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Fresh out of the two-century-old British legacy, Bangladesh, formerly known as East Pakistan from 1947 to 1971, was searching for a post-colonial architectural style. Colonial architecture in the region in general often imposed imported European elements, ignoring the preceding legacies of the Sultanate and the Mughals. The critical challenge was to find a balance between the prevailing high modernism in architecture and the local vernacular and climatic forces. The Pakistani government invited international architects to fill the gap left by a non-existent local architectural industry. Unfortunately, their work has rarely been properly analyzed. With selected case studies, this paper analyzes their work in an attempt to explore their contribution to creating a national architectural identity.

This study uses a case study approach with selected architectural projects from the period. It uses research tools such as systematic analysis of drawings, volumes and photographs and archival research.

The international architects took inspiration from the strong vernacular and climatic forces of the region. The resultant expressions of the two-decade-long search in their combined body of work are some of the finest examples of vernacular and climate-responsive architecture in the region. They transcended the regular international style and became context-specific and unique. The quest for East Pakistan's post-colonial architectural identity was partially met by the newly found identity through vernacular and climate-responsive adaptation in architecture.

This study explores how a unified vernacular and climate-responsive adaptations potentially shaped the post-colonial architectural identity of the region. No prior study exists on this issue for the time period.

The objective of this study is to investigate the concept of “earthquake resistance” in high-rise buildings and assess the current level of structural strength in the areas where these structures are situated. The study aims to identify and implement necessary measures to enhance resilience in these areas. A comprehensive literature review was conducted to develop a conceptual framework focusing on earthquake resistance's meanings, stages and physical elements to achieve these goals.

This study focuses on Istanbul, a city known for its high earthquake risk, specifically targeting the Atasehir district. The research utilizes the DEMATEL (Decision-Making Trial and Evaluation Laboratory) method to evaluate urban resilience parameters. Additionally, the Fuzzy TOPSIS (Preference Ranking Technique by Similarity) method is employed to analyze the location of five buildings in Atasehir, using criterion weights derived from this methodology.

The findings indicate that resilience varies depending on the distance of the buffers. Moreover, the amount and quality of urban equipment in the study areas have a significant impact on the earthquake resistance level of the surrounding areas where high-rise buildings are situated. Building upon this analysis, the study suggests the implementation of measures aimed at augmenting the quantity and quality of urban facilities in the study areas, consequently enhancing urban resilience.

The originality and value of this study lie in its examination of seismic resilience within the context of high-rise buildings and the identification of necessary measures to increase resilience in areas where these structures are prevalent. By focusing on Istanbul, a city with a high earthquake risk, and specifically selecting the Atasehir district as the study area, this research provides a comprehensive conceptual framework for understanding urban resilience and its physical components. Moreover, the study offers a fresh perspective on urban resilience by highlighting the influence of tall buildings on the surrounding areas. Ultimately, it provides practical recommendations for architects, urban planners and other stakeholders to improve regional earthquake resilience.

In socio-technical transition theory, resistance by existing technology and regime resistance plays a key role. The resistance is in the form of intentional improvements; eventually, the regime destabilizes and adopts the new technology, referred to as the sailing-ship effect. Researchers used a structural view and examined it as a strategic action and its relationship with new technology (competitive/symbiotic) in non-fast-changing sailing systems. This study uses a microlevel view and examines it in a fast-changing where products/services are developed by integrating existing technology with new product innovations; their success depends on addressing technical/market uncertainty. This study examines the sailing-ship effect in a fast-changing system and contributes to the socio-technical transition theory.

The authors need to examine the phenomena of the sailing-ship effect in its setting, and a case-study method is appropriate. The selected case provided diverse analytic and heuristic perspectives to examine the phenomena; therefore, it was a single case study.

In an IT scenario, the strategic actions decide and realize agility and competitive advantage by formulating appropriate goals with required budgets and coevolutionary changes to resources at product, process and organizational levels, addressing technical/market uncertainty. Moreover, the agility displayed by strategic actions determines the relationship with new technology, which is interspersed. Finally, it provided insights into struggle, navigation and negotiations, forming strategic actions to display the sailing-ship effect.

The study selected a Banking Financial Services and Insurance product of an IT Services company. As start-ups exhibit inherent (emergent) agility, the authors can examine agility as a combination of emergent and strategic actions by selecting a start-up.

The study highlights the strategic actions specific to an IT services company. It developed its product and services by steering clear from IT innovations such as native cloud and continuous deployment. It improved its products/services with necessary organizational changes and achieved the desired agility and competitive advantage. Therefore, organizations devise appropriate strategic actions to combat the sailing-ship effect apart from setting goals and selecting IT innovations.

The study expands the socio-technical transition theory by selecting a fast-changing system. It provided insights into the relationship between existing and new technology and the strategic actions necessary to manage technical and market uncertainty and achieve the desired competitive advantage, or the sailing-ship effect.

The rise of emerging economies in the innovation landscape has often been attributed to the positive spillovers of innovation capabilities from multinational corporations (MNCs). However, it is less certain that their innovative capabilities imported from the home country function effectively in the host country from the outset. This study examines the performance of the innovation capabilities of MNC subsidiaries in emerging economies over time by considering the gradual process of their learning about host countries.

We employed stochastic frontier analysis to measure innovation capabilities, our focal construct. For regression analysis, we applied the Mundlak estimator, a variant of the fixed-effects panel estimator, to a sample comprising subsidiaries of MNCs from technologically advanced nations operating in Korea between 2006 and 2016.

Our results indicate that the innovation capabilities of MNC subsidiaries initially underperform those of local firms but improve over time, eventually surpassing the capabilities of their local counterparts. Furthermore, our findings reveal that institutional distance amplifies the underperformance of the innovation capabilities of MNC subsidiaries.

This study contributes to the literature by extending both theoretical development and empirical measurement of innovation capabilities in cross-national settings. Additionally, it deepens our understanding of whether and how MNC subsidiaries adapt their innovation capabilities to the local market environment.

This study aims to develop a polymer cement-based waterproof coating with self-healing capability to efficiently and intelligently solve the building leakage caused by cracking of waterproof materials, along with excellent durability to prolong its service life.

Ion chelators are introduced into the composite system based on ethylene vinyl acetate copolymer emulsion and ordinary Portland cement to prepare self-healing polymer cement-based waterproof coating. Hydration, microstructure, wettability, mechanical properties, durability, self-healing performance and self-healing products of polymer cement-based waterproof coating with ion chelator are investigated systematically. Meanwhile, the chemical composition of self-healing products in the crack was examined.

The results showed that ion chelators could motivate the hydration of C₂S and C₃S, as well as the formation of hydration products (C-S-H gel) of the waterproof coating to improve its compactness. Compared with the control group, the waterproof coating with ion chelator had more excellent water resistance, alkali resistance, thermal and UV aging resistance. When the dosage of ion chelator was 2%, after 28 days of curing, cracks with a width of 0.29 mm in waterproof coating could fully heal and cracks with a width of 0.50 mm could achieve a self-healing efficiency of 72%. Furthermore, the results reveal that the self-healing product in the crack was calcite crystalline CaCO₃.

A novel ion chelator was introduced into the composite coating system to endow it with excellent self-healing ability to prolong its service life. It has huge application potential in the field of building waterproofing.

The author’s interest in vernacular architecture, over the years, has attracted the author’s attention to three distinctive and similar forms of architecture in faraway regions of the globe. These are; Asir region of Saudi Arabia, The Caucasus including the republic of Georgia, Chechenia, and North Ossetia, and Sichuan region in China. Stone towers dominate the landscape of these remote regions. The similarity of these towers in these far away regions is quite remarkable.

This paper will introduce these towers in their geographic, social and natural context. Although several studies have been done on these regions, it is the aim of this paper to introduce their architecture in a comparative approach to explore how these remotes corners of the globe with different historical, ethnic and cultural backgrounds developed similar architectural forms in total isolation from each other.

Architecture is a physical production of different and diverse factors. Geographically, isolated regions with similar natural and social factors, mountainous landscape, tribally-based, agrarian societies, produces similar architectural forms.

This paper is a clear testimony to the human nature and how people think, react and build, under similar conditions. Architecture becomes a manifestation of human oneness, unity, believes and behaviour.

Despite the relevance of how enterprise architecture (EA) contributes to organizational performance in contemporary digital technology-driven strategic renewal, little is known about the position of EA artifacts. Therefore, this study aims to build an integrative model of EA artifact-enabled EA value supplemented with a research agenda to enhance our understanding further.

This study leveraged grounded theory techniques and a systematic review approach to develop the integrative model and research agenda.

We inductively build a model of the position of EA artifacts in EA value creation. Additionally, we elaborate a research agenda that proposes (1) an investigation of the role of an EA practice in successful strategic change, (2) an examination of how to manage EA practice value generation and (3) longitudinal research to gain insight into the evolution of value creation by EA practices.

This study presents a model of EA artifact-enabled EA value, thereby contributing to our understanding of the mechanisms, inhibitors and success factors associated with EA value. Following our model, the proposed research agenda contains future research areas to help us better understand the mechanisms and interrelatedness of EA practices in highly dynamic environments.

The residential buildings sector has a high priority in the climate change adaptation process due to significant CO₂ emissions, high energy consumption and negative environmental impacts. The article investigates how, conversely speaking, the residential buildings will be affected by climate change, and how to improve existing structures and support long-term decisions.

The climate dataset was created using the scenarios determined by the Intergovernmental Panel on Climate Change (IPCC), and this was used in the study. Different building envelope and Heating, Ventilating and Air Conditioning (HVAC) systems scenarios have been developed and simulated. Then, the best scenario was determined with comparative results, and recommendations were developed.

The findings reveal that future temperature-increase will significantly impact buildings' cooling and heating energy use. As the outdoor air temperatures increase due to climate change, the heating loads of the buildings decrease, and the cooling loads increase significantly. While the heating energy consumption of the house was calculated at 170.85 kWh/m² in 2020, this value shall decrease significantly to 115.01 kWh/m² in 2080. On the other hand, the cooling energy doubled between 2020 and 2080 and reached 106.95 kWh/m² from 53.14 kWh/m² measured in 2020.

Single-family houses constitute a significant proportion of the building stock. An in-depth analysis of such a building type is necessary to cope with the devastating consequences of climate change. The study developed and scrutinised energy performance improvement scenarios to define the climate change adaptation process' impact and proper procedure. The study is trying to create a strategy to increase the climate resistance capabilities of buildings and fill the gaps in this regard.

Currently, China’s manufacturing industry chain still faces the danger of chain breakage due to the persistent “lack of technology” issue. The definition and detection of key nodes in the industry chain are significant to the enhancement of the stability of the industry chain. Therefore, detecting the key nodes in the manufacturing industry chain is necessary.

A complex network based on the links amongst listed manufacturing enterprises is built, and the authors analyse the network’s basic characteristics and vulnerability, taking into account the impact of scientific and technological innovation on the stability of the industry chain.

It is found that the high structural characteristic of midstream nodes in the naval architecture and marine engineering equipment industry chain determines their importance to stability, and the key status of upstream nodes is reflected in the weakness of technological innovation. The upstream nodes should focus on improving their independent innovation and R&D capability, whilst the midstream nodes should maintain a close supply–demand cooperation relationship.

The key node detection model for industry chain stability is constructed by considering various factors from the perspective of network and technological innovation. Empirical study is conducted to verify effectiveness of proposed method.

As data centres grow in size and complexity, traditional air-cooling methods are becoming less effective and more expensive. Immersion cooling, where servers are submerged in a dielectric fluid, has emerged as a promising alternative. Ensuring reliable operations in data centre applications requires the development of an effective control framework for immersion cooling systems, which necessitates the prediction of server temperature. While deep learning-based temperature prediction models have shown effectiveness, further enhancement is needed to improve their prediction accuracy. This study aims to develop a temperature prediction model using Long Short-Term Memory (LSTM) Networks based on recursive encoder-decoder architecture.

This paper explores the use of deep learning algorithms to predict the temperature of a heater in a two-phase immersion-cooled system using NOVEC 7100. The performance of recursive-long short-term memory-encoder-decoder (R-LSTM-ED), recursive-convolutional neural network-LSTM (R-CNN-LSTM) and R-LSTM approaches are compared using mean absolute error, root mean square error, mean absolute percentage error and coefficient of determination (R²) as performance metrics. The impact of window size, sampling period and noise within training data on the performance of the model is investigated.

The R-LSTM-ED consistently outperforms the R-LSTM model by 6%, 15.8% and 12.5%, and R-CNN-LSTM model by 4%, 11% and 12.3% in all forecast ranges of 10, 30 and 60 s, respectively, averaged across all the workloads considered in the study. The optimum sampling period based on the study is found to be 2 s and the window size to be 60 s. The performance of the model deteriorates significantly as the noise level reaches 10%.

The proposed models are currently trained on data collected from an experimental setup simulating data centre loads. Future research should seek to extend the applicability of the models by incorporating time series data from immersion-cooled servers.

The proposed multivariate-recursive-prediction models are trained and tested by using real Data Centre workload traces applied to the immersion-cooled system developed in the laboratory.