This study aimed to increase the energy independence of buildings by utilizing solar energy to produce renewable energy. The subject of this study was a shading structure installed in an outdoor space to provide solar energy. Solar panels were applied to the shaded structures to generate energy actively. The solar panels were designed to be moved according to the optimal tilt angle each month to produce the optimal renewable energy. The architectural design of the shading structure and the energy simulation of the solar panels were conducted using a parametric design. The results of the energy simulation showed the generation of 31,570 kWh· year−1 of renewable energy. This amount of energy is 10% higher than that produced by fixed solar panels. Thus, the moving solar panel system developed in this study not only increases the energy independence of buildings, but also has the advantage of higher renewable energy production compared with fixed solar panels. Additionally, various types of shading structures can be designed depending on the combination of solar panel modules; in particular, moving solar panels have the potential to facilitate ecofriendly designs when applied to the exterior of buildings.

Over the last few decades, contemporary museums have undergone a radical change into public places that promote socio-economic sustainability by impeding recreation, commercial, and cultural activities. This shift altered public perception of museums globally and had a profound impact on today's museums, resulting in new prototypes that differed significantly from prior ones. The study tries to answer the following questions: How far have Egyptian museums been evolving over the last decade? To what degree the radical transformation in the museum design can assist in fulfilling Egypt’s SDGs? To answer these questions the study attempts to explore how far Egyptian museums have adapted to this fundamental change by tracing the evolution of Egyptian museum design compared with the findings of the author's previous thesis in 2012 and Egypt’s SDGs The study used qualitative methods which began with a thorough literature review followed by a comparative analysis of the selected case studies. . The findings revealed that the contemporary design of the recent Egyptian museums by including the social and economic activities, significantly support the national and global agenda in term of SDG. The article provides architects, designers, and policy makers with clear design criteria to enhance the social and economic role of museums towards fulfilling SDGs.

This study aims to determine the present and future scopes of the digital economy in Bangladesh to build a developed and prosperous country by 2041. Simultaneously, it analyses the components of the Digital Economy from numerous perspectives from contributing to Bangladeshi economy with an adaptation of the 4th Industrial Revolution and emerging technologies. In the methodology section, qualitative approach is conducted to determine the research objectives where secondary data is used. Around 100 papers are collected and 51 articles are used for conducting this study. The findings of the study are to present the current state of the digital economy which is developing trends that contribute to national GDP for the adaptation of the 4IR for the transformation of smart Bangladesh. From the conceptual implication, companies and individuals are aware of the digital economy, which would lessen digital divide and create a strong link between technology and the economy. Furthermore, establishing customer confidence and trust would be a big issue for Bangladesh's digital platform economy in the future days. From a practical standpoint, IT industries and commercial organizations would have to deal with emerging 4IR and its technologies. The job market would also be expanded in a variety of areas, which would ultimately benefit the national economy. According to the study's conclusions, the digital economy is predicted to expand its commercial and corporate opportunities. Future research might be extended based on qualitative approach towards a digital Bangladesh and create a better developing economy.

Kenya’s construction industry is experiencing exponential growth in tandem with construction trends globally. With the growth experienced in the industry, there has been significant growth in the economy and a 50% contribution to the world’s landfill waste and pollution to the adjacent environment. Globally, the construction industry is among the largest consumers of natural resources and significant contributors to pollution. This has given rise to high pressure to adopt environmentally sensitive approaches in the construction industry to present a competitive advantage. It is, therefore, crucial to address the need for sustainability measures for Landscape Architecture projects to increase knowledge and awareness, create incentives geared towards supporting sustainable practices, and leverage legal instruments and policies. Green construction practices and strategies have positively impacted the environment and the Kenyan construction industry’s social and economic performance. However, there are several barriers to the adoption and improvement of monitoring and evaluation of sustainable practices, thus slowing down the industry in taking charge of sustainability.

The purpose of this study is to analyse the ways of visualization of hidden violence through a map of the city of violence called La Manada City, in its transformation from defensive to artistic strategies. For this analysis, firstly we propose the contextualization of the artwork and its authorship, and later, the research about the artistic and visual resources of the 257 items that make up the map and its guide street, in a sort of rustic hypertext of the emotions linked to the violence in the territory. The main findings of this study demonstrate the strength of the strategy used as a survival method in cases of bullying. As a conclusion, in spite of the therapeutic effects, this work cannot be understood as Art Therapy, but as combat art: it provides an understanding of the emotional city, of the disadvantaged groups that inhabit it, from the most local (as a transcript of the city of Seville) to global and universal effects on community life.

Despite the abundance of tree diversity in the natural world, and generally high tree species richness in urban areas, urban forests continue to be dominated by a limited number of species. As socio-ecological systems, urban forests are shaped by historical and current management efforts and decision-making of a wide range of human actors. Drawing on past research, we offer a conceptual framework for describing the complex interactions among tree producers and consumers as trees are selected, grown, specified, and planted in private and public urban areas. We illustrate how multiple layers of selection criteria filter down the entirety of potential local tree diversity to a handful of commonly used and accepted tree species. We detail the actors and decision makers who impact tree composition and diversity across several land types. Finally, we identify research, education and outreach needs as they relate to creating more diverse and resilient urban forest ecosystems.

Citron watermelon (Citrullus lanatus var. citroides) is an extremely drought-tolerant cucurbit crop widely grown in sub-Saharan Africa in arid and semi-arid environments characterized by drought. The species is a C3 xerophyte used for multiple purposes, including intercropping with maize and has a deep taproot system. The deep taproot system plays a key role in the species’ adaptation to dry conditions. Understanding root system development of this crop could be useful in identifying traits for breeding water-use efficient and drought-tolerant varieties. This study compared root system architecture of citron watermelon accessions under water-stress conditions. Nine selected and drought-tolerant citron watermelon accessions were grown under non-stress (NS) and water stress (WS) conditions using the root rhizotron procedure in a glasshouse. The following root system architecture (RSA) traits were measured, namely: root system width (RSW), root system depth (RSD), convex hull area (CHA), total root length (TRL), root branch count (RBC), total root volume (TRV), leaf area (LA), leaf number (LN), first seminal root length (FSRL), seminal root angle (SRA), root dry mass (RDM), shoot dry mass (SDM), root–shoot mass ratio (RSM), root mass ratio (RMR), shoot mass ratio (SMR) and root tissue density (RTD). The data collected on RSA traits were subjected to the analysis of variance (ANOVA), correlation and principal component analyses. ANOVA revealed a significant (p < 0.05) accession × water stress interaction effect for studied RSA traits. Under WS, RDM exhibited significant and positive correlations with RSM (r = 0.65), RMR (r = 0.66), RSD (r = 0.66), TRL (r = 0.60), RBC (r = 0.72), FSRL (r = 0.73) and LN (r = 0.70). Principal component analysis revealed high loading scores for the following RSA traits: RSW (0.89), RSD (0.97), TRL (0.99), TRV (0.90), TRL (0.99), RMR (0.96) and RDM (0.76). In conclusion, the study has shown that the identified RSA traits could be useful in crop improvement programmes for citron watermelon genotypes with enhanced drought adaptation for improved yield performance under drought-prone environments.

Botnets, a prominent threat to IoT security. ‘botnet’ this word is the composition of robot and network. A network of robots used to commit cybercrime. A bot means a compromised end-host or a device which is a member of a botnet. [2] Governments have become a popular target for malicious attacks. This is due to them holding mass confidential data on their network.

Many dedicated designs for real-time operations provide functionality on fixed-sized operators, but where speed, scalability, and flexibility are required, extensive research is demanded. Dedicated designs can provide real-time processing for many applications. This paper presents an FPGA-based design of a general image processor. The proposed design is based on a fixed-point representation of binary numbers. The proposed design provides a mechanism to manage matrices on-chip along with matrix arithmetic. The matrices are represented with simple identifiers and microinstruction that assist in the computation of many operations which are useful for solving complex problems. The design was successfully implemented and tested using VHDL language. The proposed design is an efficient architecture as a standalone processor with all embedding computational resources necessary for an embedded image processing application.

Blade Health Monitoring (BHM) is often necessary in power plants and in aviation to prevent excessive blade vibration and cracks. This article proposes a network of blade tip timing sensors operated in a distributed BHM system. A number of cooperating agents is implemented in smart conditioning units which can autonomously operate in an adverse environment and communicate with other nodes via a serial interface. The project uses special versions of reduced instruction set chips that are able to operate near the hot section of the engine. Due to the limited number of types of microprocessors available in the extended temperature range grading, it was necessary to fully utilize the limited hardware resources and implement preemptive multitasking. For this purpose, a custom operating system and communication protocol were designed. The protocol hosts the middle layer which hides the implementation of the distributed system. The presented architecture ensures the sufficient computational capacity in individual nodes of the network operated in adverse conditions. It is scalable and resistant to transmission errors.

Rigid-body visual tracking is an active research field with many practical applications including visual surveillance and intelligent transport system. In this paper, we define a new problem domain, called visual growth tracking, to track different parts of an object that grow non-uniformly over space and time for application in image-based plant phenotyping. The paper introduces a novel method to detect and track each leaf of a plant for automated leaf stage monitoring. The method has four phases: optimal view selection, plant architecture determination, leaf tracking and generation of a leaf status report. The proposed method uses a graph theoretic approach to reliably detect and track individual leaves by overcoming the challenge of leaf-losses based on temporal image sequence analysis for automatically generating the leaf status report containing the following phenotypes, i.e., the emergence timing of each leaf, total number of leaves present at any time, the day on which a particular leaf stopped growing, and the length and relative growth rate of individual leaves. The proposed method demonstrates high accuracy in detecting leaves and tracking them through the early vegetative stages of maize plants based on experimental evaluation on a publicly available benchmark dataset.

This paper presents the results of a recent study that was conducted with a number of German municipalities/cities. Based on the obtained and briefly presented recommendations emerging from the study, the authors propose the concept of an Urban Data Space (UDS), which facilitates an eco-system for data exchange and added value creation thereby utilizing the various types of data within a smart city/municipality. Looking at an Urban Data Space from within a German context and considering the current situation and developments in German municipalities, this paper proposes a reasonable classification of urban data that allows to relate the various data types to legal aspects and to conduct solid considerations regarding technical implementation designs and decisions. Furthermore, the Urban Data Space is described/analyzed in detail, and relevant stakeholders are identified, as well as corresponding technical artifacts are introduced. The authors propose to setup Urban Data Spaces based on emerging standards from the area of ICT reference architectures for Smart Cities, such as DIN SPEC 91357 “Open Urban Platform” and EIP SCC. Thereby, the paper walks the reader through the construction of an UDS based on the above mentioned architectures and outlines all the goals, recommendations and potentials, which an Urban Data Space can reveal to a municipality/city.

The construction industry is responsible for 40 to 45% of primary energy consumption in Europe alone. Therefore, it is essential to find new materials with a lower environmental impact in order to attain sustainable housing. This study aims to determine and compare the environmental impact of two clay samples forming a basis for the manufacture of traditional brick, a standard material in building construction; traditional red clay brick and a brick based on clay mixed with a biological ingredient. The samples of fired clay were manufactured at the laboratory scale, the results being valid exclusively as indicators for the extrapolation of the analysis to other studies. The results of the environmental impact of these formulations have been examined through an evaluation of life-cycle analysis (LCA), observing that the incorporation of biological pore forming agents led to a decrease of around 15 to 20% of all impact categories studied. Thus, the suitability of using biological-based additives in clay bricks was confirmed both for their constructive characteristics (lighter material) and increased energy efficiency (better thermal insulation) considering the environmental point of view.

This paper presents an approach to the application of the Model-Based Systems Engineering (MBSE) and Model-Based Systems Architecting (MBSA) principles to develop a Model-Based Pattern Language (MBPL). It takes too long for systems engineers and architects to develop a new system from scratch, particularly new space-based systems derived from the existing space systems architectures. A pattern language is a holistic view of reusable logical model artifacts; many are interdisciplinary and introductory, if at all. The results are mostly a combination of the application-specific logical solution, which further results in the best possible overall solution. The main benefit of the pattern language is reducing the time and validation required to generate a new space-based system architecture; this approach will develop top-level requirements in the initial phase of the system development. The rationale of the methodology proposed by the paper is as follows, collect, and decompose published literature and other open-source information available on space system architectures and system models; develop SysML models for systems, subsystems, products, assembly, subassembly level, and mission-specific requirements using CAMEO SysML software. Arrange these patterns to develop a functional ontology and construct a logical architecture pattern library. This approach created, updated, and managed SysML pattern language, which evaluated the expedited new model construction. Again, our objective is to develop a logical pattern language using public domain information and evaluate patterns by constructing a new space mission concept—for example, planetary surface habitat.

The rapidly evolving field of artificial intelligence (AI) continues to witness the introduction of innovative open-source pre-trained models, fostering advancements in various applications. One such model is Llama 2, an open-source pre-trained model released by Meta, which has garnered significant attention among early adopters. In addition to exploring the foundational elements of the Llama v2 model, this paper investigates how these early adopters leverage the capabilities of Llama 2 in their AI projects. Through a qualitative study, we delve into the perspectives, experiences, and strategies employed by early adopters to leverage Llama 2's capabilities. For the purpose of data analysis, the capabilities inherent in the Llama 2 model were employed to conduct keyword extraction from the context of the early adopters' case studies. The findings shed light on the model's strengths, weaknesses, and areas of improvement, offering valuable insights for the AI community and Meta to enhance future model iterations. Additionally, we discuss the implications of Llama 2's adoption on the broader open-source AI landscape, addressing challenges and opportunities for developers and researchers in the pursuit of cutting-edge AI solutions. The present study constitutes an early exploration of the Llama 2 pre-trained model, holding promise as a foundational basis for forthcoming research investigations.

The aim of this study is to analyse the names given to streets, monuments, spots of interest, et cetera in a street guide of an imaginary city called The Manada, whose map is constructed as a painting. For this analysis, we start from the 257 entries of the Street Guide, select their possible antecedents in literature and contextualize this street guide with respect to these antecedents. Our methodology is focused on two specific aspects of the Street guide: (1) to detect the semantic fields that emerge (with a methodology inverse to the creative one, that is, asking ourselves what key questions would result in the names of the streets) and (2) to detect the literary devices that are put into practice in the names of the places on the map, in order to determine how the relationship with the viewer-reader is established from a connotative level. The main findings of this study demonstrate that this is a unique piece, a new format both pictorial and literary, and that it has transcendence in the theme it deals with: the concealment of systemic violence. Comments about feminism, apotropaic devices and surrealism end our text.

Radiological risk affect the quality of the environment in buildings since population and workers can be potentially exposed to high level of dose. Radon gas emanated from both subsoil and building materials represents the most important source of radiation exposure for people. This study investigates the sustainability concept of a small rural village of Ischia Island, named Ciglio, in relation to the radiological risk. Radon activity concentration was measured in typical green tuff dwellings and in water samples collected from a local spring using E-Perm devices. Moreover, for green-tuff as building material, the radon emanation coefficient was calculated by gamma spectroscopy. The results highlight the importance to perform environmental radon monitoring and to investigate the radon content of building materials, especially in geographical areas characterized by traditional use of typical stones for constructions. In conclusion, the sustainability development of rural buildings is possible if the radiological risk for inhabitants and workers was assessed.

In networked driving simulation, two or more human drivers participate interactively within a shared virtual environment. Thereby, typical applications of driving simulation can be extended to consider multi-driver scenarios, where a much closer approximation of reality with its unpredictability is achieved. However, the utilized network is typically prone to a considerable amount of message traffic. In addition to restricted system scalability, the resulting degradation of network performance leads to invalid simulation outcomes or unacceptable system behavior. High-level architecture (HLA) is an IEEE standard for networked simulation. Data distribution management (DDM) is one of the service groups provided by HLA standard. The aim of the DDM service is to reduce network traffic and to save effort required to process unnecessary received data. However, different approaches for current DDM implementations show major drawbacks in terms of utilization complexity, inefficiency, and yet added network overhead. This paper presents a concept of an interest manager that takes over the DDM functionality and avoids these drawbacks. Simulation data is exchanged between the participating driving simulators only when it is necessary according to the driving situations. The concept is validated by analyzing the network load of two driving maneuvers with and without the interest manager.

Microwave radiation diagnosis technology can detect thermal changes in skin tissue earlier than anatomical changes, but its detection accuracy is limited by non-target radiation interference in the measurement environment, additional measurement errors of system units, and energy scattering and transmission between skin tissues. This paper aims to address the scientific challenges of analyzing the forward and inversion modelling detection mechanism of layered accurate temperature measurement of human skin tissue based on multi-band. The study focuses on the construction of a pencil beam antenna optimization system, the optimization strategy of high-sensitivity correlated radiometer architecture, and the high-precision multi-band forward and inversion modelling detection algorithm. The key technologies include: (1) A new method of integrated modeling and multi-index optimization of antenna with high directivity and small aperture is proposed, and a priori knowledge-guided neural network of pencil beam distribution is constructed to realize the inversion model of antenna structural parameters; (2) The influence mechanism of high sensitivity correlated radiometer architecture error is analyzed, and a periodic phase shift error correction algorithm based on uniform polar circle is designed; (3) Combining deep learning theory and hyperparameter optimization framework, an iterative model is established, and the objective function modified by the penalty factor is defined to realize a new detection method combining forward and inversion. This paper presents a theoretical foundation for the industrialization of microwave radiation diagnostic technology.

In the rapidly evolving field of data management, numerous terminologies, such as data warehouse, data lake, data lakehouse, and data mesh , have emerged, each representing a unique analytical data architecture. However, the distinctions and similarities among these paradigms often remain unclear. The present paper aimed to navigate the data architecture landscape by conducting a comparative analysis of these paradigms. The analysis a identified and elucidated the differences and similari- ties in features, capabilities, and limitations of these architectural constructs. The study outcome serves as a comprehensive guide, assisting practitioners in selecting the most suitable analytical data architecture for their specific applications.

Based on the plate tectonic theory, using seismic, geology, and public literature data, the proto-type basins and lithofacies paleogeography during the main geological periods of the passive continental margin of East Africa are restored, and the architecture characteristics of the basins and the differences in sedimentary fillings are analyzed. Combined with the dissection of discovered oil and gas reservoirs, four types of hydrocarbon accumulation models are established, the favorable hydrocarbon accumulation combinations (plays), and the next exploration directions in this region are explored. The passive continental margin basins in East Africa experienced three proto-type stages: intracontinental aborted rift during the Late Carboniferous-Triassic Karoo period, intracontinental-intercontinental rift during the Jurassic period, and passive continental margin basin since the Cretaceous period. Affected by the difference in sedimentary filling thickness between the rift period and depression period, four types of passive continental margin basins are formed: rifted type, depressed type, faulted depression type, and reformed delta type. The maximum sedimentary thickness of the rifted basins during the rift period is greater than 3500 m, and that during the depression period is less than 4000 m, forming a "single-source structure type" hydrocarbon accumulation model. The exploration of rifted basins should focus on giant structural traps at the top of the rifted sequences. The maximum sedimentary thickness of the depressed basins during the depression period exceeds 4000 m, forming a "single-source fan group type" hydrocarbon accumulation model. The dominant exploration directions of depressed basins are sedimentary sand bodies and structural-lithologic traps during the depression and drift periods. The maximum sedimentary thickness of the faulted depression basins during the rift period is greater than 3500 m, and that during the depression period is greater than 4000 m, forming a "double-source and double-combination type" hydrocarbon accumulation model. The exploration of rifted basins should focus on giant slip-collapse-debris flow sedimentary sand bodies on the upper and middle slopes. In addition to the large sedimentary thickness of the early rift and the central depression, the delta thickness of the reformed delta basins during the late depression period since the Miocene is more than 4000 m, and four structural belts (growth fault, mud diapir, thrust fold, and foredeep gentle slope) were formed from onshore to offshore, forming a "three-source and multi-combination type" hydrocarbon accumulation model. All four structural belts can form giant oil and gas fields.

It is important for food recognition to separate each ingredient within a food image at the pixel level. In this paper, we propose a new approach to segment ingredients by utilizing a CNN-based Single-Ingredient Classification Model. In detail, we firstly introduce a standardized biological-based hierarchical ingredient structure and construct a single-ingredient image dataset based on this structure. Then, we build a single-ingredient classification model based on a novel convolutional neural network (CNN) architecture that utilizes an attention mechanism. Afterwards, we propose a new framework for segmentation using the above single-ingredient classification model as the backbone. In this framework, two methods are involved in segmenting ingredients in the food images. We introduce five evaluation metrics (IoU, Dice, Purity, Entirety, Loss of GTs) to assess the performance of ingredient segmentation in terms of ingredient classification. Extensive experiments demonstrate the effectiveness of the proposed method, achieving an maximal mIoU of 0.65, mDice of 0.77, mPurity of 0.83, mEntirety of 0.80, and mLoGTs of 0.06 on the FoodSeg103 dataset. The results confirm that our CNN-based architecture achieves higher segmentation performance compared to ResNet18 and EfficientNet-B0 when used as the backbone for ingredient segmentation. We believe that our ingredient segmentation approach lays the foundation for subsequent ingredient recognition.

Among the explored solutions to reduce the environmental impact of the transport sector, Vehicle Integrated Photovoltaics. Thus, we developed a simulation tool of the distance covered by VIPV. It considers various usage patterns and vehicle types, several characteristics of the PV system and all the losses that may decrease energy yield. Focusing on passenger car, simulations indicate the order of influence of the parameters on the outputs of the model: geographic locality, shading, thresholds due to extra-consumption to charge the vehicle battery from PV and frequency of recharge with the grid. With projections of the technology in 2030, with 30 % shading, VIPV cover up to 1444 km yearly distance. This represents up to 12 % of the driven mileage. For the best month, it can get up to 14 km/day. For average Europe and worst-case conditions, VIPV cover only 293 km per year. Life Cycle Assessment (LCA) of solarized passenger car shows negative balance for low-carbon electricity mix and average solar irradiance. In favorable conditions, the carbon footprint is up to 489 kg CO₂-equivalent avoided emissions on 13 years lifespan. Beyond km and LCA focus, VIPV may provide useful functions in non-interconnected zones and for resilience in disaster zones.

The purpose of this article is to disclose the architectural proportions and nature of the Korean national treasure in Seokguram Grotto, Gyeongju. The authors compare its features with those of other ancient hypogeal or ashlar constructions and intend to rediscover its relevant hidden configuration and latent structural properties to show its uniqueness. The methods employed in the research belong initially to architectural design and composition to advance at a later stage, into the nuances of stone masonry, lighting effects or cohesive construction. In this discussion and thorough analysis, different philosophical and scientific subtleties come afloat. The results demonstrate a significant potential capable to be applied in part to recent architectural developments like Tadao Ando’s Buddha Hill in Hokkaido (2017) and the authors’ own project for a Buddhist monument.

Associations between blood cancer and genetic predisposition, including both inherited variants and acquired mutations and epimutations, have been well characterized. However, the majority of these variants affect noncoding regions, making their mechanisms difficult to hypothesize and hindering the translation of these insights into patient benefits. Fueled by unprecedented progress in next-generation sequencing and computational integrative analysis, studies have started applying combinations of epigenetic, genome architecture and functional assays to bridge the gap between noncoding variants and blood cancer. These complementary tools have not only allowed us to understand the potential malignant role of these variants but also to differentiate key variants, cell types and conditions from misleading ones. Here, we briefly review recent studies that have provided fundamental insights into our understanding of how noncoding mutations at enhancers predispose and promote blood malignancies in the context of spatial genome architecture.

This work presents some characteristics of MoNet, a computerized platform for the modeling and visualization of complex systems. Emphasis is on the ideas that allowed the successful progressive development of this modeling platform, which goes along with the implementation of applications to the modeling of several studied systems. The platform has the capacity to represent different aspects of systems modeled at different observation scales. This tool offers advantages in the sense of favoring the perception of the phenomenon of the emergence of information, associated with changes of scale. Some criteria used for the construction of this modeling platform are included. The power of current computers has made practical representing graphic resources such as shapes, line thickness, overlaying-text tags, colors and transparencies, in the graphical modeling of systems made up of many elements. By visualizing diagrams conveniently designed to highlight contrasts, these modeling platforms allow the recognition of patterns that drive our understanding of systems and their structure. Graphs that reflect the benefits of the tool regarding the visualization of systems at different scales of observation are presented to illustrate the application of the platform.

Research on image-inpainting tasks has mainly focused on enhancing performance by augmenting various stages and modules. However, this trend does not consider the increase in the number of model parameters and operational memory, which increases the burden on computational resources. To solve this problem, we propose a Parametric Efficient Image InPainting Network (PEIPNet) for efficient and effective image-inpainting. Unlike other state-of-the-art methods, the proposed model has a one-stage inpainting framework in which depthwise and pointwise convolutions are adopted to reduce the number of parameters and computational costs. To generate semantically appealing results, we selected three unique components: spatially-adaptive denormalization (SPADE), dense dilated convolution module (DDCM), and efficient self-attention (ESA). The SPADE was adopted to conditionally normalize activations according to the mask to distinguish between damaged and undamaged regions. The DDCM was employed at every scale to overcome the gradient-vanishing obstacle and gradually fill-in pixels by capturing global information along the feature maps. The ESA was utilized to obtain clues from unmasked areas by extracting long-range information. In terms of efficiency, our model has the lowest operational memory compared with other state-of-the-art methods. Both qualitative and quantitative experiments demonstrate the generalized inpainting of our method on three public datasets: Paris StreetView, CelebA, and Places2.

It is expected that scholars will continue to strengthen the depth and breadth of theoretical research on RIS, so as to provide a higher theoretical upper bound for the engineering application of RIS. While making breakthroughs in academic research, great progress has been made in engineering application research and industrialization promotion. This article will provide an overview of RIS engineering applications, mainly including the typical features, typical classifications, and typical deployment scenarios of RIS. Then the challenges and candidate solutions of the RIS are systematically and deeply analyzed, involving the cascade channel decoupling for solving the RIS beamforming, the influences and solutions of RIS regulation constraints, RIS system architecture of network controlled mode, the integrated channel regulation and information modulation, TDD mechanism used for RIS. Future trends and challenges are also provided.

The need for a relatively quick solution to the problem of providing highways with roadside service facilities necessitates the development of a series of appropriate standard projects. To increase the efficiency of these series, it is advisable to carry out the interconnection of space-planning solutions based on a particular module. Taking into account the variety of planning and landscape characteristics of the sites for the placement of objects of the mainline service, it seems advisable to choose as a module not a square or rectangular, but a triangular configuration, which allows in most cases to harmoniously block the modules. The proposed roof module in the form of a "regular" triangle facing the tetrahedron has a structural basis in the form of a single-tier rod spatial plate. The principal space-planning solutions of all four dozen objects from the approved nomenclature of the mainline service performed in the process of analyzing the possibilities show the real possibility of solving the development tasks on the basis of this system. The use of the proposed modular system makes it possible to successfully solve a number of tasks to reduce the harmful impact on the environment and effectively use renewable energy sources.

With this article we would like to clarify the often-disregarded fact by virtue of which the European Missionaries in Asia acted as catalysts of a kind of nuanced acculturation named Accommodatio (adaptation). To a great extent they became harbingers of Culture and Science more than Faith itself to the dismay of many, including the Roman Church. Such cultural and scientific transference was actually two-pronged, for simultaneously they presented in Europe unique findings related to Language, e.g. the Chinese Characters (considered to be the sole natural language), Geography, Cosmology and even Governance. We would try to prove that such procedure contributed positively to the modern scientific notions of sustainability and to provide the kind of accoutrements that model the modern world as we know it.

System-of-systems (SoS) approach is often used for simulating disruptions to business and infrastructure system networks allowing for integration of several models into one simulation. However, the integration is frequently challenging as each system is designed individually with different characteristics, such as time granularity. Understanding the impact of time granularity on propagation of disruptions between businesses and infrastructure systems and finding the appropriate granularity for the SoS simulation remain as major challenges. To tackle these, we explore how time granularity, recovery time, and disruption size affect the propagation of disruptions between constituent systems of an SoS simulation. To address this issue, we developed a High Level Architecture (HLA) simulation of 3 networks and performed a series of simulation experiments. Our results revealed that time granularity and especially recovery time have huge impact on propagation of disruptions. Consequently, we developed a model for selecting an appropriate time granularity for an SoS simulation based on expected recovery time. Our simulation experiments show that time granularity should be less than 1.13 of expected recovery time. We identified some areas for future research centered around extending the experimental factors space.

Automated machine learning (AutoML) has been heralded as the next wave in artificial intelligence with its promise to deliver high performance end-to-end machine learning pipelines with minimal effort from the user. However, despite AutoML showing great promise for computer vision tasks, to the best of our knowledge, no study has used AutoML for image-based plant phenotyping. To address this gap in knowledge, we examined the application of AutoML for image-based plant phenotyping using wheat lodging assessment with UAV imagery as an example. We compared the performance of an open-source AutoML framework, AutoKeras in image classification and regression tasks to transfer learning using modern convolutional neural network (CNN) architectures. For image classification which classified plot images as lodged or non-lodged, transfer learning with Xception and DenseNet-201 achieved best classification accuracy of 93.2%, whereas Autokeras had 92.4% accuracy. For image regression which predicted lodging scores from plot images, transfer learning with DenseNet-201 had the best performance (R2=0.8303, RMSE=9.55, MAE=7.03, MAPE=12.54%), followed closely by AutoKeras (R2=0.8273, RMSE=10.65, MAE=8.24, MAPE=13.87%). Interestingly, in both tasks, AutoKeras models had up to 40-fold faster inference times compared to the pretrained CNNs. The merits and drawbacks of AutoML compared to transfer learning for image-based plant phenotyping are discussed.

In light of climate changes, technological development and the use of renewable energy sources are considered very important nowadays, both in newly-designed structures and reconstructed historic building, resulting in the reduction of the commercial energy consumption and CO2 environmental emissions. This paper explores the possibilities of improving the energy efficiency of heritage sacred buildings by utilizing photovoltaic systems. As an exceptionally significant cultural good, the Cathedral of St. Michael the Archangel in Belgrade shall serve as a case study, with the aim of examining the methods of mounting photovoltaic (PV) panels, by taking into account the fact that the authenticity and the aesthetic value of this cultural monument must remain intact. A comparative analysis of the two options for installing PV panels on the southwestern roof of the church was performed using simulations in PVgis and PVsist V6.84 software, with the aim of establishing the most efficient option in terms of power generation. The simulation results show that photovoltaic panels can produce 151650 kWh (Option 1) and 150894 kWh (Option 2) per year, while the required amount of energy is 42726.77 kWh. The electricity produced exceeds the electricity requirements for the decorative lighting of the Cathedral Church, so it can be used for other purposes in the sacral complex.

In light of climate changes, technological development and the use of renewable energy sources are considered very important nowadays, both in newly-designed structures and reconstructed historic building, resulting in the reduction of the commercial energy consumption and CO₂ environmental emissions. This paper explores the possibilities of improving the energy efficiency of heritage sacred buildings by utilizing photovoltaic systems. As an exceptionally significant cultural good, the Cathedral of St. Michael the Archangel in Belgrade shall serve as a case study, with the aim of examining the methods of mounting photovoltaic (PV) panels, by taking into account the fact that the authenticity and the aesthetic value of this cultural monument must remain intact. A comparative analysis of the two options for installing PV panels on the southwestern roof of the church was performed using simulations in PVgis and PVsist V6.84 software, with the aim of establishing the most efficient option in terms of power generation. The simulation results show that photovoltaic panels can produce 151650 kWh (Option 1) and 150894 kWh (Option 2) per year, while the required amount of energy is 42726.77 kWh. The electricity produced exceeds the electricity requirements for the decorative lighting of the Cathedral Church, so it can be used for other purposes in the sacral complex.

By the study of the pattern book Ying Zao Fa Shi (building regulations of Song Dynasty, 1103 AD), while analyzing the combining and dimensioning rule of timber framework and tile work, a model self-generating program has been compiled for the first time. The operating framework has been firstly defined, while solving the issues of clustering principle, connecting method, output classification, etc. with the detailed description of algorithm theory. Taking the corner bracket set and nine-ridge roof for example, after the compilation and debug by Grasshopper, according to various input parameters, various models have been generated automatically by the plugin, proving the velocity and the veracity of the algorithm.

With the breakthrough of modernism, various efforts are undertaken to rationalize architecture and building processes using industrial principles. Few architects explore these as intensively as Walter Gropius, the founder of the Bauhaus. Even before World War One, and increasingly in the interwar years, Gropius and a number of colleagues undertake various experiments which manifest in a series of projects, essays, model houses and Siedlungen. These aim at conceptually different goals, i.e. they follow two different categories of industrial logic: first, a flexible construction kit and, second, an assembly line serial production. This article traces the genesis of these two concepts and analyses their characteristics using these early manifestations. Compared to existing literature, this article takes into account hitherto neglected primary sources as well as technological and construction history aspects—allowing for a distinction based not only on theoretical, but also technological and structural characteristics. This article shows that Gropius succeeds in formulating and exploring the two principles in theory and practice as well as drawing conclusions by the end of the 1920s. With them, he contributed significantly to the rationalization of architecture, and his principles have been picked up and developed further by numerous architects since then.

Over the years, the need for autonomous systems such as drones, also known as unmanned aerial vehicles (UAVs), has significantly increased in popularity across several industries, including the military. The Internet of Battlefield Things (IoBT) represents a modern technological advancement that significantly enhances the operational efficacy of defense systems. It establishes an integrated military force by connecting individuals to intelligent technology in drones, radios, equipment, antennas and ground stations. This is achieved through the utilization of cloud and edge computing, sensors, mobile devices, embedded systems, and IoT-based systems. However, IoBT security is significantly compromised by enemies that exploit the vulnerabilities and malicious intrusions that specifically target the external environment or to obtain sensitive data. In addition, a comprehensive understanding of cyberattacks and countermeasures is essential for assuring the security of IoBT. On the other hand, as cyber threats get more complicated, trust becomes increasingly important for the security of digital systems. Within this context, the zero trust architecture contends that the security of a complex network is inherently vulnerable to internal and external threats. In defense, UAV security system applications, for example, the primary purpose of the zero trust architecture is to limit the vulnerability of military UAV systems to cyberattacks, hence reducing the possibility of data breaches and illegal entry. This study conducts a systematic review aimed at identifying different aspects of cybersecurity strategies for protecting UAV systems within the IoBT domain. Furthermore, zero trust architecture is presented in the study as an effective prospective solution to the security issues that develop in defense UAV systems.

Information has been and will be a vital element for a person or department groups in an organization. That is why there are technologies that help us to give them the proper management of data; Business Intelligence is responsible for bringing technological solutions that correctly and effectively manage the entire volume of necessary and important information for companies. Among the solutions offered by Business Intelligence are Data Warehouses, Data Mining, among other business technologies that working together achieve the objectives proposed by an organization. It is important to highlight that these business technologies have been present since the 50's and have been evolving through time, improving processes, infrastructure, methodologies and implementing new technologies, which have helped to correct past mistakes based on information management for companies. There are questions about Business Intelligence. Could it be that in the not-too-distant future it will be used as an essential standard or norm in any organization for data management, since it provides many benefits and avoids failures at the time of classifying information. On the other hand, Cloud storage has been the best alternative to safeguard information and not depend on physical storage media, which are not 100% secure and are exposed to partial or total loss of information, by presenting hardware failures or security failures due to mishandling that can be given to such information.

In the design of multi-loop Networked Control Systems (NCSs) wherein each control system is characterized by heterogeneous dynamics and associated with certain set of timing specifications and constraints, appropriate metrics need to be employed for the synthesis of control and networking policies to efficiently respond to the requirements of each control loop. Majority of the design approaches for sampling, scheduling and control policies include either time-based or event-based metrics to perform pertinent actions in response to the changes of the parameters of interest. We specifically focus in this article on Age-of-Information (AoI) as a recently-developed time-based metric and threshold-based triggering function as a generic event-based metric. As the NCS model, we consider multiple heterogeneous stochastic linear control systems that close their feedback loops over a shared-resource communication network. We investigate the co-design across the NCS, and discuss the pros and cons with AoI and ET approaches in terms of asymptotic control performance measured by linear-quadratic Gaussian (LQG) cost functions. In particular, sampling and scheduling policies combining AoI and stochastic event-triggered metrics are proposed. It is argued that pure AoI functions that generate decision variables solely upon minimizing the average age irrespective of control systems dynamics may not be able to improve the overall NCS performance even compared with pure randomized policies. Our theoretical analyses are successfully validated through several simulation scenarios.

Alvar Aalto created innovative architecture in his breakthrough work, Paimio Sanatorium, located in Southwestern Finland and designed between 1928 and 1933. The technological systems in construction, such as the concrete frame, electricity, air conditioning, and lifts, developed rapidly in the interwar period and Aalto drew influences from the culturally radical modernistic discourse around the CIAM organisation and felt that architecture should respond to the demands of the age. Architecture is an applied form of art, and symbolic expression in architecture is a system with its logic. As a contrast, a building is a technological system and forms a framework within which to solve practical problems. Thus, as a technological system, the building is both material and social, during its construction and after. The theoretical underpinning for the study was the actor-network theory developed since the 1980s by the French sociologist Bruno Latour. This study clearly showed the importance of a collaborative effort in a building project. The most famous architectural solutions for Paimio Sanatorium, a demanding institutional building project, came into being in circumstances where the architect-innovator, Aalto, managed to create a viable and robust hybrid that merged collective competence with material factors.

Aim of expressional space is to facilitate the public to explore their hobby and talent in autodidact. The space for expression in Makassar City is necessary for the mural artist and the youngsters who has a hobby to play a skateboard. Their talent is insufficient attention by the government and create negative attitude because there no space to accommodate their activity. Therefore, this paper presents a design idea of expressional space by implementing the architectural geometry. The architectural geometry design principle is based on simple geometry form application as a realization of form from the space. An experience of the space for the user realizes by the relationship between the space and the interaction with the environment through geometry and form processing as the basic of the creation process in the architectural works. Content analysis method providing a landscape layout and transformation of form and building mass in form of the implementation of architectural geometry principles. The principles are pure geometry, composition of geometry, direction wall, and opening for the transformation process of expressional space form to produce and increase aesthetic value of the environment.

Through the use of Smart Sensor Networks (SSN), Marine Observatories (MO) provide continuous ocean monitoring. Deployed sensors may not perform as intended due to the heterogeneity of SSN devices’ hardware and software when combined with the Internet. Hence, SSN are regarded as complex distributed systems. As such, SSN designers will encounter challenges throughout the design phase related to time, complexity, sharing diverse domain experiences (viewpoints), and ensuring optimal performance for the deployed SSN. To this end, we describe in this article how we extended our previously proposed ArchiMO meta-model and design tool by extending an Enterprise Architecture Framework based on the ArchiMate Modeling Language. This extension proposes the incorporation of new Underwater Environmental Constraints (UEC) for SSN in ArchiMO which is coupled with the fusion of sensors with Artificial Intelligence. This serves as the basis for generating a new version of our ArchiMO design tool, which incorporates the new added constraints and invokes the AI created Database. To illustrate our proposal, we use the newly generated ArchiMO to create a model in the MO domain. Furthermore, we use our self-developed domain-specific model compiler to produce the relevant simulation code. Throughout the design phase, our approach contributes to handle and control the uncertainties and variances of the provided quality of service that may occur during the performance of the SSN, hence reducing the design activity’s complexity and time. It provides a way to share the different viewpoints of the designers in the domain of SSN.

Integrating systems acquired from third parties and legacies has become of great necessity in companies. This is mainly due to the need to exchange information between entities, such as banks, suppliers, customers, allies, etc. Therefore, it is essential to guarantee the integrity of the data and keep the integration up to date with the changes that can occur. Furthermore, reducing the transaction risk and avoiding losing information is necessary. Implementing this complex task involving technological and business challenges requires appropriate architecture implementation. This article presents an architecture named Dynamic Canonical Data Model through agnostic messages. The contribution involves treating the low link in integrating software units, also called the integration of loosely coupled software units. In particular, it focuses on internal data and external data integration. The proposal reduces their integration, maintenance time, and cost, maximizing their scalability and promoting reuse. To illustrate their components, a case study undertaken at the Mexican Logistics Company Paquetexpress is presented. The company has evaluated different enterprise application integration systems over 26 years to achieve a standardized integration. The article describes an architecture designed and implemented for this delivery company in a real-world case. The implementation’s source code was registered in the National Registry of Copyrights of Mexico.

The purpose of this article is to disclose the strenuous efforts of Laszlo Hudec in China and Antonin Raymond in Japan and India to create a modern architectural stance by heralding an incipient space syntax. In the turn of the 19th Century, for dynastic, politic and economic reasons, Eastern Asia had very little modern Architecture. It is a surprising fact that, out of happenstance, two European architects Antonin Raymond and Laszlo Hudec, had to intervene to remedy this situation, to the point of becoming 20th Century icons in Japan and China. Their fruitful careers spanned over thirty years and included locations, like Tamil Nadu or the Philippines. The Oriental territories were not an easy ground for the bold architectural achievements that they produced. Despite of faraway strangeness and uncountable personal losses, in revolutions and wars, which eventually forced them both to leave for the United States of America and never to return, they were successful in the manner of establishing a broad avenue for Modern Asian Architecture which is still recognisable today thanks to their systematic approach. However, theirs is an endangered heritage and the intention of this article is to be a just remembrance of in which way such actions could be performed, how they predated by many years a syntactic approach to architectural composition and why their legacy should be preserved.

We present observations from evaluation of internal environmental quality of industrial halls with priority on daylighting in combination with the integral lighting. The physical parameters related to indoor lighting in large industrial halls in winter and summer periods were analyzed using in situ measurements and computational methods. These are part of a comprehensive research on indoor environmental quality of industrial halls with the aims of saving energy and providing a comfortable environment for the workers while improving the productivity. The results showed that the procedures used for evaluation of residential or office buildings may not be used for industrial buildings. We also observed that the criteria of occupants’ comforts for indoor industrial buildings may differ from those of other kinds of buildings. Based on these results, an adequate attention is required for designing the industrial buildings. For this reason, appropriate evaluation methods and criteria should be created. We found the measured values of daylight factor very close to the skylight component of the total illumination. The skylight component was observed on average 30% that of the measured daylight factor values. Although the daylight is not emphasized when designing the industrial buildings and its contribution is small, but it is very important for the workers psychology and physiology. The workers must feel a connection with the exterior environment; otherwise, their productivity decreases.

In an era of rapid technological improvements, state-of-the-art methodologies and tools dedicated to protecting and promoting our cultural heritage should be developed and extensively employed in the contemporary built environment and lifestyle. At the same time, sustainability principles underline the importance of the continuous use of historic or vernacular buildings as part of the building stock of our society. Adopting a holistic, integrated, multi-disciplinary strategy can bridge technological innovation with conserving and restoring heritage buildings. The paper presents ongoing research and results of the application of Machine Learning methods for the remote monitoring of the built environment of the historic cluster in Cypriot cities. This study is part of an integrated, multi-scale, and multi-discipline study of heritage buildings towards the creation of an online HBIM platform for urban monitoring.

Virtual reality (VR) describes a family of technologies which immerse users in sensorily-stimulating virtual environments. Such technologies have increasingly found applications in the treatment of neurological and mental health disorders. Depression, anxiety, and other mood abnormalities are of concern in the growing elderly population – especially those who reside in long-term care facilities (LTCFs). The transition from the familiar home environment to the foreign LTCF introduces a number of stressors that can precipitate depression. However, recent studies reveal that VR therapy (VRT) can promote positive emotionality and improve cognitive abilities in the elderly, both at home and in LTCFs. VR thus holds potential in allowing elderly individuals to gradually adapt to their new environments – thereby mitigating the detrimental effects of place attachment and social exclusion. Nevertheless, while the current psychological literature is promising, the implementation of VR in LTCFs faces many challenges. LTCF residents must gain trust in VR technologies, care providers require training to maximize the positive effects of VRT, and decision makers must evaluate both the opportunities and obstacles in adopting VR. Here, we concisely review the implications of depression related to place attachment in LTCFs, and explore the potential therapeutic applications of VR.

The paper aims to develop and test an algorithm for classifying Russian-language text reviews of patients’ experiences with medical facilities and physicians, extracted from social media. This is motivated by the limitations of conventional methods of surveying consumers to assess their satisfaction with the quality of services, which are being replaced by automatic processing of text data from social media. This approach enables to get more objective results due to the increased representativeness and independence of the sample of service consumers. The authors have tested machine learning methods using various neural network architectures. A hybrid method was developed to classify text reviews of medical facilities posted by patients on the two most popular physician review websites in Russia. Overall, more than 60,000 reviews were analysed. The main results are as follows: 1) the classification algorithm developed by the authors has a high efficiency, the best result being achieved by the GRU-based architecture (val_accuracy = 0.9271); 2) applying the named entity search method to text messages following their partitioning improved the classification efficiency for each of the classifiers based on artificial neural networks. To further enhance the classification quality, reviews need to be semantically partitioned by target and sentiment and the resulting fragments need to be analysed separately.

This paper presents a review of cloud application architectures and its evolution. It reports observations being made during the course of a research project that tackled the problem to transfer cloud applications between different cloud infrastructures. As a side effect we learned a lot about commonalities and differences from plenty of different cloud applications which might be of value for cloud software engineers and architects. Throughout the course of the research project we analyzed industrial cloud standards, performed systematic mapping studies of cloud-native application related research papers, performed action research activities in cloud engineering projects, modeled a cloud application reference model, and performed software and domain specific language engineering activities. Two major (and sometimes overlooked) trends can be identified. First, cloud computing and its related application architecture evolution can be seen as a steady process to optimize resource utilization in cloud computing. Second, this resource utilization improvements resulted over time in an architectural evolution how cloud applications are being build and deployed. A shift from monolithic servce-oriented architectures (SOA), via independently deployable microservices towards so called serverless architectures is observable. Especially serverless architectures are more decentralized and distributed, and make more intentional use of independently provided services. In other words, a decentralizing trend in cloud application architectures is observable that emphasizes decentralized architectures known from former peer-to-peer based approaches. That is astonishing because with the rise of cloud computing (and its centralized service provisioning concept) the research interest in peer-to-peer based approaches (and its decentralizing philosophy) decreased. But this seems to change. Cloud computing could head into future of more decentralized and more meshed services.

Alternative splicing (AS) is a gene regulatory mechanism modulating gene expression in multiple ways. AS is prevalent in all eukaryotes including plants. AS generates two or more mRNAs from the precursor mRNA (pre-mRNA) to regulate transcriptome complexity and proteome diversity. Advances in next-generation sequencing, omics technology and bioinformatics tools, and computational methods provide new opportunities to quantify and visualize AS-based quantitative trait variation associated with plant growth, development, reproduction, and stress tolerance. Domestication, polyploidization and environmental perturbation may evolve novel splicing variants associated with agronomically beneficial traits. To date, pre-mRNAs from many genes are spliced into multiple transcripts that cause phenotypic variation for complex traits, both in model plant Arabidopsis and field crops. Cataloguing and exploiting such variation may provide new paths to enhance climate resilience, resource-use efficiency, productivity, and nutritional quality of staple food crops. This review provides insights into AS variation alongside gene expression analysis to select for novel phenotypic diversity for use in breeding programs. AS contributes to heterosis, enhances plant symbiosis (mycorrhiza and rhizobium), and provides a mechanistic link between the core clock genes and diverse environmental clues.

During the construction of buildings, dangerous chemicals such as benzene, formaldehyde and others are used, which accumulate during the operation of the building. High concentrations of these substances can harm human health. In this article, we have analyzed the possible impact of modular green wall systems on improving of the air. During the research, four different modular green wall systems and various plant species were considered. The result showed that a modular green wall system can improve the air quality by removing harmful pollutants from the air in the buildings. Urban design used to be turned greener and more sustainable using the modern technologies of modular green wall systems. This study focuses on the air-cleaning benefits provided by modular green wall systems and their assessment. This research contributes to fill existing literature gaps on the green wall systems on the buildings and biophilic architecture.

Although research has long established that the interaction with the natural environment is associated with better overall health and well-being outcomes, the Western model mainly focuses on treating the symptoms. In Aotearoa-New Zealand, the Indigenous Māori have long demonstrated significantly more negative health outcomes than non-Māori. Little research has examined the causes compared to Western populations or the role of the natural environment in health outcomes for Māori. An exploration of rongoā Māori (traditional healing system) was conducted to ascertain the importance of landscape in the process of healing. Eight rongoā healers or practitioners took part in semi-structured narrative interviews from June to November 2020. Transcribed interviews were analysed using an interpretative phenomenological analysis and Kaupapa Māori techniques. The findings show how rongoā is underpinned by a complex set of cultural values and beliefs, drawing from the connection to wairua (spirit), tinana (body), tikanga and whakaora (customs and healing), rākau (plants), whenua (landscape) and whānau (family). Incorporating such constructs into the landscape can foster our understanding of health and well-being and its implications for conceptualising therapeutic environments and a culturally appropriate model of care for Māori and non-Māori communities.

: In the last years, materializations of neuromorphic circuits based on nanophotonic arrangements have been proposed, which contain complete optical circuits, laser, photodetectors, photonic crystals, optical fibers, flat waveguides, and other passive optical elements of nanostructured materials, which eliminate the time of simultaneous processing of big groups of data, taking advantage of the quantum perspective and thus highly increasing the potentials of contemporary intelligent computational systems. This article is an effort to record and study the research that has been conducted concerning the methods of development and materialization of neuromorphic circuits of Neural Networks of nanophotonic arrangements. In particular, an investigative study of the methods of developing nanophotonic neuromorphic processors, their originality in neuronic architectural structure, their training methods and their optimization has been realized along with the study of special issues such as optical activation functions and cost functions.

Fire-tolerant eucalypt forests of south eastern Australia are assumed to fully recover from even the most intense fires but surprisingly very few studies have quantitatively assessed that recovery. Accurate assessment of horizontal and vertical attributes of tree crowns after fire is essential to understand the fire’s legacy effects on tree growth and on forest structure. In this study, we quantitatively assessed individual tree crowns 8.5 years after a 2009 wildfire that burnt extensive areas of eucalypt forest in temperate Australia. We used airborne lidar data validated with field measurements to estimate multiple metrics that quantified the cover, density, and vertical distribution of individual-tree crowns in 51 plots of 0.05 ha in fire-tolerant eucalypt forest across four wildfire severity types (unburnt, low, moderate, high). Significant differences in the field-assessed mean height of fire scarring as a proportion of tree height, and in the proportions of trees with epicormic (stem) resprouts were consistent with the gradation in fire severity. Linear mixed-effects models indicated persistent effects of both moderate- and high-severity wildfire on tree crown architecture. Trees at high-severity sites had significantly less crown projection area and live crown width as a proportion of total crown width than those at unburnt and low-severity sites. Significant differences in lidar-based metrics (crown cover, evenness, leaf area density profiles) indicated that tree crowns at moderate- and high-severity sites were comparatively narrow and more evenly distributed down the tree stem. These conical-shaped crowns contrasted sharply with the rounded crowns of trees at unburnt and low-severity sites, and likely influenced both tree productivity and the accuracy of biomass allometric equations for nearly a decade after the fire. Our data provide a clear example of the utility of airborne lidar data for quantifying the impacts of disturbances at the scale of individual trees. Quantified effects of contrasting fire severities on the structure of resprouter tree crowns provide a strong basis for interpreting post-fire patterns in forest canopies and vegetation profiles in lidar and other remotely-sensed data at larger scales.

Inspired by the reflective and deliberative control mechanisms used in cognitive architectures such as SOAR and Sigma, we propose an alternative decision mechanism driven by architectural appraisals allowing robots to overcome impasses. The presented work builds on and improves on our previous work on a generally applicable decision mechanism with roots in the Standard Model of the Mind and the Generalized Cognitive Hour-glass Model. The proposed decision mechanism provides automatic context-dependent switching between exploration-oriented, goal-oriented, and backtracking behavior, allowing a robot to overcome impasses. A simulation study of two applications utilizing the proposed decision mechanism is presented demonstrating the applicability of the proposed decision mechanism.

Pericentromeric regions of chromosomes enriched in tandemly repeated satellite DNA although representing a significant part of eukaryotic genomes are still understudied mainly due to interdisciplinary knowledge gaps. Recent studies suggest their important role in genome regulation, karyotype stability and evolution. Thus, the idea of satellite DNA as a junk part of the genome was refuted. Integration of data about molecular composition, chromosome behaviour and details of in situ organization of pericentromeric regions is of great interest. The objective of this work was a cytogenetic analysis of the interactions of pericentromeric regions non-homologous chromosomes in mouse spermatocytes using immuno-FISH. We analysed two events: the associations between cerntomeric regions of X chromosome and autosomes, and associations between centromeric regions of autosomal bivalents forming chromocenters. We conclude that X chromosome form temporary synaptic associations with different autosomes in early meiotic prophase I which normally can be found at pachytene-diplotene without signs of pachytene arrest. These associations are formed between the satellite DNA-enriched centomeric regions of X chromosome and different autosomes but not involve the satellite-poor centromeric region of Y-chromosome. We suggest the mechanism of X chromosome competitive replacement from such associations during synaptic correction. We showed that centromeric region of the X chromosome remains free of γH2Ax-dependent chromatin inactivation, while Y chromosome is completely inactivated. This findings highlights the predominant role of associations between satellite DNA-enriched regions of different chromosomes including X. We assume that X-autosome temporary associations is a manifestation of an additional synaptic disorders checkpoint. These associations are normally corrected before the late diplotene. We revealed that the intense spreading conditions applied to the spermatocytes I nuclei did not lead to destruction of stretched chromatin fibers i.e. elongated chromocenters enriched in satellite DNA. Revealed by us tight associations between pericentromeric regions of different autosomal bivalents and X chromosome may represent the basis for repeat stability maintenance in autosomes an X chromosome. The consequences of our findings are discussed. We obtained the preparations of mouse spermatocytes nuclei in the meiotic prophase I using two approaches: standard and extremely intense surface spread techniques. Using immuno-FISH we visualized tandemly repeated mouse Major and Minor satellite DNA located in the pericentromeric regions of chromosomes and performed a morphological comparison of the standard- and intensely spreaded meiotic nuclei. Based on our results, we assume the remarkable strength of the chromocenter-mediated associations, “chromatin “bridges”, between different bivalents at the pachytene and diplotene stages. We have demonstrated that the chromocenter “bridges” between the centromeric ends of meiotic bivalents are enriched in both tandemly repeated Major and Minor satellite DNA. Association of centromeric regions of autosomal bivalents and X-chromosome but not with Y-chromosome correlates with the absence of Major and Minor satellites on Y-chromosome. We suggest that revealed tight associations between pericentromeric regions of bivalents may represent the network-like system providing dynamic stability of chromosomal territories, as well as add new data for the hypothesis of ectopic recombination in these regions which supports sequence homogeneity between non-homologous chromosomes and does not contradict the meiotic restrictions imposed by the crossing-over interference near centromeres. We conclude that nuclear architecture in meio-sis may play an essential role in contacts between the non-homologous chromosomes providing the specific characteristics of pericentromeric DNA.

The COVID-19 pandemic has resulted in a wide range of spatial interventions to slow down the spread of the virus. The spatial limitations of narrow public circulation spaces within informal settlements, which house over one billion people around the world, make it impossible for pedestrians to practice physical distancing (or social distancing). In this paper, we propose a flexible mathematical method, named the Cluster Lane Method, for turning a planar circulation network of any size or complexity into a network of unidirectional lanes, making physical distancing possible in narrow circulation spaces by limiting face-to-face interactions. New notions and theorems about oriented graphs in graph theory are introduced. The paper ends with a discussion of the potential implementation of this cost-efficient, low-tech, sustainable solution, and with the introduction of a novel unidirectional tactile paving for the visually impaired.

The stele concept is one of the oldest enduring concepts in plant biology. This paper reviews the concept and its foundations, and builds an argument for an updated view of steles and their evolution. The history of studies of stelar organization has generated a widely ranging array of definitions of the stele that determine the way we classify steles and construct scenarios about the evolution of stelar architecture. Because at the level of the organism biological evolution proceeds by, and is reflected in, changes in development, concepts of structure need to be grounded in development in order to be relevant in an evolutionary perspective. For the stele, most of the traditional definitions that incorporate development have viewed it as the totality of tissues that either originate from procambium – currently the prevailing view – or are bordered by a boundary layer (e.g., endodermis). A definition of the stele that would bring consensus between these perspectives recasts the stele as a structural entity of dual nature. Here, I review briefly the history of the stele concept, basic terminology related to stelar organization, and traditional classifications of the steles. I then revisit boundary layers from the perspective of histogenesis as a dynamic mosaic of developmental domains. I use classic and recent anatomical and molecular data to reaffirm and explore the importance of boundary layers for stelar organization. Drawing on data from comparative anatomy, developmental regulation, and the fossil record, I offer a model for a stele concept that integrates both the boundary layer and the procambial perspective, consistent with a dual nature of the stele. The dual stele model posits that stelar architecture is determined in the apical meristem by two major cell fate specification events: a first one that specifies a provascular domain and its boundaries, and a second event that specifies a procambial domain (which will mature into conducting tissues) from cell subpopulations of the provascular domain. If the position and extent of the developmental domains defined by the two events are determined by different concentrations of the same morphogen (most likely auxin), then the distribution of this organizer factor in the shoot apical meristem, as modulated by changes in axis size and the effect of lateral organs, can explain the different stelar configurations documented among tracheophytes. This model provides a set of working hypotheses that incorporate assumptions and generate implications that can be tested empirically. The model also offers criteria for an updated classification of steles that is in line with current understanding of plant development. In this classification, steles fall into two major categories determined by the configuration of boundary layers – boundary protosteles and boundary siphonosteles, each with subtypes defined by the architecture of the vascular tissues. Validation the dual stele model and, more generally, in-depth understanding of the regulation of stelar architecture, will necessitate targeted efforts in two areas: (i) the regulation of procambium, vascular tissue, and boundary layer specification in all extant vascular plants, considering that most of the diversity in stelar architecture is hosted by seed-free plants, which are the least explored in terms of developmental regulation; (ii) the configuration of vascular tissues and, especially, boundary layers, in as many extinct species and lineages as possible.

The next-generation "Industrial Internet of Things" (IIoT) will support "Machine-to-Machine" (M2M) communications for smart Cyber-Physical-Systems and Industry 4.0, and require guaranteed cyber-security. This paper explores hardware-enforced cyber-security for critical infrastructures. It examines a Quantum-Safe "Software-Defined Deterministic IIoT" (SDD-IIoT), with a new forwarding-plane (sub-layer-3a) for deterministic M2M traffic flows. A "Software-Defined-Networking" (SDN) control-plane controls many "SDD Wide Area Networks" (SDD-WANs), realized with FPGAs. The SDN control-plane provides an "Admission-Control/Access-Control" system for network-bandwidth, using collaborating Artificial Intelligence (AI) rule-based "Zero Trust Architectures" (ZTAs). Hardware-enforced access-control eliminates all congestion, BufferBloat, and DoS/DDoS attacks in the forwarding-plane, reduces buffer-sizes by 100,000+ times, and supports ultra-reliable and uItra-low-latency communications in the SDD-WANs. The SDD-WANs can: (i) Encrypt/Authenticate M2M flows using Quantum-Safe ciphers, to withstand attacks by Quantum Computers; (ii) Implement "Guaranteed Intrusion Detection Systems" in FPGAs, to detect cyber-attacks embedded within billions of IIoT packets/second; (iii) Provide guaranteed immunity to external cyber-attacks against critical infrastructure, and exceptionally-strong immunity to internal cyber-attacks; (iv) Save $US100s of billions annually by exploiting FPGAs; and (v) Enable "Quantum Key Distribution" (QKD) Networks by providing a programmable forwarding-plane with "authenticated classical channels" and full-immunity to DoS/DDoS attacks. Extensive experimental results for an SDD-WAN over the European Union are reported.

Energy conversion and distribution (heat and electricity) is characterized by long planning horizons, investment periods and depreciation times, and it is thus difficult to plan and tell the technology that optimally fits for decades. Uncertainties include future energy prices, applicable subsidies, regulation, and even the evolution of market designs. To achieve higher adaptability to arbitrary transition paths, a technical concept based on integrated energy systems is envisioned and described. The problem of intermediate steps of evolution is tackled by introducing a novel paradigm in urban infrastructure design.It builds on standardization, modularization and economies of scale for underlying conversion units. Building on conceptual arguments for such a platform, it is then argued how actors like (among others) municipalities and district heating system operators can use this as a practical starting point for a manageable and smooth transition towards more environmental friendly supply technologies, and to commit to their own pace of transition (bearable investment/risk). environmental friendly supply technologies. Merits are not only supported by technical arguments but also by strategical and societal prospects like technology neutrality and availability of real options.

In the domain of financial trading, where accuracy and swift response to data discrep- ancies are paramount for maintaining clienttrust, our research paper delves into the development of a real-time alert system utilizing SpringBoot, a framework renowned for its robustness and adaptability in enterprise applications. We embark on a comprehensive journey, beginning with addressing thefoundational challenges inherent in monitoring trade inquiries - the necessity for real-time processing, unwavering data accuracy,and ensuring unwavering system reliability. The study then methodically transitions to the architectural design, where we explore howSpringBoot’s capabilities are optimally utilized to meet these challenges. Following this, we delve into the im- -plementationphase, detailing the strategic selection of compatible technologies and methods for effective data management and discrepancydetection. The paper culminates in a thorough evalu- ation of the system, where we assess performance across various operationalscenarios, scrutinize the accuracy of the discrepancy detection mechanisms, and integrate real-world feedback from users in thetrading sector. This holistic approach not only highlights the versatility and efficiency of SpringBoot in creating reliable alert systems in the high-stakes world of financial trading but also serves as a detailed guide for similar endeavors in this field

Information is the currency of life, but the origin of prebiotic information remains a mystery. We propose transitional pathways from the cosmic building blocks of life to the complex prebiotic organic chemistry that led to the origin of information systems. The prebiotic information system, specifically the genetic code, is segregated, linear, and digital and probably appeared during biogenesis four billion years ago. In the peptide/RNA world, lipid membranes randomly encapsulated amino acids, RNA, and protein molecules, drawn from the prebiotic soup, to initiate a molecular symbiosis inside the protocells. This endosymbiosis led to the hierarchical emergence of several requisite components of the translation machine: tRNAs, aaRS, mRNAs, and ribosomes. When assembled in the right order, the translation machine created biosynthetic polypeptides, a process that transferred information from mRNAs to proteins. This was the beginning of the prebiotic information age. The molecular attraction between tRNA and amino acids led to different stages of the translation machines and the genetic code. tRNA is an ancient molecule that designed and built mRNA for storing the information of its cognate amino acid. Each mRNA strand became the storage device for the genetic information that encoded the amino acid sequences in triplet nucleotides. As information appeared in the digital languages of the codon within mRNA, and the genetic code for protein synthesis evolved, the prebiotic chemistry then became more organized and directional. The origin of the genetic code is enigmatic; herein we propose an evolutionary explanation: the demand for a wide range of specific enzymes in the peptide/RNA world was the main selective pressure for the origin of information-directed protein synthesis. We review three main concepts on the origin and evolution of the genetic code: the stereochemical theory, the coevolution theory, and the adaptive theory. These three theories are compatible with our coevolution model of the translation machines and the genetic code. We suggest biosynthetic pathways as the origin of the specific translation machines which provided the framework for the origin of the genetic code. During translation, the genetic code developed in three stages coincident with the refinement of the translation machines: GNC code developed by the pre-tRNA/pre-aaRS /pre-mRNA machine, SNS code by the tRNA/aaRS/mRNA machine, and finally the universal genetic code by the tRNA/aaRS/mRNA/ribosome machine. Our hypothesis provides the logical and incremental steps for the origin of the programmed protein synthesis. In order to understand the prebiotic information system better, we converted letter codons into numerical codons in the Universal Genetic Code Table. We have developed a software called CATI (Codon-Amino Acid-Translator-Imitator) to translate randomly chosen numerical codons into corresponding amino acids and vice versa. This conversion has granted us insight into how the translation might have worked in the peptide/RNA world. There is great potential in the application of numerical codons to bioinformatics such as barcoding, DNA mining, or DNA fingerprinting. We constructed the likely biochemical pathways for the origin of translation and the genetic code using the Model-View-Controller (MVC) software framework, and the translation machinery step-by-step. Using AnyLogic software we were able to simulate and visualize the entire evolution of the translation machines and the genetic code. The results indicate that the emergence of the information age from the peptide/RNA world was a watershed event in the origin of life about four billion years ago.

Smart grid software interconnects multiple Engineering disciplines (power systems, communication, software and hardware technology, instrumentation, big data, etc.). The software architecture is an evolving concept in smart grid systems in which systematic architecture development is a challenging process. The architecture has to realize the complex legacy power grid systems and cope up with current Information and Communication Technologies (ICT). The distributed generation in smart grid environment expects the software architecture to be distributed and to enable local control. Smart grid architecture should also be modular, flexible and adaptable to technology upgrades. In this paper, the authors have made a comprehensive review on architecture for smart grids. An in depth analysis of layered and agent based architectures is presented and compared under various domains.

Soft-Core architecture for Analogue to Digital Converter (ADC) sampling is useful for mixed signal applications. Soft-core architecture for cutting edge odd or even ADC sampling with interface to block RAM memory has not been found. Soft-core architecture as a concept has become popular due to the advantage of customization for different applications as compared to general-core architecture suited for single application. The latest generation of piece wise sampling is odd sampling and was introduced in the second decade of the 20th century. Odd and even order sampling techniques are analogue in nature driven by a tuned (tuned for odd or even) mixer. This paper proposes a third-generation piece wise sampling with soft-core architecture that enables an option to select both odd and even while interfacing to memory mapping. The proposed odd/even has superior SNR performance of 6 dB as compared to existing architecture such as Mod-∆ which recorded worst performance of 18 dB. Advances in soft-core technology have allowed a niche odd/even switching field to be identified and studied, the study has also been extended to include memory architecture.

The Late Heavy Bombardment Period (4.1 to 3.8 billion years ago) of heightened impact cratering activity on young Earth is likely the driving force for the origin of life. During the Eoarchean, asteroids such as carbonaceous chondrites delivered the building blocks of life and water to early Earth. Asteroid collisions created innumerable hydrothermal crater lakes in the Eoarchean crust which inadvertently became the perfect cradle for prebiotic chemistry. These hydrothermal crater lakes were filled with cosmic water and the building blocks of life. forming a thick prebiotic soup. The unique combination of exogenous delivery of extraterrestrial building blocks of life, and the endogenous biosynthesis in hydrothermal impact crater lakes very likely gave rise to life. A new symbiotic model for the origin of life within the hydrothermal crater lakes is here proposed. In this scenario, life arose around four billion years ago through five hierarchical stages of increasing molecular complexity: cosmic, geologic, chemical, information, and biological. During the prebiotic synthesis, membranes first appeared in the hydrothermal crater lakes, followed by the simultaneous origin of RNA and protein molecules, creating the RNA/protein world. These proteins were noncoded protein enzymes that facilitated chemical reactions. RNA molecules formed in the hydrothermal crater basin by polymerization of the nucleotides on the montmorillonite mineral substrate. Similarly, the initial synthesis of abiotic protein enzymes was mediated by the condensation of amino acids on pyrite surfaces. The regular wet-dry cycles within the crater lakes assisted further concentration, condensation, and polymerization of the RNAs and proteins. Lipid membranes randomly encapsulated amino acids, RNA, and protein molecules from the prebiotic soup to initiate a molecular symbiosis inside the protocells, this led to the hierarchical emergence of several cell components. As the role of protein enzymes became essential for catalytic process in the RNA/protein world, Darwinian selection from noncoded to coded protein synthesis led to translation systems and the genetic code, heralding the information stage. In this stage, the biochemical pathways suggest the successive emergence of translation machineries such as tRNAs, aaRS, mRNAs, and of ribosomes for protein synthesis. The molecular attraction between tRNA and amino acid led to the emergence of translation machinery and the genetic code. tRNA is an ancient molecule that created mRNA for the purpose of storing amino acid information like a digital strip. Each mRNA strand became the storage device for genetic information that encoded the amino acid sequences in triplet nucleotides. As information became available in the digital languages of the codon within mRNA, biosynthesis became less random and more organized and directional. The original translation machinery was simpler before the emergence of the ribosome than that of today. We review three main concepts on the origin and evolution of the genetic code: the stereochemical theory, the coevolution theory, and adaptive theory. We believe that these three theories are not mutually exclusive, but are compatible with our coevolution model of translations machines and the genetic code. We suggest biosynthetic pathways as the origin of the translation machine that provided the framework for the origin of the genetic code. During translation, the genetic code developed in three stages coincident with the refinement of the translation machinery: GNC code with four codons and four amino acids during interactions of pre-tRNA/pre-aaRS /pre-mRNA, SNS code consisting of 16 codons and 10 amino acids appeared during the tRNA/aaRS/mRNA interaction, and finally the universal genetic code evolved with the emergence of the tRNA/aaRS/mRNA/ribosome machine. The universal code consists of 64 codons and 20 amino acids, with a redundancy that minimizes errors in translation. To address the question of the origin of the biological information system in the RNA/protein world, we converted letter codons into numerical codons in the Universal Genetic Code Table. We developed a software called CATI (Codon-Amino Acid-Translator-Imitator) to translate randomly chosen numerical codons into corresponding amino acids and vice versa, gaining insight into how translation might have worked in the RNA/protein world. We simulated the likely biochemical pathways for the origin of translation and the genetic code using the Model-View-Controller (MVC) software framework, and the translation machinery step-by-step. We used AnyLogic software to simulate and visualize the evolution of the translation machines and the genetic code. We conclude that the emergence of the information age from the RNA/protein world was a watershed event in the origin of life about four billion years ago.

Predatory research field in science is when an emerging scientific topic destroys current topics and characterizes a main scientific change. Predatory research field can be a basic driver of scientific and technological change that generates a 'creative destruction' in science and society in contexts of knowledge-based competition and rapid changes. The prediction of proposed theory of predatory research fields is that it destroys with a fast growth other research fields. The theoretical approach is tested here in research fields of large language models (LLM) by analyzing the transformers (a deep learning architecture based on the multi-head attention mechanism) proposed in 2017 and from November 2022 started main applications in generative artificial intelligence with innovations of BERT, ChatGPT, Microsoft Copilot (launched on February 7, 2023) and other natural language processing tools driven by AI technology for engaging conversations, gain insights, automate tasks, etc., etc. Statistical evidence suggests that growth rate of transformer technologies is 80.58%, a high level compared to all other research fields in machine learning (having a growth rate of 13.83%). Moreover, predatory research field of transformers has a destructive power such that all other domains in LLM from 2021 to 2023 have a general reduction of scientific growth. The impact of transformers is much more drastic of previous radical technologies such as CNN having a temporal growth rate of 0.16%, lower than 0.38% by transformers, ceteris paribus. These analysis reveals that transformers have characteristics to generate a radical scientific and technological change in a not-too-distant future. Overall, then, the study suggests that predatory research field on emerging topics and technologies can generate path-breaking innovations and the examination here can clarify the essential elements of the science dynamics for a better theory of scientific and technological change, providing also main implications for knowledge policy to support promising research fields and technologies to guide economic and social change.

The article is devoted to the preliminary concept of the Future Planetary Defense System (FPDS), emphasizing Astroballistics. This paper is intended to support international efforts to improve the planetary security of the Earth. The work covers three areas of knowledge: Astronautics, Astrodynamics, and Astroballistics. The most important part of the presented article is dynamic, contact combat modeling against small, deformable celestial bodies. For these purposes, the original, proprietary hydrocode of the Free Particle Method (HEFPM-G) with gravity was used. The main aim of combat is to redirect the Potentially Hazardous Objects (PHOs) to orbits safe for the Earth or destroy them. This concept's first task is to find, prepare and use dynamic three-dimensional models of celestial bodies' motion and spacecraft or human-crewed spaceships in the Solar System's relativistic frame. The second task is to prepare the FPDS' architecture and computer simulation space missions' initial concepts in the internal part of the solar system. The third and main task covers simulating, using hydrocodes, selected methods of fighting 100 m and 140 m diameter asteroids. The order of the article is as follows. The first part of the article presents an architecture and FPDS' modus operandi. Preliminary design and development of FPDS' space missions, including navigation, mission dynamics simulation, is prepared using an open-source space mission analysis and design tool. E.g., Asterank and Trajectory Browser or GMAT are presented in the second part. The third part of the article is devoted to computer hydrocodes (HEFPM-G) and the modeling and simulation of asteroid–asteroid collision, laser radiation effects on an asteroid, and FPDS spacecraft's warhead contact interaction on the small celestial body. The authors formulated the Main Planetary Defense Problem (MPDP) in this paper. The proposition of this problem solving has been realized by preparing its concepts, architecture, and modus operandi of the FPDS mission. Finally, a series of realistic simulations were made using hydrocode to deflect or destroy dangerous asteroids. The summary and conclusions can be found in the fourth part of the article.