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Using a reversible addition fragmentation chain transfer reaction, a series of resins were prepared by using N, N-diethyl acrylamide (DEA), poly (ß-hydroxyethyl methacrylate) (PHEMA) as hydrophilic blocks and poly (glycidyl methacrylate) (PGMA) as hydrophobic blocks (and as a target for immobilizing penicillin G acylase [PGA]) and the low critical solution temperature (LCST) of which could be adjusted by changing the segment length of blocks.

To make the catalytic conversion temperature of immobilized PGA fallen into the temperature range of the sol state of thermosensitive block resin, a type of thermosensitive block resin, i.e. PDEA-b-PHEMA-b-PGMA (DHGs) was synthesized to immobilize PGA, and the effect of segment order of block resin was investigated on the performance of PGA.

Carrier prepared with monomers molar ratio of n(DEA) : n(HEMA): n(GMA) = 100: 49: 36 presented loading capacity (L) and enzyme activity recovery ratio (Ar) of 110 mg/g and 90%, respectively, and a block resin with LCST value of 33 °C was essential for keeping higher Ar of PGA.

PGA has become an important biocatalyst in modern chemistry industry. However, disadvantages include difficulty in separation, poor repeatability and high cost, which limits the scope of PGA applications. The effective method is to immobilize the enzyme to the carrier, which could overcome the disadvantage of free enzyme.

This paper aims to focus on the spatial docking task of unmanned vehicles under ground conditions. The docking task of military unmanned vehicle application scenarios has strict requirements. Therefore, how to design a docking robot mechanism to achieve accurate docking between vehicles has become a challenge.

In this paper, first, the docking mechanism system is described, and the inverse kinematics model of the docking robot based on Stewart is established. Second, the genetic algorithm-based optimization method for multiobjective parameters of parallel mechanisms including workspace volume and mechanism flexibility is proposed to solve the problem of multiparameter optimization of parallel mechanism and realize the docking of unmanned vehicle space flexibility. The optimization results verify that the structural parameters meet the design requirements. Besides, the static and dynamic finite element analysis are carried out to verify the structural strength and dynamic performance of the docking robot according to the stiffness, strength, dead load and dynamic performance of the docking robot. Finally, taking the docking robot as the experimental platform, experiments are carried out under different working conditions, and the experimental results verify that the docking robot can achieve accurate docking tasks.

Experiments on the docking robot that the proposed design and optimization method has a good effect on structural strength and control accuracy. The experimental results verify that the docking robot mechanism can achieve accurate docking tasks, which is expected to provide technical guidance and reference for unmanned vehicles docking technology.

This research can provide technical guidance and reference for spatial docking task of unmanned vehicles under the ground conditions. It can also provide ideas for space docking missions, such as space simulator docking.

This study investigates the effectiveness of problem-based learning (PBL) in information literacy curricula using library e-resources to enhance information literacy self-efficacy (ILSE) of students in two universities in Indonesia, in Java Island (University A) and Sumatra Island (University B).

A comparison of the effectiveness of the approach in the two universities forms the focus of the study, which has adopted a single group quasi-experimental design which was conducted in one online teaching-learning session. The authors compared the pre-test and post-test scores of 65 library and information science (LIS) students from both universities.

The results show that the treatment enhanced ILSE effectively. After the treatment, University A students performed better than those at University B.

The factors which affected the success of PBL using library e-resources have not been identified in this study, a task for a future qualitative research study.

This study will both inspire the use of library e-resources in learning activities and promote ILSE.

Integrating PBL with library e-resources provides opportunity to identify the advantages of library e-resources in supporting student ILSE, resulting a better learning achievement.

This study aims to examine the effect intellectual capital (IC) has on firm performance of Australian companies.

Quantitative data are collected for Australian companies listed between 2004 and 2008. IC is measured using Pulic's value added intellectual coefficient (VAIC) and its components (human, structural and capital employed efficiencies (HCE, SCE, CEE)). Direct and moderating relationships between VAIC, HCE, SCE, and CEE and four measures of performance are statistically analysed.

The results suggest that there is a direct relationship between VAIC and performance of Australian publicly listed firms, particularly with CEE and to a lesser extent with HCE. A positive relationship between HCE and SCE in the prior year and performance in the current year is also found. However evidence also suggests the possibility of an alternative moderating relationship between the IC components of HCE and SCE with physical and financial capital (CEE) which impacts on firm performance.

There are some missing data and some transgression of the assumptions of OLS regression.

This paper presents the first study of the IC relationship with firm performance in Australia. Inconclusive results from prior studies in developing countries suggested the need for a study from a developed country such as Australia. The paper is also the first to investigate whether IC moderates the relationship between CEE and firm performance.

Many European businesses are small and medium enterprises (SMEs), contributing significantly to the well-being of local economies and regions. Even so, SMEs face many challenges in fostering innovation and improving performance. Furthermore, the raw material consumption is increasing globally, necessitating the development of strategies that will reduce the number of raw materials extracted and imported while improving the sustainability of small and medium-sized businesses. Consequently, promoting circular economy (CE) strategies, such as industrial symbiosis (IS) partnerships, whereby waste products from other industries serve as a source of raw materials for companies, is critical. Identifying and analysing enablers or drivers that support IS collaborations among SMEs is necessary to achieve this goal. In this regard, the purpose of this study will explore the enablers of IS among SMEs considering sustainability dimensions (environmental, social and economic). As facing a decision-making (DM) problem, the multiple attribute decision-making (MADM) approach was applied in a hesitant fuzzy (HF) environment in this research to answer the research questions. In this regard, in phase 1, IS enablers were identified and extracted using a literature review and experts’ opinions. In phase 2, the hesitant fuzzy Delphi (HFD) method was implemented to screen and finalise the enablers identified. In phase 3, casual relations among final enablers were determined using the hesitant fuzzy ANP (HF-ANP) method. Finally, in phase 4, the relative importance of enablers was calculated using the hesitant fuzzy best–worst method (HF-BWM). Consequently, this study provided potential strategies for IS that can be implemented quickly and used by local authorities to support SMEs in achieving circular waste management.

This chapter explores the significance of blockchain technology in protecting data for intelligent applications across various industries. Blockchain is a distributed ledger that ensures the immutability and security of transactions. Given the increasing need for security measures in industries, understanding blockchain technology is crucial for preparing for its future applications.

This chapter aims to examine the use of blockchain technology across industries and presents a compilation of existing and upcoming blockchain technologies for intelligent applications. The methodology involves reviewing research to understand the security needs of different industries and providing an overview of methods used to enhance multi-institutional and multidisciplinary research in areas like the financial system, smart grid, and transportation system.

The findings highlight the benefits of blockchain networks in providing transparency, trust, and security for industries. The Responsible Sourcing Blockchain Network (RSBN) is an example that utilizes blockchain's decentralized ledger to track sustainable sourcing from mine to final product. This information can be shared with auditors, corporate governance organizations, and customers.

The practical implications of this chapter are significant, serving as a valuable resource for industries concerned with identity privacy, traceability, immutability, transparency, auditability, and security. Understanding and implementing blockchain technology can address the growing need for secure and intelligent applications, ensuring data protection and enhancing trust in various sectors.