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The UNESCO recommendation under the historic urban landscapes (HUL) title and Operational Guidelines (OPG) were used to create dynamic protective boundaries to maintain the integrity and authenticity of Isfahan's heritage waterways. Accordingly, by using GIS and Isfahan urban layers, three protective zones were proposed and evaluated; the central zone, the functional zone and the visual zone.

Heritage waterways in historic cities are not adequately protected against the negative impacts of urban development, and there is a lack of a dynamic protective system to protect their integrity and authenticity. The problem can be observed in Isfahan, a historic Iranian city, where the boundaries of urban heritage waterways (Madi canals) are usually rigid and arbitrary. This study aims to develop a practicable paradigm for determining protection boundaries for Isfahan's Jolfa Madi, an urban heritage waterway.

Compared to the current protective boundaries, the authors found that proposed protective boundaries create a greater amount of protection space, which makes a strong connection among the ecological, historical and socio-economic characteristics of the urban context. Furthermore, the protective zones based on the HUL approach give Isfahan's urban planning policy the opportunity to consider participatory tools, financial tools and regulatory systems.

Many studies have emphasized a fixed-width buffer or an arbitrary distance from the urban waterway's axis (urban heritage) or its banks. Although these protections include technical conservation or setting restrictions on the adjacent buildings and blocks, studying crucial concepts such as urban dynamic, urban heritage context and producing a particular technique for protected boundaries has not been investigated. In this article three dynamic boundaries are delineated with various functions in order to provide urban heritage with dynamic preservation and sustainable development for the historic urban landscapes.

The purpose of this paper is to study the shearing performance under bi-directional loading of an interior beam–column joint (BCJ) sub-assemblage using the finite element analysis (FEA) tool (midas fea), validated in this research.

The BCJ can be defined as an essential part of the column that transfers the forces at the ends of the members connected to it. The members of the rigid jointed plane frame resist external forces by developing twisting moment, bending moment, axial force and shear force in the frame members. On the type of joints, the response to the action of lateral loads depends on reinforced concrete (RC) framed structures. The joint is considered rigid if the angle between the members remains unchanged during the structural deformation. This work examined the shear deformation, load displacement and strength of a non-seismically detailed internal concentric RC joint using non-linear FEA. The bi-directional loading imposes the oblique compression zone on one joint corner. This joint core’s oblique compression strut mechanism differs significantly from that under unidirectional loading. The numerical results are compared with experimental results in this study, with the data published in the literature.

Numerical analysis results show that, in the comparative study of numerical and experimental values, the FEA tool predicts the behaviour of the RC BCJ well. The discrepancy between the experimental and numerical results amounts to 6 to 12% end displacement of the beam, 7% resultant joint shear force, 4.23% column bar strain and 0.70% hoop strain.

The current code of practice describes the joint sub-assemblage behaviour along the single axis individually. In the non-orthogonal system, the superposition of the two axes for joint space results in overlapping the stresses and, hence, the formation of the oblique strut. This may result in a reduction in the joint capacity under bi-directional loading. The behaviour must be explored in depth, and an attempt is made for further exploration.

In this study, we explored factors driving evidence-based management (EBM) decision-making in Poland which has experienced changes from state-controlled market environments to more competitive ones. Evidence-based management requires the critical use and adaptability to information to deal with complex problems.

In total, 422 Polish managers responded to a telephone survey measuring their perceptions about decision-making culture, styles, competence, and their use of specific sources to derive the evidence to enable them to make evidence-based decisions. Informed by theoretical principles, we used Hayes’ PROCESS macro (Model 4) to examine whether each factor produced direct effects on EBM decision-making and the mediating influence of competence and style in the relationship between culture and perceived evidence-based decision-making.

All three factors correlated positively with perceived evidence-based decision-making. Moreover, style was not predictive of EBM decision-making compared to competence and culture while culture had an imposing effect on decision-making both as a direct effect and indirectly through competence.

This study provides important insights into the perceptual state of EBM among Polish managers. It emphasizes the importance of embracing diverse cultures and improving critical thinking to help managers make more evidence-based decisions during significant changes in the business world.

This project examines digital modeling strategies for existing buildings. In this context, it aims to question assumptions about the need for geometric accuracy and the efficacy of predefined ontologies. As a counterpoint to prevailing digital modeling strategies, this project proposes a digital modeling approach using a project-specific, emergent ontology.

Nishiki Market, in Kyoto, Japan, is studied as a test case. The emergent-ontology modeling process is introduced with an initial minimal set of operations including basic fold and trim operations applicable to surfaces. As the model develops iteratively, new situations are encountered for which existing rules are insufficient. In response, the model maker’s subjective judgment is invoked to introduce new operations, and ontological rules are allowed to expand.

The emergent-ontology approach, when executed on the Nishiki Market test case, enables representation of specific architectural qualities, highlighting semantic distinctions between digitally modeled elements of real-world features. The modeling approach generated project-specific knowledge, informing disciplinary understanding. Ontological emergence enabled semantic relationships to be disclosed and newly constructed.

The project proposes a novel methodology using an emergent ontology for digitally modeling existing buildings. Instead of remaining within the limitations a predefined ontology, the model maker’s subjective decisions shape the model’s ongoing development. This interpretive approach allows project-specific knowledge generation while challenging prevailing assumptions about accuracy and consistency in digital models of existing buildings.

This study aims to prepare an imprinted composite membrane with grafted temperature-sensitive blocks for the efficient adsorption and separation of rhenium(Re) from aqueous solutions.

PVDF resin membrane was used as the substrate, dopamine and chitosan (CS) were used to modify the membrane surface and temperature-sensitive block PDEA was grafted on the membrane surface. Then acrylic acid (AA) and N-methylol acrylamide (N-MAM) were used as the functional monomers, ethyleneglycol dimethacrylate (EGDMA) as the cross-linker and ascorbic acid-hydrogen peroxide (Vc-H₂O₂) as the initiator to obtain the temperature-sensitive ReO4⁻ imprinted composite membranes.

The effect of the preparation process on the performance of CS–Re–TIICM was investigated in detail, and the optimal preparation conditions were as follows: the molar ratios of AA–NH₄ReO₄, N-MAM and EGDMA were 0.13, 0.60 and 1.00, respectively. The optimal temperature and time of the reaction were 40 °C and 24 h. The maximum adsorption capacity of CS–Re–TIICM prepared under optimal conditions was 0.1071 mmol/g, and the separation was 3.90 when MnO4⁻ was used as the interfering ion. The quasi first-order kinetics model and Langmuir model were more suitable to describe the adsorption process.

With the increasing demand for Re, the recovery of Re from Re-containing secondary resources becomes important. This study demonstrated a new material that could be separated and recovered Re in a complex environment, which could effectively alleviate the conflict between the supply and demand of Re.

This contribution provided a new material for the selective separation and purification of ReO4⁻, and the adsorption capacity and separation of CS–Re–TIICM were increased with 1.673 times and 1.219 time compared with other Re adsorbents, respectively. In addition, when it was used for the purification of NH₄ReO₄ crude, the purity was increased from 91.950% to 99.999%.

The study aims to refine the local university’s supply chain management curriculum to meet regional industry demands, thus boosting the local economy.

Mixed-methods action research combined with neural network modeling was employed to align educational offerings with the needs of the local supply chain management industry.

The research indicates that curriculum revisions, informed by industry leaders and modeled through neural networks, can significantly improve the relevance of graduates' skills to the SCM sector.

The study is specific to one region and industry, suggesting a need for broader application to verify the findings.

Adopting the recommended curricular changes can yield a workforce better prepared for the SCM industry, enhancing local business performance and economic health.

The study supports a role for higher education in promoting economic vitality and social welfare through targeted, responsive curriculum development.

This study introduces an innovative approach, integrating neural network analysis with action research, to guide curriculum development in higher education based on industry requirements.

The study examines the relationship between the interaction of indigenous–foreign cultures and public employee performance (PEP) in the Ghanaian public sector due to the perceived unproductive cultures in the public sector.

The study employs a quantitative approach, where cross-sectional survey design is used to collect the data from Ghanaian public employees. The analysis is done using correlation and hierarchical regression techniques.

The results reveal that both indigenous and foreign cultures are pervasive in the Ghanaian public sector, with high power distance and individualism being dominant cultures. Furthermore, while the indigenous cultures have negative significant relationship with PEP, the foreign cultures have positive significant relationship with PEP. The foreign cultures effectively control the relationship between the indigenous cultures and PEP but insignificantly moderate such relationship.

The findings imply that deliberate attempts should be made to encourage the foreign cultures with attractive reward packages to induce workers. This will indirectly control the practice of the inimical cultures and ultimately reduce their negative effect on PEP.

The study contributes significantly to the extant literature by providing empirical evidence of the indigenous–foreign culture fit and PEP from a developing country, Ghana.

Technological tools for knowledge management (KM) actively support and enhance knowledge acquisition and sharing in organizations. However, technology for KM has been understudied, especially in terms of disruptive technologies (DTs). There is a need to identify how DTs, which are becoming increasingly important in industry and society, are applied to KM and their impact. This paper aims to examine the current state of technology and DT adoption in KM.

The analysis involves four steps. First, we examine the current status of DT in academia through a keyword co-occurrence network of literature. Second, we analyze the technological convergence (TC) of KM technology through the cooperative patent classification code co-classification analysis of patents. Third, we explore the main topics of KM technologies using BERTopic, and finally, we explore the introduction of DT into KM technologies and suggest potential TC combinations for the future.

KM technologies can be categorized into four main topics (knowledge acquisition, sharing, searching, and transfer), and DT is most often applied to knowledge transfer and acquisition. The DTs that are attracting attention from academia and industry are artificial intelligence, augmented and virtual reality, and blockchain, which have applications in healthcare, supply chain management, and human resource management.

The findings provide useful insights for organizations to build a technology roadmap for KM. They can also improve the rigid mindset of organization employees toward DT adoption and innovation. By adopting a KM system that leverages DT, organizations will be able to manage and operate efficiently and systematically.

This study aims to investigate how a firm’s sustainable competitive advantage is influenced by the combination of entrepreneurial ecological orientation, digital transformation and dynamic capabilities.

Based on the qualitative comparative analysis method, this study systematically explores the significant key conditions and configuration effects that affect the growth of sustainable competitive advantage. This study uncovers the causal relationship and complex mechanisms underlying the sustainable and unsustainable competitive advantages for new ventures, by examining the grouping effects of the above three factors – entrepreneurial ecological orientation, digital transformation and dynamic capabilities on those advantages.

A single factor fails to constitute a necessary condition for sustainable competitive advantage. Three types of configurations are beneficial to sustainable competitive advantage, namely, flexible and responsive type, dynamically adjusted type and type of opportunity resource integration, whereas four types of configurations lead to the unsustainable competitive advantage of new ventures, namely, type of organizational rigidity, informal entrepreneurial type, information-blocking type and technology-deficient type.

According to this study, adopting an entrepreneurial ecological orientation is a novel strategic move. This study offers an extensive review of three aspects of entrepreneurial ecological orientation, dynamic capacities and digital transformation and their mutually synergistic cascading effects on the sustainable competitive advantage of new ventures. This study investigates how three dimensions interact to achieve sustainable competitive advantage for firms, ultimately contributing to the study of sustainable competitive advantage strategies from an entrepreneurial ecosystem perspective.

Harmonic drives are used widely in aviation, robotics and instrumentation due to their benefits including high transmission ratio, compact structure and zero backlash. One of the common faults of a harmonic drive is the axial movement of the input shaft. In such a case, its input shaft moves in the axial direction relative to the body of the harmonic drive. The purpose of this study is to propose two fault diagnosis methods based on the current signal of the driving servomotor for the axial movement failure in terms of input shafts of harmonic drives.

In the two proposed fault diagnosis methods, the wavelet threshold algorithm is firstly used for filtering noises of the motor current signal. Then, the feature of the denoised current signal is extracted by the empirical mode decomposition (EMD) method and the wavelet packet energy-entropy (WPEE) theory, respectively, obtaining two kinds of feature sets. After a deep learning model based on the deep belief network (DBN) is constructed and trained by using these feature sets, we finally identify the normal harmonic drives and the ones with the axial movement fault.

In contrast to the traditional back propagation (BP) neural network model and support vector machine (SVM) model, the fault diagnosis methods based on the combination of the EMD (as well as the WPEE) and the DBN model can obtain higher accuracy rates of fault diagnosis for axial movement of harmonic drives, which can be greater than or equal to 97% based on the data of the performed experiment.

The authors propose two fault diagnosis methods based on the current signal of the driving servomotor for the axial movement failure in terms of input shafts of harmonic drives, which are verified by the experiment. The presented study may be beneficial for the development of self-diagnosis and self-repair systems of different robots and precision machines using harmonic drives.