigenvalues = 1.307; % of V = 5.942).

This study assessed the view of construction experts in the five states of the south-eastern geo-political zone of Nigeria, particularly as regards the barriers to the incorporation of sustainable building materials in construction projects in the region.

The purpose of this paper is to propose a two-degrees-of-freedom wire-driven 4SPS/U rigid‒flexible parallel trunk joint mechanism based on spring, in order to improve the robot’s athletic ability, load capacity and rigidity, and to ensure the coordination of multi-modal motion.

First, based on the rotation transformation matrix and closed-loop constraint equation of the parallel trunk joint mechanism, the mathematical model of its inverse position solution is constructed. Then, the Jacobian matrix of velocity and acceleration is derived by time derivative method. On this basis, the stiffness matrix of the parallel trunk joint mechanism is derived on the basis of the principle of virtual work and combined with the deformation effect of the rope driving pair and the spring elastic restraint pair. Then, the eigenvalue distribution of the stiffness matrix and the global stiffness performance index are used as the stiffness evaluation index of the mechanism. In addition, the performance index of athletic dexterity is analyzed. Finally, the distribution map of kinematic dexterity and stiffness is drawn in the workspace by numerical simulation, and the influence of the introduced spring on the stiffness distribution of the parallel trunk joint mechanism is compared and analyzed. It is concluded that the stiffness in the specific direction of the parallel trunk joint mechanism can be improved, and the stiffness distribution can be improved by adjusting the spring elastic structure parameters of the rope-driven branch chain.

Studies have shown that the wire-driven 4SPS/U rigid‒flexible parallel trunk joint mechanism based on spring has a great kinematic dexterity, load-carrying capacity and stiffness performance.

The soft-mixed structure is not mature, and there are few new materials for the soft-mixed mixture; the rope and the rigid structure are driven together with a large amount of friction and hindrance factors, etc.

It ensures that the multi-motion mode hexapod mobile robot can meet the requirement of sufficient different stiffness for different motion postures through the parallel trunk joint mechanism, and it ensures that the multi-motion mode hexapod mobile robot in multi-motion mode can meet the performance requirement of global stiffness change at different pose points of different motion postures through the parallel trunk joint mechanism.

The trunk structure is a very critical mechanism for animals. Animals in the movement to achieve smooth climbing, overturning and other different postures, such as centipede, starfish, giant salamander and other multi-legged animals, not only rely on the unique leg mechanism, but also must have a unique trunk joint mechanism. Based on the cooperation of these two mechanisms, the animal can achieve a stable, flexible and flexible variety of motion characteristics. Therefore, the trunk joint mechanism has an important significance for the coordinated movement of the whole body of the multi-sport mode mobile robot (Huang Hu-lin, 2016).

In this paper, based on the idea of combining rigid parallel mechanism with wire-driven mechanism, a trunk mechanism is designed, which is composed of four spring-based wire-driven 4SPS/U rigid‒flexible parallel trunk joint mechanism in series. Its spring-based wire-driven 4SPS/U rigid‒flexible parallel trunk joint mechanism can make the multi-motion mode mobile robot have better load capacity, mobility and stiffness performance (Qi-zhi et al., 2018; Cong-hao et al., 2018), thus improving the environmental adaptability and reliability of the multi-motion mode mobile robot.

The purpose of this paper is to make a correlation analysis between students’ online learning behavior features and course grade, and to attempt to build some effective prediction model based on limited data.

The prediction label in this paper is the course grade of students, and the eigenvalues available are student age, student gender, connection time, hits count and days of access. The machine learning model used in this paper is the classical three-layer feedforward neural networks, and the scaled conjugate gradient algorithm is adopted. Pearson correlation analysis method is used to find the relationships between course grade and the student eigenvalues.

Days of access has the highest correlation with course grade, followed by hits count, and connection time is less relevant to students’ course grade. Student age and gender have the lowest correlation with course grade. Binary classification models have much higher prediction accuracy than multi-class classification models. Data normalization and data discretization can effectively improve the prediction accuracy of machine learning models, such as ANN model in this paper.

This paper may help teachers to find some clue to identify students with learning difficulties in advance and give timely help through the online learning behavior data. It shows that acceptable prediction models based on machine learning can be built using a small and limited data set. However, introducing external data into machine learning models to improve its prediction accuracy is still a valuable and hard issue.

This paper reports a new technique for achieving optimized design for power system stabilizers. In any large scale interconnected systems, disturbances of small magnitudes are very common and low frequency oscillations pose a major problem. Hence small signal stability analysis is very important for analyzing system stability and performance. Power System Stabilizers (PSS) are used in these large interconnected systems for damping out low-frequency oscillations by providing auxiliary control signals to the generator excitation input. In this paper, collective decision optimization (CDO) algorithm, a meta-heuristic approach based on the decision making approach of human beings, has been applied for the optimal design of PSS. PSS parameters are tuned for the objective function, involving eigenvalues and damping ratios of the lightly damped electromechanical modes over a wide range of operating conditions. Also, optimal locations for PSS placement have been derived. Comparative study of the results obtained using CDO with those of grey wolf optimizer (GWO), differential Evolution (DE), Whale Optimization Algorithm (WOA) and crow search algorithm (CSA) methods, established the robustness of the algorithm in designing PSS under different operating conditions.

This paper aims to develop indicators of happiness in learning of the Thai open university (TOU)'s undergraduate students.

Sampling for the study was comprised of two groups. Group I comprised eight lecturers who are experts in their disciplines and six students who were purposively sampled. The focus group was used to validate the appropriateness of the indicators. In Group II, 332 students were engaged in a multistage sampling process. The responses were analyzed using descriptive statistics, coefficient correlation, exploratory factor analysis (EFA) and confirmatory factor analysis (CFA).

The indicators of happiness in learning of undergraduate students of TOU were classified in six categories. These included satisfaction with learning environment (five indicators), learning anxiety (five indicators), satisfaction with learning (five indicators), enthusiasm to learn (six indicators), self-satisfaction (six indicators) and readiness to learn (seven indicators). The six categories explained happiness in learning of undergraduate students of TOU at the 65% and fit empirical data.

The TOU can use the indicators for the assessment of happiness in learning of its students as well as guidelines for the improvement of its student learning environments.

There have been very few studies on indicators of happiness in learning of TOU students. Most were done at the basic education level. This study disclosed the six factors affecting happiness in learning of TOU students; therefore, it should inspire and draw attention of many in the field of higher education distance learning.

Unlike conventional aircraft, birds can glide without a vertical tail. The purpose of this paper is to analyse the influence of dihedral angle spanwise distribution on lateral-directional dynamic stability by the simulation, calculation in the development of the bird-inspired aircraft and the flight testing.

The gliding magnificent frigatebird (Fregata magnificens) was selected as the study object. The geometric and mass model of the study object were developed. Stability derivatives and moments of inertia were obtained. The lateral-directional stability was assessed under different spanwise distributions of dihedral angle. A bird-inspired aircraft was developed, and a flight test was carried out to verify the analysed results.

The results show that spanwise distribution changing of dihedral angle has influence on the lateral-directional mode stability. All of the analysed configurations have convergent Dutch roll mode and rolling mode. The key role of dihedral angle changing is to achieve a convergent spiral mode. Flight test results show that the bird-inspired aircraft has a well-convergent Dutch roll mode.

The theory that birds can achieve its lateral-directional stability by changing its dihedral angle spanwise distribution may explain the stability mechanism of gliding birds.

This paper helps to improve the understanding of bird gliding stability mechanism and provides bio-inspired solutions in aircraft designing.

A handful of models and measures currently exist for the purpose of assessing student capacity for leading social change. Ample research suggests that students of different racial and gender identity groups exhibit various understandings, motivations, and behaviors related to social engagement and transformation, yet few studies take into consideration the potential for diverse students to interpret social-change-related survey scale items differently. Using a critical quantitative approach, this study compares factor loading patterns of the Social Issues Advocacy Scale (SIAS; Nilsson, et al., 2011) across eight race/gender subgroups to test the extent to which the factor structure remains invariant. Findings suggest that intersections of race and gender do influence how scale items cluster together. This study lends support for critical quantitative research designs that examine social phenomena using a specific-group approach, and calls for scholars to consider the cultural validity of scales used to measure capacity for social justice leadership.

The study aims is to explore the cointegration level among major Asian stock indices from pre- COVID-19 to post COVID-19 times.

Johansen cointegration test is employed to know the long run relationship among the stock market indices of Hong Kong, Indonesia, Malaysia, Korea, India, Japan, China, Taiwan, Israel and South Korea. The empirical testing was done to analyze whether any significant change has been induced by the COVID-19 pandemic on the cointegrating relationship of the selected markets or not. Through statistics of trace test and maximum eigen value, total number of cointegrating equations present among all the indices during different study periods were analyzed.

The presence of cointegration was found during all the sample periods and the findings suggests that the selected stock markets are associated with each other in general. During COVID-19 crisis period the cointegration level was reduced and again it regained its original level in the next year and again reduced in the subsequent next year. So, the cointegrating relationship among selected stock market indices remains dynamic and no evidence of impact of COVID-19 on this dynamism was found.

The study has explored the level of cointegration among the major stock indices of Asian nations in the pre, during, post-crisis and the most recent periods. The interconnectedness of the stock markets during the COVID-19 times has been compared with similar periods in different years immediately preceding and succeeding the COVID-19 times which has not been done in any of the existing study.

The purpose of this paper is the study of existence and multiplicity of solutions for a nonlinear discrete boundary value problems involving the p-laplacian.

The approach is based on variational methods and critical point theory.

Theorem 1.1. Theorem 1.2. Theorem 1.3. Theorem 1.4.

The paper is original and the authors think the results are new.

This paper presents a quantitative measurement instrument for Leadership Adaptability.

Qualitative themes are examined, grouped and developed into 13 quantitative statements of Leadership Adaptability. A robust analysis is conducted to understand the relationships and underlying dimensions in the statements. Three types of dimension reduction techniques are employed: principal components analysis and two types of exploratory factor analysis. The instrument is tested in the form of a survey for the first time with public and private school leaders in the Emirate of Abu Dhabi (n = 167).

The quantitative Leadership Adaptability scale is validated by applying robust tests of dimensionality, validity and reliability. The three dimension reduction tests identified that the 13 statements are measuring a single dimension of Leadership Adaptability, and should therefore be treated as a single homogeneous scale. Reliability analyses further confirmed the results of the dimension reduction results, with a high score for Cronbach's alpha of 0.953, classified as an “excellent” level of reliability. Discriminant validity tests of the 13 statements, analysed alongside the 20-item Cultural Intelligence Scale, further confirmed the statements as being a distinct scale. Applying the instrument to Abu Dhabi school leaders showed they have high levels of adaptability.

This paper presents the first known quantitative measurement instrument for understanding Leadership Adaptability. This instrument addresses a need by developing a quantitative tool for researchers studying Leadership Adaptability, and it can be used to facilitate further exploration of this topic.