Integration Architecture Research Articles

Dual-wideband radiating surface using interleaved electric and magnetic currents: Underlying physics and experimental verification

Unlike popular multiband antenna array radiation based on either electric or magnetic surface currents, the use of mutually interleaved and tightly coupled electric and magnetic currents results in an aperture-reuse space-efficient multiband radiating surface for highly integrated antenna-frontend architecture and spatial power combining design scenarios. In this work, slot and dipole modes corresponding to magnetic and electric currents are effectively interleaved and excited in a surface to develop a space-efficient dual-wideband aperture-shared radiating surface. In this case, due to an effective reuse of the antenna aperture over both frequency bands, a high aperture-reuse efficiency is achieved. First, we devise a planar magneto-electric (ME)-dipole-alike antenna and analyze it in both the frequency and time domain. The antenna is then studied by the characteristic mode theory and the findings are validated using full-wave simulations. The developed planar ME-dipole-alike antenna is used to realize a dual-wideband radiating surface in which electric and magnetic currents are mutually coupled and interlaced, which is excited by properly oriented and distributed sources on the antenna's surface. Eventually, a highly isolated dual-wideband prototype was developed and fabricated using a cost-effective multi-layer Printed Circuit Board (PCB) process that operates in the Ku-band with both impedance and gain bandwidth of approximately 42% and in the Ka-band with respective impedance and gain bandwidth of 29% and 16.32%.

Integration of aquaponics aystem with water reuse for housing in hot arid climate: BaityKool(BK), a bio-inspired dwelling prototype in Dubai-UAE

In urban areas, there is little space available for vegetation but a potential for food production that merits to be exploited. aquaponics is a coupled system of two technologies of fish farming and soil-less vegetation, a scheme primarily proposed for hot arid regions with limited agricultural land resource availability for sustainable water reuse and food production operation. This research will include the aquaponics system as a provision of food for all occupants of a house in the most environmentally friendly manner possible. In comparison to standard vegetable production, the employment of this form of the aquaponic system results in effective water savings of up to 90% while producing part of the vegetables for salads for the residents of the BaityKool house. This paper presents the technological design of an aquaponic system as well as its architectural integration into a habitat in Dubai-UAE.

Public art as an artistic way of development of the architectural and urban environment

The article considers public art as an artistic direction that contributes to the restoration and development of the architectural and urban environment. The analysis of artistic forms of art of the end of the 20th century revealed the trends of multidisciplinarity and going beyond the artistic infrastructure into the public architectural and urban environment. Moreover, public art objects are actively introduced into the environment of super-large cities of Ukraine and only partially into the environment of other cities. The existence and rapid development of these objects is a sign of a modern super-large city with a developed architectural and urban environment and integration into the world cultural process. Public art is a form of contemporary art that interacts interactively with the viewer, raising questions about contemporary art and the space in which it is placed. Modern forms of public art were analyzed and four principles of public art were identified as a result of the systematization of existing information. These are the principles of interactivity, conceptuality, digitalization, creativity. Their harmonious combination helps to develop a friendly space in accordance with the individual needs of a person and to form an emotional interactive architectural and urban environment with a unique atmosphere and social messages. Such modern artistic mediums as installations, happenings and performances permeate the four formulated principles of public art, mainly focusing not on the result, but on the process of creation and the emotional component of the environment. They are mixed genres of visual art that use objects of public art or the artist's body to interact and change people's perception of public space. It should be noted that the development of media technologies has led to the creation of public art objects not only in physical, but also in virtual space, covering, in addition to land art and environment, also digital, conceptual and light art. This allows considering and developing the artificial space and public environment as a multi-level interactive open system with a developed cultural context that interacts with people in space and time.

An innate granuloma eradicates an environmental pathogen using Gsdmd and Nos2

Granulomas often form around pathogens that cause chronic infections. Here, we discover an innate granuloma model in mice with an environmental bacterium called Chromobacterium violaceum. Granuloma formation not only successfully walls off, but also clears, the infection. The infected lesion can arise from a single bacterium that replicates despite the presence of a neutrophil swarm. Bacterial replication ceases when macrophages organize around the infection and form a granuloma. This granuloma response is accomplished independently of adaptive immunity that is typically required to organize granulomas. The C. violaceum-induced granuloma requires at least two separate defense pathways, gasdermin D and iNOS, to maintain the integrity of the granuloma architecture. This innate granuloma successfully eradicates C. violaceum infection. Therefore, this C. violaceum-induced granuloma model demonstrates that innate immune cells successfully organize a granuloma and thereby resolve infection by an environmental pathogen.

An All-Human Hepatic Culture System for Drug Development Applications.

Finding a long-term, human-relevant culture model for primary human hepatocytes (PHHs) for pharmacological and toxicological studies remains a challenge. Current in vitro model platforms are often inconvenient and complex, lack phenotypic stability over time, and do not support multiple PHH lots, lacking experimental reproducibility and flexibility. Here, we provide a detailed protocol for the thawing, plating, and maintenance of an all-human 2D+ hepatic system (TV2D+), which takes advantage of standard two-dimensional (2D) culture techniques and equipment while maintaining the longevity and phenotypic stability over time that typically accompany more complex three-dimensional (3D) systems. The results show attachment and percent plateability in TV2D+ as a function of PHH seeding density, as well as stable functionality for at least 2 weeks in culture. A range of PHH seeding densities are assessed to achieve a successful long-term culture. When established properly, the PHHs in TV2D+ organize into hepatocyte colonies, express a hepatic-specific marker, and maintain viability, architectural integrity, and physiologically relevant levels of albumin and urea. This unique combination of attributes makes the TV2D+ system a suitable hepatic model for a variety of pharmacological and toxicological applications.

Synergistic Combination of Reductive Covalent Functionalization and Atomic Layer Deposition—Towards Spatially Defined Graphene‐Organic‐Inorganic Heterostructures

AbstractThree‐dimensionally (3D) well‐ordered and highly integrated graphene hybrid architectures are considered to be next‐generation multifunctional graphene materials but still remain elusive. Here, we report the first realization of unprecedented 3D‐patterned graphene nano‐ensembles composed of a graphene monolayer, a tailor‐made structured organophenyl layer, and three metal oxide films, providing the first example of such a hybrid nano‐architecture. These spatially resolved and hierarchically structured quinary hybrids are generated via a two‐dimensional (2D)‐functionalization‐mediated atomic layer deposition growth process, involving an initial lateral molecular programming of the graphene lattice via lithography‐assisted 2D functionalization and a subsequent stepwise molecular assembly in these regions in the z‐direction. Our breakthrough lays the foundation for the construction of emerging 3D‐patterned graphene heterostructures.

Synergistic Combination of Reductive Covalent Functionalization and Atomic Layer Deposition-Towards Spatially Defined Graphene-Organic-Inorganic Heterostructures.

Three-dimensionally (3D) well-ordered and highly integrated graphene hybrid architectures are considered to be next-generation multifunctional graphene materials but still remain elusive. Here, we report the first realization of unprecedented 3D-patterned graphene nano-ensembles composed of a graphene monolayer, a tailor-made structured organophenyl layer, and three metal oxide films, providing the first example of such a hybrid nano-architecture. These spatially resolved and hierarchically structured quinary hybrids are generated via a two-dimensional (2D)-functionalization-mediated atomic layer deposition growth process, involving an initial lateral molecular programming of the graphene lattice via lithography-assisted 2D functionalization and a subsequent stepwise molecular assembly in these regions in the z-direction. Our breakthrough lays the foundation for the construction of emerging 3D-patterned graphene heterostructures.

Combining Neural Architecture Search with Knowledge Graphs in Transformer: Advancing Chili Disease Detection

With the advancement in modern agricultural technologies, ensuring crop health and enhancing yield have become paramount. This study aims to address potential shortcomings in the existing chili disease detection methods, particularly the absence of optimized model architecture and in-depth domain knowledge integration. By introducing a neural architecture search (NAS) and knowledge graphs, an attempt is made to bridge this gap, targeting enhanced detection accuracy and robustness. A disease detection model based on the Transformer and knowledge graphs is proposed. Upon evaluating various object detection models on edge computing platforms, it was observed that the dynamic head module surpassed the performance of the multi-head attention mechanism during data processing. The experimental results further indicated that when integrating all the data augmentation methods, the model achieved an optimal mean average precision (mAP) of 0.94. Additionally, the dynamic head module exhibited superior accuracy and recall compared to the traditional multi-head attention mechanism. In conclusion, this research offers a novel perspective and methodology for chili disease detection, with aspirations that the findings will contribute to the further advancement of modern agriculture.

Integration Patterns for Open Subsurface Data Universe (OSDU)

The Open Subsurface Data Universe (OSDU) initiative has gained significant traction in the oil and gas industry as a collaborative platform for standardizing data access and sharing and holds great promise for transforming the oil and gas industry's data landscape. However, as with any large-scale data integration effort, there are several challenges that organizations must address when integrating their systems and data with OSDU. To fully realize the potential of OSDU, effective integration patterns are essential. This paper presents a comprehensive overview of integration patterns tailored for OSDU, addressing various challenges and opportunities associated with data integration, interoperability, and system architecture. We discuss key considerations, best practices, and implementation examples to guide organizations in successful OSDU integration.

A Combinatorial Regulatory Platform Determines Expression of RNA Polymerase III Subunit RPC7α (POLR3G) in Cancer.

RNA polymerase III (Pol III) subunit RPC7α, which is encoded by POLR3G in humans, has been linked to both tumor growth and metastasis. Accordantly, high POLR3G expression is a negative prognostic factor in multiple cancer subtypes. To date, the mechanisms underlying POLR3G upregulation have remained poorly defined. We performed a large-scale genomic survey of mRNA and chromatin signatures to predict drivers of POLR3G expression in cancer. Our survey uncovers positive determinants of POLR3G expression, including a gene-internal super-enhancer bound with multiple transcription factors (TFs) that promote POLR3G expression, as well as negative determinants that include gene-internal DNA methylation, retinoic-acid induced differentiation, and MXD4-mediated disruption of POLR3G expression. We show that novel TFs identified in our survey, including ZNF131 and ZNF207, functionally enhance POLR3G expression, whereas MXD4 likely obstructs MYC-driven expression of POLR3G and other growth-related genes. Integration of chromatin architecture and gene regulatory signatures identifies additional factors, including histone demethylase KDM5B, as likely influencers of POLR3G gene activity. Taken together, our findings support a model in which POLR3G expression is determined with multiple factors and dynamic regulatory programs, expanding our understanding of the circuitry underlying POLR3G upregulation and downstream consequences in cancer.

An Integrated Method for Reducing Arrival Interval by Optimizing Train Operation and Route Setting

The arrival interval at high-speed railway stations is one of the key factors that restrict the improvement of the train following intervals. In the process of practical railway operation, sudden conflicts occur sometimes. Especially when the conflict arises at the station, because the home signal cannot be opened in time, the emergency may affect the adjustment of the train operation under the scheduled timetable, resulting in a longer train following interval or even delay. With the development of artificial intelligence and the deep integration of big data, the architecture of train operation control and dispatch integration is gradually improving from the theoretical point. Based on this and inspired by the Green Wave policy, we propose an integrated operation method that reduces the arrival interval by avoiding unnecessary stops in front of the home signal and increasing the running speed of trains through the throat area. It is a two-step optimization method combining both intelligent optimization and mathematical–theoretical analysis algorithms. In the first step, the recommended approaching speed and position are obtained by analytical calculation. In the second step, the speed profile from the current position to the position corresponding to the recommended approaching speed is optimized by intelligent optimization algorithms. Finally, the integrated method is verified through the analysis of two distinct case studies. The first case study utilizes data from the Beijing–Shanghai high-speed railway line, while the second one is based on the field test. The numerical result shows that the proposed method could save the entry running time effectively, compared with the normal strategy given by the train driver. The method can mitigate controllable conflict events occurring at the station and provides theoretical support for practical operation.

Ag-integrated mixed metallic Co-Fe-Ni-Mn hydroxide composite as advanced electrode for high-performance hybrid supercapacitors

Direct growth of redox-active noble metals and rational design of multifunctional electrochemical active materials play crucial roles in developing novel electrode materials for energy storage devices. In this regard, silver (Ag) has attracted great attention in the design of efficient electrodes. Inspired by the house/building process, which means electing the right land, it lays a strong foundation and building essential columns for a complex structure. Herein, we report the construction of multifaceted heterostructure cobalt-iron hydroxide (CFOH) nanowires (NWs)@nickel cobalt manganese hydroxides and/or hydrate (NCMOH) nanosheets (NSs) on the Ag-deposited nickel foam and carbon cloth (i.e., Ag/NF and Ag/CC) substrates. Moreover, the formation and charge storage mechanism of Ag are described, and these contribute to good conductive and redox chemistry features. The switching architectural integrity of metal and redox materials on metallic frames may significantly boost charge storage and rate performance with noticeable drop in resistance. The as-fabricated Ag@CFOH@NCMOH/NF electrode delivered superior areal capacity value of 2081.9 µA h cm−2 at 5 mA cm−2. Moreover, as-assembled hybrid cell based on NF (HC/NF) device exhibited remarkable areal capacity value of 1.82 mA h cm−2 at 5 mA cm−2 with excellent rate capability of 74.77% even at 70 mA cm−2 Furthermore, HC/NF device achieved maximum energy and power densities of 1.39 mW h cm−2 and 42.35 mW cm−2, respectively. To verify practical applicability, both devices were also tested to serve as a self-charging station for various portable electronic devices.

Tree Architecture & Blockchain Integration: An off-the-shelf Experimental Approach

Temporally sensitive tree modeling and urban park spatially explicit simulation offer advantages to large-scale landscape planning and design, especially in the context of smart applications for virtual parks and forests, while Blockchain technology provides collaborative engineering, data integrity, and information confidence. A proof-of-concept 2.5D tree architecture and Blockchain integration technique (distributed Internet-of-Trees images, “IoTr-images”) was presented as a low-cost metaverse case study that affects the forest monitoring and digital landscape architecture design infrastructures. At the core of the proposed feature-based parametric modeling methodology is a 2.5D tree CAD model composed of two perpendicular 2D tree frames on which recorded tree texture has been assigned. A “Batch command-line programming” technique has been implemented, as a user-defined routine at the top of a commercial CAD platform, to describe the proposed off-the-self method and to create tangible tree-image NFT tokens (Internet-of-Trees-images Blockchain). As important findings were recorded, the add-in planning intelligence, the superior data integrity, and confidence, the offline relaxed error-free CAD design, and the superiority in terms of time and cost compared to traditional 3D tree modeling methods (laser scanning, close-range photogrammetry, etc.); as well as the satisfactory tree modeling accuracy for smart forest monitoring and landscape architecture applications. The proposed 2.5D parametric tree model added new value to the CAD-Blockchain integration industry because a plain “Blockchain/Merkle hash tree” tracks tree geometry growth and texture change temporarily with simple parametric transactions (i.e. controlled hash tree magnification/scaling). So, metaverse functionality (decentralized, autonomous, coordinated, and parallel design; same-data sharing; data validation), modification and redesign ability, and planning intelligence are effectively supported by the proposed technique. Main contributions are regarded as the ability for smart forest distributed surveillance and collaborative parallel landscape architecture design, open-source Web-based educational simulations, as well as the potential for off-the-shelf contractual collaborative frameworks (smart contracts between designers and clients). Stratification based on forest types improved above-ground biomass (AGB) estimation, especially when AGB was greater than 500 Mg/ha, using the proposed “IoTr-images” technique. So, this research provides new insight into AGB modeling and monitoring. Finally, the proposed method’s robustness has been validated by performance evaluation testing.

Found in translation-Fibrosis in metabolic dysfunction-associated steatohepatitis (MASH).

Metabolic dysfunction-associated steatohepatitis (MASH) is a severe form of liver disease that poses a global health threat because of its potential to progress to advanced fibrosis, leading to cirrhosis and liver cancer. Recent advances in single-cell methodologies, refined disease models, and genetic and epigenetic insights have provided a nuanced understanding of MASH fibrogenesis, with substantial cellular heterogeneity in MASH livers providing potentially targetable cell-cell interactions and behavior. Unlike fibrogenesis, mechanisms underlying fibrosis regression in MASH are still inadequately understood, although antifibrotic targets have been recently identified. A refined antifibrotic treatment framework could lead to noninvasive assessment and targeted therapies that preserve hepatocellular function and restore the liver's architectural integrity.

Canopy architecture and diurnal CO2 uptake in male and female clones of yerba‐mate cultivated in monoculture and agroforestry

AbstractSecondary sexual dimorphism (SSD) in flowering plants is expressed by sexual differences of characters that are not directly related to gamete production. The leaf C/N ratio, photosynthetic traits or clonal responses have never been studied in relation to SSD in yerba‐mate. It was hypothesized that leaf and plant photosynthesis are higher in female than in male individuals because females must supply photoassimilates to compensate for the additional reproductive investments of SSD in biomass. Here, we investigated how two contrasting light environments (monoculture—MO and agroforestry—AFS) and plant genders change leaf and plant photosynthesis, plant architecture, leaf and branch biomass production and C and N investments of two male and two female clones. To model the 3D yerba‐mate structure, virtual trees were constructed using measurements of plant morphology using VPlant modelling software. The light‐response curves of leaf CO2 assimilation were used to model instantaneous leaf and daily plant photosynthesis. Photosynthetic traits derived from light‐response curves did not differ between MO and AFS. Some architectural traits were segregated sexually only in MO, while some physiological ones only in AFS. Leaf photosynthesis was higher in females than in males in AFS over a large part of the diurnal cycle, but SSD was not expressed in carbon gains at plant or daily scales. Leaf C/N ratio was higher in MO than in AFS, indicating MO as an ecosystem with higher degree of environmental degradation. Female clones had leaves with lower C/N ratio than males in both systems, relating to higher leaf photosynthesis on an area basis in females. SSD expressed in leaf photosynthesis over a large part of the diurnal cycle in AFS was not observed in carbon gains at plant or daily scales, indicating that the integration of physiology and architecture equalized the gender specificities. The insensitivity of photosynthetic traits derived from light‐response curves indicated acclimation of yerba‐mate leaves to a wide range of incoming light.

The Ambiguous Architecture of Economic Integration in East Asia

The Ambiguous Architecture of Economic Integration in East Asia

Optimising acoustic performance, cost efficiency, and embodied carbon in internal partitions: A holistic approach for sustainable building design

The successful design of a building is a complex endeavor that requires careful consideration of multiple factors and disciplines, ultimately aiming for a holistic outcome throughout the entire process—from design and delivery to the lifespan of the building. To achieve this outcome, various aspects, such as architectural design, structural integrity, functionality, environmental sustainability, cost efficiency, and occupant comfort, must be balanced and integrated. This paper explores the relationship between acoustic performance, cost implications, and embodied carbon in internal partitions within the context of building design. It emphasises the importance of a holistic approach in considering these factors collectively and highlights the early integration of acoustic considerations, cost-effective materials and techniques, and environmental sustainability. By making informed decisions, stakeholders can optimize building outcomes by creating superior acoustic environments while minimizing costs and environmental impact. This paper aims to provide a guide for professionals, underlining the significance of a comprehensive approach in achieving optimal project results.

Data Guardianship: Safeguarding Compliance in AI/ML Cloud Ecosystems

AI has found widespread application across various sectors, including security, healthcare, finance, and national defense. However, alongside its transformative advancements, there has been an unfortunate trend of malicious exploitation of AI capabilities. Concurrently, the rapid evolution of cloud computing technology has introduced cloud-based AI systems. Regrettably, vulnerabilities inherent in cloud computing infrastructure also pose risks to the security of AI services. We observe that the integrity of training data is pivotal, as any compromise therein directly impacts the efficacy of AI systems. Against this backdrop, we assert the paramount importance of preserving data integrity within AI systems. To address this imperative, we propose a data integrity architecture guided by the National Institute of Standards and Technology (NIST) cyber security framework. Leveraging block chain technology and smart contracts emerges as a fitting solution to tackle integrity challenges, owing to their characteristics of shared and decentralized ledgers. Smart contracts facilitate automated policy enforcement, enable continuous monitoring of data integrity, and mitigate the risk of data tampering.

Lightweight extensive green roof for building renovation: Summer performance analysis and application in a living laboratory

Extensive green roofs are considered an effective energy conservation measure for increasing buildings’ energy efficiency and reducing the heat wave effect in dense build environments. In this context the present work has a two-fold objective: the first is to test and analyse a commercial extensive lightweight green roof sample through an experimental monitoring campaign carried out in a hot climate during the summer time; the second is to provide a practical case study application showing the architectural integration of the extensive green roof technology for existing buildings. The experimental monitoring campaign has been set for analyzing the temperature levels of an extensive green roof compared with a traditional horizontal roof finished with cement tile. The temperature levels have been analysed through a set of sensors positioned at different levels to characterise the green roof response to the climatic forces during summer. The results show that the air temperature in proximity to the green surface (15 cm above the greenery) is warmer than the undisturbed ambient air temperature during the day and lower during the night by 2–2.5 °C. The soil substrate and the vegetative layer contribute to increase ambient air humidity levels. As expected, the evapotranspiration of the green layer increases during a typical sunny day resulting in more water content in the air above the vegetative level of about 4–8 %. The surface temperature of the ground below the vegetation layer and the temperature of the ground layer (8 cm deep) shows beneficial attenuation and time shift properties with respectively 12–15 °C and 3–4 h. Compared to the traditional cement tiles the green roof shows lower intralayer temperature with differences ranging from 6 to 8 °C. Moreover, the renovation case study represents a practical example of green roof technology integration in a real environment. The study has high replicability, and it is meant to be an interesting example for researchers and professionals to boost the green roof technology application for higher-quality built environments.

CloudDenseNet: Lightweight Ground-Based Cloud Classification Method for Large-Scale Datasets Based on Reconstructed DenseNet.

Cloud observation serves as the fundamental bedrock for acquiring comprehensive cloud-related information. The categorization of distinct ground-based clouds holds profound implications within the meteorological domain, boasting significant applications. Deep learning has substantially improved ground-based cloud classification, with automated feature extraction being simpler and far more accurate than using traditional methods. A reengineering of the DenseNet architecture has given rise to an innovative cloud classification method denoted as CloudDenseNet. A novel CloudDense Block has been meticulously crafted to amplify channel attention and elevate the salient features pertinent to cloud classification endeavors. The lightweight CloudDenseNet structure is designed meticulously according to the distinctive characteristics of ground-based clouds and the intricacies of large-scale diverse datasets, which amplifies the generalization ability and elevates the recognition accuracy of the network. The optimal parameter is obtained by combining transfer learning with designed numerous experiments, which significantly enhances the network training efficiency and expedites the process. The methodology achieves an impressive 93.43% accuracy on the large-scale diverse dataset, surpassing numerous published methods. This attests to the substantial potential of the CloudDenseNet architecture for integration into ground-based cloud classification tasks.