Framework For Construction Research Articles

The Potential of Wood Construction Waste Circularity

Wood construction waste circularity presents enormous potential to significantly de-crease total greenhouse gas (GHG) emissions in the European Union (EU). Latvia could become a frontrunner due to its historic relationship with forestry, wood construction practises and unused potential of the innovative application of wood. This research examines what the potential of “circular wood” in Latvia is, how ready the Latvian wood house construction sector is to engage in a circular economy and wood waste circularity and whether the legal framework is ready to support wood waste management in the country. This study presents a combined approach for systematic wood construction product circularity assessment that includes a review of existing EU and Latvian frameworks for construction and demolition waste (CDW) management and wood construction, a general analysis of wood waste recycling systems and technologies, a quantitative data analysis of construction waste management in Latvia and qualitative data analysis of the Latvian wood house construction sector, and interviews with a focus group of Latvian wood industry representatives. The Latvian scope has allowed us to clarify the pattern methodology and impact points to be replicated, tested and measured further on a broader scale, in other countries, or throughout the whole EU. The main findings reveal a potential life cycle assessment (LCA) verifying the circularity of wood and limitations of wood construction waste circularity in Latvia in terms of wood house construction industry readiness and a legal framework as well as overall social prejudices for circular construction. Findings indicate an overall awareness and level of willingness to participate and engage in the circular construction models among Latvians; however, proactiveness and support (legal and financial) is expected from the government and municipalities. The recommendations point towards improvements in wood waste data management, the wood construction sector and the overall impact on sustainable development goals.

Chimpanzees employ context-specific behavioral strategies within fission-fusion societies.

Fission-fusion social systems allow individuals to make flexible choices about where, with whom, and in what contexts to spend their time in response to competing social and ecological pressures. The ability for fission-fusion societies to support individual behavioral strategies that vary across contexts has been suggested, but the potential function of such context-specific social choices remains largely understudied. We adopted the concept of social niche construction to explore possible differences in social complexity at the individual and group level across feeding contexts. Specifically, we examined patterns of co-attendance across two common ecological contexts in wild Central African chimpanzees (Pan troglodytes troglodytes) in the Goualougo Triangle, Republic of Congo. From data compiled over 6years, we used multidimensional social network analysis to study the patterns of co-attendance generated from 436 group scans at Ficus and 4527 visits to termite mounds. These two contexts were chosen, because they are both fixed spatial features across the landscape that serve as well-defined points to compare association patterns. We identified context-specific social niche construction in a fission-fusion chimpanzee society that produce different patterns of relationships and social complexity that are consistent in their expression over many years, and offer functional benefits. While enhancing our understanding of chimpanzee behavioral strategies, culture, and conservation, our investigation also indicates that the social niche construction framework aids in elucidating the evolutionary advantages of fission-fusion sociality by accounting for intra- and interindividual variability, cognition, and choice in newfound ways.

Anticipatory climate policy mix pathways: a framework for ex-ante construction and assessment applied to the road transport sector

ABSTRACT Globally, climate policy implementation is failing to deliver on the ambitions outlined in the Paris Agreement and countries’ Nationally Determined Contributions. We argue that a more strategic and anticipatory approach to policy mix design and implementation can help contribute to realizing these ambitions. Policy mixes need to co-evolve as energy transitions progress, in order to effectively target multiple transition challenges as these change over time. Accordingly, policy assessments need to both consider interactions between instruments and adopt a dynamic perspective, in terms of design logics and evaluative criteria. We highlight the need for a construction and assessment methodology for designing policy mix pathways which explicitly considers durability risks which could weaken support and lead to dismantling, and anticipatory design principles which can help mitigate these risks. Our paper addresses this gap by proposing and illustrating a novel framework for policy instrument mix pathway construction and ex-ante assessment. We identify generalizable durability challenges for effective anticipatory design: dynamic cost effectiveness, the distributive impacts and acceptance of pathways, along with fiscal and governance requirements for effective implementation. We demonstrate the value of the approach by application to the German light-duty vehicle sector transition. We construct and comparatively assess three illustrative pathways promising to deliver the German LDV sector 2030 GHG targets. The pathways differ in logic, and which of three main market dynamics driving a diffusion-stage transition they emphasize: battery electric vehicle (BEV) purchase, vehicle stock usage, and internal combustion engine (ICE) vehicle scrappage. Accordingly, the pathways utilize different instrument combinations, design features and calibrations. We also assess the illustrative pathways and discuss trade-offs. We argue that this approach can help improve climate policy planning and implementation processes, and increase the likelihood attaining ambitious mitigation targets.

Construction and application of standard system for the preservation of pathogenic microorganism resources

Standards are the technical support for economic activities and social development. The construction and standardization of the pathogenic microorganism preservation standard system is an important technical foundation for the high-quality development of preservation work. Establishing a pathogenic microorganism resource standard system is also important to the national biosafety standards. Through the standardization of pathogenic microbial resource preservation, we can ensure the effective management and sustainable utilization of pathogenic microbial resources, promote the transformation of resources, and serve as an important new element of new productivity to assist the innovative development of biosafety science and technology. This article elaborates and analyzes the establishment background, construction framework, standardization process, and application effects of the standard system for preserving pathogenic microbial resources, providing stronger support for further improving the standard system and promoting the standardization of pathogenic microbial resource preservation.

Creating a comprehensive framework for design, construction and management of healthy buildings

While healthy buildings are investigated in academic research, practice, and policy, they often fail to address the needs and gaps due to insufficient knowledge transfer between them. Moreover, there is no general definition of healthy buildings that could act as a reference for different stakeholders of the building sector. Therefore, this paper presents a novel framework for healthy buildings and a definition for compiling existing knowledge and addressing the needs and gaps. The holistic approach of the framework was developed through an extensive literature review and tested with 12 building case studies in the major European climate zones. The framework outlines five different dimensions (improving mental and physical health, designed for human needs, sustainably built and managed, resilient and adaptive, empowering people), including 24 indicators and sub-indicators. The validation of the framework revealed that it is possible to assess different building projects against different indicators under each dimension. However, challenges remain due to issues such as lack of time, cost of data collection, or lack of documentation. The developed framework provides a balanced approach that promotes both individual well-being and broader sustainability goals. It provides necessary guidance to inform practitioners and policy makers as well as other building sector stakeholders to integrate healthy buildings thinking into their project development, assessment, and decision making.

Characterizing pituitary adenomas in clinical notes: Corpus construction and its application in LLMs.

Objective: Faced with the challenges of differential diagnosis caused by the complex clinical manifestations and high pathological heterogeneity of pituitary adenomas, this study aims to construct a high-quality annotated corpus to characterize pituitary adenomas in clinical notes containing rich diagnosis and treatment information. Methods: A dataset from a pituitary adenomas neurosurgery treatment center of a tertiary first-class hospital in China was retrospectively collected. A semi-automatic corpus construction framework was designed. A total of 2000 documents containing 9430 sentences and 524,232 words were annotated, and the text corpus of pituitary adenomas (TCPA) was constructed and analyzed. Its potential application in large language models (LLMs) was explored through fine-tuning and prompting experiments. Results: TCPA had 4782 medical entities and 28,998 tokens, achieving good quality with the inter-annotator agreement value of 0.862-0.986. The LLMs experiments showed that TCPA can be used to automatically identify clinical information from free texts, and introducing instances with clinical characteristics can effectively reduce the need for training data, thereby reducing labor costs. Conclusion: This study characterized pituitary adenomas in clinical notes, and the proposed method were able to serve as references for relevant research in medical natural language scenarios with highly specialized language structure and terminology.

Massive fields in AdS from constructive holography

Collective field theory offers a constructive framework for exploring the AdS/CFT duality. In this article, we focus on constructing rotations within the light-front quantized collective field theory for the full set of spatial coordinates in the dual bulk AdS spacetime. Two intricate aspects require attention: how rotations involving the emergent holographic coordinate are implemented, and how rotations that involve the spatial coordinates participating in the construction of the light-cone coordinates X± are realized. Our construction is in agreement with Metsaev’s construction directly in the gravity theory. Additionally, we derive the eigenfunctions of the AdS mass operator, which dictate the GKPW rule for the emergent higher-dimensional theory.

Research on the Basic Framework and Elements of Landscape System Construction

Research on the Basic Framework and Elements of Landscape System Construction

THEORETICAL BASIS OF THE FORMATION AND DEVELOPMENT OF GREEN BUILDING

Green construction is a key element of Ukraine's sustainable development, as it contributes to reducing the impact on the environment and increasing the energy efficiency of buildings, which is critically important in the face of global climate change and modern challenges. Green construction also supports Ukraine's integration into the international economy through the implementation of environmental standards, which increases the competitiveness of domestic companies. The purpose of the article is to single out the theoretical basis of the formation and development of green construction, as well as to determine the main problems in this field in Ukraine and ways to solve them. The analysis of Ukrainian and foreign studies have showed that the development of green construction in Ukraine has significant potential, especially under the condition of effective implementation of international standards and their adaptation to local realities, which will contribute not only to the preservation of the environment, but also to economic development, improving the quality of life and health population. The theoretical basis of the formation and development of green construction is systematized. The legislative and regulatory framework for green construction aimed at supporting ecologically sustainable development and construction in Ukraine has been analyzed. The main problems faced by green construction on the way to its development in Ukraine (insufficient regulatory framework, high cost of implementing ecological technologies, low level of public awareness and environmental culture, lack of qualified specialists, technical limitations and infrastructure challenges) are identified, and also given possible solutions to these problems. It is noted that for the further development of green construction, it is necessary to implement comprehensive strategies, which include stimulating investments in the green sector, developing and implementing new technologies, raising quality standards, and promoting environmental education. It is emphasized that government support through financial instruments, such as tax incentives and subsidies, can also contribute to increasing the number of green buildings.

Distinct mechanisms and functions of episodic memory.

The concept of episodic memory (EM) faces significant challenges by two claims: EM might not be a distinct memory system, and EM might be an epiphenomenon of a more general capacity for mental time travel (MTT). Nevertheless, the observations leading to these arguments do not preclude the existence of a mechanically and functionally distinct EM system. First, modular systems, like cognition, can have distinct subsystems that may not be distinguishable in the system's final output. EM could be such a subsystem, even though its effects may be difficult to distinguish from those of other subsystems. Second, EM could have a distinct and consistent low-level function, which is used in diverse high-level functions such as MTT. This article introduces the scenario construction framework, proposing that EM crucially rests on memory traces containing the gist of an episodic experience. During retrieval, EM traces trigger the reconstruction of semantic representations, which were active during the remembered episode, and are further enriched with semantic information, to generate a scenario of the past experience. This conceptualization of EM is consistent with studies on the neural basis of EM and resolves the two challenges while retaining the key properties associated with EM. This article is part of the theme issue 'Elements of episodic memory: lessons from 40 years of research'.

Towards an automated framework for numerical prediction of residual stresses and deformations in metal additive manufacturing

Metal additive manufacturing (AM) revolutionizes design with complex structures and customizable material properties. However, high-energy heat source utilized in metal AM creates non-uniform temperature gradients, which usually leads to significant residual stresses and deformations. The present study proposes a line source based semi-analytical thermo-mechanical approach. The accuracy of the proposed line source based model is thoroughly examined by comparing with corresponding experiments in the literature and other numerical models. Besides, an automated framework for fast construction of a thermo-mechanical FE model for the metal AM process is introduced. A numerical tool AM-builder is developed to bridge the gap between AM process parameters and the FE model. The proposed automated framework is followed by utilization of the AM-builder and the line source based model. A purely numerical example is conducted to demonstrate the effectiveness of the proposed automated framework in rapidly constructing AM thermo-mechanical models for various geometries.

BuildAMol: a versatile Python toolkit for fragment-based molecular design

In recent years computational methods for molecular modeling have become a prime focus of computational biology and cheminformatics. Many dedicated systems exist for modeling specific classes of molecules such as proteins or small drug-like ligands. These are often heavily tailored toward the automated generation of molecular structures based on some meta-input by the user and are not intended for expert-driven structure assembly. Dedicated manual or semi-automated assembly software tools exist for a variety of molecule classes but are limited in the scope of structures they can produce. In this work we present BuildAMol, a highly flexible and extendable, general-purpose fragment-based molecular assembly toolkit. Written in Python and featuring a well-documented, user-friendly API, BuildAMol empowers researchers with a framework for detailed manual or semi-automated construction of diverse molecular models. Unlike specialized software, BuildAMol caters to a broad range of applications. We demonstrate its versatility across various use cases, encompassing generating metal complexes or the modeling of dendrimers or integrated into a drug discovery pipeline. By providing a robust foundation for expert-driven model building, BuildAMol holds promise as a valuable tool for the continuous integration and advancement of powerful deep learning techniques.Scientific contributionBuildAMol introduces a cutting-edge framework for molecular modeling that seamlessly blends versatility with user-friendly accessibility. This innovative toolkit integrates modeling, modification, optimization, and visualization functions within a unified API, and facilitates collaboration with other cheminformatics libraries. BuildAMol, with its shallow learning curve, serves as a versatile tool for various molecular applications while also laying the groundwork for the development of specialized software tools, contributing to the progress of molecular research and innovation.

Fine-grained digital twin sharing framework for smart construction through an incentive mechanism

Prefabricated construction is increasingly applied in the construction industry. Recent academic and industrial efforts highlight that Digital Twin as a Service (DTaaS) is an innovative solution to strengthen the advantages of prefabricated construction by enabling continuous monitoring, precise control, and optimized maintenance of each unique module. However, the complexity of digital twins presents significant challenges for both platforms and subcontractors to apply and fully understand this technology. It is, therefore, crucial to develop a well-designed sharing environment where stakeholders volunteer to share their digital twin resources for synergistic benefits. This research proposes an innovative blockchain-based fine-grained digital twin sharing framework, with detailed architecture focused on two key stages of prefabricated construction: on-site construction and logistics involving warehousing and transport. An incentive mechanism is introduced to encourage all the stakeholders engaged in digital twin sharing framework to contribute and share more digital twin resources. Evolutionary and cooperative games explore the effective settings of the incentive policies, aiming to ensure the feasibility and sustainability of the proposed system by motivating users to share digital twins with fine granularity. Mathematical and numerical results demonstrate the optimal subsidy policies with/without budgetary constraints and further highlight the effectiveness of well-crafted incentives. Findings reveal that better performance in terms of profitability and digital twin sharing is achieved under the proposed incentives. Subsidies are primarily allocated to offset costs with a certain budget, whereas the emphasis shifts towards quality improvement under an ample budget. This study lays a solid foundation for digital twin reuse and development.

Kerangka Pengembangan dan Kepemimpinan Budaya Mutu dalam Konstruksi di Indonesia: Tinjauan Studi Literatur

Leadership is an indispensable element in the process of initiating and maintaining the development of a quality culture in a construction organization. Leadership can create an appropriate environment to provide maximum comfort to group members to improve performance and productivity. Strong leadership from top management is essential in developing and maintaining a quality-based culture in an organization that acts as a catalyst for the implementation of Total Quality Management (TQM). This paper aims to discuss the conceptual framework of how leadership can help change the quality culture in an organization. The discussion was carried out using a literature review of the concepts of Quality, Culture and Leadership and Organizational Culture. Analysis of the study was carried out on cultural changes and the role of leadership in developing a quality culture. The results of the study show that organizations need to shift from their current culture to a TQM culture that focuses on quality as the main strategy. Furthermore, thirteen important cultural dimensions can be identified that contribute to the successful implementation of TQM, where most of these dimensions are related to leadership. The proposed Quality Culture Development and Leadership Framework in Construction in Indonesia can be a model for developing a quality culture in construction organizations through effective leadership, so that construction organizations can use it creatively to minimize inconsistencies and conflicts.

Video Art and Collective Memory in Turkey

The aim of this article is to present and study contemporary video practices since the 2000s in Turkey through the representation of time and collective memory. The article features the four video artists who have structured the video art scene in Turkey: Ali Kazma, Halil Altındere, Erkan Özgen and Seza Paker. This research addresses two interconnected issues: firstly, the purpose is to examine how the distinct technical parameters of video production shape a synthesized temporality. This inquiry naturally gives rise to a secondary purpose: in what manner does this constructed temporality facilitate the exploration of memory and historical discourse? The hypothesis is that the video image, both as a technical artifact and a conceptual construct, inherently possesses its unique framework for temporal construction, thereby actively contributing to novel reinterpretations of collective memory and historiography The methodology involves conducting a formal analysis of the video content. This approach focuses on examining the visual elements, composition, use of color, sound, editing techniques, and overall aesthetics of the video to gain deeper insights into its artistic significance and meaning. By employing formal analysis, the aim of this article is to decipher the visual language employed by the video artists and uncover nuanced layers of interpretation.

Optimization of multiple ecological infrastructures across the land–sea interface for coordination management: A case study around Laizhou Bay in China

Ecological infrastructure (EI), providing ecosystem services across the land-sea interface, has been proposed as a key element in sustainable terrestrial-marine ecosystem coordinated governance. Terrestrial and marine ecosystems should be regarded as an integrated unit for guaranteeing coastal ecological security. However, the existing EI construction framework focused on terrestrial ecosystems, and few studies consider the composite characteristics of the terrestrial-marine ecosystem in coastal areas. In the case study of Laizhou Bay, China, this study proposes an optimization method for multiple ecological infrastructures (MEIs) across the land-sea interface. The method is oriented towards achieving trans-regional scale cohesion, enhancing terrestrial-riverine-marine linkages, providing adequate pathways for marine ecological protection, and promoting coordinated conservation of terrestrial and marine ecosystems. The results showed that: (1) The new optimization framework synthetically considering the terrestrial multi-scale EI networks cohesion, hydrological corridors, and marine conservation network is available. (2) The preliminary ecological sources (PESs) are mainly distributed in the eastern mountainous areas, the estuary of the Yellow River, and six marine protected areas. The spatial imbalance of EI resulted in four marine protected areas in the southwest of the Bohai Sea insufficiently connected between sea-to-sea ecological sources. (3) The integrated MEIs includes four newly added ecological sources (two each for land and sea), eight trans-regional ecological corridors, 17 hydrological corridors, and 11 marine ecological corridors. Through optimization, the MEIs avoid fragmentation across multi-scale terrestrial regions, promote river-based connectivity between land and sea, and increase pathways for marine ecological protection, thereby ensuring effective circulation of regional ecological materials. (4) MEIs-conserved priority areas include 12.4 km2 ecological pinch points and 6.39 km2 marine biological protective points. Focusing on these conserved priority areas provides spatial references for the implementation planning of MEIs. Compared with traditional respective ecosystem networks, the MEIs across land-sea interface optimization approach is feasible for terrestrial-marine ecosystem coordinated management.

From EMI to CLIL: negotiating teacher identity

ABSTRACT In English-medium instruction (EMI), students learn content knowledge through their additional language. Despite the implicit English learning goals, EMI content subject teachers have been urged to provide more language support for their students. Such expectations may not be something that EMI teachers were professionally prepared for. It is then worth examining how EMI teachers (re)construct their identity when facing such new expectations. Based on Wenger’s [Wenger, E. (1998). Communities of Practice: Learning, Meaning, and Identity. Cambridge University Press] identity construction framework, this qualitative multiple case study reveals how three EMI teachers in Hong Kong and Mainland China secondary schools negotiated their identity when being supported to incorporate language teaching in their content lessons. From data collected in co-planning meetings, lesson observations and interviews, all the teachers were engaged in constructing the identity of language aware content teachers, but some of them appeared to experience identity conflicts. The contrast of the three cases reveals that teachers’ professional training, school context and curriculum requirement are important in shaping teachers’ professional identity. Teachers’ agency also impacts on how teachers negotiate their identity, especially when facing contextual constraints. These findings underscore the importance of preparing teachers both psychologically and practically in EMI teacher education.

Reinforcement learning optimal control method for multi chiller HVAC system in an existing office building

Abstract Given that buildings consume approximately 33% of global energy, and HVAC systems contribute nearly half of a building’s total energy demand, optimizing their efficiency is imperative for sustainable energy use. Many existing buildings operate HVAC systems inefficiently, displaying non-stationary behavior. Current reinforcement learning (RL) training methods rely on historical data, which is often obtained through costly modeling or trial-and-error methods in real buildings. This paper introduces a novel reinforcement learning construction framework designed to improve the robustness and learning speed of RL control while reducing learning costs. The framework is specifically tailored for existing office buildings. Applying this framework to control HVAC systems in real office buildings in Beijing, engineering practice results demonstrate: during the data collection phase, energy efficiency surpasses traditional rule-based control methods from the previous year, achieving significantly improved energy performance (a 17.27% reduction) with minimal comfort sacrifices. The system achieves acceptable robustness, learning speed, and control stability. Reduced ongoing manual supervision leads to savings in optimization labor. Systematic exploration of actions required for RL training lays the foundation for RL algorithm development. Furthermore, by leveraging collected data, a reinforcement learning control algorithm is established, validating the reliability of this approach. This construction framework reduces the prerequisites for historical data and models, providing an acceptable alternative for systems with insufficient data or equipment conditions.

Construction framework of smart tourism big data mining model driven by blockchain technology

In the era of sharing economy, the tourism market is increasingly characterized by personalized demand, mobile consumption and product segmentation. This paper aims to apply big data mining technology in the field of smart tourism. Firstly, it focuses on image summary selection and collaborative filtering technology based on big data mining. It then demonstrates the integration of blockchain in smart tourism, emphasizing the use of decentralized structures and smart contracts to achieve data security and transparency, and describes the testing process of smart tourism platforms, including data preparation and platform operational efficiency testing. Finally, the research results of this paper are summarized, and the development potential and practical application value of smart tourism are demonstrated. The results show that in the smart tourism big data mining model, the minimum support for the data set is 10 % and 20 %, respectively. Moreover, with the increase of the number of nodes in the same data set, the running time decreases gradually. It can be seen that smart tourism big data mining has strong scalability.

VR map construction for orchard robot teleoperation based on dual-source positioning and sparse point cloud segmentation

The unstructured nature of orchard environments presents significant challenges for autonomous navigation of orchard robots. Teleoperation, combined with virtual reality (VR), has emerged as a promising solution to overcome the limitations of on-board autonomous navigation capabilities in general-purpose robots. However, constructing accurate and semantically meaningful VR maps for orchard environments remains a challenge. This study proposes a novel VR map construction framework for orchard robot teleoperation visualization. It comprises two key components: dual-source combined positioning and semantic segmentation based on sparse point clouds. First, a novel sliding window-based data fusion approach is proposed to address the positioning challenges in semi-obstructed orchard environments. This approach combines GNSS data and laser matching to achieve robust and accurate positioning for orchard robots. Second, the framework capitalizes on the installation characteristics of mobile robot radars to achieve real-time classification of sparse point clouds. This allows for the removal of unstable elements, such as leaves, which would hinder effective teleoperation. By integrating these components, a VR map suitable for VR teleoperation of orchard robots is achieved. To validate the effectiveness of the proposed method, a VR teleoperation platform was constructed. The experimental results demonstrate that the method successfully fulfills the fundamental requirements for map visualization during VR remote operation of orchard robots. Furthermore, this study provides a valuable reference for the application of digital twins in agricultural robotics.