Integration Architecture Research Articles

The Integration of Troglodyte Architecture into Contemporary Architecture, A Fusion of Tradition and Modernity: The Case of Dar Hi in Nefta

Troglodyte architecture, characterized by the utilization of natural caves or structures carved into rock, stands as amesmerizing testament to humanity's adaptability to its surroundings. This study explores the integration of troglodytearchitecture into contemporary design, with a specific focus on Dar Hi in Nefta, Tunisia. It investigates the historicalfoundations, core principles, and the application of troglodyte architecture in modern architectural practices. Theanalysis begins with a historical overview, tracing the evolution of troglodyte structures and their adaptability todiverse environments. The centerpiece of this exploration is the detailed examination of Dar Hi, showcasing how itencapsulates traditional troglodyte elements within a contemporary architectural framework. It dissects thearchitectural components, materials, and design strategies employed, emphasizing sustainability and culturalpreservation. Moreover, this research highlights the experiential aspect, emphasizing how Dar Hi's design fosters asensory connection with Nefta's cultural heritage. It emphasizes how the integration of troglodyte architecturalelements within the establishment creates a unique blend of tradition and modernity. By spotlighting the case studyof Dar Hi, this study sheds light on the potential of harmonizing ancient architectural wisdom with modern design,aiming to inspire discussions on preserving and creatively incorporating troglodyte architecture into contemporaryarchitectural discourse.

Principles of Cloud Computing Infrastructure IaaS

Infrastructure as a Service (IaaS) represents a cornerstone in contemporary cloud computing, providing essential on-demand computing resources, including servers, storage, and networking. This paper explores the foundational principles of IaaS, highlighting its ability to facilitate dynamic server management through practices like auto-scaling and ephemeral server utilization. The use of custom images in IaaS ensures minimal downtime and scalable deployment, while loose coupling enhances fault tolerance and adaptability. Emphasizing high availability through auto-scaling, IaaS supports continuous operations even in geographically vulnerable areas. The security framework of IaaS, encompassing a shared responsibility model, ensures robust data protection and compliance with industry standards. The paper also addresses cost optimization strategies and the integration of hybrid cloud architectures to maximize resource efficiency and maintain data integrity. Overall, IaaS is integral to modern IT infrastructure, offering flexible, scalable, and cost-effective solutions that align with the evolving demands of the digital landscape.

Effective Strategies for Managing Multi-Cloud Salesforce Solutions

Businesses are using multi-cloud solutions to improve flexibility, scalability, and efficiency in today's dynamic environment. Salesforce, a prominent CRM platform, is crucial to many organizations' multi-cloud ecosystems. To achieve seamless integration, maximum performance, and safe operations, administering Salesforce products across numerous cloud environments requires distinct methodologies. This paper discusses best practices, essential concerns, and practical solutions for managing multi-cloud Salesforce applications. The research starts with multi-cloud advantages and difficulties. By using various cloud providers, companies may prevent vendor lock-in, improve resilience, and customize solutions. These benefits complicate data management, integration, and security. The article begins with multi-cloud Salesforce integration techniques. It emphasizes the need for a smooth integration architecture between Salesforce and other cloud services. API-based integrations, middleware platforms, and cloud-based integration services are tested for real-time data synchronization and latency. The study also examines data integration technologies and their influence on data consistency and accuracy across numerous cloud environments. The second segment handles multi-cloud Salesforce data management issues. It addresses data governance, quality control, and storage optimization. Strong data management practices that meet industry and regulatory standards are prioritized. The study examines data transfer, backup, and recovery tools and methods that enable effective data management across cloud platforms.

A multi-scale information integration framework for infrared and visible image fusion

Infrared and visible image fusion aims at generating a fused image containing the intensity and detail information of source images, and the key issue is effectively measuring and integrating the complementary information of multi-modality images from the same scene. Existing methods mostly adopt a simple weight in the loss function to decide the information retention of each modality rather than adaptively measuring complementary information for different image pairs. In this study, we propose a multi-scale dual attention (MDA) framework for infrared and visible image fusion, which is designed to measure and integrate multi-scale complementary information in both structure and loss function at the image and patch level. In our method, the residual downsample block decomposes source images into three scales first. Then, dual attention fusion block integrates complementary information and generates a spatial and channel attention map at the same and adjacent scale for feature fusion. Finally, the output image is reconstructed by the residual reconstruction block. Loss function consists of image-level, feature-level and patch-level three parts, of which the calculation of the image-level and patch-level two parts are based on the weights generated by the complementary information measurement. Indeed, to constrain the pixel intensity distribution between the output and infrared image, a style loss is added. Our fusion results perform robust and informative across different scenarios. Qualitative and quantitative results on three datasets illustrate that our method is able to preserve both thermal radiation and detailed information from two modalities and achieve comparable results compared with the other state-of-the-art methods. Ablation experiments show the effectiveness of our information integration architecture and adaptively measure complementary information retention in the loss function. Our code is available at https://github.com/SSyangguang/MDA.

Data imbalance in cardiac health diagnostics using CECG-GAN

Heart disease is the world’s leading cause of death. Diagnostic models based on electrocardiograms (ECGs) are often limited by the scarcity of high-quality data and issues of data imbalance. To address these challenges, we propose a conditional generative adversarial network (CECG-GAN). This strategy enables the generation of samples that closely approximate the distribution of ECG data. Additionally, CECG-GAN addresses waveform jitter, slow processing speeds, and dataset imbalance issues through the integration of a transformer architecture. We evaluated this approach using two datasets: MIT-BIH and CSPC2020. The experimental results demonstrate that CECG-GAN achieves outstanding performance metrics. Notably, the percentage root mean square difference (PRD) reached 55.048, indicating a high degree of similarity between generated and actual ECG waveforms. Additionally, the Fréchet distance (FD) was approximately 1.139, the root mean square error (RMSE) registered at 0.232, and the mean absolute error (MAE) was recorded at 0.166.

The Role of Modular Architecture in The Context of Is/It Project Outsourcing: An Empirical Analysis

The outsourcing of information systems and information technology (IS/IT) has become a prevalent practice in both developed and emerging economies, with the aim of achieving economies of scale and competitive advantages. In general, an IS/IT outsourcing deal concerns an agreement or contract (service level agreement or SLA) between parties in which one party (the vendor organization) agrees to deliver certain services to another party (the customer organization). The outsourcing literature is persistently reporting high failure rates in IS/IT project outsourcing and suggests that the IS/IT project outsourcing process is a complex maneuver. However, it is likely that due to inappropriate strategies and short-sightedness, at least a third of IS/IT outsourcing projects fail to deliver intended targets. For decades, in numerous fields, the issue of complexity has been addressed by applying the concept of modularity. Modular architecture is a key aspect of the concept of modularity. An in-house team of skilled individuals possessing expertise in architectural and systems integration knowledge may help to achieve competitive advantage by effectively managing complexity. In addition to achieving economies of scale, the customer organization may also achieve agility and flexibility by combining the advantages of modularity and outsourcing. This study examines the feasibility of applying the concept of modularity in the context of IS/IT project outsourcing with the aim of further expanding its scope. The findings of empirical analyses of four cases suggest that numerous aspects of the concept of modularity are relevant in the context of IS/IT project outsourcing. The ‘modular architecture’ has emerged as one of the most relevant and was identified in three out of the four analyzed cases. It implies that the ‘modular architecture’ aspect ought to receive greater attention when designing or planning a new IS/IT outsourcing project. The authors argue by stating that the present study has provided support for the point of view that engineering concepts such as modularity can be applied with substantial relevance to research domains which are predominantly considered from an IT management-perspective. Perhaps the use of the same concept, i.e., modularity, at both the technical and management level will provide a common vocabulary and may be even more to achieve better alignment between both levels and contribute to realizing more successful IS/IT outsourcing projects in the future. However, at the very least, a common vocabulary should help in collaboration between researchers at both levels to advance the research and practice in IS/IT project outsourcing, to which this is an invitation. It would be a contribution to the new and emerging research area focusing on applying engineering concepts to the design of enterprises, coined Enterprise Engineering. In addition to theoretical contributions, this study has implications at a practical level by providing an alternative lens for the CIO’s to analyze their future IS/IT projects.

Thermoelectric active window frame: Constructive integration and preheating analysis

Building heating and cooling systems using thermoelectricity appear to be a feasible alternative, as it presents several features including versatility and high reliance. While most applications of thermoelectricity in buildings are found in wall systems, window integration shows excellent potential for enhancing the thermal performance of buildings at the façade level, compensating heat losses that take place in windows. Combining energy efficient ventilation with heat recovery leads to a significant reduction of the required energy, keeping desired comfort conditions inside buildings. Thus, the following study presents the design of an active window frame with an integrated thermoelectric system, attaining two functions: pre-heating the supply air, while simultaneously recovering the waste heat energy from exhaust air. Two full-scale prototypes were built, each featuring a different airflow pattern, and preliminary tests for heating mode were carried out under laboratory conditions. The results revealed a similar performance comparing both prototypes, achieving a COP ranging 1.56 to 2.71 for prototype A, while prototype B ranged from 1.62 to 2.65. The results showcase superior heating efficiency compared to a previous experiments conducted by the research group, where a maximum COP of 1.91 was achieved. From a building perspective, wider adoption of thermoelectricity applied to thermal conditioning is hindered by lack of suitable products for architectural integration. Therefore, the system's innovation stems from optimized design, integrated construction, and industrialized production, enhancing energy efficiency in buildings via a compact façade integrated system without space compromise.

Mapping morphological cortical networks with joint probability distributions from multiple morphological features

Morphological features sourced from structural magnetic resonance imaging can be used to infer human brain connectivity. Although integrating different morphological features may theoretically be beneficial for obtaining more precise morphological connectivity networks (MCNs), the empirical evidence to support this supposition is scarce. Moreover, the incorporation of different morphological features remains an open question. In this study, we proposed a method to construct cortical MCNs based on multiple morphological features. Specifically, we adopted a multi-dimensional kernel density estimation algorithm to fit regional joint probability distributions (PDs) from different combinations of four morphological features, and estimated inter-regional similarity in the joint PDs via Jensen-Shannon divergence. We evaluated the method by comparing the resultant MCNs with those built based on different single morphological features in terms of topological organization, test-retest reliability, biological plausibility, and behavioral and cognitive relevance. We found that, compared to MCNs built based on different single morphological features, MCNs derived from multiple morphological features displayed less segregated, but more integrated network architecture and different hubs, had higher test-retest reliability, encompassed larger proportions of inter-hemispheric edges and edges between brain regions within the same cytoarchitectonic class, and explained more inter-individual variance in behavior and cognition. These findings were largely reproducible when different brain atlases were used for cortical parcellation. Further analysis of macaque MCNs revealed weak, but significant correlations with axonal connectivity from tract-tracing, independent of the number of morphological features. Altogether, this paper proposes a new method for integrating different morphological features, which will be beneficial for constructing MCNs.

History and evolution of the healing gardens: Investigating the building-nature relationship in the healthcare setting

Healing gardens, a longstanding feature of medical institutions, have garnered attention from scholars for their health-promoting properties across various stages of research. Through a historical literature review and contemporary case analysis of healing gardens, this research investigates how to achieve therapeutic integration by fostering effective connections between buildings and nature through typological design. Combined with qualitative and design-driven research methodologies, including the use of visualization tools such as drawings, models, and images, six models of building-nature integration in contemporary healthcare architecture are identified. This article bridges a research gap in the field of healing garden design and concludes by demonstrating that “typology” is only a design strategy according to context and building performance. In addition to positions of healing gardens, critical factors such as spatial organization, aesthetics, and sustainability, incorporating elements such as accessibility, readability, comfort, and ecological factors, must be carefully considered to achieve integration.

Evaluating novel building products through a building design-oriented LCA approach: Example of VIPs in terrace applications

Abstract INTRODUCTION: The construction industry is considered conservative in adopting new products/technologies, and environmental characteristics are one of the most important features of novel solutions. In this context, our study aims to present a building design-oriented assessment of a novel building product by extending the functional unit scope and involving multiple realistic building design scenarios. The task will be performed using the example of vacuum insulation panels (VIPs), a superinsulation product that can be used in various building applications. The study will focus on terrace insulation applications, where VIPs are an attractive solution for building designers due to the possibility of barrier-free floor design. However, they lack environmental evaluation. METHOD: A life cycle assessment (LCA) analysis is performed on two hypothetical buildings located in Ljubljana (Slovenia) for the cradle-to-gate and operational energy life cycle stages (A1-A3 + B6 according to EN 15978). A whole-year dynamic thermal response simulation was executed using the Design Builder software. Five barrier-free terrace design scenarios that influence the embodied and operational carbon footprint (while maintaining the functional and architectural integrity of the building design) were examined. RESULTS: The study showed that although EPS insulation showed a smaller embodied carbon footprint on the product level, the building level analysis showed that using VIPs in terrace applications leads to favourable or comparable environmental impact. CONCLUSIONS: Building products can be evaluated on three functional unit levels: product, application and building. By extending the boundaries from the product/application level to the entire building level, the study provides an example of a building design-oriented approach to LCA. The complexity increases by upgrading the functional unit scope to the building level, while the results become more case-specific and less general. Ideally, a novel building product should show environmental superiority on all three levels. However, as there are almost countless design possibilities in buildings, environmental superiority (or inferiority) on the product level does not necessarily indicate superiority (or inferiority) on the building level.

Skin Cancer Segmentation using CNN

This groundbreaking research introduces a comprehensive strategy for advancing medical image segmentation, merging two pivotal concepts to significantly enhance both the accuracy and efficiency of the segmentation process. The first component of our approach involves the integration of polar transformations as a preprocessing step applied to the original dataset. This transformative technique is designed to address the challenges associated with segmenting single structures of elliptical shape in medical images, such as organs (e.g., heart and kidneys), skin lesions, polyps, and various abnormalities. By centering the polar transformation on the object's focal point, a reduction in dimensionality is achieved, coupled with a distinct separation of segmentation and localization tasks. Two distinct methodologies for selecting an optimal polar origin are proposed: one involving estimation through a segmentation neural network trained on non-polar images, and the other employing a dedicated neural network trained to pre dict the optimal origin. The second key element of our approach is around the integration of the DoubleU-Net architecture, a powerful encoder-decoder model specifically designed for the task of semantic image segmentation. DoubleU- Net is a group of two U-Net architectures, each with a specific purpose. The initial U-Net is pre-trained on VGG-19 as the encoder and uses features learned from ImageNet to provide efficient information transfer. In order to store more semantic information and content, a second U-Net was added to the base to enhance the capabilities of the network. Join Atrous Spatial Pyramid Pooling (ASPP) to develop network data extraction content. The combination of DoubleU-Net architecture and joint transformation as a step forward shows good segmentation performance in different clinical tasks, including liver segmentation, polyp detection vision, skin segmentation, and epicardial fat tissue segmentation. It shows that various medical projects, including various diagnostic methods such as colonoscopy, dermoscopy, microscopy, have a positive impact on the plan. More importantly, the method performs well in difficult cases, such as the segmentation of small and flat polyps in CVC-ClinicDB and the 2015 subset of the MICCAI Automated Polyp Detection dataset. The results demonstrate the accuracy and generality of the combination, making it the best way to evaluate medical images in context; Our study has revealed a new method of skin cancer diagnosis that combines the power of deep learning with innovation. Advanced technology. The combination of dual U-Net architecture and polar coordinate transformation not only improves the accuracy of classification of lesions but also improves the robustness of the model to changes in image features. This study contributes to the development of computer-aided diagnostic systems for early diagnosis. Experimental results show that our method provides good accuracy, sensitivity, and specificity in detecting malignant and benign tumors. Additionally, we are conducting ablation studies to determine the contribution of each presentation and treatment of skin cancer to ultimately benefit patients and determine these benefits. We also apply the transformation of the joint as the first step to improve the discrimination ability of the model. This mechanical change effectively reduces the impact caused by changes in wound size, shape, and direction by displaying the original image of the polar system. By standardizing the representation of skin diseases, polar transformation improves the model's ability to generalize across different data sets and improves overall performance.

Exchange coupling in (Co/Pt)2/Nb/(Pt/Co)2 multilayers induced by the Yu–Shiba–Rusinov bound states

The Ruderman–Kittel–Kasuya–Yosida (RKKY) theory of oscillatory exchange interaction in synthetic antiferromagnetic multilayers results in the oscillation behavior of giant magnetoresistance ratio. In addition, the formation of Yu–Shiba–Rusinov (YSR) bound states will induce an extra antiferromagnetic interaction, which is expected to mediate stronger exchange coupling than conventional RKKY interaction. However, the YSR bound states have only been studied in some superconducting hosts with magnetic impurities. The narrow range of material systems that are not compatible with the device integration architecture limits the practical application of YSR interaction. Here, we observe the RKKY interaction and provide the evidence for YSR interaction in Pt/(Co/Pt)2/Nb/(Pt/Co)2/Pt synthetic antiferromagnetic multilayers by quantitatively determining the coupling energy via ferromagnetic resonance technique.

An Intelligent Model and Methodology for Predicting Length of Stay and Survival in a Critical Care Hospital Unit

This paper describes the design and methodology for the development and validation of an intelligent model in the healthcare domain. The generated model relies on artificial intelligence techniques, aiming to predict the length of stay and survival rate of patients admitted to a critical care hospitalization unit with better results than predictive systems using scoring. The proposed methodology is based on the following stages: preliminary data analysis, analysis of the architecture and systems integration model, the big data model approach, information structure and process development, and the application of machine learning techniques. This investigation substantiates that automated machine learning models significantly surpass traditional prediction techniques for patient outcomes within critical care settings. Specifically, the machine learning-based model attained an F1 score of 0.351 for mortality forecast and 0.615 for length of stay, in contrast to the traditional scoring model’s F1 scores of 0.112 for mortality and 0.412 for length of stay. These results strongly support the advantages of integrating advanced computational techniques in critical healthcare environments. It is also shown that the use of integration architectures allows for improving the quality of the information by providing a data repository large enough to generate intelligent models. From a clinical point of view, obtaining more accurate results in the estimation of the ICU stay and survival offers the possibility of expanding the uses of the model to the identification and prioritization of patients who are candidates for admission to the ICU, as well as the management of patients with specific conditions.

Method for Determining the Level of Centralization in BTC Lightning Nodes: A Centrality Analysis of the Lightning Network

This study explores the Bitcoin Lightning Network (BLN), a Layer 2 solution for faster and cheaper transactions. Concerns about centralization have emerged due to the increasing concentration of power among specific nodes, named “hubs.” Statistical measures like the Gini coefficient reveal a trend towards centralization, challenging the LN’s decentralized nature. Consequently, further research is necessary to address this issue and ensure the integrity of the LN architecture. This paper aims to establish a method for determining the level of centralization within the BLN by applying centrality analysis techniques. Study revealed that over the six-year period Gini coefficient increased from 0.87 to 0.955, indicating significant inequality and apparent centralization of BLN nodes.

Genome integrity as a potential index of longevity in Ashkenazi Centenarian’s families

The aging process, or senescence, is characterized by age-specific decline in physical and physiological function, and increased frailty and genomic changes, including mutation accumulation. However, the mechanisms through which changes in genomic architecture influence human longevity have remained obscure. Copy number variants (CNVs), an abundant class of genomic variants, offer unique opportunities for understanding age-related genomic changes. Here we report the spectrum of CNVs in a cohort of 670 Ashkenazi Jewish centenarians, their progeny, and unrelated controls. The average ages of these groups were 97.4 ± 2.8, 69.2 ± 9.2, and 66.5 ± 7.0 respectively. For the first time, we compared different size classes of CNVs, from 1 kB to 100 MB in size. Using a high-resolution custom Affymetrix array, targeting 44,639 genomic regions, we identified a total of 12,166, 22,188, and 10,285 CNVs in centenarians, their progeny, and control groups, respectively. Interestingly, the offspring group showed the highest number of unique CNVs, followed by control and centenarians. While both gains and losses were found in all three groups, centenarians showed a significantly higher average number of both total gains and losses relative to their controls (p < 0.0327, 0.0182, respectively). Moreover, centenarians showed a lower total length of genomic material lost, suggesting that they may maintain superior genomic integrity over time. We also observe a significance fold increase of CNVs among the offspring, implying greater genomic integrity and a putative mechanism for longevity preservation. Genomic regions that experienced loss or gains appear to be distributed across many sites in the genome and contain genes involved in DNA transcription, cellular transport, developmental pathways, and metabolic functions. Our findings suggest that the exceptional longevity observed in centenarians may be attributed to the prolonged maintenance of functionally important genes. These genes are intrinsic to specific genomic regions as well as to the overall integrity of the genomic architecture. Additionally, a strong association between longer CNVs and differential gene expression observed in this study supports the notion that genomic integrity could positively influence longevity.

Automatic Evaluation Method for Functional Movement Screening Based on Multi-Scale Lightweight 3D Convolution and an Encoder–Decoder

Functional Movement Screening (FMS) is a test used to evaluate fundamental movement patterns in the human body and identify functional limitations. However, the challenge of carrying out an automated assessment of FMS is that complex human movements are difficult to model accurately and efficiently. To address this challenge, this paper proposes an automatic evaluation method for FMS based on a multi-scale lightweight 3D convolution encoder–decoder (ML3D-ED) architecture. This method adopts a self-built multi-scale lightweight 3D convolution architecture to extract features from videos. The extracted features are then processed using an encoder–decoder architecture and probabilistic integration technique to effectively predict the final score distribution. This architecture, compared with the traditional Two-Stream Inflated 3D ConvNet (I3D) network, offers a better performance and accuracy in capturing advanced human movement features in temporal and spatial dimensions. Specifically, the ML3D-ED backbone network reduces the number of parameters by 59.5% and the computational cost by 77.7% when compared to I3D. Experiments have shown that ML3D-ED achieves an accuracy of 93.33% on public datasets, demonstrating an improvement of approximately 9% over the best existing method. This outcome demonstrates the effectiveness of and advancements made by the ML3D-ED architecture and probabilistic integration technique in extracting advanced human movement features and evaluating functional movements.

Research on the Design Method of Rural Lodging Based on the Integration of Architecture and Environment

The concept of modern tourism intelligent application in China is to fully meet the information needs of tourists and customer experience, and the development of intelligent tourism relying on Internet of Things (IoT) is its most basic guarantee condition. With the rise of ethnic village tourism and the change of new consumer lifestyle, B&amp;B shows an explosive development. Tourism consumers are also shifting from hotels to home stays in the process of tourism. Therefore, based on IOT application as the starting point, this paper firstly, gives a more detailed description of the development process and marketing status of home stays, and discusses its various problems. Then, based on the TP theory of ethnic villages, Porter's five forces analysis model and the SWOT analysis method of ethnic villages, the marketing environment of homestays is studied in depth to discover their advantages.The HTOE model develops a marketing mix strategy for B&amp;Bs that meets the actual situation of ethnic village development

Vertical farming in urban environments: A review of architectural integration and food security

Vertical farming in urban environments has emerged as a promising solution to address the challenges of food security while efficiently utilizing limited urban spaces. This paper provides a comprehensive review of the architectural integration of vertical farming systems and their impact on enhancing food security. Urbanization and population growth have led to increased pressure on traditional agriculture, necessitating innovative approaches to meet the rising demand for food. Vertical farming involves cultivating crops in vertically stacked layers or inclined surfaces within controlled environments, such as skyscrapers, warehouses, or specially designed structures. The integration of vertical farming into urban architecture is a multifaceted endeavor that involves considerations of space utilization, energy efficiency, and sustainable practices. Architectural integration plays a pivotal role in the success of vertical farming systems. This review explores various design strategies employed in integrating vertical farms into urban landscapes, including the incorporation of green walls, modular systems, and adaptive reuse of existing structures. The symbiotic relationship between architecture and agriculture is crucial for optimizing resource utilization, ensuring efficient energy distribution, and minimizing environmental impact. Furthermore, the review addresses the implications of architectural choices on the overall efficiency and scalability of vertical farming. It examines the role of technology in creating smart, automated farming systems that can be seamlessly integrated into urban structures. The integration of sensors, artificial intelligence, and robotics enhances precision farming, resulting in higher yields and resource efficiency. A significant focus of the paper is on the implications of vertical farming for food security. By bringing food production closer to urban centers, vertical farming reduces the reliance on long-distance transportation, minimizing carbon footprints and enhancing the resilience of food supply chains. Additionally, the controlled environment of vertical farms mitigates the impact of climate variability on crop yields, contributing to more stable and secure food production. In conclusion, this paper synthesizes the current knowledge on the integration of vertical farming into urban architecture, emphasizing its role in addressing food security challenges. The review underscores the importance of innovative architectural approaches and technological advancements in realizing the full potential of vertical farming for sustainable and secure urban food production.

The Construction of Two-tier Equity Structure of Joint Stock Companies in China from the Perspective of Green Finance

In this modern era business and changing landscapes, the construction of a two-tier equity structure within Chinese joint stock companies has proved to be a very innovative and augmented strategy. This paper scrutinizes the unorthodox integration of financial architecture and ecological sustainability by evaluation of this structure through the lens of green finance. The interlacing of the principles of environmental responsibility with mainframes of corporate governance enlightens the unique dynamics and outcomes of the two-tier equity model. This study comprehensively analyses and elucidates how this mainframe facilitates the shareholder interests as they align with long-term ecological objectives. This in turn cultivates a promising environment for sustainable development. As we draw onto the theoretical calculations and perspective supplemented with empirical evidences, this research study gives birth to amenable perspectives that the green finance has the potential to transform the Chinese context by shaping the future trajectory of corporate structures. Using a dataset consisting of Chinese publicly traded companies from 2001-2017, this study investigates how a lack of funding has led to a scarcity of environmentally friendly technologies in China. We also investigate how green finance laws help businesses overcome financial hurdles on the road to eco-friendly innovation. It has been observed that a company's capacity for green innovation decreases as its financial constraints grow, and that privately held businesses are at greater danger of this happening than government-owned ones.

Innovative Applications of XR in Architectural Sustainability: Current Trends and Future Prospects

Due to the limited global resources and the threat of climate change, sustainable development has become a critical issue. This study aims to delve into the various applications of Extended Reality (XR), including Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR), in sustainable architectural design. Through virtual experiences, visualisation of architectural ecosystems, BIM integration, and environmental simulations, XR technology provides designers with a more comprehensive dataset and perspective. However, despite showcasing the potential of XR technology, further research and practical implementation are necessary to deepen our understanding of its role in architectural sustainability and address potential technological and application challenges. The article emphasizes the need to holistically consider multiple dimensions of data when applying XR technology in architectural design, enabling a more comprehensive evaluation of the sustainability of design solutions.